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Sample records for gene expression classifier

  1. A Gene Expression Classifier of Node-Positive Colorectal Cancer

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    Paul F. Meeh

    2009-10-01

    Full Text Available We used digital long serial analysis of gene expression to discover gene expression differences between node-negative and node-positive colorectal tumors and developed a multigene classifier able to discriminate between these two tumor types. We prepared and sequenced long serial analysis of gene expression libraries from one node-negative and one node-positive colorectal tumor, sequenced to a depth of 26,060 unique tags, and identified 262 tags significantly differentially expressed between these two tumors (P < 2 x 10-6. We confirmed the tag-to-gene assignments and differential expression of 31 genes by quantitative real-time polymerase chain reaction, 12 of which were elevated in the node-positive tumor. We analyzed the expression levels of these 12 upregulated genes in a validation panel of 23 additional tumors and developed an optimized seven-gene logistic regression classifier. The classifier discriminated between node-negative and node-positive tumors with 86% sensitivity and 80% specificity. Receiver operating characteristic analysis of the classifier revealed an area under the curve of 0.86. Experimental manipulation of the function of one classification gene, Fibronectin, caused profound effects on invasion and migration of colorectal cancer cells in vitro. These results suggest that the development of node-positive colorectal cancer occurs in part through elevated epithelial FN1 expression and suggest novel strategies for the diagnosis and treatment of advanced disease.

  2. Gene-expression Classifier in Papillary Thyroid Carcinoma

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    Londero, Stefano Christian; Jespersen, Marie Louise; Krogdahl, Annelise

    2016-01-01

    BACKGROUND: No reliable biomarker for metastatic potential in the risk stratification of papillary thyroid carcinoma exists. We aimed to develop a gene-expression classifier for metastatic potential. MATERIALS AND METHODS: Genome-wide expression analyses were used. Development cohort: freshly...

  3. Glycosyltransferase Gene Expression Profiles Classify Cancer Types and Propose Prognostic Subtypes

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    Ashkani, Jahanshah; Naidoo, Kevin J.

    2016-05-01

    Aberrant glycosylation in tumours stem from altered glycosyltransferase (GT) gene expression but can the expression profiles of these signature genes be used to classify cancer types and lead to cancer subtype discovery? The differential structural changes to cellular glycan structures are predominantly regulated by the expression patterns of GT genes and are a hallmark of neoplastic cell metamorphoses. We found that the expression of 210 GT genes taken from 1893 cancer patient samples in The Cancer Genome Atlas (TCGA) microarray data are able to classify six cancers; breast, ovarian, glioblastoma, kidney, colon and lung. The GT gene expression profiles are used to develop cancer classifiers and propose subtypes. The subclassification of breast cancer solid tumour samples illustrates the discovery of subgroups from GT genes that match well against basal-like and HER2-enriched subtypes and correlates to clinical, mutation and survival data. This cancer type glycosyltransferase gene signature finding provides foundational evidence for the centrality of glycosylation in cancer.

  4. Clustering based gene expression feature selection method: A computational approach to enrich the classifier efficiency of differentially expressed genes

    KAUST Repository

    Abusamra, Heba

    2016-07-20

    The native nature of high dimension low sample size of gene expression data make the classification task more challenging. Therefore, feature (gene) selection become an apparent need. Selecting a meaningful and relevant genes for classifier not only decrease the computational time and cost, but also improve the classification performance. Among different approaches of feature selection methods, however most of them suffer from several problems such as lack of robustness, validation issues etc. Here, we present a new feature selection technique that takes advantage of clustering both samples and genes. Materials and methods We used leukemia gene expression dataset [1]. The effectiveness of the selected features were evaluated by four different classification methods; support vector machines, k-nearest neighbor, random forest, and linear discriminate analysis. The method evaluate the importance and relevance of each gene cluster by summing the expression level for each gene belongs to this cluster. The gene cluster consider important, if it satisfies conditions depend on thresholds and percentage otherwise eliminated. Results Initial analysis identified 7120 differentially expressed genes of leukemia (Fig. 15a), after applying our feature selection methodology we end up with specific 1117 genes discriminating two classes of leukemia (Fig. 15b). Further applying the same method with more stringent higher positive and lower negative threshold condition, number reduced to 58 genes have be tested to evaluate the effectiveness of the method (Fig. 15c). The results of the four classification methods are summarized in Table 11. Conclusions The feature selection method gave good results with minimum classification error. Our heat-map result shows distinct pattern of refines genes discriminating between two classes of leukemia.

  5. Building gene expression profile classifiers with a simple and efficient rejection option in R.

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    Benso, Alfredo; Di Carlo, Stefano; Politano, Gianfranco; Savino, Alessandro; Hafeezurrehman, Hafeez

    2011-01-01

    The collection of gene expression profiles from DNA microarrays and their analysis with pattern recognition algorithms is a powerful technology applied to several biological problems. Common pattern recognition systems classify samples assigning them to a set of known classes. However, in a clinical diagnostics setup, novel and unknown classes (new pathologies) may appear and one must be able to reject those samples that do not fit the trained model. The problem of implementing a rejection option in a multi-class classifier has not been widely addressed in the statistical literature. Gene expression profiles represent a critical case study since they suffer from the curse of dimensionality problem that negatively reflects on the reliability of both traditional rejection models and also more recent approaches such as one-class classifiers. This paper presents a set of empirical decision rules that can be used to implement a rejection option in a set of multi-class classifiers widely used for the analysis of gene expression profiles. In particular, we focus on the classifiers implemented in the R Language and Environment for Statistical Computing (R for short in the remaining of this paper). The main contribution of the proposed rules is their simplicity, which enables an easy integration with available data analysis environments. Since in the definition of a rejection model tuning of the involved parameters is often a complex and delicate task, in this paper we exploit an evolutionary strategy to automate this process. This allows the final user to maximize the rejection accuracy with minimum manual intervention. This paper shows how the use of simple decision rules can be used to help the use of complex machine learning algorithms in real experimental setups. The proposed approach is almost completely automated and therefore a good candidate for being integrated in data analysis flows in labs where the machine learning expertise required to tune traditional

  6. Localizing genes to cerebellar layers by classifying ISH images.

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    Lior Kirsch

    Full Text Available Gene expression controls how the brain develops and functions. Understanding control processes in the brain is particularly hard since they involve numerous types of neurons and glia, and very little is known about which genes are expressed in which cells and brain layers. Here we describe an approach to detect genes whose expression is primarily localized to a specific brain layer and apply it to the mouse cerebellum. We learn typical spatial patterns of expression from a few markers that are known to be localized to specific layers, and use these patterns to predict localization for new genes. We analyze images of in-situ hybridization (ISH experiments, which we represent using histograms of local binary patterns (LBP and train image classifiers and gene classifiers for four layers of the cerebellum: the Purkinje, granular, molecular and white matter layer. On held-out data, the layer classifiers achieve accuracy above 94% (AUC by representing each image at multiple scales and by combining multiple image scores into a single gene-level decision. When applied to the full mouse genome, the classifiers predict specific layer localization for hundreds of new genes in the Purkinje and granular layers. Many genes localized to the Purkinje layer are likely to be expressed in astrocytes, and many others are involved in lipid metabolism, possibly due to the unusual size of Purkinje cells.

  7. Assessment of a 44 gene classifier for the evaluation of chronic fatigue syndrome from peripheral blood mononuclear cell gene expression.

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    Daniel Frampton

    Full Text Available Chronic fatigue syndrome (CFS is a clinically defined illness estimated to affect millions of people worldwide causing significant morbidity and an annual cost of billions of dollars. Currently there are no laboratory-based diagnostic methods for CFS. However, differences in gene expression profiles between CFS patients and healthy persons have been reported in the literature. Using mRNA relative quantities for 44 previously identified reporter genes taken from a large dataset comprising both CFS patients and healthy volunteers, we derived a gene profile scoring metric to accurately classify CFS and healthy samples. This metric out-performed any of the reporter genes used individually as a classifier of CFS.To determine whether the reporter genes were robust across populations, we applied this metric to classify a separate blind dataset of mRNA relative quantities from a new population of CFS patients and healthy persons with limited success. Although the metric was able to successfully classify roughly two-thirds of both CFS and healthy samples correctly, the level of misclassification was high. We conclude many of the previously identified reporter genes are study-specific and thus cannot be used as a broad CFS diagnostic.

  8. A new approach to enhance the performance of decision tree for classifying gene expression data.

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    Hassan, Md; Kotagiri, Ramamohanarao

    2013-12-20

    Gene expression data classification is a challenging task due to the large dimensionality and very small number of samples. Decision tree is one of the popular machine learning approaches to address such classification problems. However, the existing decision tree algorithms use a single gene feature at each node to split the data into its child nodes and hence might suffer from poor performance specially when classifying gene expression dataset. By using a new decision tree algorithm where, each node of the tree consists of more than one gene, we enhance the classification performance of traditional decision tree classifiers. Our method selects suitable genes that are combined using a linear function to form a derived composite feature. To determine the structure of the tree we use the area under the Receiver Operating Characteristics curve (AUC). Experimental analysis demonstrates higher classification accuracy using the new decision tree compared to the other existing decision trees in literature. We experimentally compare the effect of our scheme against other well known decision tree techniques. Experiments show that our algorithm can substantially boost the classification performance of the decision tree.

  9. Regularization strategies for hyperplane classifiers: application to cancer classification with gene expression data.

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    Andries, Erik; Hagstrom, Thomas; Atlas, Susan R; Willman, Cheryl

    2007-02-01

    Linear discrimination, from the point of view of numerical linear algebra, can be treated as solving an ill-posed system of linear equations. In order to generate a solution that is robust in the presence of noise, these problems require regularization. Here, we examine the ill-posedness involved in the linear discrimination of cancer gene expression data with respect to outcome and tumor subclasses. We show that a filter factor representation, based upon Singular Value Decomposition, yields insight into the numerical ill-posedness of the hyperplane-based separation when applied to gene expression data. We also show that this representation yields useful diagnostic tools for guiding the selection of classifier parameters, thus leading to improved performance.

  10. Integrative Analysis of DCE-MRI and Gene Expression Profiles in Construction of a Gene Classifier for Assessment of Hypoxia-Related Risk of Chemoradiotherapy Failure in Cervical Cancer

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    Fjeldbo, Christina S; Julin, Cathinka H; Lando, Malin

    2016-01-01

    platforms. The prognostic value was independent of existing clinical markers, regardless of clinical endpoints. CONCLUSIONS: A robust DCE-MRI-associated gene classifier has been constructed that may be used to achieve an early indication of patients' risk of hypoxia-related chemoradiotherapy failure.......PURPOSE: A 31-gene expression signature reflected in dynamic contrast enhanced (DCE)-MR images and correlated with hypoxia-related aggressiveness in cervical cancer was identified in previous work. We here aimed to construct a dichotomous classifier with key signature genes and a predefined...... as an indicator of hypoxia. RESULTS: Classifier candidates were constructed by integrative analysis of ABrix and gene expression profiles in the training cohort and evaluated by a leave-one-out cross-validation approach. On the basis of their ability to separate patients correctly according to hypoxia status, a 6...

  11. A Machine Learned Classifier That Uses Gene Expression Data to Accurately Predict Estrogen Receptor Status

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    Bastani, Meysam; Vos, Larissa; Asgarian, Nasimeh; Deschenes, Jean; Graham, Kathryn; Mackey, John; Greiner, Russell

    2013-01-01

    Background Selecting the appropriate treatment for breast cancer requires accurately determining the estrogen receptor (ER) status of the tumor. However, the standard for determining this status, immunohistochemical analysis of formalin-fixed paraffin embedded samples, suffers from numerous technical and reproducibility issues. Assessment of ER-status based on RNA expression can provide more objective, quantitative and reproducible test results. Methods To learn a parsimonious RNA-based classifier of hormone receptor status, we applied a machine learning tool to a training dataset of gene expression microarray data obtained from 176 frozen breast tumors, whose ER-status was determined by applying ASCO-CAP guidelines to standardized immunohistochemical testing of formalin fixed tumor. Results This produced a three-gene classifier that can predict the ER-status of a novel tumor, with a cross-validation accuracy of 93.17±2.44%. When applied to an independent validation set and to four other public databases, some on different platforms, this classifier obtained over 90% accuracy in each. In addition, we found that this prediction rule separated the patients' recurrence-free survival curves with a hazard ratio lower than the one based on the IHC analysis of ER-status. Conclusions Our efficient and parsimonious classifier lends itself to high throughput, highly accurate and low-cost RNA-based assessments of ER-status, suitable for routine high-throughput clinical use. This analytic method provides a proof-of-principle that may be applicable to developing effective RNA-based tests for other biomarkers and conditions. PMID:24312637

  12. A machine learned classifier that uses gene expression data to accurately predict estrogen receptor status.

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    Meysam Bastani

    Full Text Available BACKGROUND: Selecting the appropriate treatment for breast cancer requires accurately determining the estrogen receptor (ER status of the tumor. However, the standard for determining this status, immunohistochemical analysis of formalin-fixed paraffin embedded samples, suffers from numerous technical and reproducibility issues. Assessment of ER-status based on RNA expression can provide more objective, quantitative and reproducible test results. METHODS: To learn a parsimonious RNA-based classifier of hormone receptor status, we applied a machine learning tool to a training dataset of gene expression microarray data obtained from 176 frozen breast tumors, whose ER-status was determined by applying ASCO-CAP guidelines to standardized immunohistochemical testing of formalin fixed tumor. RESULTS: This produced a three-gene classifier that can predict the ER-status of a novel tumor, with a cross-validation accuracy of 93.17±2.44%. When applied to an independent validation set and to four other public databases, some on different platforms, this classifier obtained over 90% accuracy in each. In addition, we found that this prediction rule separated the patients' recurrence-free survival curves with a hazard ratio lower than the one based on the IHC analysis of ER-status. CONCLUSIONS: Our efficient and parsimonious classifier lends itself to high throughput, highly accurate and low-cost RNA-based assessments of ER-status, suitable for routine high-throughput clinical use. This analytic method provides a proof-of-principle that may be applicable to developing effective RNA-based tests for other biomarkers and conditions.

  13. Gene expression-based classifiers identify Staphylococcus aureus infection in mice and humans.

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    Sun Hee Ahn

    Full Text Available Staphylococcus aureus causes a spectrum of human infection. Diagnostic delays and uncertainty lead to treatment delays and inappropriate antibiotic use. A growing literature suggests the host's inflammatory response to the pathogen represents a potential tool to improve upon current diagnostics. The hypothesis of this study is that the host responds differently to S. aureus than to E. coli infection in a quantifiable way, providing a new diagnostic avenue. This study uses Bayesian sparse factor modeling and penalized binary regression to define peripheral blood gene-expression classifiers of murine and human S. aureus infection. The murine-derived classifier distinguished S. aureus infection from healthy controls and Escherichia coli-infected mice across a range of conditions (mouse and bacterial strain, time post infection and was validated in outbred mice (AUC>0.97. A S. aureus classifier derived from a cohort of 94 human subjects distinguished S. aureus blood stream infection (BSI from healthy subjects (AUC 0.99 and E. coli BSI (AUC 0.84. Murine and human responses to S. aureus infection share common biological pathways, allowing the murine model to classify S. aureus BSI in humans (AUC 0.84. Both murine and human S. aureus classifiers were validated in an independent human cohort (AUC 0.95 and 0.92, respectively. The approach described here lends insight into the conserved and disparate pathways utilized by mice and humans in response to these infections. Furthermore, this study advances our understanding of S. aureus infection; the host response to it; and identifies new diagnostic and therapeutic avenues.

  14. Gene-expression patterns in peripheral blood classify familial breast cancer susceptibility.

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    Piccolo, Stephen R; Andrulis, Irene L; Cohen, Adam L; Conner, Thomas; Moos, Philip J; Spira, Avrum E; Buys, Saundra S; Johnson, W Evan; Bild, Andrea H

    2015-11-04

    Women with a family history of breast cancer face considerable uncertainty about whether to pursue standard screening, intensive screening, or prophylactic surgery. Accurate and individualized risk-estimation approaches may help these women make more informed decisions. Although highly penetrant genetic variants have been associated with familial breast cancer (FBC) risk, many individuals do not carry these variants, and many carriers never develop breast cancer. Common risk variants have a relatively modest effect on risk and show limited potential for predicting FBC development. As an alternative, we hypothesized that additional genomic data types, such as gene-expression levels, which can reflect genetic and epigenetic variation, could contribute to classifying a person's risk status. Specifically, we aimed to identify common patterns in gene-expression levels across individuals who develop FBC. We profiled peripheral blood mononuclear cells from women with a family history of breast cancer (with or without a germline BRCA1/2 variant) and from controls. We used the support vector machines algorithm to differentiate between patients who developed FBC and those who did not. Our study used two independent datasets, a training set of 124 women from Utah (USA) and an external validation (test) set from Ontario (Canada) of 73 women (197 total). We controlled for expression variation associated with clinical, demographic, and treatment variables as well as lymphocyte markers. Our multigene biomarker provided accurate, individual-level estimates of FBC occurrence for the Utah cohort (AUC = 0.76 [0.67-84]) . Even at their lower confidence bounds, these accuracy estimates meet or exceed estimates from alternative approaches. Our Ontario cohort resulted in similarly high levels of accuracy (AUC = 0.73 [0.59-0.86]), thus providing external validation of our findings. Individuals deemed to have "high" risk by our model would have an estimated 2.4 times greater odds of

  15. Identification and optimization of classifier genes from multi-class earthworm microarray dataset.

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    Ying Li

    Full Text Available Monitoring, assessment and prediction of environmental risks that chemicals pose demand rapid and accurate diagnostic assays. A variety of toxicological effects have been associated with explosive compounds TNT and RDX. One important goal of microarray experiments is to discover novel biomarkers for toxicity evaluation. We have developed an earthworm microarray containing 15,208 unique oligo probes and have used it to profile gene expression in 248 earthworms exposed to TNT, RDX or neither. We assembled a new machine learning pipeline consisting of several well-established feature filtering/selection and classification techniques to analyze the 248-array dataset in order to construct classifier models that can separate earthworm samples into three groups: control, TNT-treated, and RDX-treated. First, a total of 869 genes differentially expressed in response to TNT or RDX exposure were identified using a univariate statistical algorithm of class comparison. Then, decision tree-based algorithms were applied to select a subset of 354 classifier genes, which were ranked by their overall weight of significance. A multiclass support vector machine (MC-SVM method and an unsupervised K-mean clustering method were applied to independently refine the classifier, producing a smaller subset of 39 and 30 classifier genes, separately, with 11 common genes being potential biomarkers. The combined 58 genes were considered the refined subset and used to build MC-SVM and clustering models with classification accuracy of 83.5% and 56.9%, respectively. This study demonstrates that the machine learning approach can be used to identify and optimize a small subset of classifier/biomarker genes from high dimensional datasets and generate classification models of acceptable precision for multiple classes.

  16. Novel gene sets improve set-level classification of prokaryotic gene expression data.

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    Holec, Matěj; Kuželka, Ondřej; Železný, Filip

    2015-10-28

    Set-level classification of gene expression data has received significant attention recently. In this setting, high-dimensional vectors of features corresponding to genes are converted into lower-dimensional vectors of features corresponding to biologically interpretable gene sets. The dimensionality reduction brings the promise of a decreased risk of overfitting, potentially resulting in improved accuracy of the learned classifiers. However, recent empirical research has not confirmed this expectation. Here we hypothesize that the reported unfavorable classification results in the set-level framework were due to the adoption of unsuitable gene sets defined typically on the basis of the Gene ontology and the KEGG database of metabolic networks. We explore an alternative approach to defining gene sets, based on regulatory interactions, which we expect to collect genes with more correlated expression. We hypothesize that such more correlated gene sets will enable to learn more accurate classifiers. We define two families of gene sets using information on regulatory interactions, and evaluate them on phenotype-classification tasks using public prokaryotic gene expression data sets. From each of the two gene-set families, we first select the best-performing subtype. The two selected subtypes are then evaluated on independent (testing) data sets against state-of-the-art gene sets and against the conventional gene-level approach. The novel gene sets are indeed more correlated than the conventional ones, and lead to significantly more accurate classifiers. The novel gene sets are indeed more correlated than the conventional ones, and lead to significantly more accurate classifiers. Novel gene sets defined on the basis of regulatory interactions improve set-level classification of gene expression data. The experimental scripts and other material needed to reproduce the experiments are available at http://ida.felk.cvut.cz/novelgenesets.tar.gz.

  17. Thyroid nodules with indeterminate cytology: molecular imaging with 99mTc-methoxyisobutylisonitrile (MIBI) is more cost-effective than the Afirma registered gene expression classifier

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    Heinzel, Alexander; Mueller, Dirk; Behrendt, Florian F.; Giovanella, Luca; Mottaghy, Felix M.; Verburg, Frederik A.

    2014-01-01

    To compare the cost-effectiveness of 99m Tc-methoxyisobutylisonitrile (MIBI) thyroid scintigraphy and the Afirma registered gene expression classifier for the assessment of cytologically indeterminate thyroid nodules. A decision tree model was used. Costs were calculated from the perspective of the German health insurance system. The robustness of the results was assessed with probabilistic sensitivity analyses using a Monte Carlo simulation. Life expectancy was 34.3 years (estimated costs per patient EUR1,459 - EUR2,224) for the MIBI scan and 34.1 years (estimated costs EUR3,560 - EUR4,071) for the molecular test. These results were confirmed by the Monte Carlo simulation. MIBI thyroid scintigraphy is more cost-effective than the gene expression classifier. (orig.)

  18. Feature genes in metastatic breast cancer identified by MetaDE and SVM classifier methods.

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    Tuo, Youlin; An, Ning; Zhang, Ming

    2018-03-01

    The aim of the present study was to investigate the feature genes in metastatic breast cancer samples. A total of 5 expression profiles of metastatic breast cancer samples were downloaded from the Gene Expression Omnibus database, which were then analyzed using the MetaQC and MetaDE packages in R language. The feature genes between metastasis and non‑metastasis samples were screened under the threshold of PSVM) classifier training and verification. The accuracy of the SVM classifier was then evaluated using another independent dataset from The Cancer Genome Atlas database. Finally, function and pathway enrichment analyses for genes in the SVM classifier were performed. A total of 541 feature genes were identified between metastatic and non‑metastatic samples. The top 10 genes with the highest betweenness centrality values in the PPI network of feature genes were Nuclear RNA Export Factor 1, cyclin‑dependent kinase 2 (CDK2), myelocytomatosis proto‑oncogene protein (MYC), Cullin 5, SHC Adaptor Protein 1, Clathrin heavy chain, Nucleolin, WD repeat domain 1, proteasome 26S subunit non‑ATPase 2 and telomeric repeat binding factor 2. The cyclin‑dependent kinase inhibitor 1A (CDKN1A), E2F transcription factor 1 (E2F1), and MYC interacted with CDK2. The SVM classifier constructed by the top 30 feature genes was able to distinguish metastatic samples from non‑metastatic samples [correct rate, specificity, positive predictive value and negative predictive value >0.89; sensitivity >0.84; area under the receiver operating characteristic curve (AUROC) >0.96]. The verification of the SVM classifier in an independent dataset (35 metastatic samples and 143 non‑metastatic samples) revealed an accuracy of 94.38% and AUROC of 0.958. Cell cycle associated functions and pathways were the most significant terms of the 30 feature genes. A SVM classifier was constructed to assess the possibility of breast cancer metastasis, which presented high accuracy in several

  19. GeneBins: a database for classifying gene expression data, with application to plant genome arrays

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    Weiller Georg

    2007-03-01

    Full Text Available Abstract Background To interpret microarray experiments, several ontological analysis tools have been developed. However, current tools are limited to specific organisms. Results We developed a bioinformatics system to assign the probe set sequences of any organism to a hierarchical functional classification modelled on KEGG ontology. The GeneBins database currently supports the functional classification of expression data from four Affymetrix arrays; Arabidopsis thaliana, Oryza sativa, Glycine max and Medicago truncatula. An online analysis tool to identify relevant functions is also provided. Conclusion GeneBins provides resources to interpret gene expression results from microarray experiments. It is available at http://bioinfoserver.rsbs.anu.edu.au/utils/GeneBins/

  20. Thyroid nodules with indeterminate cytology: molecular imaging with {sup 99m}Tc-methoxyisobutylisonitrile (MIBI) is more cost-effective than the Afirma registered gene expression classifier

    Energy Technology Data Exchange (ETDEWEB)

    Heinzel, Alexander [RWTH Aachen University Hospital, Department of Nuclear Medicine, Aachen, Pauwelsstrasse 30 (Germany); Institute for Neuroscience and Medicine (INM-4), Research Centre, Juelich (Germany); Mueller, Dirk [University of Cologne, Institute for Health Economics and Clinical Epidemiology, Cologne (Germany); Behrendt, Florian F. [RWTH Aachen University Hospital, Department of Nuclear Medicine, Aachen, Pauwelsstrasse 30 (Germany); Giovanella, Luca [Institute of Southern Switzerland, Department of Nuclear Medicine Oncology, Belinzona (Switzerland); Mottaghy, Felix M.; Verburg, Frederik A. [RWTH Aachen University Hospital, Department of Nuclear Medicine, Aachen, Pauwelsstrasse 30 (Germany); Maastricht University Medical Center, Department of Nuclear Medicine, Maastricht (Netherlands)

    2014-08-15

    To compare the cost-effectiveness of {sup 99m}Tc-methoxyisobutylisonitrile (MIBI) thyroid scintigraphy and the Afirma registered gene expression classifier for the assessment of cytologically indeterminate thyroid nodules. A decision tree model was used. Costs were calculated from the perspective of the German health insurance system. The robustness of the results was assessed with probabilistic sensitivity analyses using a Monte Carlo simulation. Life expectancy was 34.3 years (estimated costs per patient EUR1,459 - EUR2,224) for the MIBI scan and 34.1 years (estimated costs EUR3,560 - EUR4,071) for the molecular test. These results were confirmed by the Monte Carlo simulation. MIBI thyroid scintigraphy is more cost-effective than the gene expression classifier. (orig.)

  1. A novel algorithm for simplification of complex gene classifiers in cancer

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    Wilson, Raphael A.; Teng, Ling; Bachmeyer, Karen M.; Bissonnette, Mei Lin Z.; Husain, Aliya N.; Parham, David M.; Triche, Timothy J.; Wing, Michele R.; Gastier-Foster, Julie M.; Barr, Frederic G.; Hawkins, Douglas S.; Anderson, James R.; Skapek, Stephen X.; Volchenboum, Samuel L.

    2013-01-01

    The clinical application of complex molecular classifiers as diagnostic or prognostic tools has been limited by the time and cost needed to apply them to patients. Using an existing fifty-gene expression signature known to separate two molecular subtypes of the pediatric cancer rhabdomyosarcoma, we show that an exhaustive iterative search algorithm can distill this complex classifier down to two or three features with equal discrimination. We validated the two-gene signatures using three separate and distinct data sets, including one that uses degraded RNA extracted from formalin-fixed, paraffin-embedded material. Finally, to demonstrate the generalizability of our algorithm, we applied it to a lung cancer data set to find minimal gene signatures that can distinguish survival. Our approach can easily be generalized and coupled to existing technical platforms to facilitate the discovery of simplified signatures that are ready for routine clinical use. PMID:23913937

  2. Robust assignment of cancer subtypes from expression data using a uni-variate gene expression average as classifier

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    Lauss, Martin; Frigyesi, Attila; Ryden, Tobias; Höglund, Mattias

    2010-01-01

    Genome wide gene expression data is a rich source for the identification of gene signatures suitable for clinical purposes and a number of statistical algorithms have been described for both identification and evaluation of such signatures. Some employed algorithms are fairly complex and hence sensitive to over-fitting whereas others are more simple and straight forward. Here we present a new type of simple algorithm based on ROC analysis and the use of metagenes that we believe will be a good complement to existing algorithms. The basis for the proposed approach is the use of metagenes, instead of collections of individual genes, and a feature selection using AUC values obtained by ROC analysis. Each gene in a data set is assigned an AUC value relative to the tumor class under investigation and the genes are ranked according to these values. Metagenes are then formed by calculating the mean expression level for an increasing number of ranked genes, and the metagene expression value that optimally discriminates tumor classes in the training set is used for classification of new samples. The performance of the metagene is then evaluated using LOOCV and balanced accuracies. We show that the simple uni-variate gene expression average algorithm performs as well as several alternative algorithms such as discriminant analysis and the more complex approaches such as SVM and neural networks. The R package rocc is freely available at http://cran.r-project.org/web/packages/rocc/index.html

  3. Random Subspace Aggregation for Cancer Prediction with Gene Expression Profiles

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    Liying Yang

    2016-01-01

    Full Text Available Background. Precisely predicting cancer is crucial for cancer treatment. Gene expression profiles make it possible to analyze patterns between genes and cancers on the genome-wide scale. Gene expression data analysis, however, is confronted with enormous challenges for its characteristics, such as high dimensionality, small sample size, and low Signal-to-Noise Ratio. Results. This paper proposes a method, termed RS_SVM, to predict gene expression profiles via aggregating SVM trained on random subspaces. After choosing gene features through statistical analysis, RS_SVM randomly selects feature subsets to yield random subspaces and training SVM classifiers accordingly and then aggregates SVM classifiers to capture the advantage of ensemble learning. Experiments on eight real gene expression datasets are performed to validate the RS_SVM method. Experimental results show that RS_SVM achieved better classification accuracy and generalization performance in contrast with single SVM, K-nearest neighbor, decision tree, Bagging, AdaBoost, and the state-of-the-art methods. Experiments also explored the effect of subspace size on prediction performance. Conclusions. The proposed RS_SVM method yielded superior performance in analyzing gene expression profiles, which demonstrates that RS_SVM provides a good channel for such biological data.

  4. A Classification Framework Applied to Cancer Gene Expression Profiles

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    Hussein Hijazi

    2013-01-01

    Full Text Available Classification of cancer based on gene expression has provided insight into possible treatment strategies. Thus, developing machine learning methods that can successfully distinguish among cancer subtypes or normal versus cancer samples is important. This work discusses supervised learning techniques that have been employed to classify cancers. Furthermore, a two-step feature selection method based on an attribute estimation method (e.g., ReliefF and a genetic algorithm was employed to find a set of genes that can best differentiate between cancer subtypes or normal versus cancer samples. The application of different classification methods (e.g., decision tree, k-nearest neighbor, support vector machine (SVM, bagging, and random forest on 5 cancer datasets shows that no classification method universally outperforms all the others. However, k-nearest neighbor and linear SVM generally improve the classification performance over other classifiers. Finally, incorporating diverse types of genomic data (e.g., protein-protein interaction data and gene expression increase the prediction accuracy as compared to using gene expression alone.

  5. Classifying genes to the correct Gene Ontology Slim term in Saccharomyces cerevisiae using neighbouring genes with classification learning

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    Tsatsoulis Costas

    2010-05-01

    Full Text Available Abstract Background There is increasing evidence that gene location and surrounding genes influence the functionality of genes in the eukaryotic genome. Knowing the Gene Ontology Slim terms associated with a gene gives us insight into a gene's functionality by informing us how its gene product behaves in a cellular context using three different ontologies: molecular function, biological process, and cellular component. In this study, we analyzed if we could classify a gene in Saccharomyces cerevisiae to its correct Gene Ontology Slim term using information about its location in the genome and information from its nearest-neighbouring genes using classification learning. Results We performed experiments to establish that the MultiBoostAB algorithm using the J48 classifier could correctly classify Gene Ontology Slim terms of a gene given information regarding the gene's location and information from its nearest-neighbouring genes for training. Different neighbourhood sizes were examined to determine how many nearest neighbours should be included around each gene to provide better classification rules. Our results show that by just incorporating neighbour information from each gene's two-nearest neighbours, the percentage of correctly classified genes to their correct Gene Ontology Slim term for each ontology reaches over 80% with high accuracy (reflected in F-measures over 0.80 of the classification rules produced. Conclusions We confirmed that in classifying genes to their correct Gene Ontology Slim term, the inclusion of neighbour information from those genes is beneficial. Knowing the location of a gene and the Gene Ontology Slim information from neighbouring genes gives us insight into that gene's functionality. This benefit is seen by just including information from a gene's two-nearest neighbouring genes.

  6. Gene expression variation to predict 10-year survival in lymph-node-negative breast cancer

    International Nuclear Information System (INIS)

    Karlsson, Elin; Delle, Ulla; Danielsson, Anna; Olsson, Björn; Abel, Frida; Karlsson, Per; Helou, Khalil

    2008-01-01

    It is of great significance to find better markers to correctly distinguish between high-risk and low-risk breast cancer patients since the majority of breast cancer cases are at present being overtreated. 46 tumours from node-negative breast cancer patients were studied with gene expression microarrays. A t-test was carried out in order to find a set of genes where the expression might predict clinical outcome. Two classifiers were used for evaluation of the gene lists, a correlation-based classifier and a Voting Features Interval (VFI) classifier. We then evaluated the predictive accuracy of this expression signature on tumour sets from two similar studies on lymph-node negative patients. They had both developed gene expression signatures superior to current methods in classifying node-negative breast tumours. These two signatures were also tested on our material. A list of 51 genes whose expression profiles could predict clinical outcome with high accuracy in our material (96% or 89% accuracy in cross-validation, depending on type of classifier) was developed. When tested on two independent data sets, the expression signature based on the 51 identified genes had good predictive qualities in one of the data sets (74% accuracy), whereas their predictive value on the other data set were poor, presumably due to the fact that only 23 of the 51 genes were found in that material. We also found that previously developed expression signatures could predict clinical outcome well to moderately well in our material (72% and 61%, respectively). The list of 51 genes derived in this study might have potential for clinical utility as a prognostic gene set, and may include candidate genes of potential relevance for clinical outcome in breast cancer. According to the predictions by this expression signature, 30 of the 46 patients may have benefited from different adjuvant treatment than they recieved. The research on these tumours was approved by the Medical Faculty Research

  7. Enhanced gene ranking approaches using modified trace ratio algorithm for gene expression data

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    Shruti Mishra

    Full Text Available Microarray technology enables the understanding and investigation of gene expression levels by analyzing high dimensional datasets that contain few samples. Over time, microarray expression data have been collected for studying the underlying biological mechanisms of disease. One such application for understanding the mechanism is by constructing a gene regulatory network (GRN. One of the foremost key criteria for GRN discovery is gene selection. Choosing a generous set of genes for the structure of the network is highly desirable. For this role, two suitable methods were proposed for selection of appropriate genes. The first approach comprises a gene selection method called Information gain, where the dataset is reformed and fused with another distinct algorithm called Trace Ratio (TR. Our second method is the implementation of our projected modified TR algorithm, where the scoring base for finding weight matrices has been re-designed. Both the methods' efficiency was shown with different classifiers that include variants of the Artificial Neural Network classifier, such as Resilient Propagation, Quick Propagation, Back Propagation, Manhattan Propagation and Radial Basis Function Neural Network and also the Support Vector Machine (SVM classifier. In the study, it was confirmed that both of the proposed methods worked well and offered high accuracy with a lesser number of iterations as compared to the original Trace Ratio algorithm. Keywords: Gene regulatory network, Gene selection, Information gain, Trace ratio, Canonical correlation analysis, Classification

  8. LINE FUSION GENES: a database of LINE expression in human genes

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    Park Hong-Seog

    2006-06-01

    Full Text Available Abstract Background Long Interspersed Nuclear Elements (LINEs are the most abundant retrotransposons in humans. About 79% of human genes are estimated to contain at least one segment of LINE per transcription unit. Recent studies have shown that LINE elements can affect protein sequences, splicing patterns and expression of human genes. Description We have developed a database, LINE FUSION GENES, for elucidating LINE expression throughout the human gene database. We searched the 28,171 genes listed in the NCBI database for LINE elements and analyzed their structures and expression patterns. The results show that the mRNA sequences of 1,329 genes were affected by LINE expression. The LINE expression types were classified on the basis of LINEs in the 5' UTR, exon or 3' UTR sequences of the mRNAs. Our database provides further information, such as the tissue distribution and chromosomal location of the genes, and the domain structure that is changed by LINE integration. We have linked all the accession numbers to the NCBI data bank to provide mRNA sequences for subsequent users. Conclusion We believe that our work will interest genome scientists and might help them to gain insight into the implications of LINE expression for human evolution and disease. Availability http://www.primate.or.kr/line

  9. A systems biology-based classifier for hepatocellular carcinoma diagnosis.

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    Yanqiong Zhang

    Full Text Available AIM: The diagnosis of hepatocellular carcinoma (HCC in the early stage is crucial to the application of curative treatments which are the only hope for increasing the life expectancy of patients. Recently, several large-scale studies have shed light on this problem through analysis of gene expression profiles to identify markers correlated with HCC progression. However, those marker sets shared few genes in common and were poorly validated using independent data. Therefore, we developed a systems biology based classifier by combining the differential gene expression with topological features of human protein interaction networks to enhance the ability of HCC diagnosis. METHODS AND RESULTS: In the Oncomine platform, genes differentially expressed in HCC tissues relative to their corresponding normal tissues were filtered by a corrected Q value cut-off and Concept filters. The identified genes that are common to different microarray datasets were chosen as the candidate markers. Then, their networks were analyzed by GeneGO Meta-Core software and the hub genes were chosen. After that, an HCC diagnostic classifier was constructed by Partial Least Squares modeling based on the microarray gene expression data of the hub genes. Validations of diagnostic performance showed that this classifier had high predictive accuracy (85.88∼92.71% and area under ROC curve (approximating 1.0, and that the network topological features integrated into this classifier contribute greatly to improving the predictive performance. Furthermore, it has been demonstrated that this modeling strategy is not only applicable to HCC, but also to other cancers. CONCLUSION: Our analysis suggests that the systems biology-based classifier that combines the differential gene expression and topological features of human protein interaction network may enhance the diagnostic performance of HCC classifier.

  10. The rules of gene expression in plants: Organ identity and gene body methylation are key factors for regulation of gene expression in Arabidopsis thaliana

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    Gutiérrez Rodrigo A

    2008-09-01

    Full Text Available Abstract Background Microarray technology is a widely used approach for monitoring genome-wide gene expression. For Arabidopsis, there are over 1,800 microarray hybridizations representing many different experimental conditions on Affymetrix™ ATH1 gene chips alone. This huge amount of data offers a unique opportunity to infer the principles that govern the regulation of gene expression in plants. Results We used bioinformatics methods to analyze publicly available data obtained using the ATH1 chip from Affymetrix. A total of 1887 ATH1 hybridizations were normalized and filtered to eliminate low-quality hybridizations. We classified and compared control and treatment hybridizations and determined differential gene expression. The largest differences in gene expression were observed when comparing samples obtained from different organs. On average, ten-fold more genes were differentially expressed between organs as compared to any other experimental variable. We defined "gene responsiveness" as the number of comparisons in which a gene changed its expression significantly. We defined genes with the highest and lowest responsiveness levels as hypervariable and housekeeping genes, respectively. Remarkably, housekeeping genes were best distinguished from hypervariable genes by differences in methylation status in their transcribed regions. Moreover, methylation in the transcribed region was inversely correlated (R2 = 0.8 with gene responsiveness on a genome-wide scale. We provide an example of this negative relationship using genes encoding TCA cycle enzymes, by contrasting their regulatory responsiveness to nitrate and methylation status in their transcribed regions. Conclusion Our results indicate that the Arabidopsis transcriptome is largely established during development and is comparatively stable when faced with external perturbations. We suggest a novel functional role for DNA methylation in the transcribed region as a key determinant

  11. Tumor Microenvironment Gene Signature as a Prognostic Classifier and Therapeutic Target

    Science.gov (United States)

    2016-06-01

    AWARD NUMBER: W81XWH-14-1-0107 TITLE: Tumor Microenvironment Gene Signature as a Prognostic Classifier and Therapeutic Target PRINCIPAL...AND SUBTITLE Tumor Microenvironment Gene Signature as a 5a. CONTRACT NUMBER W81XWH-14-1-0107 Prognostic Classifier and Therapeutic Target 5b...gene signature that correlates with poor survival in ovarian cancer patients. We are refining this gene signature to develop biomarkers for the

  12. GOexpress: an R/Bioconductor package for the identification and visualisation of robust gene ontology signatures through supervised learning of gene expression data.

    Science.gov (United States)

    Rue-Albrecht, Kévin; McGettigan, Paul A; Hernández, Belinda; Nalpas, Nicolas C; Magee, David A; Parnell, Andrew C; Gordon, Stephen V; MacHugh, David E

    2016-03-11

    Identification of gene expression profiles that differentiate experimental groups is critical for discovery and analysis of key molecular pathways and also for selection of robust diagnostic or prognostic biomarkers. While integration of differential expression statistics has been used to refine gene set enrichment analyses, such approaches are typically limited to single gene lists resulting from simple two-group comparisons or time-series analyses. In contrast, functional class scoring and machine learning approaches provide powerful alternative methods to leverage molecular measurements for pathway analyses, and to compare continuous and multi-level categorical factors. We introduce GOexpress, a software package for scoring and summarising the capacity of gene ontology features to simultaneously classify samples from multiple experimental groups. GOexpress integrates normalised gene expression data (e.g., from microarray and RNA-seq experiments) and phenotypic information of individual samples with gene ontology annotations to derive a ranking of genes and gene ontology terms using a supervised learning approach. The default random forest algorithm allows interactions between all experimental factors, and competitive scoring of expressed genes to evaluate their relative importance in classifying predefined groups of samples. GOexpress enables rapid identification and visualisation of ontology-related gene panels that robustly classify groups of samples and supports both categorical (e.g., infection status, treatment) and continuous (e.g., time-series, drug concentrations) experimental factors. The use of standard Bioconductor extension packages and publicly available gene ontology annotations facilitates straightforward integration of GOexpress within existing computational biology pipelines.

  13. Gene Expression Ratios Lead to Accurate and Translatable Predictors of DR5 Agonism across Multiple Tumor Lineages.

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    Anupama Reddy

    Full Text Available Death Receptor 5 (DR5 agonists demonstrate anti-tumor activity in preclinical models but have yet to demonstrate robust clinical responses. A key limitation may be the lack of patient selection strategies to identify those most likely to respond to treatment. To overcome this limitation, we screened a DR5 agonist Nanobody across >600 cell lines representing 21 tumor lineages and assessed molecular features associated with response. High expression of DR5 and Casp8 were significantly associated with sensitivity, but their expression thresholds were difficult to translate due to low dynamic ranges. To address the translational challenge of establishing thresholds of gene expression, we developed a classifier based on ratios of genes that predicted response across lineages. The ratio classifier outperformed the DR5+Casp8 classifier, as well as standard approaches for feature selection and classification using genes, instead of ratios. This classifier was independently validated using 11 primary patient-derived pancreatic xenograft models showing perfect predictions as well as a striking linearity between prediction probability and anti-tumor response. A network analysis of the genes in the ratio classifier captured important biological relationships mediating drug response, specifically identifying key positive and negative regulators of DR5 mediated apoptosis, including DR5, CASP8, BID, cFLIP, XIAP and PEA15. Importantly, the ratio classifier shows translatability across gene expression platforms (from Affymetrix microarrays to RNA-seq and across model systems (in vitro to in vivo. Our approach of using gene expression ratios presents a robust and novel method for constructing translatable biomarkers of compound response, which can also probe the underlying biology of treatment response.

  14. Gene Expression Ratios Lead to Accurate and Translatable Predictors of DR5 Agonism across Multiple Tumor Lineages.

    Science.gov (United States)

    Reddy, Anupama; Growney, Joseph D; Wilson, Nick S; Emery, Caroline M; Johnson, Jennifer A; Ward, Rebecca; Monaco, Kelli A; Korn, Joshua; Monahan, John E; Stump, Mark D; Mapa, Felipa A; Wilson, Christopher J; Steiger, Janine; Ledell, Jebediah; Rickles, Richard J; Myer, Vic E; Ettenberg, Seth A; Schlegel, Robert; Sellers, William R; Huet, Heather A; Lehár, Joseph

    2015-01-01

    Death Receptor 5 (DR5) agonists demonstrate anti-tumor activity in preclinical models but have yet to demonstrate robust clinical responses. A key limitation may be the lack of patient selection strategies to identify those most likely to respond to treatment. To overcome this limitation, we screened a DR5 agonist Nanobody across >600 cell lines representing 21 tumor lineages and assessed molecular features associated with response. High expression of DR5 and Casp8 were significantly associated with sensitivity, but their expression thresholds were difficult to translate due to low dynamic ranges. To address the translational challenge of establishing thresholds of gene expression, we developed a classifier based on ratios of genes that predicted response across lineages. The ratio classifier outperformed the DR5+Casp8 classifier, as well as standard approaches for feature selection and classification using genes, instead of ratios. This classifier was independently validated using 11 primary patient-derived pancreatic xenograft models showing perfect predictions as well as a striking linearity between prediction probability and anti-tumor response. A network analysis of the genes in the ratio classifier captured important biological relationships mediating drug response, specifically identifying key positive and negative regulators of DR5 mediated apoptosis, including DR5, CASP8, BID, cFLIP, XIAP and PEA15. Importantly, the ratio classifier shows translatability across gene expression platforms (from Affymetrix microarrays to RNA-seq) and across model systems (in vitro to in vivo). Our approach of using gene expression ratios presents a robust and novel method for constructing translatable biomarkers of compound response, which can also probe the underlying biology of treatment response.

  15. Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

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    Teng Shaolei

    2013-01-01

    Full Text Available Abstract Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs and Support Vector Machines (SVMs were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. Conclusions A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression.

  16. Mining gene expression data of multiple sclerosis.

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    Pi Guo

    Full Text Available Microarray produces a large amount of gene expression data, containing various biological implications. The challenge is to detect a panel of discriminative genes associated with disease. This study proposed a robust classification model for gene selection using gene expression data, and performed an analysis to identify disease-related genes using multiple sclerosis as an example.Gene expression profiles based on the transcriptome of peripheral blood mononuclear cells from a total of 44 samples from 26 multiple sclerosis patients and 18 individuals with other neurological diseases (control were analyzed. Feature selection algorithms including Support Vector Machine based on Recursive Feature Elimination, Receiver Operating Characteristic Curve, and Boruta algorithms were jointly performed to select candidate genes associating with multiple sclerosis. Multiple classification models categorized samples into two different groups based on the identified genes. Models' performance was evaluated using cross-validation methods, and an optimal classifier for gene selection was determined.An overlapping feature set was identified consisting of 8 genes that were differentially expressed between the two phenotype groups. The genes were significantly associated with the pathways of apoptosis and cytokine-cytokine receptor interaction. TNFSF10 was significantly associated with multiple sclerosis. A Support Vector Machine model was established based on the featured genes and gave a practical accuracy of ∼86%. This binary classification model also outperformed the other models in terms of Sensitivity, Specificity and F1 score.The combined analytical framework integrating feature ranking algorithms and Support Vector Machine model could be used for selecting genes for other diseases.

  17. Gene-expression profiling after exposure to C-ion beams

    International Nuclear Information System (INIS)

    Saegusa, Kumiko; Furuno, Aki; Ishikawa, Kenichi; Ishikawa, Atsuko; Ohtsuka, Yoshimi; Kawai, Seiko; Imai, Takashi; Nojima, Kumie

    2005-01-01

    It is recognized that carbon-ion beam kills cancer cells more efficiently than X-ray. In this study we have compared cellular gene expression response after carbon-ion beam exposure with that after X-ray exposure. Gene expression profiles of cultured neonatal human dermal fibroblasts (NHDF) at 0, 1, 3, 6, 12, 18, and 24 hr after exposure to 0.1, 2 and 5 Gy of X-ray or carbon-ion beam were obtained using 22K oligonucleotide microarray. N-way ANOVA analysis of whole gene expression data sets selected 960 genes for carbon-ion beam and 977 genes for X-ray, respectively. Interestingly, majority of these genes (91% for carbon-ion beam and 88% for X-ray, respectively) were down regulated. The selected genes were further classified by their dose-dependence or time-dependence of gene expression change (fold change>1.5). It was revealed that genes involved in cell proliferation had tendency to show time-dependent up regulation by carbon-ion beam. Another N-way ANOVA analysis was performed to select 510 genes, and further selection was made to find 70 genes that showed radiation species-dependent gene expression change (fold change>1.25). These genes were then categorized by the K-Mean clustering method into 4 clusters. Each cluster showed tendency to contain genes involved in cell cycle regulation, cell death, responses to stress and metabolisms, respectively. (author)

  18. Global expression differences and tissue specific expression differences in rice evolution result in two contrasting types of differentially expressed genes

    KAUST Repository

    Horiuchi, Youko

    2015-12-23

    Background Since the development of transcriptome analysis systems, many expression evolution studies characterized evolutionary forces acting on gene expression, without explicit discrimination between global expression differences and tissue specific expression differences. However, different types of gene expression alteration should have different effects on an organism, the evolutionary forces that act on them might be different, and different types of genes might show different types of differential expression between species. To confirm this, we studied differentially expressed (DE) genes among closely related groups that have extensive gene expression atlases, and clarified characteristics of different types of DE genes including the identification of regulating loci for differential expression using expression quantitative loci (eQTL) analysis data. Results We detected differentially expressed (DE) genes between rice subspecies in five homologous tissues that were verified using japonica and indica transcriptome atlases in public databases. Using the transcriptome atlases, we classified DE genes into two types, global DE genes and changed-tissues DE genes. Global type DE genes were not expressed in any tissues in the atlas of one subspecies, however changed-tissues type DE genes were expressed in both subspecies with different tissue specificity. For the five tissues in the two japonica-indica combinations, 4.6 ± 0.8 and 5.9 ± 1.5 % of highly expressed genes were global and changed-tissues DE genes, respectively. Changed-tissues DE genes varied in number between tissues, increasing linearly with the abundance of tissue specifically expressed genes in the tissue. Molecular evolution of global DE genes was rapid, unlike that of changed-tissues DE genes. Based on gene ontology, global and changed-tissues DE genes were different, having no common GO terms. Expression differences of most global DE genes were regulated by cis-eQTLs. Expression

  19. SVM classifier to predict genes important for self-renewal and pluripotency of mouse embryonic stem cells

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    Xu Huilei

    2010-12-01

    Full Text Available Abstract Background Mouse embryonic stem cells (mESCs are derived from the inner cell mass of a developing blastocyst and can be cultured indefinitely in-vitro. Their distinct features are their ability to self-renew and to differentiate to all adult cell types. Genes that maintain mESCs self-renewal and pluripotency identity are of interest to stem cell biologists. Although significant steps have been made toward the identification and characterization of such genes, the list is still incomplete and controversial. For example, the overlap among candidate self-renewal and pluripotency genes across different RNAi screens is surprisingly small. Meanwhile, machine learning approaches have been used to analyze multi-dimensional experimental data and integrate results from many studies, yet they have not been applied to specifically tackle the task of predicting and classifying self-renewal and pluripotency gene membership. Results For this study we developed a classifier, a supervised machine learning framework for predicting self-renewal and pluripotency mESCs stemness membership genes (MSMG using support vector machines (SVM. The data used to train the classifier was derived from mESCs-related studies using mRNA microarrays, measuring gene expression in various stages of early differentiation, as well as ChIP-seq studies applied to mESCs profiling genome-wide binding of key transcription factors, such as Nanog, Oct4, and Sox2, to the regulatory regions of other genes. Comparison to other classification methods using the leave-one-out cross-validation method was employed to evaluate the accuracy and generality of the classification. Finally, two sets of candidate genes from genome-wide RNA interference screens are used to test the generality and potential application of the classifier. Conclusions Our results reveal that an SVM approach can be useful for prioritizing genes for functional validation experiments and complement the analyses of high

  20. Differential genome-wide gene expression profiling of bovine largest and second-largest follicles: identification of genes associated with growth of dominant follicles

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    Takahashi Toru

    2010-02-01

    Full Text Available Abstract Background Bovine follicular development is regulated by numerous molecular mechanisms and biological pathways. In this study, we tried to identify differentially expressed genes between largest (F1 and second-largest follicles (F2, and classify them by global gene expression profiling using a combination of microarray and quantitative real-time PCR (QPCR analysis. The follicular status of F1 and F2 were further evaluated in terms of healthy and atretic conditions by investigating mRNA localization of identified genes. Methods Global gene expression profiles of F1 (10.7 +/- 0.7 mm and F2 (7.8 +/- 0.2 mm were analyzed by hierarchical cluster analysis and expression profiles of 16 representative genes were confirmed by QPCR analysis. In addition, localization of six identified transcripts was investigated in healthy and atretic follicles using in situ hybridization. The healthy or atretic condition of examined follicles was classified by progesterone and estradiol concentrations in follicular fluid. Results Hierarchical cluster analysis of microarray data classified the follicles into two clusters. Cluster A was composed of only F2 and was characterized by high expression of 31 genes including IGFBP5, whereas cluster B contained only F1 and predominantly expressed 45 genes including CYP19 and FSHR. QPCR analysis confirmed AMH, CYP19, FSHR, GPX3, PlGF, PLA2G1B, SCD and TRB2 were greater in F1 than F2, while CCL2, GADD45A, IGFBP5, PLAUR, SELP, SPP1, TIMP1 and TSP2 were greater in F2 than in F1. In situ hybridization showed that AMH and CYP19 were detected in granulosa cells (GC of healthy as well as atretic follicles. PlGF was localized in GC and in the theca layer (TL of healthy follicles. IGFBP5 was detected in both GC and TL of atretic follicles. GADD45A and TSP2 were localized in both GC and TL of atretic follicles, whereas healthy follicles expressed them only in GC. Conclusion We demonstrated that global gene expression profiling of F

  1. Differential gene expression patterns between smokers and non‐smokers: cause or consequence?

    Science.gov (United States)

    Jansen, Rick; Brooks, Andy; Willemsen, Gonneke; van Grootheest, Gerard; de Geus, Eco; Smit, Jan H.; Penninx, Brenda W.; Boomsma, Dorret I.

    2015-01-01

    Abstract The molecular mechanisms causing smoking‐induced health decline are largely unknown. To elucidate the molecular pathways involved in cause and consequences of smoking behavior, we conducted a genome‐wide gene expression study in peripheral blood samples targeting 18 238 genes. Data of 743 smokers, 1686 never smokers and 890 ex‐smokers were available from two population‐based cohorts from the Netherlands. In addition, data of 56 monozygotic twin pairs discordant for ever smoking were used. One hundred thirty‐two genes were differentially expressed between current smokers and never smokers (P smokers into account, expression of these 132 genes was classified into reversible (94 genes), slowly reversible (31 genes), irreversible (6 genes) or inconclusive (1 gene). Expression of 6 of the 132 genes (three reversible and three slowly reversible) was confirmed to be reactive to smoking as they were differentially expressed in monozygotic pairs discordant for smoking. Cis‐expression quantitative trait loci for GPR56 and RARRES3 (downregulated in smokers) were associated with increased number of cigarettes smoked per day in a large genome‐wide association meta‐analysis, suggesting a causative effect of GPR56 and RARRES3 expression on smoking behavior. In conclusion, differential gene expression patterns in smokers are extensive and cluster in several underlying disease pathways. Gene expression differences seem mainly direct consequences of smoking, and largely reversible after smoking cessation. However, we also identified DNA variants that may influence smoking behavior via the mediating gene expression. PMID:26594007

  2. Customized oligonucleotide microarray gene expression-based classification of neuroblastoma patients outperforms current clinical risk stratification.

    Science.gov (United States)

    Oberthuer, André; Berthold, Frank; Warnat, Patrick; Hero, Barbara; Kahlert, Yvonne; Spitz, Rüdiger; Ernestus, Karen; König, Rainer; Haas, Stefan; Eils, Roland; Schwab, Manfred; Brors, Benedikt; Westermann, Frank; Fischer, Matthias

    2006-11-01

    To develop a gene expression-based classifier for neuroblastoma patients that reliably predicts courses of the disease. Two hundred fifty-one neuroblastoma specimens were analyzed using a customized oligonucleotide microarray comprising 10,163 probes for transcripts with differential expression in clinical subgroups of the disease. Subsequently, the prediction analysis for microarrays (PAM) was applied to a first set of patients with maximally divergent clinical courses (n = 77). The classification accuracy was estimated by a complete 10-times-repeated 10-fold cross validation, and a 144-gene predictor was constructed from this set. This classifier's predictive power was evaluated in an independent second set (n = 174) by comparing results of the gene expression-based classification with those of risk stratification systems of current trials from Germany, Japan, and the United States. The first set of patients was accurately predicted by PAM (cross-validated accuracy, 99%). Within the second set, the PAM classifier significantly separated cohorts with distinct courses (3-year event-free survival [EFS] 0.86 +/- 0.03 [favorable; n = 115] v 0.52 +/- 0.07 [unfavorable; n = 59] and 3-year overall survival 0.99 +/- 0.01 v 0.84 +/- 0.05; both P model, the PAM predictor classified patients of the second set more accurately than risk stratification of current trials from Germany, Japan, and the United States (P < .001; hazard ratio, 4.756 [95% CI, 2.544 to 8.893]). Integration of gene expression-based class prediction of neuroblastoma patients may improve risk estimation of current neuroblastoma trials.

  3. Gene expression and gene therapy imaging

    International Nuclear Information System (INIS)

    Rome, Claire; Couillaud, Franck; Moonen, Chrit T.W.

    2007-01-01

    The fast growing field of molecular imaging has achieved major advances in imaging gene expression, an important element of gene therapy. Gene expression imaging is based on specific probes or contrast agents that allow either direct or indirect spatio-temporal evaluation of gene expression. Direct evaluation is possible with, for example, contrast agents that bind directly to a specific target (e.g., receptor). Indirect evaluation may be achieved by using specific substrate probes for a target enzyme. The use of marker genes, also called reporter genes, is an essential element of MI approaches for gene expression in gene therapy. The marker gene may not have a therapeutic role itself, but by coupling the marker gene to a therapeutic gene, expression of the marker gene reports on the expression of the therapeutic gene. Nuclear medicine and optical approaches are highly sensitive (detection of probes in the picomolar range), whereas MRI and ultrasound imaging are less sensitive and require amplification techniques and/or accumulation of contrast agents in enlarged contrast particles. Recently developed MI techniques are particularly relevant for gene therapy. Amongst these are the possibility to track gene therapy vectors such as stem cells, and the techniques that allow spatiotemporal control of gene expression by non-invasive heating (with MRI guided focused ultrasound) and the use of temperature sensitive promoters. (orig.)

  4. Development of Gene Expression Signatures for Practical Radiation Biodosimetry

    International Nuclear Information System (INIS)

    Paul, Sunirmal; Amundson, Sally A.

    2008-01-01

    Purpose: In a large-scale radiologic emergency, estimates of exposure doses and radiation injury would be required for individuals without physical dosimeters. Current methods are inadequate for the task, so we are developing gene expression profiles for radiation biodosimetry. This approach could provide both an estimate of physical radiation dose and an indication of the extent of individual injury or future risk. Methods and Materials: We used whole genome microarray expression profiling as a discovery platform to identify genes with the potential to predict radiation dose across an exposure range relevant for medical decision making in a radiologic emergency. Human peripheral blood from 10 healthy donors was irradiated ex vivo, and global gene expression was measured both 6 and 24 h after exposure. Results: A 74-gene signature was identified that distinguishes between four radiation doses (0.5, 2, 5, and 8 Gy) and controls. More than one third of these genes are regulated by TP53. A nearest centroid classifier using these same 74 genes correctly predicted 98% of samples taken either 6 h or 24 h after treatment as unexposed, exposed to 0.5, 2, or ≥5 Gy. Expression patterns of five genes (CDKN1A, FDXR, SESN1, BBC3, and PHPT1) from this signature were also confirmed by real-time polymerase chain reaction. Conclusion: The ability of a single gene set to predict radiation dose throughout a window of time without need for individual pre-exposure controls represents an important advance in the development of gene expression for biodosimetry

  5. Supplementary Material for: Global expression differences and tissue specific expression differences in rice evolution result in two contrasting types of differentially expressed genes

    KAUST Repository

    Horiuchi, Youko; Harushima, Yoshiaki; Fujisawa, Hironori; Mochizuki, Takako; Fujita, Masahiro; Ohyanagi, Hajime; Kurata, Nori

    2015-01-01

    Abstract Background Since the development of transcriptome analysis systems, many expression evolution studies characterized evolutionary forces acting on gene expression, without explicit discrimination between global expression differences and tissue specific expression differences. However, different types of gene expression alteration should have different effects on an organism, the evolutionary forces that act on them might be different, and different types of genes might show different types of differential expression between species. To confirm this, we studied differentially expressed (DE) genes among closely related groups that have extensive gene expression atlases, and clarified characteristics of different types of DE genes including the identification of regulating loci for differential expression using expression quantitative loci (eQTL) analysis data. Results We detected differentially expressed (DE) genes between rice subspecies in five homologous tissues that were verified using japonica and indica transcriptome atlases in public databases. Using the transcriptome atlases, we classified DE genes into two types, global DE genes and changed-tissues DE genes. Global type DE genes were not expressed in any tissues in the atlas of one subspecies, however changed-tissues type DE genes were expressed in both subspecies with different tissue specificity. For the five tissues in the two japonica-indica combinations, 4.6 ± 0.8 and 5.9 ± 1.5 % of highly expressed genes were global and changed-tissues DE genes, respectively. Changed-tissues DE genes varied in number between tissues, increasing linearly with the abundance of tissue specifically expressed genes in the tissue. Molecular evolution of global DE genes was rapid, unlike that of changed-tissues DE genes. Based on gene ontology, global and changed-tissues DE genes were different, having no common GO terms. Expression differences of most global DE genes were regulated by cis

  6. Effects of cultural characteristics on building an emotion classifier through facial expression analysis

    Science.gov (United States)

    da Silva, Flávio Altinier Maximiano; Pedrini, Helio

    2015-03-01

    Facial expressions are an important demonstration of humanity's humors and emotions. Algorithms capable of recognizing facial expressions and associating them with emotions were developed and employed to compare the expressions that different cultural groups use to show their emotions. Static pictures of predominantly occidental and oriental subjects from public datasets were used to train machine learning algorithms, whereas local binary patterns, histogram of oriented gradients (HOGs), and Gabor filters were employed to describe the facial expressions for six different basic emotions. The most consistent combination, formed by the association of HOG filter and support vector machines, was then used to classify the other cultural group: there was a strong drop in accuracy, meaning that the subtle differences of facial expressions of each culture affected the classifier performance. Finally, a classifier was trained with images from both occidental and oriental subjects and its accuracy was higher on multicultural data, evidencing the need of a multicultural training set to build an efficient classifier.

  7. Microarray gene expression profiling and analysis in renal cell carcinoma

    Directory of Open Access Journals (Sweden)

    Sadhukhan Provash

    2004-06-01

    Full Text Available Abstract Background Renal cell carcinoma (RCC is the most common cancer in adult kidney. The accuracy of current diagnosis and prognosis of the disease and the effectiveness of the treatment for the disease are limited by the poor understanding of the disease at the molecular level. To better understand the genetics and biology of RCC, we profiled the expression of 7,129 genes in both clear cell RCC tissue and cell lines using oligonucleotide arrays. Methods Total RNAs isolated from renal cell tumors, adjacent normal tissue and metastatic RCC cell lines were hybridized to affymatrix HuFL oligonucleotide arrays. Genes were categorized into different functional groups based on the description of the Gene Ontology Consortium and analyzed based on the gene expression levels. Gene expression profiles of the tissue and cell line samples were visualized and classified by singular value decomposition. Reverse transcription polymerase chain reaction was performed to confirm the expression alterations of selected genes in RCC. Results Selected genes were annotated based on biological processes and clustered into functional groups. The expression levels of genes in each group were also analyzed. Seventy-four commonly differentially expressed genes with more than five-fold changes in RCC tissues were identified. The expression alterations of selected genes from these seventy-four genes were further verified using reverse transcription polymerase chain reaction (RT-PCR. Detailed comparison of gene expression patterns in RCC tissue and RCC cell lines shows significant differences between the two types of samples, but many important expression patterns were preserved. Conclusions This is one of the initial studies that examine the functional ontology of a large number of genes in RCC. Extensive annotation, clustering and analysis of a large number of genes based on the gene functional ontology revealed many interesting gene expression patterns in RCC. Most

  8. AGEMAP: a gene expression database for aging in mice.

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    Jacob M Zahn

    2007-11-01

    Full Text Available We present the AGEMAP (Atlas of Gene Expression in Mouse Aging Project gene expression database, which is a resource that catalogs changes in gene expression as a function of age in mice. The AGEMAP database includes expression changes for 8,932 genes in 16 tissues as a function of age. We found great heterogeneity in the amount of transcriptional changes with age in different tissues. Some tissues displayed large transcriptional differences in old mice, suggesting that these tissues may contribute strongly to organismal decline. Other tissues showed few or no changes in expression with age, indicating strong levels of homeostasis throughout life. Based on the pattern of age-related transcriptional changes, we found that tissues could be classified into one of three aging processes: (1 a pattern common to neural tissues, (2 a pattern for vascular tissues, and (3 a pattern for steroid-responsive tissues. We observed that different tissues age in a coordinated fashion in individual mice, such that certain mice exhibit rapid aging, whereas others exhibit slow aging for multiple tissues. Finally, we compared the transcriptional profiles for aging in mice to those from humans, flies, and worms. We found that genes involved in the electron transport chain show common age regulation in all four species, indicating that these genes may be exceptionally good markers of aging. However, we saw no overall correlation of age regulation between mice and humans, suggesting that aging processes in mice and humans may be fundamentally different.

  9. Gene expression

    International Nuclear Information System (INIS)

    Hildebrand, C.E.; Crawford, B.D.; Walters, R.A.; Enger, M.D.

    1983-01-01

    We prepared probes for isolating functional pieces of the metallothionein locus. The probes enabled a variety of experiments, eventually revealing two mechanisms for metallothionein gene expression, the order of the DNA coding units at the locus, and the location of the gene site in its chromosome. Once the switch regulating metallothionein synthesis was located, it could be joined by recombinant DNA methods to other, unrelated genes, then reintroduced into cells by gene-transfer techniques. The expression of these recombinant genes could then be induced by exposing the cells to Zn 2+ or Cd 2+ . We would thus take advantage of the clearly defined switching properties of the metallothionein gene to manipulate the expression of other, perhaps normally constitutive, genes. Already, despite an incomplete understanding of how the regulatory switch of the metallothionein locus operates, such experiments have been performed successfully

  10. Differential expression patterns of housekeeping genes increase diagnostic and prognostic value in lung cancer

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    Yu-Chun Chang

    2018-05-01

    Full Text Available Background Using DNA microarrays, we previously identified 451 genes expressed in 19 different human tissues. Although ubiquitously expressed, the variable expression patterns of these “housekeeping genes” (HKGs could separate one normal human tissue type from another. Current focus on identifying “specific disease markers” is problematic as single gene expression in a given sample represents the specific cellular states of the sample at the time of collection. In this study, we examine the diagnostic and prognostic potential of the variable expressions of HKGs in lung cancers. Methods Microarray and RNA-seq data for normal lungs, lung adenocarcinomas (AD, squamous cell carcinomas of the lung (SQCLC, and small cell carcinomas of the lung (SCLC were collected from online databases. Using 374 of 451 HKGs, differentially expressed genes between pairs of sample types were determined via two-sided, homoscedastic t-test. Principal component analysis and hierarchical clustering classified normal lung and lung cancers subtypes according to relative gene expression variations. We used uni- and multi-variate cox-regressions to identify significant predictors of overall survival in AD patients. Classifying genes were selected using a set of training samples and then validated using an independent test set. Gene Ontology was examined by PANTHER. Results This study showed that the differential expression patterns of 242, 245, and 99 HKGs were able to distinguish normal lung from AD, SCLC, and SQCLC, respectively. From these, 70 HKGs were common across the three lung cancer subtypes. These HKGs have low expression variation compared to current lung cancer markers (e.g., EGFR, KRAS and were involved in the most common biological processes (e.g., metabolism, stress response. In addition, the expression pattern of 106 HKGs alone was a significant classifier of AD versus SQCLC. We further highlighted that a panel of 13 HKGs was an independent predictor of

  11. The clinical impact of hypoxia-regulated gene expression in loco-regional gastroesophageal cancer

    DEFF Research Database (Denmark)

    Winther, M.; Alsner, J.; Tramm, T.

    2015-01-01

    Purpose/Objective: In a former study (1), the hypoxia gene expression classifier, developed in head and neck squamous cell carcinomas, was applied in 89 patients with loco-regional gastroesophageal cancer (GC). Analysis of the 15 genes was indicative of hypoxia being more profound in esophagus...... and display greater heterogeneity compared to AC. However, previous indications that the hypoxia classifier might hold prognostic significance in ESCC patients could not be confirmed. Ongoing work includes in vitro studies of esophageal cancer cell lines in order to identify alternative hypoxia induced genes...... and to further explore the prognostic value of hypoxia in patients with loco-regional gastroesophageal cancer. (Figure Presented)....

  12. Gene expression profiles in stages II and III colon cancers

    DEFF Research Database (Denmark)

    Thorsteinsson, Morten; Kirkeby, Lene T; Hansen, Raino

    2012-01-01

    PURPOSE: A 128-gene signature has been proposed to predict outcome in patients with stages II and III colorectal cancers. In the present study, we aimed to reproduce and validate the 128-gene signature in external and independent material. METHODS: Gene expression data from the original material...... were retrieved from the Gene Expression Omnibus (GEO) (n¿=¿111) in addition to a Danish data set (n¿=¿37). All patients had stages II and III colon cancers. A Prediction Analysis of Microarray classifier, based on the 128-gene signature and the original training set of stage I (n¿=¿65) and stage IV (n...... correctly predicted as stage IV-like, and the remaining patients were predicted as stage I-like and unclassifiable, respectively. Stage II patients could not be stratified. CONCLUSIONS: The 128-gene signature showed reproducibility in stage III colon cancer, but could not predict recurrence in stage II...

  13. Hormonal Modulation of Breast Cancer Gene Expression: Implications for Intrinsic Subtyping in Premenopausal Women

    OpenAIRE

    Bernhardt, Sarah M.; Dasari, Pallave; Walsh, David; Townsend, Amanda R.; Price, Timothy J.; Ingman, Wendy V.

    2016-01-01

    Clinics are increasingly adopting gene-expression profiling to diagnose breast cancer subtype, providing an intrinsic, molecular portrait of the tumor. For example, the PAM50-based Prosigna test quantifies expression of 50 key genes to classify breast cancer subtype, and this method of classification has been demonstrated to be superior over traditional immunohistochemical methods that detect proteins, to predict risk of disease recurrence. However, these tests were largely developed and vali...

  14. A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data

    KAUST Repository

    Abusamra, Heba

    2013-05-01

    Microarray technology has enriched the study of gene expression in such a way that scientists are now able to measure the expression levels of thousands of genes in a single experiment. Microarray gene expression data gained great importance in recent years due to its role in disease diagnoses and prognoses which help to choose the appropriate treatment plan for patients. This technology has shifted a new era in molecular classification, interpreting gene expression data remains a difficult problem and an active research area due to their native nature of “high dimensional low sample size”. Such problems pose great challenges to existing classification methods. Thus, effective feature selection techniques are often needed in this case to aid to correctly classify different tumor types and consequently lead to a better understanding of genetic signatures as well as improve treatment strategies. This thesis aims on a comparative study of state-of-the-art feature selection methods, classification methods, and the combination of them, based on gene expression data. We compared the efficiency of three different classification methods including: support vector machines, k- nearest neighbor and random forest, and eight different feature selection methods, including: information gain, twoing rule, sum minority, max minority, gini index, sum of variances, t- statistics, and one-dimension support vector machine. Five-fold cross validation was used to evaluate the classification performance. Two publicly available gene expression data sets of glioma were used for this study. Different experiments have been applied to compare the performance of the classification methods with and without performing feature selection. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in

  15. High-throughput Microarray Detection of Vomeronasal Receptor Gene Expression in Rodents

    Directory of Open Access Journals (Sweden)

    Xiaohong Zhang

    2010-11-01

    Full Text Available We performed comprehensive data mining to explore the vomeronasal receptor (V1R & V2R repertoires in mouse and rat using the mm5 and rn3 genome, respectively. This bioinformatic analysis was followed by investigation of gene expression using a custom designed high-density oligonucleotide array containing all of these receptors and other selected genes of interest. This array enabled us to detect the specific expression of V1R and V2Rs which were previously identified solely based on computational prediction from gene sequence data, thereby establishing that these genes are indeed part of the vomeronasal system, especially the V2Rs. 168 V1Rs and 98 V2Rs were detected to be highly enriched in mouse vomeronasal organ (VNO, and 108 V1Rs and 87 V2Rs in rat VNO. We monitored the expression profile of mouse VR genes in other non-VNO tissues with the result that some VR genes were re-designated as VR-like genes based on their non-olfactory expression pattern. Temporal expression profiles for mouse VR genes were characterized and their patterns were classified, revealing the developmental dynamics of these so-called pheromone receptors. We found numerous patterns of temporal expression which indicate possible behavior-related functions. The uneven composition of VR genes in certain patterns suggests a functional differentiation between the two types of VR genes. We found the coherence between VR genes and transcription factors in terms of their temporal expression patterns. In situ hybridization experiments were performed to evaluate the cell number change over time for selected receptor genes.

  16. Neighboring Genes Show Correlated Evolution in Gene Expression

    Science.gov (United States)

    Ghanbarian, Avazeh T.; Hurst, Laurence D.

    2015-01-01

    When considering the evolution of a gene’s expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking. PMID:25743543

  17. Gene Expression Commons: an open platform for absolute gene expression profiling.

    Directory of Open Access Journals (Sweden)

    Jun Seita

    Full Text Available Gene expression profiling using microarrays has been limited to comparisons of gene expression between small numbers of samples within individual experiments. However, the unknown and variable sensitivities of each probeset have rendered the absolute expression of any given gene nearly impossible to estimate. We have overcome this limitation by using a very large number (>10,000 of varied microarray data as a common reference, so that statistical attributes of each probeset, such as the dynamic range and threshold between low and high expression, can be reliably discovered through meta-analysis. This strategy is implemented in a web-based platform named "Gene Expression Commons" (https://gexc.stanford.edu/ which contains data of 39 distinct highly purified mouse hematopoietic stem/progenitor/differentiated cell populations covering almost the entire hematopoietic system. Since the Gene Expression Commons is designed as an open platform, investigators can explore the expression level of any gene, search by expression patterns of interest, submit their own microarray data, and design their own working models representing biological relationship among samples.

  18. Face-selective regions differ in their ability to classify facial expressions.

    Science.gov (United States)

    Zhang, Hui; Japee, Shruti; Nolan, Rachel; Chu, Carlton; Liu, Ning; Ungerleider, Leslie G

    2016-04-15

    Recognition of facial expressions is crucial for effective social interactions. Yet, the extent to which the various face-selective regions in the human brain classify different facial expressions remains unclear. We used functional magnetic resonance imaging (fMRI) and support vector machine pattern classification analysis to determine how well face-selective brain regions are able to decode different categories of facial expression. Subjects participated in a slow event-related fMRI experiment in which they were shown 32 face pictures, portraying four different expressions: neutral, fearful, angry, and happy and belonging to eight different identities. Our results showed that only the amygdala and the posterior superior temporal sulcus (STS) were able to accurately discriminate between these expressions, albeit in different ways: the amygdala discriminated fearful faces from non-fearful faces, whereas STS discriminated neutral from emotional (fearful, angry and happy) faces. In contrast to these findings on the classification of emotional expression, only the fusiform face area (FFA) and anterior inferior temporal cortex (aIT) could discriminate among the various facial identities. Further, the amygdala and STS were better than FFA and aIT at classifying expression, while FFA and aIT were better than the amygdala and STS at classifying identity. Taken together, our findings indicate that the decoding of facial emotion and facial identity occurs in different neural substrates: the amygdala and STS for the former and FFA and aIT for the latter. Published by Elsevier Inc.

  19. Tumour gene expression predicts response to cetuximab in patients with KRAS wild-type metastatic colorectal cancer.

    Science.gov (United States)

    Baker, J B; Dutta, D; Watson, D; Maddala, T; Munneke, B M; Shak, S; Rowinsky, E K; Xu, L-A; Harbison, C T; Clark, E A; Mauro, D J; Khambata-Ford, S

    2011-02-01

    Although it is accepted that metastatic colorectal cancers (mCRCs) that carry activating mutations in KRAS are unresponsive to anti-epidermal growth factor receptor (EGFR) monoclonal antibodies, a significant fraction of KRAS wild-type (wt) mCRCs are also unresponsive to anti-EGFR therapy. Genes encoding EGFR ligands amphiregulin (AREG) and epiregulin (EREG) are promising gene expression-based markers but have not been incorporated into a test to dichotomise KRAS wt mCRC patients with respect to sensitivity to anti-EGFR treatment. We used RT-PCR to test 110 candidate gene expression markers in primary tumours from 144 KRAS wt mCRC patients who received monotherapy with the anti-EGFR antibody cetuximab. Results were correlated with multiple clinical endpoints: disease control, objective response, and progression-free survival (PFS). Expression of many of the tested candidate genes, including EREG and AREG, strongly associate with all clinical endpoints. Using multivariate analysis with two-layer five-fold cross-validation, we constructed a four-gene predictive classifier. Strikingly, patients below the classifier cutpoint had PFS and disease control rates similar to those of patients with KRAS mutant mCRC. Gene expression appears to identify KRAS wt mCRC patients who receive little benefit from cetuximab. It will be important to test this model in an independent validation study.

  20. Gene organization in rice revealed by full-length cDNA mapping and gene expression analysis through microarray.

    Directory of Open Access Journals (Sweden)

    Kouji Satoh

    Full Text Available Rice (Oryza sativa L. is a model organism for the functional genomics of monocotyledonous plants since the genome size is considerably smaller than those of other monocotyledonous plants. Although highly accurate genome sequences of indica and japonica rice are available, additional resources such as full-length complementary DNA (FL-cDNA sequences are also indispensable for comprehensive analyses of gene structure and function. We cross-referenced 28.5K individual loci in the rice genome defined by mapping of 578K FL-cDNA clones with the 56K loci predicted in the TIGR genome assembly. Based on the annotation status and the presence of corresponding cDNA clones, genes were classified into 23K annotated expressed (AE genes, 33K annotated non-expressed (ANE genes, and 5.5K non-annotated expressed (NAE genes. We developed a 60mer oligo-array for analysis of gene expression from each locus. Analysis of gene structures and expression levels revealed that the general features of gene structure and expression of NAE and ANE genes were considerably different from those of AE genes. The results also suggested that the cloning efficiency of rice FL-cDNA is associated with the transcription activity of the corresponding genetic locus, although other factors may also have an effect. Comparison of the coverage of FL-cDNA among gene families suggested that FL-cDNA from genes encoding rice- or eukaryote-specific domains, and those involved in regulatory functions were difficult to produce in bacterial cells. Collectively, these results indicate that rice genes can be divided into distinct groups based on transcription activity and gene structure, and that the coverage bias of FL-cDNA clones exists due to the incompatibility of certain eukaryotic genes in bacteria.

  1. Development of a blood-based gene expression algorithm for assessment of obstructive coronary artery disease in non-diabetic patients

    Directory of Open Access Journals (Sweden)

    Ellis Stephen G

    2011-03-01

    Full Text Available Abstract Background Alterations in gene expression in peripheral blood cells have been shown to be sensitive to the presence and extent of coronary artery disease (CAD. A non-invasive blood test that could reliably assess obstructive CAD likelihood would have diagnostic utility. Results Microarray analysis of RNA samples from a 195 patient Duke CATHGEN registry case:control cohort yielded 2,438 genes with significant CAD association (p RT-PCR analysis of these 113 genes in a PREDICT cohort of 640 non-diabetic subject samples was used for algorithm development. Gene expression correlations identified clusters of CAD classifier genes which were reduced to meta-genes using LASSO. The final classifier for assessment of obstructive CAD was derived by Ridge Regression and contained sex-specific age functions and 6 meta-gene terms, comprising 23 genes. This algorithm showed a cross-validated estimated AUC = 0.77 (95% CI 0.73-0.81 in ROC analysis. Conclusions We have developed a whole blood classifier based on gene expression, age and sex for the assessment of obstructive CAD in non-diabetic patients from a combination of microarray and RT-PCR data derived from studies of patients clinically indicated for invasive angiography. Clinical trial registration information PREDICT, Personalized Risk Evaluation and Diagnosis in the Coronary Tree, http://www.clinicaltrials.gov, NCT00500617

  2. Gene expression of panaxydol-treated human melanoma cells using radioactive cDNA microarrays

    International Nuclear Information System (INIS)

    Cho, Joong Youn; Yu, Su Jin; Soh, Jeong Won; Kim, Meyoung Kon

    2001-01-01

    Polyacetylenic alcohols derived from Panax ginseng have been studied to be an anticancer reagent previously. One of the Panax ginseng polyacetylenic alcohols, i.e., panaxydol, has been studied to possess an antiproliferative effect on human melanoma cell line (SK-MEL-1). In ths study, radioactive cDNA microarrays enabled an efficient approach to analyze the pattern of gene expression (3.194 genes in a total) simultaneously. The bioinformatics selection of human cDNAs, which is specifically designed for immunology, apoptosis and signal transduction, were arrayed on nylon membranes. Using with 33 P labeled probes, this method provided highly sensitive gene expression profiles of our interest including apoptosis, cell proliferation, cell cycle, and signal transduction. Gene expression profiles were also classified into several categories in accordance with the duration of panaxydol treatment. Consequently, the gene profiles of our interest were significantly up (199 genes, > 2.0 of Z-ratio) or down-(196 genes, < 2.0 of Z-ratio) regulated in panaxydol-treated human melanoma cells

  3. Gene expression of panaxydol-treated human melanoma cells using radioactive cDNA microarrays

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Joong Youn; Yu, Su Jin; Soh, Jeong Won; Kim, Meyoung Kon [College of Medicine, Korea Univ., Seoul (Korea, Republic of)

    2001-07-01

    Polyacetylenic alcohols derived from Panax ginseng have been studied to be an anticancer reagent previously. One of the Panax ginseng polyacetylenic alcohols, i.e., panaxydol, has been studied to possess an antiproliferative effect on human melanoma cell line (SK-MEL-1). In ths study, radioactive cDNA microarrays enabled an efficient approach to analyze the pattern of gene expression (3.194 genes in a total) simultaneously. The bioinformatics selection of human cDNAs, which is specifically designed for immunology, apoptosis and signal transduction, were arrayed on nylon membranes. Using with {sup 33}P labeled probes, this method provided highly sensitive gene expression profiles of our interest including apoptosis, cell proliferation, cell cycle, and signal transduction. Gene expression profiles were also classified into several categories in accordance with the duration of panaxydol treatment. Consequently, the gene profiles of our interest were significantly up (199 genes, > 2.0 of Z-ratio) or down-(196 genes, < 2.0 of Z-ratio) regulated in panaxydol-treated human melanoma cells.

  4. Classifying chemical mode of action using gene networks and machine learning: a case study with the herbicide linuron.

    Science.gov (United States)

    Ornostay, Anna; Cowie, Andrew M; Hindle, Matthew; Baker, Christopher J O; Martyniuk, Christopher J

    2013-12-01

    The herbicide linuron (LIN) is an endocrine disruptor with an anti-androgenic mode of action. The objectives of this study were to (1) improve knowledge of androgen and anti-androgen signaling in the teleostean ovary and to (2) assess the ability of gene networks and machine learning to classify LIN as an anti-androgen using transcriptomic data. Ovarian explants from vitellogenic fathead minnows (FHMs) were exposed to three concentrations of either 5α-dihydrotestosterone (DHT), flutamide (FLUT), or LIN for 12h. Ovaries exposed to DHT showed a significant increase in 17β-estradiol (E2) production while FLUT and LIN had no effect on E2. To improve understanding of androgen receptor signaling in the ovary, a reciprocal gene expression network was constructed for DHT and FLUT using pathway analysis and these data suggested that steroid metabolism, translation, and DNA replication are processes regulated through AR signaling in the ovary. Sub-network enrichment analysis revealed that FLUT and LIN shared more regulated gene networks in common compared to DHT. Using transcriptomic datasets from different fish species, machine learning algorithms classified LIN successfully with other anti-androgens. This study advances knowledge regarding molecular signaling cascades in the ovary that are responsive to androgens and anti-androgens and provides proof of concept that gene network analysis and machine learning can classify priority chemicals using experimental transcriptomic data collected from different fish species. © 2013.

  5. Hormonal modulation of breast cancer gene expression: implications for intrinsic subtyping in pre-menopausal women

    OpenAIRE

    Sarah M Bernhardt; Pallave Dasari; David Walsh; Amanda R Townsend; Amanda R Townsend; Timothy J Price; Timothy J Price; Wendy V Ingman

    2016-01-01

    Clinics are increasingly adopting gene expression profiling to diagnose breast cancer subtype, providing an intrinsic, molecular portrait of the tumour. For example, the PAM50-based Prosigna test quantifies expression of 50 key genes to classify breast cancer subtype, and this method of classification has been demonstrated to be superior over traditional immunohistochemical methods that detect proteins, to predict risk of disease recurrence. However, these tests were largely developed and val...

  6. Imaging gene expression in gene therapy

    International Nuclear Information System (INIS)

    Wiebe, Leonard I.

    1997-01-01

    Full text. Gene therapy can be used to introduce new genes, or to supplement the function of indigenous genes. At the present time, however, there is non-invasive test to demonstrate efficacy of the gene transfer and expression processes. It has been postulated that scintigraphic imaging can offer unique information on both the site at which the transferred gene is expressed, and the degree of expression, both of which are critical issue for safety and clinical efficacy. Many current studies are based on 'suicide gene therapy' of cancer. Cells modified to express these genes commit metabolic suicide in the presence of an enzyme encoded by the transferred gene and a specifically-convertible pro drug. Pro drug metabolism can lead to selective metabolic trapping, required for scintigraphy. Herpes simplex virus type-1 thymidine kinase (H S V-1 t k + ) has been use for 'suicide' in vivo tumor gene therapy. It has been proposed that radiolabelled nucleosides can be used as radiopharmaceuticals to detect H S V-1 t k + gene expression where the H S V-1 t k + gene serves a reporter or therapeutic function. Animal gene therapy models have been studied using purine-([ 18 F]F H P G; [ 18 F]-A C V), and pyrimidine- ([ 123 / 131 I]I V R F U; [ 124 / 131I ]) antiviral nucleosides. Principles of gene therapy and gene therapy imaging will be reviewed and experimental data for [ 123 / 131I ]I V R F U imaging with the H S V-1 t k + reporter gene will be presented

  7. Determining Physical Mechanisms of Gene Expression Regulation from Single Cell Gene Expression Data

    OpenAIRE

    Ezer, Daphne; Moignard, Victoria; G?ttgens, Berthold; Adryan, Boris

    2016-01-01

    Many genes are expressed in bursts, which can contribute to cell-to-cell heterogeneity. It is now possible to measure this heterogeneity with high throughput single cell gene expression assays (single cell qPCR and RNA-seq). These experimental approaches generate gene expression distributions which can be used to estimate the kinetic parameters of gene expression bursting, namely the rate that genes turn on, the rate that genes turn off, and the rate of transcription. We construct a complete ...

  8. Expression profiling of hypothetical genes in Desulfovibrio vulgaris leads to improved functional annotation

    Energy Technology Data Exchange (ETDEWEB)

    Elias, Dwayne A.; Mukhopadhyay, Aindrila; Joachimiak, Marcin P.; Drury, Elliott C.; Redding, Alyssa M.; Yen, Huei-Che B.; Fields, Matthew W.; Hazen, Terry C.; Arkin, Adam P.; Keasling, Jay D.; Wall, Judy D.

    2008-10-27

    Hypothetical and conserved hypothetical genes account for>30percent of sequenced bacterial genomes. For the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough, 347 of the 3634 genes were annotated as conserved hypothetical (9.5percent) along with 887 hypothetical genes (24.4percent). Given the large fraction of the genome, it is plausible that some of these genes serve critical cellular roles. The study goals were to determine which genes were expressed and provide a more functionally based annotation. To accomplish this, expression profiles of 1234 hypothetical and conserved genes were used from transcriptomic datasets of 11 environmental stresses, complemented with shotgun LC-MS/MS and AMT tag proteomic data. Genes were divided into putatively polycistronic operons and those predicted to be monocistronic, then classified by basal expression levels and grouped according to changes in expression for one or multiple stresses. 1212 of these genes were transcribed with 786 producing detectable proteins. There was no evidence for expression of 17 predicted genes. Except for the latter, monocistronic gene annotation was expanded using the above criteria along with matching Clusters of Orthologous Groups. Polycistronic genes were annotated in the same manner with inferences from their proximity to more confidently annotated genes. Two targeted deletion mutants were used as test cases to determine the relevance of the inferred functional annotations.

  9. Imaging gene expression in gene therapy

    Energy Technology Data Exchange (ETDEWEB)

    Wiebe, Leonard I. [Alberta Univ., Edmonton (Canada). Noujaim Institute for Pharmaceutical Oncology Research

    1997-12-31

    Full text. Gene therapy can be used to introduce new genes, or to supplement the function of indigenous genes. At the present time, however, there is non-invasive test to demonstrate efficacy of the gene transfer and expression processes. It has been postulated that scintigraphic imaging can offer unique information on both the site at which the transferred gene is expressed, and the degree of expression, both of which are critical issue for safety and clinical efficacy. Many current studies are based on `suicide gene therapy` of cancer. Cells modified to express these genes commit metabolic suicide in the presence of an enzyme encoded by the transferred gene and a specifically-convertible pro drug. Pro drug metabolism can lead to selective metabolic trapping, required for scintigraphy. Herpes simplex virus type-1 thymidine kinase (H S V-1 t k{sup +}) has been use for `suicide` in vivo tumor gene therapy. It has been proposed that radiolabelled nucleosides can be used as radiopharmaceuticals to detect H S V-1 t k{sup +} gene expression where the H S V-1 t k{sup +} gene serves a reporter or therapeutic function. Animal gene therapy models have been studied using purine-([{sup 18} F]F H P G; [{sup 18} F]-A C V), and pyrimidine- ([{sup 123}/{sup 131} I]I V R F U; [{sup 124}/{sup 131I}]) antiviral nucleosides. Principles of gene therapy and gene therapy imaging will be reviewed and experimental data for [{sup 123}/{sup 131I}]I V R F U imaging with the H S V-1 t k{sup +} reporter gene will be presented

  10. Radioactive cDNA microarrys for gene expression profiles in antidepressant therapy

    International Nuclear Information System (INIS)

    Lee, M. S.; Han, B. J.; Cha, J. H.; Ryu, Y. M.; Shin, E. K.; Park, J. H.; Park, Y. H.; Kim, M. K.

    2002-01-01

    Using radioactive cDNA microarray, we investigated a pattern of gene regulation under treatment of antidepressant on patients of depressive disoder. Basic microarray technology was performed as previously described in our research. The bioinformatic selection of human cDNAs, which is specifically designed for psychiatry, neurology, and signal transduction, were arrayed on nylon membranes. Using with 33P-labeled probes, this method provided highly sensitive gene expression profiles of our interest including brain receptors, drug metabolism, and cellular signalings. Gene expression profiles were also classified into several categories in accordance with the gene-regulation of antidepressant. The gene profiles of our interest were significantly up- (16 genes, >2.0 of Z-ratio) or down- (24 genes, <-2.0 of Z ratio) regulated when compared the good responsed group with the bad-responsed one. Consequently, we demonstrated that radioactive human cDNA microarray is highly likely to be an efficient technology for evaluating the gene regulation of antidepressants, such as selective serotonin-reuptake inhibitors (SSRIs), by using high-throughput biotechnology

  11. Classification across gene expression microarray studies

    Directory of Open Access Journals (Sweden)

    Kuner Ruprecht

    2009-12-01

    Full Text Available Abstract Background The increasing number of gene expression microarray studies represents an important resource in biomedical research. As a result, gene expression based diagnosis has entered clinical practice for patient stratification in breast cancer. However, the integration and combined analysis of microarray studies remains still a challenge. We assessed the potential benefit of data integration on the classification accuracy and systematically evaluated the generalization performance of selected methods on four breast cancer studies comprising almost 1000 independent samples. To this end, we introduced an evaluation framework which aims to establish good statistical practice and a graphical way to monitor differences. The classification goal was to correctly predict estrogen receptor status (negative/positive and histological grade (low/high of each tumor sample in an independent study which was not used for the training. For the classification we chose support vector machines (SVM, predictive analysis of microarrays (PAM, random forest (RF and k-top scoring pairs (kTSP. Guided by considerations relevant for classification across studies we developed a generalization of kTSP which we evaluated in addition. Our derived version (DV aims to improve the robustness of the intrinsic invariance of kTSP with respect to technologies and preprocessing. Results For each individual study the generalization error was benchmarked via complete cross-validation and was found to be similar for all classification methods. The misclassification rates were substantially higher in classification across studies, when each single study was used as an independent test set while all remaining studies were combined for the training of the classifier. However, with increasing number of independent microarray studies used in the training, the overall classification performance improved. DV performed better than the average and showed slightly less variance. In

  12. Classification of gene expression data: A hubness-aware semi-supervised approach.

    Science.gov (United States)

    Buza, Krisztian

    2016-04-01

    Classification of gene expression data is the common denominator of various biomedical recognition tasks. However, obtaining class labels for large training samples may be difficult or even impossible in many cases. Therefore, semi-supervised classification techniques are required as semi-supervised classifiers take advantage of unlabeled data. Gene expression data is high-dimensional which gives rise to the phenomena known under the umbrella of the curse of dimensionality, one of its recently explored aspects being the presence of hubs or hubness for short. Therefore, hubness-aware classifiers have been developed recently, such as Naive Hubness-Bayesian k-Nearest Neighbor (NHBNN). In this paper, we propose a semi-supervised extension of NHBNN which follows the self-training schema. As one of the core components of self-training is the certainty score, we propose a new hubness-aware certainty score. We performed experiments on publicly available gene expression data. These experiments show that the proposed classifier outperforms its competitors. We investigated the impact of each of the components (classification algorithm, semi-supervised technique, hubness-aware certainty score) separately and showed that each of these components are relevant to the performance of the proposed approach. Our results imply that our approach may increase classification accuracy and reduce computational costs (i.e., runtime). Based on the promising results presented in the paper, we envision that hubness-aware techniques will be used in various other biomedical machine learning tasks. In order to accelerate this process, we made an implementation of hubness-aware machine learning techniques publicly available in the PyHubs software package (http://www.biointelligence.hu/pyhubs) implemented in Python, one of the most popular programming languages of data science. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  13. Selective modes determine evolutionary rates, gene compactness and expression patterns in Brassica.

    Science.gov (United States)

    Guo, Yue; Liu, Jing; Zhang, Jiefu; Liu, Shengyi; Du, Jianchang

    2017-07-01

    It has been well documented that most nuclear protein-coding genes in organisms can be classified into two categories: positively selected genes (PSGs) and negatively selected genes (NSGs). The characteristics and evolutionary fates of different types of genes, however, have been poorly understood. In this study, the rates of nonsynonymous substitution (K a ) and the rates of synonymous substitution (K s ) were investigated by comparing the orthologs between the two sequenced Brassica species, Brassica rapa and Brassica oleracea, and the evolutionary rates, gene structures, expression patterns, and codon bias were compared between PSGs and NSGs. The resulting data show that PSGs have higher protein evolutionary rates, lower synonymous substitution rates, shorter gene length, fewer exons, higher functional specificity, lower expression level, higher tissue-specific expression and stronger codon bias than NSGs. Although the quantities and values are different, the relative features of PSGs and NSGs have been largely verified in the model species Arabidopsis. These data suggest that PSGs and NSGs differ not only under selective pressure (K a /K s ), but also in their evolutionary, structural and functional properties, indicating that selective modes may serve as a determinant factor for measuring evolutionary rates, gene compactness and expression patterns in Brassica. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

  14. Sparse representation of multi parametric DCE-MRI features using K-SVD for classifying gene expression based breast cancer recurrence risk

    Science.gov (United States)

    Mahrooghy, Majid; Ashraf, Ahmed B.; Daye, Dania; Mies, Carolyn; Rosen, Mark; Feldman, Michael; Kontos, Despina

    2014-03-01

    We evaluate the prognostic value of sparse representation-based features by applying the K-SVD algorithm on multiparametric kinetic, textural, and morphologic features in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). K-SVD is an iterative dimensionality reduction method that optimally reduces the initial feature space by updating the dictionary columns jointly with the sparse representation coefficients. Therefore, by using K-SVD, we not only provide sparse representation of the features and condense the information in a few coefficients but also we reduce the dimensionality. The extracted K-SVD features are evaluated by a machine learning algorithm including a logistic regression classifier for the task of classifying high versus low breast cancer recurrence risk as determined by a validated gene expression assay. The features are evaluated using ROC curve analysis and leave one-out cross validation for different sparse representation and dimensionality reduction numbers. Optimal sparse representation is obtained when the number of dictionary elements is 4 (K=4) and maximum non-zero coefficients is 2 (L=2). We compare K-SVD with ANOVA based feature selection for the same prognostic features. The ROC results show that the AUC of the K-SVD based (K=4, L=2), the ANOVA based, and the original features (i.e., no dimensionality reduction) are 0.78, 0.71. and 0.68, respectively. From the results, it can be inferred that by using sparse representation of the originally extracted multi-parametric, high-dimensional data, we can condense the information on a few coefficients with the highest predictive value. In addition, the dimensionality reduction introduced by K-SVD can prevent models from over-fitting.

  15. Gene expression patterns in blood leukocytes discriminate patients with acute infections

    Science.gov (United States)

    Allman, Windy; Chung, Wendy; Mejias, Asuncion; Ardura, Monica; Glaser, Casey; Wittkowski, Knut M.; Piqueras, Bernard; Banchereau, Jacques; Palucka, A. Karolina; Chaussabel, Damien

    2007-01-01

    Each infectious agent represents a unique combination of pathogen-associated molecular patterns that interact with specific pattern-recognition receptors expressed on immune cells. Therefore, we surmised that the blood immune cells of individuals with different infections might bear discriminative transcriptional signatures. Gene expression profiles were obtained for 131 peripheral blood samples from pediatric patients with acute infections caused by influenza A virus, Gram-negative (Escherichia coli) or Gram-positive (Staphylococcus aureus and Streptococcus pneumoniae) bacteria. Thirty-five genes were identified that best discriminate patients with influenza A virus infection from patients with either E coli or S pneumoniae infection. These genes classified with 95% accuracy (35 of 37 samples) an independent set of patients with either influenza A, E coli, or S pneumoniae infection. A different signature discriminated patients with E coli versus S aureus infections with 85% accuracy (34 of 40). Furthermore, distinctive gene expression patterns were observed in patients presenting with respiratory infections of different etiologies. Thus, microarray analyses of patient peripheral blood leukocytes might assist in the differential diagnosis of infectious diseases. PMID:17105821

  16. MO-DE-207B-03: Improved Cancer Classification Using Patient-Specific Biological Pathway Information Via Gene Expression Data

    Energy Technology Data Exchange (ETDEWEB)

    Young, M; Craft, D [Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States)

    2016-06-15

    Purpose: To develop an efficient, pathway-based classification system using network biology statistics to assist in patient-specific response predictions to radiation and drug therapies across multiple cancer types. Methods: We developed PICS (Pathway Informed Classification System), a novel two-step cancer classification algorithm. In PICS, a matrix m of mRNA expression values for a patient cohort is collapsed into a matrix p of biological pathways. The entries of p, which we term pathway scores, are obtained from either principal component analysis (PCA), normal tissue centroid (NTC), or gene expression deviation (GED). The pathway score matrix is clustered using both k-means and hierarchical clustering, and a clustering is judged by how well it groups patients into distinct survival classes. The most effective pathway scoring/clustering combination, per clustering p-value, thus generates various ‘signatures’ for conventional and functional cancer classification. Results: PICS successfully regularized large dimension gene data, separated normal and cancerous tissues, and clustered a large patient cohort spanning six cancer types. Furthermore, PICS clustered patient cohorts into distinct, statistically-significant survival groups. For a suboptimally-debulked ovarian cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00127) showed significant improvement over that of a prior gene expression-classified study (p = .0179). For a pancreatic cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00141) showed significant improvement over that of a prior gene expression-classified study (p = .04). Pathway-based classification confirmed biomarkers for the pyrimidine, WNT-signaling, glycerophosphoglycerol, beta-alanine, and panthothenic acid pathways for ovarian cancer. Despite its robust nature, PICS requires significantly less run time than current pathway scoring methods. Conclusion: This work validates the PICS method to improve

  17. Differential hexosamine biosynthetic pathway gene expression with type 2 diabetes

    Directory of Open Access Journals (Sweden)

    Megan Coomer

    2014-01-01

    Full Text Available The hexosamine biosynthetic pathway (HBP culminates in the attachment of O-linked β-N-acetylglucosamine (O-GlcNAc onto serine/threonine residues of target proteins. The HBP is regulated by several modulators, i.e. O-linked β-N-acetylglucosaminyl transferase (OGT and β-N-acetylglucosaminidase (OGA catalyze the addition and removal of O-GlcNAc moieties, respectively; while flux is controlled by the rate-limiting enzyme glutamine:fructose-6-phosphate amidotransferase (GFPT, transcribed by two genes, GFPT1 and GFPT2. Since increased HBP flux is glucose-responsive and linked to insulin resistance/type 2 diabetes onset, we hypothesized that diabetic individuals exhibit differential expression of HBP regulatory genes. Volunteers (n = 60; n = 20 Mixed Ancestry, n = 40 Caucasian were recruited from Stellenbosch and Paarl (Western Cape, South Africa and classified as control, pre- or diabetic according to fasting plasma glucose and HbA1c levels, respectively. RNA was purified from leukocytes isolated from collected blood samples and OGT, OGA, GFPT1 and GFPT2 expressions determined by quantitative real-time PCR. The data reveal lower OGA expression in diabetic individuals (P < 0.01, while pre- and diabetic subjects displayed attenuated OGT expression vs. controls (P < 0.01 and P < 0.001, respectively. Moreover, GFPT2 expression decreased in pre- and diabetic Caucasians vs. controls (P < 0.05 and P < 0.01, respectively. We also found ethnic differences, i.e. Mixed Ancestry individuals exhibited a 2.4-fold increase in GFPT2 expression vs. Caucasians, despite diagnosis (P < 0.01. Gene expression of HBP regulators differs between diabetic and non-diabetic individuals, together with distinct ethnic-specific gene profiles. Thus differential HBP gene regulation may offer diagnostic utility and provide candidate susceptibility genes for different ethnic groupings.

  18. A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data of Glioma

    KAUST Repository

    Abusamra, Heba

    2013-11-01

    Microarray gene expression data gained great importance in recent years due to its role in disease diagnoses and prognoses which help to choose the appropriate treatment plan for patients. This technology has shifted a new era in molecular classification. Interpreting gene expression data remains a difficult problem and an active research area due to their native nature of “high dimensional low sample size”. Such problems pose great challenges to existing classification methods. Thus, effective feature selection techniques are often needed in this case to aid to correctly classify different tumor types and consequently lead to a better understanding of genetic signatures as well as improve treatment strategies. This paper aims on a comparative study of state-of-the- art feature selection methods, classification methods, and the combination of them, based on gene expression data. We compared the efficiency of three different classification methods including: support vector machines, k-nearest neighbor and random forest, and eight different feature selection methods, including: information gain, twoing rule, sum minority, max minority, gini index, sum of variances, t-statistics, and one-dimension support vector machine. Five-fold cross validation was used to evaluate the classification performance. Two publicly available gene expression data sets of glioma were used in the experiments. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in different feature selection methods is investigated and the most frequent features selected in each fold among all methods for both datasets are evaluated.

  19. A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data of Glioma

    KAUST Repository

    Abusamra, Heba

    2013-01-01

    Microarray gene expression data gained great importance in recent years due to its role in disease diagnoses and prognoses which help to choose the appropriate treatment plan for patients. This technology has shifted a new era in molecular classification. Interpreting gene expression data remains a difficult problem and an active research area due to their native nature of “high dimensional low sample size”. Such problems pose great challenges to existing classification methods. Thus, effective feature selection techniques are often needed in this case to aid to correctly classify different tumor types and consequently lead to a better understanding of genetic signatures as well as improve treatment strategies. This paper aims on a comparative study of state-of-the- art feature selection methods, classification methods, and the combination of them, based on gene expression data. We compared the efficiency of three different classification methods including: support vector machines, k-nearest neighbor and random forest, and eight different feature selection methods, including: information gain, twoing rule, sum minority, max minority, gini index, sum of variances, t-statistics, and one-dimension support vector machine. Five-fold cross validation was used to evaluate the classification performance. Two publicly available gene expression data sets of glioma were used in the experiments. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in different feature selection methods is investigated and the most frequent features selected in each fold among all methods for both datasets are evaluated.

  20. Differential gene expression in patients with subsyndromal symptomatic depression and major depressive disorder.

    Science.gov (United States)

    Yang, Chengqing; Hu, Guoqin; Li, Zezhi; Wang, Qingzhong; Wang, Xuemei; Yuan, Chengmei; Wang, Zuowei; Hong, Wu; Lu, Weihong; Cao, Lan; Chen, Jun; Wang, Yong; Yu, Shunying; Zhou, Yimin; Yi, Zhenghui; Fang, Yiru

    2017-01-01

    Subsyndromal symptomatic depression (SSD) is a subtype of subthreshold depressive and can lead to significant psychosocial functional impairment. Although the pathogenesis of major depressive disorder (MDD) and SSD still remains poorly understood, a set of studies have found that many same genetic factors play important roles in the etiology of these two disorders. Nowadays, the differential gene expression between MDD and SSD is still unknown. In our previous study, we compared the expression profile and made the classification with the leukocytes by using whole-genome cRNA microarrays among drug-free first-episode subjects with SSD, MDD and matched healthy controls (8 subjects in each group), and finally determined 48 gene expression signatures. Based on these findings, we further clarify whether these genes mRNA was different expressed in peripheral blood in patients with SSD, MDD and healthy controls (60 subjects respectively). With the help of the quantitative real-time reverse transcription-polymerase chain reaction (RT-qPCR), we gained gene relative expression levels among the three groups. We found that there are three of the forty eight co-regulated genes had differential expression in peripheral blood among the three groups, which are CD84, STRN, CTNS gene (F = 3.528, p = 0.034; F = 3.382, p = 0.039; F = 3.801, p = 0.026, respectively) while there were no significant differences for other genes. CD84, STRN, CTNS gene may have significant value for performing diagnostic functions and classifying SSD, MDD and healthy controls.

  1. Construction and use of gene expression covariation matrix

    Directory of Open Access Journals (Sweden)

    Bellis Michel

    2009-07-01

    Full Text Available Abstract Background One essential step in the massive analysis of transcriptomic profiles is the calculation of the correlation coefficient, a value used to select pairs of genes with similar or inverse transcriptional profiles across a large fraction of the biological conditions examined. Until now, the choice between the two available methods for calculating the coefficient has been dictated mainly by technological considerations. Specifically, in analyses based on double-channel techniques, researchers have been required to use covariation correlation, i.e. the correlation between gene expression changes measured between several pairs of biological conditions, expressed for example as fold-change. In contrast, in analyses of single-channel techniques scientists have been restricted to the use of coexpression correlation, i.e. correlation between gene expression levels. To our knowledge, nobody has ever examined the possible benefits of using covariation instead of coexpression in massive analyses of single channel microarray results. Results We describe here how single-channel techniques can be treated like double-channel techniques and used to generate both gene expression changes and covariation measures. We also present a new method that allows the calculation of both positive and negative correlation coefficients between genes. First, we perform systematic comparisons between two given biological conditions and classify, for each comparison, genes as increased (I, decreased (D, or not changed (N. As a result, the original series of n gene expression level measures assigned to each gene is replaced by an ordered string of n(n-1/2 symbols, e.g. IDDNNIDID....DNNNNNNID, with the length of the string corresponding to the number of comparisons. In a second step, positive and negative covariation matrices (CVM are constructed by calculating statistically significant positive or negative correlation scores for any pair of genes by comparing their

  2. Evolution and expression analysis of the grape (Vitis vinifera L.) WRKY gene family.

    Science.gov (United States)

    Guo, Chunlei; Guo, Rongrong; Xu, Xiaozhao; Gao, Min; Li, Xiaoqin; Song, Junyang; Zheng, Yi; Wang, Xiping

    2014-04-01

    WRKY proteins comprise a large family of transcription factors that play important roles in plant defence regulatory networks, including responses to various biotic and abiotic stresses. To date, no large-scale study of WRKY genes has been undertaken in grape (Vitis vinifera L.). In this study, a total of 59 putative grape WRKY genes (VvWRKY) were identified and renamed on the basis of their respective chromosome distribution. A multiple sequence alignment analysis using all predicted grape WRKY genes coding sequences, together with those from Arabidopsis thaliana and tomato (Solanum lycopersicum), indicated that the 59 VvWRKY genes can be classified into three main groups (I-III). An evaluation of the duplication events suggested that several WRKY genes arose before the divergence of the grape and Arabidopsis lineages. Moreover, expression profiles derived from semiquantitative PCR and real-time quantitative PCR analyses showed distinct expression patterns in various tissues and in response to different treatments. Four VvWRKY genes showed a significantly higher expression in roots or leaves, 55 responded to varying degrees to at least one abiotic stress treatment, and the expression of 38 were altered following powdery mildew (Erysiphe necator) infection. Most VvWRKY genes were downregulated in response to abscisic acid or salicylic acid treatments, while the expression of a subset was upregulated by methyl jasmonate or ethylene treatments.

  3. Co-expression network analysis of duplicate genes in maize (Zea mays L.) reveals no subgenome bias.

    Science.gov (United States)

    Li, Lin; Briskine, Roman; Schaefer, Robert; Schnable, Patrick S; Myers, Chad L; Flagel, Lex E; Springer, Nathan M; Muehlbauer, Gary J

    2016-11-04

    Gene duplication is prevalent in many species and can result in coding and regulatory divergence. Gene duplications can be classified as whole genome duplication (WGD), tandem and inserted (non-syntenic). In maize, WGD resulted in the subgenomes maize1 and maize2, of which maize1 is considered the dominant subgenome. However, the landscape of co-expression network divergence of duplicate genes in maize is still largely uncharacterized. To address the consequence of gene duplication on co-expression network divergence, we developed a gene co-expression network from RNA-seq data derived from 64 different tissues/stages of the maize reference inbred-B73. WGD, tandem and inserted gene duplications exhibited distinct regulatory divergence. Inserted duplicate genes were more likely to be singletons in the co-expression networks, while WGD duplicate genes were likely to be co-expressed with other genes. Tandem duplicate genes were enriched in the co-expression pattern where co-expressed genes were nearly identical for the duplicates in the network. Older gene duplications exhibit more extensive co-expression variation than younger duplications. Overall, non-syntenic genes primarily from inserted duplications show more co-expression divergence. Also, such enlarged co-expression divergence is significantly related to duplication age. Moreover, subgenome dominance was not observed in the co-expression networks - maize1 and maize2 exhibit similar levels of intra subgenome correlations. Intriguingly, the level of inter subgenome co-expression was similar to the level of intra subgenome correlations, and genes from specific subgenomes were not likely to be the enriched in co-expression network modules and the hub genes were not predominantly from any specific subgenomes in maize. Our work provides a comprehensive analysis of maize co-expression network divergence for three different types of gene duplications and identifies potential relationships between duplication types

  4. Stochastic biological response to radiation. Comprehensive analysis of gene expression

    International Nuclear Information System (INIS)

    Inoue, Tohru; Hirabayashi, Yoko

    2012-01-01

    Authors explain that the radiation effect on biological system is stochastic along the law of physics, differing from chemical effect, using instances of Cs-137 gamma-ray (GR) and benzene (BZ) exposures to mice and of resultant comprehensive analyses of gene expression. Single GR irradiation is done with Gamma Cell 40 (CSR) to C57BL/6 or C3H/He mouse at 0, 0.6 and 3 Gy. BE is given orally at 150 mg/kg/day for 5 days x 2 weeks. Bone marrow cells are sampled 1 month after the exposure. Comprehensive gene expression is analyzed by Gene Chip Mouse Genome 430 2.0 Array (Affymetrix) and data are processed by programs like case normalization, statistics, network generation, functional analysis etc. GR irradiation brings about changes of gene expression, which are classifiable in common genes variable commonly on the dose change and stochastic genes variable stochastically within each dose: e.g., with Welch-t-test, significant differences are between 0/3 Gy (dose-specific difference, 455 pbs (probe set), in stochastic 2113 pbs), 0/0.6 Gy (267 in 1284 pbs) and 0.6/3 Gy (532 pbs); and with one-way analysis of variation (ANOVA) and hierarchial/dendrographic analyses, 520 pbs are shown to involve the dose-dependent 226 and dose-specific 294 pbs. It is also shown that at 3 Gy, expression of common genes are rather suppressed, including those related to the proliferation/apoptosis of B/T cells, and of stochastic genes, related to cell division/signaling. Ven diagram of the common genes of above 520 pbs, stochastic 2113 pbs at 3 Gy and 1284 pbs at 0.6 Gy shows the overlapping genes 29, 2 and 4, respectively, indicating only 35 pbs are overlapping in total. Network analysis of changes by GR shows the rather high expression of genes around hub of cAMP response element binding protein (CREB) at 0.6 Gy, and rather variable expression around CREB hub/suppressed expression of kinesin hub at 3 Gy; in the network by BZ exposure, unchanged or low expression around p53 hub and suppression

  5. Differentially expressed genes of Coptotermes formosanus (Isoptera: Rhinotermitidae) challenged by chemical insecticides.

    Science.gov (United States)

    Zhang, Yi; Zhao, Yuanyuan; Qiu, Xuehong; Han, Richou

    2013-08-01

    Coptotermes formosanus Shiraki (Isoptera: Rhinotermitidae) termites are harmful social insects to wood constructions. The current control methods heavily depend on the chemical insecticides with increasing resistance. Analysis of the differentially expressed genes mediated by chemical insecticides will contribute to the understanding of the termite resistance to chemicals and to the establishment of alternative control measures. In the present article, a full-length cDNA library was constructed from the termites induced by a mixture of commonly used insecticides (0.01% sulfluramid and 0.01% triflumuron) for 24 h, by using the RNA ligase-mediated Rapid Amplification cDNA End method. Fifty-eight differentially expressed clones were obtained by polymerase chain reaction and confirmed by dot-blot hybridization. Forty-six known sequences were obtained, which clustered into 33 unique sequences grouped in 6 contigs and 27 singlets. Sixty-seven percent (22) of the sequences had counterpart genes from other organisms, whereas 33% (11) were undescribed. A Gene Ontology analysis classified 33 unique sequences into different functional categories. In general, most of the differential expression genes were involved in binding and catalytic activity.

  6. Gene co-expression networks and profiles reveal potential biomarkers of boar taint in pigs

    DEFF Research Database (Denmark)

    Drag, Markus; Skinkyté-Juskiené, R.; Do, Duy Ngoc

    synthesis. In testis, >80 DE genes were functionally classified by the PANTHER tool to “Gonadotropin releasing hormone receptor” and “Wnt signaling” pathways which play a role in reproductive maturation and proliferation of spermatogonia, respectively. WGCNA was used to build co-expression modules...

  7. Gently does it: Humans outperform a software classifier in recognizing subtle, nonstereotypical facial expressions.

    Science.gov (United States)

    Yitzhak, Neta; Giladi, Nir; Gurevich, Tanya; Messinger, Daniel S; Prince, Emily B; Martin, Katherine; Aviezer, Hillel

    2017-12-01

    According to dominant theories of affect, humans innately and universally express a set of emotions using specific configurations of prototypical facial activity. Accordingly, thousands of studies have tested emotion recognition using sets of highly intense and stereotypical facial expressions, yet their incidence in real life is virtually unknown. In fact, a commonplace experience is that emotions are expressed in subtle and nonprototypical forms. Such facial expressions are at the focus of the current study. In Experiment 1, we present the development and validation of a novel stimulus set consisting of dynamic and subtle emotional facial displays conveyed without constraining expressers to using prototypical configurations. Although these subtle expressions were more challenging to recognize than prototypical dynamic expressions, they were still well recognized by human raters, and perhaps most importantly, they were rated as more ecological and naturalistic than the prototypical expressions. In Experiment 2, we examined the characteristics of subtle versus prototypical expressions by subjecting them to a software classifier, which used prototypical basic emotion criteria. Although the software was highly successful at classifying prototypical expressions, it performed very poorly at classifying the subtle expressions. Further validation was obtained from human expert face coders: Subtle stimuli did not contain many of the key facial movements present in prototypical expressions. Together, these findings suggest that emotions may be successfully conveyed to human viewers using subtle nonprototypical expressions. Although classic prototypical facial expressions are well recognized, they appear less naturalistic and may not capture the richness of everyday emotional communication. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  8. Gene Structures, Classification, and Expression Models of the DREB Transcription Factor Subfamily in Populus trichocarpa

    Directory of Open Access Journals (Sweden)

    Yunlin Chen

    2013-01-01

    Full Text Available We identified 75 dehydration-responsive element-binding (DREB protein genes in Populus trichocarpa. We analyzed gene structures, phylogenies, domain duplications, genome localizations, and expression profiles. The phylogenic construction suggests that the PtrDREB gene subfamily can be classified broadly into six subtypes (DREB A-1 to A-6 in Populus. The chromosomal localizations of the PtrDREB genes indicated 18 segmental duplication events involving 36 genes and six redundant PtrDREB genes were involved in tandem duplication events. There were fewer introns in the PtrDREB subfamily. The motif composition of PtrDREB was highly conserved in the same subtype. We investigated expression profiles of this gene subfamily from different tissues and/or developmental stages. Sixteen genes present in the digital expression analysis had high levels of transcript accumulation. The microarray results suggest that 18 genes were upregulated. We further examined the stress responsiveness of 15 genes by qRT-PCR. A digital northern analysis showed that the PtrDREB17, 18, and 32 genes were highly induced in leaves under cold stress, and the same expression trends were shown by qRT-PCR. Taken together, these observations may lay the foundation for future functional analyses to unravel the biological roles of Populus’ DREB genes.

  9. Identification of small secreted peptides (SSPs) in maize and expression analysis of partial SSP genes in reproductive tissues.

    Science.gov (United States)

    Li, Ye Long; Dai, Xin Ren; Yue, Xun; Gao, Xin-Qi; Zhang, Xian Sheng

    2014-10-01

    Maize 1,491 small secreted peptides were identified, which were classified according to the character of peptide sequences. Partial SSP gene expressions in reproductive tissues were determined by qRT-PCR. Small secreted peptides (SSPs) are important cell-cell communication messengers in plants. Most information on plant SSPs come from Arabidopsis thaliana and Oryza sativa, while little is known about the SSPs of other grass species such as maize (Zea mays). In this study, we identified 1,491 SSP genes from maize genomic sequences. These putative SSP genes were distributed throughout the ten maize chromosomes. Among them, 611 SSPs were classified into 198 superfamilies according to their conserved domains, and 725 SSPs with four or more cysteines at their C-termini shared similar cysteine arrangements with their counterparts in other plant species. Moreover, the SSPs requiring post-translational modification, as well as defensin-like (DEFL) proteins, were identified. Further, the expression levels of 110 SSP genes were analyzed in reproductive tissues, including male flower, pollen, silk, and ovary. Most of the genes encoding basal-layer antifungal peptide-like, small coat proteins-like, thioredoxin-like proteins, γ-thionins-like, and DEFL proteins showed high expression levels in the ovary and male flower compared with their levels in silk and mature pollen. The rapid alkalinization factor-like genes were highly expressed only in the mature ovary and mature pollen, and pollen Ole e 1-like genes showed low expression in silk. The results of this study provide basic information for further analysis of SSP functions in the reproductive process of maize.

  10. Gene structure and expression characteristic of a novel odorant receptor gene cluster in the parasitoid wasp Microplitis mediator (Hymenoptera: Braconidae).

    Science.gov (United States)

    Wang, S-N; Shan, S; Zheng, Y; Peng, Y; Lu, Z-Y; Yang, Y-Q; Li, R-J; Zhang, Y-J; Guo, Y-Y

    2017-08-01

    Odorant receptors (ORs) expressed in the antennae of parasitoid wasps are responsible for detection of various lipophilic airborne molecules. In the present study, 107 novel OR genes were identified from Microplitis mediator antennal transcriptome data. Phylogenetic analysis of the set of OR genes from M. mediator and Microplitis demolitor revealed that M. mediator OR (MmedOR) genes can be classified into different subfamilies, and the majority of MmedORs in each subfamily shared high sequence identities and clear orthologous relationships to M. demolitor ORs. Within a subfamily, six MmedOR genes, MmedOR98, 124, 125, 126, 131 and 155, shared a similar gene structure and were tightly linked in the genome. To evaluate whether the clustered MmedOR genes share common regulatory features, the transcription profile and expression characteristics of the six closely related OR genes were investigated in M. mediator. Rapid amplification of cDNA ends-PCR experiments revealed that the OR genes within the cluster were transcribed as single mRNAs, and a bicistronic mRNA for two adjacent genes (MmedOR124 and MmedOR98) was also detected in female antennae by reverse transcription PCR. In situ hybridization experiments indicated that each OR gene within the cluster was expressed in a different number of cells. Moreover, there was no co-expression of the two highly related OR genes, MmedOR124 and MmedOR98, which appeared to be individually expressed in a distinct population of neurons. Overall, there were distinct expression profiles of closely related MmedOR genes from the same cluster in M. mediator. These data provide a basic understanding of the olfactory coding in parasitoid wasps. © 2017 The Royal Entomological Society.

  11. Shared Gene Expression Alterations in Nasal and Bronchial Epithelium for Lung Cancer Detection.

    Science.gov (United States)

    2017-07-01

    We previously derived and validated a bronchial epithelial gene expression biomarker to detect lung cancer in current and former smokers. Given that bronchial and nasal epithelial gene expression are similarly altered by cigarette smoke exposure, we sought to determine if cancer-associated gene expression might also be detectable in the more readily accessible nasal epithelium. Nasal epithelial brushings were prospectively collected from current and former smokers undergoing diagnostic evaluation for pulmonary lesions suspicious for lung cancer in the AEGIS-1 (n = 375) and AEGIS-2 (n = 130) clinical trials and gene expression profiled using microarrays. All statistical tests were two-sided. We identified 535 genes that were differentially expressed in the nasal epithelium of AEGIS-1 patients diagnosed with lung cancer vs those with benign disease after one year of follow-up ( P  cancer-associated gene expression alterations between the two airway sites ( P  lung cancer classifier derived in the AEGIS-1 cohort that combined clinical factors (age, smoking status, time since quit, mass size) and nasal gene expression (30 genes) had statistically significantly higher area under the curve (0.81; 95% confidence interval [CI] = 0.74 to 0.89, P  = .01) and sensitivity (0.91; 95% CI = 0.81 to 0.97, P  = .03) than a clinical-factor only model in independent samples from the AEGIS-2 cohort. These results support that the airway epithelial field of lung cancer-associated injury in ever smokers extends to the nose and demonstrates the potential of using nasal gene expression as a noninvasive biomarker for lung cancer detection. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  12. Impact of methoxyacetic acid on mouse Leydig cell gene expression

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    Waxman David J

    2010-06-01

    Full Text Available Abstract Background Methoxyacetic acid (MAA is the active metabolite of the widely used industrial chemical ethylene glycol monomethyl ether, which is associated with various developmental and reproductive toxicities, including neural toxicity, blood and immune disorders, limb degeneration and testicular toxicity. Testicular toxicity is caused by degeneration of germ cells in association with changes in gene expression in both germ cells and Sertoli cells of the testis. This study investigates the impact of MAA on gene expression in testicular Leydig cells, which play a critical role in germ cell survival and male reproductive function. Methods Cultured mouse TM3 Leydig cells were treated with MAA for 3, 8, and 24 h and changes in gene expression were monitored by genome-wide transcriptional profiling. Results A total of 3,912 MAA-responsive genes were identified. Ingenuity Pathway analysis identified reproductive system disease, inflammatory disease and connective tissue disorder as the top biological functions affected by MAA. The MAA-responsive genes were classified into 1,366 early responders, 1,387 mid-responders, and 1,138 late responders, based on the time required for MAA to elicit a response. Analysis of enriched functional clusters for each subgroup identified 106 MAA early response genes involved in transcription regulation, including 32 genes associated with developmental processes. 60 DNA-binding proteins responded to MAA rapidly but transiently, and may contribute to the downstream effects of MAA seen for many mid and late response genes. Genes within the phosphatidylinositol/phospholipase C/calcium signaling pathway, whose activity is required for potentiation of nuclear receptor signaling by MAA, were also enriched in the set of early MAA response genes. In contrast, many of the genes responding to MAA at later time points encode membrane proteins that contribute to cell adhesion and membrane signaling. Conclusions These findings

  13. Statistical Considerations for Immunohistochemistry Panel Development after Gene Expression Profiling of Human Cancers

    Science.gov (United States)

    Betensky, Rebecca A.; Nutt, Catherine L.; Batchelor, Tracy T.; Louis, David N.

    2005-01-01

    In recent years there have been a number of microarray expression studies in which different types of tumors were classified by identifying a panel of differentially expressed genes. Immunohistochemistry is a practical and robust method for extending gene expression data to common pathological specimens with the advantage of being applicable to paraffin-embedded tissues. However, the number of assays required for successful immunohistochemical classification remains unclear. We propose a simulation-based method for assessing sample size for an immunohistochemistry investigation after a promising gene expression study of human tumors. The goals of such an immunohistochemistry study would be to develop and validate a marker panel that yields improved prognostic classification of cancer patients. We demonstrate how the preliminary gene expression data, coupled with certain realistic assumptions, can be used to estimate the number of immunohistochemical assays required for development. These assumptions are more tenable than alternative assumptions that would be required for crude analytic sample size calculations and that may yield underpowered and inefficient studies. We applied our methods to the design of an immunohistochemistry study for glioma classification and estimated the number of assays required to ensure satisfactory technical and prognostic validation. Simulation approaches for computing power and sample size that are based on existing gene expression data provide a powerful tool for efficient design of follow-up genomic studies. PMID:15858152

  14. FARO server: Meta-analysis of gene expression by matching gene expression signatures to a compendium of public gene expression data

    DEFF Research Database (Denmark)

    Manijak, Mieszko P.; Nielsen, Henrik Bjørn

    2011-01-01

    circumvented by instead matching gene expression signatures to signatures of other experiments. FINDINGS: To facilitate this we present the Functional Association Response by Overlap (FARO) server, that match input signatures to a compendium of 242 gene expression signatures, extracted from more than 1700...... Arabidopsis microarray experiments. CONCLUSIONS: Hereby we present a publicly available tool for robust characterization of Arabidopsis gene expression experiments which can point to similar experimental factors in other experiments. The server is available at http://www.cbs.dtu.dk/services/faro/....

  15. Digital gene expression analysis of gene expression differences within Brassica diploids and allopolyploids.

    Science.gov (United States)

    Jiang, Jinjin; Wang, Yue; Zhu, Bao; Fang, Tingting; Fang, Yujie; Wang, Youping

    2015-01-27

    Brassica includes many successfully cultivated crop species of polyploid origin, either by ancestral genome triplication or by hybridization between two diploid progenitors, displaying complex repetitive sequences and transposons. The U's triangle, which consists of three diploids and three amphidiploids, is optimal for the analysis of complicated genomes after polyploidization. Next-generation sequencing enables the transcriptome profiling of polyploids on a global scale. We examined the gene expression patterns of three diploids (Brassica rapa, B. nigra, and B. oleracea) and three amphidiploids (B. napus, B. juncea, and B. carinata) via digital gene expression analysis. In total, the libraries generated between 5.7 and 6.1 million raw reads, and the clean tags of each library were mapped to 18547-21995 genes of B. rapa genome. The unambiguous tag-mapped genes in the libraries were compared. Moreover, the majority of differentially expressed genes (DEGs) were explored among diploids as well as between diploids and amphidiploids. Gene ontological analysis was performed to functionally categorize these DEGs into different classes. The Kyoto Encyclopedia of Genes and Genomes analysis was performed to assign these DEGs into approximately 120 pathways, among which the metabolic pathway, biosynthesis of secondary metabolites, and peroxisomal pathway were enriched. The non-additive genes in Brassica amphidiploids were analyzed, and the results indicated that orthologous genes in polyploids are frequently expressed in a non-additive pattern. Methyltransferase genes showed differential expression pattern in Brassica species. Our results provided an understanding of the transcriptome complexity of natural Brassica species. The gene expression changes in diploids and allopolyploids may help elucidate the morphological and physiological differences among Brassica species.

  16. A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data

    KAUST Repository

    Abusamra, Heba

    2013-01-01

    Different experiments have been applied to compare the performance of the classification methods with and without performing feature selection. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in different feature selection methods is investigated and the most frequent features selected in each fold among all methods for both datasets are evaluated.

  17. Automated Detection of Cancer Associated Genes Using a Combined Fuzzy-Rough-Set-Based F-Information and Water Swirl Algorithm of Human Gene Expression Data.

    Directory of Open Access Journals (Sweden)

    Pugalendhi Ganesh Kumar

    Full Text Available This study describes a novel approach to reducing the challenges of highly nonlinear multiclass gene expression values for cancer diagnosis. To build a fruitful system for cancer diagnosis, in this study, we introduced two levels of gene selection such as filtering and embedding for selection of potential genes and the most relevant genes associated with cancer, respectively. The filter procedure was implemented by developing a fuzzy rough set (FR-based method for redefining the criterion function of f-information (FI to identify the potential genes without discretizing the continuous gene expression values. The embedded procedure is implemented by means of a water swirl algorithm (WSA, which attempts to optimize the rule set and membership function required to classify samples using a fuzzy-rule-based multiclassification system (FRBMS. Two novel update equations are proposed in WSA, which have better exploration and exploitation abilities while designing a self-learning FRBMS. The efficiency of our new approach was evaluated on 13 multicategory and 9 binary datasets of cancer gene expression. Additionally, the performance of the proposed FRFI-WSA method in designing an FRBMS was compared with existing methods for gene selection and optimization such as genetic algorithm (GA, particle swarm optimization (PSO, and artificial bee colony algorithm (ABC on all the datasets. In the global cancer map with repeated measurements (GCM_RM dataset, the FRFI-WSA showed the smallest number of 16 most relevant genes associated with cancer using a minimal number of 26 compact rules with the highest classification accuracy (96.45%. In addition, the statistical validation used in this study revealed that the biological relevance of the most relevant genes associated with cancer and their linguistics detected by the proposed FRFI-WSA approach are better than those in the other methods. The simple interpretable rules with most relevant genes and effectively

  18. Three gene expression vector sets for concurrently expressing multiple genes in Saccharomyces cerevisiae.

    Science.gov (United States)

    Ishii, Jun; Kondo, Takashi; Makino, Harumi; Ogura, Akira; Matsuda, Fumio; Kondo, Akihiko

    2014-05-01

    Yeast has the potential to be used in bulk-scale fermentative production of fuels and chemicals due to its tolerance for low pH and robustness for autolysis. However, expression of multiple external genes in one host yeast strain is considerably labor-intensive due to the lack of polycistronic transcription. To promote the metabolic engineering of yeast, we generated systematic and convenient genetic engineering tools to express multiple genes in Saccharomyces cerevisiae. We constructed a series of multi-copy and integration vector sets for concurrently expressing two or three genes in S. cerevisiae by embedding three classical promoters. The comparative expression capabilities of the constructed vectors were monitored with green fluorescent protein, and the concurrent expression of genes was monitored with three different fluorescent proteins. Our multiple gene expression tool will be helpful to the advanced construction of genetically engineered yeast strains in a variety of research fields other than metabolic engineering. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

  19. Construction of a novel multi-gene assay (42-gene classifier) for prediction of late recurrence in ER-positive breast cancer patients.

    Science.gov (United States)

    Tsunashima, Ryo; Naoi, Yasuto; Shimazu, Kenzo; Kagara, Naofumi; Shimoda, Masashi; Tanei, Tomonori; Miyake, Tomohiro; Kim, Seung Jin; Noguchi, Shinzaburo

    2018-05-04

    Prediction models for late (> 5 years) recurrence in ER-positive breast cancer need to be developed for the accurate selection of patients for extended hormonal therapy. We attempted to develop such a prediction model focusing on the differences in gene expression between breast cancers with early and late recurrence. For the training set, 779 ER-positive breast cancers treated with tamoxifen alone for 5 years were selected from the databases (GSE6532, GSE12093, GSE17705, and GSE26971). For the validation set, 221 ER-positive breast cancers treated with adjuvant hormonal therapy for 5 years with or without chemotherapy at our hospital were included. Gene expression was assayed by DNA microarray analysis (Affymetrix U133 plus 2.0). With the 42 genes differentially expressed in early and late recurrence breast cancers in the training set, a prediction model (42GC) for late recurrence was constructed. The patients classified by 42GC into the late recurrence-like group showed a significantly (P = 0.006) higher late recurrence rate as expected but a significantly (P = 1.62 × E-13) lower rate for early recurrence than non-late recurrence-like group. These observations were confirmed for the validation set, i.e., P = 0.020 for late recurrence and P = 5.70 × E-5 for early recurrence. We developed a unique prediction model (42GC) for late recurrence by focusing on the biological differences between breast cancers with early and late recurrence. Interestingly, patients in the late recurrence-like group by 42GC were at low risk for early recurrence.

  20. Gene expression profiling in woman with women with breast cancer in a Saudi population

    International Nuclear Information System (INIS)

    Amer, Saud M. Bin; Maqbool, Z.; Nirmal, Maimoona S.; Hussain, Syed S.; Jeprel, Hatim A.; Qattan, Amal T.; Tulbah, Asma M.; Malik, Osama A.; Al-Tweigeri, Taher A.

    2008-01-01

    Objective was to generate consensus gene expression profiles of invasive breast tumors from a small cohort of Saudi females and to explore the possibility that they may be broadly conserved between Caucasian and Middle Eastern populations. This study was performed at King Faisal Specialist Hospital and Research Center, Riyadh, Kingdom of Saudi Arabia, from January 2005 to January 2007. Gene expression profiles were generated from 38 invasive breast tumors and 8 tumor adjacent tissues (TATs) using BD Atlas cDNA expression arrays containing 1176 genes. Results were confirmed by reverse transcriptase polymerase chain reaction and analyzed by 2-dimensional unsupervised hierarchical clustering. The analysis identified 48 differentially expressed genes in tumors from which 25 are already reported by various western studies. Forty-three of these genes were also differentially expressed in TATs. The same data set has been able to distinguish between tumors and the TAT's, interestingly by using only 4 of the differentially expressed genes. Moreover, we were able to group the patients according to prognosis to an extent by hierarchical clustering. Our results indicate that expression profiles between Saudi females with breast cancer and the Caucasian population are conserved to some extent, and can be used to classify patients according to prognostic groups. We also suggest 3 differentially expressed genes (IGHG3, CDK3 and RPS9) in tumors may have a novel role in breast cancer. In addition, the role of TATs is much more essential in breast cancer and needs to be explored thoroughly. (author)

  1. Identification of genes differentially expressed in ectomycorrhizal roots during the Pinus pinaster-Laccaria bicolor interaction.

    Science.gov (United States)

    Flores-Monterroso, Aranzazu; Canales, Javier; de la Torre, Fernando; Ávila, Concepción; Cánovas, Francisco M

    2013-06-01

    Ectomycorrhizal associations are of major ecological importance in temperate and boreal forests. The development of a functional ectomycorrhiza requires many genetic and biochemical changes. In this study, suppressive subtraction hybridization was used to identify differentially expressed genes in the roots of maritime pine (Pinus pinaster Aiton) inoculated with Laccaria bicolor, a mycorrhizal fungus. A total number of 200 unigenes were identified as being differentially regulated in maritime pine roots during the development of mycorrhiza. These unigenes were classified into 10 categories according to the function of their homologues in the GenBank database. Approximately, 40 % of the differentially expressed transcripts were genes that coded for unknown proteins in the databases or that had no homology to known genes. A group of these differentially expressed genes was selected to validate the results using quantitative real-time PCR. The transcript levels of the representative genes were compared between the non-inoculated and inoculated plants at 1, 5, 15 and 30 days after inoculation. The observed expression patterns indicate (1) changes in the composition of the wall cell, (2) tight regulation of defence genes during the development of mycorrhiza and (3) changes in carbon and nitrogen metabolism. Ammonium excess or deficiency dramatically affected the stability of ectomycorrhiza and altered gene expression in maritime pine roots.

  2. Large scale gene expression meta-analysis reveals tissue-specific, sex-biased gene expression in humans

    Directory of Open Access Journals (Sweden)

    Benjamin Mayne

    2016-10-01

    Full Text Available The severity and prevalence of many diseases are known to differ between the sexes. Organ specific sex-biased gene expression may underpin these and other sexually dimorphic traits. To further our understanding of sex differences in transcriptional regulation, we performed meta-analyses of sex biased gene expression in multiple human tissues. We analysed 22 publicly available human gene expression microarray data sets including over 2500 samples from 15 different tissues and 9 different organs. Briefly, by using an inverse-variance method we determined the effect size difference of gene expression between males and females. We found the greatest sex differences in gene expression in the brain, specifically in the anterior cingulate cortex, (1818 genes, followed by the heart (375 genes, kidney (224 genes, colon (218 genes and thyroid (163 genes. More interestingly, we found different parts of the brain with varying numbers and identity of sex-biased genes, indicating that specific cortical regions may influence sexually dimorphic traits. The majority of sex-biased genes in other tissues such as the bladder, liver, lungs and pancreas were on the sex chromosomes or involved in sex hormone production. On average in each tissue, 32% of autosomal genes that were expressed in a sex-biased fashion contained androgen or estrogen hormone response elements. Interestingly, across all tissues, we found approximately two-thirds of autosomal genes that were sex-biased were not under direct influence of sex hormones. To our knowledge this is the largest analysis of sex-biased gene expression in human tissues to date. We identified many sex-biased genes that were not under the direct influence of sex chromosome genes or sex hormones. These may provide targets for future development of sex-specific treatments for diseases.

  3. Differential Gene Expression and Aging

    Directory of Open Access Journals (Sweden)

    Laurent Seroude

    2002-01-01

    Full Text Available It has been established that an intricate program of gene expression controls progression through the different stages in development. The equally complex biological phenomenon known as aging is genetically determined and environmentally modulated. This review focuses on the genetic component of aging, with a special emphasis on differential gene expression. At least two genetic pathways regulating organism longevity act by modifying gene expression. Many genes are also subjected to age-dependent transcriptional regulation. Some age-related gene expression changes are prevented by caloric restriction, the most robust intervention that slows down the aging process. Manipulating the expression of some age-regulated genes can extend an organism's life span. Remarkably, the activity of many transcription regulatory elements is linked to physiological age as opposed to chronological age, indicating that orderly and tightly controlled regulatory pathways are active during aging.

  4. Polycistronic gene expression in Aspergillus niger.

    Science.gov (United States)

    Schuetze, Tabea; Meyer, Vera

    2017-09-25

    Genome mining approaches predict dozens of biosynthetic gene clusters in each of the filamentous fungal genomes sequenced so far. However, the majority of these gene clusters still remain cryptic because they are not expressed in their natural host. Simultaneous expression of all genes belonging to a biosynthetic pathway in a heterologous host is one approach to activate biosynthetic gene clusters and to screen the metabolites produced for bioactivities. Polycistronic expression of all pathway genes under control of a single and tunable promoter would be the method of choice, as this does not only simplify cloning procedures, but also offers control on timing and strength of expression. However, polycistronic gene expression is a feature not commonly found in eukaryotic host systems, such as Aspergillus niger. In this study, we tested the suitability of the viral P2A peptide for co-expression of three genes in A. niger. Two genes descend from Fusarium oxysporum and are essential to produce the secondary metabolite enniatin (esyn1, ekivR). The third gene (luc) encodes the reporter luciferase which was included to study position effects. Expression of the polycistronic gene cassette was put under control of the Tet-On system to ensure tunable gene expression in A. niger. In total, three polycistronic expression cassettes which differed in the position of luc were constructed and targeted to the pyrG locus in A. niger. This allowed direct comparison of the luciferase activity based on the position of the luciferase gene. Doxycycline-mediated induction of the Tet-On expression cassettes resulted in the production of one long polycistronic mRNA as proven by Northern analyses, and ensured comparable production of enniatin in all three strains. Notably, gene position within the polycistronic expression cassette matters, as, luciferase activity was lowest at position one and had a comparable activity at positions two and three. The P2A peptide can be used to express at

  5. Analyzing large gene expression and methylation data profiles using StatBicRM: statistical biclustering-based rule mining.

    Directory of Open Access Journals (Sweden)

    Ujjwal Maulik

    Full Text Available Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution. The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post

  6. Analyzing large gene expression and methylation data profiles using StatBicRM: statistical biclustering-based rule mining.

    Science.gov (United States)

    Maulik, Ujjwal; Mallik, Saurav; Mukhopadhyay, Anirban; Bandyopadhyay, Sanghamitra

    2015-01-01

    Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining) to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution). The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown) data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post-discretized data

  7. Transcriptome-wide identification of preferentially expressed genes in the hypothalamus and pituitary gland

    Directory of Open Access Journals (Sweden)

    Jonny eSt-Amand

    2012-01-01

    Full Text Available To identify preferentially expressed genes in the central endocrine organs of the hypothalamus and pituitary gland, we generated transcriptome-wide mRNA profiles of the mouse hypothalamus, pituitary gland and parietal cortex using serial analysis of gene expression (SAGE. Total counts of SAGE tags for the hypothalamus, pituitary gland and parietal cortex were 165824, 126688 and 161045 tags, respectively. This represented 59244, 45151 and 55131 distinct tags, respectively. Comparison of these mRNA profiles revealed that 22 mRNA species, including three potential novel transcripts, were preferentially expressed in the hypothalamus. In addition to well-known hypothalamic transcripts, such as hypocretin, several genes involved in hormone function, intracellular transduction, metabolism, protein transport, steroidogenesis, extracellular matrix and brain disease were identified as preferentially expressed hypothalamic transcripts. In the pituitary gland, 106 mRNA species, including 60 potential novel transcripts, were preferentially expressed. In addition to well-known pituitary genes, such as growth hormone and thyroid stimulating hormone beta, a number of genes classified to function in transport, amino acid metabolism, intracellular transduction, cell adhesion, disulfide bond formation, stress response, transcription, protein synthesis and turnover, cell differentiation, the cell cycle and in the cytoskeleton and extracellular matrix were also preferentially expressed. In conclusion, the current study identified not only well-known hypothalamic and pituitary transcripts but also a number of new candidates likely to be involved in endocrine homeostatic systems regulated by the hypothalamus and pituitary gland.

  8. Transcriptome-wide identification of preferentially expressed genes in the hypothalamus and pituitary gland.

    Science.gov (United States)

    St-Amand, Jonny; Yoshioka, Mayumi; Tanaka, Keitaro; Nishida, Yuichiro

    2011-01-01

    To identify preferentially expressed genes in the central endocrine organs of the hypothalamus and pituitary gland, we generated transcriptome-wide mRNA profiles of the hypothalamus, pituitary gland, and parietal cortex in male mice (12-15 weeks old) using serial analysis of gene expression (SAGE). Total counts of SAGE tags for the hypothalamus, pituitary gland, and parietal cortex were 165824, 126688, and 161045 tags, respectively. This represented 59244, 45151, and 55131 distinct tags, respectively. Comparison of these mRNA profiles revealed that 22 mRNA species, including three potential novel transcripts, were preferentially expressed in the hypothalamus. In addition to well-known hypothalamic transcripts, such as hypocretin, several genes involved in hormone function, intracellular transduction, metabolism, protein transport, steroidogenesis, extracellular matrix, and brain disease were identified as preferentially expressed hypothalamic transcripts. In the pituitary gland, 106 mRNA species, including 60 potential novel transcripts, were preferentially expressed. In addition to well-known pituitary genes, such as growth hormone and thyroid stimulating hormone beta, a number of genes classified to function in transport, amino acid metabolism, intracellular transduction, cell adhesion, disulfide bond formation, stress response, transcription, protein synthesis, and turnover, cell differentiation, the cell cycle, and in the cytoskeleton and extracellular matrix were also preferentially expressed. In conclusion, the current study identified not only well-known hypothalamic and pituitary transcripts but also a number of new candidates likely to be involved in endocrine homeostatic systems regulated by the hypothalamus and pituitary gland.

  9. Gene expression profiling reveals distinct molecular signatures associated with the rupture of intracranial aneurysm.

    Science.gov (United States)

    Nakaoka, Hirofumi; Tajima, Atsushi; Yoneyama, Taku; Hosomichi, Kazuyoshi; Kasuya, Hidetoshi; Mizutani, Tohru; Inoue, Ituro

    2014-08-01

    The rupture of intracranial aneurysm (IA) causes subarachnoid hemorrhage associated with high morbidity and mortality. We compared gene expression profiles in aneurysmal domes between unruptured IAs and ruptured IAs (RIAs) to elucidate biological mechanisms predisposing to the rupture of IA. We determined gene expression levels of 8 RIAs, 5 unruptured IAs, and 10 superficial temporal arteries with the Agilent microarrays. To explore biological heterogeneity of IAs, we classified the samples into subgroups showing similar gene expression patterns, using clustering methods. The clustering analysis identified 4 groups: superficial temporal arteries and unruptured IAs were aggregated into their own clusters, whereas RIAs segregated into 2 distinct subgroups (early and late RIAs). Comparing gene expression levels between early RIAs and unruptured IAs, we identified 430 upregulated and 617 downregulated genes in early RIAs. The upregulated genes were associated with inflammatory and immune responses and phagocytosis including S100/calgranulin genes (S100A8, S100A9, and S100A12). The downregulated genes suggest mechanical weakness of aneurysm walls. The expressions of Krüppel-like family of transcription factors (KLF2, KLF12, and KLF15), which were anti-inflammatory regulators, and CDKN2A, which was located on chromosome 9p21 that was the most consistently replicated locus in genome-wide association studies of IA, were also downregulated. We demonstrate that gene expression patterns of RIAs were different according to the age of patients. The results suggest that macrophage-mediated inflammation is a key biological pathway for IA rupture. The identified genes can be good candidates for molecular markers of rupture-prone IAs and therapeutic targets. © 2014 American Heart Association, Inc.

  10. Classification of genes and putative biomarker identification using distribution metrics on expression profiles.

    Directory of Open Access Journals (Sweden)

    Hung-Chung Huang

    Full Text Available BACKGROUND: Identification of genes with switch-like properties will facilitate discovery of regulatory mechanisms that underlie these properties, and will provide knowledge for the appropriate application of Boolean networks in gene regulatory models. As switch-like behavior is likely associated with tissue-specific expression, these gene products are expected to be plausible candidates as tissue-specific biomarkers. METHODOLOGY/PRINCIPAL FINDINGS: In a systematic classification of genes and search for biomarkers, gene expression profiles (GEPs of more than 16,000 genes from 2,145 mouse array samples were analyzed. Four distribution metrics (mean, standard deviation, kurtosis and skewness were used to classify GEPs into four categories: predominantly-off, predominantly-on, graded (rheostatic, and switch-like genes. The arrays under study were also grouped and examined by tissue type. For example, arrays were categorized as 'brain group' and 'non-brain group'; the Kolmogorov-Smirnov distance and Pearson correlation coefficient were then used to compare GEPs between brain and non-brain for each gene. We were thus able to identify tissue-specific biomarker candidate genes. CONCLUSIONS/SIGNIFICANCE: The methodology employed here may be used to facilitate disease-specific biomarker discovery.

  11. Classification between normal and tumor tissues based on the pair-wise gene expression ratio

    International Nuclear Information System (INIS)

    Yap, YeeLeng; Zhang, XueWu; Ling, MT; Wang, XiangHong; Wong, YC; Danchin, Antoine

    2004-01-01

    Precise classification of cancer types is critically important for early cancer diagnosis and treatment. Numerous efforts have been made to use gene expression profiles to improve precision of tumor classification. However, reliable cancer-related signals are generally lacking. Using recent datasets on colon and prostate cancer, a data transformation procedure from single gene expression to pair-wise gene expression ratio is proposed. Making use of the internal consistency of each expression profiling dataset this transformation improves the signal to noise ratio of the dataset and uncovers new relevant cancer-related signals (features). The efficiency in using the transformed dataset to perform normal/tumor classification was investigated using feature partitioning with informative features (gene annotation) as discriminating axes (single gene expression or pair-wise gene expression ratio). Classification results were compared to the original datasets for up to 10-feature model classifiers. 82 and 262 genes that have high correlation to tissue phenotype were selected from the colon and prostate datasets respectively. Remarkably, data transformation of the highly noisy expression data successfully led to lower the coefficient of variation (CV) for the within-class samples as well as improved the correlation with tissue phenotypes. The transformed dataset exhibited lower CV when compared to that of single gene expression. In the colon cancer set, the minimum CV decreased from 45.3% to 16.5%. In prostate cancer, comparable CV was achieved with and without transformation. This improvement in CV, coupled with the improved correlation between the pair-wise gene expression ratio and tissue phenotypes, yielded higher classification efficiency, especially with the colon dataset – from 87.1% to 93.5%. Over 90% of the top ten discriminating axes in both datasets showed significant improvement after data transformation. The high classification efficiency achieved suggested

  12. Histone modification profiles are predictive for tissue/cell-type specific expression of both protein-coding and microRNA genes

    Directory of Open Access Journals (Sweden)

    Zhang Michael Q

    2011-05-01

    Full Text Available Abstract Background Gene expression is regulated at both the DNA sequence level and through modification of chromatin. However, the effect of chromatin on tissue/cell-type specific gene regulation (TCSR is largely unknown. In this paper, we present a method to elucidate the relationship between histone modification/variation (HMV and TCSR. Results A classifier for differentiating CD4+ T cell-specific genes from housekeeping genes using HMV data was built. We found HMV in both promoter and gene body regions to be predictive of genes which are targets of TCSR. For example, the histone modification types H3K4me3 and H3K27ac were identified as the most predictive for CpG-related promoters, whereas H3K4me3 and H3K79me3 were the most predictive for nonCpG-related promoters. However, genes targeted by TCSR can be predicted using other type of HMVs as well. Such redundancy implies that multiple type of underlying regulatory elements, such as enhancers or intragenic alternative promoters, which can regulate gene expression in a tissue/cell-type specific fashion, may be marked by the HMVs. Finally, we show that the predictive power of HMV for TCSR is not limited to protein-coding genes in CD4+ T cells, as we successfully predicted TCSR targeted genes in muscle cells, as well as microRNA genes with expression specific to CD4+ T cells, by the same classifier which was trained on HMV data of protein-coding genes in CD4+ T cells. Conclusion We have begun to understand the HMV patterns that guide gene expression in both tissue/cell-type specific and ubiquitous manner.

  13. Genome-wide identification and expression analysis of the WRKY gene family in cassava

    Directory of Open Access Journals (Sweden)

    Yunxie eWei

    2016-02-01

    Full Text Available The WRKY family, a large family of transcription factors (TFs found in higher plants, plays central roles in many aspects of physiological processes and adaption to environment. However, little information is available regarding the WRKY family in cassava (Manihot esculenta. In the present study, 85 WRKY genes were identified from the cassava genome and classified into three groups according to conserved WRKY domains and zinc-finger structure. Conserved motif analysis showed that all of the identified MeWRKYs had the conserved WRKY domain. Gene structure analysis suggested that the number of introns in MeWRKY genes varied from 1 to 5, with the majority of MeWRKY genes containing 3 exons. Expression profiles of MeWRKY genes in different tissues and in response to drought stress were analyzed using the RNA-seq technique. The results showed that 72 MeWRKY genes had differential expression in their transcript abundance and 78 MeWRKY genes were differentially expressed in response to drought stresses in different accessions, indicating their contribution to plant developmental processes and drought stress resistance in cassava. Finally, the expression of 9 WRKY genes was analyzed by qRT-PCR under osmotic, salt, ABA, H2O2, and cold treatments, indicating that MeWRKYs may be involved in different signaling pathways. Taken together, this systematic analysis identifies some tissue-specific and abiotic stress-responsive candidate MeWRKY genes for further functional assays in planta, and provides a solid foundation for understanding of abiotic stress responses and signal transduction mediated by WRKYs in cassava.

  14. Genome-Wide Identification and Expression Analysis of the WRKY Gene Family in Cassava.

    Science.gov (United States)

    Wei, Yunxie; Shi, Haitao; Xia, Zhiqiang; Tie, Weiwei; Ding, Zehong; Yan, Yan; Wang, Wenquan; Hu, Wei; Li, Kaimian

    2016-01-01

    The WRKY family, a large family of transcription factors (TFs) found in higher plants, plays central roles in many aspects of physiological processes and adaption to environment. However, little information is available regarding the WRKY family in cassava (Manihot esculenta). In the present study, 85 WRKY genes were identified from the cassava genome and classified into three groups according to conserved WRKY domains and zinc-finger structure. Conserved motif analysis showed that all of the identified MeWRKYs had the conserved WRKY domain. Gene structure analysis suggested that the number of introns in MeWRKY genes varied from 1 to 5, with the majority of MeWRKY genes containing three exons. Expression profiles of MeWRKY genes in different tissues and in response to drought stress were analyzed using the RNA-seq technique. The results showed that 72 MeWRKY genes had differential expression in their transcript abundance and 78 MeWRKY genes were differentially expressed in response to drought stresses in different accessions, indicating their contribution to plant developmental processes and drought stress resistance in cassava. Finally, the expression of 9 WRKY genes was analyzed by qRT-PCR under osmotic, salt, ABA, H2O2, and cold treatments, indicating that MeWRKYs may be involved in different signaling pathways. Taken together, this systematic analysis identifies some tissue-specific and abiotic stress-responsive candidate MeWRKY genes for further functional assays in planta, and provides a solid foundation for understanding of abiotic stress responses and signal transduction mediated by WRKYs in cassava.

  15. Adipose gene expression prior to weight loss can differentiate and weakly predict dietary responders.

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    David M Mutch

    Full Text Available BACKGROUND: The ability to identify obese individuals who will successfully lose weight in response to dietary intervention will revolutionize disease management. Therefore, we asked whether it is possible to identify subjects who will lose weight during dietary intervention using only a single gene expression snapshot. METHODOLOGY/PRINCIPAL FINDINGS: The present study involved 54 female subjects from the Nutrient-Gene Interactions in Human Obesity-Implications for Dietary Guidelines (NUGENOB trial to determine whether subcutaneous adipose tissue gene expression could be used to predict weight loss prior to the 10-week consumption of a low-fat hypocaloric diet. Using several statistical tests revealed that the gene expression profiles of responders (8-12 kgs weight loss could always be differentiated from non-responders (<4 kgs weight loss. We also assessed whether this differentiation was sufficient for prediction. Using a bottom-up (i.e. black-box approach, standard class prediction algorithms were able to predict dietary responders with up to 61.1%+/-8.1% accuracy. Using a top-down approach (i.e. using differentially expressed genes to build a classifier improved prediction accuracy to 80.9%+/-2.2%. CONCLUSION: Adipose gene expression profiling prior to the consumption of a low-fat diet is able to differentiate responders from non-responders as well as serve as a weak predictor of subjects destined to lose weight. While the degree of prediction accuracy currently achieved with a gene expression snapshot is perhaps insufficient for clinical use, this work reveals that the comprehensive molecular signature of adipose tissue paves the way for the future of personalized nutrition.

  16. Gene expression inference with deep learning.

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    Chen, Yifei; Li, Yi; Narayan, Rajiv; Subramanian, Aravind; Xie, Xiaohui

    2016-06-15

    Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. D-GEX is available at https://github.com/uci-cbcl/D-GEX CONTACT: xhx@ics.uci.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  17. Genome-Wide Identification and Expression Analysis of the UGlcAE Gene Family in Tomato

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    Xing Ding

    2018-05-01

    Full Text Available The UGlcAE has the capability of interconverting UDP-d-galacturonic acid and UDP-d-glucuronic acid, and UDP-d-galacturonic acid is an activated precursor for the synthesis of pectins in plants. In this study, we identified nine UGlcAE protein-encoding genes in tomato. The nine UGlcAE genes that were distributed on eight chromosomes in tomato, and the corresponding proteins contained one or two trans-membrane domains. The phylogenetic analysis showed that SlUGlcAE genes could be divided into seven groups, designated UGlcAE1 to UGlcAE6, of which the UGlcAE2 were classified into two groups. Expression profile analysis revealed that the SlUGlcAE genes display diverse expression patterns in various tomato tissues. Selective pressure analysis indicated that all of the amino acid sites of SlUGlcAE proteins are undergoing purifying selection. Fifteen stress-, hormone-, and development-related elements were identified in the upstream regions (0.5 kb of these SlUGlcAE genes. Furthermore, we investigated the expression patterns of SlUGlcAE genes in response to three hormones (indole-3-acetic acid (IAA, gibberellin (GA, and salicylic acid (SA. We detected firmness, pectin contents, and expression levels of UGlcAE family genes during the development of tomato fruit. Here, we systematically summarize the general characteristics of the SlUGlcAE genes in tomato, which could provide a basis for further function studies of tomato UGlcAE genes.

  18. Global transgenerational gene expression dynamics in two newly synthesized allohexaploid wheat (Triticum aestivum lines

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    Qi Bao

    2012-01-01

    Full Text Available Abstract Background Alteration in gene expression resulting from allopolyploidization is a prominent feature in plants, but its spectrum and extent are not fully known. Common wheat (Triticum aestivum was formed via allohexaploidization about 10,000 years ago, and became the most important crop plant. To gain further insights into the genome-wide transcriptional dynamics associated with the onset of common wheat formation, we conducted microarray-based genome-wide gene expression analysis on two newly synthesized allohexaploid wheat lines with chromosomal stability and a genome constitution analogous to that of the present-day common wheat. Results Multi-color GISH (genomic in situ hybridization was used to identify individual plants from two nascent allohexaploid wheat lines between Triticum turgidum (2n = 4x = 28; genome BBAA and Aegilops tauschii (2n = 2x = 14; genome DD, which had a stable chromosomal constitution analogous to that of common wheat (2n = 6x = 42; genome BBAADD. Genome-wide analysis of gene expression was performed for these allohexaploid lines along with their parental plants from T. turgidum and Ae. tauschii, using the Affymetrix Gene Chip Wheat Genome-Array. Comparison with the parental plants coupled with inclusion of empirical mid-parent values (MPVs revealed that whereas the great majority of genes showed the expected parental additivity, two major patterns of alteration in gene expression in the allohexaploid lines were identified: parental dominance expression and non-additive expression. Genes involved in each of the two altered expression patterns could be classified into three distinct groups, stochastic, heritable and persistent, based on their transgenerational heritability and inter-line conservation. Strikingly, whereas both altered patterns of gene expression showed a propensity of inheritance, identity of the involved genes was highly stochastic, consistent with the involvement of diverse Gene Ontology (GO

  19. A lung cancer risk classifier comprising genome maintenance genes measured in normal bronchial epithelial cells.

    Science.gov (United States)

    Yeo, Jiyoun; Crawford, Erin L; Zhang, Xiaolu; Khuder, Sadik; Chen, Tian; Levin, Albert; Blomquist, Thomas M; Willey, James C

    2017-05-02

    Annual low dose CT (LDCT) screening of individuals at high demographic risk reduces lung cancer mortality by more than 20%. However, subjects selected for screening based on demographic criteria typically have less than a 10% lifetime risk for lung cancer. Thus, there is need for a biomarker that better stratifies subjects for LDCT screening. Toward this goal, we previously reported a lung cancer risk test (LCRT) biomarker comprising 14 genome-maintenance (GM) pathway genes measured in normal bronchial epithelial cells (NBEC) that accurately classified cancer (CA) from non-cancer (NC) subjects. The primary goal of the studies reported here was to optimize the LCRT biomarker for high specificity and ease of clinical implementation. Targeted competitive multiplex PCR amplicon libraries were prepared for next generation sequencing (NGS) analysis of transcript abundance at 68 sites among 33 GM target genes in NBEC specimens collected from a retrospective cohort of 120 subjects, including 61 CA cases and 59 NC controls. Genes were selected for analysis based on contribution to the previously reported LCRT biomarker and/or prior evidence for association with lung cancer risk. Linear discriminant analysis was used to identify the most accurate classifier suitable to stratify subjects for screening. After cross-validation, a model comprising expression values from 12 genes (CDKN1A, E2F1, ERCC1, ERCC4, ERCC5, GPX1, GSTP1, KEAP1, RB1, TP53, TP63, and XRCC1) and demographic factors age, gender, and pack-years smoking, had Receiver Operator Characteristic area under the curve (ROC AUC) of 0.975 (95% CI: 0.96-0.99). The overall classification accuracy was 93% (95% CI 88%-98%) with sensitivity 93.1%, specificity 92.9%, positive predictive value 93.1% and negative predictive value 93%. The ROC AUC for this classifier was significantly better (p < 0.0001) than the best model comprising demographic features alone. The LCRT biomarker reported here displayed high accuracy and ease

  20. Identification of specific gene expression profiles in fibroblasts derived from middle ear cholesteatoma.

    Science.gov (United States)

    Yoshikawa, Mamoru; Kojima, Hiromi; Wada, Kota; Tsukidate, Toshiharu; Okada, Naoko; Saito, Hirohisa; Moriyama, Hiroshi

    2006-07-01

    To investigate the role of fibroblasts in the pathogenesis of cholesteatoma. Tissue specimens were obtained from our patients. Middle ear cholesteatoma-derived fibroblasts (MECFs) and postauricular skin-derived fibroblasts (SFs) as controls were then cultured for a few weeks. These fibroblasts were stimulated with interleukin (IL) 1alpha and/or IL-1beta before gene expression assays. We used the human genome U133A probe array (GeneChip) and real-time polymerase chain reaction to examine and compare the gene expression profiles of the MECFs and SFs. Six patients who had undergone tympanoplasty. The IL-1alpha-regulated genes were classified into 4 distinct clusters on the basis of profiles differentially regulated by SF and MECF using a hierarchical clustering analysis. The messenger RNA expressions of LARC (liver and activation-regulated chemokine), GMCSF (granulocyte-macrophage colony-stimulating factor), epiregulin, ICAM1 (intercellular adhesion molecule 1), and TGFA (transforming growth factor alpha) were more strongly up-regulated by IL-1alpha and/or IL-1beta in MECF than in SF, suggesting that these fibroblasts derived from different tissues retained their typical gene expression profiles. Fibroblasts may play a role in hyperkeratosis of middle ear cholesteatoma by releasing molecules involved in inflammation and epidermal growth. These fibroblasts may retain tissue-specific characteristics presumably controlled by epigenetic mechanisms.

  1. Scaling of gene expression data allowing the comparison of different gene expression platforms

    NARCIS (Netherlands)

    van Ruissen, Fred; Schaaf, Gerben J.; Kool, Marcel; Baas, Frank; Ruijter, Jan M.

    2008-01-01

    Serial analysis of gene expression (SAGE) and microarrays have found a widespread application, but much ambiguity exists regarding the amalgamation of the data resulting from these technologies. Cross-platform utilization of gene expression data from the SAGE and microarray technology could reduce

  2. cis sequence effects on gene expression

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    Jacobs Kevin

    2007-08-01

    Full Text Available Abstract Background Sequence and transcriptional variability within and between individuals are typically studied independently. The joint analysis of sequence and gene expression variation (genetical genomics provides insight into the role of linked sequence variation in the regulation of gene expression. We investigated the role of sequence variation in cis on gene expression (cis sequence effects in a group of genes commonly studied in cancer research in lymphoblastoid cell lines. We estimated the proportion of genes exhibiting cis sequence effects and the proportion of gene expression variation explained by cis sequence effects using three different analytical approaches, and compared our results to the literature. Results We generated gene expression profiling data at N = 697 candidate genes from N = 30 lymphoblastoid cell lines for this study and used available candidate gene resequencing data at N = 552 candidate genes to identify N = 30 candidate genes with sufficient variance in both datasets for the investigation of cis sequence effects. We used two additive models and the haplotype phylogeny scanning approach of Templeton (Tree Scanning to evaluate association between individual SNPs, all SNPs at a gene, and diplotypes, with log-transformed gene expression. SNPs and diplotypes at eight candidate genes exhibited statistically significant (p cis sequence effects in our study, respectively. Conclusion Based on analysis of our results and the extant literature, one in four genes exhibits significant cis sequence effects, and for these genes, about 30% of gene expression variation is accounted for by cis sequence variation. Despite diverse experimental approaches, the presence or absence of significant cis sequence effects is largely supported by previously published studies.

  3. Extracting gene expression patterns and identifying co-expressed genes from microarray data reveals biologically responsive processes

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    Paules Richard S

    2007-11-01

    Full Text Available Abstract Background A common observation in the analysis of gene expression data is that many genes display similarity in their expression patterns and therefore appear to be co-regulated. However, the variation associated with microarray data and the complexity of the experimental designs make the acquisition of co-expressed genes a challenge. We developed a novel method for Extracting microarray gene expression Patterns and Identifying co-expressed Genes, designated as EPIG. The approach utilizes the underlying structure of gene expression data to extract patterns and identify co-expressed genes that are responsive to experimental conditions. Results Through evaluation of the correlations among profiles, the magnitude of variation in gene expression profiles, and profile signal-to-noise ratio's, EPIG extracts a set of patterns representing co-expressed genes. The method is shown to work well with a simulated data set and microarray data obtained from time-series studies of dauer recovery and L1 starvation in C. elegans and after ultraviolet (UV or ionizing radiation (IR-induced DNA damage in diploid human fibroblasts. With the simulated data set, EPIG extracted the appropriate number of patterns which were more stable and homogeneous than the set of patterns that were determined using the CLICK or CAST clustering algorithms. However, CLICK performed better than EPIG and CAST with respect to the average correlation between clusters/patterns of the simulated data. With real biological data, EPIG extracted more dauer-specific patterns than CLICK. Furthermore, analysis of the IR/UV data revealed 18 unique patterns and 2661 genes out of approximately 17,000 that were identified as significantly expressed and categorized to the patterns by EPIG. The time-dependent patterns displayed similar and dissimilar responses between IR and UV treatments. Gene Ontology analysis applied to each pattern-related subset of co-expressed genes revealed underlying

  4. Differential gene expression in granulosa cells from polycystic ovary syndrome patients with and without insulin resistance: identification of susceptibility gene sets through network analysis.

    Science.gov (United States)

    Kaur, Surleen; Archer, Kellie J; Devi, M Gouri; Kriplani, Alka; Strauss, Jerome F; Singh, Rita

    2012-10-01

    Polycystic ovary syndrome (PCOS) is a heterogeneous, genetically complex, endocrine disorder of uncertain etiology in women. Our aim was to compare the gene expression profiles in stimulated granulosa cells of PCOS women with and without insulin resistance vs. matched controls. This study included 12 normal ovulatory women (controls), 12 women with PCOS without evidence for insulin resistance (PCOS non-IR), and 16 women with insulin resistance (PCOS-IR) undergoing in vitro fertilization. Granulosa cell gene expression profiling was accomplished using Affymetrix Human Genome-U133 arrays. Differentially expressed genes were classified according to gene ontology using ingenuity pathway analysis tools. Microarray results for selected genes were confirmed by real-time quantitative PCR. A total of 211 genes were differentially expressed in PCOS non-IR and PCOS-IR granulosa cells (fold change≥1.5; P≤0.001) vs. matched controls. Diabetes mellitus and inflammation genes were significantly increased in PCOS-IR patients. Real-time quantitative PCR confirmed higher expression of NCF2 (2.13-fold), TCF7L2 (1.92-fold), and SERPINA1 (5.35-fold). Increased expression of inflammation genes ITGAX (3.68-fold) and TAB2 (1.86-fold) was confirmed in PCOS non-IR. Different cardiometabolic disease genes were differentially expressed in the two groups. Decreased expression of CAV1 (-3.58-fold) in PCOS non-IR and SPARC (-1.88-fold) in PCOS-IR was confirmed. Differential expression of genes involved in TGF-β signaling (IGF2R, increased; and HAS2, decreased), and oxidative stress (TXNIP, increased) was confirmed in both groups. Microarray analysis demonstrated differential expression of genes linked to diabetes mellitus, inflammation, cardiovascular diseases, and infertility in the granulosa cells of PCOS women with and without insulin resistance. Because these dysregulated genes are also involved in oxidative stress, lipid metabolism, and insulin signaling, we hypothesize that these

  5. Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease.

    Science.gov (United States)

    Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

    2014-01-01

    We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. http://rged.wall-eva.net. © The Author(s) 2014. Published by Oxford University Press.

  6. Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease

    Science.gov (United States)

    Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

    2014-01-01

    We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Availability and implementation: Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. Database URL: http://rged.wall-eva.net PMID:25252782

  7. Using gene co-expression network analysis to predict biomarkers for chronic lymphocytic leukemia

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    Borlawsky Tara B

    2010-10-01

    Full Text Available Abstract Background Chronic lymphocytic leukemia (CLL is the most common adult leukemia. It is a highly heterogeneous disease, and can be divided roughly into indolent and progressive stages based on classic clinical markers. Immunoglobin heavy chain variable region (IgVH mutational status was found to be associated with patient survival outcome, and biomarkers linked to the IgVH status has been a focus in the CLL prognosis research field. However, biomarkers highly correlated with IgVH mutational status which can accurately predict the survival outcome are yet to be discovered. Results In this paper, we investigate the use of gene co-expression network analysis to identify potential biomarkers for CLL. Specifically we focused on the co-expression network involving ZAP70, a well characterized biomarker for CLL. We selected 23 microarray datasets corresponding to multiple types of cancer from the Gene Expression Omnibus (GEO and used the frequent network mining algorithm CODENSE to identify highly connected gene co-expression networks spanning the entire genome, then evaluated the genes in the co-expression network in which ZAP70 is involved. We then applied a set of feature selection methods to further select genes which are capable of predicting IgVH mutation status from the ZAP70 co-expression network. Conclusions We have identified a set of genes that are potential CLL prognostic biomarkers IL2RB, CD8A, CD247, LAG3 and KLRK1, which can predict CLL patient IgVH mutational status with high accuracies. Their prognostic capabilities were cross-validated by applying these biomarker candidates to classify patients into different outcome groups using a CLL microarray datasets with clinical information.

  8. Molecular sub-classification of renal epithelial tumors using meta-analysis of gene expression microarrays.

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    Thomas Sanford

    Full Text Available To evaluate the accuracy of the sub-classification of renal cortical neoplasms using molecular signatures.A search of publicly available databases was performed to identify microarray datasets with multiple histologic sub-types of renal cortical neoplasms. Meta-analytic techniques were utilized to identify differentially expressed genes for each histologic subtype. The lists of genes obtained from the meta-analysis were used to create predictive signatures through the use of a pair-based method. These signatures were organized into an algorithm to sub-classify renal neoplasms. The use of these signatures according to our algorithm was validated on several independent datasets.We identified three Gene Expression Omnibus datasets that fit our criteria to develop a training set. All of the datasets in our study utilized the Affymetrix platform. The final training dataset included 149 samples represented by the four most common histologic subtypes of renal cortical neoplasms: 69 clear cell, 41 papillary, 16 chromophobe, and 23 oncocytomas. When validation of our signatures was performed on external datasets, we were able to correctly classify 68 of the 72 samples (94%. The correct classification by subtype was 19/20 (95% for clear cell, 14/14 (100% for papillary, 17/19 (89% for chromophobe, 18/19 (95% for oncocytomas.Through the use of meta-analytic techniques, we were able to create an algorithm that sub-classified renal neoplasms on a molecular level with 94% accuracy across multiple independent datasets. This algorithm may aid in selecting molecular therapies and may improve the accuracy of subtyping of renal cortical tumors.

  9. Modulation of gene expression made easy

    DEFF Research Database (Denmark)

    Solem, Christian; Jensen, Peter Ruhdal

    2002-01-01

    A new approach for modulating gene expression, based on randomization of promoter (spacer) sequences, was developed. The method was applied to chromosomal genes in Lactococcus lactis and shown to generate libraries of clones with broad ranges of expression levels of target genes. In one example...... that the method can be applied to modulating the expression of native genes on the chromosome. We constructed a series of strains in which the expression of the las operon, containing the genes pfk, pyk, and ldh, was modulated by integrating a truncated copy of the pfk gene. Importantly, the modulation affected...

  10. Systematic assessment of multi-gene predictors of pan-cancer cell line sensitivity to drugs exploiting gene expression data [version 1; referees: 2 approved

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    Linh Nguyen

    2016-12-01

    Full Text Available Background: Selected gene mutations are routinely used to guide the selection of cancer drugs for a given patient tumour. Large pharmacogenomic data sets were introduced to discover more of these single-gene markers of drug sensitivity. Very recently, machine learning regression has been used to investigate how well cancer cell line sensitivity to drugs is predicted depending on the type of molecular profile. The latter has revealed that gene expression data is the most predictive profile in the pan-cancer setting. However, no study to date has exploited GDSC data to systematically compare the performance of machine learning models based on multi-gene expression data against that of widely-used single-gene markers based on genomics data. Methods: Here we present this systematic comparison using Random Forest (RF classifiers exploiting the expression levels of 13,321 genes and an average of 501 tested cell lines per drug. To account for time-dependent batch effects in IC50 measurements, we employ independent test sets generated with more recent GDSC data than that used to train the predictors and show that this is a more realistic validation than K-fold cross-validation. Results and Discussion: Across 127 GDSC drugs, our results show that the single-gene markers unveiled by the MANOVA analysis tend to achieve higher precision than these RF-based multi-gene models, at the cost of generally having a poor recall (i.e. correctly detecting only a small part of the cell lines sensitive to the drug. Regarding overall classification performance, about two thirds of the drugs are better predicted by multi-gene RF classifiers. Among the drugs with the most predictive of these models, we found pyrimethamine, sunitinib and 17-AAG. Conclusions: We now know that this type of models can predict in vitro tumour response to these drugs. These models can thus be further investigated on in vivo tumour models.

  11. Identification, classification and differential expression of oleosin genes in tung tree (Vernicia fordii).

    Science.gov (United States)

    Cao, Heping; Zhang, Lin; Tan, Xiaofeng; Long, Hongxu; Shockey, Jay M

    2014-01-01

    Triacylglycerols (TAG) are the major molecules of energy storage in eukaryotes. TAG are packed in subcellular structures called oil bodies or lipid droplets. Oleosins (OLE) are the major proteins in plant oil bodies. Multiple isoforms of OLE are present in plants such as tung tree (Vernicia fordii), whose seeds are rich in novel TAG with a wide range of industrial applications. The objectives of this study were to identify OLE genes, classify OLE proteins and analyze OLE gene expression in tung trees. We identified five tung tree OLE genes coding for small hydrophobic proteins. Genome-wide phylogenetic analysis and multiple sequence alignment demonstrated that the five tung OLE genes represented the five OLE subfamilies and all contained the "proline knot" motif (PX5SPX3P) shared among 65 OLE from 19 tree species, including the sequenced genomes of Prunus persica (peach), Populus trichocarpa (poplar), Ricinus communis (castor bean), Theobroma cacao (cacao) and Vitis vinifera (grapevine). Tung OLE1, OLE2 and OLE3 belong to the S type and OLE4 and OLE5 belong to the SM type of Arabidopsis OLE. TaqMan and SYBR Green qPCR methods were used to study the differential expression of OLE genes in tung tree tissues. Expression results demonstrated that 1) All five OLE genes were expressed in developing tung seeds, leaves and flowers; 2) OLE mRNA levels were much higher in seeds than leaves or flowers; 3) OLE1, OLE2 and OLE3 genes were expressed in tung seeds at much higher levels than OLE4 and OLE5 genes; 4) OLE mRNA levels rapidly increased during seed development; and 5) OLE gene expression was well-coordinated with tung oil accumulation in the seeds. These results suggest that tung OLE genes 1-3 probably play major roles in tung oil accumulation and/or oil body development. Therefore, they might be preferred targets for tung oil engineering in transgenic plants.

  12. Identification, classification and differential expression of oleosin genes in tung tree (Vernicia fordii.

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    Heping Cao

    Full Text Available Triacylglycerols (TAG are the major molecules of energy storage in eukaryotes. TAG are packed in subcellular structures called oil bodies or lipid droplets. Oleosins (OLE are the major proteins in plant oil bodies. Multiple isoforms of OLE are present in plants such as tung tree (Vernicia fordii, whose seeds are rich in novel TAG with a wide range of industrial applications. The objectives of this study were to identify OLE genes, classify OLE proteins and analyze OLE gene expression in tung trees. We identified five tung tree OLE genes coding for small hydrophobic proteins. Genome-wide phylogenetic analysis and multiple sequence alignment demonstrated that the five tung OLE genes represented the five OLE subfamilies and all contained the "proline knot" motif (PX5SPX3P shared among 65 OLE from 19 tree species, including the sequenced genomes of Prunus persica (peach, Populus trichocarpa (poplar, Ricinus communis (castor bean, Theobroma cacao (cacao and Vitis vinifera (grapevine. Tung OLE1, OLE2 and OLE3 belong to the S type and OLE4 and OLE5 belong to the SM type of Arabidopsis OLE. TaqMan and SYBR Green qPCR methods were used to study the differential expression of OLE genes in tung tree tissues. Expression results demonstrated that 1 All five OLE genes were expressed in developing tung seeds, leaves and flowers; 2 OLE mRNA levels were much higher in seeds than leaves or flowers; 3 OLE1, OLE2 and OLE3 genes were expressed in tung seeds at much higher levels than OLE4 and OLE5 genes; 4 OLE mRNA levels rapidly increased during seed development; and 5 OLE gene expression was well-coordinated with tung oil accumulation in the seeds. These results suggest that tung OLE genes 1-3 probably play major roles in tung oil accumulation and/or oil body development. Therefore, they might be preferred targets for tung oil engineering in transgenic plants.

  13. Using gene expression noise to understand gene regulation

    NARCIS (Netherlands)

    Munsky, B.; Neuert, G.; van Oudenaarden, A.

    2012-01-01

    Phenotypic variation is ubiquitous in biology and is often traceable to underlying genetic and environmental variation. However, even genetically identical cells in identical environments display variable phenotypes. Stochastic gene expression, or gene expression "noise," has been suggested as a

  14. Indirect two-sided relative ranking: a robust similarity measure for gene expression data

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    Licamele Louis

    2010-03-01

    Full Text Available Abstract Background There is a large amount of gene expression data that exists in the public domain. This data has been generated under a variety of experimental conditions. Unfortunately, these experimental variations have generally prevented researchers from accurately comparing and combining this wealth of data, which still hides many novel insights. Results In this paper we present a new method, which we refer to as indirect two-sided relative ranking, for comparing gene expression profiles that is robust to variations in experimental conditions. This method extends the current best approach, which is based on comparing the correlations of the up and down regulated genes, by introducing a comparison based on the correlations in rankings across the entire database. Because our method is robust to experimental variations, it allows a greater variety of gene expression data to be combined, which, as we show, leads to richer scientific discoveries. Conclusions We demonstrate the benefit of our proposed indirect method on several datasets. We first evaluate the ability of the indirect method to retrieve compounds with similar therapeutic effects across known experimental barriers, namely vehicle and batch effects, on two independent datasets (one private and one public. We show that our indirect method is able to significantly improve upon the previous state-of-the-art method with a substantial improvement in recall at rank 10 of 97.03% and 49.44%, on each dataset, respectively. Next, we demonstrate that our indirect method results in improved accuracy for classification in several additional datasets. These datasets demonstrate the use of our indirect method for classifying cancer subtypes, predicting drug sensitivity/resistance, and classifying (related cell types. Even in the absence of a known (i.e., labeled experimental barrier, the improvement of the indirect method in each of these datasets is statistically significant.

  15. A strategy for full interrogation of prognostic gene expression patterns: exploring the biology of diffuse large B cell lymphoma.

    Directory of Open Access Journals (Sweden)

    Lisa M Rimsza

    Full Text Available Gene expression profiling yields quantitative data on gene expression used to create prognostic models that accurately predict patient outcome in diffuse large B cell lymphoma (DLBCL. Often, data are analyzed with genes classified by whether they fall above or below the median expression level. We sought to determine whether examining multiple cut-points might be a more powerful technique to investigate the association of gene expression with outcome.We explored gene expression profiling data using variable cut-point analysis for 36 genes with reported prognostic value in DLBCL. We plotted two-group survival logrank test statistics against corresponding cut-points of the gene expression levels and smooth estimates of the hazard ratio of death versus gene expression levels. To facilitate comparisons we also standardized the expression of each of the genes by the fraction of patients that would be identified by any cut-point. A multiple comparison adjusted permutation p-value identified 3 different patterns of significance: 1 genes with significant cut-point points below the median, whose loss is associated with poor outcome (e.g. HLA-DR; 2 genes with significant cut-points above the median, whose over-expression is associated with poor outcome (e.g. CCND2; and 3 genes with significant cut-points on either side of the median, (e.g. extracellular molecules such as FN1.Variable cut-point analysis with permutation p-value calculation can be used to identify significant genes that would not otherwise be identified with median cut-points and may suggest biological patterns of gene effects.

  16. Differences in gene expression profiles and signaling pathways in rhabdomyolysis-induced acute kidney injury.

    Science.gov (United States)

    Geng, Xiaodong; Wang, Yuanda; Hong, Quan; Yang, Jurong; Zheng, Wei; Zhang, Gang; Cai, Guangyan; Chen, Xiangmei; Wu, Di

    2015-01-01

    Rhabdomyolysis is a threatening syndrome because it causes the breakdown of skeletal muscle. Muscle destruction leads to the release of myoglobin, intracellular proteins, and electrolytes into the circulation. The aim of this study was to investigate the differences in gene expression profiles and signaling pathways upon rhabdomyolysis-induced acute kidney injury (AKI). In this study, we used glycerol-induced renal injury as a model of rhabdomyolysis-induced AKI. We analyzed data and relevant information from the Gene Expression Omnibus database (No: GSE44925). The gene expression data for three untreated mice were compared to data for five mice with rhabdomyolysis-induced AKI. The expression profiling of the three untreated mice and the five rhabdomyolysis-induced AKI mice was performed using microarray analysis. We examined the levels of Cyp3a13, Rela, Aldh7a1, Jun, CD14. And Cdkn1a using RT-PCR to determine the accuracy of the microarray results. The microarray analysis showed that there were 1050 downregulated and 659 upregulated genes in the rhabdomyolysis-induced AKI mice compared to the control group. The interactions of all differentially expressed genes in the Signal-Net were analyzed. Cyp3a13 and Rela had the most interactions with other genes. The data showed that Rela and Aldh7a1 were the key nodes and had important positions in the Signal-Net. The genes Jun, CD14, and Cdkn1a were also significantly upregulated. The pathway analysis classified the differentially expressed genes into 71 downregulated and 48 upregulated pathways including the PI3K/Akt, MAPK, and NF-κB signaling pathways. The results of this study indicate that the NF-κB, MAPK, PI3K/Akt, and apoptotic pathways are regulated in rhabdomyolysis-induced AKI.

  17. Exploring matrix factorization techniques for significant genes identification of Alzheimer’s disease microarray gene expression data

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    Hu Xiaohua

    2011-07-01

    Full Text Available Abstract Background The wide use of high-throughput DNA microarray technology provide an increasingly detailed view of human transcriptome from hundreds to thousands of genes. Although biomedical researchers typically design microarray experiments to explore specific biological contexts, the relationships between genes are hard to identified because they are complex and noisy high-dimensional data and are often hindered by low statistical power. The main challenge now is to extract valuable biological information from the colossal amount of data to gain insight into biological processes and the mechanisms of human disease. To overcome the challenge requires mathematical and computational methods that are versatile enough to capture the underlying biological features and simple enough to be applied efficiently to large datasets. Methods Unsupervised machine learning approaches provide new and efficient analysis of gene expression profiles. In our study, two unsupervised knowledge-based matrix factorization methods, independent component analysis (ICA and nonnegative matrix factorization (NMF are integrated to identify significant genes and related pathways in microarray gene expression dataset of Alzheimer’s disease. The advantage of these two approaches is they can be performed as a biclustering method by which genes and conditions can be clustered simultaneously. Furthermore, they can group genes into different categories for identifying related diagnostic pathways and regulatory networks. The difference between these two method lies in ICA assume statistical independence of the expression modes, while NMF need positivity constrains to generate localized gene expression profiles. Results In our work, we performed FastICA and non-smooth NMF methods on DNA microarray gene expression data of Alzheimer’s disease respectively. The simulation results shows that both of the methods can clearly classify severe AD samples from control samples, and

  18. FERAL : Network-based classifier with application to breast cancer outcome prediction

    NARCIS (Netherlands)

    Allahyar, A.; De Ridder, J.

    2015-01-01

    Motivation: Breast cancer outcome prediction based on gene expression profiles is an important strategy for personalize patient care. To improve performance and consistency of discovered markers of the initial molecular classifiers, network-based outcome prediction methods (NOPs) have been proposed.

  19. Optimatization of transient transformation methods to study gene expression in Musa acuminata (AAA group) cultivar Ambon Lumut

    Science.gov (United States)

    Prayuni, Kinasih; Dwivany, Fenny M.

    2015-09-01

    Banana is classified as a climateric fruit, whose ripening is regulated by ethylene. Ethylene is synthesized from ACC (1-aminocyclopropane-1-carboxylic acid) by ACC oxidase enzyme which is encoded by ACO gene. Controling an important gene expression in ethylene biosynthesis pathway has became a target to delay the ripening process. Therefore in the previous study we have designed a MaACO-RNAi construct to control MaACO gene expression. In this research, we study the effectiveness of different transient transformation methods to deliver the construct. Direct injection, with or no vaccum infiltration methods were used to deliver MaACO-RNAi construct. All of the methods succesfully deliver the construct into banana fruits based on RT-PCR result.

  20. Characterization of differentially expressed genes using high-dimensional co-expression networks

    DEFF Research Database (Denmark)

    Coelho Goncalves de Abreu, Gabriel; Labouriau, Rodrigo S.

    2010-01-01

    We present a technique to characterize differentially expressed genes in terms of their position in a high-dimensional co-expression network. The set-up of Gaussian graphical models is used to construct representations of the co-expression network in such a way that redundancy and the propagation...... that allow to make effective inference in problems with high degree of complexity (e.g. several thousands of genes) and small number of observations (e.g. 10-100) as typically occurs in high throughput gene expression studies. Taking advantage of the internal structure of decomposable graphical models, we...... construct a compact representation of the co-expression network that allows to identify the regions with high concentration of differentially expressed genes. It is argued that differentially expressed genes located in highly interconnected regions of the co-expression network are less informative than...

  1. Regulation of eucaryotic gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Brent, R.; Ptashne, M.S

    1989-05-23

    This patent describes a method of regulating the expression of a gene in a eucaryotic cell. The method consists of: providing in the eucaryotic cell, a peptide, derived from or substantially similar to a peptide of a procaryotic cell able to bind to DNA upstream from or within the gene, the amount of the peptide being sufficient to bind to the gene and thereby control expression of the gene.

  2. Expression loss and revivification of RhoB gene in ovary carcinoma carcinogenesis and development.

    Science.gov (United States)

    Liu, Yingwei; Song, Na; Ren, Kexing; Meng, Shenglan; Xie, Yao; Long, Qida; Chen, Xiancheng; Zhao, Xia

    2013-01-01

    RhoB, a member of small GTPases belonging to the Ras protein superfamily, might have a suppressive activity in cancer progression. Here, expression of RhoB gene was evaluated in human benign, borderline and malignant ovary tumors by immunostaining, with normal ovary tissue as control. Malignant tumors were assessed according to Federation Internationale de Gynecologie Obstetrique (FIGO) guidelines and classified in stage I-IV. Revivification of RhoB gene was investigated by analyzing the effect of histone deacetylase (HDAC) inhibitor trichostatin (TSA) and methyltransferase inhibitor 5-azacytidine (5-Aza) on ovarian cancer cells via RT-PCR and western blot. Apoptosis of ovary cancer cells was detected using flowcytometry and fluorescence microscopy. Subsequently, RhoB expression is detected in normal ovary epithelium, borderline tumors, and decreases significantly or lost in the majority of ovarian cancer specimen (Pcancer cells, but 5-Aza couldn't. Interference into Revivification of RhoB gene results in reduction of ovary carcinoma cell apoptosis. It is proposed that loss of RhoB expression occurs frequently in ovary carcinogenesis and progression and its expression could be regulated by histone deacetylation but not by promoter hypermethylation, which may serve as a prospective gene treatment target for the patients with ovarian malignancy not responding to standard therapies.

  3. A three-gene expression signature model for risk stratification of patients with neuroblastoma.

    Science.gov (United States)

    Garcia, Idoia; Mayol, Gemma; Ríos, José; Domenech, Gema; Cheung, Nai-Kong V; Oberthuer, André; Fischer, Matthias; Maris, John M; Brodeur, Garrett M; Hero, Barbara; Rodríguez, Eva; Suñol, Mariona; Galvan, Patricia; de Torres, Carmen; Mora, Jaume; Lavarino, Cinzia

    2012-04-01

    Neuroblastoma is an embryonal tumor with contrasting clinical courses. Despite elaborate stratification strategies, precise clinical risk assessment still remains a challenge. The purpose of this study was to develop a PCR-based predictor model to improve clinical risk assessment of patients with neuroblastoma. The model was developed using real-time PCR gene expression data from 96 samples and tested on separate expression data sets obtained from real-time PCR and microarray studies comprising 362 patients. On the basis of our prior study of differentially expressed genes in favorable and unfavorable neuroblastoma subgroups, we identified three genes, CHD5, PAFAH1B1, and NME1, strongly associated with patient outcome. The expression pattern of these genes was used to develop a PCR-based single-score predictor model. The model discriminated patients into two groups with significantly different clinical outcome [set 1: 5-year overall survival (OS): 0.93 ± 0.03 vs. 0.53 ± 0.06, 5-year event-free survival (EFS): 0.85 ± 0.04 vs. 0.042 ± 0.06, both P model was an independent marker for survival (P model robustly classified patients in the total cohort and in different clinically relevant risk subgroups. We propose for the first time in neuroblastoma, a technically simple PCR-based predictor model that could help refine current risk stratification systems. ©2012 AACR.

  4. Genome-wide identification and expression analysis of the mitogen-activated protein kinase gene family in cassava

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    Yan Yan

    2016-08-01

    Full Text Available Mitogen-activated protein kinases (MAPKs play central roles in plant developmental processes, hormone signaling transduction, and responses to abiotic stress. However, no data are currently available about the MAPK family in cassava, an important tropical crop. Herein, 21 MeMAPK genes were identified from cassava. Phylogenetic analysis indicated that MeMAPKs could be classified into four subfamilies. Gene structure analysis demonstrated that the number of introns in MeMAPK genes ranged from 1 to 10, suggesting large variation among cassava MAPK genes. Conserved motif analysis indicated that all MeMAPKs had typical protein kinase domains. Transcriptomic analysis suggested that MeMAPK genes showed differential expression patterns in distinct tissues and in response to drought stress between wild subspecies and cultivated varieties. Interaction networks and co-expression analyses revealed that crucial pathways controlled by MeMAPK networks may be involved in the differential response to drought stress in different accessions of cassava. Expression of nine selected MAPK genes showed that these genes could comprehensively respond to osmotic, salt, cold, oxidative stressors, and abscisic acid (ABA signaling. These findings yield new insights into the transcriptional control of MAPK gene expression, provide an improved understanding of abiotic stress responses and signaling transduction in cassava, and lead to potential applications in the genetic improvement of cassava cultivars.

  5. Clinical value of prognosis gene expression signatures in colorectal cancer: a systematic review.

    Directory of Open Access Journals (Sweden)

    Rebeca Sanz-Pamplona

    Full Text Available INTRODUCTION: The traditional staging system is inadequate to identify those patients with stage II colorectal cancer (CRC at high risk of recurrence or with stage III CRC at low risk. A number of gene expression signatures to predict CRC prognosis have been proposed, but none is routinely used in the clinic. The aim of this work was to assess the prediction ability and potential clinical usefulness of these signatures in a series of independent datasets. METHODS: A literature review identified 31 gene expression signatures that used gene expression data to predict prognosis in CRC tissue. The search was based on the PubMed database and was restricted to papers published from January 2004 to December 2011. Eleven CRC gene expression datasets with outcome information were identified and downloaded from public repositories. Random Forest classifier was used to build predictors from the gene lists. Matthews correlation coefficient was chosen as a measure of classification accuracy and its associated p-value was used to assess association with prognosis. For clinical usefulness evaluation, positive and negative post-tests probabilities were computed in stage II and III samples. RESULTS: Five gene signatures showed significant association with prognosis and provided reasonable prediction accuracy in their own training datasets. Nevertheless, all signatures showed low reproducibility in independent data. Stratified analyses by stage or microsatellite instability status showed significant association but limited discrimination ability, especially in stage II tumors. From a clinical perspective, the most predictive signatures showed a minor but significant improvement over the classical staging system. CONCLUSIONS: The published signatures show low prediction accuracy but moderate clinical usefulness. Although gene expression data may inform prognosis, better strategies for signature validation are needed to encourage their widespread use in the clinic.

  6. The use of genetic programming in the analysis of quantitative gene expression profiles for identification of nodal status in bladder cancer

    International Nuclear Information System (INIS)

    Mitra, Anirban P; Almal, Arpit A; George, Ben; Fry, David W; Lenehan, Peter F; Pagliarulo, Vincenzo; Cote, Richard J; Datar, Ram H; Worzel, William P

    2006-01-01

    Previous studies on bladder cancer have shown nodal involvement to be an independent indicator of prognosis and survival. This study aimed at developing an objective method for detection of nodal metastasis from molecular profiles of primary urothelial carcinoma tissues. The study included primary bladder tumor tissues from 60 patients across different stages and 5 control tissues of normal urothelium. The entire cohort was divided into training and validation sets comprised of node positive and node negative subjects. Quantitative expression profiling was performed for a panel of 70 genes using standardized competitive RT-PCR and the expression values of the training set samples were run through an iterative machine learning process called genetic programming that employed an N-fold cross validation technique to generate classifier rules of limited complexity. These were then used in a voting algorithm to classify the validation set samples into those associated with or without nodal metastasis. The generated classifier rules using 70 genes demonstrated 81% accuracy on the validation set when compared to the pathological nodal status. The rules showed a strong predilection for ICAM1, MAP2K6 and KDR resulting in gene expression motifs that cumulatively suggested a pattern ICAM1>MAP2K6>KDR for node positive cases. Additionally, the motifs showed CDK8 to be lower relative to ICAM1, and ANXA5 to be relatively high by itself in node positive tumors. Rules generated using only ICAM1, MAP2K6 and KDR were comparably robust, with a single representative rule producing an accuracy of 90% when used by itself on the validation set, suggesting a crucial role for these genes in nodal metastasis. Our study demonstrates the use of standardized quantitative gene expression values from primary bladder tumor tissues as inputs in a genetic programming system to generate classifier rules for determining the nodal status. Our method also suggests the involvement of ICAM1, MAP2K6, KDR

  7. Inferring gene expression dynamics via functional regression analysis

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    Leng Xiaoyan

    2008-01-01

    Full Text Available Abstract Background Temporal gene expression profiles characterize the time-dynamics of expression of specific genes and are increasingly collected in current gene expression experiments. In the analysis of experiments where gene expression is obtained over the life cycle, it is of interest to relate temporal patterns of gene expression associated with different developmental stages to each other to study patterns of long-term developmental gene regulation. We use tools from functional data analysis to study dynamic changes by relating temporal gene expression profiles of different developmental stages to each other. Results We demonstrate that functional regression methodology can pinpoint relationships that exist between temporary gene expression profiles for different life cycle phases and incorporates dimension reduction as needed for these high-dimensional data. By applying these tools, gene expression profiles for pupa and adult phases are found to be strongly related to the profiles of the same genes obtained during the embryo phase. Moreover, one can distinguish between gene groups that exhibit relationships with positive and others with negative associations between later life and embryonal expression profiles. Specifically, we find a positive relationship in expression for muscle development related genes, and a negative relationship for strictly maternal genes for Drosophila, using temporal gene expression profiles. Conclusion Our findings point to specific reactivation patterns of gene expression during the Drosophila life cycle which differ in characteristic ways between various gene groups. Functional regression emerges as a useful tool for relating gene expression patterns from different developmental stages, and avoids the problems with large numbers of parameters and multiple testing that affect alternative approaches.

  8. Synthetic promoter libraries- tuning of gene expression

    DEFF Research Database (Denmark)

    Hammer, Karin; Mijakovic, Ivan; Jensen, Peter Ruhdal

    2006-01-01

    knockout and strong overexpression. However, applications such as metabolic optimization and control analysis necessitate a continuous set of expression levels with only slight increments in strength to cover a specific window around the wildtype expression level of the studied gene; this requirement can......The study of gene function often requires changing the expression of a gene and evaluating the consequences. In principle, the expression of any given gene can be modulated in a quasi-continuum of discrete expression levels but the traditional approaches are usually limited to two extremes: gene...

  9. Gene expression signature of normal cell-of-origin predicts ovarian tumor outcomes.

    Directory of Open Access Journals (Sweden)

    Melissa A Merritt

    Full Text Available The potential role of the cell-of-origin in determining the tumor phenotype has been raised, but not adequately examined. We hypothesized that distinct cells-of-origin may play a role in determining ovarian tumor phenotype and outcome. Here we describe a new cell culture medium for in vitro culture of paired normal human ovarian (OV and fallopian tube (FT epithelial cells from donors without cancer. While these cells have been cultured individually for short periods of time, to our knowledge this is the first long-term culture of both cell types from the same donors. Through analysis of the gene expression profiles of the cultured OV/FT cells we identified a normal cell-of-origin gene signature that classified primary ovarian cancers into OV-like and FT-like subgroups; this classification correlated with significant differences in clinical outcomes. The identification of a prognostically significant gene expression signature derived solely from normal untransformed cells is consistent with the hypothesis that the normal cell-of-origin may be a source of ovarian tumor heterogeneity and the associated differences in tumor outcome.

  10. A cell-based in vitro alternative to identify skin sensitizers by gene expression

    International Nuclear Information System (INIS)

    Hooyberghs, Jef; Schoeters, Elke; Lambrechts, Nathalie; Nelissen, Inge; Witters, Hilda; Schoeters, Greet; Heuvel, Rosette van den

    2008-01-01

    The ethical and economic burden associated with animal testing for assessment of skin sensitization has triggered intensive research effort towards development and validation of alternative methods. In addition, new legislation on the registration and use of cosmetics and chemicals promote the use of suitable alternatives for hazard assessment. Our previous studies demonstrated that human CD34 + progenitor-derived dendritic cells from cord blood express specific gene profiles upon exposure to low molecular weight sensitizing chemicals. This paper presents a classification model based on this cell type which is successful in discriminating sensitizing chemicals from non-sensitizing chemicals based on transcriptome analysis of 13 genes. Expression profiles of a set of 10 sensitizers and 11 non-sensitizers were analyzed by RT-PCR using 9 different exposure conditions and a total of 73 donor samples. Based on these data a predictive dichotomous classifier for skin sensitizers has been constructed, which is referred to as . In a first step the dimensionality of the input data was reduced by selectively rejecting a number of exposure conditions and genes. Next, the generalization of a linear classifier was evaluated by a cross-validation which resulted in a prediction performance with a concordance of 89%, a specificity of 97% and a sensitivity of 82%. These results show that the present model may be a useful human in vitro alternative for further use in a test strategy towards the reduction of animal use for skin sensitization

  11. Differential Gene Expression in Primary Breast Tumors Associated with Lymph Node Metastasis

    International Nuclear Information System (INIS)

    Ellsworth, R.E.; Field, L.A.; Kane, J.L.; Love, B.; Hooke, J.A.; Shriver, C.D.

    2011-01-01

    Lymph node status remains one of the most useful prognostic indicators in breast cancer; however, current methods to assess nodal status disrupt the lymphatic system and may lead to secondary complications. Identification of molecular signatures discriminating lymph node-positive from lymph node-negative primary tumors would allow for stratification of patients requiring surgical assesment of lymph nodes. Primary breast tumors from women with negative (n=41) and positive (n=35) lymph node status matched for possible confounding factors were subjected to laser micro dissection and gene expression data generated. Although ANOVA analysis (P 1.5) revealed 13 differentially expressed genes, hierarchical clustering classified 90% of node-negative but only 66% of node-positive tumors correctly. The inability to derive molecular profiles of metastasis in primary tumors may reflect tumor heterogeneity, paucity of cells within the primary tumor with metastatic potential, influence of the microenvironment, or inherited host susceptibility to metastasis

  12. Differential Gene Expression in Primary Breast Tumors Associated with Lymph Node Metastasis

    Science.gov (United States)

    Ellsworth, Rachel E.; Field, Lori A.; Love, Brad; Kane, Jennifer L.; Hooke, Jeffrey A.; Shriver, Craig D.

    2011-01-01

    Lymph node status remains one of the most useful prognostic indicators in breast cancer; however, current methods to assess nodal status disrupt the lymphatic system and may lead to secondary complications. Identification of molecular signatures discriminating lymph node-positive from lymph node-negative primary tumors would allow for stratification of patients requiring surgical assesment of lymph nodes. Primary breast tumors from women with negative (n = 41) and positive (n = 35) lymph node status matched for possible confounding factors were subjected to laser microdissection and gene expression data generated. Although ANOVA analysis (P 1.5) revealed 13 differentially expressed genes, hierarchical clustering classified 90% of node-negative but only 66% of node-positive tumors correctly. The inability to derive molecular profiles of metastasis in primary tumors may reflect tumor heterogeneity, paucity of cells within the primary tumor with metastatic potential, influence of the microenvironment, or inherited host susceptibility to metastasis. PMID:22295210

  13. Differential Gene Expression in Primary Breast Tumors Associated with Lymph Node Metastasis

    Directory of Open Access Journals (Sweden)

    Rachel E. Ellsworth

    2011-01-01

    Full Text Available Lymph node status remains one of the most useful prognostic indicators in breast cancer; however, current methods to assess nodal status disrupt the lymphatic system and may lead to secondary complications. Identification of molecular signatures discriminating lymph node-positive from lymph node-negative primary tumors would allow for stratification of patients requiring surgical assesment of lymph nodes. Primary breast tumors from women with negative (=41 and positive (=35 lymph node status matched for possible confounding factors were subjected to laser microdissection and gene expression data generated. Although ANOVA analysis (1.5 revealed 13 differentially expressed genes, hierarchical clustering classified 90% of node-negative but only 66% of node-positive tumors correctly. The inability to derive molecular profiles of metastasis in primary tumors may reflect tumor heterogeneity, paucity of cells within the primary tumor with metastatic potential, influence of the microenvironment, or inherited host susceptibility to metastasis.

  14. Gene expression and functional studies of the optic nerve head astrocyte transcriptome from normal African Americans and Caucasian Americans donors.

    Directory of Open Access Journals (Sweden)

    Haixi Miao

    2008-08-01

    Full Text Available To determine whether optic nerve head (ONH astrocytes, a key cellular component of glaucomatous neuropathy, exhibit differential gene expression in primary cultures of astrocytes from normal African American (AA donors compared to astrocytes from normal Caucasian American (CA donors.We used oligonucleotide Affymetrix microarray (HG U133A & HG U133A 2.0 chips to compare gene expression levels in cultured ONH astrocytes from twelve CA and twelve AA normal age matched donor eyes. Chips were normalized with Robust Microarray Analysis (RMA in R using Bioconductor. Significant differential gene expression levels were detected using mixed effects modeling and Statistical Analysis of Microarray (SAM. Functional analysis and Gene Ontology were used to classify differentially expressed genes. Differential gene expression was validated by quantitative real time RT-PCR. Protein levels were detected by Western blots and ELISA. Cell adhesion and migration assays tested physiological responses. Glutathione (GSH assay detected levels of intracellular GSH.Multiple analyses selected 87 genes differentially expressed between normal AA and CA (P<0.01. The most relevant genes expressed in AA were categorized by function, including: signal transduction, response to stress, ECM genes, migration and cell adhesion.These data show that normal astrocytes from AA and CA normal donors display distinct expression profiles that impact astrocyte functions in the ONH. Our data suggests that differences in gene expression in ONH astrocytes may be specific to the development and/or progression of glaucoma in AA.

  15. Adaptive Evolution of Gene Expression in Drosophila.

    Science.gov (United States)

    Nourmohammad, Armita; Rambeau, Joachim; Held, Torsten; Kovacova, Viera; Berg, Johannes; Lässig, Michael

    2017-08-08

    Gene expression levels are important quantitative traits that link genotypes to molecular functions and fitness. In Drosophila, population-genetic studies have revealed substantial adaptive evolution at the genomic level, but the evolutionary modes of gene expression remain controversial. Here, we present evidence that adaptation dominates the evolution of gene expression levels in flies. We show that 64% of the observed expression divergence across seven Drosophila species are adaptive changes driven by directional selection. Our results are derived from time-resolved data of gene expression divergence across a family of related species, using a probabilistic inference method for gene-specific selection. Adaptive gene expression is stronger in specific functional classes, including regulation, sensory perception, sexual behavior, and morphology. Moreover, we identify a large group of genes with sex-specific adaptation of expression, which predominantly occurs in males. Our analysis opens an avenue to map system-wide selection on molecular quantitative traits independently of their genetic basis. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  16. Adaptive Evolution of Gene Expression in Drosophila

    Directory of Open Access Journals (Sweden)

    Armita Nourmohammad

    2017-08-01

    Full Text Available Gene expression levels are important quantitative traits that link genotypes to molecular functions and fitness. In Drosophila, population-genetic studies have revealed substantial adaptive evolution at the genomic level, but the evolutionary modes of gene expression remain controversial. Here, we present evidence that adaptation dominates the evolution of gene expression levels in flies. We show that 64% of the observed expression divergence across seven Drosophila species are adaptive changes driven by directional selection. Our results are derived from time-resolved data of gene expression divergence across a family of related species, using a probabilistic inference method for gene-specific selection. Adaptive gene expression is stronger in specific functional classes, including regulation, sensory perception, sexual behavior, and morphology. Moreover, we identify a large group of genes with sex-specific adaptation of expression, which predominantly occurs in males. Our analysis opens an avenue to map system-wide selection on molecular quantitative traits independently of their genetic basis.

  17. RRHGE: A Novel Approach to Classify the Estrogen Receptor Based Breast Cancer Subtypes

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    Ashish Saini

    2014-01-01

    Full Text Available Background. Breast cancer is the most common type of cancer among females with a high mortality rate. It is essential to classify the estrogen receptor based breast cancer subtypes into correct subclasses, so that the right treatments can be applied to lower the mortality rate. Using gene signatures derived from gene interaction networks to classify breast cancers has proven to be more reproducible and can achieve higher classification performance. However, the interactions in the gene interaction network usually contain many false-positive interactions that do not have any biological meanings. Therefore, it is a challenge to incorporate the reliability assessment of interactions when deriving gene signatures from gene interaction networks. How to effectively extract gene signatures from available resources is critical to the success of cancer classification. Methods. We propose a novel method to measure and extract the reliable (biologically true or valid interactions from gene interaction networks and incorporate the extracted reliable gene interactions into our proposed RRHGE algorithm to identify significant gene signatures from microarray gene expression data for classifying ER+ and ER− breast cancer samples. Results. The evaluation on real breast cancer samples showed that our RRHGE algorithm achieved higher classification accuracy than the existing approaches.

  18. H-ferritin-regulated microRNAs modulate gene expression in K562 cells.

    Directory of Open Access Journals (Sweden)

    Flavia Biamonte

    Full Text Available In a previous study, we showed that the silencing of the heavy subunit (FHC offerritin, the central iron storage molecule in the cell, is accompanied by a modification in global gene expression. In this work, we explored whether different FHC amounts might modulate miRNA expression levels in K562 cells and studied the impact of miRNAs in gene expression profile modifications. To this aim, we performed a miRNA-mRNA integrative analysis in K562 silenced for FHC (K562shFHC comparing it with K562 transduced with scrambled RNA (K562shRNA. Four miRNAs, namely hsa-let-7g, hsa-let-7f, hsa-let-7i and hsa-miR-125b, were significantly up-regulated in silenced cells. The remarkable down-regulation of these miRNAs, following FHC expression rescue, supports a specific relation between FHC silencing and miRNA-modulation. The integration of target predictions with miRNA and gene expression profiles led to the identification of a regulatory network which includes the miRNAs up-regulated by FHC silencing, as well as91 down-regulated putative target genes. These genes were further classified in 9 networks; the highest scoring network, "Cell Death and Survival, Hematological System Development and Function, Hematopoiesis", is composed by 18 focus molecules including RAF1 and ERK1/2. We confirmed that, following FHC silencing, ERK1/2 phosphorylation is severely impaired and that RAF1 mRNA is significantly down-regulated. Taken all together, our data indicate that, in our experimental model, FHC silencing may affect RAF1/pERK1/2 levels through the modulation of a specific set of miRNAs and add new insights in to the relationship among iron homeostasis and miRNAs.

  19. Presymptomatic Diagnosis of Celiac Disease in Predisposed Children: The Role of Gene Expression Profile.

    Science.gov (United States)

    Galatola, Martina; Cielo, Donatella; Panico, Camilla; Stellato, Pio; Malamisura, Basilio; Carbone, Lorenzo; Gianfrani, Carmen; Troncone, Riccardo; Greco, Luigi; Auricchio, Renata

    2017-09-01

    The prevalence of celiac disease (CD) has increased significantly in recent years, and risk prediction and early diagnosis have become imperative especially in at-risk families. In a previous study, we identified individuals with CD based on the expression profile of a set of candidate genes in peripheral blood monocytes. Here we evaluated the expression of a panel of CD candidate genes in peripheral blood mononuclear cells from at-risk infants long time before any symptom or production of antibodies. We analyzed the gene expression of a set of 9 candidate genes, associated with CD, in 22 human leukocyte antigen predisposed children from at-risk families for CD, studied from birth to 6 years of age. Nine of them developed CD (patients) and 13 did not (controls). We analyzed gene expression at 3 different time points (age matched in the 2 groups): 4-19 months before diagnosis, at the time of CD diagnosis, and after at least 1 year of a gluten-free diet. At similar age points, controls were also evaluated. Three genes (KIAA, TAGAP [T-cell Activation GTPase Activating Protein], and SH2B3 [SH2B Adaptor Protein 3]) were overexpressed in patients, compared with controls, at least 9 months before CD diagnosis. At a stepwise discriminant analysis, 4 genes (RGS1 [Regulator of G-protein signaling 1], TAGAP, TNFSF14 [Tumor Necrosis Factor (Ligand) Superfamily member 14], and SH2B3) differentiate patients from controls before serum antibodies production and clinical symptoms. Multivariate equation correctly classified CD from non-CD children in 95.5% of patients. The expression of a small set of candidate genes in peripheral blood mononuclear cells can predict CD at least 9 months before the appearance of any clinical and serological signs of the disease.

  20. Heterogeneity wavelet kinetics from DCE-MRI for classifying gene expression based breast cancer recurrence risk.

    Science.gov (United States)

    Mahrooghy, Majid; Ashraf, Ahmed B; Daye, Dania; Mies, Carolyn; Feldman, Michael; Rosen, Mark; Kontos, Despina

    2013-01-01

    Breast tumors are heterogeneous lesions. Intra-tumor heterogeneity presents a major challenge for cancer diagnosis and treatment. Few studies have worked on capturing tumor heterogeneity from imaging. Most studies to date consider aggregate measures for tumor characterization. In this work we capture tumor heterogeneity by partitioning tumor pixels into subregions and extracting heterogeneity wavelet kinetic (HetWave) features from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to obtain the spatiotemporal patterns of the wavelet coefficients and contrast agent uptake from each partition. Using a genetic algorithm for feature selection, and a logistic regression classifier with leave one-out cross validation, we tested our proposed HetWave features for the task of classifying breast cancer recurrence risk. The classifier based on our features gave an ROC AUC of 0.78, outperforming previously proposed kinetic, texture, and spatial enhancement variance features which give AUCs of 0.69, 0.64, and 0.65, respectively.

  1. Cancer classification through filtering progressive transductive support vector machine based on gene expression data

    Science.gov (United States)

    Lu, Xinguo; Chen, Dan

    2017-08-01

    Traditional supervised classifiers neglect a large amount of data which not have sufficient follow-up information, only work with labeled data. Consequently, the small sample size limits the advancement of design appropriate classifier. In this paper, a transductive learning method which combined with the filtering strategy in transductive framework and progressive labeling strategy is addressed. The progressive labeling strategy does not need to consider the distribution of labeled samples to evaluate the distribution of unlabeled samples, can effective solve the problem of evaluate the proportion of positive and negative samples in work set. Our experiment result demonstrate that the proposed technique have great potential in cancer prediction based on gene expression.

  2. Systematic assessment of multi-gene predictors of pan-cancer cell line sensitivity to drugs exploiting gene expression data [version 2; referees: 2 approved

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    Linh Nguyen

    2017-03-01

    Full Text Available Background: Selected gene mutations are routinely used to guide the selection of cancer drugs for a given patient tumour. Large pharmacogenomic data sets, such as those by Genomics of Drug Sensitivity in Cancer (GDSC consortium, were introduced to discover more of these single-gene markers of drug sensitivity. Very recently, machine learning regression has been used to investigate how well cancer cell line sensitivity to drugs is predicted depending on the type of molecular profile. The latter has revealed that gene expression data is the most predictive profile in the pan-cancer setting. However, no study to date has exploited GDSC data to systematically compare the performance of machine learning models based on multi-gene expression data against that of widely-used single-gene markers based on genomics data. Methods: Here we present this systematic comparison using Random Forest (RF classifiers exploiting the expression levels of 13,321 genes and an average of 501 tested cell lines per drug. To account for time-dependent batch effects in IC50 measurements, we employ independent test sets generated with more recent GDSC data than that used to train the predictors and show that this is a more realistic validation than standard k-fold cross-validation. Results and Discussion: Across 127 GDSC drugs, our results show that the single-gene markers unveiled by the MANOVA analysis tend to achieve higher precision than these RF-based multi-gene models, at the cost of generally having a poor recall (i.e. correctly detecting only a small part of the cell lines sensitive to the drug. Regarding overall classification performance, about two thirds of the drugs are better predicted by the multi-gene RF classifiers. Among the drugs with the most predictive of these models, we found pyrimethamine, sunitinib and 17-AAG. Conclusions: Thanks to this unbiased validation, we now know that this type of models can predict in vitro tumour response to some of these

  3. Characterization and expression of the cytochrome P450 gene family in diamondback moth, Plutella xylostella (L.).

    Science.gov (United States)

    Yu, Liying; Tang, Weiqi; He, Weiyi; Ma, Xiaoli; Vasseur, Liette; Baxter, Simon W; Yang, Guang; Huang, Shiguo; Song, Fengqin; You, Minsheng

    2015-03-10

    Cytochrome P450 monooxygenases are present in almost all organisms and can play vital roles in hormone regulation, metabolism of xenobiotics and in biosynthesis or inactivation of endogenous compounds. In the present study, a genome-wide approach was used to identify and analyze the P450 gene family of diamondback moth, Plutella xylostella, a destructive worldwide pest of cruciferous crops. We identified 85 putative cytochrome P450 genes from the P. xylostella genome, including 84 functional genes and 1 pseudogene. These genes were classified into 26 families and 52 subfamilies. A phylogenetic tree constructed with three additional insect species shows extensive gene expansions of P. xylostella P450 genes from clans 3 and 4. Gene expression of cytochrome P450s was quantified across multiple developmental stages (egg, larva, pupa and adult) and tissues (head and midgut) using P. xylostella strains susceptible or resistant to insecticides chlorpyrifos and fiprinol. Expression of the lepidopteran specific CYP367s predominantly occurred in head tissue suggesting a role in either olfaction or detoxification. CYP340s with abundant transposable elements and relatively high expression in the midgut probably contribute to the detoxification of insecticides or plant toxins in P. xylostella. This study will facilitate future functional studies of the P. xylostella P450s in detoxification.

  4. Identifying potential maternal genes of Bombyx mori using digital gene expression profiling

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    Xu, Pingzhen

    2018-01-01

    Maternal genes present in mature oocytes play a crucial role in the early development of silkworm. Although maternal genes have been widely studied in many other species, there has been limited research in Bombyx mori. High-throughput next generation sequencing provides a practical method for gene discovery on a genome-wide level. Herein, a transcriptome study was used to identify maternal-related genes from silkworm eggs. Unfertilized eggs from five different stages of early development were used to detect the changing situation of gene expression. The expressed genes showed different patterns over time. Seventy-six maternal genes were annotated according to homology analysis with Drosophila melanogaster. More than half of the differentially expressed maternal genes fell into four expression patterns, while the expression patterns showed a downward trend over time. The functional annotation of these material genes was mainly related to transcription factor activity, growth factor activity, nucleic acid binding, RNA binding, ATP binding, and ion binding. Additionally, twenty-two gene clusters including maternal genes were identified from 18 scaffolds. Altogether, we plotted a profile for the maternal genes of Bombyx mori using a digital gene expression profiling method. This will provide the basis for maternal-specific signature research and improve the understanding of the early development of silkworm. PMID:29462160

  5. Time-Course Gene Set Analysis for Longitudinal Gene Expression Data.

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    Boris P Hejblum

    2015-06-01

    Full Text Available Gene set analysis methods, which consider predefined groups of genes in the analysis of genomic data, have been successfully applied for analyzing gene expression data in cross-sectional studies. The time-course gene set analysis (TcGSA introduced here is an extension of gene set analysis to longitudinal data. The proposed method relies on random effects modeling with maximum likelihood estimates. It allows to use all available repeated measurements while dealing with unbalanced data due to missing at random (MAR measurements. TcGSA is a hypothesis driven method that identifies a priori defined gene sets with significant expression variations over time, taking into account the potential heterogeneity of expression within gene sets. When biological conditions are compared, the method indicates if the time patterns of gene sets significantly differ according to these conditions. The interest of the method is illustrated by its application to two real life datasets: an HIV therapeutic vaccine trial (DALIA-1 trial, and data from a recent study on influenza and pneumococcal vaccines. In the DALIA-1 trial TcGSA revealed a significant change in gene expression over time within 69 gene sets during vaccination, while a standard univariate individual gene analysis corrected for multiple testing as well as a standard a Gene Set Enrichment Analysis (GSEA for time series both failed to detect any significant pattern change over time. When applied to the second illustrative data set, TcGSA allowed the identification of 4 gene sets finally found to be linked with the influenza vaccine too although they were found to be associated to the pneumococcal vaccine only in previous analyses. In our simulation study TcGSA exhibits good statistical properties, and an increased power compared to other approaches for analyzing time-course expression patterns of gene sets. The method is made available for the community through an R package.

  6. Gene expression signature in organized and growth arrested mammaryacini predicts good outcome in breast cancer

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    Fournier, Marcia V.; Martin, Katherine J.; Kenny, Paraic A.; Xhaja, Kris; Bosch, Irene; Yaswen, Paul; Bissell, Mina J.

    2006-02-08

    To understand how non-malignant human mammary epithelial cells (HMEC) transit from a disorganized proliferating to an organized growth arrested state, and to relate this process to the changes that occur in breast cancer, we studied gene expression changes in non-malignant HMEC grown in three-dimensional cultures, and in a previously published panel of microarray data for 295 breast cancer samples. We hypothesized that the gene expression pattern of organized and growth arrested mammary acini would share similarities with breast tumors with good prognoses. Using Affymetrix HG-U133A microarrays, we analyzed the expression of 22,283 gene transcripts in two HMEC cell lines, 184 (finite life span) and HMT3522 S1 (immortal non-malignant), on successive days post-seeding in a laminin-rich extracellular matrix assay. Both HMECs underwent growth arrest in G0/G1 and differentiated into polarized acini between days 5 and 7. We identified gene expression changes with the same temporal pattern in both lines. We show that genes that are significantly lower in the organized, growth arrested HMEC than in their proliferating counterparts can be used to classify breast cancer patients into poor and good prognosis groups with high accuracy. This study represents a novel unsupervised approach to identifying breast cancer markers that may be of use clinically.

  7. Functional dissection of drought-responsive gene expression patterns in Cynodon dactylon L.

    Science.gov (United States)

    Kim, Changsoo; Lemke, Cornelia; Paterson, Andrew H

    2009-05-01

    Water deficit is one of the main abiotic factors that affect plant productivity in subtropical regions. To identify genes induced during the water stress response in Bermudagrass (Cynodon dactylon), cDNA macroarrays were used. The macroarray analysis identified 189 drought-responsive candidate genes from C. dactylon, of which 120 were up-regulated and 69 were down-regulated. The candidate genes were classified into seven groups by cluster analysis of expression levels across two intensities and three durations of imposed stress. Annotation using BLASTX suggested that up-regulated genes may be involved in proline biosynthesis, signal transduction pathways, protein repair systems, and removal of toxins, while down-regulated genes were mostly related to basic plant metabolism such as photosynthesis and glycolysis. The functional classification of gene ontology (GO) was consistent with the BLASTX results, also suggesting some crosstalk between abiotic and biotic stress. Comparative analysis of cis-regulatory elements from the candidate genes implicated specific elements in drought response in Bermudagrass. Although only a subset of genes was studied, Bermudagrass shared many drought-responsive genes and cis-regulatory elements with other botanical models, supporting a strategy of cross-taxon application of drought-responsive genes, regulatory cues, and physiological-genetic information.

  8. Inverse dose-rate-effects on the expressions of extra-cellular matrix-related genes in low-dose-rate γ-ray irradiated murine cells

    International Nuclear Information System (INIS)

    Sugihara, Takashi; Tanaka, Kimio; Oghiso, Yoichi; Murano, Hayato

    2008-01-01

    Based on the results of previous microarray analyses of murine NIH3T3/PG13Luc cells irradiated with continuous low-dose-rate (LDR) γ-ray or end-high-dose-rate-irradiations (end-HDR) at the end of the LDR-irradiation period, the inverse dose-rate-effects on gene expression levels were observed. To compare differences of the effects between LDR-irradiation and HDR-irradiation, HDR-irradiations at 2 different times, one (ini-HDR) at the same time at the start of LDR-irradiation and the other (end-HDR), were performed. The up-regulated genes were classified into two types, in which one was up-regulated in LDR-, ini-HDR-, and end-HDR irradiation such as Cdkn1a and Ccng1, which were reported as p53-dependent genes, and the other was up-regulated in LDR- and ini-HDR irradiations such as pro-collagen TypeIa2/Colla2, TenascinC/Tnc, and Fibulin5/Fbln5, which were reported as extra-cellular matrix-related (ECM) genes. The time dependent gene expression patterns in LDR-irradiation were also classified into two types, in which one was an early response such as in Cdkn1a and Ccng1 and the other was a delayed response such as the ECM genes which have no linearity to total dose. The protein expression pattern of Cdkn1a increased dose dependently in LDR- and end-HDR-irradiations, but those of p53Ser15/18 and MDM2 in LDR-irradiations were different from end-HDR-irradiations. Furthermore, the gene expression levels of the ECM genes in embryonic fibroblasts from p53-deficient mice were not increased by LDR- and end-HDR-irradiation, so the delayed expressions of the ECM genes seem to be regulated by p53. Consequently, the inverse dose-rate-effects on the expression levels of the ECM genes in LDR- and end-HDR-irradiations may be explained from different time responses by p53 status. (author)

  9. Logic Learning Machine and standard supervised methods for Hodgkin's lymphoma prognosis using gene expression data and clinical variables.

    Science.gov (United States)

    Parodi, Stefano; Manneschi, Chiara; Verda, Damiano; Ferrari, Enrico; Muselli, Marco

    2018-03-01

    This study evaluates the performance of a set of machine learning techniques in predicting the prognosis of Hodgkin's lymphoma using clinical factors and gene expression data. Analysed samples from 130 Hodgkin's lymphoma patients included a small set of clinical variables and more than 54,000 gene features. Machine learning classifiers included three black-box algorithms ( k-nearest neighbour, Artificial Neural Network, and Support Vector Machine) and two methods based on intelligible rules (Decision Tree and the innovative Logic Learning Machine method). Support Vector Machine clearly outperformed any of the other methods. Among the two rule-based algorithms, Logic Learning Machine performed better and identified a set of simple intelligible rules based on a combination of clinical variables and gene expressions. Decision Tree identified a non-coding gene ( XIST) involved in the early phases of X chromosome inactivation that was overexpressed in females and in non-relapsed patients. XIST expression might be responsible for the better prognosis of female Hodgkin's lymphoma patients.

  10. The functional landscape of mouse gene expression

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    Zhang Wen

    2004-12-01

    Full Text Available Abstract Background Large-scale quantitative analysis of transcriptional co-expression has been used to dissect regulatory networks and to predict the functions of new genes discovered by genome sequencing in model organisms such as yeast. Although the idea that tissue-specific expression is indicative of gene function in mammals is widely accepted, it has not been objectively tested nor compared with the related but distinct strategy of correlating gene co-expression as a means to predict gene function. Results We generated microarray expression data for nearly 40,000 known and predicted mRNAs in 55 mouse tissues, using custom-built oligonucleotide arrays. We show that quantitative transcriptional co-expression is a powerful predictor of gene function. Hundreds of functional categories, as defined by Gene Ontology 'Biological Processes', are associated with characteristic expression patterns across all tissues, including categories that bear no overt relationship to the tissue of origin. In contrast, simple tissue-specific restriction of expression is a poor predictor of which genes are in which functional categories. As an example, the highly conserved mouse gene PWP1 is widely expressed across different tissues but is co-expressed with many RNA-processing genes; we show that the uncharacterized yeast homolog of PWP1 is required for rRNA biogenesis. Conclusions We conclude that 'functional genomics' strategies based on quantitative transcriptional co-expression will be as fruitful in mammals as they have been in simpler organisms, and that transcriptional control of mammalian physiology is more modular than is generally appreciated. Our data and analyses provide a public resource for mammalian functional genomics.

  11. Expression of Sox genes in tooth development.

    Science.gov (United States)

    Kawasaki, Katsushige; Kawasaki, Maiko; Watanabe, Momoko; Idrus, Erik; Nagai, Takahiro; Oommen, Shelly; Maeda, Takeyasu; Hagiwara, Nobuko; Que, Jianwen; Sharpe, Paul T; Ohazama, Atsushi

    2015-01-01

    Members of the Sox gene family play roles in many biological processes including organogenesis. We carried out comparative in situ hybridization analysis of seventeen sox genes (Sox1-14, 17, 18, 21) during murine odontogenesis from the epithelial thickening to the cytodifferentiation stages. Localized expression of five Sox genes (Sox6, 9, 13, 14 and 21) was observed in tooth bud epithelium. Sox13 showed restricted expression in the primary enamel knots. At the early bell stage, three Sox genes (Sox8, 11, 17 and 21) were expressed in pre-ameloblasts, whereas two others (Sox5 and 18) showed expression in odontoblasts. Sox genes thus showed a dynamic spatio-temporal expression during tooth development.

  12. Profiling Gene Expression in Germinating Brassica Roots.

    Science.gov (United States)

    Park, Myoung Ryoul; Wang, Yi-Hong; Hasenstein, Karl H

    2014-01-01

    Based on previously developed solid-phase gene extraction (SPGE) we examined the mRNA profile in primary roots of Brassica rapa seedlings for highly expressed genes like ACT7 (actin7), TUB (tubulin1), UBQ (ubiquitin), and low expressed GLK (glucokinase) during the first day post-germination. The assessment was based on the mRNA load of the SPGE probe of about 2.1 ng. The number of copies of the investigated genes changed spatially along the length of primary roots. The expression level of all genes differed significantly at each sample position. Among the examined genes ACT7 expression was most even along the root. UBQ was highest at the tip and root-shoot junction (RS). TUB and GLK showed a basipetal gradient. The temporal expression of UBQ was highest in the MZ 9 h after primary root emergence and higher than at any other sample position. Expressions of GLK in EZ and RS increased gradually over time. SPGE extraction is the result of oligo-dT and oligo-dA hybridization and the results illustrate that SPGE can be used for gene expression profiling at high spatial and temporal resolution. SPGE needles can be used within two weeks when stored at 4 °C. Our data indicate that gene expression studies that are based on the entire root miss important differences in gene expression that SPGE is able to resolve for example growth adjustments during gravitropism.

  13. Development and validation of a gene expression-based signature to predict distant metastasis in locoregionally advanced nasopharyngeal carcinoma: a retrospective, multicentre, cohort study.

    Science.gov (United States)

    Tang, Xin-Ran; Li, Ying-Qin; Liang, Shao-Bo; Jiang, Wei; Liu, Fang; Ge, Wen-Xiu; Tang, Ling-Long; Mao, Yan-Ping; He, Qing-Mei; Yang, Xiao-Jing; Zhang, Yuan; Wen, Xin; Zhang, Jian; Wang, Ya-Qin; Zhang, Pan-Pan; Sun, Ying; Yun, Jing-Ping; Zeng, Jing; Li, Li; Liu, Li-Zhi; Liu, Na; Ma, Jun

    2018-03-01

    Gene expression patterns can be used as prognostic biomarkers in various types of cancers. We aimed to identify a gene expression pattern for individual distant metastatic risk assessment in patients with locoregionally advanced nasopharyngeal carcinoma. In this multicentre, retrospective, cohort analysis, we included 937 patients with locoregionally advanced nasopharyngeal carcinoma from three Chinese hospitals: the Sun Yat-sen University Cancer Center (Guangzhou, China), the Affiliated Hospital of Guilin Medical University (Guilin, China), and the First People's Hospital of Foshan (Foshan, China). Using microarray analysis, we profiled mRNA gene expression between 24 paired locoregionally advanced nasopharyngeal carcinoma tumours from patients at Sun Yat-sen University Cancer Center with or without distant metastasis after radical treatment. Differentially expressed genes were examined using digital expression profiling in a training cohort (Guangzhou training cohort; n=410) to build a gene classifier using a penalised regression model. We validated the prognostic accuracy of this gene classifier in an internal validation cohort (Guangzhou internal validation cohort, n=204) and two external independent cohorts (Guilin cohort, n=165; Foshan cohort, n=158). The primary endpoint was distant metastasis-free survival. Secondary endpoints were disease-free survival and overall survival. We identified 137 differentially expressed genes between metastatic and non-metastatic locoregionally advanced nasopharyngeal carcinoma tissues. A distant metastasis gene signature for locoregionally advanced nasopharyngeal carcinoma (DMGN) that consisted of 13 genes was generated to classify patients into high-risk and low-risk groups in the training cohort. Patients with high-risk scores in the training cohort had shorter distant metastasis-free survival (hazard ratio [HR] 4·93, 95% CI 2·99-8·16; padvanced nasopharyngeal carcinoma and might be able to predict which patients benefit

  14. Gene expression profiling of canine osteosarcoma reveals genes associated with short and long survival times

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    Rao Nagesha AS

    2009-09-01

    Full Text Available Abstract Background Gene expression profiling of spontaneous tumors in the dog offers a unique translational opportunity to identify prognostic biomarkers and signaling pathways that are common to both canine and human. Osteosarcoma (OS accounts for approximately 80% of all malignant bone tumors in the dog. Canine OS are highly comparable with their human counterpart with respect to histology, high metastatic rate and poor long-term survival. This study investigates the prognostic gene profile among thirty-two primary canine OS using canine specific cDNA microarrays representing 20,313 genes to identify genes and cellular signaling pathways associated with survival. This, the first report of its kind in dogs with OS, also demonstrates the advantages of cross-species comparison with human OS. Results The 32 tumors were classified into two prognostic groups based on survival time (ST. They were defined as short survivors (dogs with poor prognosis: surviving fewer than 6 months and long survivors (dogs with better prognosis: surviving 6 months or longer. Fifty-one transcripts were found to be differentially expressed, with common upregulation of these genes in the short survivors. The overexpressed genes in short survivors are associated with possible roles in proliferation, drug resistance or metastasis. Several deregulated pathways identified in the present study, including Wnt signaling, Integrin signaling and Chemokine/cytokine signaling are comparable to the pathway analysis conducted on human OS gene profiles, emphasizing the value of the dog as an excellent model for humans. Conclusion A molecular-based method for discrimination of outcome for short and long survivors is useful for future prognostic stratification at initial diagnosis, where genes and pathways associated with cell cycle/proliferation, drug resistance and metastasis could be potential targets for diagnosis and therapy. The similarities between human and canine OS makes the

  15. Unstable Expression of Commonly Used Reference Genes in Rat Pancreatic Islets Early after Isolation Affects Results of Gene Expression Studies.

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    Lucie Kosinová

    Full Text Available The use of RT-qPCR provides a powerful tool for gene expression studies; however, the proper interpretation of the obtained data is crucially dependent on accurate normalization based on stable reference genes. Recently, strong evidence has been shown indicating that the expression of many commonly used reference genes may vary significantly due to diverse experimental conditions. The isolation of pancreatic islets is a complicated procedure which creates severe mechanical and metabolic stress leading possibly to cellular damage and alteration of gene expression. Despite of this, freshly isolated islets frequently serve as a control in various gene expression and intervention studies. The aim of our study was to determine expression of 16 candidate reference genes and one gene of interest (F3 in isolated rat pancreatic islets during short-term cultivation in order to find a suitable endogenous control for gene expression studies. We compared the expression stability of the most commonly used reference genes and evaluated the reliability of relative and absolute quantification using RT-qPCR during 0-120 hrs after isolation. In freshly isolated islets, the expression of all tested genes was markedly depressed and it increased several times throughout the first 48 hrs of cultivation. We observed significant variability among samples at 0 and 24 hrs but substantial stabilization from 48 hrs onwards. During the first 48 hrs, relative quantification failed to reflect the real changes in respective mRNA concentrations while in the interval 48-120 hrs, the relative expression generally paralleled the results determined by absolute quantification. Thus, our data call into question the suitability of relative quantification for gene expression analysis in pancreatic islets during the first 48 hrs of cultivation, as the results may be significantly affected by unstable expression of reference genes. However, this method could provide reliable information

  16. Sequence homology and expression profile of genes associated with DNA repair pathways in Mycobacterium leprae.

    Science.gov (United States)

    Sharma, Mukul; Vedithi, Sundeep Chaitanya; Das, Madhusmita; Roy, Anindya; Ebenezer, Mannam

    2017-01-01

    Survival of Mycobacterium leprae, the causative bacteria for leprosy, in the human host is dependent to an extent on the ways in which its genome integrity is retained. DNA repair mechanisms protect bacterial DNA from damage induced by various stress factors. The current study is aimed at understanding the sequence and functional annotation of DNA repair genes in M. leprae. T he genome of M. leprae was annotated using sequence alignment tools to identify DNA repair genes that have homologs in Mycobacterium tuberculosis and Escherichia coli. A set of 96 genes known to be involved in DNA repair mechanisms in E. coli and Mycobacteriaceae were chosen as a reference. Among these, 61 were identified in M. leprae based on sequence similarity and domain architecture. The 61 were classified into 36 characterized gene products (59%), 11 hypothetical proteins (18%), and 14 pseudogenes (23%). All these genes have homologs in M. tuberculosis and 49 (80.32%) in E. coli. A set of 12 genes which are absent in E. coli were present in M. leprae and in Mycobacteriaceae. These 61 genes were further investigated for their expression profiles in the whole transcriptome microarray data of M. leprae which was obtained from the signal intensities of 60bp probes, tiling the entire genome with 10bp overlaps. It was noted that transcripts corresponding to all the 61 genes were identified in the transcriptome data with varying expression levels ranging from 0.18 to 2.47 fold (normalized with 16SrRNA). The mRNA expression levels of a representative set of seven genes ( four annotated and three hypothetical protein coding genes) were analyzed using quantitative Polymerase Chain Reaction (qPCR) assays with RNA extracted from skin biopsies of 10 newly diagnosed, untreated leprosy cases. It was noted that RNA expression levels were higher for genes involved in homologous recombination whereas the genes with a low level of expression are involved in the direct repair pathway. This study provided

  17. ICGE: an R package for detecting relevant clusters and atypical units in gene expression

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    Irigoien Itziar

    2012-02-01

    Full Text Available Abstract Background Gene expression technologies have opened up new ways to diagnose and treat cancer and other diseases. Clustering algorithms are a useful approach with which to analyze genome expression data. They attempt to partition the genes into groups exhibiting similar patterns of variation in expression level. An important problem associated with gene classification is to discern whether the clustering process can find a relevant partition as well as the identification of new genes classes. There are two key aspects to classification: the estimation of the number of clusters, and the decision as to whether a new unit (gene, tumor sample... belongs to one of these previously identified clusters or to a new group. Results ICGE is a user-friendly R package which provides many functions related to this problem: identify the number of clusters using mixed variables, usually found by applied biomedical researchers; detect whether the data have a cluster structure; identify whether a new unit belongs to one of the pre-identified clusters or to a novel group, and classify new units into the corresponding cluster. The functions in the ICGE package are accompanied by help files and easy examples to facilitate its use. Conclusions We demonstrate the utility of ICGE by analyzing simulated and real data sets. The results show that ICGE could be very useful to a broad research community.

  18. Comprehensive analysis of gene expression patterns of hedgehog-related genes

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    Baillie David

    2006-10-01

    Full Text Available Abstract Background The Caenorhabditis elegans genome encodes ten proteins that share sequence similarity with the Hedgehog signaling molecule through their C-terminal autoprocessing Hint/Hog domain. These proteins contain novel N-terminal domains, and C. elegans encodes dozens of additional proteins containing only these N-terminal domains. These gene families are called warthog, groundhog, ground-like and quahog, collectively called hedgehog (hh-related genes. Previously, the expression pattern of seventeen genes was examined, which showed that they are primarily expressed in the ectoderm. Results With the completion of the C. elegans genome sequence in November 2002, we reexamined and identified 61 hh-related ORFs. Further, we identified 49 hh-related ORFs in C. briggsae. ORF analysis revealed that 30% of the genes still had errors in their predictions and we improved these predictions here. We performed a comprehensive expression analysis using GFP fusions of the putative intergenic regulatory sequence with one or two transgenic lines for most genes. The hh-related genes are expressed in one or a few of the following tissues: hypodermis, seam cells, excretory duct and pore cells, vulval epithelial cells, rectal epithelial cells, pharyngeal muscle or marginal cells, arcade cells, support cells of sensory organs, and neuronal cells. Using time-lapse recordings, we discovered that some hh-related genes are expressed in a cyclical fashion in phase with molting during larval development. We also generated several translational GFP fusions, but they did not show any subcellular localization. In addition, we also studied the expression patterns of two genes with similarity to Drosophila frizzled, T23D8.1 and F27E11.3A, and the ortholog of the Drosophila gene dally-like, gpn-1, which is a heparan sulfate proteoglycan. The two frizzled homologs are expressed in a few neurons in the head, and gpn-1 is expressed in the pharynx. Finally, we compare the

  19. Radioactive cDNA microarray (II): Gene expression profiling of antidepressant treatment by human cDNA microarray

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    Lee, Ji Hye; Kang, Rhee Hun; Ham, Byung Joo; Lee, Min Su; Shin, Kyung Ho; Choe, Jae Gol; Kim, Meyoung Kon [College of Medicine, Univ. of Korea, Seoul (Korea, Republic of)

    2003-07-01

    Major depressive disorder is a prevalent psychiatric disorder in primary care, associated with impaired patient functioning and well-being. Fluoxetine is a selective serotonin-reuptake inhibitors (SSRIs) and is a commonly prescribed antidepressant compound. Its action is primarily attributed to selective inhibition of the reuptake of serotonin (5-hydroxytryptamine) in the central nervous system. Objectives ; the aims of this study were two-fold: (1) to determine the usefulness for investigation of the transcription profiles in depression patients, and (2) to assess the differences in gene expression profiles between positive response group and negative response groups by fluoxetine treatment. This study included 53 patients with major depression (26 in positive response group with antidepressant treatment, 27 in negative response group with antidepressant treatment), and 53 healthy controls. To examine the difference of gene expression profile in depression patients, radioactive complementary DNA microarrays were used to evaluate changes in the expression of 1,152 genes in total. Using 33p-labeled probes, this method provided highly sensitive gene expression profiles including brain receptors, drug metabolism, and cellular signaling. Gene transcription profiles were classified into several categories in accordance with the antidepressant gene-regulation. The gene profiles were significantly up-(22 genes) and down-(16 genes) regulated in the positive response group when compared to the control group. Also, in the negative response group, 35 genes were up-regulated and 8 genes were down-regulated when compared to the control group. Consequently, we demonstrated that radioactive human cDNA microarray is highly likely to be an efficient technology for evaluating the gene regulation of antidepressants, such as selective serotonin-reuptake inhibitors (SSRIs), by using high-throughput biotechnology.

  20. Radioactive cDNA microarray (II): Gene expression profiling of antidepressant treatment by human cDNA microarray

    International Nuclear Information System (INIS)

    Lee, Ji Hye; Kang, Rhee Hun; Ham, Byung Joo; Lee, Min Su; Shin, Kyung Ho; Choe, Jae Gol; Kim, Meyoung Kon

    2003-01-01

    Major depressive disorder is a prevalent psychiatric disorder in primary care, associated with impaired patient functioning and well-being. Fluoxetine is a selective serotonin-reuptake inhibitors (SSRIs) and is a commonly prescribed antidepressant compound. Its action is primarily attributed to selective inhibition of the reuptake of serotonin (5-hydroxytryptamine) in the central nervous system. Objectives ; the aims of this study were two-fold: (1) to determine the usefulness for investigation of the transcription profiles in depression patients, and (2) to assess the differences in gene expression profiles between positive response group and negative response groups by fluoxetine treatment. This study included 53 patients with major depression (26 in positive response group with antidepressant treatment, 27 in negative response group with antidepressant treatment), and 53 healthy controls. To examine the difference of gene expression profile in depression patients, radioactive complementary DNA microarrays were used to evaluate changes in the expression of 1,152 genes in total. Using 33p-labeled probes, this method provided highly sensitive gene expression profiles including brain receptors, drug metabolism, and cellular signaling. Gene transcription profiles were classified into several categories in accordance with the antidepressant gene-regulation. The gene profiles were significantly up-(22 genes) and down-(16 genes) regulated in the positive response group when compared to the control group. Also, in the negative response group, 35 genes were up-regulated and 8 genes were down-regulated when compared to the control group. Consequently, we demonstrated that radioactive human cDNA microarray is highly likely to be an efficient technology for evaluating the gene regulation of antidepressants, such as selective serotonin-reuptake inhibitors (SSRIs), by using high-throughput biotechnology

  1. Simple Comparative Analyses of Differentially Expressed Gene Lists May Overestimate Gene Overlap.

    Science.gov (United States)

    Lawhorn, Chelsea M; Schomaker, Rachel; Rowell, Jonathan T; Rueppell, Olav

    2018-04-16

    Comparing the overlap between sets of differentially expressed genes (DEGs) within or between transcriptome studies is regularly used to infer similarities between biological processes. Significant overlap between two sets of DEGs is usually determined by a simple test. The number of potentially overlapping genes is compared to the number of genes that actually occur in both lists, treating every gene as equal. However, gene expression is controlled by transcription factors that bind to a variable number of transcription factor binding sites, leading to variation among genes in general variability of their expression. Neglecting this variability could therefore lead to inflated estimates of significant overlap between DEG lists. With computer simulations, we demonstrate that such biases arise from variation in the control of gene expression. Significant overlap commonly arises between two lists of DEGs that are randomly generated, assuming that the control of gene expression is variable among genes but consistent between corresponding experiments. More overlap is observed when transcription factors are specific to their binding sites and when the number of genes is considerably higher than the number of different transcription factors. In contrast, overlap between two DEG lists is always lower than expected when the genetic architecture of expression is independent between the two experiments. Thus, the current methods for determining significant overlap between DEGs are potentially confounding biologically meaningful overlap with overlap that arises due to variability in control of expression among genes, and more sophisticated approaches are needed.

  2. Methods for monitoring multiple gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Berka, Randy [Davis, CA; Bachkirova, Elena [Davis, CA; Rey, Michael [Davis, CA

    2012-05-01

    The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

  3. Methods for monitoring multiple gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Berka, Randy; Bachkirova, Elena; Rey, Michael

    2013-10-01

    The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

  4. Determinants of human adipose tissue gene expression

    DEFF Research Database (Denmark)

    Viguerie, Nathalie; Montastier, Emilie; Maoret, Jean-José

    2012-01-01

    weight maintenance diets. For 175 genes, opposite regulation was observed during calorie restriction and weight maintenance phases, independently of variations in body weight. Metabolism and immunity genes showed inverse profiles. During the dietary intervention, network-based analyses revealed strong...... interconnection between expression of genes involved in de novo lipogenesis and components of the metabolic syndrome. Sex had a marked influence on AT expression of 88 transcripts, which persisted during the entire dietary intervention and after control for fat mass. In women, the influence of body mass index...... on expression of a subset of genes persisted during the dietary intervention. Twenty-two genes revealed a metabolic syndrome signature common to men and women. Genetic control of AT gene expression by cis signals was observed for 46 genes. Dietary intervention, sex, and cis genetic variants independently...

  5. Gene Expression Profiles for Predicting Metastasis in Breast Cancer: A Cross-Study Comparison of Classification Methods

    Directory of Open Access Journals (Sweden)

    Mark Burton

    2012-01-01

    Full Text Available Machine learning has increasingly been used with microarray gene expression data and for the development of classifiers using a variety of methods. However, method comparisons in cross-study datasets are very scarce. This study compares the performance of seven classification methods and the effect of voting for predicting metastasis outcome in breast cancer patients, in three situations: within the same dataset or across datasets on similar or dissimilar microarray platforms. Combining classification results from seven classifiers into one voting decision performed significantly better during internal validation as well as external validation in similar microarray platforms than the underlying classification methods. When validating between different microarray platforms, random forest, another voting-based method, proved to be the best performing method. We conclude that voting based classifiers provided an advantage with respect to classifying metastasis outcome in breast cancer patients.

  6. Endometrial gene expression profile of pregnant sows with extreme phenotypes for reproductive efficiency.

    Science.gov (United States)

    Córdoba, S; Balcells, I; Castelló, A; Ovilo, C; Noguera, J L; Timoneda, O; Sánchez, A

    2015-10-05

    Prolificacy can directly impact porcine profitability, but large genetic variation and low heritability have been found regarding litter size among porcine breeds. To identify key differences in gene expression associated to swine reproductive efficiency, we performed a transcriptome analysis of sows' endometrium from an Iberian x Meishan F2 population at day 30-32 of gestation, classified according to their estimated breeding value (EBV) as high (H, EBV > 0) and low (L, EBV ratio = 3.50), PTHLH (p = 0.03; H/L ratio = 3.69), MMP8 (p = 0.01; H/L ratio =4.41) and SCNN1G (p = 0.04; H/L ratio = 3.42). Although selected miRNAs showed similar expression levels between H and L groups, significant correlation was found between the expression level of ssc-miR-133a (p < 0.01) and ssc-miR-92a (p < 0.01) and validated genes. These results provide a better understanding of the genetic architecture of prolificacy-related traits and embryo implantation failure in pigs.

  7. Identification of a developmental gene expression signature, including HOX genes, for the normal human colonic crypt stem cell niche: overexpression of the signature parallels stem cell overpopulation during colon tumorigenesis.

    Science.gov (United States)

    Bhatlekar, Seema; Addya, Sankar; Salunek, Moreh; Orr, Christopher R; Surrey, Saul; McKenzie, Steven; Fields, Jeremy Z; Boman, Bruce M

    2014-01-15

    Our goal was to identify a unique gene expression signature for human colonic stem cells (SCs). Accordingly, we determined the gene expression pattern for a known SC-enriched region--the crypt bottom. Colonic crypts and isolated crypt subsections (top, middle, and bottom) were purified from fresh, normal, human, surgical specimens. We then used an innovative strategy that used two-color microarrays (∼18,500 genes) to compare gene expression in the crypt bottom with expression in the other crypt subsections (middle or top). Array results were validated by PCR and immunostaining. About 25% of genes analyzed were expressed in crypts: 88 preferentially in the bottom, 68 in the middle, and 131 in the top. Among genes upregulated in the bottom, ∼30% were classified as growth and/or developmental genes including several in the PI3 kinase pathway, a six-transmembrane protein STAMP1, and two homeobox (HOXA4, HOXD10) genes. qPCR and immunostaining validated that HOXA4 and HOXD10 are selectively expressed in the normal crypt bottom and are overexpressed in colon carcinomas (CRCs). Immunostaining showed that HOXA4 and HOXD10 are co-expressed with the SC markers CD166 and ALDH1 in cells at the normal crypt bottom, and the number of these co-expressing cells is increased in CRCs. Thus, our findings show that these two HOX genes are selectively expressed in colonic SCs and that HOX overexpression in CRCs parallels the SC overpopulation that occurs during CRC development. Our study suggests that developmental genes play key roles in the maintenance of normal SCs and crypt renewal, and contribute to the SC overpopulation that drives colon tumorigenesis.

  8. Gene expression changes for antioxidants pathways in the mouse cochlea: relations to age-related hearing deficits.

    Directory of Open Access Journals (Sweden)

    Sherif F Tadros

    Full Text Available Age-related hearing loss - presbycusis - is the number one neurodegenerative disorder and top communication deficit of our aged population. Like many aging disorders of the nervous system, damage from free radicals linked to production of reactive oxygen and/or nitrogen species (ROS and RNS, respectively may play key roles in disease progression. The efficacy of the antioxidant systems, e.g., glutathione and thioredoxin, is an important factor in pathophysiology of the aging nervous system. In this investigation, relations between the expression of antioxidant-related genes in the auditory portion of the inner ear - cochlea, and age-related hearing loss was explored for CBA/CaJ mice. Forty mice were classified into four groups according to age and degree of hearing loss. Cochlear mRNA samples were collected and cDNA generated. Using Affymetrix® GeneChip, the expressions of 56 antioxidant-related gene probes were analyzed to estimate the differences in gene expression between the four subject groups. The expression of Glutathione peroxidase 6, Gpx6; Thioredoxin reductase 1, Txnrd1; Isocitrate dehydrogenase 1, Idh1; and Heat shock protein 1, Hspb1; were significantly different, or showed large fold-change differences between subject groups. The Gpx6, Txnrd1 and Hspb1 gene expression changes were validated using qPCR. The Gpx6 gene was upregulated while the Txnrd1 gene was downregulated with age/hearing loss. The Hspb1 gene was found to be downregulated in middle-aged animals as well as those with mild presbycusis, whereas it was upregulated in those with severe presbycusis. These results facilitate development of future interventions to predict, prevent or slow down the progression of presbycusis.

  9. Social Regulation of Gene Expression in Threespine Sticklebacks.

    Directory of Open Access Journals (Sweden)

    Anna K Greenwood

    Full Text Available Identifying genes that are differentially expressed in response to social interactions is informative for understanding the molecular basis of social behavior. To address this question, we described changes in gene expression as a result of differences in the extent of social interactions. We housed threespine stickleback (Gasterosteus aculeatus females in either group conditions or individually for one week, then measured levels of gene expression in three brain regions using RNA-sequencing. We found that numerous genes in the hindbrain/cerebellum had altered expression in response to group or individual housing. However, relatively few genes were differentially expressed in either the diencephalon or telencephalon. The list of genes upregulated in fish from social groups included many genes related to neural development and cell adhesion as well as genes with functions in sensory signaling, stress, and social and reproductive behavior. The list of genes expressed at higher levels in individually-housed fish included several genes previously identified as regulated by social interactions in other animals. The identified genes are interesting targets for future research on the molecular mechanisms of normal social interactions.

  10. A constructive approach to gene expression dynamics

    International Nuclear Information System (INIS)

    Ochiai, T.; Nacher, J.C.; Akutsu, T.

    2004-01-01

    Recently, experiments on mRNA abundance (gene expression) have revealed that gene expression shows a stationary organization described by a scale-free distribution. Here we propose a constructive approach to gene expression dynamics which restores the scale-free exponent and describes the intermediate state dynamics. This approach requires only one assumption: Markov property

  11. On the statistical assessment of classifiers using DNA microarray data

    Directory of Open Access Journals (Sweden)

    Carella M

    2006-08-01

    Full Text Available Abstract Background In this paper we present a method for the statistical assessment of cancer predictors which make use of gene expression profiles. The methodology is applied to a new data set of microarray gene expression data collected in Casa Sollievo della Sofferenza Hospital, Foggia – Italy. The data set is made up of normal (22 and tumor (25 specimens extracted from 25 patients affected by colon cancer. We propose to give answers to some questions which are relevant for the automatic diagnosis of cancer such as: Is the size of the available data set sufficient to build accurate classifiers? What is the statistical significance of the associated error rates? In what ways can accuracy be considered dependant on the adopted classification scheme? How many genes are correlated with the pathology and how many are sufficient for an accurate colon cancer classification? The method we propose answers these questions whilst avoiding the potential pitfalls hidden in the analysis and interpretation of microarray data. Results We estimate the generalization error, evaluated through the Leave-K-Out Cross Validation error, for three different classification schemes by varying the number of training examples and the number of the genes used. The statistical significance of the error rate is measured by using a permutation test. We provide a statistical analysis in terms of the frequencies of the genes involved in the classification. Using the whole set of genes, we found that the Weighted Voting Algorithm (WVA classifier learns the distinction between normal and tumor specimens with 25 training examples, providing e = 21% (p = 0.045 as an error rate. This remains constant even when the number of examples increases. Moreover, Regularized Least Squares (RLS and Support Vector Machines (SVM classifiers can learn with only 15 training examples, with an error rate of e = 19% (p = 0.035 and e = 18% (p = 0.037 respectively. Moreover, the error rate

  12. Stably Expressed Genes Involved in Basic Cellular Functions.

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    Kejian Wang

    Full Text Available Stably Expressed Genes (SEGs whose expression varies within a narrow range may be involved in core cellular processes necessary for basic functions. To identify such genes, we re-analyzed existing RNA-Seq gene expression profiles across 11 organs at 4 developmental stages (from immature to old age in both sexes of F344 rats (n = 4/group; 320 samples. Expression changes (calculated as the maximum expression / minimum expression for each gene of >19000 genes across organs, ages, and sexes ranged from 2.35 to >109-fold, with a median of 165-fold. The expression of 278 SEGs was found to vary ≤4-fold and these genes were significantly involved in protein catabolism (proteasome and ubiquitination, RNA transport, protein processing, and the spliceosome. Such stability of expression was further validated in human samples where the expression variability of the homologous human SEGs was significantly lower than that of other genes in the human genome. It was also found that the homologous human SEGs were generally less subject to non-synonymous mutation than other genes, as would be expected of stably expressed genes. We also found that knockout of SEG homologs in mouse models was more likely to cause complete preweaning lethality than non-SEG homologs, corroborating the fundamental roles played by SEGs in biological development. Such stably expressed genes and pathways across life-stages suggest that tight control of these processes is important in basic cellular functions and that perturbation by endogenous (e.g., genetics or exogenous agents (e.g., drugs, environmental factors may cause serious adverse effects.

  13. Lithium ions induce prestalk-associated gene expression and inhibit prespore gene expression in Dictyostelium discoideum

    NARCIS (Netherlands)

    Peters, Dorien J.M.; Lookeren Campagne, Michiel M. van; Haastert, Peter J.M. van; Spek, Wouter; Schaap, Pauline

    1989-01-01

    We investigated the effect of Li+ on two types of cyclic AMP-regulated gene expression and on basal and cyclic AMP-stimulated inositol 1,4,5-trisphosphate (Ins(1,4,5)P3) levels. Li+ effectively inhibits cyclic AMP-induced prespore gene expression, half-maximal inhibition occurring at about 2mM-LiCl.

  14. Genome-Wide Identification and Transcriptome-Based Expression Profiling of the Sox Gene Family in the Nile Tilapia (Oreochromis niloticus).

    Science.gov (United States)

    Wei, Ling; Yang, Chao; Tao, Wenjing; Wang, Deshou

    2016-02-23

    The Sox transcription factor family is characterized with the presence of a Sry-related high-mobility group (HMG) box and plays important roles in various biological processes in animals, including sex determination and differentiation, and the development of multiple organs. In this study, 27 Sox genes were identified in the genome of the Nile tilapia (Oreochromis niloticus), and were classified into seven groups. The members of each group of the tilapia Sox genes exhibited a relatively conserved exon-intron structure. Comparative analysis showed that the Sox gene family has undergone an expansion in tilapia and other teleost fishes following their whole genome duplication, and group K only exists in teleosts. Transcriptome-based analysis demonstrated that most of the tilapia Sox genes presented stage-specific and/or sex-dimorphic expressions during gonadal development, and six of the group B Sox genes were specifically expressed in the adult brain. Our results provide a better understanding of gene structure and spatio-temporal expression of the Sox gene family in tilapia, and will be useful for further deciphering the roles of the Sox genes during sex determination and gonadal development in teleosts.

  15. Genome-Wide Identification and Transcriptome-Based Expression Profiling of the Sox Gene Family in the Nile Tilapia (Oreochromis niloticus

    Directory of Open Access Journals (Sweden)

    Ling Wei

    2016-02-01

    Full Text Available The Sox transcription factor family is characterized with the presence of a Sry-related high-mobility group (HMG box and plays important roles in various biological processes in animals, including sex determination and differentiation, and the development of multiple organs. In this study, 27 Sox genes were identified in the genome of the Nile tilapia (Oreochromis niloticus, and were classified into seven groups. The members of each group of the tilapia Sox genes exhibited a relatively conserved exon-intron structure. Comparative analysis showed that the Sox gene family has undergone an expansion in tilapia and other teleost fishes following their whole genome duplication, and group K only exists in teleosts. Transcriptome-based analysis demonstrated that most of the tilapia Sox genes presented stage-specific and/or sex-dimorphic expressions during gonadal development, and six of the group B Sox genes were specifically expressed in the adult brain. Our results provide a better understanding of gene structure and spatio-temporal expression of the Sox gene family in tilapia, and will be useful for further deciphering the roles of the Sox genes during sex determination and gonadal development in teleosts.

  16. Identification of genes differentially expressed in Mikania micrantha during Cuscuta campestris infection by suppression subtractive hybridization.

    Science.gov (United States)

    Li, Dong-Mei; Staehelin, Christian; Zhang, Yi-Shun; Peng, Shao-Lin

    2009-09-01

    The influence of Cuscuta campestris on its host Mikania micrantha has been studied with respect to biomass accumulation, physiology and ecology. Molecular events of this parasitic plant-plant interaction are poorly understood, however. In this study, we identified novel genes from M. micrantha induced by C. campestris infection. Genes expressed upon parasitization by C. campestris at early post-penetration stages were investigated by construction and characterization of subtracted cDNA libraries from shoots and stems of M. micrantha. Three hundred and three presumably up-regulated expressed sequence tags (ESTs) were identified and classified in functional categories, such as "metabolism", "cell defence and stress", "transcription factor", "signal transduction", "transportation" and "photosynthesis". In shoots and stems of infected M. micrantha, genes associated with defence responses and cell wall modifications were induced, confirming similar data from other parasitic plant-plant interactions. However, gene expression profiles in infected shoots and stems were found to be different. Compared to infected shoots, more genes induced in response to biotic and abiotic stress factors were identified in infected stems. Furthermore, database comparisons revealed a notable number of M. micrantha ESTs that matched genes with unknown function. Expression analysis by quantitative real-time RT-PCR of 21 genes (from different functional categories) showed significantly increased levels for 13 transcripts in response to C. campestris infection. In conclusion, this study provides an overview of genes from parasitized M. micrantha at early post-penetration stages. The acquired data form the basis for a molecular understanding of host reactions in response to parasitic plants.

  17. Assessment of gene expression profiles in peripheral occlusive arterial disease.

    Science.gov (United States)

    Bubenek, Serban; Nastase, Anca; Niculescu, Ana Maria; Baila, Sorin; Herlea, Vlad; Lazar, Vadimir; Paslaru, Liliana; Botezatu, Anca; Tomescu, Dana; Popescu, Irinel; Dima, Simona

    2012-01-01

    Molecular events responsible for the onset and progression of peripheral occlusive arterial disease (POAD) are incompletely understood. Gene expression profiling may point out relevant features of the disease. Tissue samples were collected as operatory waste from a total of 36 patients with (n = 18) and without (n = 18) POAD. The tissues were histologically evaluated, and the patients with POAD were classified according to Leriche-Fontaine (LF) classification: 11% with stage IIB, 22% with stage III, and 67% with stage IV. Total RNA was isolated from all samples and hybridized onto Agilent 4×44K Oligo microarray slides. The bioinformatic analysis identified genes differentially expressed between control and pathologic tissues. Ten genes with a fold change ≥ 2 (1 with a fold change ≥ 1.8) were selected for quantitative polymerase chain reaction validation (GPC3, CFD, GDF10, ITLN1, TSPAN8, MMP28, NNMT, SERPINA5, LUM, and FDXR). C-reactive protein (CRP) was assessed with a specific assay, while nicotinamide N-methyltransferase (NNMT) was evaluated in the patient serum by enzyme-linked immunosorbent assay. A multiple regression analysis showed that the level of CRP in the serum is correlated with the POAD LF stages (r(2) = 0.22, P = 0.046) and that serum NNMT is higher in IV LF POAD patients (P = 0.005). The mRNA gene expression of LUM is correlated with the LF stage (r(2) = 0.45, P = 0.009), and the mRNA level of ITLN1 is correlated with the ankle-brachial index (r(2) = 0.42, P = 0.008). Our analysis shows that NNMT, ITLN1, LUM, CFD, and TSPAN8 in combination with other known markers, such as CRP, could be evaluated as a panel of biomarkers of POAD. Copyright © 2012 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved.

  18. Classification of early-stage non-small cell lung cancer by weighing gene expression profiles with connectivity information.

    Science.gov (United States)

    Zhang, Ao; Tian, Suyan

    2018-05-01

    Pathway-based feature selection algorithms, which utilize biological information contained in pathways to guide which features/genes should be selected, have evolved quickly and become widespread in the field of bioinformatics. Based on how the pathway information is incorporated, we classify pathway-based feature selection algorithms into three major categories-penalty, stepwise forward, and weighting. Compared to the first two categories, the weighting methods have been underutilized even though they are usually the simplest ones. In this article, we constructed three different genes' connectivity information-based weights for each gene and then conducted feature selection upon the resulting weighted gene expression profiles. Using both simulations and a real-world application, we have demonstrated that when the data-driven connectivity information constructed from the data of specific disease under study is considered, the resulting weighted gene expression profiles slightly outperform the original expression profiles. In summary, a big challenge faced by the weighting method is how to estimate pathway knowledge-based weights more accurately and precisely. Only until the issue is conquered successfully will wide utilization of the weighting methods be impossible. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Dynamic Response Genes in CD4+ T Cells Reveal a Network of Interactive Proteins that Classifies Disease Activity in Multiple Sclerosis

    Directory of Open Access Journals (Sweden)

    Sandra Hellberg

    2016-09-01

    Full Text Available Multiple sclerosis (MS is a chronic inflammatory disease of the CNS and has a varying disease course as well as variable response to treatment. Biomarkers may therefore aid personalized treatment. We tested whether in vitro activation of MS patient-derived CD4+ T cells could reveal potential biomarkers. The dynamic gene expression response to activation was dysregulated in patient-derived CD4+ T cells. By integrating our findings with genome-wide association studies, we constructed a highly connected MS gene module, disclosing cell activation and chemotaxis as central components. Changes in several module genes were associated with differences in protein levels, which were measurable in cerebrospinal fluid and were used to classify patients from control individuals. In addition, these measurements could predict disease activity after 2 years and distinguish low and high responders to treatment in two additional, independent cohorts. While further validation is needed in larger cohorts prior to clinical implementation, we have uncovered a set of potentially promising biomarkers.

  20. Aberrant expression of the tyrosine kinase receptor EphA4 and the transcription factor twist in Sézary syndrome identified by gene expression analysis.

    Science.gov (United States)

    van Doorn, Remco; Dijkman, Remco; Vermeer, Maarten H; Out-Luiting, Jacoba J; van der Raaij-Helmer, Elisabeth M H; Willemze, Rein; Tensen, Cornelis P

    2004-08-15

    Sézary syndrome (Sz) is a malignancy of CD4+ memory skin-homing T cells and presents with erythroderma, lymphadenopathy, and peripheral blood involvement. To gain more insight into the molecular features of Sz, oligonucleotide array analysis was performed comparing gene expression patterns of CD4+ T cells from peripheral blood of patients with Sz with those of patients with erythroderma secondary to dermatitis and healthy controls. Using unsupervised hierarchical clustering gene, expression patterns of T cells from patients with Sz were classified separately from those of benign T cells. One hundred twenty-three genes were identified as significantly differentially expressed and had an average fold change exceeding 2. T cells from patients with Sz demonstrated decreased expression of the following hematopoietic malignancy-linked tumor suppressor genes: TGF-beta receptor II, Mxi1, Riz1, CREB-binding protein, BCL11a, STAT4, and Forkhead Box O1A. Moreover, the tyrosine kinase receptor EphA4 and the potentially oncogenic transcription factor Twist were highly and selectively expressed in T cells of patients with Sz. High expression of EphA4 and Twist was also observed in lesional skin biopsy specimens of a subset of patients with cutaneous T cell lymphomas related to Sz, whereas their expression was nearly undetectable in benign T cells or in skin lesions of patients with inflammatory dermatoses. Detection of EphA4 and Twist may be used in the molecular diagnosis of Sz and related cutaneous T-cell lymphomas. Furthermore, the membrane-bound EphA4 receptor may serve as a target for directed therapeutic intervention.

  1. Gene expression in Citrus sinensis fruit tissues harvested from huanglongbing-infected trees: comparison with girdled fruit.

    Science.gov (United States)

    Liao, Hui-Ling; Burns, Jacqueline K

    2012-05-01

    Distribution of viable Candidatus Liberibacter asiaticus (CaLas) in sweet orange fruit and leaves ('Hamlin' and 'Valencia') and transcriptomic changes associated with huanglongbing (HLB) infection in fruit tissues are reported. Viable CaLas was present in most fruit tissues tested in HLB trees, with the highest titre detected in vascular tissue near the calyx abscission zone. Transcriptomic changes associated with HLB infection were analysed in flavedo (FF), vascular tissue (VT), and juice vesicles (JV) from symptomatic (SY), asymptomatic (AS), and healthy (H) fruit. In SY 'Hamlin', HLB altered the expression of more genes in FF and VT than in JV, whereas in SY 'Valencia', the number of genes whose expression was changed by HLB was similar in these tissues. The expression of more genes was altered in SY 'Valencia' JV than in SY 'Hamlin' JV. More genes were also affected in AS 'Valencia' FF and VT than in AS 'Valencia' JV. Most genes whose expression was changed by HLB were classified as transporters or involved in carbohydrate metabolism. Physiological characteristics of HLB-infected and girdled fruit were compared to differentiate between HLB-specific and carbohydrate metabolism-related symptoms. SY and girdled fruit were smaller than H and ungirdled fruit, respectively, with poor juice quality. However, girdling did not cause misshapen fruit or differential peel coloration. Quantitative PCR analysis indicated that many selected genes changed their expression significantly in SY flavedo but not in girdled flavedo. Mechanisms regulating development of HLB symptoms may lie in the host disease response rather than being a direct consequence of carbohydrate starvation.

  2. Validation of commonly used reference genes for sleep-related gene expression studies

    Directory of Open Access Journals (Sweden)

    Castro Rosa MRPS

    2009-05-01

    Full Text Available Abstract Background Sleep is a restorative process and is essential for maintenance of mental and physical health. In an attempt to understand the complexity of sleep, multidisciplinary strategies, including genetic approaches, have been applied to sleep research. Although quantitative real time PCR has been used in previous sleep-related gene expression studies, proper validation of reference genes is currently lacking. Thus, we examined the effect of total or paradoxical sleep deprivation (TSD or PSD on the expression stability of the following frequently used reference genes in brain and blood: beta-actin (b-actin, beta-2-microglobulin (B2M, glyceraldehyde-3-phosphate dehydrogenase (GAPDH, and hypoxanthine guanine phosphoribosyl transferase (HPRT. Results Neither TSD nor PSD affected the expression stability of all tested genes in both tissues indicating that b-actin, B2M, GAPDH and HPRT are appropriate reference genes for the sleep-related gene expression studies. In order to further verify these results, the relative expression of brain derived neurotrophic factor (BDNF and glycerol-3-phosphate dehydrogenase1 (GPD1 was evaluated in brain and blood, respectively. The normalization with each of four reference genes produced similar pattern of expression in control and sleep deprived rats, but subtle differences in the magnitude of expression fold change were observed which might affect the statistical significance. Conclusion This study demonstrated that sleep deprivation does not alter the expression stability of commonly used reference genes in brain and blood. Nonetheless, the use of multiple reference genes in quantitative RT-PCR is required for the accurate results.

  3. Hormonal modulation of breast cancer gene expression: implications for intrinsic subtyping in pre-menopausal women

    Directory of Open Access Journals (Sweden)

    Sarah M Bernhardt

    2016-11-01

    Full Text Available Clinics are increasingly adopting gene expression profiling to diagnose breast cancer subtype, providing an intrinsic, molecular portrait of the tumour. For example, the PAM50-based Prosigna test quantifies expression of 50 key genes to classify breast cancer subtype, and this method of classification has been demonstrated to be superior over traditional immunohistochemical methods that detect proteins, to predict risk of disease recurrence. However, these tests were largely developed and validated using breast cancer samples from post-menopausal women. Thus, the accuracy of such tests has not been explored in the context of the hormonal fluctuations in estrogen and progesterone that occur during the menstrual cycle in pre-menopausal women. Concordance between traditional methods of subtyping and the new tests in pre-menopausal women is likely to depend on the stage of the menstrual cycle at which the tissue sample is taken, and the relative effect of hormones on expression of genes versus proteins. The lack of knowledge around the effect of fluctuating estrogen and progesterone on gene expression in breast cancer patients raises serious concerns for intrinsic subtyping in pre-menopausal women, which comprise about 25% of breast cancer diagnoses. Further research on the impact of the menstrual cycle on intrinsic breast cancer profiling is required if pre-menopausal women are to benefit from the new technology of intrinsic subtyping.

  4. Stochastic gene expression in Arabidopsis thaliana.

    Science.gov (United States)

    Araújo, Ilka Schultheiß; Pietsch, Jessica Magdalena; Keizer, Emma Mathilde; Greese, Bettina; Balkunde, Rachappa; Fleck, Christian; Hülskamp, Martin

    2017-12-14

    Although plant development is highly reproducible, some stochasticity exists. This developmental stochasticity may be caused by noisy gene expression. Here we analyze the fluctuation of protein expression in Arabidopsis thaliana. Using the photoconvertible KikGR marker, we show that the protein expressions of individual cells fluctuate over time. A dual reporter system was used to study extrinsic and intrinsic noise of marker gene expression. We report that extrinsic noise is higher than intrinsic noise and that extrinsic noise in stomata is clearly lower in comparison to several other tissues/cell types. Finally, we show that cells are coupled with respect to stochastic protein expression in young leaves, hypocotyls and roots but not in mature leaves. Our data indicate that stochasticity of gene expression can vary between tissues/cell types and that it can be coupled in a non-cell-autonomous manner.

  5. Quantitative utilization of prior biological knowledge in the Bayesian network modeling of gene expression data

    Directory of Open Access Journals (Sweden)

    Gao Shouguo

    2011-08-01

    Full Text Available Abstract Background Bayesian Network (BN is a powerful approach to reconstructing genetic regulatory networks from gene expression data. However, expression data by itself suffers from high noise and lack of power. Incorporating prior biological knowledge can improve the performance. As each type of prior knowledge on its own may be incomplete or limited by quality issues, integrating multiple sources of prior knowledge to utilize their consensus is desirable. Results We introduce a new method to incorporate the quantitative information from multiple sources of prior knowledge. It first uses the Naïve Bayesian classifier to assess the likelihood of functional linkage between gene pairs based on prior knowledge. In this study we included cocitation in PubMed and schematic similarity in Gene Ontology annotation. A candidate network edge reservoir is then created in which the copy number of each edge is proportional to the estimated likelihood of linkage between the two corresponding genes. In network simulation the Markov Chain Monte Carlo sampling algorithm is adopted, and samples from this reservoir at each iteration to generate new candidate networks. We evaluated the new algorithm using both simulated and real gene expression data including that from a yeast cell cycle and a mouse pancreas development/growth study. Incorporating prior knowledge led to a ~2 fold increase in the number of known transcription regulations recovered, without significant change in false positive rate. In contrast, without the prior knowledge BN modeling is not always better than a random selection, demonstrating the necessity in network modeling to supplement the gene expression data with additional information. Conclusion our new development provides a statistical means to utilize the quantitative information in prior biological knowledge in the BN modeling of gene expression data, which significantly improves the performance.

  6. Deriving Trading Rules Using Gene Expression Programming

    Directory of Open Access Journals (Sweden)

    Adrian VISOIU

    2011-01-01

    Full Text Available This paper presents how buy and sell trading rules are generated using gene expression programming with special setup. Market concepts are presented and market analysis is discussed with emphasis on technical analysis and quantitative methods. The use of genetic algorithms in deriving trading rules is presented. Gene expression programming is applied in a form where multiple types of operators and operands are used. This gives birth to multiple gene contexts and references between genes in order to keep the linear structure of the gene expression programming chromosome. The setup of multiple gene contexts is presented. The case study shows how to use the proposed gene setup to derive trading rules encoded by Boolean expressions, using a dataset with the reference exchange rates between the Euro and the Romanian leu. The conclusions highlight the positive results obtained in deriving useful trading rules.

  7. Using PCR to Target Misconceptions about Gene Expression

    Directory of Open Access Journals (Sweden)

    Leslie K. Wright

    2013-02-01

    Full Text Available We present a PCR-based laboratory exercise that can be used with first- or second-year biology students to help overcome common misconceptions about gene expression. Biology students typically do not have a clear understanding of the difference between genes (DNA and gene expression (mRNA/protein and often believe that genes exist in an organism or cell only when they are expressed. This laboratory exercise allows students to carry out a PCR-based experiment designed to challenge their misunderstanding of the difference between genes and gene expression. Students first transform E. coli with an inducible GFP gene containing plasmid and observe induced and un-induced colonies. The following exercise creates cognitive dissonance when actual PCR results contradict their initial (incorrect predictions of the presence of the GFP gene in transformed cells. Field testing of this laboratory exercise resulted in learning gains on both knowledge and application questions on concepts related to genes and gene expression.

  8. Differential gene expression during Trypanosoma cruzi metacyclogenesis

    Directory of Open Access Journals (Sweden)

    Marco Aurelio Krieger

    1999-09-01

    Full Text Available The transformation of epimastigotes into metacyclic trypomastigotes involves changes in the pattern of expressed genes, resulting in important morphological and functional differences between these developmental forms of Trypanosoma cruzi. In order to identify and characterize genes involved in triggering the metacyclogenesis process and in conferring to metacyclic trypomastigotes their stage specific biological properties, we have developed a method allowing the isolation of genes specifically expressed when comparing two close related cell populations (representation of differential expression or RDE. The method is based on the PCR amplification of gene sequences selected by hybridizing and subtracting the populations in such a way that after some cycles of hybridization-amplification genes specific to a given population are highly enriched. The use of this method in the analysis of differential gene expression during T. cruzi metacyclogenesis (6 hr and 24 hr of differentiation and metacyclic trypomastigotes resulted in the isolation of several clones from each time point. Northern blot analysis showed that some genes are transiently expressed (6 hr and 24 hr differentiating cells, while others are present in differentiating cells and in metacyclic trypomastigotes. Nucleotide sequencing of six clones characterized so far showed that they do not display any homology to gene sequences available in the GeneBank.

  9. Conditional gene expression in the mouse using a Sleeping Beauty gene-trap transposon

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    Hackett Perry B

    2006-06-01

    Full Text Available Abstract Background Insertional mutagenesis techniques with transposable elements have been popular among geneticists studying model organisms from E. coli to Drosophila and, more recently, the mouse. One such element is the Sleeping Beauty (SB transposon that has been shown in several studies to be an effective insertional mutagen in the mouse germline. SB transposon vector studies have employed different functional elements and reporter molecules to disrupt and report the expression of endogenous mouse genes. We sought to generate a transposon system that would be capable of reporting the expression pattern of a mouse gene while allowing for conditional expression of a gene of interest in a tissue- or temporal-specific pattern. Results Here we report the systematic development and testing of a transposon-based gene-trap system incorporating the doxycycline-repressible Tet-Off (tTA system that is capable of activating the expression of genes under control of a Tet response element (TRE promoter. We demonstrate that the gene trap system is fully functional in vitro by introducing the "gene-trap tTA" vector into human cells by transposition and identifying clones that activate expression of a TRE-luciferase transgene in a doxycycline-dependent manner. In transgenic mice, we mobilize gene-trap tTA vectors, discover parameters that can affect germline mobilization rates, and identify candidate gene insertions to demonstrate the in vivo functionality of the vector system. We further demonstrate that the gene-trap can act as a reporter of endogenous gene expression and it can be coupled with bioluminescent imaging to identify genes with tissue-specific expression patterns. Conclusion Akin to the GAL4/UAS system used in the fly, we have made progress developing a tool for mutating and revealing the expression of mouse genes by generating the tTA transactivator in the presence of a secondary TRE-regulated reporter molecule. A vector like the gene

  10. Analysis of multiplex gene expression maps obtained by voxelation

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    Smith Desmond J

    2009-04-01

    Full Text Available Abstract Background Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between gene expression maps obtained by voxelation and gene functions. Results To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged gene expression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the gene expression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of gene expression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar gene expression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in

  11. Analysis of multiplex gene expression maps obtained by voxelation.

    Science.gov (United States)

    An, Li; Xie, Hongbo; Chin, Mark H; Obradovic, Zoran; Smith, Desmond J; Megalooikonomou, Vasileios

    2009-04-29

    Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between gene expression maps obtained by voxelation and gene functions. To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged gene expression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the gene expression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of gene expression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar gene expression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in cortex and corpus callosum. The experimental

  12. A comparative gene expression database for invertebrates

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    Ormestad Mattias

    2011-08-01

    Full Text Available Abstract Background As whole genome and transcriptome sequencing gets cheaper and faster, a great number of 'exotic' animal models are emerging, rapidly adding valuable data to the ever-expanding Evo-Devo field. All these new organisms serve as a fantastic resource for the research community, but the sheer amount of data, some published, some not, makes detailed comparison of gene expression patterns very difficult to summarize - a problem sometimes even noticeable within a single lab. The need to merge existing data with new information in an organized manner that is publicly available to the research community is now more necessary than ever. Description In order to offer a homogenous way of storing and handling gene expression patterns from a variety of organisms, we have developed the first web-based comparative gene expression database for invertebrates that allows species-specific as well as cross-species gene expression comparisons. The database can be queried by gene name, developmental stage and/or expression domains. Conclusions This database provides a unique tool for the Evo-Devo research community that allows the retrieval, analysis and comparison of gene expression patterns within or among species. In addition, this database enables a quick identification of putative syn-expression groups that can be used to initiate, among other things, gene regulatory network (GRN projects.

  13. Genetic Variants Contribute to Gene Expression Variability in Humans

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    Hulse, Amanda M.; Cai, James J.

    2013-01-01

    Expression quantitative trait loci (eQTL) studies have established convincing relationships between genetic variants and gene expression. Most of these studies focused on the mean of gene expression level, but not the variance of gene expression level (i.e., gene expression variability). In the present study, we systematically explore genome-wide association between genetic variants and gene expression variability in humans. We adapt the double generalized linear model (dglm) to simultaneously fit the means and the variances of gene expression among the three possible genotypes of a biallelic SNP. The genomic loci showing significant association between the variances of gene expression and the genotypes are termed expression variability QTL (evQTL). Using a data set of gene expression in lymphoblastoid cell lines (LCLs) derived from 210 HapMap individuals, we identify cis-acting evQTL involving 218 distinct genes, among which 8 genes, ADCY1, CTNNA2, DAAM2, FERMT2, IL6, PLOD2, SNX7, and TNFRSF11B, are cross-validated using an extra expression data set of the same LCLs. We also identify ∼300 trans-acting evQTL between >13,000 common SNPs and 500 randomly selected representative genes. We employ two distinct scenarios, emphasizing single-SNP and multiple-SNP effects on expression variability, to explain the formation of evQTL. We argue that detecting evQTL may represent a novel method for effectively screening for genetic interactions, especially when the multiple-SNP influence on expression variability is implied. The implication of our results for revealing genetic mechanisms of gene expression variability is discussed. PMID:23150607

  14. Correction of gene expression data

    DEFF Research Database (Denmark)

    Darbani Shirvanehdeh, Behrooz; Stewart, C. Neal, Jr.; Noeparvar, Shahin

    2014-01-01

    This report investigates for the first time the potential inter-treatment bias source of cell number for gene expression studies. Cell-number bias can affect gene expression analysis when comparing samples with unequal total cellular RNA content or with different RNA extraction efficiencies....... For maximal reliability of analysis, therefore, comparisons should be performed at the cellular level. This could be accomplished using an appropriate correction method that can detect and remove the inter-treatment bias for cell-number. Based on inter-treatment variations of reference genes, we introduce...

  15. Gene expression in colorectal cancer

    DEFF Research Database (Denmark)

    Birkenkamp-Demtroder, Karin; Christensen, Lise Lotte; Olesen, Sanne Harder

    2002-01-01

    Understanding molecular alterations in colorectal cancer (CRC) is needed to define new biomarkers and treatment targets. We used oligonucleotide microarrays to monitor gene expression of about 6,800 known genes and 35,000 expressed sequence tags (ESTs) on five pools (four to six samples in each...... pool) of total RNA from left-sided sporadic colorectal carcinomas. We compared normal tissue to carcinoma tissue from Dukes' stages A-D (noninvasive to distant metastasis) and identified 908 known genes and 4,155 ESTs that changed remarkably from normal to tumor tissue. Based on intensive filtering 226...

  16. Multiscale Embedded Gene Co-expression Network Analysis.

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    Won-Min Song

    2015-11-01

    Full Text Available Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3, the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA by: i introducing quality control of co-expression similarities, ii parallelizing embedded network construction, and iii developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs. We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA. MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

  17. Multiscale Embedded Gene Co-expression Network Analysis.

    Science.gov (United States)

    Song, Won-Min; Zhang, Bin

    2015-11-01

    Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

  18. Genome-wide identification and comparative expression analysis reveal a rapid expansion and functional divergence of duplicated genes in the WRKY gene family of cabbage, Brassica oleracea var. capitata.

    Science.gov (United States)

    Yao, Qiu-Yang; Xia, En-Hua; Liu, Fei-Hu; Gao, Li-Zhi

    2015-02-15

    WRKY transcription factors (TFs), one of the ten largest TF families in higher plants, play important roles in regulating plant development and resistance. To date, little is known about the WRKY TF family in Brassica oleracea. Recently, the completed genome sequence of cabbage (B. oleracea var. capitata) allows us to systematically analyze WRKY genes in this species. A total of 148 WRKY genes were characterized and classified into seven subgroups that belong to three major groups. Phylogenetic and synteny analyses revealed that the repertoire of cabbage WRKY genes was derived from a common ancestor shared with Arabidopsis thaliana. The B. oleracea WRKY genes were found to be preferentially retained after the whole-genome triplication (WGT) event in its recent ancestor, suggesting that the WGT event had largely contributed to a rapid expansion of the WRKY gene family in B. oleracea. The analysis of RNA-Seq data from various tissues (i.e., roots, stems, leaves, buds, flowers and siliques) revealed that most of the identified WRKY genes were positively expressed in cabbage, and a large portion of them exhibited patterns of differential and tissue-specific expression, demonstrating that these gene members might play essential roles in plant developmental processes. Comparative analysis of the expression level among duplicated genes showed that gene expression divergence was evidently presented among cabbage WRKY paralogs, indicating functional divergence of these duplicated WRKY genes. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. Tumor Classification Using High-Order Gene Expression Profiles Based on Multilinear ICA

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    Ming-gang Du

    2009-01-01

    Full Text Available Motivation. Independent Components Analysis (ICA maximizes the statistical independence of the representational components of a training gene expression profiles (GEP ensemble, but it cannot distinguish relations between the different factors, or different modes, and it is not available to high-order GEP Data Mining. In order to generalize ICA, we introduce Multilinear-ICA and apply it to tumor classification using high order GEP. Firstly, we introduce the basis conceptions and operations of tensor and recommend Support Vector Machine (SVM classifier and Multilinear-ICA. Secondly, the higher score genes of original high order GEP are selected by using t-statistics and tabulate tensors. Thirdly, the tensors are performed by Multilinear-ICA. Finally, the SVM is used to classify the tumor subtypes. Results. To show the validity of the proposed method, we apply it to tumor classification using high order GEP. Though we only use three datasets, the experimental results show that the method is effective and feasible. Through this survey, we hope to gain some insight into the problem of high order GEP tumor classification, in aid of further developing more effective tumor classification algorithms.

  20. Comparative molecular neuroanatomy of mammalian neocortex: what can gene expression tell us about areas and layers?

    Science.gov (United States)

    Watakabe, Akiya

    2009-04-01

    It is over 100 years since Brodmann proposed the homology of layer and area structure of the cerebral cortex across species. His proposal was based on the extensive comparative analyses of various mammalian brains. Although such homology is now well accepted, the recent data in our laboratory showed striking variations of gene expression patterns across areas and species. Are cortical layers and areas really homologous? If they are, to what extent and how are they similar or different? We are trying to answer these questions by identifying the homologous neuronal types common to various areas and species. Toward this goal, we started to classify the cortical pyramidal neurons by expression of particular sets of genes. By using fluorescent double in situ hybridization combined with retrograde tracers, we are characterizing the gene expression phenotypes and projection specificity of cortical excitatory neuron types. In this review, I discuss the recent findings in our laboratory in light of the past and present knowledge about cortical cell types, which provides insight to the homology (and lack thereof) of the mammalian neocortical organization.

  1. Discovering time-lagged rules from microarray data using gene profile classifiers

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    Ponzoni Ignacio

    2011-04-01

    Full Text Available Abstract Background Gene regulatory networks have an essential role in every process of life. In this regard, the amount of genome-wide time series data is becoming increasingly available, providing the opportunity to discover the time-delayed gene regulatory networks that govern the majority of these molecular processes. Results This paper aims at reconstructing gene regulatory networks from multiple genome-wide microarray time series datasets. In this sense, a new model-free algorithm called GRNCOP2 (Gene Regulatory Network inference by Combinatorial OPtimization 2, which is a significant evolution of the GRNCOP algorithm, was developed using combinatorial optimization of gene profile classifiers. The method is capable of inferring potential time-delay relationships with any span of time between genes from various time series datasets given as input. The proposed algorithm was applied to time series data composed of twenty yeast genes that are highly relevant for the cell-cycle study, and the results were compared against several related approaches. The outcomes have shown that GRNCOP2 outperforms the contrasted methods in terms of the proposed metrics, and that the results are consistent with previous biological knowledge. Additionally, a genome-wide study on multiple publicly available time series data was performed. In this case, the experimentation has exhibited the soundness and scalability of the new method which inferred highly-related statistically-significant gene associations. Conclusions A novel method for inferring time-delayed gene regulatory networks from genome-wide time series datasets is proposed in this paper. The method was carefully validated with several publicly available data sets. The results have demonstrated that the algorithm constitutes a usable model-free approach capable of predicting meaningful relationships between genes, revealing the time-trends of gene regulation.

  2. Vascular Gene Expression: A Hypothesis

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    Angélica Concepción eMartínez-Navarro

    2013-07-01

    Full Text Available The phloem is the conduit through which photoassimilates are distributed from autotrophic to heterotrophic tissues and is involved in the distribution of signaling molecules that coordinate plant growth and responses to the environment. Phloem function depends on the coordinate expression of a large array of genes. We have previously identified conserved motifs in upstream regions of the Arabidopsis genes, encoding the homologs of pumpkin phloem sap mRNAs, displaying expression in vascular tissues. This tissue-specific expression in Arabidopsis is predicted by the overrepresentation of GA/CT-rich motifs in gene promoters. In this work we have searched for common motifs in upstream regions of the homologous genes from plants considered to possess a primitive vascular tissue (a lycophyte, as well as from others that lack a true vascular tissue (a bryophyte, and finally from chlorophytes. Both lycophyte and bryophyte display motifs similar to those found in Arabidopsis with a significantly low E-value, while the chlorophytes showed either a different conserved motif or no conserved motif at all. These results suggest that these same genes are expressed coordinately in non- vascular plants; this coordinate expression may have been one of the prerequisites for the development of conducting tissues in plants. We have also analyzed the phylogeny of conserved proteins that may be involved in phloem function and development. The presence of CmPP16, APL, FT and YDA in chlorophytes suggests the recruitment of ancient regulatory networks for the development of the vascular tissue during evolution while OPS is a novel protein specific to vascular plants.

  3. GSEH: A Novel Approach to Select Prostate Cancer-Associated Genes Using Gene Expression Heterogeneity.

    Science.gov (United States)

    Kim, Hyunjin; Choi, Sang-Min; Park, Sanghyun

    2018-01-01

    When a gene shows varying levels of expression among normal people but similar levels in disease patients or shows similar levels of expression among normal people but different levels in disease patients, we can assume that the gene is associated with the disease. By utilizing this gene expression heterogeneity, we can obtain additional information that abets discovery of disease-associated genes. In this study, we used collaborative filtering to calculate the degree of gene expression heterogeneity between classes and then scored the genes on the basis of the degree of gene expression heterogeneity to find "differentially predicted" genes. Through the proposed method, we discovered more prostate cancer-associated genes than 10 comparable methods. The genes prioritized by the proposed method are potentially significant to biological processes of a disease and can provide insight into them.

  4. The evolution of gene expression in primates

    OpenAIRE

    Tashakkori Ghanbarian, Avazeh

    2015-01-01

    The evolution of a gene’s expression profile is commonly assumed to be independent of its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between expression of neighboring genes in extant taxa. Indeed, in all eukaryotic genomes, genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their e...

  5. Reduced expression of Autographa californica nucleopolyhedrovirus ORF34, an essential gene, enhances heterologous gene expression

    International Nuclear Information System (INIS)

    Salem, Tamer Z.; Zhang, Fengrui; Thiem, Suzanne M.

    2013-01-01

    Autographa californica multiple nucleopolyhedrovirus ORF34 is part of a transcriptional unit that includes ORF32, encoding a viral fibroblast growth factor (FGF) and ORF33. We identified ORF34 as a candidate for deletion to improve protein expression in the baculovirus expression system based on enhanced reporter gene expression in an RNAi screen of virus genes. However, ORF34 was shown to be an essential gene. To explore ORF34 function, deletion (KO34) and rescue bacmids were constructed and characterized. Infection did not spread from primary KO34 transfected cells and supernatants from KO34 transfected cells could not infect fresh Sf21 cells whereas the supernatant from the rescue bacmids transfection could recover the infection. In addition, budded viruses were not observed in KO34 transfected cells by electron microscopy, nor were viral proteins detected from the transfection supernatants by western blots. These demonstrate that ORF34 is an essential gene with a possible role in infectious virus production.

  6. Reduced expression of Autographa californica nucleopolyhedrovirus ORF34, an essential gene, enhances heterologous gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Salem, Tamer Z. [Department of Entomology, Michigan State University, East Lansing, MI 48824 (United States); Department of Microbial Molecular Biology, AGERI, Agricultural Research Center, Giza 12619 (Egypt); Division of Biomedical Sciences, Zewail University, Zewail City of Science and Technology, Giza 12588 (Egypt); Zhang, Fengrui [Department of Entomology, Michigan State University, East Lansing, MI 48824 (United States); Thiem, Suzanne M., E-mail: smthiem@msu.edu [Department of Entomology, Michigan State University, East Lansing, MI 48824 (United States); Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824 (United States)

    2013-01-20

    Autographa californica multiple nucleopolyhedrovirus ORF34 is part of a transcriptional unit that includes ORF32, encoding a viral fibroblast growth factor (FGF) and ORF33. We identified ORF34 as a candidate for deletion to improve protein expression in the baculovirus expression system based on enhanced reporter gene expression in an RNAi screen of virus genes. However, ORF34 was shown to be an essential gene. To explore ORF34 function, deletion (KO34) and rescue bacmids were constructed and characterized. Infection did not spread from primary KO34 transfected cells and supernatants from KO34 transfected cells could not infect fresh Sf21 cells whereas the supernatant from the rescue bacmids transfection could recover the infection. In addition, budded viruses were not observed in KO34 transfected cells by electron microscopy, nor were viral proteins detected from the transfection supernatants by western blots. These demonstrate that ORF34 is an essential gene with a possible role in infectious virus production.

  7. How large a training set is needed to develop a classifier for microarray data?

    Science.gov (United States)

    Dobbin, Kevin K; Zhao, Yingdong; Simon, Richard M

    2008-01-01

    A common goal of gene expression microarray studies is the development of a classifier that can be used to divide patients into groups with different prognoses, or with different expected responses to a therapy. These types of classifiers are developed on a training set, which is the set of samples used to train a classifier. The question of how many samples are needed in the training set to produce a good classifier from high-dimensional microarray data is challenging. We present a model-based approach to determining the sample size required to adequately train a classifier. It is shown that sample size can be determined from three quantities: standardized fold change, class prevalence, and number of genes or features on the arrays. Numerous examples and important experimental design issues are discussed. The method is adapted to address ex post facto determination of whether the size of a training set used to develop a classifier was adequate. An interactive web site for performing the sample size calculations is provided. We showed that sample size calculations for classifier development from high-dimensional microarray data are feasible, discussed numerous important considerations, and presented examples.

  8. Signature gene expression reveals novel clues to the molecular mechanisms of dimorphic transition in Penicillium marneffei.

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    Ence Yang

    2014-10-01

    Full Text Available Systemic dimorphic fungi cause more than one million new infections each year, ranking them among the significant public health challenges currently encountered. Penicillium marneffei is a systemic dimorphic fungus endemic to Southeast Asia. The temperature-dependent dimorphic phase transition between mycelium and yeast is considered crucial for the pathogenicity and transmission of P. marneffei, but the underlying mechanisms are still poorly understood. Here, we re-sequenced P. marneffei strain PM1 using multiple sequencing platforms and assembled the genome using hybrid genome assembly. We determined gene expression levels using RNA sequencing at the mycelial and yeast phases of P. marneffei, as well as during phase transition. We classified 2,718 genes with variable expression across conditions into 14 distinct groups, each marked by a signature expression pattern implicated at a certain stage in the dimorphic life cycle. Genes with the same expression patterns tend to be clustered together on the genome, suggesting orchestrated regulations of the transcriptional activities of neighboring genes. Using qRT-PCR, we validated expression levels of all genes in one of clusters highly expressed during the yeast-to-mycelium transition. These included madsA, a gene encoding MADS-box transcription factor whose gene family is exclusively expanded in P. marneffei. Over-expression of madsA drove P. marneffei to undergo mycelial growth at 37°C, a condition that restricts the wild-type in the yeast phase. Furthermore, analyses of signature expression patterns suggested diverse roles of secreted proteins at different developmental stages and the potential importance of non-coding RNAs in mycelium-to-yeast transition. We also showed that RNA structural transition in response to temperature changes may be related to the control of thermal dimorphism. Together, our findings have revealed multiple molecular mechanisms that may underlie the dimorphic transition

  9. Distinct types of primary cutaneous large B-cell lymphoma identified by gene expression profiling.

    Science.gov (United States)

    Hoefnagel, Juliette J; Dijkman, Remco; Basso, Katia; Jansen, Patty M; Hallermann, Christian; Willemze, Rein; Tensen, Cornelis P; Vermeer, Maarten H

    2005-05-01

    In the European Organization for Research and Treatment of Cancer (EORTC) classification 2 types of primary cutaneous large B-cell lymphoma (PCLBCL) are distinguished: primary cutaneous follicle center cell lymphomas (PCFCCL) and PCLBCL of the leg (PCLBCL-leg). Distinction between both groups is considered important because of differences in prognosis (5-year survival > 95% and 52%, respectively) and the first choice of treatment (radiotherapy or systemic chemotherapy, respectively), but is not generally accepted. To establish a molecular basis for this subdivision in the EORTC classification, we investigated the gene expression profiles of 21 PCLBCLs by oligonucleotide microarray analysis. Hierarchical clustering based on a B-cell signature (7450 genes) classified PCLBCL into 2 distinct subgroups consisting of, respectively, 8 PCFCCLs and 13 PCLBCLsleg. PCLBCLs-leg showed increased expression of genes associated with cell proliferation; the proto-oncogenes Pim-1, Pim-2, and c-Myc; and the transcription factors Mum1/IRF4 and Oct-2. In the group of PCFCCL high expression of SPINK2 was observed. Further analysis suggested that PCFCCLs and PCLBCLs-leg have expression profiles similar to that of germinal center B-cell-like and activated B-cell-like diffuse large B-cell lymphoma, respectively. The results of this study suggest that different pathogenetic mechanisms are involved in the development of PCFCCLs and PCLBCLs-leg and provide molecular support for the subdivision used in the EORTC classification.

  10. Widespread ectopic expression of olfactory receptor genes

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    Yanai Itai

    2006-05-01

    Full Text Available Abstract Background Olfactory receptors (ORs are the largest gene family in the human genome. Although they are expected to be expressed specifically in olfactory tissues, some ectopic expression has been reported, with special emphasis on sperm and testis. The present study systematically explores the expression patterns of OR genes in a large number of tissues and assesses the potential functional implication of such ectopic expression. Results We analyzed the expression of hundreds of human and mouse OR transcripts, via EST and microarray data, in several dozens of human and mouse tissues. Different tissues had specific, relatively small OR gene subsets which had particularly high expression levels. In testis, average expression was not particularly high, and very few highly expressed genes were found, none corresponding to ORs previously implicated in sperm chemotaxis. Higher expression levels were more common for genes with a non-OR genomic neighbor. Importantly, no correlation in expression levels was detected for human-mouse orthologous pairs. Also, no significant difference in expression levels was seen between intact and pseudogenized ORs, except for the pseudogenes of subfamily 7E which has undergone a human-specific expansion. Conclusion The OR superfamily as a whole, show widespread, locus-dependent and heterogeneous expression, in agreement with a neutral or near neutral evolutionary model for transcription control. These results cannot reject the possibility that small OR subsets might play functional roles in different tissues, however considerable care should be exerted when offering a functional interpretation for ectopic OR expression based only on transcription information.

  11. Effect of propolis ethanol extract on myostatin gene expression and muscle morphometry of Nile tilapia in net cages.

    Science.gov (United States)

    Buck, E L; Mizubuti, I Y; Alfieri, A A; Otonel, R A A; Buck, L Y; Souza, F P; Prado-Calixto, O P; Poveda-Parra, A R; Alexandre Filho, L; Lopera-Barrero, N M

    2017-03-16

    Propolis can be used as growth enhancer due to its antimicrobial, antioxidant, and immune-stimulant properties, but its effects on morphometry and muscle gene expression are largely unknown. The present study evaluates the influence of propolis on muscle morphometry and myostatin gene expression in Nile tilapia (Oreochromis niloticus) bred in net cages. Reversed males (GIFT strain) with an initial weight of 170 ± 25 g were distributed in a (2 x 4) factorial scheme, with two diets (DPRO, commercial diet with 4% propolis ethanol extract and DCON, commercial diet without propolis, control) and four assessment periods (0, 35, 70, and 105 experimental days). Muscles were evaluated at each assessment period. Histomorphometric analysis classified the fiber diameters into four groups: 50 μm. RT-qPCR was performed to assess myostatin gene expression. Fibers 30 µm (30-50 and > 50 µm) at 70 days were 25.39% and 40.07% for DPRO and DCON, respectively. There was greater myostatin gene expression at 105 days, averaging 1.93 and 1.89 for DCON and DPRO, respectively, with no significant difference in any of the analyzed periods. Propolis ethanol extract did not affect the diameter of muscle fibers or the gene expression of myostatin. Future studies should describe the mechanisms of natural products' effects on muscle growth and development since these factors are highly relevant for fish production performance.

  12. Analysis of the stability of housekeeping gene expression in the left cardiac ventricle of rats submitted to chronic intermittent hypoxia

    Directory of Open Access Journals (Sweden)

    Guilherme Silva Julian

    Full Text Available ABSTRACT Obstructive sleep apnea (OSA has been associated with oxidative stress and various cardiovascular consequences, such as increased cardiovascular disease risk. Quantitative real-time PCR is frequently employed to assess changes in gene expression in experimental models. In this study, we analyzed the effects of chronic intermittent hypoxia (an experimental model of OSA on housekeeping gene expression in the left cardiac ventricle of rats. Analyses via four different approaches-use of the geNorm, BestKeeper, and NormFinder algorithms; and 2−ΔCt (threshold cycle data analysis-produced similar results: all genes were found to be suitable for use, glyceraldehyde-3-phosphate dehydrogenase and 18S being classified as the most and the least stable, respectively. The use of more than one housekeeping gene is strongly advised.

  13. Identification of Human HK Genes and Gene Expression Regulation Study in Cancer from Transcriptomics Data Analysis

    Science.gov (United States)

    Zhang, Zhang; Liu, Jingxing; Wu, Jiayan; Yu, Jun

    2013-01-01

    The regulation of gene expression is essential for eukaryotes, as it drives the processes of cellular differentiation and morphogenesis, leading to the creation of different cell types in multicellular organisms. RNA-Sequencing (RNA-Seq) provides researchers with a powerful toolbox for characterization and quantification of transcriptome. Many different human tissue/cell transcriptome datasets coming from RNA-Seq technology are available on public data resource. The fundamental issue here is how to develop an effective analysis method to estimate expression pattern similarities between different tumor tissues and their corresponding normal tissues. We define the gene expression pattern from three directions: 1) expression breadth, which reflects gene expression on/off status, and mainly concerns ubiquitously expressed genes; 2) low/high or constant/variable expression genes, based on gene expression level and variation; and 3) the regulation of gene expression at the gene structure level. The cluster analysis indicates that gene expression pattern is higher related to physiological condition rather than tissue spatial distance. Two sets of human housekeeping (HK) genes are defined according to cell/tissue types, respectively. To characterize the gene expression pattern in gene expression level and variation, we firstly apply improved K-means algorithm and a gene expression variance model. We find that cancer-associated HK genes (a HK gene is specific in cancer group, while not in normal group) are expressed higher and more variable in cancer condition than in normal condition. Cancer-associated HK genes prefer to AT-rich genes, and they are enriched in cell cycle regulation related functions and constitute some cancer signatures. The expression of large genes is also avoided in cancer group. These studies will help us understand which cell type-specific patterns of gene expression differ among different cell types, and particularly for cancer. PMID:23382867

  14. Sequence homology and expression profile of genes associated with dna repair pathways in Mycobacterium leprae

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    Mukul Sharma

    2017-01-01

    Full Text Available Background: Survival of Mycobacterium leprae, the causative bacteria for leprosy, in the human host is dependent to an extent on the ways in which its genome integrity is retained. DNA repair mechanisms protect bacterial DNA from damage induced by various stress factors. The current study is aimed at understanding the sequence and functional annotation of DNA repair genes in M. leprae. Methods: T he genome of M. leprae was annotated using sequence alignment tools to identify DNA repair genes that have homologs in Mycobacterium tuberculosis and Escherichia coli. A set of 96 genes known to be involved in DNA repair mechanisms in E. coli and Mycobacteriaceae were chosen as a reference. Among these, 61 were identified in M. leprae based on sequence similarity and domain architecture. The 61 were classified into 36 characterized gene products (59%, 11 hypothetical proteins (18%, and 14 pseudogenes (23%. All these genes have homologs in M. tuberculosis and 49 (80.32% in E. coli. A set of 12 genes which are absent in E. coli were present in M. leprae and in Mycobacteriaceae. These 61 genes were further investigated for their expression profiles in the whole transcriptome microarray data of M. leprae which was obtained from the signal intensities of 60bp probes, tiling the entire genome with 10bp overlaps. Results: It was noted that transcripts corresponding to all the 61 genes were identified in the transcriptome data with varying expression levels ranging from 0.18 to 2.47 fold (normalized with 16SrRNA. The mRNA expression levels of a representative set of seven genes ( four annotated and three hypothetical protein coding genes were analyzed using quantitative Polymerase Chain Reaction (qPCR assays with RNA extracted from skin biopsies of 10 newly diagnosed, untreated leprosy cases. It was noted that RNA expression levels were higher for genes involved in homologous recombination whereas the genes with a low level of expression are involved in the

  15. Comparison of immunological characteristics of peripheral, splenic and tonsilar naïve B cells by differential gene expression meta-analyses.

    Science.gov (United States)

    Chokeshai-u-saha, Kaj; Lepoivre, Cyrille; Grieco, Luca; Nguyen, Catherine; Ruxrungtham, Kiat

    2012-12-01

    Naïve B cells isolated from peripheral blood, spleen and tonsil are commonly used in human B cell studies. However, little has been written about their possible variations in immunological properties. This study compared differential gene expression in human naive B subsets by meta-analysis using expression data available in Gene Expression Onimbus (GEO). Gene expression files of the Affymetrix Human Genome U133A Array (Affymetrix) were downloaded to collect 21 total array data samples of peripheral naïve B cells (n=10), splenic naïve B cells (n=2), tonsilar naïve B cells (n=3), peripheral memory B cells (n=4) and splenic memory B cells (n=2). Prior to differential gene expression analyses, data were normalized in order to reduce non-biological variation among the datasets. Comparisons of peripheral naive B cells with their splenic and tonsilar counterparts showed remarkable differences in terms of gene expression (29 and 202 genes, respectively). However, only minor differences were detected between splenic and tonsilar naive B cells (10 genes), consistent with the clustering results classifying both of them as lymphoid naive B cells. Differential gene expression results also implied higher stimulating states of lymphoid naive B cells when compared with peripheral blood naive B cells. These included enhanced expressions of CD27, CR2, EGR1, GADD45B, ICAM1, ICOSLG, IGHA, IL6, MMP9, SAMSN1, SMAD7, TNFAIP3, but reduced HLA-DOB expression. Our findings suggest that results generated from peripheral naive B cells may not always be applicable to the biological activities of other lymphoid naïve B cells. Nonetheless, further biological study is warranted.

  16. Genome-wide identification and expression analysis of the CIPK gene family in cassava

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    Wei eHu

    2015-10-01

    Full Text Available Cassava is an important food and potential biofuel crop that is tolerant to multiple abiotic stressors. The mechanisms underlying these tolerances are currently less known. CBL-interacting protein kinases (CIPKs have been shown to play crucial roles in plant developmental processes, hormone signaling transduction, and in the response to abiotic stress. However, no data is currently available about the CPK family in cassava. In this study, a total of 25 CIPK genes were identified from cassava genome based on our previous genome sequencing data. Phylogenetic analysis suggested that 25 MeCIPKs could be classified into four subfamilies, which was supported by exon-intron organizations and the architectures of conserved protein motifs. Transcriptomic analysis of a wild subspecies and two cultivated varieties showed that most MeCIPKs had different expression patterns between wild subspecies and cultivatars in different tissues or in response to drought stress. Some orthologous genes involved in CIPK interaction networks were identified between Arabidopsis and cassava. The interaction networks and co-expression patterns of these orthologous genes revealed that the crucial pathways controlled by CIPK networks may be involved in the differential response to drought stress in different accessions of cassava. Nine MeCIPK genes were selected to investigate their transcriptional response to various stimuli and the results showed the comprehensive response of the tested MeCIPK genes to osmotic, salt, cold, oxidative stressors, and ABA signaling. The identification and expression analysis of CIPK family suggested that CIPK genes are important components of development and multiple signal transduction pathways in cassava. The findings of this study will help lay a foundation for the functional characterization of the CIPK gene family and provide an improved understanding of abiotic stress responses and signaling transduction in cassava.

  17. Dynamic association rules for gene expression data analysis.

    Science.gov (United States)

    Chen, Shu-Chuan; Tsai, Tsung-Hsien; Chung, Cheng-Han; Li, Wen-Hsiung

    2015-10-14

    The purpose of gene expression analysis is to look for the association between regulation of gene expression levels and phenotypic variations. This association based on gene expression profile has been used to determine whether the induction/repression of genes correspond to phenotypic variations including cell regulations, clinical diagnoses and drug development. Statistical analyses on microarray data have been developed to resolve gene selection issue. However, these methods do not inform us of causality between genes and phenotypes. In this paper, we propose the dynamic association rule algorithm (DAR algorithm) which helps ones to efficiently select a subset of significant genes for subsequent analysis. The DAR algorithm is based on association rules from market basket analysis in marketing. We first propose a statistical way, based on constructing a one-sided confidence interval and hypothesis testing, to determine if an association rule is meaningful. Based on the proposed statistical method, we then developed the DAR algorithm for gene expression data analysis. The method was applied to analyze four microarray datasets and one Next Generation Sequencing (NGS) dataset: the Mice Apo A1 dataset, the whole genome expression dataset of mouse embryonic stem cells, expression profiling of the bone marrow of Leukemia patients, Microarray Quality Control (MAQC) data set and the RNA-seq dataset of a mouse genomic imprinting study. A comparison of the proposed method with the t-test on the expression profiling of the bone marrow of Leukemia patients was conducted. We developed a statistical way, based on the concept of confidence interval, to determine the minimum support and minimum confidence for mining association relationships among items. With the minimum support and minimum confidence, one can find significant rules in one single step. The DAR algorithm was then developed for gene expression data analysis. Four gene expression datasets showed that the proposed

  18. Gene expression in periodontal tissues following treatment

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    Eisenacher Martin

    2008-07-01

    Full Text Available Abstract Background In periodontitis, treatment aimed at controlling the periodontal biofilm infection results in a resolution of the clinical and histological signs of inflammation. Although the cell types found in periodontal tissues following treatment have been well described, information on gene expression is limited to few candidate genes. Therefore, the aim of the study was to determine the expression profiles of immune and inflammatory genes in periodontal tissues from sites with severe chronic periodontitis following periodontal therapy in order to identify genes involved in tissue homeostasis. Gingival biopsies from 12 patients with severe chronic periodontitis were taken six to eight weeks following non-surgical periodontal therapy, and from 11 healthy controls. As internal standard, RNA of an immortalized human keratinocyte line (HaCaT was used. Total RNA was subjected to gene expression profiling using a commercially available microarray system focusing on inflammation-related genes. Post-hoc confirmation of selected genes was done by Realtime-PCR. Results Out of the 136 genes analyzed, the 5% most strongly expressed genes compared to healthy controls were Interleukin-12A (IL-12A, Versican (CSPG-2, Matrixmetalloproteinase-1 (MMP-1, Down syndrome critical region protein-1 (DSCR-1, Macrophage inflammatory protein-2β (Cxcl-3, Inhibitor of apoptosis protein-1 (BIRC-1, Cluster of differentiation antigen 38 (CD38, Regulator of G-protein signalling-1 (RGS-1, and Finkel-Biskis-Jinkins murine osteosarcoma virus oncogene (C-FOS; the 5% least strongly expressed genes were Receptor-interacting Serine/Threonine Kinase-2 (RIP-2, Complement component 3 (C3, Prostaglandin-endoperoxide synthase-2 (COX-2, Interleukin-8 (IL-8, Endothelin-1 (EDN-1, Plasminogen activator inhibitor type-2 (PAI-2, Matrix-metalloproteinase-14 (MMP-14, and Interferon regulating factor-7 (IRF-7. Conclusion Gene expression profiles found in periodontal tissues following

  19. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks | Center for Cancer Research

    Science.gov (United States)

    The purpose of this study was to develop a method of classifying cancers to specific diagnostic categories based on their gene expression signatures using artificial neural networks (ANNs). We trained the ANNs using the small, round blue-cell tumors (SRBCTs) as a model. These cancers belong to four distinct diagnostic categories and often present diagnostic dilemmas in

  20. Gene expression profiles in skeletal muscle after gene electrotransfer

    DEFF Research Database (Denmark)

    Hojman, Pernille; Zibert, John R; Gissel, Hanne

    2007-01-01

    BACKGROUND: Gene transfer by electroporation (DNA electrotransfer) to muscle results in high level long term transgenic expression, showing great promise for treatment of e.g. protein deficiency syndromes. However little is known about the effects of DNA electrotransfer on muscle fibres. We have...... caused down-regulation of structural proteins e.g. sarcospan and catalytic enzymes. Injection of DNA induced down-regulation of intracellular transport proteins e.g. sentrin. The effects on muscle fibres were transient as the expression profiles 3 weeks after treatment were closely related......) followed by a long low voltage pulse (LV, 100 V/cm, 400 ms); a pulse combination optimised for efficient and safe gene transfer. Muscles were transfected with green fluorescent protein (GFP) and excised at 4 hours, 48 hours or 3 weeks after treatment. RESULTS: Differentially expressed genes were...

  1. Comparative gene expression between two yeast species

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    Guan Yuanfang

    2013-01-01

    Full Text Available Abstract Background Comparative genomics brings insight into sequence evolution, but even more may be learned by coupling sequence analyses with experimental tests of gene function and regulation. However, the reliability of such comparisons is often limited by biased sampling of expression conditions and incomplete knowledge of gene functions across species. To address these challenges, we previously systematically generated expression profiles in Saccharomyces bayanus to maximize functional coverage as compared to an existing Saccharomyces cerevisiae data repository. Results In this paper, we take advantage of these two data repositories to compare patterns of ortholog expression in a wide variety of conditions. First, we developed a scalable metric for expression divergence that enabled us to detect a significant correlation between sequence and expression conservation on the global level, which previous smaller-scale expression studies failed to detect. Despite this global conservation trend, between-species gene expression neighborhoods were less well-conserved than within-species comparisons across different environmental perturbations, and approximately 4% of orthologs exhibited a significant change in co-expression partners. Furthermore, our analysis of matched perturbations collected in both species (such as diauxic shift and cell cycle synchrony demonstrated that approximately a quarter of orthologs exhibit condition-specific expression pattern differences. Conclusions Taken together, these analyses provide a global view of gene expression patterns between two species, both in terms of the conditions and timing of a gene's expression as well as co-expression partners. Our results provide testable hypotheses that will direct future experiments to determine how these changes may be specified in the genome.

  2. Evidence of inflammatory immune signaling in chronic fatigue syndrome: A pilot study of gene expression in peripheral blood

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    Vernon Suzanne D

    2008-09-01

    Full Text Available Abstract Background Genomic profiling of peripheral blood reveals altered immunity in chronic fatigue syndrome (CFS however interpretation remains challenging without immune demographic context. The object of this work is to identify modulation of specific immune functional components and restructuring of co-expression networks characteristic of CFS using the quantitative genomics of peripheral blood. Methods Gene sets were constructed a priori for CD4+ T cells, CD8+ T cells, CD19+ B cells, CD14+ monocytes and CD16+ neutrophils from published data. A group of 111 women were classified using empiric case definition (U.S. Centers for Disease Control and Prevention and unsupervised latent cluster analysis (LCA. Microarray profiles of peripheral blood were analyzed for expression of leukocyte-specific gene sets and characteristic changes in co-expression identified from topological evaluation of linear correlation networks. Results Median expression for a set of 6 genes preferentially up-regulated in CD19+ B cells was significantly lower in CFS (p = 0.01 due mainly to PTPRK and TSPAN3 expression. Although no other gene set was differentially expressed at p Conclusion Dissection of blood microarray profiles points to B cell dysfunction with coordinated immune activation supporting persistent inflammation and antibody-mediated NK cell modulation of T cell activity. This has clinical implications as the CD19+ genes identified could provide robust and biologically meaningful basis for the early detection and unambiguous phenotyping of CFS.

  3. Minimal gene selection for classification and diagnosis prediction based on gene expression profile

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    Alireza Mehridehnavi

    2013-01-01

    Conclusion: We have shown that the use of two most significant genes based on their S/N ratios and selection of suitable training samples can lead to classify DLBCL patients with a rather good result. Actually with the aid of mentioned methods we could compensate lack of enough number of patients, improve accuracy of classifying and reduce complication of computations and so running time.

  4. Interactive visualization of gene regulatory networks with associated gene expression time series data

    NARCIS (Netherlands)

    Westenberg, M.A.; Hijum, van S.A.F.T.; Lulko, A.T.; Kuipers, O.P.; Roerdink, J.B.T.M.; Linsen, L.; Hagen, H.; Hamann, B.

    2008-01-01

    We present GENeVis, an application to visualize gene expression time series data in a gene regulatory network context. This is a network of regulator proteins that regulate the expression of their respective target genes. The networks are represented as graphs, in which the nodes represent genes,

  5. Functional heterogeneity of cancer-associated fibroblasts from human colon tumors shows specific prognostic gene expression signature.

    Science.gov (United States)

    Herrera, Mercedes; Islam, Abul B M M K; Herrera, Alberto; Martín, Paloma; García, Vanesa; Silva, Javier; Garcia, Jose M; Salas, Clara; Casal, Ignacio; de Herreros, Antonio García; Bonilla, Félix; Peña, Cristina

    2013-11-01

    Cancer-associated fibroblasts (CAF) actively participate in reciprocal communication with tumor cells and with other cell types in the microenvironment, contributing to a tumor-permissive neighborhood and promoting tumor progression. The aim of this study is the characterization of how CAFs from primary human colon tumors promote migration of colon cancer cells. Primary CAF cultures from 15 primary human colon tumors were established. Their enrichment in CAFs was evaluated by the expression of various epithelial and myofibroblast specific markers. Coculture assays of primary CAFs with different colon tumor cells were performed to evaluate promigratory CAF-derived effects on cancer cells. Gene expression profiles were developed to further investigate CAF characteristics. Coculture assays showed significant differences in fibroblast-derived paracrine promigratory effects on cancer cells. Moreover, the association between CAFs' promigratory effects on cancer cells and classic fibroblast activation or stemness markers was observed. CAF gene expression profiles were analyzed by microarray to identify deregulated genes in different promigratory CAFs. The gene expression signature, derived from the most protumorogenic CAFs, was identified. Interestingly, this "CAF signature" showed a remarkable prognostic value for the clinical outcome of patients with colon cancer. Moreover, this prognostic value was validated in an independent series of 142 patients with colon cancer, by quantitative real-time PCR (qRT-PCR), with a set of four genes included in the "CAF signature." In summary, these studies show for the first time the heterogeneity of primary CAFs' effect on colon cancer cell migration. A CAF gene expression signature able to classify patients with colon cancer into high- and low-risk groups was identified.

  6. Gene Expression Associated with Early and Late Chronotypes in Drosophila melanogaster

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    Mirko ePegoraro

    2015-05-01

    Full Text Available The circadian clock provides the temporal framework for rhythmic behavioural and metabolic functions. In the modern era of industrialization, work and social pressures, the clock function is often jeopardized, resulting in adverse and chronic effects on health. Understanding circadian clock function, particularly individual variation in diurnal phase preference (chronotype, and the molecular mechanisms underlying such chronotypes may lead to interventions that could abrogate clock dysfunction and improve human (and animal health and welfare. Our preliminary studies suggested that fruitflies, like humans, can be classified as early rising ‘larks’ or late rising ‘owls’, providing a convenient model system for these types of studies. We have identified strains of flies showing increased preference for morning emergence (Early or E from the pupal case, or more pronounced preference for evening emergence (Late or L. We have sampled pupae the day before eclosion (4th day after pupariation at 4 h intervals in the E and L strains, and examined differences in gene expression by RNAseq. We have identified differentially expressed transcripts between the E and L strains which provide candidate genes for studies of Drosophila chronotypes and their human orthologues.

  7. The Ubiquitin-Conjugating Enzyme Gene Family in Longan (Dimocarpus longan Lour.: Genome-Wide Identification and Gene Expression during Flower Induction and Abiotic Stress Responses

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    Dengwei Jue

    2018-03-01

    Full Text Available Ubiquitin-conjugating enzymes (E2s or UBC enzymes play vital roles in plant development and combat various biotic and abiotic stresses. Longan (Dimocarpus longan Lour. is an important fruit tree in the subtropical region of Southeast Asia and Australia; however the characteristics of the UBC gene family in longan remain unknown. In this study, 40 D. longan UBC genes (DlUBCs, which were classified into 15 groups, were identified in the longan genome. An RNA-seq based analysis showed that DlUBCs showed distinct expression in nine longan tissues. Genome-wide RNA-seq and qRT-PCR based gene expression analysis revealed that 11 DlUBCs were up- or down-regualted in the cultivar “Sijimi” (SJ, suggesting that these genes may be important for flower induction. Finally, qRT-PCR analysis showed that the mRNA levels of 13 DlUBCs under SA (salicylic acid treatment, seven under methyl jasmonate (MeJA treatment, 27 under heat treatment, and 16 under cold treatment were up- or down-regulated, respectively. These results indicated that the DlUBCs may play important roles in responses to abiotic stresses. Taken together, our results provide a comprehensive insight into the organization, phylogeny, and expression patterns of the longan UBC genes, and therefore contribute to the greater understanding of their biological roles in longan.

  8. Serial analysis of gene expression (SAGE)

    NARCIS (Netherlands)

    van Ruissen, Fred; Baas, Frank

    2007-01-01

    In 1995, serial analysis of gene expression (SAGE) was developed as a versatile tool for gene expression studies. SAGE technology does not require pre-existing knowledge of the genome that is being examined and therefore SAGE can be applied to many different model systems. In this chapter, the SAGE

  9. An Interactive Database of Cocaine-Responsive Gene Expression

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    Willard M. Freeman

    2002-01-01

    Full Text Available The postgenomic era of large-scale gene expression studies is inundating drug abuse researchers and many other scientists with findings related to gene expression. This information is distributed across many different journals, and requires laborious literature searches. Here, we present an interactive database that combines existing information related to cocaine-mediated changes in gene expression in an easy-to-use format. The database is limited to statistically significant changes in mRNA or protein expression after cocaine administration. The Flash-based program is integrated into a Web page, and organizes changes in gene expression based on neuroanatomical region, general function, and gene name. Accompanying each gene is a description of the gene, links to the original publications, and a link to the appropriate OMIM (Online Mendelian Inheritance in Man entry. The nature of this review allows for timely modifications and rapid inclusion of new publications, and should help researchers build second-generation hypotheses on the role of gene expression changes in the physiology and behavior of cocaine abuse. Furthermore, this method of organizing large volumes of scientific information can easily be adapted to assist researchers in fields outside of drug abuse.

  10. CDX2 gene expression in acute lymphoblastic leukemia

    International Nuclear Information System (INIS)

    Arnaoaut, H.H.; Mokhtar, D.A.; Samy, R.M.; Omar, Sh.A.; Khames, S.A.

    2014-01-01

    CDX genes are classically known as regulators of axial elongation during early embryogenesis. An unsuspected role for CDX genes has been revealed during hematopoietic development. The CDX gene family member CDX2 belongs to the most frequent aberrantly expressed proto-oncogenes in human acute leukemias and is highly leukemogenic in experimental models. We used reversed transcriptase polymerase chain reaction (RT-PCR) to determine the expression level of CDX2 gene in 30 pediatric patients with acute lymphoblastic leukemia (ALL) at diagnosis and 30 healthy volunteers. ALL patients were followed up to detect minimal residual disease (MRD) on days 15 and 42 of induction. We found that CDX2 gene was expressed in 50% of patients and not expressed in controls. Associations between gene expression and different clinical and laboratory data of patients revealed no impact on different findings. With follow up, we could not confirm that CDX2 expression had a prognostic significance.

  11. Identification of reference genes in human myelomonocytic cells for gene expression studies in altered gravity.

    Science.gov (United States)

    Thiel, Cora S; Hauschild, Swantje; Tauber, Svantje; Paulsen, Katrin; Raig, Christiane; Raem, Arnold; Biskup, Josefine; Gutewort, Annett; Hürlimann, Eva; Unverdorben, Felix; Buttron, Isabell; Lauber, Beatrice; Philpot, Claudia; Lier, Hartwin; Engelmann, Frank; Layer, Liliana E; Ullrich, Oliver

    2015-01-01

    Gene expression studies are indispensable for investigation and elucidation of molecular mechanisms. For the process of normalization, reference genes ("housekeeping genes") are essential to verify gene expression analysis. Thus, it is assumed that these reference genes demonstrate similar expression levels over all experimental conditions. However, common recommendations about reference genes were established during 1 g conditions and therefore their applicability in studies with altered gravity has not been demonstrated yet. The microarray technology is frequently used to generate expression profiles under defined conditions and to determine the relative difference in expression levels between two or more different states. In our study, we searched for potential reference genes with stable expression during different gravitational conditions (microgravity, normogravity, and hypergravity) which are additionally not altered in different hardware systems. We were able to identify eight genes (ALB, B4GALT6, GAPDH, HMBS, YWHAZ, ABCA5, ABCA9, and ABCC1) which demonstrated no altered gene expression levels in all tested conditions and therefore represent good candidates for the standardization of gene expression studies in altered gravity.

  12. Training ANFIS structure using genetic algorithm for liver cancer classification based on microarray gene expression data

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    Bülent Haznedar

    2017-02-01

    Full Text Available Classification is an important data mining technique, which is used in many fields mostly exemplified as medicine, genetics and biomedical engineering. The number of studies about classification of the datum on DNA microarray gene expression is specifically increased in recent years. However, because of the reasons as the abundance of gene numbers in the datum as microarray gene expressions and the nonlinear relations mostly across those datum, the success of conventional classification algorithms can be limited. Because of these reasons, the interest on classification methods which are based on artificial intelligence to solve the problem on classification has been gradually increased in recent times. In this study, a hybrid approach which is based on Adaptive Neuro-Fuzzy Inference System (ANFIS and Genetic Algorithm (GA are suggested in order to classify liver microarray cancer data set. Simulation results are compared with the results of other methods. According to the results obtained, it is seen that the recommended method is better than the other methods.

  13. Inferring gene networks from discrete expression data

    KAUST Repository

    Zhang, L.

    2013-07-18

    The modeling of gene networks from transcriptional expression data is an important tool in biomedical research to reveal signaling pathways and to identify treatment targets. Current gene network modeling is primarily based on the use of Gaussian graphical models applied to continuous data, which give a closedformmarginal likelihood. In this paper,we extend network modeling to discrete data, specifically data from serial analysis of gene expression, and RNA-sequencing experiments, both of which generate counts of mRNAtranscripts in cell samples.We propose a generalized linear model to fit the discrete gene expression data and assume that the log ratios of the mean expression levels follow a Gaussian distribution.We restrict the gene network structures to decomposable graphs and derive the graphs by selecting the covariance matrix of the Gaussian distribution with the hyper-inverse Wishart priors. Furthermore, we incorporate prior network models based on gene ontology information, which avails existing biological information on the genes of interest. We conduct simulation studies to examine the performance of our discrete graphical model and apply the method to two real datasets for gene network inference. © The Author 2013. Published by Oxford University Press. All rights reserved.

  14. Gene Expression Analyses of HER-2/neu and ESR1 in Patients with Breast Cancer

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    Omid Kheyri Nadergoli

    2017-10-01

    Full Text Available ABSTRACT Background: Her-2 and ESR1 genes, that interact in the cell signaling pathway, are the most important molecular markers of breast cancer, which have been amplified or overexpressed in 30% and 70%, respectively. This study was performed to evaluate the gene expression levels of Her-2 and ESR1 genes in tumor cells and its adjacent normal tissue of breast cancer patients and compared them whit clinical-pathological features. Methods: In total, 80 tissue specimens from 40 patients, with an average age of 48.47 years, were examined by Real-time PCR technique, and ultimately evaluated the expression level of Her-2 and ESR1genes. The data were analyzed by REST 2009 V2.0.13 statistical software. Results: HER2 and ESR1 overexpression was identified in 19 (48% and 12 (30% of 40 patients respectively, which was higher and lower than that recorded in international statistics, respectively. ESR1 overexpression was associated with Stage 3A and lymph node involvement 2 (N2 (P = 0.04 and P = 0.047, respectively. No significant correlation was observed between the expression of HER2 and ESR1 and other clinical-pathological features, however, the relative differences were identified in the expression levels of genes between main group and groups that were classified according to the clinical-pathological features and age. Conclusions: Overexpression of Her-2 and ESR1 genes in the patients of our study are higher and lower than international statistics, respectively, indicating the differences in genetic, environmental and ethnic factors that involved in the developing of breast cancer.

  15. Reference Gene Screening for Analyzing Gene Expression Across Goat Tissue

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    Yu Zhang

    2013-12-01

    Full Text Available Real-time quantitative PCR (qRT-PCR is one of the important methods for investigating the changes in mRNA expression levels in cells and tissues. Selection of the proper reference genes is very important when calibrating the results of real-time quantitative PCR. Studies on the selection of reference genes in goat tissues are limited, despite the economic importance of their meat and dairy products. We used real-time quantitative PCR to detect the expression levels of eight reference gene candidates (18S, TBP, HMBS, YWHAZ, ACTB, HPRT1, GAPDH and EEF1A2 in ten tissues types sourced from Boer goats. The optimal reference gene combination was selected according to the results determined by geNorm, NormFinder and Bestkeeper software packages. The analyses showed that tissue is an important variability factor in genes expression stability. When all tissues were considered, 18S, TBP and HMBS is the optimal reference combination for calibrating quantitative PCR analysis of gene expression from goat tissues. Dividing data set by tissues, ACTB was the most stable in stomach, small intestine and ovary, 18S in heart and spleen, HMBS in uterus and lung, TBP in liver, HPRT1 in kidney and GAPDH in muscle. Overall, this study provided valuable information about the goat reference genes that can be used in order to perform a proper normalisation when relative quantification by qRT-PCR studies is undertaken.

  16. Expression microarray identifies the unliganded glucocorticoid receptor as a regulator of gene expression in mammary epithelial cells

    International Nuclear Information System (INIS)

    Ritter, Heather D; Mueller, Christopher R

    2014-01-01

    While glucocorticoids and the liganded glucocorticoid receptor (GR) have a well-established role in the maintenance of differentiation and suppression of apoptosis in breast tissue, the involvement of unliganded GR in cellular processes is less clear. Our previous studies implicated unliganded GR as a positive regulator of the BRCA1 tumour suppressor gene in the absence of glucocorticoid hormone, which suggested it could play a similar role in the regulation of other genes. An shRNA vector directed against GR was used to create mouse mammary cell lines with depleted endogenous levels of this receptor in order to further characterize the role of GR in breast cells. An expression microarray screen for targets of unliganded GR was performed using our GR-depleted cell lines maintained in the absence of glucocorticoids. Candidate genes positively regulated by unliganded GR were identified, classified by Gene Ontology and Ingenuity Pathway Analysis, and validated using quantitative real-time reverse transcriptase PCR. Chromatin immunoprecipitation and dual luciferase expression assays were conducted to further investigate the mechanism through which unliganded GR regulates these genes. Expression microarray analysis revealed 260 targets negatively regulated and 343 targets positively regulated by unliganded GR. A number of the positively regulated targets were involved in pro-apoptotic networks, possibly opposing the activity of liganded GR targets. Validation and further analysis of five candidates from the microarray indicated that two of these, Hsd11b1 and Ch25h, were regulated by unliganded GR in a manner similar to Brca1 during glucocorticoid treatment. Furthermore, GR was shown to interact directly with and upregulate the Ch25h promoter in the absence, but not the presence, of hydrocortisone (HC), confirming our previously described model of gene regulation by unliganded GR. This work presents the first identification of targets of unliganded GR. We propose that

  17. Genome-Wide Identification, Evolution and Expression Analysis of the Grape (Vitis vinifera L. Zinc Finger-Homeodomain Gene Family

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    Hao Wang

    2014-04-01

    Full Text Available Plant zinc finger-homeodomain (ZHD genes encode a family of transcription factors that have been demonstrated to play an important role in the regulation of plant growth and development. In this study, we identified a total of 13 ZHD genes (VvZHD in the grape genome that were further classified into at least seven groups. Genome synteny analysis revealed that a number of VvZHD genes were present in the corresponding syntenic blocks of Arabidopsis, indicating that they arose before the divergence of these two species. Gene expression analysis showed that the identified VvZHD genes displayed distinct spatiotemporal expression patterns, and were differentially regulated under various stress conditions and hormone treatments, suggesting that the grape VvZHDs might be also involved in plant response to a variety of biotic and abiotic insults. Our work provides insightful information and knowledge about the ZHD genes in grape, which provides a framework for further characterization of their roles in regulation of stress tolerance as well as other aspects of grape productivity.

  18. Studying the Complex Expression Dependences between Sets of Coexpressed Genes

    Directory of Open Access Journals (Sweden)

    Mario Huerta

    2014-01-01

    Full Text Available Organisms simplify the orchestration of gene expression by coregulating genes whose products function together in the cell. The use of clustering methods to obtain sets of coexpressed genes from expression arrays is very common; nevertheless there are no appropriate tools to study the expression networks among these sets of coexpressed genes. The aim of the developed tools is to allow studying the complex expression dependences that exist between sets of coexpressed genes. For this purpose, we start detecting the nonlinear expression relationships between pairs of genes, plus the coexpressed genes. Next, we form networks among sets of coexpressed genes that maintain nonlinear expression dependences between all of them. The expression relationship between the sets of coexpressed genes is defined by the expression relationship between the skeletons of these sets, where this skeleton represents the coexpressed genes with a well-defined nonlinear expression relationship with the skeleton of the other sets. As a result, we can study the nonlinear expression relationships between a target gene and other sets of coexpressed genes, or start the study from the skeleton of the sets, to study the complex relationships of activation and deactivation between the sets of coexpressed genes that carry out the different cellular processes present in the expression experiments.

  19. The ordering of expression among a few genes can provide simple cancer biomarkers and signal BRCA1 mutations

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    Parmigiani Giovanni

    2009-08-01

    Full Text Available Abstract Background A major challenge in computational biology is to extract knowledge about the genetic nature of disease from high-throughput data. However, an important obstacle to both biological understanding and clinical applications is the "black box" nature of the decision rules provided by most machine learning approaches, which usually involve many genes combined in a highly complex fashion. Achieving biologically relevant results argues for a different strategy. A promising alternative is to base prediction entirely upon the relative expression ordering of a small number of genes. Results We present a three-gene version of "relative expression analysis" (RXA, a rigorous and systematic comparison with earlier approaches in a variety of cancer studies, a clinically relevant application to predicting germline BRCA1 mutations in breast cancer and a cross-study validation for predicting ER status. In the BRCA1 study, RXA yields high accuracy with a simple decision rule: in tumors carrying mutations, the expression of a "reference gene" falls between the expression of two differentially expressed genes, PPP1CB and RNF14. An analysis of the protein-protein interactions among the triplet of genes and BRCA1 suggests that the classifier has a biological foundation. Conclusion RXA has the potential to identify genomic "marker interactions" with plausible biological interpretation and direct clinical applicability. It provides a general framework for understanding the roles of the genes involved in decision rules, as illustrated for the difficult and clinically relevant problem of identifying BRCA1 mutation carriers.

  20. Gene expression of the mismatch repair gene MSH2 in primary colorectal cancer

    DEFF Research Database (Denmark)

    Jensen, Lars Henrik; Kuramochi, Hidekazu; Crüger, Dorthe Gylling

    2011-01-01

    promoter was only detected in 14 samples and only at a low level with no correlation to gene expression. MSH2 gene expression was not a prognostic factor for overall survival in univariate or multivariate analysis. The gene expression of MSH2 is a potential quantitative marker ready for further clinical...

  1. Transcriptional Profiling of Host Gene Expression in Chicken Embryo Fibroblasts Infected with Reticuloendotheliosis Virus Strain HA1101.

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    Ji Miao

    Full Text Available Reticuloendotheliosis virus (REV, a member of the Gammaretrovirus genus in the Retroviridae family, causes an immunosuppressive, oncogenic and runting-stunting syndrome in multiple avian hosts. To better understand the host interactions at the transcriptional level, microarray data analysis was performed in chicken embryo fibroblast cells at 1, 3, 5, and 7 days after infection with REV. This study identified 1,785 differentially expressed genes that were classified into several functional groups including signal transduction, immune response, biological adhesion and endocytosis. Significant differences were mainly observed in the expression of genes involved in the immune response, especially during the later post-infection time points. These results revealed that differentially expressed genes IL6, STAT1, MyD88, TLRs, NF-κB, IRF-7, and ISGs play important roles in the pathogenicity of REV infection. Our study is the first to use microarray analysis to investigate REV, and these findings provide insights into the underlying mechanisms of the host antiviral response and the molecular basis of viral pathogenesis.

  2. The relationship among gene expression, the evolution of gene dosage, and the rate of protein evolution.

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    Jean-François Gout

    2010-05-01

    Full Text Available The understanding of selective constraints affecting genes is a major issue in biology. It is well established that gene expression level is a major determinant of the rate of protein evolution, but the reasons for this relationship remain highly debated. Here we demonstrate that gene expression is also a major determinant of the evolution of gene dosage: the rate of gene losses after whole genome duplications in the Paramecium lineage is negatively correlated to the level of gene expression, and this relationship is not a byproduct of other factors known to affect the fate of gene duplicates. This indicates that changes in gene dosage are generally more deleterious for highly expressed genes. This rule also holds for other taxa: in yeast, we find a clear relationship between gene expression level and the fitness impact of reduction in gene dosage. To explain these observations, we propose a model based on the fact that the optimal expression level of a gene corresponds to a trade-off between the benefit and cost of its expression. This COSTEX model predicts that selective pressure against mutations changing gene expression level or affecting the encoded protein should on average be stronger in highly expressed genes and hence that both the frequency of gene loss and the rate of protein evolution should correlate negatively with gene expression. Thus, the COSTEX model provides a simple and common explanation for the general relationship observed between the level of gene expression and the different facets of gene evolution.

  3. Noise minimization in eukaryotic gene expression.

    Directory of Open Access Journals (Sweden)

    Hunter B Fraser

    2004-06-01

    Full Text Available All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or "noise." Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection.

  4. Noise minimization in eukaryotic gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Fraser, Hunter B.; Hirsh, Aaron E.; Giaever, Guri; Kumm, Jochen; Eisen, Michael B.

    2004-01-15

    All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or noise. Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection.

  5. Noise minimization in eukaryotic gene expression

    International Nuclear Information System (INIS)

    Fraser, Hunter B.; Hirsh, Aaron E.; Giaever, Guri; Kumm, Jochen; Eisen, Michael B.

    2004-01-01

    All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or noise. Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection

  6. Identification of wild soybean (Glycine soja) TIFY family genes and their expression profiling analysis under bicarbonate stress.

    Science.gov (United States)

    Zhu, Dan; Bai, Xi; Luo, Xiao; Chen, Qin; Cai, Hua; Ji, Wei; Zhu, Yanming

    2013-02-01

    Wild soybean (Glycine soja L. G07256) exhibits a greater adaptability to soil bicarbonate stress than cultivated soybean, and recent discoveries show that TIFY family genes are involved in the response to several abiotic stresses. A genomic and transcriptomic analysis of all TIFY genes in G. soja, compared with G. max, will provide insight into the function of this gene family in plant bicarbonate stress response. This article identified and characterized 34 TIFY genes in G. soja. Sequence analyses indicated that most GsTIFY proteins had two conserved domains: TIFY and Jas. Phylogenetic analyses suggested that these GsTIFY genes could be classified into two groups. A clustering analysis of all GsTIFY transcript expression profiles from bicarbonate stress treated G. soja showed that there were five different transcript patterns in leaves and six different transcript patterns in roots when the GsTIFY family responds to bicarbonate stress. Moreover, the expression level changes of all TIFY genes in cultivated soybean, treated with bicarbonate stress, were also verified. The expression comparison analysis of TIFYs between wild and cultivated soybeans confirmed that, different from the cultivated soybean, GsTIFY (10a, 10b, 10c, 10d, 10e, 10f, 11a, and 11b) were dramatically up-regulated at the early stage of stress, while GsTIFY 1c and 2b were significantly up-regulated at the later period of stress. The frequently stress responsive and diverse expression profiles of the GsTIFY gene family suggests that this family may play important roles in plant environmental stress responses and adaptation.

  7. Positive selection on gene expression in the human brain

    DEFF Research Database (Denmark)

    Khaitovich, Philipp; Tang, Kun; Franz, Henriette

    2006-01-01

    Recent work has shown that the expression levels of genes transcribed in the brains of humans and chimpanzees have changed less than those of genes transcribed in other tissues [1] . However, when gene expression changes are mapped onto the evolutionary lineage in which they occurred, the brain...... shows more changes than other tissues in the human lineage compared to the chimpanzee lineage [1] , [2] and [3] . There are two possible explanations for this: either positive selection drove more gene expression changes to fixation in the human brain than in the chimpanzee brain, or genes expressed...... in the brain experienced less purifying selection in humans than in chimpanzees, i.e. gene expression in the human brain is functionally less constrained. The first scenario would be supported if genes that changed their expression in the brain in the human lineage showed more selective sweeps than other genes...

  8. An algorithm to discover gene signatures with predictive potential

    Directory of Open Access Journals (Sweden)

    Hallett Robin M

    2010-09-01

    Full Text Available Abstract Background The advent of global gene expression profiling has generated unprecedented insight into our molecular understanding of cancer, including breast cancer. For example, human breast cancer patients display significant diversity in terms of their survival, recurrence, metastasis as well as response to treatment. These patient outcomes can be predicted by the transcriptional programs of their individual breast tumors. Predictive gene signatures allow us to correctly classify human breast tumors into various risk groups as well as to more accurately target therapy to ensure more durable cancer treatment. Results Here we present a novel algorithm to generate gene signatures with predictive potential. The method first classifies the expression intensity for each gene as determined by global gene expression profiling as low, average or high. The matrix containing the classified data for each gene is then used to score the expression of each gene based its individual ability to predict the patient characteristic of interest. Finally, all examined genes are ranked based on their predictive ability and the most highly ranked genes are included in the master gene signature, which is then ready for use as a predictor. This method was used to accurately predict the survival outcomes in a cohort of human breast cancer patients. Conclusions We confirmed the capacity of our algorithm to generate gene signatures with bona fide predictive ability. The simplicity of our algorithm will enable biological researchers to quickly generate valuable gene signatures without specialized software or extensive bioinformatics training.

  9. Genome-wide identification and comparative expression analysis of LEA genes in watermelon and melon genomes.

    Science.gov (United States)

    Celik Altunoglu, Yasemin; Baloglu, Mehmet Cengiz; Baloglu, Pinar; Yer, Esra Nurten; Kara, Sibel

    2017-01-01

    Late embryogenesis abundant (LEA) proteins are large and diverse group of polypeptides which were first identified during seed dehydration and then in vegetative plant tissues during different stress responses. Now, gene family members of LEA proteins have been detected in various organisms. However, there is no report for this protein family in watermelon and melon until this study. A total of 73 LEA genes from watermelon ( ClLEA ) and 61 LEA genes from melon ( CmLEA ) were identified in this comprehensive study. They were classified into four and three distinct clusters in watermelon and melon, respectively. There was a correlation between gene structure and motif composition among each LEA groups. Segmental duplication played an important role for LEA gene expansion in watermelon. Maximum gene ontology of LEA genes was observed with poplar LEA genes. For evaluation of tissue specific expression patterns of ClLEA and CmLEA genes, publicly available RNA-seq data were analyzed. The expression analysis of selected LEA genes in root and leaf tissues of drought-stressed watermelon and melon were examined using qRT-PCR. Among them, ClLEA - 12 - 17 - 46 genes were quickly induced after drought application. Therefore, they might be considered as early response genes for water limitation conditions in watermelon. In addition, CmLEA - 42 - 43 genes were found to be up-regulated in both tissues of melon under drought stress. Our results can open up new frontiers about understanding of functions of these important family members under normal developmental stages and stress conditions by bioinformatics and transcriptomic approaches.

  10. A stochastic approach to multi-gene expression dynamics

    International Nuclear Information System (INIS)

    Ochiai, T.; Nacher, J.C.; Akutsu, T.

    2005-01-01

    In the last years, tens of thousands gene expression profiles for cells of several organisms have been monitored. Gene expression is a complex transcriptional process where mRNA molecules are translated into proteins, which control most of the cell functions. In this process, the correlation among genes is crucial to determine the specific functions of genes. Here, we propose a novel multi-dimensional stochastic approach to deal with the gene correlation phenomena. Interestingly, our stochastic framework suggests that the study of the gene correlation requires only one theoretical assumption-Markov property-and the experimental transition probability, which characterizes the gene correlation system. Finally, a gene expression experiment is proposed for future applications of the model

  11. Assays for noninvasive imaging of reporter gene expression

    International Nuclear Information System (INIS)

    Gambhir, S.S.; Barrio, J.R.; Herschman, H.R.; Phelps, M.E.

    1999-01-01

    Repeated, noninvasive imaging of reporter gene expression is emerging as a valuable tool for monitoring the expression of genes in animals and humans. Monitoring of organ/cell transplantation in living animals and humans, and the assessment of environmental, behavioral, and pharmacologic modulation of gene expression in transgenic animals should soon be possible. The earliest clinical application is likely to be monitoring human gene therapy in tumors transduced with the herpes simplex virus type 1 thymidine kinase (HSV1-tk) suicide gene. Several candidate assays for imaging reporter gene expression have been studied, utilizing cytosine deaminase (CD), HSV1-tk, and dopamine 2 receptor (D2R) as reporter genes. For the HSV1-tk reporter gene, both uracil nucleoside derivatives (e.g., 5-iodo-2'-fluoro-2'-deoxy-1-β-D-arabinofuranosyl-5-iodouracil [FIAU] labeled with 124 I, 131 I ) and acycloguanosine derivatives {e.g., 8-[ 18 F]fluoro-9-[[2-hydroxy-1-(hydroxymethyl)ethoxy]methyl]guanine (8-[ 18 F]-fluoroganciclovir) ([ 18 F]FGCV), 9-[(3-[ 18 F]fluoro-1-hydroxy-2-propoxy)methyl]guanine ([ 18 F]FHPG)} have been investigated as reporter probes. For the D2R reporter gene, a derivative of spiperone {3-(2'-[ 18 F]-Fluoroethyl)spiperone ([ 18 F]FESP)} has been used with positron emission tomography (PET) imaging. In this review, the principles and specific assays for imaging reporter gene expression are presented and discussed. Specific examples utilizing adenoviral-mediated delivery of a reporter gene as well as tumors expressing reporter genes are discussed

  12. Identification of Differentially Expressed Genes Associated with Apple Fruit Ripening and Softening by Suppression Subtractive Hybridization.

    Science.gov (United States)

    Zhang, Zongying; Jiang, Shenghui; Wang, Nan; Li, Min; Ji, Xiaohao; Sun, Shasha; Liu, Jingxuan; Wang, Deyun; Xu, Haifeng; Qi, Sumin; Wu, Shujing; Fei, Zhangjun; Feng, Shouqian; Chen, Xuesen

    2015-01-01

    Apple is one of the most economically important horticultural fruit crops worldwide. It is critical to gain insights into fruit ripening and softening to improve apple fruit quality and extend shelf life. In this study, forward and reverse suppression subtractive hybridization libraries were generated from 'Taishanzaoxia' apple fruits sampled around the ethylene climacteric to isolate ripening- and softening-related genes. A set of 648 unigenes were derived from sequence alignment and cluster assembly of 918 expressed sequence tags. According to gene ontology functional classification, 390 out of 443 unigenes (88%) were assigned to the biological process category, 356 unigenes (80%) were classified in the molecular function category, and 381 unigenes (86%) were allocated to the cellular component category. A total of 26 unigenes differentially expressed during fruit development period were analyzed by quantitative RT-PCR. These genes were involved in cell wall modification, anthocyanin biosynthesis, aroma production, stress response, metabolism, transcription, or were non-annotated. Some genes associated with cell wall modification, anthocyanin biosynthesis and aroma production were up-regulated and significantly correlated with ethylene production, suggesting that fruit texture, coloration and aroma may be regulated by ethylene in 'Taishanzaoxia'. Some of the identified unigenes associated with fruit ripening and softening have not been characterized in public databases. The results contribute to an improved characterization of changes in gene expression during apple fruit ripening and softening.

  13. PRAME gene expression profile in medulloblastoma

    Directory of Open Access Journals (Sweden)

    Tânia Maria Vulcani-Freitas

    2011-02-01

    Full Text Available Medulloblastoma is the most common malignant tumors of central nervous system in the childhood. The treatment is severe, harmful and, thus, has a dismal prognosis. As PRAME is present in various cancers, including meduloblastoma, and has limited expression in normal tissues, this antigen can be an ideal vaccine target for tumor immunotherapy. In order to find a potential molecular target, we investigated PRAME expression in medulloblastoma fragments and we compare the results with the clinical features of each patient. Analysis of gene expression was performed by real-time quantitative PCR from 37 tumor samples. The Mann-Whitney test was used to analysis the relationship between gene expression and clinical characteristics. Kaplan-Meier curves were used to evaluate survival. PRAME was overexpressed in 84% samples. But no statistical association was found between clinical features and PRAME overexpression. Despite that PRAME gene could be a strong candidate for immunotherapy since it is highly expressed in medulloblastomas.

  14. A Critical Evaluation of Network and Pathway-Based Classifiers for Outcome Prediction in Breast Cancer

    NARCIS (Netherlands)

    C. Staiger (Christine); S. Cadot; R Kooter; M. Dittrich (Marcus); T. Müller (Tobias); G.W. Klau (Gunnar); L.F.A. Wessels (Lodewyk)

    2012-01-01

    htmlabstractRecently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically

  15. Inflammation, Adenoma and Cancer: Objective Classification of Colon Biopsy Specimens with Gene Expression Signature

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    Orsolya Galamb

    2008-01-01

    Full Text Available Gene expression analysis of colon biopsies using high-density oligonucleotide microarrays can contribute to the understanding of local pathophysiological alterations and to functional classification of adenoma (15 samples, colorectal carcinomas (CRC (15 and inflammatory bowel diseases (IBD (14. Total RNA was extracted, amplified and biotinylated from frozen colonic biopsies. Genome-wide gene expression profile was evaluated by HGU133plus2 microarrays and verified by RT-PCR. We applied two independent methods for data normalization and used PAM for feature selection. Leave one-out stepwise discriminant analysis was performed. Top validated genes included collagenIVα1, lipocalin-2, calumenin, aquaporin-8 genes in CRC; CD44, met proto-oncogene, chemokine ligand-12, ADAM-like decysin-1 and ATP-binding casette-A8 genes in adenoma; and lipocalin-2, ubiquitin D and IFITM2 genes in IBD. Best differentiating markers between Ulcerative colitis and Crohn's disease were cyclin-G2; tripartite motif-containing-31; TNFR shedding aminopeptidase regulator-1 and AMICA. The discriminant analysis was able to classify the samples in overall 96.2% using 7 discriminatory genes (indoleamine-pyrrole-2,3-dioxygenase, ectodermal-neural cortex, TIMP3, fucosyltransferase-8, collectin sub-family member 12, carboxypeptidase D, and transglutaminase-2. Using routine biopsy samples we successfully performed whole genomic microarray analysis to identify discriminative signatures. Our results provide further insight into the pathophysiological background of colonic diseases. The results set up data warehouse which can be mined further.

  16. Systematic identification of human housekeeping genes possibly useful as references in gene expression studies.

    Science.gov (United States)

    Caracausi, Maria; Piovesan, Allison; Antonaros, Francesca; Strippoli, Pierluigi; Vitale, Lorenza; Pelleri, Maria Chiara

    2017-09-01

    The ideal reference, or control, gene for the study of gene expression in a given organism should be expressed at a medium‑high level for easy detection, should be expressed at a constant/stable level throughout different cell types and within the same cell type undergoing different treatments, and should maintain these features through as many different tissues of the organism. From a biological point of view, these theoretical requirements of an ideal reference gene appear to be best suited to housekeeping (HK) genes. Recent advancements in the quality and completeness of human expression microarray data and in their statistical analysis may provide new clues toward the quantitative standardization of human gene expression studies in biology and medicine, both cross‑ and within‑tissue. The systematic approach used by the present study is based on the Transcriptome Mapper tool and exploits the automated reassignment of probes to corresponding genes, intra‑ and inter‑sample normalization, elaboration and representation of gene expression values in linear form within an indexed and searchable database with a graphical interface recording quantitative levels of expression, expression variability and cross‑tissue width of expression for more than 31,000 transcripts. The present study conducted a meta‑analysis of a pool of 646 expression profile data sets from 54 different human tissues and identified actin γ 1 as the HK gene that best fits the combination of all the traditional criteria to be used as a reference gene for general use; two ribosomal protein genes, RPS18 and RPS27, and one aquaporin gene, POM121 transmembrane nucleporin C, were also identified. The present study provided a list of tissue‑ and organ‑specific genes that may be most suited for the following individual tissues/organs: Adipose tissue, bone marrow, brain, heart, kidney, liver, lung, ovary, skeletal muscle and testis; and also provides in these cases a representative

  17. The effect of heat stress on gene expression, synthesis of steroids, and apoptosis in bovine granulosa cells.

    Science.gov (United States)

    Li, Lian; Wu, Jie; Luo, Man; Sun, Yu; Wang, Genlin

    2016-05-01

    Summer heat stress (HS) is a major contributing factor in low fertility in lactating dairy cows in hot environments. Heat stress inhibits ovarian follicular development leading to diminished reproductive efficiency of dairy cows during summer. Ovarian follicle development is a complex process. During follicle development, granulosa cells (GCs) replicate, secrete hormones, and support the growth of the oocyte. To obtain an overview of the effects of heat stress on GCs, digital gene expression profiling was employed to screen and identify differentially expressed genes (DEGs; false discovery rate (FDR) ≤ 0.001, fold change ≥2) of cultured GCs during heat stress. A total of 1211 DEGs including 175 upregulated and 1036 downregulated ones were identified, of which DEGs can be classified into Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The results suggested that heat stress triggers a dramatic and complex program of altered gene expression in GCs. We hypothesized that heat stress could induce the apoptosis and dysfunction of GCs. Real-time reverse transcription-polymerase chain reaction (RT-PCR) was used to evaluate the expression of steroidogenic genes (steroidogenic acute regulatory protein (Star), cytochrome P-450 (CYP11A1), CYP19A1, and steroidogenic factor 1 (SF-1)) and apoptosis-related genes (caspase-3, BCL-2, and BAX). Radio immunoassay (RIA) was used to analyze the level of 17β-estradiol (E2) and progesterone (P4). We also assessed the apoptosis of GCs by flow cytometry. Our data suggested that heat stress induced GC apoptosis through the BAX/BCL-2 pathway and reduced the steroidogenic gene messenger RNA (mRNA) expression and E2 synthesis. These results suggest that the decreased function of GCs may cause ovarian dysfunction and offer an improved understanding of the molecular mechanism responsible for the low fertility in cattle in summer.

  18. SIGNATURE: A workbench for gene expression signature analysis

    Directory of Open Access Journals (Sweden)

    Chang Jeffrey T

    2011-11-01

    Full Text Available Abstract Background The biological phenotype of a cell, such as a characteristic visual image or behavior, reflects activities derived from the expression of collections of genes. As such, an ability to measure the expression of these genes provides an opportunity to develop more precise and varied sets of phenotypes. However, to use this approach requires computational methods that are difficult to implement and apply, and thus there is a critical need for intelligent software tools that can reduce the technical burden of the analysis. Tools for gene expression analyses are unusually difficult to implement in a user-friendly way because their application requires a combination of biological data curation, statistical computational methods, and database expertise. Results We have developed SIGNATURE, a web-based resource that simplifies gene expression signature analysis by providing software, data, and protocols to perform the analysis successfully. This resource uses Bayesian methods for processing gene expression data coupled with a curated database of gene expression signatures, all carried out within a GenePattern web interface for easy use and access. Conclusions SIGNATURE is available for public use at http://genepattern.genome.duke.edu/signature/.

  19. Genomic Organization, Phylogenetic Comparison and Differential Expression of the SBP-Box Family Genes in Grape

    Science.gov (United States)

    Hou, Hongmin; Li, Jun; Gao, Min; Singer, Stacy D.; Wang, Hao; Mao, Linyong; Fei, Zhangjun; Wang, Xiping

    2013-01-01

    Background The SBP-box gene family is specific to plants and encodes a class of zinc finger-containing transcription factors with a broad range of functions. Although SBP-box genes have been identified in numerous plants including green algae, moss, silver birch, snapdragon, Arabidopsis, rice and maize, there is little information concerning SBP-box genes, or the corresponding miR156/157, function in grapevine. Methodology/Principal Findings Eighteen SBP-box gene family members were identified in Vitis vinifera, twelve of which bore sequences that were complementary to miRNA156/157. Phylogenetic reconstruction demonstrated that plant SBP-domain proteins could be classified into seven subgroups, with the V. vinifera SBP-domain proteins being more closely related to SBP-domain proteins from dicotyledonous angiosperms than those from monocotyledonous angiosperms. In addition, synteny analysis between grape and Arabidopsis demonstrated that homologs of several grape SBP genes were found in corresponding syntenic blocks of Arabidopsis. Expression analysis of the grape SBP-box genes in various organs and at different stages of fruit development in V. quinquangularis ‘Shang-24’ revealed distinct spatiotemporal patterns. While the majority of the grape SBP-box genes lacking a miR156/157 target site were expressed ubiquitously and constitutively, most genes bearing a miR156/157 target site exhibited distinct expression patterns, possibly due to the inhibitory role of the microRNA. Furthermore, microarray data mining and quantitative real-time RT-PCR analysis identified several grape SBP-box genes that are potentially involved in the defense against biotic and abiotic stresses. Conclusion The results presented here provide a further understanding of SBP-box gene function in plants, and yields additional insights into the mechanism of stress management in grape, which may have important implications for the future success of this crop. PMID:23527172

  20. Automatic Human Facial Expression Recognition Based on Integrated Classifier From Monocular Video with Uncalibrated Camera

    Directory of Open Access Journals (Sweden)

    Yu Tao

    2017-01-01

    Full Text Available An automatic recognition framework for human facial expressions from a monocular video with an uncalibrated camera is proposed. The expression characteristics are first acquired from a kind of deformable template, similar to a facial muscle distribution. After associated regularization, the time sequences from the trait changes in space-time under complete expressional production are then arranged line by line in a matrix. Next, the matrix dimensionality is reduced by a method of manifold learning of neighborhood-preserving embedding. Finally, the refined matrix containing the expression trait information is recognized by a classifier that integrates the hidden conditional random field (HCRF and support vector machine (SVM. In an experiment using the Cohn–Kanade database, the proposed method showed a comparatively higher recognition rate than the individual HCRF or SVM methods in direct recognition from two-dimensional human face traits. Moreover, the proposed method was shown to be more robust than the typical Kotsia method because the former contains more structural characteristics of the data to be classified in space-time

  1. Plasticity-Related Gene Expression During Eszopiclone-Induced Sleep.

    Science.gov (United States)

    Gerashchenko, Dmitry; Pasumarthi, Ravi K; Kilduff, Thomas S

    2017-07-01

    Experimental evidence suggests that restorative processes depend on synaptic plasticity changes in the brain during sleep. We used the expression of plasticity-related genes to assess synaptic plasticity changes during drug-induced sleep. We first characterized sleep induced by eszopiclone in mice during baseline conditions and during the recovery from sleep deprivation. We then compared the expression of 18 genes and two miRNAs critically involved in synaptic plasticity in these mice. Gene expression was assessed in the cerebral cortex and hippocampus by the TaqMan reverse transcription polymerase chain reaction and correlated with sleep parameters. Eszopiclone reduced the latency to nonrapid eye movement (NREM) sleep and increased NREM sleep amounts. Eszopiclone had no effect on slow wave activity (SWA) during baseline conditions but reduced the SWA increase during recovery sleep (RS) after sleep deprivation. Gene expression analyses revealed three distinct patterns: (1) four genes had higher expression either in the cortex or hippocampus in the group of mice with increased amounts of wakefulness; (2) a large proportion of plasticity-related genes (7 out of 18 genes) had higher expression during RS in the cortex but not in the hippocampus; and (3) six genes and the two miRNAs showed no significant changes across conditions. Even at a relatively high dose (20 mg/kg), eszopiclone did not reduce the expression of plasticity-related genes during RS period in the cortex. These results indicate that gene expression associated with synaptic plasticity occurs in the cortex in the presence of a hypnotic medication. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

  2. Evaluation of suitable reference genes for gene expression studies in bovine muscular tissue

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    Dunner Susana

    2008-09-01

    Full Text Available Abstract Background Real-time reverse transcriptase quantitative polymerase chain reaction (real-time RTqPCR is a technique used to measure mRNA species copy number as a way to determine key genes involved in different biological processes. However, the expression level of these key genes may vary among tissues or cells not only as a consequence of differential expression but also due to different factors, including choice of reference genes to normalize the expression levels of the target genes; thus the selection of reference genes is critical for expression studies. For this purpose, ten candidate reference genes were investigated in bovine muscular tissue. Results The value of stability of ten candidate reference genes included in three groups was estimated: the so called 'classical housekeeping' genes (18S, GAPDH and ACTB, a second set of genes used in expression studies conducted on other tissues (B2M, RPII, UBC and HMBS and a third set of novel genes (SF3A1, EEF1A2 and CASC3. Three different statistical algorithms were used to rank the genes by their stability measures as produced by geNorm, NormFinder and Bestkeeper. The three methods tend to agree on the most stably expressed genes and the least in muscular tissue. EEF1A2 and HMBS followed by SF3A1, ACTB, and CASC3 can be considered as stable reference genes, and B2M, RPII, UBC and GAPDH would not be appropriate. Although the rRNA-18S stability measure seems to be within the range of acceptance, its use is not recommended because its synthesis regulation is not representative of mRNA levels. Conclusion Based on geNorm algorithm, we propose the use of three genes SF3A1, EEF1A2 and HMBS as references for normalization of real-time RTqPCR in muscle expression studies.

  3. Expression profiling identifies genes involved in emphysema severity

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    Bowman Rayleen V

    2009-09-01

    Full Text Available Abstract Chronic obstructive pulmonary disease (COPD is a major public health problem. The aim of this study was to identify genes involved in emphysema severity in COPD patients. Gene expression profiling was performed on total RNA extracted from non-tumor lung tissue from 30 smokers with emphysema. Class comparison analysis based on gas transfer measurement was performed to identify differentially expressed genes. Genes were then selected for technical validation by quantitative reverse transcriptase-PCR (qRT-PCR if also represented on microarray platforms used in previously published emphysema studies. Genes technically validated advanced to tests of biological replication by qRT-PCR using an independent test set of 62 lung samples. Class comparison identified 98 differentially expressed genes (p p Gene expression profiling of lung from emphysema patients identified seven candidate genes associated with emphysema severity including COL6A3, SERPINF1, ZNHIT6, NEDD4, CDKN2A, NRN1 and GSTM3.

  4. Decoupling Linear and Nonlinear Associations of Gene Expression

    KAUST Repository

    Itakura, Alan

    2013-05-01

    The FANTOM consortium has generated a large gene expression dataset of different cell lines and tissue cultures using the single-molecule sequencing technology of HeliscopeCAGE. This provides a unique opportunity to investigate novel associations between gene expression over time and different cell types. Here, we create a MatLab wrapper for a powerful and computationally intensive set of statistics known as Maximal Information Coefficient, and then calculate this statistic for a large, comprehensive dataset containing gene expression of a variety of differentiating tissues. We then distinguish between linear and nonlinear associations, and then create gene association networks. Following this analysis, we are then able to identify clusters of linear gene associations that then associate nonlinearly with other clusters of linearity, providing insight to much more complex connections between gene expression patterns than previously anticipated.

  5. Decoupling Linear and Nonlinear Associations of Gene Expression

    KAUST Repository

    Itakura, Alan

    2013-01-01

    The FANTOM consortium has generated a large gene expression dataset of different cell lines and tissue cultures using the single-molecule sequencing technology of HeliscopeCAGE. This provides a unique opportunity to investigate novel associations between gene expression over time and different cell types. Here, we create a MatLab wrapper for a powerful and computationally intensive set of statistics known as Maximal Information Coefficient, and then calculate this statistic for a large, comprehensive dataset containing gene expression of a variety of differentiating tissues. We then distinguish between linear and nonlinear associations, and then create gene association networks. Following this analysis, we are then able to identify clusters of linear gene associations that then associate nonlinearly with other clusters of linearity, providing insight to much more complex connections between gene expression patterns than previously anticipated.

  6. Genetic architecture of gene expression in the chicken

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    Stanley Dragana

    2013-01-01

    Full Text Available Abstract Background The annotation of many genomes is limited, with a large proportion of identified genes lacking functional assignments. The construction of gene co-expression networks is a powerful approach that presents a way of integrating information from diverse gene expression datasets into a unified analysis which allows inferences to be drawn about the role of previously uncharacterised genes. Using this approach, we generated a condition-free gene co-expression network for the chicken using data from 1,043 publically available Affymetrix GeneChip Chicken Genome Arrays. This data was generated from a diverse range of experiments, including different tissues and experimental conditions. Our aim was to identify gene co-expression modules and generate a tool to facilitate exploration of the functional chicken genome. Results Fifteen modules, containing between 24 and 473 genes, were identified in the condition-free network. Most of the modules showed strong functional enrichment for particular Gene Ontology categories. However, a few showed no enrichment. Transcription factor binding site enrichment was also noted. Conclusions We have demonstrated that this chicken gene co-expression network is a useful tool in gene function prediction and the identification of putative novel transcription factors and binding sites. This work highlights the relevance of this methodology for functional prediction in poorly annotated genomes such as the chicken.

  7. Bayesian assignment of gene ontology terms to gene expression experiments

    Science.gov (United States)

    Sykacek, P.

    2012-01-01

    Motivation: Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. Results: This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Availability: Source code under GPL license is available from the author. Contact: peter.sykacek@boku.ac.at PMID:22962488

  8. Bayesian assignment of gene ontology terms to gene expression experiments.

    Science.gov (United States)

    Sykacek, P

    2012-09-15

    Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Source code under GPL license is available from the author. peter.sykacek@boku.ac.at.

  9. Gene expression profile data for mouse facial development

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    Sonia M. Leach

    2017-08-01

    Full Text Available This article contains data related to the research articles "Spatial and Temporal Analysis of Gene Expression during Growth and Fusion of the Mouse Facial Prominences" (Feng et al., 2009 [1] and “Systems Biology of facial development: contributions of ectoderm and mesenchyme” (Hooper et al., 2017 In press [2]. Embryonic mammalian craniofacial development is a complex process involving the growth, morphogenesis, and fusion of distinct facial prominences into a functional whole. Aberrant gene regulation during this process can lead to severe craniofacial birth defects, including orofacial clefting. As a means to understand the genes involved in facial development, we had previously dissected the embryonic mouse face into distinct prominences: the mandibular, maxillary or nasal between E10.5 and E12.5. The prominences were then processed intact, or separated into ectoderm and mesenchyme layers, prior analysis of RNA expression using microarrays (Feng et al., 2009, Hooper et al., 2017 in press [1,2]. Here, individual gene expression profiles have been built from these datasets that illustrate the timing of gene expression in whole prominences or in the separated tissue layers. The data profiles are presented as an indexed and clickable list of the genes each linked to a graphical image of that gene׳s expression profile in the ectoderm, mesenchyme, or intact prominence. These data files will enable investigators to obtain a rapid assessment of the relative expression level of any gene on the array with respect to time, tissue, prominence, and expression trajectory.

  10. Microarray analysis of gene expression in peripheral blood mononuclear cells from dioxin-exposed human subjects

    International Nuclear Information System (INIS)

    McHale, Cliona M.; Zhang, Luoping; Hubbard, Alan E.; Zhao, Xin; Baccarelli, Andrea; Pesatori, Angela C.; Smith, Martyn T.; Landi, Maria Teresa

    2007-01-01

    Tetrachlorodibenzo-p-dioxin (TCDD) is classified as a human carcinogen and exerts toxic effects on the skin (chloracne). Effects on reproductive, immunological, and endocrine systems have also been observed in animal models. TCDD acts through the aryl hydrocarbon receptor (AhR) pathway influencing largely unknown gene networks. An industrial accident in Seveso, Italy in 1976 exposed thousands of people to substantial quantities of TCDD. Twenty years after the exposure, this study examines global gene expression in the mononuclear cells of 26 Seveso female never smokers, with similar age, alcohol consumption, use of medications, and background plasma levels of 22 dioxin congeners unrelated to the Seveso accident. Plasma dioxin levels were still elevated in the exposed subjects. We performed analyses in two different comparison groups. The first included high-exposed study subjects compared with individuals with background TCDD levels (average plasma levels 99.4 and 6.7 ppt, respectively); the second compared subjects who developed chloracne after the accident, and those who did not develop this disease. Overall, we observed a modest alteration of gene expression based on dioxin levels or on chloracne status. In the comparison between high levels and background levels of TCDD, four histone genes were up-regulated and modified expression of HIST1H3H was confirmed by real-time PCR. In the comparison between chloracne case-control subjects, five hemoglobin genes were up-regulated. Pathway analysis revealed two major networks for each comparison, involving cell proliferation, apoptosis, immunological and hematological disease, and other pathways. Further examination of the role of these genes in dioxin induced-toxicity is warranted

  11. Integrated olfactory receptor and microarray gene expression databases

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    Crasto Chiquito J

    2007-06-01

    Full Text Available Abstract Background Gene expression patterns of olfactory receptors (ORs are an important component of the signal encoding mechanism in the olfactory system since they determine the interactions between odorant ligands and sensory neurons. We have developed the Olfactory Receptor Microarray Database (ORMD to house OR gene expression data. ORMD is integrated with the Olfactory Receptor Database (ORDB, which is a key repository of OR gene information. Both databases aim to aid experimental research related to olfaction. Description ORMD is a Web-accessible database that provides a secure data repository for OR microarray experiments. It contains both publicly available and private data; accessing the latter requires authenticated login. The ORMD is designed to allow users to not only deposit gene expression data but also manage their projects/experiments. For example, contributors can choose whether to make their datasets public. For each experiment, users can download the raw data files and view and export the gene expression data. For each OR gene being probed in a microarray experiment, a hyperlink to that gene in ORDB provides access to genomic and proteomic information related to the corresponding olfactory receptor. Individual ORs archived in ORDB are also linked to ORMD, allowing users access to the related microarray gene expression data. Conclusion ORMD serves as a data repository and project management system. It facilitates the study of microarray experiments of gene expression in the olfactory system. In conjunction with ORDB, ORMD integrates gene expression data with the genomic and functional data of ORs, and is thus a useful resource for both olfactory researchers and the public.

  12. Gene expression analysis of flax seed development

    Science.gov (United States)

    2011-01-01

    Background Flax, Linum usitatissimum L., is an important crop whose seed oil and stem fiber have multiple industrial applications. Flax seeds are also well-known for their nutritional attributes, viz., omega-3 fatty acids in the oil and lignans and mucilage from the seed coat. In spite of the importance of this crop, there are few molecular resources that can be utilized toward improving seed traits. Here, we describe flax embryo and seed development and generation of comprehensive genomic resources for the flax seed. Results We describe a large-scale generation and analysis of expressed sequences in various tissues. Collectively, the 13 libraries we have used provide a broad representation of genes active in developing embryos (globular, heart, torpedo, cotyledon and mature stages) seed coats (globular and torpedo stages) and endosperm (pooled globular to torpedo stages) and genes expressed in flowers, etiolated seedlings, leaves, and stem tissue. A total of 261,272 expressed sequence tags (EST) (GenBank accessions LIBEST_026995 to LIBEST_027011) were generated. These EST libraries included transcription factor genes that are typically expressed at low levels, indicating that the depth is adequate for in silico expression analysis. Assembly of the ESTs resulted in 30,640 unigenes and 82% of these could be identified on the basis of homology to known and hypothetical genes from other plants. When compared with fully sequenced plant genomes, the flax unigenes resembled poplar and castor bean more than grape, sorghum, rice or Arabidopsis. Nearly one-fifth of these (5,152) had no homologs in sequences reported for any organism, suggesting that this category represents genes that are likely unique to flax. Digital analyses revealed gene expression dynamics for the biosynthesis of a number of important seed constituents during seed development. Conclusions We have developed a foundational database of expressed sequences and collection of plasmid clones that comprise

  13. Gene expression analysis of flax seed development

    Directory of Open Access Journals (Sweden)

    Sharpe Andrew

    2011-04-01

    Full Text Available Abstract Background Flax, Linum usitatissimum L., is an important crop whose seed oil and stem fiber have multiple industrial applications. Flax seeds are also well-known for their nutritional attributes, viz., omega-3 fatty acids in the oil and lignans and mucilage from the seed coat. In spite of the importance of this crop, there are few molecular resources that can be utilized toward improving seed traits. Here, we describe flax embryo and seed development and generation of comprehensive genomic resources for the flax seed. Results We describe a large-scale generation and analysis of expressed sequences in various tissues. Collectively, the 13 libraries we have used provide a broad representation of genes active in developing embryos (globular, heart, torpedo, cotyledon and mature stages seed coats (globular and torpedo stages and endosperm (pooled globular to torpedo stages and genes expressed in flowers, etiolated seedlings, leaves, and stem tissue. A total of 261,272 expressed sequence tags (EST (GenBank accessions LIBEST_026995 to LIBEST_027011 were generated. These EST libraries included transcription factor genes that are typically expressed at low levels, indicating that the depth is adequate for in silico expression analysis. Assembly of the ESTs resulted in 30,640 unigenes and 82% of these could be identified on the basis of homology to known and hypothetical genes from other plants. When compared with fully sequenced plant genomes, the flax unigenes resembled poplar and castor bean more than grape, sorghum, rice or Arabidopsis. Nearly one-fifth of these (5,152 had no homologs in sequences reported for any organism, suggesting that this category represents genes that are likely unique to flax. Digital analyses revealed gene expression dynamics for the biosynthesis of a number of important seed constituents during seed development. Conclusions We have developed a foundational database of expressed sequences and collection of plasmid

  14. Genome-Wide Identification and Expression Analysis of WRKY Gene Family in Capsicum annuum L.

    Science.gov (United States)

    Diao, Wei-Ping; Snyder, John C; Wang, Shu-Bin; Liu, Jin-Bing; Pan, Bao-Gui; Guo, Guang-Jun; Wei, Ge

    2016-01-01

    The WRKY family of transcription factors is one of the most important families of plant transcriptional regulators with members regulating multiple biological processes, especially in regulating defense against biotic and abiotic stresses. However, little information is available about WRKYs in pepper (Capsicum annuum L.). The recent release of completely assembled genome sequences of pepper allowed us to perform a genome-wide investigation for pepper WRKY proteins. In the present study, a total of 71 WRKY genes were identified in the pepper genome. According to structural features of their encoded proteins, the pepper WRKY genes (CaWRKY) were classified into three main groups, with the second group further divided into five subgroups. Genome mapping analysis revealed that CaWRKY were enriched on four chromosomes, especially on chromosome 1, and 15.5% of the family members were tandemly duplicated genes. A phylogenetic tree was constructed depending on WRKY domain' sequences derived from pepper and Arabidopsis. The expression of 21 selected CaWRKY genes in response to seven different biotic and abiotic stresses (salt, heat shock, drought, Phytophtora capsici, SA, MeJA, and ABA) was evaluated by quantitative RT-PCR; Some CaWRKYs were highly expressed and up-regulated by stress treatment. Our results will provide a platform for functional identification and molecular breeding studies of WRKY genes in pepper.

  15. Identification of suitable reference genes for gene expression studies of shoulder instability.

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    Mariana Ferreira Leal

    Full Text Available Shoulder instability is a common shoulder injury, and patients present with plastic deformation of the glenohumeral capsule. Gene expression analysis may be a useful tool for increasing the general understanding of capsule deformation, and reverse-transcription quantitative polymerase chain reaction (RT-qPCR has become an effective method for such studies. Although RT-qPCR is highly sensitive and specific, it requires the use of suitable reference genes for data normalization to guarantee meaningful and reproducible results. In the present study, we evaluated the suitability of a set of reference genes using samples from the glenohumeral capsules of individuals with and without shoulder instability. We analyzed the expression of six commonly used reference genes (ACTB, B2M, GAPDH, HPRT1, TBP and TFRC in the antero-inferior, antero-superior and posterior portions of the glenohumeral capsules of cases and controls. The stability of the candidate reference gene expression was determined using four software packages: NormFinder, geNorm, BestKeeper and DataAssist. Overall, HPRT1 was the best single reference gene, and HPRT1 and B2M composed the best pair of reference genes from different analysis groups, including simultaneous analysis of all tissue samples. GenEx software was used to identify the optimal number of reference genes to be used for normalization and demonstrated that the accumulated standard deviation resulting from the use of 2 reference genes was similar to that resulting from the use of 3 or more reference genes. To identify the optimal combination of reference genes, we evaluated the expression of COL1A1. Although the use of different reference gene combinations yielded variable normalized quantities, the relative quantities within sample groups were similar and confirmed that no obvious differences were observed when using 2, 3 or 4 reference genes. Consequently, the use of 2 stable reference genes for normalization, especially

  16. Detecting microRNA activity from gene expression data

    LENUS (Irish Health Repository)

    Madden, Stephen F

    2010-05-18

    Abstract Background MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions. Results Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with gene expression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. Conclusions We describe a technique to integrate gene expression data and miRNA target predictions from multiple sources.

  17. Detecting microRNA activity from gene expression data.

    LENUS (Irish Health Repository)

    Madden, Stephen F

    2010-01-01

    BACKGROUND: MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions. RESULTS: Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with gene expression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. CONCLUSIONS: We describe a technique to integrate gene expression data and miRNA target predictions from multiple sources.

  18. Gene expression results in lipopolysaccharide-stimulated monocytes depend significantly on the choice of reference genes

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    Øvstebø Reidun

    2010-05-01

    Full Text Available Abstract Background Gene expression in lipopolysaccharide (LPS-stimulated monocytes is mainly studied by quantitative real-time reverse transcription PCR (RT-qPCR using GAPDH (glyceraldehyde 3-phosphate dehydrogenase or ACTB (beta-actin as reference gene for normalization. Expression of traditional reference genes has been shown to vary substantially under certain conditions leading to invalid results. To investigate whether traditional reference genes are stably expressed in LPS-stimulated monocytes or if RT-qPCR results are dependent on the choice of reference genes, we have assessed and evaluated gene expression stability of twelve candidate reference genes in this model system. Results Twelve candidate reference genes were quantified by RT-qPCR in LPS-stimulated, human monocytes and evaluated using the programs geNorm, Normfinder and BestKeeper. geNorm ranked PPIB (cyclophilin B, B2M (beta-2-microglobulin and PPIA (cyclophilin A as the best combination for gene expression normalization in LPS-stimulated monocytes. Normfinder suggested TBP (TATA-box binding protein and B2M as the best combination. Compared to these combinations, normalization using GAPDH alone resulted in significantly higher changes of TNF-α (tumor necrosis factor-alpha and IL10 (interleukin 10 expression. Moreover, a significant difference in TNF-α expression between monocytes stimulated with equimolar concentrations of LPS from N. meningitides and E. coli, respectively, was identified when using the suggested combinations of reference genes for normalization, but stayed unrecognized when employing a single reference gene, ACTB or GAPDH. Conclusions Gene expression levels in LPS-stimulated monocytes based on RT-qPCR results differ significantly when normalized to a single gene or a combination of stably expressed reference genes. Proper evaluation of reference gene stabiliy is therefore mandatory before reporting RT-qPCR results in LPS-stimulated monocytes.

  19. Differentially expressed genes in iron-induced prion protein conversion

    International Nuclear Information System (INIS)

    Kim, Minsun; Kim, Eun-hee; Choi, Bo-Ran; Woo, Hee-Jong

    2016-01-01

    The conversion of the cellular prion protein (PrP C ) to the protease-resistant isoform is the key event in chronic neurodegenerative diseases, including transmissible spongiform encephalopathies (TSEs). Increased iron in prion-related disease has been observed due to the prion protein-ferritin complex. Additionally, the accumulation and conversion of recombinant PrP (rPrP) is specifically derived from Fe(III) but not Fe(II). Fe(III)-mediated PK-resistant PrP (PrP res ) conversion occurs within a complex cellular environment rather than via direct contact between rPrP and Fe(III). In this study, differentially expressed genes correlated with prion degeneration by Fe(III) were identified using Affymetrix microarrays. Following Fe(III) treatment, 97 genes were differentially expressed, including 85 upregulated genes and 12 downregulated genes (≥1.5-fold change in expression). However, Fe(II) treatment produced moderate alterations in gene expression without inducing dramatic alterations in gene expression profiles. Moreover, functional grouping of identified genes indicated that the differentially regulated genes were highly associated with cell growth, cell maintenance, and intra- and extracellular transport. These findings showed that Fe(III) may influence the expression of genes involved in PrP folding by redox mechanisms. The identification of genes with altered expression patterns in neural cells may provide insights into PrP conversion mechanisms during the development and progression of prion-related diseases. - Highlights: • Differential genes correlated with prion degeneration by Fe(III) were identified. • Genes were identified in cell proliferation and intra- and extracellular transport. • In PrP degeneration, redox related genes were suggested. • Cbr2, Rsad2, Slc40a1, Amph and Mvd were expressed significantly.

  20. Regulation of meiotic gene expression in plants

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    Adele eZhou

    2014-08-01

    Full Text Available With the recent advances in genomics and sequencing technologies, databases of transcriptomes representing many cellular processes have been built. Meiotic transcriptomes in plants have been studied in Arabidopsis thaliana, rice (Oryza sativa, wheat (Triticum aestivum, petunia (Petunia hybrida, sunflower (Helianthus annuus, and maize (Zea mays. Studies in all organisms, but particularly in plants, indicate that a very large number of genes are expressed during meiosis, though relatively few of them seem to be required for the completion of meiosis. In this review, we focus on gene expression at the RNA level and analyze the meiotic transcriptome datasets and explore expression patterns of known meiotic genes to elucidate how gene expression could be regulated during meiosis. We also discuss mechanisms, such as chromatin organization and non-coding RNAs, that might be involved in the regulation of meiotic transcription patterns.

  1. Evaluating the consistency of gene sets used in the analysis of bacterial gene expression data

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    Tintle Nathan L

    2012-08-01

    Full Text Available Abstract Background Statistical analyses of whole genome expression data require functional information about genes in order to yield meaningful biological conclusions. The Gene Ontology (GO and Kyoto Encyclopedia of Genes and Genomes (KEGG are common sources of functionally grouped gene sets. For bacteria, the SEED and MicrobesOnline provide alternative, complementary sources of gene sets. To date, no comprehensive evaluation of the data obtained from these resources has been performed. Results We define a series of gene set consistency metrics directly related to the most common classes of statistical analyses for gene expression data, and then perform a comprehensive analysis of 3581 Affymetrix® gene expression arrays across 17 diverse bacteria. We find that gene sets obtained from GO and KEGG demonstrate lower consistency than those obtained from the SEED and MicrobesOnline, regardless of gene set size. Conclusions Despite the widespread use of GO and KEGG gene sets in bacterial gene expression data analysis, the SEED and MicrobesOnline provide more consistent sets for a wide variety of statistical analyses. Increased use of the SEED and MicrobesOnline gene sets in the analysis of bacterial gene expression data may improve statistical power and utility of expression data.

  2. Agave tequilana MADS genes show novel expression patterns in meristems, developing bulbils and floral organs.

    Science.gov (United States)

    Delgado Sandoval, Silvia del Carmen; Abraham Juárez, María Jazmín; Simpson, June

    2012-03-01

    Agave tequilana is a monocarpic perennial species that flowers after 5-8 years of vegetative growth signaling the end of the plant's life cycle. When fertilization is unsuccessful, vegetative bulbils are induced on the umbels of the inflorescence near the bracteoles from newly formed meristems. Although the regulation of inflorescence and flower development has been described in detail for monocarpic annuals and polycarpic species, little is known at the molecular level for these processes in monocarpic perennials, and few studies have been carried out on bulbils. Histological samples revealed the early induction of umbel meristems soon after the initiation of the vegetative to inflorescence transition in A. tequilana. To identify candidate genes involved in the regulation of floral induction, a search for MADS-box transcription factor ESTs was conducted using an A. tequilana transcriptome database. Seven different MIKC MADS genes classified into 6 different types were identified based on previously characterized A. thaliana and O. sativa MADS genes and sequences from non-grass monocotyledons. Quantitative real-time PCR analysis of the seven candidate MADS genes in vegetative, inflorescence, bulbil and floral tissues uncovered novel patterns of expression for some of the genes in comparison with orthologous genes characterized in other species. In situ hybridization studies using two different genes showed expression in specific tissues of vegetative meristems and floral buds. Distinct MADS gene regulatory patterns in A. tequilana may be related to the specific reproductive strategies employed by this species.

  3. Identifying key genes in rheumatoid arthritis by weighted gene co-expression network analysis.

    Science.gov (United States)

    Ma, Chunhui; Lv, Qi; Teng, Songsong; Yu, Yinxian; Niu, Kerun; Yi, Chengqin

    2017-08-01

    This study aimed to identify rheumatoid arthritis (RA) related genes based on microarray data using the WGCNA (weighted gene co-expression network analysis) method. Two gene expression profile datasets GSE55235 (10 RA samples and 10 healthy controls) and GSE77298 (16 RA samples and seven healthy controls) were downloaded from Gene Expression Omnibus database. Characteristic genes were identified using metaDE package. WGCNA was used to find disease-related networks based on gene expression correlation coefficients, and module significance was defined as the average gene significance of all genes used to assess the correlation between the module and RA status. Genes in the disease-related gene co-expression network were subject to functional annotation and pathway enrichment analysis using Database for Annotation Visualization and Integrated Discovery. Characteristic genes were also mapped to the Connectivity Map to screen small molecules. A total of 599 characteristic genes were identified. For each dataset, characteristic genes in the green, red and turquoise modules were most closely associated with RA, with gene numbers of 54, 43 and 79, respectively. These genes were enriched in totally enriched in 17 Gene Ontology terms, mainly related to immune response (CD97, FYB, CXCL1, IKBKE, CCR1, etc.), inflammatory response (CD97, CXCL1, C3AR1, CCR1, LYZ, etc.) and homeostasis (C3AR1, CCR1, PLN, CCL19, PPT1, etc.). Two small-molecule drugs sanguinarine and papaverine were predicted to have a therapeutic effect against RA. Genes related to immune response, inflammatory response and homeostasis presumably have critical roles in RA pathogenesis. Sanguinarine and papaverine have a potential therapeutic effect against RA. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

  4. Evaluation of Appropriate Reference Genes for Gene Expression Normalization during Watermelon Fruit Development.

    Directory of Open Access Journals (Sweden)

    Qiusheng Kong

    Full Text Available Gene expression analysis in watermelon (Citrullus lanatus fruit has drawn considerable attention with the availability of genome sequences to understand the regulatory mechanism of fruit development and to improve its quality. Real-time quantitative reverse-transcription PCR (qRT-PCR is a routine technique for gene expression analysis. However, appropriate reference genes for transcript normalization in watermelon fruits have not been well characterized. The aim of this study was to evaluate the appropriateness of 12 genes for their potential use as reference genes in watermelon fruits. Expression variations of these genes were measured in 48 samples obtained from 12 successive developmental stages of parthenocarpic and fertilized fruits of two watermelon genotypes by using qRT-PCR analysis. Considering the effects of genotype, fruit setting method, and developmental stage, geNorm determined clathrin adaptor complex subunit (ClCAC, β-actin (ClACT, and alpha tubulin 5 (ClTUA5 as the multiple reference genes in watermelon fruit. Furthermore, ClCAC alone or together with SAND family protein (ClSAND was ranked as the single or two best reference genes by NormFinder. By using the top-ranked reference genes to normalize the transcript abundance of phytoene synthase (ClPSY1, a good correlation between lycopene accumulation and ClPSY1 expression pattern was observed in ripening watermelon fruit. These validated reference genes will facilitate the accurate measurement of gene expression in the studies on watermelon fruit biology.

  5. Evaluation of Appropriate Reference Genes for Gene Expression Normalization during Watermelon Fruit Development.

    Science.gov (United States)

    Kong, Qiusheng; Yuan, Jingxian; Gao, Lingyun; Zhao, Liqiang; Cheng, Fei; Huang, Yuan; Bie, Zhilong

    2015-01-01

    Gene expression analysis in watermelon (Citrullus lanatus) fruit has drawn considerable attention with the availability of genome sequences to understand the regulatory mechanism of fruit development and to improve its quality. Real-time quantitative reverse-transcription PCR (qRT-PCR) is a routine technique for gene expression analysis. However, appropriate reference genes for transcript normalization in watermelon fruits have not been well characterized. The aim of this study was to evaluate the appropriateness of 12 genes for their potential use as reference genes in watermelon fruits. Expression variations of these genes were measured in 48 samples obtained from 12 successive developmental stages of parthenocarpic and fertilized fruits of two watermelon genotypes by using qRT-PCR analysis. Considering the effects of genotype, fruit setting method, and developmental stage, geNorm determined clathrin adaptor complex subunit (ClCAC), β-actin (ClACT), and alpha tubulin 5 (ClTUA5) as the multiple reference genes in watermelon fruit. Furthermore, ClCAC alone or together with SAND family protein (ClSAND) was ranked as the single or two best reference genes by NormFinder. By using the top-ranked reference genes to normalize the transcript abundance of phytoene synthase (ClPSY1), a good correlation between lycopene accumulation and ClPSY1 expression pattern was observed in ripening watermelon fruit. These validated reference genes will facilitate the accurate measurement of gene expression in the studies on watermelon fruit biology.

  6. Differential neutrophil gene expression in early bovine pregnancy

    Directory of Open Access Journals (Sweden)

    Kizaki Keiichiro

    2013-02-01

    Full Text Available Abstract Background In food production animals, especially cattle, the diagnosis of gestation is important because the timing of gestation directly affects the running of farms. Various methods have been used to detect gestation, but none of them are ideal because of problems with the timing of detection or the accuracy, simplicity, or cost of the method. A new method for detecting gestation, which involves assessing interferon-tau (IFNT-stimulated gene expression in peripheral blood leukocytes (PBL, was recently proposed. PBL fractionation methods were used to examine whether the expression profiles of various PBL populations could be used as reliable diagnostic markers of bovine gestation. Methods PBL were collected on days 0 (just before artificial insemination, 7, 14, 17, 21, and 28 of gestation. The gene expression levels of the PBL were assessed with microarray analysis and/or quantitative real-time reverse transcription (q PCR. PBL fractions were collected by flow cytometry or density gradient cell separation using Histopaque 1083 or Ficoll-Conray solutions. The expression levels of four IFNT-stimulated genes, interferon-stimulated protein 15 kDa (ISG15, myxovirus-resistance (MX 1 and 2, and 2′-5′-oligoadenylate synthetase (OAS1, were then analyzed in each fraction through day 28 of gestation using qPCR. Results Microarray analysis detected 72 and 28 genes in whole PBL that were significantly higher on days 14 and 21 of gestation, respectively, than on day 0. The upregulated genes included IFNT-stimulated genes. The expression levels of these genes increased with the progression of gestation until day 21. In flow cytometry experiments, on day 14 the expression levels of all of the genes were significantly higher in the granulocyte fraction than in the other fractions. Their expression gradually decreased through day 28 of gestation. Strong correlations were observed between the expression levels of the four genes in the granulocyte

  7. Genome-wide identification, characterisation and expression analysis of the MADS-box gene family in Prunus mume.

    Science.gov (United States)

    Xu, Zongda; Zhang, Qixiang; Sun, Lidan; Du, Dongliang; Cheng, Tangren; Pan, Huitang; Yang, Weiru; Wang, Jia

    2014-10-01

    MADS-box genes encode transcription factors that play crucial roles in plant development, especially in flower and fruit development. To gain insight into this gene family in Prunus mume, an important ornamental and fruit plant in East Asia, and to elucidate their roles in flower organ determination and fruit development, we performed a genome-wide identification, characterisation and expression analysis of MADS-box genes in this Rosaceae tree. In this study, 80 MADS-box genes were identified in P. mume and categorised into MIKC, Mα, Mβ, Mγ and Mδ groups based on gene structures and phylogenetic relationships. The MIKC group could be further classified into 12 subfamilies. The FLC subfamily was absent in P. mume and the six tandemly arranged DAM genes might experience a species-specific evolution process in P. mume. The MADS-box gene family might experience an evolution process from MIKC genes to Mδ genes to Mα, Mβ and Mγ genes. The expression analysis suggests that P. mume MADS-box genes have diverse functions in P. mume development and the functions of duplicated genes diverged after the duplication events. In addition to its involvement in the development of female gametophytes, type I genes also play roles in male gametophytes development. In conclusion, this study adds to our understanding of the roles that the MADS-box genes played in flower and fruit development and lays a foundation for selecting candidate genes for functional studies in P. mume and other species. Furthermore, this study also provides a basis to study the evolution of the MADS-box family.

  8. Validation of suitable reference genes for quantitative gene expression analysis in Panax ginseng

    Directory of Open Access Journals (Sweden)

    Meizhen eWang

    2016-01-01

    Full Text Available Reverse transcription-qPCR (RT-qPCR has become a popular method for gene expression studies. Its results require data normalization by housekeeping genes. No single gene is proved to be stably expressed under all experimental conditions. Therefore, systematic evaluation of reference genes is necessary. With the aim to identify optimum reference genes for RT-qPCR analysis of gene expression in different tissues of Panax ginseng and the seedlings grown under heat stress, we investigated the expression stability of eight candidate reference genes, including elongation factor 1-beta (EF1-β, elongation factor 1-gamma (EF1-γ, eukaryotic translation initiation factor 3G (IF3G, eukaryotic translation initiation factor 3B (IF3B, actin (ACT, actin11 (ACT11, glyceraldehyde-3-phosphate dehydrogenase (GAPDH and cyclophilin ABH-like protein (CYC, using four widely used computational programs: geNorm, Normfinder, BestKeeper, and the comparative ΔCt method. The results were then integrated using the web-based tool RefFinder. As a result, EF1-γ, IF3G and EF1-β were the three most stable genes in different tissues of P. ginseng, while IF3G, ACT11 and GAPDH were the top three-ranked genes in seedlings treated with heat. Using three better reference genes alone or in combination as internal control, we examined the expression profiles of MAR, a multiple function-associated mRNA-like non-coding RNA (mlncRNA in P. ginseng. Taken together, we recommended EF1-γ/IF3G and IF3G/ACT11 as the suitable pair of reference genes for RT-qPCR analysis of gene expression in different tissues of P. ginseng and the seedlings grown under heat stress, respectively. The results serve as a foundation for future studies on P. ginseng functional genomics.

  9. Expression of activation-induced cytidine deaminase gene in B lymphocytes of patients with common variable immunodeficiency.

    Science.gov (United States)

    Abolhassani, Hassan; Farrokhi, Amir Salek; Pourhamdi, Shabnam; Mohammadinejad, Payam; Sadeghi, Bamdad; Moazzeni, Seyed-Mohammad; Aghamohammadi, Asghar

    2013-08-01

    Common variable immunodeficiency (CVID) is a heterogeneous disorder characterized by reduced serum level of IgG, IgA or IgM and recurrent bacterial infections. Class switch recombination (CSR) as a critical process in immunoglobulin production is defective in a group of CVID patients. Activation-induced cytidine deaminase (AID) protein is an important molecule involving CSR process. The aim of this study was to investigate the AID gene mRNA production in a group of CVID patients indicating possible role of this molecule in this disorder. Peripheral blood mononuclear cells (PBMC) of 29 CVID patients and 21 healthy controls were isolated and stimulated by CD40L and IL-4 to induce AID gene expression. After 5 days AID gene mRNA production was investigated by real time polymerase chain reaction. AID gene was expressed in all of the studied patients. However the mean density of extracted AID mRNA showed higher level in CVID patients (230.95±103.04 ng/ml) rather than controls (210.00±44.72 ng/ml; P=0.5). CVID cases with lower level of AID had decreased total level of IgE (P=0.04) and stimulated IgE production (P=0.02); while cases with increased level of AID presented higher level of IgA (P=0.04) and numbers of B cells (P=0.02) and autoimmune disease (P=0.02). Different levels of AID gene expression may have important roles in dysregulation of immune system and final clinical presentation in CVID patients. Therefore investigating the expression of AID gene can help in classifying CVID patients.

  10. Improved Sleep in Military Personnel is Associated with Changes in the Expression of Inflammatory Genes and Improvement in Depression Symptoms

    Directory of Open Access Journals (Sweden)

    Whitney S. Livingston

    2015-04-01

    Full Text Available Study Objectives: Sleep disturbances are common in military personnel and are associated with increased risk for psychiatric morbidity, including posttraumatic stress disorder and depression, as well as inflammation. Improved sleep quality is linked to reductions in inflammatory bio-markers; however, the underlying mechanisms remain elusive. Methods: In this study we examine whole genome expression changes related to improved sleep in 68 military personnel diagnosed with insomnia. Subjects were classified into the following groups and then compared: improved sleep (n=46, or non-improved sleep (n=22 following three months of standard of care treatment for insomnia. Within subject differential expression was determined from microarray data using the Partek Genomics Suite analysis program and the interactive pathway analysis was used to determine key regulators of observed expression changes. Changes in symptoms of depression and posttraumatic stress disorder were also compared. Results: At baseline both groups were similar in demographics, clinical characteristics, and gene-expression profiles. The microarray data revealed that 217 coding genes were differentially expressed at the follow-up-period compared to baseline in the participants with improved sleep. Expression of inflammatory cytokines were reduced including IL-1β, IL-6, IL-8 and IL-13, with fold changes ranging from -3.19 to -2.1, and there were increases in the expression of inflammatory regulatory genes including toll-like receptors 1, 4, 7, and 8 in the improved sleep group. Interactive pathway analysis revealed 6 gene networks, including ubiquitin which was a major regulator in these gene-expression changes. The improved sleep group also had a significant reduction in the severity of depressive symptoms.Conclusions: Interventions that restore sleep likely reduce the expression of inflammatory genes, which relate to ubiquitin genes and relate to reductions in depressive symptoms.

  11. Identification of differentially expressed genes in flax (Linum usitatissimum L.) under saline-alkaline stress by digital gene expression.

    Science.gov (United States)

    Yu, Ying; Huang, Wengong; Chen, Hongyu; Wu, Guangwen; Yuan, Hongmei; Song, Xixia; Kang, Qinghua; Zhao, Dongsheng; Jiang, Weidong; Liu, Yan; Wu, Jianzhong; Cheng, Lili; Yao, Yubo; Guan, Fengzhi

    2014-10-01

    The salinization and alkalization of soil are widespread environmental problems, and alkaline salt stress is more destructive than neutral salt stress. Therefore, understanding the mechanism of plant tolerance to saline-alkaline stress has become a major challenge. However, little attention has been paid to the mechanism of plant alkaline salt tolerance. In this study, gene expression profiling of flax was analyzed under alkaline-salt stress (AS2), neutral salt stress (NSS) and alkaline stress (AS) by digital gene expression. Three-week-old flax seedlings were placed in 25 mM Na2CO3 (pH11.6) (AS2), 50mM NaCl (NSS) and NaOH (pH11.6) (AS) for 18 h. There were 7736, 1566 and 454 differentially expressed genes in AS2, NSS and AS compared to CK, respectively. The GO category gene enrichment analysis revealed that photosynthesis was particularly affected in AS2, carbohydrate metabolism was particularly affected in NSS, and the response to biotic stimulus was particularly affected in AS. We also analyzed the expression pattern of five categories of genes including transcription factors, signaling transduction proteins, phytohormones, reactive oxygen species proteins and transporters under these three stresses. Some key regulatory gene families involved in abiotic stress, such as WRKY, MAPKKK, ABA, PrxR and ion channels, were differentially expressed. Compared with NSS and AS, AS2 triggered more differentially expressed genes and special pathways, indicating that the mechanism of AS2 was more complex than NSS and AS. To the best of our knowledge, this was the first transcriptome analysis of flax in response to saline-alkaline stress. These data indicate that common and diverse features of saline-alkaline stress provide novel insights into the molecular mechanisms of plant saline-alkaline tolerance and offer a number of candidate genes as potential markers of tolerance to saline-alkaline stress. Copyright © 2014 Elsevier B.V. All rights reserved.

  12. Classification based upon gene expression data: bias and precision of error rates.

    Science.gov (United States)

    Wood, Ian A; Visscher, Peter M; Mengersen, Kerrie L

    2007-06-01

    Gene expression data offer a large number of potentially useful predictors for the classification of tissue samples into classes, such as diseased and non-diseased. The predictive error rate of classifiers can be estimated using methods such as cross-validation. We have investigated issues of interpretation and potential bias in the reporting of error rate estimates. The issues considered here are optimization and selection biases, sampling effects, measures of misclassification rate, baseline error rates, two-level external cross-validation and a novel proposal for detection of bias using the permutation mean. Reporting an optimal estimated error rate incurs an optimization bias. Downward bias of 3-5% was found in an existing study of classification based on gene expression data and may be endemic in similar studies. Using a simulated non-informative dataset and two example datasets from existing studies, we show how bias can be detected through the use of label permutations and avoided using two-level external cross-validation. Some studies avoid optimization bias by using single-level cross-validation and a test set, but error rates can be more accurately estimated via two-level cross-validation. In addition to estimating the simple overall error rate, we recommend reporting class error rates plus where possible the conditional risk incorporating prior class probabilities and a misclassification cost matrix. We also describe baseline error rates derived from three trivial classifiers which ignore the predictors. R code which implements two-level external cross-validation with the PAMR package, experiment code, dataset details and additional figures are freely available for non-commercial use from http://www.maths.qut.edu.au/profiles/wood/permr.jsp

  13. Improved gene expression signature of testicular carcinoma in situ

    DEFF Research Database (Denmark)

    Almstrup, Kristian; Leffers, Henrik; Lothe, Ragnhild A

    2007-01-01

    on global gene expression in testicular CIS have been previously published. We have merged the two data sets on CIS samples (n = 6) and identified the shared gene expression signature in relation to expression in normal testis. Among the top-20 highest expressed genes, one-third was transcription factors...... development' were significantly altered and could collectively affect cellular pathways like the WNT signalling cascade, which thus may be disrupted in testicular CIS. The merged CIS data from two different microarray platforms, to our knowledge, provide the most precise CIS gene expression signature to date....

  14. The gsdf gene locus harbors evolutionary conserved and clustered genes preferentially expressed in fish previtellogenic oocytes.

    Science.gov (United States)

    Gautier, Aude; Le Gac, Florence; Lareyre, Jean-Jacques

    2011-02-01

    The gonadal soma-derived factor (GSDF) belongs to the transforming growth factor-β superfamily and is conserved in teleostean fish species. Gsdf is specifically expressed in the gonads, and gene expression is restricted to the granulosa and Sertoli cells in trout and medaka. The gsdf gene expression is correlated to early testis differentiation in medaka and was shown to stimulate primordial germ cell and spermatogonia proliferation in trout. In the present study, we show that the gsdf gene localizes to a syntenic chromosomal fragment conserved among vertebrates although no gsdf-related gene is detected on the corresponding genomic region in tetrapods. We demonstrate using quantitative RT-PCR that most of the genes localized in the synteny are specifically expressed in medaka gonads. Gsdf is the only gene of the synteny with a much higher expression in the testis compared to the ovary. In contrast, gene expression pattern analysis of the gsdf surrounding genes (nup54, aff1, klhl8, sdad1, and ptpn13) indicates that these genes are preferentially expressed in the female gonads. The tissue distribution of these genes is highly similar in medaka and zebrafish, two teleostean species that have diverged more than 110 million years ago. The cellular localization of these genes was determined in medaka gonads using the whole-mount in situ hybridization technique. We confirm that gsdf gene expression is restricted to Sertoli and granulosa cells in contact with the premeiotic and meiotic cells. The nup54 gene is expressed in spermatocytes and previtellogenic oocytes. Transcripts corresponding to the ovary-specific genes (aff1, klhl8, and sdad1) are detected only in previtellogenic oocytes. No expression was detected in the gonocytes in 10 dpf embryos. In conclusion, we show that the gsdf gene localizes to a syntenic chromosomal fragment harboring evolutionary conserved genes in vertebrates. These genes are preferentially expressed in previtelloogenic oocytes, and thus, they

  15. Selection of reference genes for quantitative gene expression normalization in flax (Linum usitatissimum L.

    Directory of Open Access Journals (Sweden)

    Neutelings Godfrey

    2010-04-01

    Full Text Available Abstract Background Quantitative real-time PCR (qRT-PCR is currently the most accurate method for detecting differential gene expression. Such an approach depends on the identification of uniformly expressed 'housekeeping genes' (HKGs. Extensive transcriptomic data mining and experimental validation in different model plants have shown that the reliability of these endogenous controls can be influenced by the plant species, growth conditions and organs/tissues examined. It is therefore important to identify the best reference genes to use in each biological system before using qRT-PCR to investigate differential gene expression. In this paper we evaluate different candidate HKGs for developmental transcriptomic studies in the economically-important flax fiber- and oil-crop (Linum usitatissimum L. Results Specific primers were designed in order to quantify the expression levels of 20 different potential housekeeping genes in flax roots, internal- and external-stem tissues, leaves and flowers at different developmental stages. After calculations of PCR efficiencies, 13 HKGs were retained and their expression stabilities evaluated by the computer algorithms geNorm and NormFinder. According to geNorm, 2 Transcriptional Elongation Factors (TEFs and 1 Ubiquitin gene are necessary for normalizing gene expression when all studied samples are considered. However, only 2 TEFs are required for normalizing expression in stem tissues. In contrast, NormFinder identified glyceraldehyde-3-phosphate dehydrogenase (GADPH as the most stably expressed gene when all samples were grouped together, as well as when samples were classed into different sub-groups. qRT-PCR was then used to investigate the relative expression levels of two splice variants of the flax LuMYB1 gene (homologue of AtMYB59. LuMYB1-1 and LuMYB1-2 were highly expressed in the internal stem tissues as compared to outer stem tissues and other samples. This result was confirmed with both ge

  16. Selection of reference genes for quantitative gene expression normalization in flax (Linum usitatissimum L.).

    Science.gov (United States)

    Huis, Rudy; Hawkins, Simon; Neutelings, Godfrey

    2010-04-19

    Quantitative real-time PCR (qRT-PCR) is currently the most accurate method for detecting differential gene expression. Such an approach depends on the identification of uniformly expressed 'housekeeping genes' (HKGs). Extensive transcriptomic data mining and experimental validation in different model plants have shown that the reliability of these endogenous controls can be influenced by the plant species, growth conditions and organs/tissues examined. It is therefore important to identify the best reference genes to use in each biological system before using qRT-PCR to investigate differential gene expression. In this paper we evaluate different candidate HKGs for developmental transcriptomic studies in the economically-important flax fiber- and oil-crop (Linum usitatissimum L). Specific primers were designed in order to quantify the expression levels of 20 different potential housekeeping genes in flax roots, internal- and external-stem tissues, leaves and flowers at different developmental stages. After calculations of PCR efficiencies, 13 HKGs were retained and their expression stabilities evaluated by the computer algorithms geNorm and NormFinder. According to geNorm, 2 Transcriptional Elongation Factors (TEFs) and 1 Ubiquitin gene are necessary for normalizing gene expression when all studied samples are considered. However, only 2 TEFs are required for normalizing expression in stem tissues. In contrast, NormFinder identified glyceraldehyde-3-phosphate dehydrogenase (GADPH) as the most stably expressed gene when all samples were grouped together, as well as when samples were classed into different sub-groups.qRT-PCR was then used to investigate the relative expression levels of two splice variants of the flax LuMYB1 gene (homologue of AtMYB59). LuMYB1-1 and LuMYB1-2 were highly expressed in the internal stem tissues as compared to outer stem tissues and other samples. This result was confirmed with both geNorm-designated- and Norm

  17. The Medicago truncatula gene expression atlas web server

    Directory of Open Access Journals (Sweden)

    Tang Yuhong

    2009-12-01

    Full Text Available Abstract Background Legumes (Leguminosae or Fabaceae play a major role in agriculture. Transcriptomics studies in the model legume species, Medicago truncatula, are instrumental in helping to formulate hypotheses about the role of legume genes. With the rapid growth of publically available Affymetrix GeneChip Medicago Genome Array GeneChip data from a great range of tissues, cell types, growth conditions, and stress treatments, the legume research community desires an effective bioinformatics system to aid efforts to interpret the Medicago genome through functional genomics. We developed the Medicago truncatula Gene Expression Atlas (MtGEA web server for this purpose. Description The Medicago truncatula Gene Expression Atlas (MtGEA web server is a centralized platform for analyzing the Medicago transcriptome. Currently, the web server hosts gene expression data from 156 Affymetrix GeneChip® Medicago genome arrays in 64 different experiments, covering a broad range of developmental and environmental conditions. The server enables flexible, multifaceted analyses of transcript data and provides a range of additional information about genes, including different types of annotation and links to the genome sequence, which help users formulate hypotheses about gene function. Transcript data can be accessed using Affymetrix probe identification number, DNA sequence, gene name, functional description in natural language, GO and KEGG annotation terms, and InterPro domain number. Transcripts can also be discovered through co-expression or differential expression analysis. Flexible tools to select a subset of experiments and to visualize and compare expression profiles of multiple genes have been implemented. Data can be downloaded, in part or full, in a tabular form compatible with common analytical and visualization software. The web server will be updated on a regular basis to incorporate new gene expression data and genome annotation, and is accessible

  18. A gene co-expression network in whole blood of schizophrenia patients is independent of antipsychotic-use and enriched for brain-expressed genes.

    Directory of Open Access Journals (Sweden)

    Simone de Jong

    Full Text Available Despite large-scale genome-wide association studies (GWAS, the underlying genes for schizophrenia are largely unknown. Additional approaches are therefore required to identify the genetic background of this disorder. Here we report findings from a large gene expression study in peripheral blood of schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co-expression modules associated with schizophrenia. Several of these disease related modules are likely to reflect expression changes due to antipsychotic medication. However, two of the disease modules could be replicated in an independent second data set involving antipsychotic-free patients and controls. One of these robustly defined disease modules is significantly enriched with brain-expressed genes and with genetic variants that were implicated in a GWAS study, which could imply a causal role in schizophrenia etiology. The most highly connected intramodular hub gene in this module (ABCF1, is located in, and regulated by the major histocompatibility (MHC complex, which is intriguing in light of the fact that common allelic variants from the MHC region have been implicated in schizophrenia. This suggests that the MHC increases schizophrenia susceptibility via altered gene expression of regulatory genes in this network.

  19. Gene Expression Profiling Soybean Stem Tissue Early Response to Sclerotinia sclerotiorum and In Silico Mapping in Relation to Resistance Markers

    Directory of Open Access Journals (Sweden)

    Bernarda Calla

    2009-07-01

    Full Text Available White mold, caused by (Lib. de Bary, can be a serious disease of crops grown under cool, moist environments. In many plants, such as soybean [ (L. Merr.], complete genetic resistance does not exist. To identify possible genes involved in defense against this pathogen, and to determine possible physiological changes that occur during infection, a microarray screen was conducted using stem tissue to evaluate changes in gene expression between partially resistant and susceptible soybean genotypes at 8 and 14 hours post inoculation. RNA from 15 day-old inoculated plants was labeled and hybridized to soybean cDNA microarrays. ANOVA identified 1270 significant genes from the comparison between time points and 105 genes from the comparison between genotypes. Selected genes were classified into functional categories. The analyses identified changes in cell-wall composition and signaling pathways, as well as suggesting a role for anthocyanin and anthocyanidin synthesis in the defense against . In-silico mapping of both the differentially expressed transcripts and of public markers associated with partial resistance to white mold, provided evidence of several differentially expressed genes being closely positioned to white mold resistance markers, with the two most promising genes encoding a PR-5 and anthocyanidin synthase.

  20. Combining multiple hypothesis testing and affinity propagation clustering leads to accurate, robust and sample size independent classification on gene expression data

    Directory of Open Access Journals (Sweden)

    Sakellariou Argiris

    2012-10-01

    Full Text Available Abstract Background A feature selection method in microarray gene expression data should be independent of platform, disease and dataset size. Our hypothesis is that among the statistically significant ranked genes in a gene list, there should be clusters of genes that share similar biological functions related to the investigated disease. Thus, instead of keeping N top ranked genes, it would be more appropriate to define and keep a number of gene cluster exemplars. Results We propose a hybrid FS method (mAP-KL, which combines multiple hypothesis testing and affinity propagation (AP-clustering algorithm along with the Krzanowski & Lai cluster quality index, to select a small yet informative subset of genes. We applied mAP-KL on real microarray data, as well as on simulated data, and compared its performance against 13 other feature selection approaches. Across a variety of diseases and number of samples, mAP-KL presents competitive classification results, particularly in neuromuscular diseases, where its overall AUC score was 0.91. Furthermore, mAP-KL generates concise yet biologically relevant and informative N-gene expression signatures, which can serve as a valuable tool for diagnostic and prognostic purposes, as well as a source of potential disease biomarkers in a broad range of diseases. Conclusions mAP-KL is a data-driven and classifier-independent hybrid feature selection method, which applies to any disease classification problem based on microarray data, regardless of the available samples. Combining multiple hypothesis testing and AP leads to subsets of genes, which classify unknown samples from both, small and large patient cohorts with high accuracy.

  1. A deep auto-encoder model for gene expression prediction.

    Science.gov (United States)

    Xie, Rui; Wen, Jia; Quitadamo, Andrew; Cheng, Jianlin; Shi, Xinghua

    2017-11-17

    Gene expression is a key intermediate level that genotypes lead to a particular trait. Gene expression is affected by various factors including genotypes of genetic variants. With an aim of delineating the genetic impact on gene expression, we build a deep auto-encoder model to assess how good genetic variants will contribute to gene expression changes. This new deep learning model is a regression-based predictive model based on the MultiLayer Perceptron and Stacked Denoising Auto-encoder (MLP-SAE). The model is trained using a stacked denoising auto-encoder for feature selection and a multilayer perceptron framework for backpropagation. We further improve the model by introducing dropout to prevent overfitting and improve performance. To demonstrate the usage of this model, we apply MLP-SAE to a real genomic datasets with genotypes and gene expression profiles measured in yeast. Our results show that the MLP-SAE model with dropout outperforms other models including Lasso, Random Forests and the MLP-SAE model without dropout. Using the MLP-SAE model with dropout, we show that gene expression quantifications predicted by the model solely based on genotypes, align well with true gene expression patterns. We provide a deep auto-encoder model for predicting gene expression from SNP genotypes. This study demonstrates that deep learning is appropriate for tackling another genomic problem, i.e., building predictive models to understand genotypes' contribution to gene expression. With the emerging availability of richer genomic data, we anticipate that deep learning models play a bigger role in modeling and interpreting genomics.

  2. Positron emission tomography imaging of gene expression

    International Nuclear Information System (INIS)

    Tang Ganghua

    2001-01-01

    The merging of molecular biology and nuclear medicine is developed into molecular nuclear medicine. Positron emission tomography (PET) of gene expression in molecular nuclear medicine has become an attractive area. Positron emission tomography imaging gene expression includes the antisense PET imaging and the reporter gene PET imaging. It is likely that the antisense PET imaging will lag behind the reporter gene PET imaging because of the numerous issues that have not yet to be resolved with this approach. The reporter gene PET imaging has wide application into animal experimental research and human applications of this approach will likely be reported soon

  3. Understanding gene expression in coronary artery disease through ...

    Indian Academy of Sciences (India)

    Understanding gene expression in coronary artery disease through global profiling, network analysis and independent validation of key candidate genes. Prathima ... Table 2. Differentially expressed genes in CAD compared to age and gender matched controls. .... Regulation of nuclear pre-mRNA domain containing 1A.

  4. Gene expression profile of pulpitis.

    Science.gov (United States)

    Galicia, J C; Henson, B R; Parker, J S; Khan, A A

    2016-06-01

    The cost, prevalence and pain associated with endodontic disease necessitate an understanding of the fundamental molecular aspects of its pathogenesis. This study was aimed to identify the genetic contributors to pulpal pain and inflammation. Inflamed pulps were collected from patients diagnosed with irreversible pulpitis (n=20). Normal pulps from teeth extracted for various reasons served as controls (n=20). Pain level was assessed using a visual analog scale (VAS). Genome-wide microarray analysis was performed using Affymetrix GeneTitan Multichannel Instrument. The difference in gene expression levels were determined by the significance analysis of microarray program using a false discovery rate (q-value) of 5%. Genes involved in immune response, cytokine-cytokine receptor interaction and signaling, integrin cell surface interactions, and others were expressed at relatively higher levels in the pulpitis group. Moreover, several genes known to modulate pain and inflammation showed differential expression in asymptomatic and mild pain patients (⩾30 mm on VAS) compared with those with moderate to severe pain. This exploratory study provides a molecular basis for the clinical diagnosis of pulpitis. With an enhanced understanding of pulpal inflammation, future studies on treatment and management of pulpitis and on pain associated with it can have a biological reference to bridge treatment strategies with pulpal biology.

  5. Mel-18, a mammalian Polycomb gene, regulates angiogenic gene expression of endothelial cells.

    Science.gov (United States)

    Jung, Ji-Hye; Choi, Hyun-Jung; Maeng, Yong-Sun; Choi, Jung-Yeon; Kim, Minhyung; Kwon, Ja-Young; Park, Yong-Won; Kim, Young-Myeong; Hwang, Daehee; Kwon, Young-Guen

    2010-10-01

    Mel-18 is a mammalian homolog of Polycomb group (PcG) genes. Microarray analysis revealed that Mel-18 expression was induced during endothelial progenitor cell (EPC) differentiation and correlates with the expression of EC-specific protein markers. Overexpression of Mel-18 promoted EPC differentiation and angiogenic activity of ECs. Accordingly, silencing Mel-18 inhibited EC migration and tube formation in vitro. Gene expression profiling showed that Mel-18 regulates angiogenic genes including kinase insert domain receptor (KDR), claudin 5, and angiopoietin-like 2. Our findings demonstrate, for the first time, that Mel-18 plays a significant role in the angiogenic function of ECs by regulating endothelial gene expression. Copyright © 2010 Elsevier Inc. All rights reserved.

  6. Gene Expression Omnibus (GEO)

    Data.gov (United States)

    U.S. Department of Health & Human Services — Gene Expression Omnibus is a public functional genomics data repository supporting MIAME-compliant submissions of array- and sequence-based data. Tools are provided...

  7. Identification and validation of suitable endogenous reference genes for gene expression studies in human peripheral blood

    Directory of Open Access Journals (Sweden)

    Turner Renee J

    2009-08-01

    Full Text Available Abstract Background Gene expression studies require appropriate normalization methods. One such method uses stably expressed reference genes. Since suitable reference genes appear to be unique for each tissue, we have identified an optimal set of the most stably expressed genes in human blood that can be used for normalization. Methods Whole-genome Affymetrix Human 2.0 Plus arrays were examined from 526 samples of males and females ages 2 to 78, including control subjects and patients with Tourette syndrome, stroke, migraine, muscular dystrophy, and autism. The top 100 most stably expressed genes with a broad range of expression levels were identified. To validate the best candidate genes, we performed quantitative RT-PCR on a subset of 10 genes (TRAP1, DECR1, FPGS, FARP1, MAPRE2, PEX16, GINS2, CRY2, CSNK1G2 and A4GALT, 4 commonly employed reference genes (GAPDH, ACTB, B2M and HMBS and PPIB, previously reported to be stably expressed in blood. Expression stability and ranking analysis were performed using GeNorm and NormFinder algorithms. Results Reference genes were ranked based on their expression stability and the minimum number of genes needed for nomalization as calculated using GeNorm showed that the fewest, most stably expressed genes needed for acurate normalization in RNA expression studies of human whole blood is a combination of TRAP1, FPGS, DECR1 and PPIB. We confirmed the ranking of the best candidate control genes by using an alternative algorithm (NormFinder. Conclusion The reference genes identified in this study are stably expressed in whole blood of humans of both genders with multiple disease conditions and ages 2 to 78. Importantly, they also have different functions within cells and thus should be expressed independently of each other. These genes should be useful as normalization genes for microarray and RT-PCR whole blood studies of human physiology, metabolism and disease.

  8. Validation of reference genes for quantifying changes in gene expression in virus-infected tobacco.

    Science.gov (United States)

    Baek, Eseul; Yoon, Ju-Yeon; Palukaitis, Peter

    2017-10-01

    To facilitate quantification of gene expression changes in virus-infected tobacco plants, eight housekeeping genes were evaluated for their stability of expression during infection by one of three systemically-infecting viruses (cucumber mosaic virus, potato virus X, potato virus Y) or a hypersensitive-response-inducing virus (tobacco mosaic virus; TMV) limited to the inoculated leaf. Five reference-gene validation programs were used to establish the order of the most stable genes for the systemically-infecting viruses as ribosomal protein L25 > β-Tubulin > Actin, and the least stable genes Ubiquitin-conjugating enzyme (UCE) genes were EF1α > Cysteine protease > Actin, and the least stable genes were GAPDH genes, three defense responsive genes were examined to compare their relative changes in gene expression caused by each virus. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. Analyzing kernel matrices for the identification of differentially expressed genes.

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    Xiao-Lei Xia

    Full Text Available One of the most important applications of microarray data is the class prediction of biological samples. For this purpose, statistical tests have often been applied to identify the differentially expressed genes (DEGs, followed by the employment of the state-of-the-art learning machines including the Support Vector Machines (SVM in particular. The SVM is a typical sample-based classifier whose performance comes down to how discriminant samples are. However, DEGs identified by statistical tests are not guaranteed to result in a training dataset composed of discriminant samples. To tackle this problem, a novel gene ranking method namely the Kernel Matrix Gene Selection (KMGS is proposed. The rationale of the method, which roots in the fundamental ideas of the SVM algorithm, is described. The notion of ''the separability of a sample'' which is estimated by performing [Formula: see text]-like statistics on each column of the kernel matrix, is first introduced. The separability of a classification problem is then measured, from which the significance of a specific gene is deduced. Also described is a method of Kernel Matrix Sequential Forward Selection (KMSFS which shares the KMGS method's essential ideas but proceeds in a greedy manner. On three public microarray datasets, our proposed algorithms achieved noticeably competitive performance in terms of the B.632+ error rate.

  10. Gene expression patterns in pancreatic tumors, cells and tissues.

    Directory of Open Access Journals (Sweden)

    Anson W Lowe

    2007-03-01

    Full Text Available Cancers of the pancreas originate from both the endocrine and exocrine elements of the organ, and represent a major cause of cancer-related death. This study provides a comprehensive assessment of gene expression for pancreatic tumors, the normal pancreas, and nonneoplastic pancreatic disease.DNA microarrays were used to assess the gene expression for surgically derived pancreatic adenocarcinomas, islet cell tumors, and mesenchymal tumors. The addition of normal pancreata, isolated islets, isolated pancreatic ducts, and pancreatic adenocarcinoma cell lines enhanced subsequent analysis by increasing the diversity in gene expression profiles obtained. Exocrine, endocrine, and mesenchymal tumors displayed unique gene expression profiles. Similarities in gene expression support the pancreatic duct as the origin of adenocarcinomas. In addition, genes highly expressed in other cancers and associated with specific signal transduction pathways were also found in pancreatic tumors.The scope of the present work was enhanced by the inclusion of publicly available datasets that encompass a wide spectrum of human tissues and enabled the identification of candidate genes that may serve diagnostic and therapeutic goals.

  11. A longitudinal study of gene expression in healthy individuals

    Directory of Open Access Journals (Sweden)

    Tessier Michel

    2009-06-01

    Full Text Available Abstract Background The use of gene expression in venous blood either as a pharmacodynamic marker in clinical trials of drugs or as a diagnostic test requires knowledge of the variability in expression over time in healthy volunteers. Here we defined a normal range of gene expression over 6 months in the blood of four cohorts of healthy men and women who were stratified by age (22–55 years and > 55 years and gender. Methods Eleven immunomodulatory genes likely to play important roles in inflammatory conditions such as rheumatoid arthritis and infection in addition to four genes typically used as reference genes were examined by quantitative reverse transcription-polymerase chain reaction (qRT-PCR, as well as the full genome as represented by Affymetrix HG U133 Plus 2.0 microarrays. Results Gene expression levels as assessed by qRT-PCR and microarray were relatively stable over time with ~2% of genes as measured by microarray showing intra-subject differences over time periods longer than one month. Fifteen genes varied by gender. The eleven genes examined by qRT-PCR remained within a limited dynamic range for all individuals. Specifically, for the seven most stably expressed genes (CXCL1, HMOX1, IL1RN, IL1B, IL6R, PTGS2, and TNF, 95% of all samples profiled fell within 1.5–2.5 Ct, the equivalent of a 4- to 6-fold dynamic range. Two subjects who experienced severe adverse events of cancer and anemia, had microarray gene expression profiles that were distinct from normal while subjects who experienced an infection had only slightly elevated levels of inflammatory markers. Conclusion This study defines the range and variability of gene expression in healthy men and women over a six-month period. These parameters can be used to estimate the number of subjects needed to observe significant differences from normal gene expression in clinical studies. A set of genes that varied by gender was also identified as were a set of genes with elevated

  12. Vaginal Gene Expression During Treatment With Aromatase Inhibitors.

    Science.gov (United States)

    Kallak, Theodora Kunovac; Baumgart, Juliane; Nilsson, Kerstin; Åkerud, Helena; Poromaa, Inger Sundström; Stavreus-Evers, Anneli

    2015-12-01

    Aromatase inhibitor (AI) treatment suppresses estrogen biosynthesis and causes genitourinary symptoms of menopause such as vaginal symptoms, ultimately affecting the quality of life for many postmenopausal women with breast cancer. Thus, the aim of this study was to examine vaginal gene expression in women during treatment with AIs compared with estrogen-treated women. The secondary aim was to study the presence and localization of vaginal aromatase. Vaginal biopsies were collected from postmenopausal women treated with AIs and from age-matched control women treated with vaginal estrogen therapy. Differential gene expression was studied with the Affymetrix Gene Chip Gene 1.0 ST Array (Affymetrix Inc, Santa Clara, CA) system, Ingenuity pathway analysis, quantitative real-time polymerase chain reaction, and immunohistochemistry. The expression of 279 genes differed between the 2 groups; AI-treated women had low expression of genes involved in cell differentiation, proliferation, and cell adhesion. Some differentially expressed genes were found to interact indirectly with the estrogen receptor alpha. In addition, aromatase protein staining was evident in the basal and the intermediate vaginal epithelium layers, and also in stromal cells with a slightly stronger staining intensity found in AI-treated women. In this study, we demonstrated that genes involved in cell differentiation, proliferation, and cell adhesion are differentially expressed in AI-treated women. The expression of vaginal aromatase suggests that this could be the result of local and systemic inhibition of aromatase. Our results emphasize the role of estrogen for vaginal cell differentiation and proliferation and future drug candidates should be aimed at improving cell differentiation and proliferation. Copyright © 2015 Elsevier Inc. All rights reserved.

  13. AffyMiner: mining differentially expressed genes and biological knowledge in GeneChip microarray data

    Directory of Open Access Journals (Sweden)

    Xia Yuannan

    2006-12-01

    Full Text Available Abstract Background DNA microarrays are a powerful tool for monitoring the expression of tens of thousands of genes simultaneously. With the advance of microarray technology, the challenge issue becomes how to analyze a large amount of microarray data and make biological sense of them. Affymetrix GeneChips are widely used microarrays, where a variety of statistical algorithms have been explored and used for detecting significant genes in the experiment. These methods rely solely on the quantitative data, i.e., signal intensity; however, qualitative data are also important parameters in detecting differentially expressed genes. Results AffyMiner is a tool developed for detecting differentially expressed genes in Affymetrix GeneChip microarray data and for associating gene annotation and gene ontology information with the genes detected. AffyMiner consists of the functional modules, GeneFinder for detecting significant genes in a treatment versus control experiment and GOTree for mapping genes of interest onto the Gene Ontology (GO space; and interfaces to run Cluster, a program for clustering analysis, and GenMAPP, a program for pathway analysis. AffyMiner has been used for analyzing the GeneChip data and the results were presented in several publications. Conclusion AffyMiner fills an important gap in finding differentially expressed genes in Affymetrix GeneChip microarray data. AffyMiner effectively deals with multiple replicates in the experiment and takes into account both quantitative and qualitative data in identifying significant genes. AffyMiner reduces the time and effort needed to compare data from multiple arrays and to interpret the possible biological implications associated with significant changes in a gene's expression.

  14. Regulation of Gene Expression in Protozoa Parasites

    Directory of Open Access Journals (Sweden)

    Consuelo Gomez

    2010-01-01

    Full Text Available Infections with protozoa parasites are associated with high burdens of morbidity and mortality across the developing world. Despite extensive efforts to control the transmission of these parasites, the spread of populations resistant to drugs and the lack of effective vaccines against them contribute to their persistence as major public health problems. Parasites should perform a strict control on the expression of genes involved in their pathogenicity, differentiation, immune evasion, or drug resistance, and the comprehension of the mechanisms implicated in that control could help to develop novel therapeutic strategies. However, until now these mechanisms are poorly understood in protozoa. Recent investigations into gene expression in protozoa parasites suggest that they possess many of the canonical machineries employed by higher eukaryotes for the control of gene expression at transcriptional, posttranscriptional, and epigenetic levels, but they also contain exclusive mechanisms. Here, we review the current understanding about the regulation of gene expression in Plasmodium sp., Trypanosomatids, Entamoeba histolytica and Trichomonas vaginalis.

  15. Regulation of gene expression in protozoa parasites.

    Science.gov (United States)

    Gomez, Consuelo; Esther Ramirez, M; Calixto-Galvez, Mercedes; Medel, Olivia; Rodríguez, Mario A

    2010-01-01

    Infections with protozoa parasites are associated with high burdens of morbidity and mortality across the developing world. Despite extensive efforts to control the transmission of these parasites, the spread of populations resistant to drugs and the lack of effective vaccines against them contribute to their persistence as major public health problems. Parasites should perform a strict control on the expression of genes involved in their pathogenicity, differentiation, immune evasion, or drug resistance, and the comprehension of the mechanisms implicated in that control could help to develop novel therapeutic strategies. However, until now these mechanisms are poorly understood in protozoa. Recent investigations into gene expression in protozoa parasites suggest that they possess many of the canonical machineries employed by higher eukaryotes for the control of gene expression at transcriptional, posttranscriptional, and epigenetic levels, but they also contain exclusive mechanisms. Here, we review the current understanding about the regulation of gene expression in Plasmodium sp., Trypanosomatids, Entamoeba histolytica and Trichomonas vaginalis.

  16. A gene co-expression network in whole blood of schizophrenia patients is independent of antipsychotic-use and enriched for brain-expressed genes

    DEFF Research Database (Denmark)

    de Jong, Simone; Boks, Marco P M; Fuller, Tova F

    2012-01-01

    Despite large-scale genome-wide association studies (GWAS), the underlying genes for schizophrenia are largely unknown. Additional approaches are therefore required to identify the genetic background of this disorder. Here we report findings from a large gene expression study in peripheral blood...... of schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co......, and regulated by the major histocompatibility (MHC) complex, which is intriguing in light of the fact that common allelic variants from the MHC region have been implicated in schizophrenia. This suggests that the MHC increases schizophrenia susceptibility via altered gene expression of regulatory genes...

  17. Divergent and nonuniform gene expression patterns in mouse brain

    Science.gov (United States)

    Morris, John A.; Royall, Joshua J.; Bertagnolli, Darren; Boe, Andrew F.; Burnell, Josh J.; Byrnes, Emi J.; Copeland, Cathy; Desta, Tsega; Fischer, Shanna R.; Goldy, Jeff; Glattfelder, Katie J.; Kidney, Jolene M.; Lemon, Tracy; Orta, Geralyn J.; Parry, Sheana E.; Pathak, Sayan D.; Pearson, Owen C.; Reding, Melissa; Shapouri, Sheila; Smith, Kimberly A.; Soden, Chad; Solan, Beth M.; Weller, John; Takahashi, Joseph S.; Overly, Caroline C.; Lein, Ed S.; Hawrylycz, Michael J.; Hohmann, John G.; Jones, Allan R.

    2010-01-01

    Considerable progress has been made in understanding variations in gene sequence and expression level associated with phenotype, yet how genetic diversity translates into complex phenotypic differences remains poorly understood. Here, we examine the relationship between genetic background and spatial patterns of gene expression across seven strains of mice, providing the most extensive cellular-resolution comparative analysis of gene expression in the mammalian brain to date. Using comprehensive brainwide anatomic coverage (more than 200 brain regions), we applied in situ hybridization to analyze the spatial expression patterns of 49 genes encoding well-known pharmaceutical drug targets. Remarkably, over 50% of the genes examined showed interstrain expression variation. In addition, the variability was nonuniformly distributed across strain and neuroanatomic region, suggesting certain organizing principles. First, the degree of expression variance among strains mirrors genealogic relationships. Second, expression pattern differences were concentrated in higher-order brain regions such as the cortex and hippocampus. Divergence in gene expression patterns across the brain could contribute significantly to variations in behavior and responses to neuroactive drugs in laboratory mouse strains and may help to explain individual differences in human responsiveness to neuroactive drugs. PMID:20956311

  18. Rethinking cell-cycle-dependent gene expression in Schizosaccharomyces pombe.

    Science.gov (United States)

    Cooper, Stephen

    2017-11-01

    Three studies of gene expression during the division cycle of Schizosaccharomyces pombe led to the proposal that a large number of genes are expressed at particular times during the S. pombe cell cycle. Yet only a small fraction of genes proposed to be expressed in a cell-cycle-dependent manner are reproducible in all three published studies. In addition to reproducibility problems, questions about expression amplitudes, cell-cycle timing of expression, synchronization artifacts, and the problem with methods for synchronizing cells must be considered. These problems and complications prompt the idea that caution should be used before accepting the conclusion that there are a large number of genes expressed in a cell-cycle-dependent manner in S. pombe.

  19. Variation-preserving normalization unveils blind spots in gene expression profiling

    Science.gov (United States)

    Roca, Carlos P.; Gomes, Susana I. L.; Amorim, Mónica J. B.; Scott-Fordsmand, Janeck J.

    2017-01-01

    RNA-Seq and gene expression microarrays provide comprehensive profiles of gene activity, but lack of reproducibility has hindered their application. A key challenge in the data analysis is the normalization of gene expression levels, which is currently performed following the implicit assumption that most genes are not differentially expressed. Here, we present a mathematical approach to normalization that makes no assumption of this sort. We have found that variation in gene expression is much larger than currently believed, and that it can be measured with available assays. Our results also explain, at least partially, the reproducibility problems encountered in transcriptomics studies. We expect that this improvement in detection will help efforts to realize the full potential of gene expression profiling, especially in analyses of cellular processes involving complex modulations of gene expression. PMID:28276435

  20. G-NEST: a gene neighborhood scoring tool to identify co-conserved, co-expressed genes

    Directory of Open Access Journals (Sweden)

    Lemay Danielle G

    2012-09-01

    Full Text Available Abstract Background In previous studies, gene neighborhoods—spatial clusters of co-expressed genes in the genome—have been defined using arbitrary rules such as requiring adjacency, a minimum number of genes, a fixed window size, or a minimum expression level. In the current study, we developed a Gene Neighborhood Scoring Tool (G-NEST which combines genomic location, gene expression, and evolutionary sequence conservation data to score putative gene neighborhoods across all possible window sizes simultaneously. Results Using G-NEST on atlases of mouse and human tissue expression data, we found that large neighborhoods of ten or more genes are extremely rare in mammalian genomes. When they do occur, neighborhoods are typically composed of families of related genes. Both the highest scoring and the largest neighborhoods in mammalian genomes are formed by tandem gene duplication. Mammalian gene neighborhoods contain highly and variably expressed genes. Co-localized noisy gene pairs exhibit lower evolutionary conservation of their adjacent genome locations, suggesting that their shared transcriptional background may be disadvantageous. Genes that are essential to mammalian survival and reproduction are less likely to occur in neighborhoods, although neighborhoods are enriched with genes that function in mitosis. We also found that gene orientation and protein-protein interactions are partially responsible for maintenance of gene neighborhoods. Conclusions Our experiments using G-NEST confirm that tandem gene duplication is the primary driver of non-random gene order in mammalian genomes. Non-essentiality, co-functionality, gene orientation, and protein-protein interactions are additional forces that maintain gene neighborhoods, especially those formed by tandem duplicates. We expect G-NEST to be useful for other applications such as the identification of core regulatory modules, common transcriptional backgrounds, and chromatin domains. The

  1. Weighted gene co-expression network analysis of expression data of monozygotic twins identifies specific modules and hub genes related to BMI.

    Science.gov (United States)

    Wang, Weijing; Jiang, Wenjie; Hou, Lin; Duan, Haiping; Wu, Yili; Xu, Chunsheng; Tan, Qihua; Li, Shuxia; Zhang, Dongfeng

    2017-11-13

    The therapeutic management of obesity is challenging, hence further elucidating the underlying mechanisms of obesity development and identifying new diagnostic biomarkers and therapeutic targets are urgent and necessary. Here, we performed differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) to identify significant genes and specific modules related to BMI based on gene expression profile data of 7 discordant monozygotic twins. In the differential gene expression analysis, it appeared that 32 differentially expressed genes (DEGs) were with a trend of up-regulation in twins with higher BMI when compared to their siblings. Categories of positive regulation of nitric-oxide synthase biosynthetic process, positive regulation of NF-kappa B import into nucleus, and peroxidase activity were significantly enriched within GO database and NF-kappa B signaling pathway within KEGG database. DEGs of NAMPT, TLR9, PTGS2, HBD, and PCSK1N might be associated with obesity. In the WGCNA, among the total 20 distinct co-expression modules identified, coral1 module (68 genes) had the strongest positive correlation with BMI (r = 0.56, P = 0.04) and disease status (r = 0.56, P = 0.04). Categories of positive regulation of phospholipase activity, high-density lipoprotein particle clearance, chylomicron remnant clearance, reverse cholesterol transport, intermediate-density lipoprotein particle, chylomicron, low-density lipoprotein particle, very-low-density lipoprotein particle, voltage-gated potassium channel complex, cholesterol transporter activity, and neuropeptide hormone activity were significantly enriched within GO database for this module. And alcoholism and cell adhesion molecules pathways were significantly enriched within KEGG database. Several hub genes, such as GAL, ASB9, NPPB, TBX2, IL17C, APOE, ABCG4, and APOC2 were also identified. The module eigengene of saddlebrown module (212 genes) was also significantly

  2. G-NEST: A gene neighborhood scoring tool to identify co-conserved, co-expressed genes

    Science.gov (United States)

    In previous studies, gene neighborhoods--spatial clusters of co-expressed genes in the genome--have been defined using arbitrary rules such as requiring adjacency, a minimum number of genes, a fixed window size, or a minimum expression level. In the current study, we developed a Gene Neighborhood Sc...

  3. Selection for the compactness of highly expressed genes in Gallus gallus

    Directory of Open Access Journals (Sweden)

    Zhou Ming

    2010-05-01

    Full Text Available Abstract Background Coding sequence (CDS length, gene size, and intron length vary within a genome and among genomes. Previous studies in diverse organisms, including human, D. Melanogaster, C. elegans, S. cerevisiae, and Arabidopsis thaliana, indicated that there are negative relationships between expression level and gene size, CDS length as well as intron length. Different models such as selection for economy model, genomic design model, and mutational bias hypotheses have been proposed to explain such observation. The debate of which model is a superior one to explain the observation has not been settled down. The chicken (Gallus gallus is an important model organism that bridges the evolutionary gap between mammals and other vertebrates. As D. Melanogaster, chicken has a larger effective population size, selection for chicken genome is expected to be more effective in increasing protein synthesis efficiency. Therefore, in this study the chicken was used as a model organism to elucidate the interaction between gene features and expression pattern upon selection pressure. Results Based on different technologies, we gathered expression data for nuclear protein coding, single-splicing genes from Gallus gallus genome and compared them with gene parameters. We found that gene size, CDS length, first intron length, average intron length, and total intron length are negatively correlated with expression level and expression breadth significantly. The tissue specificity is positively correlated with the first intron length but negatively correlated with the average intron length, and not correlated with the CDS length and protein domain numbers. Comparison analyses showed that ubiquitously expressed genes and narrowly expressed genes with the similar expression levels do not differ in compactness. Our data provided evidence that the genomic design model can not, at least in part, explain our observations. We grouped all somatic-tissue-specific genes

  4. Differential gene expression profile of the calanoid copepod, Pseudodiaptomus annandalei, in response to nickel exposure.

    Science.gov (United States)

    Jiang, Jie-Lan; Wang, Gui-Zhong; Mao, Ming-Guang; Wang, Ke-Jian; Li, Shao-Jing; Zeng, Chao-Shu

    2013-03-01

    To better understand the underlying mechanisms of reactions of copepods exposed to elevated level of nickel, the suppression subtractive hybridization (SSH) was used to elucidate the response of the copepod Pseudodiaptomus annandalei to nickel exposure at the gene level. P. annandale is one of a few copepod species that can be cultured relatively easy under laboratory condition, and it is considered to be a potential model species for toxicity study. In the present study, P. annandalei were exposed to nickel at a concentration of 8.86 mgL(-1) for 24h, after which the RNA was prepared for SSH using unexposed P. annandalei as drivers. A total of 474 clones on the middle scale in the SSH library were sequenced. Among these genes, 129 potential functional genes were recognized based on the BLAST searches in NCBI and Uniprot databases. These genes were then categorized into nine groups in association with different biological processes using AmiGO against the Gene Ontology database. Of the 129 genes, 127 translatable DNA sequences were predicted to be proteins, and the putative amino acid sequences were searched for conserved domains (CD) and proteins using the CD-Search service and BLASTp. Among 129 genes, 119 (92.2%) were annotated to be involved in different biological processes, while 10 genes (7.8%) were classified as an unknown-function gene group. To further confirm the up-regulation of differentially expressed genes, the quantitative real time PCR were performed to test eight randomly selected genes, in which five of them, i.e. α-tubulin, ribosomal protein L13, ferritin, separase and Myohemerythrin-1, exhibited clear up-regulation after nickel exposure. In addition, MnSOD was further studied for the differential expression pattern after nickel exposure and the results showed that MnSOD had a time- and dose-dependent expression pattern in the copepod after nickel exposure. To the best of our knowledge, this is the first attempt to investigate the toxicity

  5. Identifying Regulatory Patterns at the 3'end Regions of Over-expressed and Under-expressed Genes

    KAUST Repository

    Othoum, Ghofran K

    2013-05-01

    Promoters, neighboring regulatory regions and those extending further upstream of the 5’end of genes, are considered one of the main components affecting the expression status of genes in a specific phenotype. More recently research by Chen et al. (2006, 2012) and Mapendano et al. (2010) demonstrated that the 3’end regulatory regions of genes also influence gene expression. However, the association between the regulatory regions surrounding 3’end of genes and their over- or under-expression status in a particular phenotype has not been systematically studied. The aim of this study is to ascertain if regulatory regions surrounding the 3’end of genes contain sufficient regulatory information to correlate genes with their expression status in a particular phenotype. Over- and under-expressed ovarian cancer (OC) genes were used as a model. Exploratory analysis of the 3’end regions were performed by transforming the annotated regions using principal component analysis (PCA), followed by clustering the transformed data thereby achieving a clear separation of genes with different expression status. Additionally, several classification algorithms such as Naïve Bayes, Random Forest and Support Vector Machine (SVM) were tested with different parameter settings to analyze the discriminatory capacity of the 3’end regions of genes related to their gene expression status. The best performance was achieved using the SVM classification model with 10-fold cross-validation that yielded an accuracy of 98.4%, sensitivity of 99.5% and specificity of 92.5%. For gene expression status for newly available instances, based on information derived from the 3’end regions, an SVM predictive model was developed with 10-fold cross-validation that yielded an accuracy of 67.0%, sensitivity of 73.2% and specificity of 61.0%. Moreover, building an SVM with polynomial kernel model to PCA transformed data yielded an accuracy of 83.1%, sensitivity of 92.5% and specificity of 74.8% using

  6. Identifying Regulatory Patterns at the 3'end Regions of Over-expressed and Under-expressed Genes

    KAUST Repository

    Othoum, Ghofran K

    2013-01-01

    Promoters, neighboring regulatory regions and those extending further upstream of the 5’end of genes, are considered one of the main components affecting the expression status of genes in a specific phenotype. More recently research by Chen et al. (2006, 2012) and Mapendano et al. (2010) demonstrated that the 3’end regulatory regions of genes also influence gene expression. However, the association between the regulatory regions surrounding 3’end of genes and their over- or under-expression status in a particular phenotype has not been systematically studied. The aim of this study is to ascertain if regulatory regions surrounding the 3’end of genes contain sufficient regulatory information to correlate genes with their expression status in a particular phenotype. Over- and under-expressed ovarian cancer (OC) genes were used as a model. Exploratory analysis of the 3’end regions were performed by transforming the annotated regions using principal component analysis (PCA), followed by clustering the transformed data thereby achieving a clear separation of genes with different expression status. Additionally, several classification algorithms such as Naïve Bayes, Random Forest and Support Vector Machine (SVM) were tested with different parameter settings to analyze the discriminatory capacity of the 3’end regions of genes related to their gene expression status. The best performance was achieved using the SVM classification model with 10-fold cross-validation that yielded an accuracy of 98.4%, sensitivity of 99.5% and specificity of 92.5%. For gene expression status for newly available instances, based on information derived from the 3’end regions, an SVM predictive model was developed with 10-fold cross-validation that yielded an accuracy of 67.0%, sensitivity of 73.2% and specificity of 61.0%. Moreover, building an SVM with polynomial kernel model to PCA transformed data yielded an accuracy of 83.1%, sensitivity of 92.5% and specificity of 74.8% using

  7. Aging and Gene Expression in the Primate Brain

    Energy Technology Data Exchange (ETDEWEB)

    Fraser, Hunter B.; Khaitovich, Philipp; Plotkin, Joshua B.; Paabo, Svante; Eisen, Michael B.

    2005-02-18

    It is well established that gene expression levels in many organisms change during the aging process, and the advent of DNA microarrays has allowed genome-wide patterns of transcriptional changes associated with aging to be studied in both model organisms and various human tissues. Understanding the effects of aging on gene expression in the human brain is of particular interest, because of its relation to both normal and pathological neurodegeneration. Here we show that human cerebral cortex, human cerebellum, and chimpanzee cortex each undergo different patterns of age-related gene expression alterations. In humans, many more genes undergo consistent expression changes in the cortex than in the cerebellum; in chimpanzees, many genes change expression with age in cortex, but the pattern of changes in expression bears almost no resemblance to that of human cortex. These results demonstrate the diversity of aging patterns present within the human brain, as well as how rapidly genome-wide patterns of aging can evolve between species; they may also have implications for the oxidative free radical theory of aging, and help to improve our understanding of human neurodegenerative diseases.

  8. Aging and gene expression in the primate brain.

    Directory of Open Access Journals (Sweden)

    Hunter B Fraser

    2005-09-01

    Full Text Available It is well established that gene expression levels in many organisms change during the aging process, and the advent of DNA microarrays has allowed genome-wide patterns of transcriptional changes associated with aging to be studied in both model organisms and various human tissues. Understanding the effects of aging on gene expression in the human brain is of particular interest, because of its relation to both normal and pathological neurodegeneration. Here we show that human cerebral cortex, human cerebellum, and chimpanzee cortex each undergo different patterns of age-related gene expression alterations. In humans, many more genes undergo consistent expression changes in the cortex than in the cerebellum; in chimpanzees, many genes change expression with age in cortex, but the pattern of changes in expression bears almost no resemblance to that of human cortex. These results demonstrate the diversity of aging patterns present within the human brain, as well as how rapidly genome-wide patterns of aging can evolve between species; they may also have implications for the oxidative free radical theory of aging, and help to improve our understanding of human neurodegenerative diseases.

  9. Clock Genes Influence Gene Expression in Growth Plate and Endochondral Ossification in Mice*

    Science.gov (United States)

    Takarada, Takeshi; Kodama, Ayumi; Hotta, Shogo; Mieda, Michihiro; Shimba, Shigeki; Hinoi, Eiichi; Yoneda, Yukio

    2012-01-01

    We have previously shown transient promotion by parathyroid hormone of Period-1 (Per1) expression in cultured chondrocytes. Here we show the modulation by clock genes of chondrogenic differentiation through gene transactivation of the master regulator of chondrogenesis Indian hedgehog (IHH) in chondrocytes of the growth plate. Several clock genes were expressed with oscillatory rhythmicity in cultured chondrocytes and rib growth plate in mice, whereas chondrogenesis was markedly inhibited in stable transfectants of Per1 in chondrocytic ATDC5 cells and in rib growth plate chondrocytes from mice deficient of brain and muscle aryl hydrocarbon receptor nuclear translocator-like (BMAL1). Ihh promoter activity was regulated by different clock gene products, with clear circadian rhythmicity in expression profiles of Ihh in the growth plate. In BMAL1-null mice, a predominant decrease was seen in Ihh expression in the growth plate with a smaller body size than in wild-type mice. BMAL1 deficit led to disruption of the rhythmic expression profiles of both Per1 and Ihh in the growth plate. A clear rhythmicity was seen with Ihh expression in ATDC5 cells exposed to dexamethasone. In young mice defective of BMAL1 exclusively in chondrocytes, similar abnormalities were found in bone growth and Ihh expression. These results suggest that endochondral ossification is under the regulation of particular clock gene products expressed in chondrocytes during postnatal skeletogenesis through a mechanism relevant to the rhythmic Ihh expression. PMID:22936800

  10. Rhythmic diel pattern of gene expression in juvenile maize leaf.

    Directory of Open Access Journals (Sweden)

    Maciej Jończyk

    Full Text Available BACKGROUND: Numerous biochemical and physiological parameters of living organisms follow a circadian rhythm. Although such rhythmic behavior is particularly pronounced in plants, which are strictly dependent on the daily photoperiod, data on the molecular aspects of the diurnal cycle in plants is scarce and mostly concerns the model species Arabidopsis thaliana. Here we studied the leaf transcriptome in seedlings of maize, an important C4 crop only distantly related to A. thaliana, throughout a cycle of 10 h darkness and 14 h light to look for rhythmic patterns of gene expression. RESULTS: Using DNA microarrays comprising ca. 43,000 maize-specific probes we found that ca. 12% of all genes showed clear-cut diel rhythms of expression. Cluster analysis identified 35 groups containing from four to ca. 1,000 genes, each comprising genes of similar expression patterns. Perhaps unexpectedly, the most pronounced and most common (concerning the highest number of genes expression maxima were observed towards and during the dark phase. Using Gene Ontology classification several meaningful functional associations were found among genes showing similar diel expression patterns, including massive induction of expression of genes related to gene expression, translation, protein modification and folding at dusk and night. Additionally, we found a clear-cut tendency among genes belonging to individual clusters to share defined transcription factor-binding sequences. CONCLUSIONS: Co-expressed genes belonging to individual clusters are likely to be regulated by common mechanisms. The nocturnal phase of the diurnal cycle involves gross induction of fundamental biochemical processes and should be studied more thoroughly than was appreciated in most earlier physiological studies. Although some general mechanisms responsible for the diel regulation of gene expression might be shared among plants, details of the diurnal regulation of gene expression seem to differ

  11. Molecular transformation, gene cloning, and gene expression systems for filamentous fungi

    Science.gov (United States)

    Gold, Scott E.; Duick, John W.; Redman, Regina S.; Rodriguez, Rusty J.

    2001-01-01

    This chapter discusses the molecular transformation, gene cloning, and gene expression systems for filamentous fungi. Molecular transformation involves the movement of discrete amounts of DNA into cells, the expression of genes on the transported DNA, and the sustainable replication of the transforming DNA. The ability to transform fungi is dependent on the stable replication and expression of genes located on the transforming DNA. Three phenomena observed in bacteria, that is, competence, plasmids, and restriction enzymes to facilitate cloning, were responsible for the development of molecular transformation in fungi. Initial transformation success with filamentous fungi, involving the complementation of auxotrophic mutants by exposure to sheared genomic DNA or RNA from wt isolates, occurred with low transformation efficiencies. In addition, it was difficult to retrieve complementing DNA fragments and isolate genes of interest. This prompted the development of transformation vectors and methods to increase efficiencies. The physiological studies performed with fungi indicated that the cell wall could be removed to generate protoplasts. It was evident that protoplasts could be transformed with significantly greater efficiencies than walled cells.

  12. With Reference to Reference Genes: A Systematic Review of Endogenous Controls in Gene Expression Studies.

    Science.gov (United States)

    Chapman, Joanne R; Waldenström, Jonas

    2015-01-01

    The choice of reference genes that are stably expressed amongst treatment groups is a crucial step in real-time quantitative PCR gene expression studies. Recent guidelines have specified that a minimum of two validated reference genes should be used for normalisation. However, a quantitative review of the literature showed that the average number of reference genes used across all studies was 1.2. Thus, the vast majority of studies continue to use a single gene, with β-actin (ACTB) and/or glyceraldehyde 3-phosphate dehydrogenase (GAPDH) being commonly selected in studies of vertebrate gene expression. Few studies (15%) tested a panel of potential reference genes for stability of expression before using them to normalise data. Amongst studies specifically testing reference gene stability, few found ACTB or GAPDH to be optimal, whereby these genes were significantly less likely to be chosen when larger panels of potential reference genes were screened. Fewer reference genes were tested for stability in non-model organisms, presumably owing to a dearth of available primers in less well characterised species. Furthermore, the experimental conditions under which real-time quantitative PCR analyses were conducted had a large influence on the choice of reference genes, whereby different studies of rat brain tissue showed different reference genes to be the most stable. These results highlight the importance of validating the choice of normalising reference genes before conducting gene expression studies.

  13. Gene expression variability in human hepatic drug metabolizing enzymes and transporters.

    Directory of Open Access Journals (Sweden)

    Lun Yang

    Full Text Available Interindividual variability in the expression of drug-metabolizing enzymes and transporters (DMETs in human liver may contribute to interindividual differences in drug efficacy and adverse reactions. Published studies that analyzed variability in the expression of DMET genes were limited by sample sizes and the number of genes profiled. We systematically analyzed the expression of 374 DMETs from a microarray data set consisting of gene expression profiles derived from 427 human liver samples. The standard deviation of interindividual expression for DMET genes was much higher than that for non-DMET genes. The 20 DMET genes with the largest variability in the expression provided examples of the interindividual variation. Gene expression data were also analyzed using network analysis methods, which delineates the similarities of biological functionalities and regulation mechanisms for these highly variable DMET genes. Expression variability of human hepatic DMET genes may affect drug-gene interactions and disease susceptibility, with concomitant clinical implications.

  14. Identification of a gene expression profile that discriminates indirect-acting genotoxins from direct-acting genotoxins

    Energy Technology Data Exchange (ETDEWEB)

    Hu Ting; Gibson, David P.; Carr, Gregory J.; Torontali, Suzanne M.; Tiesman, Jay P.; Chaney, Joel G.; Aardema, Marilyn J

    2004-05-18

    During the safety evaluation process of new drugs and chemicals, a battery of genotoxicity tests is conducted starting with in vitro genotoxicity assays. Obtaining positive results in in vitro genotoxicity tests is not uncommon. Follow-up studies to determine the biological relevance of positive genotoxicity results are costly, time consuming, and utilize animals. More efficient methods, especially for identifying a putative mode of action like an indirect mechanism of genotoxicity (where DNA molecules are not the initial primary targets), would greatly improve the risk assessment for genotoxins. To this end, we are participating in an International Life Sciences Institute (ILSI) project involving studies of gene expression changes caused by model genotoxins. The purpose of the work is to evaluate gene expression tools in general, and specifically for discriminating genotoxins that are direct-acting from indirect-acting. Our lab has evaluated gene expression changes as well as micronuclei (MN) in L5178Y TK{sup +/-} mouse lymphoma cells treated with six compounds. Direct-acting genotoxins (where DNA is the initial primary target) that were evaluated included the DNA crosslinking agents, mitomycin C (MMC) and cisplatin (CIS), and an alkylating agent, methyl methanesulfonate (MMS). Indirect-acting genotoxins included hydroxyurea (HU), a ribonucleotide reductase inhibitor, taxol (TXL), a microtubule inhibitor, and etoposide (ETOP), a DNA topoisomerase II inhibitor. Microarray gene expression analysis was conducted using Affymetrix mouse oligonucleotide arrays on RNA samples derived from cells which were harvested immediately after the 4 h chemical treatment, and 20 h after the 4 h chemical treatment. The evaluation of these experimental results yields evidence of differentially regulated genes at both 4 and 24 h time points that appear to have discriminating power for direct versus indirect genotoxins, and therefore may serve as a fingerprint for classifying chemicals

  15. Gravity-regulated gene expression in Arabidopsis thaliana

    Science.gov (United States)

    Sederoff, Heike; Brown, Christopher S.; Heber, Steffen; Kajla, Jyoti D.; Kumar, Sandeep; Lomax, Terri L.; Wheeler, Benjamin; Yalamanchili, Roopa

    Plant growth and development is regulated by changes in environmental signals. Plants sense environmental changes and respond to them by modifying gene expression programs to ad-just cell growth, differentiation, and metabolism. Functional expression of genes comprises many different processes including transcription, translation, post-transcriptional and post-translational modifications, as well as the degradation of RNA and proteins. Recently, it was discovered that small RNAs (sRNA, 18-24 nucleotides long), which are heritable and systemic, are key elements in regulating gene expression in response to biotic and abiotic changes. Sev-eral different classes of sRNAs have been identified that are part of a non-cell autonomous and phloem-mobile network of regulators affecting transcript stability, translational kinetics, and DNA methylation patterns responsible for heritable transcriptional silencing (epigenetics). Our research has focused on gene expression changes in response to gravistimulation of Arabidopsis roots. Using high-throughput technologies including microarrays and 454 sequencing, we iden-tified rapid changes in transcript abundance of genes as well as differential expression of small RNA in Arabidopsis root apices after minutes of reorientation. Some of the differentially regu-lated transcripts are encoded by genes that are important for the bending response. Functional mutants of those genes respond faster to reorientation than the respective wild type plants, indicating that these proteins are repressors of differential cell elongation. We compared the gravity responsive sRNAs to the changes in transcript abundances of their putative targets and identified several potential miRNA: target pairs. Currently, we are using mutant and transgenic Arabidopsis plants to characterize the function of those miRNAs and their putative targets in gravitropic and phototropic responses in Arabidopsis.

  16. Acute Vhl gene inactivation induces cardiac HIF-dependent erythropoietin gene expression.

    Directory of Open Access Journals (Sweden)

    Marta Miró-Murillo

    Full Text Available Von Hippel Lindau (Vhl gene inactivation results in embryonic lethality. The consequences of its inactivation in adult mice, and of the ensuing activation of the hypoxia-inducible factors (HIFs, have been explored mainly in a tissue-specific manner. This mid-gestation lethality can be also circumvented by using a floxed Vhl allele in combination with an ubiquitous tamoxifen-inducible recombinase Cre-ER(T2. Here, we characterize a widespread reduction in Vhl gene expression in Vhl(floxed-UBC-Cre-ER(T2 adult mice after dietary tamoxifen administration, a convenient route of administration that has yet to be fully characterized for global gene inactivation. Vhl gene inactivation rapidly resulted in a marked splenomegaly and skin erythema, accompanied by renal and hepatic induction of the erythropoietin (Epo gene, indicative of the in vivo activation of the oxygen sensing HIF pathway. We show that acute Vhl gene inactivation also induced Epo gene expression in the heart, revealing cardiac tissue to be an extra-renal source of EPO. Indeed, primary cardiomyocytes and HL-1 cardiac cells both induce Epo gene expression when exposed to low O(2 tension in a HIF-dependent manner. Thus, as well as demonstrating the potential of dietary tamoxifen administration for gene inactivation studies in UBC-Cre-ER(T2 mouse lines, this data provides evidence of a cardiac oxygen-sensing VHL/HIF/EPO pathway in adult mice.

  17. Hepatocyte specific expression of human cloned genes

    Energy Technology Data Exchange (ETDEWEB)

    Cortese, R

    1986-01-01

    A large number of proteins are specifically synthesized in the hepatocyte. Only the adult liver expresses the complete repertoire of functions which are required at various stages during development. There is therefore a complex series of regulatory mechanisms responsible for the maintenance of the differentiated state and for the developmental and physiological variations in the pattern of gene expression. Human hepatoma cell lines HepG2 and Hep3B display a pattern of gene expression similar to adult and fetal liver, respectively; in contrast, cultured fibroblasts or HeLa cells do not express most of the liver specific genes. They have used these cell lines for transfection experiments with cloned human liver specific genes. DNA segments coding for alpha1-antitrypsin and retinol binding protein (two proteins synthesized both in fetal and adult liver) are expressed in the hepatoma cell lines HepG2 and Hep3B, but not in HeLa cells or fibroblasts. A DNA segment coding for haptoglobin (a protein synthesized only after birth) is only expressed in the hepatoma cell line HepG2 but not in Hep3B nor in non hepatic cell lines. The information for tissue specific expression is located in the 5' flanking region of all three genes. In vivo competition experiments show that these DNA segments bind to a common, apparently limiting, transacting factor. Conventional techniques (Bal deletions, site directed mutagenesis, etc.) have been used to precisely identify the DNA sequences responsible for these effects. The emerging picture is complex: they have identified multiple, separate transcriptional signals, essential for maximal promoter activation and tissue specific expression. Some of these signals show a negative effect on transcription in fibroblast cell lines.

  18. Optimal Reference Genes for Gene Expression Normalization in Trichomonas vaginalis

    Science.gov (United States)

    dos Santos, Odelta; de Vargas Rigo, Graziela; Frasson, Amanda Piccoli; Macedo, Alexandre José; Tasca, Tiana

    2015-01-01

    Trichomonas vaginalis is the etiologic agent of trichomonosis, the most common non-viral sexually transmitted disease worldwide. This infection is associated with several health consequences, including cervical and prostate cancers and HIV acquisition. Gene expression analysis has been facilitated because of available genome sequences and large-scale transcriptomes in T. vaginalis, particularly using quantitative real-time polymerase chain reaction (qRT-PCR), one of the most used methods for molecular studies. Reference genes for normalization are crucial to ensure the accuracy of this method. However, to the best of our knowledge, a systematic validation of reference genes has not been performed for T. vaginalis. In this study, the transcripts of nine candidate reference genes were quantified using qRT-PCR under different cultivation conditions, and the stability of these genes was compared using the geNorm and NormFinder algorithms. The most stable reference genes were α-tubulin, actin and DNATopII, and, conversely, the widely used T. vaginalis reference genes GAPDH and β-tubulin were less stable. The PFOR gene was used to validate the reliability of the use of these candidate reference genes. As expected, the PFOR gene was upregulated when the trophozoites were cultivated with ferrous ammonium sulfate when the DNATopII, α-tubulin and actin genes were used as normalizing gene. By contrast, the PFOR gene was downregulated when the GAPDH gene was used as an internal control, leading to misinterpretation of the data. These results provide an important starting point for reference gene selection and gene expression analysis with qRT-PCR studies of T. vaginalis. PMID:26393928

  19. Vascular Gene Expression in Nonneoplastic and Malignant Brain

    Science.gov (United States)

    Madden, Stephen L.; Cook, Brian P.; Nacht, Mariana; Weber, William D.; Callahan, Michelle R.; Jiang, Yide; Dufault, Michael R.; Zhang, Xiaoming; Zhang, Wen; Walter-Yohrling, Jennifer; Rouleau, Cecile; Akmaev, Viatcheslav R.; Wang, Clarence J.; Cao, Xiaohong; St. Martin, Thia B.; Roberts, Bruce L.; Teicher, Beverly A.; Klinger, Katherine W.; Stan, Radu-Virgil; Lucey, Brenden; Carson-Walter, Eleanor B.; Laterra, John; Walter, Kevin A.

    2004-01-01

    Malignant gliomas are uniformly lethal tumors whose morbidity is mediated in large part by the angiogenic response of the brain to the invading tumor. This profound angiogenic response leads to aggressive tumor invasion and destruction of surrounding brain tissue as well as blood-brain barrier breakdown and life-threatening cerebral edema. To investigate the molecular mechanisms governing the proliferation of abnormal microvasculature in malignant brain tumor patients, we have undertaken a cell-specific transcriptome analysis from surgically harvested nonneoplastic and tumor-associated endothelial cells. SAGE-derived endothelial cell gene expression patterns from glioma and nonneoplastic brain tissue reveal distinct gene expression patterns and consistent up-regulation of certain glioma endothelial marker genes across patient samples. We define the G-protein-coupled receptor RDC1 as a tumor endothelial marker whose expression is distinctly induced in tumor endothelial cells of both brain and peripheral vasculature. Further, we demonstrate that the glioma-induced gene, PV1, shows expression both restricted to endothelial cells and coincident with endothelial cell tube formation. As PV1 provides a framework for endothelial cell caveolar diaphragms, this protein may serve to enhance glioma-induced disruption of the blood-brain barrier and transendothelial exchange. Additional characterization of this extensive brain endothelial cell gene expression database will provide unique molecular insights into vascular gene expression. PMID:15277233

  20. A predictive toxicogenomics signature to classify genotoxic versus non-genotoxic chemicals in human TK6 cells

    Directory of Open Access Journals (Sweden)

    Andrew Williams

    2015-12-01

    Full Text Available Genotoxicity testing is a critical component of chemical assessment. The use of integrated approaches in genetic toxicology, including the incorporation of gene expression data to determine the DNA damage response pathways involved in response, is becoming more common. In companion papers previously published in Environmental and Molecular Mutagenesis, Li et al. (2015 [6] developed a dose optimization protocol that was based on evaluating expression changes in several well-characterized stress-response genes using quantitative real-time PCR in human lymphoblastoid TK6 cells in culture. This optimization approach was applied to the analysis of TK6 cells exposed to one of 14 genotoxic or 14 non-genotoxic agents, with sampling 4 h post-exposure. Microarray-based transcriptomic analyses were then used to develop a classifier for genotoxicity using the nearest shrunken centroids method. A panel of 65 genes was identified that could accurately classify toxicants as genotoxic or non-genotoxic. In Buick et al. (2015 [1], the utility of the biomarker for chemicals that require metabolic activation was evaluated. In this study, TK6 cells were exposed to increasing doses of four chemicals (two genotoxic that require metabolic activation and two non-genotoxic chemicals in the presence of rat liver S9 to demonstrate that S9 does not impair the ability to classify genotoxicity using this genomic biomarker in TK6cells.

  1. A support vector machine and a random forest classifier indicates a 15-miRNA set related to osteosarcoma recurrence

    Directory of Open Access Journals (Sweden)

    He Y

    2018-01-01

    Full Text Available Yunfei He,1,2,* Jun Ma,1,* An Wang,1,3,* Weiheng Wang,1 Shengchang Luo,1 Yaoming Liu,2 Xiaojian Ye1 1Department of Orthopaedics, Changzheng Hospital Affiliated with Second Military Medical University, Shanghai, 2Department of Orthopaedics, Lanzhou General Hospital of Lanzhou Military Command Region, Lanzhou, 3Department of Orthopaedics, Shanghai Armed Police Force Hospital, Shanghai, People’s Republic of China *These authors contributed equally to this work Background: Osteosarcoma, which originates in the mesenchymal tissue, is the prevalent primary solid malignancy of the bone. It is of great importance to explore the mechanisms of metastasis and recurrence, which are two primary reasons accounting for the high death rate in osteosarcoma. Data and methods: Three miRNA expression profiles related to osteosarcoma were downloaded from GEO DataSets. Differentially expressed miRNAs (DEmiRs were screened using MetaDE.ES of the MetaDE package. A support vector machine (SVM classifier was constructed using optimal miRNAs, and its prediction efficiency for recurrence was detected in independent datasets. Finally, a co-expression network was constructed based on the DEmiRs and their target genes. Results: In total, 78 significantly DEmiRs were screened. The SVM classifier constructed by 15 miRNAs could accurately classify 58 samples in 65 samples (89.2% in the GSE39040 database, which was validated in another two databases, GSE39052 (84.62%, 22/26 and GSE79181 (91.3%, 21/23. Cox regression showed that four miRNAs, including hsa-miR-10b, hsa-miR-1227, hsa-miR-146b-3p, and hsa-miR-873, significantly correlated with tumor recurrence time. There were 137, 147, 145, and 77 target genes of the above four miRNAs, respectively, which were assigned to 17 gene ontology functionally annotated terms and 14 Kyoto Encyclopedia of Genes and Genomes pathways. Among them, the “Osteoclast differentiation” pathway contained a total of seven target genes and was

  2. GeneCAT--novel webtools that combine BLAST and co-expression analyses

    DEFF Research Database (Denmark)

    Mutwil, Marek; Obro, Jens; Willats, William G T

    2008-01-01

    The gene co-expression analysis toolbox (GeneCAT) introduces several novel microarray data analyzing tools. First, the multigene co-expression analysis, combined with co-expressed gene networks, provides a more powerful data mining technique than standard, single-gene co-expression analysis. Second...... orthologs in the plant model organisms Arabidopsis thaliana and Hordeum vulgare (Barley). GeneCAT is equipped with expression data for the model plant A. thaliana, and first to introduce co-expression mining tools for the monocot Barley. GeneCAT is available at http://genecat.mpg.de....

  3. Automated discovery of functional generality of human gene expression programs.

    Directory of Open Access Journals (Sweden)

    Georg K Gerber

    2007-08-01

    Full Text Available An important research problem in computational biology is the identification of expression programs, sets of co-expressed genes orchestrating normal or pathological processes, and the characterization of the functional breadth of these programs. The use of human expression data compendia for discovery of such programs presents several challenges including cellular inhomogeneity within samples, genetic and environmental variation across samples, uncertainty in the numbers of programs and sample populations, and temporal behavior. We developed GeneProgram, a new unsupervised computational framework based on Hierarchical Dirichlet Processes that addresses each of the above challenges. GeneProgram uses expression data to simultaneously organize tissues into groups and genes into overlapping programs with consistent temporal behavior, to produce maps of expression programs, which are sorted by generality scores that exploit the automatically learned groupings. Using synthetic and real gene expression data, we showed that GeneProgram outperformed several popular expression analysis methods. We applied GeneProgram to a compendium of 62 short time-series gene expression datasets exploring the responses of human cells to infectious agents and immune-modulating molecules. GeneProgram produced a map of 104 expression programs, a substantial number of which were significantly enriched for genes involved in key signaling pathways and/or bound by NF-kappaB transcription factors in genome-wide experiments. Further, GeneProgram discovered expression programs that appear to implicate surprising signaling pathways or receptor types in the response to infection, including Wnt signaling and neurotransmitter receptors. We believe the discovered map of expression programs involved in the response to infection will be useful for guiding future biological experiments; genes from programs with low generality scores might serve as new drug targets that exhibit minimal

  4. Blood cell gene expression profiling in rheumatoid arthritis. Discriminative genes and effect of rheumatoid factor

    DEFF Research Database (Denmark)

    Bovin, Lone Frier; Rieneck, Klaus; Workman, Christopher

    2004-01-01

    To study the pathogenic importance of the rheumatoid factor (RF) in rheumatoid arthritis (RA) and to identify genes differentially expressed in patients and healthy individuals, total RNA was isolated from peripheral blood mononuclear cells (PBMC) from eight RF-positive and six RF-negative RA...... patients, and seven healthy controls. Gene expression of about 10,000 genes were examined using oligonucleotide-based DNA chip microarrays. The analyses showed no significant differences in PBMC expression patterns from RF-positive and RF-negative patients. However, comparisons of gene expression patterns...

  5. A compendium of canine normal tissue gene expression.

    Directory of Open Access Journals (Sweden)

    Joseph Briggs

    Full Text Available BACKGROUND: Our understanding of disease is increasingly informed by changes in gene expression between normal and abnormal tissues. The release of the canine genome sequence in 2005 provided an opportunity to better understand human health and disease using the dog as clinically relevant model. Accordingly, we now present the first genome-wide, canine normal tissue gene expression compendium with corresponding human cross-species analysis. METHODOLOGY/PRINCIPAL FINDINGS: The Affymetrix platform was utilized to catalogue gene expression signatures of 10 normal canine tissues including: liver, kidney, heart, lung, cerebrum, lymph node, spleen, jejunum, pancreas and skeletal muscle. The quality of the database was assessed in several ways. Organ defining gene sets were identified for each tissue and functional enrichment analysis revealed themes consistent with known physio-anatomic functions for each organ. In addition, a comparison of orthologous gene expression between matched canine and human normal tissues uncovered remarkable similarity. To demonstrate the utility of this dataset, novel canine gene annotations were established based on comparative analysis of dog and human tissue selective gene expression and manual curation of canine probeset mapping. Public access, using infrastructure identical to that currently in use for human normal tissues, has been established and allows for additional comparisons across species. CONCLUSIONS/SIGNIFICANCE: These data advance our understanding of the canine genome through a comprehensive analysis of gene expression in a diverse set of tissues, contributing to improved functional annotation that has been lacking. Importantly, it will be used to inform future studies of disease in the dog as a model for human translational research and provides a novel resource to the community at large.

  6. Expression of streptavidin gene in bacteria and plants

    International Nuclear Information System (INIS)

    Guan, Xueni; Wurtele, E.S.; Nikolau, B.J.

    1990-01-01

    Six biotin-containing proteins are present in plants, representing at least four different biotin enzymes. The physiological function of these biotin enzymes is not understood. Streptavidin, a protein from Streptomyces avidinii, binds tightly and specifically to biotin causing inactivation of biotin enzymes. One approach to elucidating the physiological function of biotin enzymes in plant metabolism is to create transgenic plants expressing the streptavidin gene. A plasmid containing a fused streptavidin-beta-galactosidase gene has been expressed in E. coli. We also have constructed various fusion genes that include an altered CaMV 35S promoter, signal peptides to target the streptavidin protein to specific organelles, and the streptavidin coding gene. We are examining the expression of these genes in cells of carrot

  7. Evaluation of suitable reference genes for gene expression studies ...

    Indian Academy of Sciences (India)

    2011-12-14

    Dec 14, 2011 ... MADS family of TFs control floral organ identity within each whorl of the flower by activating downstream genes. Measuring gene expression in different tissue types and developmental stages is of fundamental importance in TFs functional research. In last few years, quantitative real-time. PCR (qRT-PCR) ...

  8. Identification of differentially expressed genes in cucumber (Cucumis sativus L.) root under waterlogging stress by digital gene expression profile.

    Science.gov (United States)

    Qi, Xiao-Hua; Xu, Xue-Wen; Lin, Xiao-Jian; Zhang, Wen-Jie; Chen, Xue-Hao

    2012-03-01

    High-throughput tag-sequencing (Tag-seq) analysis based on the Solexa Genome Analyzer platform was applied to analyze the gene expression profiling of cucumber plant at 5 time points over a 24h period of waterlogging treatment. Approximately 5.8 million total clean sequence tags per library were obtained with 143013 distinct clean tag sequences. Approximately 23.69%-29.61% of the distinct clean tags were mapped unambiguously to the unigene database, and 53.78%-60.66% of the distinct clean tags were mapped to the cucumber genome database. Analysis of the differentially expressed genes revealed that most of the genes were down-regulated in the waterlogging stages, and the differentially expressed genes mainly linked to carbon metabolism, photosynthesis, reactive oxygen species generation/scavenging, and hormone synthesis/signaling. Finally, quantitative real-time polymerase chain reaction using nine genes independently verified the tag-mapped results. This present study reveals the comprehensive mechanisms of waterlogging-responsive transcription in cucumber. Copyright © 2011 Elsevier Inc. All rights reserved.

  9. Cartilage-selective genes identified in genome-scale analysis of non-cartilage and cartilage gene expression

    Directory of Open Access Journals (Sweden)

    Cohn Zachary A

    2007-06-01

    Full Text Available Abstract Background Cartilage plays a fundamental role in the development of the human skeleton. Early in embryogenesis, mesenchymal cells condense and differentiate into chondrocytes to shape the early skeleton. Subsequently, the cartilage anlagen differentiate to form the growth plates, which are responsible for linear bone growth, and the articular chondrocytes, which facilitate joint function. However, despite the multiplicity of roles of cartilage during human fetal life, surprisingly little is known about its transcriptome. To address this, a whole genome microarray expression profile was generated using RNA isolated from 18–22 week human distal femur fetal cartilage and compared with a database of control normal human tissues aggregated at UCLA, termed Celsius. Results 161 cartilage-selective genes were identified, defined as genes significantly expressed in cartilage with low expression and little variation across a panel of 34 non-cartilage tissues. Among these 161 genes were cartilage-specific genes such as cartilage collagen genes and 25 genes which have been associated with skeletal phenotypes in humans and/or mice. Many of the other cartilage-selective genes do not have established roles in cartilage or are novel, unannotated genes. Quantitative RT-PCR confirmed the unique pattern of gene expression observed by microarray analysis. Conclusion Defining the gene expression pattern for cartilage has identified new genes that may contribute to human skeletogenesis as well as provided further candidate genes for skeletal dysplasias. The data suggest that fetal cartilage is a complex and transcriptionally active tissue and demonstrate that the set of genes selectively expressed in the tissue has been greatly underestimated.

  10. Gene expression during Drosophila melanogaster egg development before and after reproductive diapause

    Directory of Open Access Journals (Sweden)

    Baker Dean A

    2009-05-01

    Full Text Available Abstract Background Despite the importance of egg development to the female life cycle in Drosophila, global patterns of gene expression have not been examined in detail, primarily due to the difficulty in isolating synchronised developmental stages in sufficient quantities for gene expression profiling. Entry into vitellogenesis is a key stage of oogenesis and by forcing females into reproductive diapause we are able to arrest oogenesis at the pre-vitellogenic stages. Releasing females from diapause allows collection of relatively synchronous developing egg populations and an investigation of some of the transcriptional dynamics apparent before and after reproductive diapause. Results Focusing on gender-biased transcription, we identified mechanisms of egg development suppressed during reproductive dormancy as well as other molecular changes unique to the diapausing female. A microarray based analysis generated a set of 3565 transcripts with at least 2-fold greater expression in females as compared to control males, 1392 such changes were biased during reproductive dormancy. In addition, we also detect 1922 up-regulated transcriptional changes after entry into vitellogenesis, which were classified into discrete blocks of co-expression. We discuss some of the regulatory aspects apparent after re-initiation of egg development, exploring the underlying functions, maternal contribution and evolutionary conservation of co-expression patterns involved in egg production. Conclusion Although much of the work we present is descriptive, fundamental aspects of egg development and gender-biased transcription can be derived from our time-series experiment. We believe that our dataset will facilitate further exploration of the developmental and evolutionary characteristics of oogenesis as well as the nature of reproductive arrest in Drosophila.

  11. Gene expression profiling of resting and activated vascular smooth muscle cells by serial analysis of gene expression and clustering analysis

    NARCIS (Netherlands)

    Beauchamp, Nicholas J.; van Achterberg, Tanja A. E.; Engelse, Marten A.; Pannekoek, Hans; de Vries, Carlie J. M.

    2003-01-01

    Migration and proliferation of vascular smooth muscle cells (SMCs) are key events in atherosclerosis. However, little is known about alterations in gene expression upon transition of the quiescent, contractile SMC to the proliferative SMC. We performed serial analysis of gene expression (SAGE) of

  12. [Genome-wide identification and expression analysis of the WRKY gene family in peach].

    Science.gov (United States)

    Gu, Yan-bing; Ji, Zhi-rui; Chi, Fu-mei; Qiao, Zhuang; Xu, Cheng-nan; Zhang, Jun-xiang; Zhou, Zong-shan; Dong, Qing-long

    2016-03-01

    The WRKY transcription factors are one of the largest families of transcriptional regulators and play diverse regulatory roles in biotic and abiotic stresses, plant growth and development processes. In this study, the WRKY DNA-binding domain (Pfam Database number: PF03106) downloaded from Pfam protein families database was exploited to identify WRKY genes from the peach (Prunus persica 'Lovell') genome using HMMER 3.0. The obtained amino acid sequences were analyzed with DNAMAN 5.0, WebLogo 3, MEGA 5.1, MapInspect and MEME bioinformatics softwares. Totally 61 peach WRKY genes were found in the peach genome. Our phylogenetic analysis revealed that peach WRKY genes were classified into three Groups: Ⅰ, Ⅱ and Ⅲ. The WRKY N-terminal and C-terminal domains of Group Ⅰ (group I-N and group I-C) were monophyletic. The Group Ⅱ was sub-divided into five distinct clades (groupⅡ-a, Ⅱ-b, Ⅱ-c, Ⅱ-d and Ⅱ-e). Our domain analysis indicated that the WRKY regions contained a highly conserved heptapeptide stretch WRKYGQK at its N-terminus followed by a zinc-finger motif. The chromosome mapping analysis showed that peach WRKY genes were distributed with different densities over 8 chromosomes. The intron-exon structure analysis revealed that structures of the WRKY gene were highly conserved in the peach. The conserved motif analysis showed that the conserved motifs 1, 2 and 3, which specify the WRKY domain, were observed in all peach WRKY proteins, motif 5 as the unknown domain was observed in group Ⅱ-d, two WRKY domains were assigned to GroupⅠ. SqRT-PCR and qRT-PCR results indicated that 16 PpWRKY genes were expressed in roots, stems, leaves, flowers and fruits at various expression levels. Our analysis thus identified the PpWRKY gene families, and future functional studies are needed to reveal its specific roles.

  13. Oxygen and tissue culture affect placental gene expression.

    Science.gov (United States)

    Brew, O; Sullivan, M H F

    2017-07-01

    Placental explant culture is an important model for studying placental development and functions. We investigated the differences in placental gene expression in response to tissue culture, atmospheric and physiologic oxygen concentrations. Placental explants were collected from normal term (38-39 weeks of gestation) placentae with no previous uterine contractile activity. Placental transcriptomic expressions were evaluated with GeneChip ® Human Genome U133 Plus 2.0 arrays (Affymetrix). We uncovered sub-sets of genes that regulate response to stress, induction of apoptosis programmed cell death, mis-regulation of cell growth, proliferation, cell morphogenesis, tissue viability, and protection from apoptosis in cultured placental explants. We also identified a sub-set of genes with highly unstable pattern of expression after exposure to tissue culture. Tissue culture irrespective of oxygen concentration induced dichotomous increase in significant gene expression and increased enrichment of significant pathways and transcription factor targets (TFTs) including HIF1A. The effect was exacerbated by culture at atmospheric oxygen concentration, where further up-regulation of TFTs including PPARA, CEBPD, HOXA9 and down-regulated TFTs such as JUND/FOS suggest intrinsic heightened key biological and metabolic mechanisms such as glucose use, lipid biosynthesis, protein metabolism; apoptosis, inflammatory responses; and diminished trophoblast proliferation, differentiation, invasion, regeneration, and viability. These findings demonstrate that gene expression patterns differ between pre-culture and cultured explants, and the gene expression of explants cultured at atmospheric oxygen concentration favours stressed, pro-inflammatory and increased apoptotic transcriptomic response. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. VH gene expression and regulation in the mutant Alicia rabbit. Rescue of VHa2 allotype expression.

    Science.gov (United States)

    Chen, H T; Alexander, C B; Young-Cooper, G O; Mage, R G

    1993-04-01

    Rabbits of the Alicia strain, derived from rabbits expressing the VHa2 allotype, have a mutation in the H chain locus that has a cis effect upon the expression of VHa2 and VHa- genes. A small deletion at the most J-proximal (3') end of the VH locus leads to low expression of all the genes on the entire chromosome in heterozygous ali mutants and altered relative expression of VH genes in homozygotes. To study VH gene expression and regulation, we used the polymerase chain reaction to amplify the VH genes expressed in spleens of young and adult wild-type and mutant Alicia rabbits. The cDNA from reverse transcription of splenic mRNA was amplified and polymerase chain reaction libraries were constructed and screened with oligonucleotides from framework regions 1 and 3, as well as JH. Thirty-three VH-positive clones were sequenced and analyzed. We found that in mutant Alicia rabbits, products of the first functional VH gene (VH4a2), (or VH4a2-like genes) were expressed in 2- to 8-wk-olds. Expression of both the VHx and VHy types of VHa- genes was also elevated but the relative proportions of VHx and VHy, especially VHx, decreased whereas the relative levels of expression of VH4a2 or VH4a2-like genes increased with age. Our results suggest that the appearance of sequences resembling that of the VH1a2, which is deleted in the mutant ali rabbits, could be caused by alterations of the sequences of the rearranged VH4a2 genes by gene conversions and/or rearrangement of upstream VH1a2-like genes later in development.

  15. Genome-wide analysis of the sox family in the calcareous sponge Sycon ciliatum: multiple genes with unique expression patterns

    Directory of Open Access Journals (Sweden)

    Fortunato Sofia

    2012-07-01

    Full Text Available Abstract Background Sox genes are HMG-domain containing transcription factors with important roles in developmental processes in animals; many of them appear to have conserved functions among eumetazoans. Demosponges have fewer Sox genes than eumetazoans, but their roles remain unclear. The aim of this study is to gain insight into the early evolutionary history of the Sox gene family by identification and expression analysis of Sox genes in the calcareous sponge Sycon ciliatum. Methods Calcaronean Sox related sequences were retrieved by searching recently generated genomic and transcriptome sequence resources and analyzed using variety of phylogenetic methods and identification of conserved motifs. Expression was studied by whole mount in situ hybridization. Results We have identified seven Sox genes and four Sox-related genes in the complete genome of Sycon ciliatum. Phylogenetic and conserved motif analyses showed that five of Sycon Sox genes represent groups B, C, E, and F present in cnidarians and bilaterians. Two additional genes are classified as Sox genes but cannot be assigned to specific subfamilies, and four genes are more similar to Sox genes than to other HMG-containing genes. Thus, the repertoire of Sox genes is larger in this representative of calcareous sponges than in the demosponge Amphimedon queenslandica. It remains unclear whether this is due to the expansion of the gene family in Sycon or a secondary reduction in the Amphimedon genome. In situ hybridization of Sycon Sox genes revealed a variety of expression patterns during embryogenesis and in specific cell types of adult sponges. Conclusions In this study, we describe a large family of Sox genes in Sycon ciliatum with dynamic expression patterns, indicating that Sox genes are regulators in development and cell type determination in sponges, as observed in higher animals. The revealed differences between demosponge and calcisponge Sox genes repertoire highlight the need to

  16. The human cumulus--oocyte complex gene-expression profile

    Science.gov (United States)

    Assou, Said; Anahory, Tal; Pantesco, Véronique; Le Carrour, Tanguy; Pellestor, Franck; Klein, Bernard; Reyftmann, Lionel; Dechaud, Hervé; De Vos, John; Hamamah, Samir

    2006-01-01

    BACKGROUND The understanding of the mechanisms regulating human oocyte maturation is still rudimentary. We have identified transcripts differentially expressed between immature and mature oocytes, and cumulus cells. METHODS Using oligonucleotides microarrays, genome wide gene expression was studied in pooled immature and mature oocytes or cumulus cells from patients who underwent IVF. RESULTS In addition to known genes such as DAZL, BMP15 or GDF9, oocytes upregulated 1514 genes. We show that PTTG3 and AURKC are respectively the securin and the Aurora kinase preferentially expressed during oocyte meiosis. Strikingly, oocytes overexpressed previously unreported growth factors such as TNFSF13/APRIL, FGF9, FGF14, and IL4, and transcription factors including OTX2, SOX15 and SOX30. Conversely, cumulus cells, in addition to known genes such as LHCGR or BMPR2, overexpressed cell-tocell signaling genes including TNFSF11/RANKL, numerous complement components, semaphorins (SEMA3A, SEMA6A, SEMA6D) and CD genes such as CD200. We also identified 52 genes progressively increasing during oocyte maturation, comprising CDC25A and SOCS7. CONCLUSION The identification of genes up and down regulated during oocyte maturation greatly improves our understanding of oocyte biology and will provide new markers that signal viable and competent oocytes. Furthermore, genes found expressed in cumulus cells are potential markers of granulosa cell tumors. PMID:16571642

  17. Platelet-derived growth factor (PDGF) B-chain gene expression by activated blood monocytes precedes the expression of the PDGF A-chain gene

    International Nuclear Information System (INIS)

    Martinet, Y.; Jaffe, H.A.; Yamauchi, K.; Betsholtz, C.; Westermark, B.; Heldin, C.H.; Crystal, R.G.

    1987-01-01

    When activated, normal human blood monocytes are known to express the c-sis proto-oncogene coding for PDGF B-chain. Since normal human platelet PDGF molecules are dimers of A and B chains and platelets and monocytes are derived from the same marrow precursors, activated blood monocytes were simultaneously evaluated for their expression of PDGF A and B chain genes. Human blood monocytes were purified by adherence, cultured with or without activation by lipopolysaccharide and poly(A)+ RNA evaluated using Northern analysis and 32 P-labeled A-chain and B-chain (human c-sis) probes. Unstimulated blood monocytes did not express either A-chain or B-chain genes. In contrast, activated monocytes expressed a 4.2 kb mRNA B-chain transcript at 4 hr, but the B-chain mRNA levels declined significantly over the next 18 hr. In comparison, activated monocytes expressed very little A-chain mRNA at 4 hr, but at 12 hr 1.9, 2.3, and 2.8 kb transcripts were observed and persisted through 24 hr. Thus, activation of blood monocytes is followed by PDGF B-chain gene expression preceding PDGF A-chain gene expression, suggesting a difference in the regulation of the expression of the genes for these two chains by these cells

  18. Finding gene regulatory network candidates using the gene expression knowledge base.

    Science.gov (United States)

    Venkatesan, Aravind; Tripathi, Sushil; Sanz de Galdeano, Alejandro; Blondé, Ward; Lægreid, Astrid; Mironov, Vladimir; Kuiper, Martin

    2014-12-10

    Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

  19. Variation in gene expression within clones of the earthworm Dendrobaena octaedra.

    Directory of Open Access Journals (Sweden)

    Marina Mustonen

    Full Text Available Gene expression is highly plastic, which can help organisms to both acclimate and adapt to changing environments. Possible variation in gene expression among individuals with the same genotype (among clones is not widely considered, even though it could impact the results of studies that focus on gene expression phenotypes, for example studies using clonal lines. We examined the extent of within and between clone variation in gene expression in the earthworm Dendrobaena octaedra, which reproduces through apomictic parthenogenesis. Five microsatellite markers were developed and used to confirm that offspring are genetic clones of their parent. After that, expression of 12 genes was measured from five individuals each from six clonal lines after exposure to copper contaminated soil. Variation in gene expression was higher over all genotypes than within genotypes, as initially assumed. A subset of the genes was also examined in the offspring of exposed individuals in two of the clonal lines. In this case, variation in gene expression within genotypes was as high as that observed over all genotypes. One gene in particular (chymotrypsin inhibitor also showed significant differences in the expression levels among genetically identical individuals. Gene expression can vary considerably, and the extent of variation may depend on the genotypes and genes studied. Ensuring a large sample, with many different genotypes, is critical in studies comparing gene expression phenotypes. Researchers should be especially cautious inferring gene expression phenotypes when using only a single clonal or inbred line, since the results might be specific to only certain genotypes.

  20. Dlx homeobox gene family expression in osteoclasts.

    Science.gov (United States)

    Lézot, F; Thomas, B L; Blin-Wakkach, C; Castaneda, B; Bolanos, A; Hotton, D; Sharpe, P T; Heymann, D; Carles, G F; Grigoriadis, A E; Berdal, A

    2010-06-01

    Skeletal growth and homeostasis require the finely orchestrated secretion of mineralized tissue matrices by highly specialized cells, balanced with their degradation by osteoclasts. Time- and site-specific expression of Dlx and Msx homeobox genes in the cells secreting these matrices have been identified as important elements in the regulation of skeletal morphology. Such specific expression patterns have also been reported in osteoclasts for Msx genes. The aim of the present study was to establish the expression patterns of Dlx genes in osteoclasts and identify their function in regulating skeletal morphology. The expression patterns of all Dlx genes were examined during the whole osteoclastogenesis using different in vitro models. The results revealed that Dlx1 and Dlx2 are the only Dlx family members with a possible function in osteoclastogenesis as well as in mature osteoclasts. Dlx5 and Dlx6 were detected in the cultures but appear to be markers of monocytes and their derivatives. In vivo, Dlx2 expression in osteoclasts was examined using a Dlx2/LacZ transgenic mouse. Dlx2 is expressed in a subpopulation of osteoclasts in association with tooth, brain, nerve, and bone marrow volumetric growths. Altogether the present data suggest a role for Dlx2 in regulation of skeletal morphogenesis via functions within osteoclasts. (c) 2010 Wiley-Liss, Inc.

  1. Expression patterns of WRKY genes in di-haploid Populus simonii × P. nigra in response to salinity stress revealed by quantitative real-time PCR and RNA sequencing.

    Science.gov (United States)

    Wang, Shengji; Wang, Jiying; Yao, Wenjing; Zhou, Boru; Li, Renhua; Jiang, Tingbo

    2014-10-01

    Spatio-temporal expression patterns of 13 out of 119 poplar WRKY genes indicated dynamic and tissue-specific roles of WRKY family proteins in salinity stress tolerance. To understand the expression patterns of poplar WRKY genes under salinity stress, 51 of the 119 WRKY genes were selected from di-haploid Populus simonii × P. nigra by quantitative real-time PCR (qRT-PCR). We used qRT-PCR to profile the expression of the top 13 genes under salinity stress across seven time points, and employed RNA-Seq platforms to cross-validate it. Results demonstrated that all the 13 WRKY genes were expressed in root, stem, and leaf tissues, but their expression levels and overall patterns varied notably in these tissues. Regarding overall gene expression in roots, the 13 genes were significantly highly expressed at all six time points after the treatment, reaching the plateau of expression at hour 9. In leaves, the 13 genes were similarly up-regulated from 3 to 12 h in response to NaCl treatment. In stems, however, expression levels of the 13 genes did not show significant changes after the NaCl treatment. Regarding individual gene expression across the time points and the three tissues, the 13 genes can be classified into three clusters: the lowly expressed Cluster 1 containing PthWRKY28, 45 and 105; intermediately expressed Clusters 2 including PthWRKY56, 88 and 116; and highly expressed Cluster 3 consisting of PthWRKY41, 44, 51, 61, 62, 75 and 106. In general, genes in Cluster 2 and 3 displayed a dynamic pattern of "induced amplification-recovering", suggesting that these WRKY genes and corresponding pathways may play a critical role in mediating salt response and tolerance in a dynamic and tissue-specific manner.

  2. PRAME Gene Expression in Acute Leukemia and Its Clinical Significance

    International Nuclear Information System (INIS)

    Ding, Kai; Wang, Xiao-ming; Fu, Rong; Ruan, Er-bao; Liu, Hui; Shao, Zong-hong

    2012-01-01

    To investigate the expression of the preferentially expressed antigen of melanoma (PRAME) gene in acute leukemia and its clinical significance. The level of expressed PRAME mRNA in bone marrow mononuclear cells from 34 patients with acute leukemia (AL) and in 12 bone marrow samples from healthy volunteers was measured via RT-PCR. Correlation analyses between PRAME gene expression and the clinical characteristics (gender, age, white blood count, immunophenotype of leukemia, percentage of blast cells, and karyotype) of the patients were performed. The PRAME gene was expressed in 38.2% of all 34 patients, in 40.7% of the patients with acute myelogenous leukemia (AML, n=27), and in 28.6% of the patients with acute lymphoblastic leukemia (ALL, n=7), but was not expressed in the healthy volunteers. The difference in the expression levels between AML and ALL patients was statistically significant. The rate of gene expression was 80% in M 3 , 33.3% in M 2 , and 28.6% in M 5 . Gene expression was also found to be correlated with CD15 and CD33 expression and abnormal karyotype, but not with age, gender, white blood count or percentage of blast cells. The PRAME gene is highly expressed in acute leukemia and could be a useful marker to monitor minimal residual disease. This gene is also a candidate target for the immunotherapy of acute leukemia

  3. Epigenetic regulation on the gene expression signature in esophagus adenocarcinoma.

    Science.gov (United States)

    Xi, Ting; Zhang, Guizhi

    2017-02-01

    Understanding the molecular mechanisms represents an important step in the development of diagnostic and therapeutic measures of esophagus adenocarcinoma (NOS). The objective of this study is to identify the epigenetic regulation on gene expression in NOS, shedding light on the molecular mechanisms of NOS. In this study, 78 patients with NOS were included and the data of mRNA, miRNA and DNA methylation of were downloaded from The Cancer Genome Atlas (TCGA). Differential analysis between NOS and controls was performed in terms of gene expression, miRNA expression, and DNA methylation. Bioinformatic analysis was followed to explore the regulation mechanisms of miRNA and DNA methylationon gene expression. Totally, up to 1320 differentially expressed genes (DEGs) and 32 differentially expressed miRNAs were identified. 240 DEGs that were not only the target genes but also negatively correlated with the screened differentially expressed miRNAs. 101 DEGs were found to be highlymethylated in CpG islands. Then, 8 differentially methylated genes (DMGs) were selected, which showed down-regulated expression in NOS. Among of these genes, 6 genes including ADHFE1, DPP6, GRIA4, CNKSR2, RPS6KA6 and ZNF135 were target genes of differentially expressed miRNAs (hsa-mir-335, hsa-mir-18a, hsa-mir-93, hsa-mir-106b and hsa-mir-21). The identified altered miRNA, genes and DNA methylation site may be applied as biomarkers for diagnosis and prognosis of NOS. Copyright © 2016 Elsevier GmbH. All rights reserved.

  4. Codon usage and amino acid usage influence genes expression level.

    Science.gov (United States)

    Paul, Prosenjit; Malakar, Arup Kumar; Chakraborty, Supriyo

    2018-02-01

    Highly expressed genes in any species differ in the usage frequency of synonymous codons. The relative recurrence of an event of the favored codon pair (amino acid pairs) varies between gene and genomes due to varying gene expression and different base composition. Here we propose a new measure for predicting the gene expression level, i.e., codon plus amino bias index (CABI). Our approach is based on the relative bias of the favored codon pair inclination among the genes, illustrated by analyzing the CABI score of the Medicago truncatula genes. CABI showed strong correlation with all other widely used measures (CAI, RCBS, SCUO) for gene expression analysis. Surprisingly, CABI outperforms all other measures by showing better correlation with the wet-lab data. This emphasizes the importance of the neighboring codons of the favored codon in a synonymous group while estimating the expression level of a gene.

  5. Profile of the genes expressed in the human peripheral retina, macula, and retinal pigment epithelium determined through serial analysis of gene expression (SAGE)

    Science.gov (United States)

    Sharon, Dror; Blackshaw, Seth; Cepko, Constance L.; Dryja, Thaddeus P.

    2002-01-01

    We used the serial analysis of gene expression (SAGE) technique to catalogue and measure the relative levels of expression of the genes expressed in the human peripheral retina, macula, and retinal pigment epithelium (RPE) from one or both of two humans, aged 88 and 44 years. The cone photoreceptor contribution to all transcription in the retina was found to be similar in the macula versus the retinal periphery, whereas the rod contribution was greater in the periphery versus the macula. Genes encoding structural proteins for axons were found to be expressed at higher levels in the macula versus the retinal periphery, probably reflecting the large proportion of ganglion cells in the central retina. In comparison with the younger eye, the peripheral retina of the older eye had a substantially higher proportion of mRNAs from genes encoding proteins involved in iron metabolism or protection against oxidative damage and a substantially lower proportion of mRNAs from genes encoding proteins involved in rod phototransduction. These differences may reflect the difference in age between the two donors or merely interindividual variation. The RPE library had numerous previously unencountered tags, suggesting that this cell type has a large, idiosyncratic repertoire of expressed genes. Comparison of these libraries with 100 reported nonocular SAGE libraries revealed 89 retina-specific or enriched genes expressed at substantial levels, of which 14 are known to cause a retinal disease and 53 are RPE-specific genes. We expect that these libraries will serve as a resource for understanding the relative expression levels of genes in the retina and the RPE and for identifying additional disease genes. PMID:11756676

  6. Disease gene characterization through large-scale co-expression analysis.

    Directory of Open Access Journals (Sweden)

    Allen Day

    2009-12-01

    Full Text Available In the post genome era, a major goal of biology is the identification of specific roles for individual genes. We report a new genomic tool for gene characterization, the UCLA Gene Expression Tool (UGET.Celsius, the largest co-normalized microarray dataset of Affymetrix based gene expression, was used to calculate the correlation between all possible gene pairs on all platforms, and generate stored indexes in a web searchable format. The size of Celsius makes UGET a powerful gene characterization tool. Using a small seed list of known cartilage-selective genes, UGET extended the list of known genes by identifying 32 new highly cartilage-selective genes. Of these, 7 of 10 tested were validated by qPCR including the novel cartilage-specific genes SDK2 and FLJ41170. In addition, we retrospectively tested UGET and other gene expression based prioritization tools to identify disease-causing genes within known linkage intervals. We first demonstrated this utility with UGET using genetically heterogeneous disorders such as Joubert syndrome, microcephaly, neuropsychiatric disorders and type 2 limb girdle muscular dystrophy (LGMD2 and then compared UGET to other gene expression based prioritization programs which use small but discrete and well annotated datasets. Finally, we observed a significantly higher gene correlation shared between genes in disease networks associated with similar complex or Mendelian disorders.UGET is an invaluable resource for a geneticist that permits the rapid inclusion of expression criteria from one to hundreds of genes in genomic intervals linked to disease. By using thousands of arrays UGET annotates and prioritizes genes better than other tools especially with rare tissue disorders or complex multi-tissue biological processes. This information can be critical in prioritization of candidate genes for sequence analysis.

  7. Molecular Imaging of Gene Expression and Efficacy following Adenoviral-Mediated Brain Tumor Gene Therapy

    Directory of Open Access Journals (Sweden)

    Alnawaz Rehemtulla

    2002-01-01

    Full Text Available Cancer gene therapy is an active area of research relying upon the transfer and subsequent expression of a therapeutic transgene into tumor cells in order to provide for therapeutic selectivity. Noninvasive assessment of therapeutic response and correlation of the location, magnitude, and duration of transgene expression in vivo would be particularly useful in the development of cancer gene therapy protocols by facilitating optimization of gene transfer protocols, vector development, and prodrug dosing schedules. In this study, we developed an adenoviral vector containing both the therapeutic transgene yeast cytosine deaminase (yCD along with an optical reporter gene (luciferase. Following intratumoral injection of the vector into orthotopic 9L gliomas, anatomical and diffusion-weighted MR images were obtained over time in order to provide for quantitative assessment of overall therapeutic efficacy and spatial heterogeneity of cell kill, respectively. In addition, bioluminescence images were acquired to assess the duration and magnitude of gene expression. MR images revealed significant reduction in tumor growth rates associated with yCD/5-fluorocytosine (5FC gene therapy. Significant increases in mean tumor diffusion values were also observed during treatment with 5FC. Moreover, spatial heterogeneity in tumor diffusion changes were also observed revealing that diffusion magnetic resonance imaging could detect regional therapeutic effects due to the nonuniform delivery and/or expression of the therapeutic yCD transgene within the tumor mass. In addition, in vivo bioluminescence imaging detected luciferase gene expression, which was found to decrease over time during administration of the prodrug providing a noninvasive surrogate marker for monitoring gene expression. These results demonstrate the efficacy of the yCD/5FC strategy for the treatment of brain tumors and reveal the feasibility of using multimodality molecular and functional imaging

  8. Differential Regulation of Gene Expression of Alveolar Epithelial Cell Markers in Human Lung Adenocarcinoma-Derived A549 Clones

    Directory of Open Access Journals (Sweden)

    Hiroshi Kondo

    2015-01-01

    Full Text Available Stem cell therapy appears to be promising for restoring damaged or irreparable lung tissue. However, establishing a simple and reproducible protocol for preparing lung progenitor populations is difficult because the molecular basis for alveolar epithelial cell differentiation is not fully understood. We investigated an in vitro system to analyze the regulatory mechanisms of alveolus-specific gene expression using a human alveolar epithelial type II (ATII cell line, A549. After cloning A549 subpopulations, each clone was classified into five groups according to cell morphology and marker gene expression. Two clones (B7 and H12 were further analyzed. Under serum-free culture conditions, surfactant protein C (SPC, an ATII marker, was upregulated in both H12 and B7. Aquaporin 5 (AQP5, an ATI marker, was upregulated in H12 and significantly induced in B7. When the RAS/MAPK pathway was inhibited, SPC and thyroid transcription factor-1 (TTF-1 expression levels were enhanced. After treatment with dexamethasone (DEX, 8-bromoadenosine 3′5′-cyclic monophosphate (8-Br-cAMP, 3-isobutyl-1-methylxanthine (IBMX, and keratinocyte growth factor (KGF, surfactant protein B and TTF-1 expression levels were enhanced. We found that A549-derived clones have plasticity in gene expression of alveolar epithelial differentiation markers and could be useful in studying ATII maintenance and differentiation.

  9. Screening for interaction effects in gene expression data.

    Directory of Open Access Journals (Sweden)

    Peter J Castaldi

    Full Text Available Expression quantitative trait (eQTL studies are a powerful tool for identifying genetic variants that affect levels of messenger RNA. Since gene expression is controlled by a complex network of gene-regulating factors, one way to identify these factors is to search for interaction effects between genetic variants and mRNA levels of transcription factors (TFs and their respective target genes. However, identification of interaction effects in gene expression data pose a variety of methodological challenges, and it has become clear that such analyses should be conducted and interpreted with caution. Investigating the validity and interpretability of several interaction tests when screening for eQTL SNPs whose effect on the target gene expression is modified by the expression level of a transcription factor, we characterized two important methodological issues. First, we stress the scale-dependency of interaction effects and highlight that commonly applied transformation of gene expression data can induce or remove interactions, making interpretation of results more challenging. We then demonstrate that, in the setting of moderate to strong interaction effects on the order of what may be reasonably expected for eQTL studies, standard interaction screening can be biased due to heteroscedasticity induced by true interactions. Using simulation and real data analysis, we outline a set of reasonable minimum conditions and sample size requirements for reliable detection of variant-by-environment and variant-by-TF interactions using the heteroscedasticity consistent covariance-based approach.

  10. Anterior-posterior regionalized gene expression in the Ciona notochord.

    Science.gov (United States)

    Reeves, Wendy; Thayer, Rachel; Veeman, Michael

    2014-04-01

    In the simple ascidian chordate Ciona, the signaling pathways and gene regulatory networks giving rise to initial notochord induction are largely understood and the mechanisms of notochord morphogenesis are being systematically elucidated. The notochord has generally been thought of as a non-compartmentalized or regionalized organ that is not finely patterned at the level of gene expression. Quantitative imaging methods have recently shown, however, that notochord cell size, shape, and behavior vary consistently along the anterior-posterior (AP) axis. Here we screen candidate genes by whole mount in situ hybridization for potential AP asymmetry. We identify 4 genes that show non-uniform expression in the notochord. Ezrin/radixin/moesin (ERM) is expressed more strongly in the secondary notochord lineage than the primary. CTGF is expressed stochastically in a subset of notochord cells. A novel calmodulin-like gene (BCamL) is expressed more strongly at both the anterior and posterior tips of the notochord. A TGF-β ortholog is expressed in a gradient from posterior to anterior. The asymmetries in ERM, BCamL, and TGF-β expression are evident even before the notochord cells have intercalated into a single-file column. We conclude that the Ciona notochord is not a homogeneous tissue but instead shows distinct patterns of regionalized gene expression. Copyright © 2013 Wiley Periodicals, Inc.

  11. Changes in gene expression following androgen receptor blockade ...

    Indian Academy of Sciences (India)

    Madhu urs

    of gene expression in the ventral prostate, it is not clear whether all the gene expression ... These include clusterin, methionine adenosyl transferase IIα, and prostate-specific ..... MAGEE1 melanoma antigen and no similarity was found with the ...

  12. Expression and clinical significance of Pax6 gene in retinoblastoma

    Directory of Open Access Journals (Sweden)

    Hai-Dong Huang

    2013-07-01

    Full Text Available AIM: To discuss the expression and clinical significance of Pax6 gene in retinoblastoma(Rb. METHODS: Totally 15 cases of fresh Rb organizations were selected as observation group and 15 normal retinal organizations as control group. Western-Blot and reverse transcriptase polymerase chain reaction(RT-PCRmethods were used to detect Pax6 protein and Pax6 mRNA expressions of the normal retina organizations and Rb organizations. At the same time, Western Blot method was used to detect the Pax6 gene downstream MATH5 and BRN3b differentiation gene protein level expression. After the comparison between two groups, the expression and clinical significance of Pax6 gene in Rb were discussed. RESULTS: In the observation group, average value of mRNA expression of Pax6 gene was 0.99±0.03; average value of Pax6 gene protein expression was 2.07±0.15; average value of BRN3b protein expression was 0.195±0.016; average value of MATH5 protein expression was 0.190±0.031. They were significantly higher than the control group, and the differences were statistically significant(PCONCLUSION: Abnormal expression of Pax6 gene is likely to accelerate the occurrence of Rb.

  13. Gene expression, cellular localisation and function of glutamine synthetase isozymes in wheat (Triticum aestivum L.)

    DEFF Research Database (Denmark)

    Bernard, Stéphanie M.; Møller, Anders Laurell Blom; Dionisio, Giuseppe

    2008-01-01

    ). Phylogenetic analysis showed that the wheat GS sub-families together with the GS genes from other monocotyledonous species form four distinct clades. Immunolocalisation studies in leaves, stems and rachis in plants at flowering showed GS protein to be present in parenchyma, phloem companion and perifascicular......We present the first cloning and study of glutamine synthetase (GS) genes in wheat (Triticum aestivum L.). Based on sequence analysis, phylogenetic studies and mapping data, ten GS sequences were classified into four sub-families: GS2 (a, b and c), GS1 (a, b and c), GSr (1 and 2) and GSe (1 and 2...... sheath cells. In situ localisation confirmed that GS1 transcripts were present in the perifascicular sheath cells whilst those for GSr were confined to the vascular cells. Studies of the expression and protein profiles showed that all GS sub-families were differentially expressed in the leaves, peduncle...

  14. Lung cancer gene expression database analysis incorporating prior knowledge with support vector machine-based classification method

    Directory of Open Access Journals (Sweden)

    Huang Desheng

    2009-07-01

    Full Text Available Abstract Background A reliable and precise classification is essential for successful diagnosis and treatment of cancer. Gene expression microarrays have provided the high-throughput platform to discover genomic biomarkers for cancer diagnosis and prognosis. Rational use of the available bioinformation can not only effectively remove or suppress noise in gene chips, but also avoid one-sided results of separate experiment. However, only some studies have been aware of the importance of prior information in cancer classification. Methods Together with the application of support vector machine as the discriminant approach, we proposed one modified method that incorporated prior knowledge into cancer classification based on gene expression data to improve accuracy. A public well-known dataset, Malignant pleural mesothelioma and lung adenocarcinoma gene expression database, was used in this study. Prior knowledge is viewed here as a means of directing the classifier using known lung adenocarcinoma related genes. The procedures were performed by software R 2.80. Results The modified method performed better after incorporating prior knowledge. Accuracy of the modified method improved from 98.86% to 100% in training set and from 98.51% to 99.06% in test set. The standard deviations of the modified method decreased from 0.26% to 0 in training set and from 3.04% to 2.10% in test set. Conclusion The method that incorporates prior knowledge into discriminant analysis could effectively improve the capacity and reduce the impact of noise. This idea may have good future not only in practice but also in methodology.

  15. Observation of intermittency in gene expression on cDNA microarrays

    CERN Document Server

    Peterson, L E

    2002-01-01

    We used scaled factorial moments to search for intermittency in the log expression ratios (LERs) for thousands of genes spotted on cDNA microarrays (gene chips). Results indicate varying levels of intermittency in gene expression. The observation of intermittency in the data analyzed provides a complimentary handle on moderately expressed genes, generally not tackled by conventional techniques.

  16. Gene expression during testis development in Duroc boars

    DEFF Research Database (Denmark)

    Lervik, Siri; Kristoffersen, Anja Bråthen; Conley, Lene

    2015-01-01

    . Nine clusters of genes with significant differential expression over time and 49 functional charts were found in the analysed testis samples. Prominent pathways in the prepubertal testis were associated with tissue renewal, cell respiration and increased endocytocis. E-cadherines may be associated...... with the onset of pubertal development. With elevated steroidogenesis (weeks 16 to 27), there was an increase in the expression of genes in the MAPK pathway, STAR and its analogue STARD6. A pubertal shift in genes coding for cellular cholesterol transport was observed. Increased expression of meiotic pathways...

  17. Equivalent Gene Expression Profiles between Glatopa™ and Copaxone®.

    Directory of Open Access Journals (Sweden)

    Josephine S D'Alessandro

    Full Text Available Glatopa™ is a generic glatiramer acetate recently approved for the treatment of patients with relapsing forms of multiple sclerosis. Gene expression profiling was performed as a means to evaluate equivalence of Glatopa and Copaxone®. Microarray analysis containing 39,429 unique probes across the entire genome was performed in murine glatiramer acetate--responsive Th2-polarized T cells, a test system highly relevant to the biology of glatiramer acetate. A closely related but nonequivalent glatiramoid molecule was used as a control to establish assay sensitivity. Multiple probe-level (Student's t-test and sample-level (principal component analysis, multidimensional scaling, and hierarchical clustering statistical analyses were utilized to look for differences in gene expression induced by the test articles. The analyses were conducted across all genes measured, as well as across a subset of genes that were shown to be modulated by Copaxone. The following observations were made across multiple statistical analyses: the expression of numerous genes was significantly changed by treatment with Copaxone when compared against media-only control; gene expression profiles induced by Copaxone and Glatopa were not significantly different; and gene expression profiles induced by Copaxone and the nonequivalent glatiramoid were significantly different, underscoring the sensitivity of the test system and the multiple analysis methods. Comparative analysis was also performed on sets of transcripts relevant to T-cell biology and antigen presentation, among others that are known to be modulated by glatiramer acetate. No statistically significant differences were observed between Copaxone and Glatopa in the expression levels (magnitude and direction of these glatiramer acetate-regulated genes. In conclusion, multiple methods consistently supported equivalent gene expression profiles between Copaxone and Glatopa.

  18. Using RNA-Seq data to select refence genes for normalizing gene expression in apple roots

    Science.gov (United States)

    Gene expression in apple roots in response to various stress conditions is a less-explored research subject. Reliable reference genes for normalizing quantitative gene expression data have not been carefully investigated. In this study, the suitability of a set of 15 apple genes were evaluated for t...

  19. Comparative gene expression of intestinal metabolizing enzymes.

    Science.gov (United States)

    Shin, Ho-Chul; Kim, Hye-Ryoung; Cho, Hee-Jung; Yi, Hee; Cho, Soo-Min; Lee, Dong-Goo; Abd El-Aty, A M; Kim, Jin-Suk; Sun, Duxin; Amidon, Gordon L

    2009-11-01

    The purpose of this study was to compare the expression profiles of drug-metabolizing enzymes in the intestine of mouse, rat and human. Total RNA was isolated from the duodenum and the mRNA expression was measured using Affymetrix GeneChip oligonucleotide arrays. Detected genes from the intestine of mouse, rat and human were ca. 60% of 22690 sequences, 40% of 8739 and 47% of 12559, respectively. Total genes of metabolizing enzymes subjected in this study were 95, 33 and 68 genes in mouse, rat and human, respectively. Of phase I enzymes, the mouse exhibited abundant gene expressions for Cyp3a25, Cyp4v3, Cyp2d26, followed by Cyp2b20, Cyp2c65 and Cyp4f14, whereas, the rat showed higher expression profiles of Cyp3a9, Cyp2b19, Cyp4f1, Cyp17a1, Cyp2d18, Cyp27a1 and Cyp4f6. However, the highly expressed P450 enzymes were CYP3A4, CYP3A5, CYP4F3, CYP2C18, CYP2C9, CYP2D6, CYP3A7, CYP11B1 and CYP2B6 in the human. For phase II enzymes, glucuronosyltransferase Ugt1a6, glutathione S-transferases Gstp1, Gstm3 and Gsta2, sulfotransferase Sult1b1 and acyltransferase Dgat1 were highly expressed in the mouse. The rat revealed predominant expression of glucuronosyltransferases Ugt1a1 and Ugt1a7, sulfotransferase Sult1b1, acetyltransferase Dlat and acyltransferase Dgat1. On the other hand, in human, glucuronosyltransferases UGT2B15 and UGT2B17, glutathione S-transferases MGST3, GSTP1, GSTA2 and GSTM4, sulfotransferases ST1A3 and SULT1A2, acetyltransferases SAT1 and CRAT, and acyltransferase AGPAT2 were dominantly detected. Therefore, current data indicated substantial interspecies differences in the pattern of intestinal gene expression both for P450 enzymes and phase II drug-metabolizing enzymes. This genomic database is expected to improve our understanding of interspecies variations in estimating intestinal prehepatic clearance of oral drugs.

  20. Identification of Anhydrobiosis-related Genes from an Expressed Sequence Tag Database in the Cryptobiotic Midge Polypedilum vanderplanki (Diptera; Chironomidae)*

    Science.gov (United States)

    Cornette, Richard; Kanamori, Yasushi; Watanabe, Masahiko; Nakahara, Yuichi; Gusev, Oleg; Mitsumasu, Kanako; Kadono-Okuda, Keiko; Shimomura, Michihiko; Mita, Kazuei; Kikawada, Takahiro; Okuda, Takashi

    2010-01-01

    Some organisms are able to survive the loss of almost all their body water content, entering a latent state known as anhydrobiosis. The sleeping chironomid (Polypedilum vanderplanki) lives in the semi-arid regions of Africa, and its larvae can survive desiccation in an anhydrobiotic form during the dry season. To unveil the molecular mechanisms of this resistance to desiccation, an anhydrobiosis-related Expressed Sequence Tag (EST) database was obtained from the sequences of three cDNA libraries constructed from P. vanderplanki larvae after 0, 12, and 36 h of desiccation. The database contained 15,056 ESTs distributed into 4,807 UniGene clusters. ESTs were classified according to gene ontology categories, and putative expression patterns were deduced for all clusters on the basis of the number of clones in each library; expression patterns were confirmed by real-time PCR for selected genes. Among up-regulated genes, antioxidants, late embryogenesis abundant (LEA) proteins, and heat shock proteins (Hsps) were identified as important groups for anhydrobiosis. Genes related to trehalose metabolism and various transporters were also strongly induced by desiccation. Those results suggest that the oxidative stress response plays a central role in successful anhydrobiosis. Similarly, protein denaturation and aggregation may be prevented by marked up-regulation of Hsps and the anhydrobiosis-specific LEA proteins. A third major feature is the predicted increase in trehalose synthesis and in the expression of various transporter proteins allowing the distribution of trehalose and other solutes to all tissues. PMID:20833722

  1. A role for gene duplication and natural variation of gene expression in the evolution of metabolism.

    Directory of Open Access Journals (Sweden)

    Daniel J Kliebenstein

    Full Text Available BACKGROUND: Most eukaryotic genomes have undergone whole genome duplications during their evolutionary history. Recent studies have shown that the function of these duplicated genes can diverge from the ancestral gene via neo- or sub-functionalization within single genotypes. An additional possibility is that gene duplicates may also undergo partitioning of function among different genotypes of a species leading to genetic differentiation. Finally, the ability of gene duplicates to diverge may be limited by their biological function. METHODOLOGY/PRINCIPAL FINDINGS: To test these hypotheses, I estimated the impact of gene duplication and metabolic function upon intraspecific gene expression variation of segmental and tandem duplicated genes within Arabidopsis thaliana. In all instances, the younger tandem duplicated genes showed higher intraspecific gene expression variation than the average Arabidopsis gene. Surprisingly, the older segmental duplicates also showed evidence of elevated intraspecific gene expression variation albeit typically lower than for the tandem duplicates. The specific biological function of the gene as defined by metabolic pathway also modulated the level of intraspecific gene expression variation. The major energy metabolism and biosynthetic pathways showed decreased variation, suggesting that they are constrained in their ability to accumulate gene expression variation. In contrast, a major herbivory defense pathway showed significantly elevated intraspecific variation suggesting that it may be under pressure to maintain and/or generate diversity in response to fluctuating insect herbivory pressures. CONCLUSION: These data show that intraspecific variation in gene expression is facilitated by an interaction of gene duplication and biological activity. Further, this plays a role in controlling diversity of plant metabolism.

  2. Gene expression studies of reference genes for quantitative real-time PCR: an overview in insects.

    Science.gov (United States)

    Shakeel, Muhammad; Rodriguez, Alicia; Tahir, Urfa Bin; Jin, Fengliang

    2018-02-01

    Whenever gene expression is being examined, it is essential that a normalization process is carried out to eliminate non-biological variations. The use of reference genes, such as glyceraldehyde-3-phosphate dehydrogenase, actin, and ribosomal protein genes, is the usual method of choice for normalizing gene expression. Although reference genes are used to normalize target gene expression, a major problem is that the stability of these genes differs among tissues, developmental stages, species, and responses to abiotic factors. Therefore, the use and validation of multiple reference genes are required. This review discusses the reasons that why RT-qPCR has become the preferred method for validating results of gene expression profiles, the use of specific and non-specific dyes and the importance of use of primers and probes for qPCR as well as to discuss several statistical algorithms developed to help the validation of potential reference genes. The conflicts arising in the use of classical reference genes in gene normalization and their replacement with novel references are also discussed by citing the high stability and low stability of classical and novel reference genes under various biotic and abiotic experimental conditions by employing various methods applied for the reference genes amplification.

  3. Application of biclustering of gene expression data and gene set enrichment analysis methods to identify potentially disease causing nanomaterials

    Directory of Open Access Journals (Sweden)

    Andrew Williams

    2015-12-01

    Full Text Available Background: The presence of diverse types of nanomaterials (NMs in commerce is growing at an exponential pace. As a result, human exposure to these materials in the environment is inevitable, necessitating the need for rapid and reliable toxicity testing methods to accurately assess the potential hazards associated with NMs. In this study, we applied biclustering and gene set enrichment analysis methods to derive essential features of altered lung transcriptome following exposure to NMs that are associated with lung-specific diseases. Several datasets from public microarray repositories describing pulmonary diseases in mouse models following exposure to a variety of substances were examined and functionally related biclusters of genes showing similar expression profiles were identified. The identified biclusters were then used to conduct a gene set enrichment analysis on pulmonary gene expression profiles derived from mice exposed to nano-titanium dioxide (nano-TiO2, carbon black (CB or carbon nanotubes (CNTs to determine the disease significance of these data-driven gene sets.Results: Biclusters representing inflammation (chemokine activity, DNA binding, cell cycle, apoptosis, reactive oxygen species (ROS and fibrosis processes were identified. All of the NM studies were significant with respect to the bicluster related to chemokine activity (DAVID; FDR p-value = 0.032. The bicluster related to pulmonary fibrosis was enriched in studies where toxicity induced by CNT and CB studies was investigated, suggesting the potential for these materials to induce lung fibrosis. The pro-fibrogenic potential of CNTs is well established. Although CB has not been shown to induce fibrosis, it induces stronger inflammatory, oxidative stress and DNA damage responses than nano-TiO2 particles.Conclusion: The results of the analysis correctly identified all NMs to be inflammogenic and only CB and CNTs as potentially fibrogenic. In addition to identifying several

  4. GOBO: gene expression-based outcome for breast cancer online.

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    Markus Ringnér

    Full Text Available Microarray-based gene expression analysis holds promise of improving prognostication and treatment decisions for breast cancer patients. However, the heterogeneity of breast cancer emphasizes the need for validation of prognostic gene signatures in larger sample sets stratified into relevant subgroups. Here, we describe a multifunctional user-friendly online tool, GOBO (http://co.bmc.lu.se/gobo, allowing a range of different analyses to be performed in an 1881-sample breast tumor data set, and a 51-sample breast cancer cell line set, both generated on Affymetrix U133A microarrays. GOBO supports a wide range of applications including: 1 rapid assessment of gene expression levels in subgroups of breast tumors and cell lines, 2 identification of co-expressed genes for creation of potential metagenes, 3 association with outcome for gene expression levels of single genes, sets of genes, or gene signatures in multiple subgroups of the 1881-sample breast cancer data set. The design and implementation of GOBO facilitate easy incorporation of additional query functions and applications, as well as additional data sets irrespective of tumor type and array platform.

  5. Using Next-Generation Sequencing to Detect Differential Expression Genes in Bradysia odoriphaga after Exposure to Insecticides

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    Haoliang Chen

    2017-11-01

    Full Text Available Bradysia odoriphaga (Diptera: Sciaridae is the most important pest of Chinese chive. Insecticides are used widely and frequently to control B. odoriphaga in China. However, the performance of the insecticides chlorpyrifos and clothianidin in controlling the Chinese chive maggot is quite different. Using next generation sequencing technology, different expression unigenes (DEUs in B. odoriphaga were detected after treatment with chlorpyrifos and clothianidin for 6 and 48 h in comparison with control. The number of DEUs ranged between 703 and 1161 after insecticide treatment. In these DEUs, 370–863 unigenes can be classified into 41–46 categories of gene ontology (GO, and 354–658 DEUs can be mapped into 987–1623 Kyoto Encyclopedia of Genes and Genomes (KEGG pathways. The expressions of DEUs related to insecticide-metabolism-related genes were analyzed. The cytochrome P450-like unigene group was the largest group in DEUs. Most glutathione S-transferase-like unigenes were down-regulated and most sodium channel-like unigenes were up-regulated after insecticide treatment. Finally, 14 insecticide-metabolism-related unigenes were chosen to confirm the relative expression in each treatment by quantitative Real Time Polymerase Chain Reaction (qRT-PCR. The results of qRT-PCR and RNA Sequencing (RNA-Seq are fairly well-established. Our results demonstrate that a next-generation sequencing tool facilitates the identification of insecticide-metabolism-related genes and the illustration of the insecticide mechanisms of chlorpyrifos and clothianidin.

  6. Regulation of mitochondrial gene expression, the epigenetic enigma

    NARCIS (Netherlands)

    Mposhi, Archibold; van der Wijst, Monique G. P.; Faber, Klaas Nico; Rots, Marianne G.

    2017-01-01

    Epigenetics provides an important layer of information on top of the DNA sequence and is essential for establishing gene expression profiles. Extensive studies have shown that nuclear DNA methylation and histone modifications influence nuclear gene expression. However, it remains unclear whether

  7. Ebola virus infection induces irregular dendritic cell gene expression.

    Science.gov (United States)

    Melanson, Vanessa R; Kalina, Warren V; Williams, Priscilla

    2015-02-01

    Filoviruses subvert the human immune system in part by infecting and replicating in dendritic cells (DCs). Using gene arrays, a phenotypic profile of filovirus infection in human monocyte-derived DCs was assessed. Monocytes from human donors were cultured in GM-CSF and IL-4 and were infected with Ebola virus Kikwit variant for up to 48 h. Extracted DC RNA was analyzed on SuperArray's Dendritic and Antigen Presenting Cell Oligo GEArray and compared to uninfected controls. Infected DCs exhibited increased expression of cytokine, chemokine, antiviral, and anti-apoptotic genes not seen in uninfected controls. Significant increases of intracellular antiviral and MHC I and II genes were also noted in EBOV-infected DCs. However, infected DCs failed to show any significant difference in co-stimulatory T-cell gene expression from uninfected DCs. Moreover, several chemokine genes were activated, but there was sparse expression of chemokine receptors that enabled activated DCs to home to lymph nodes. Overall, statistically significant expression of several intracellular antiviral genes was noted, which may limit viral load but fails to stop replication. EBOV gene expression profiling is of vital importance in understanding pathogenesis and devising novel therapeutic treatments such as small-molecule inhibitors.

  8. Distinct iris gene expression profiles of primary angle closure glaucoma and primary open angle glaucoma and their interaction with ocular biometric parameters.

    Science.gov (United States)

    Seet, Li-Fong; Narayanaswamy, Arun; Finger, Sharon N; Htoon, Hla M; Nongpiur, Monisha E; Toh, Li Zhen; Ho, Henrietta; Perera, Shamira A; Wong, Tina T

    2016-11-01

    This study aimed to evaluate differences in iris gene expression profiles between primary angle closure glaucoma (PACG) and primary open angle glaucoma (POAG) and their interaction with biometric characteristics. Prospective study. Thirty-five subjects with PACG and thirty-three subjects with POAG who required trabeculectomy were enrolled at the Singapore National Eye Centre, Singapore. Iris specimens, obtained by iridectomy, were analysed by real-time polymerase chain reaction for expression of type I collagen, vascular endothelial growth factor (VEGF)-A, -B and -C, as well as VEGF receptors (VEGFRs) 1 and 2. Anterior segment optical coherence tomography (ASOCT) imaging for biometric parameters, including anterior chamber depth (ACD), anterior chamber volume (ACV) and lens vault (LV), was also performed pre-operatively. Relative mRNA levels between PACG and POAG irises, biometric measurements, discriminant analyses using genes and biometric parameters. COL1A1, VEGFB, VEGFC and VEGFR2 mRNA expression was higher in PACG compared to POAG irises. LV, ACD and ACV were significantly different between the two subgroups. Discriminant analyses based on gene expression, biometric parameters or a combination of both gene expression and biometrics (LV and ACV), correctly classified 94.1%, 85.3% and 94.1% of the original PACG and POAG cases, respectively. The discriminant function combining genes and biometrics demonstrated the highest accuracy in cross-validated classification of the two glaucoma subtypes. Distinct iris gene expression supports the pathophysiological differences that exist between PACG and POAG. Biometric parameters can combine with iris gene expression to more accurately define PACG from POAG. © 2016 The Authors. Clinical & Experimental Ophthalmology published by John Wiley & Sons Australia, Ltd on behalf of Royal Australian and New Zealand College of Ophthalmologists.

  9. Multiclass classification for skin cancer profiling based on the integration of heterogeneous gene expression series.

    Science.gov (United States)

    Gálvez, Juan Manuel; Castillo, Daniel; Herrera, Luis Javier; San Román, Belén; Valenzuela, Olga; Ortuño, Francisco Manuel; Rojas, Ignacio

    2018-01-01

    Most of the research studies developed applying microarray technology to the characterization of different pathological states of any disease may fail in reaching statistically significant results. This is largely due to the small repertoire of analysed samples, and to the limitation in the number of states or pathologies usually addressed. Moreover, the influence of potential deviations on the gene expression quantification is usually disregarded. In spite of the continuous changes in omic sciences, reflected for instance in the emergence of new Next-Generation Sequencing-related technologies, the existing availability of a vast amount of gene expression microarray datasets should be properly exploited. Therefore, this work proposes a novel methodological approach involving the integration of several heterogeneous skin cancer series, and a later multiclass classifier design. This approach is thus a way to provide the clinicians with an intelligent diagnosis support tool based on the use of a robust set of selected biomarkers, which simultaneously distinguishes among different cancer-related skin states. To achieve this, a multi-platform combination of microarray datasets from Affymetrix and Illumina manufacturers was carried out. This integration is expected to strengthen the statistical robustness of the study as well as the finding of highly-reliable skin cancer biomarkers. Specifically, the designed operation pipeline has allowed the identification of a small subset of 17 differentially expressed genes (DEGs) from which to distinguish among 7 involved skin states. These genes were obtained from the assessment of a number of potential batch effects on the gene expression data. The biological interpretation of these genes was inspected in the specific literature to understand their underlying information in relation to skin cancer. Finally, in order to assess their possible effectiveness in cancer diagnosis, a cross-validation Support Vector Machines (SVM

  10. Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data

    Directory of Open Access Journals (Sweden)

    Cheung Leo

    2007-02-01

    Bayesian inferences. Simulation studies showed that, even without any knowledge of the underlying generative model, the KIGP performed very close to the theoretical Bayesian bound not only in the case with a linear Bayesian classifier but also in the case with a very non-linear Bayesian classifier. This sheds light on its broader usability to microarray data analysis problems, especially to those that linear methods work awkwardly. The KIGP was also applied to four published microarray datasets, and the results showed that the KIGP performed better than or at least as well as any of the referred state-of-the-art methods did in all of these cases. Conclusion Mathematically built on the kernel-induced feature space concept under a Bayesian framework, the KIGP method presented in this paper provides a unified machine learning approach to explore both the linear and the possibly non-linear underlying relationship between the target features of a given binary disease classification problem and the related explanatory gene expression data. More importantly, it incorporates the model parameter tuning into the framework. The model selection problem is addressed in the form of selecting a proper kernel type. The KIGP method also gives Bayesian probabilistic predictions for disease classification. These properties and features are beneficial to most real-world applications. The algorithm is naturally robust in numerical computation. The simulation studies and the published data studies demonstrated that the proposed KIGP performs satisfactorily and consistently.

  11. Xylella fastidiosa gene expression analysis by DNA microarrays

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    Regiane F. Travensolo

    2009-01-01

    Full Text Available Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM2 and liquid BCYE. All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others. The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants.

  12. Clinicopathologic and gene expression parameters predict liver cancer prognosis

    International Nuclear Information System (INIS)

    Hao, Ke; Zhong, Hua; Greenawalt, Danielle; Ferguson, Mark D; Ng, Irene O; Sham, Pak C; Poon, Ronnie T; Molony, Cliona; Schadt, Eric E; Dai, Hongyue; Luk, John M; Lamb, John; Zhang, Chunsheng; Xie, Tao; Wang, Kai; Zhang, Bin; Chudin, Eugene; Lee, Nikki P; Mao, Mao

    2011-01-01

    The prognosis of hepatocellular carcinoma (HCC) varies following surgical resection and the large variation remains largely unexplained. Studies have revealed the ability of clinicopathologic parameters and gene expression to predict HCC prognosis. However, there has been little systematic effort to compare the performance of these two types of predictors or combine them in a comprehensive model. Tumor and adjacent non-tumor liver tissues were collected from 272 ethnic Chinese HCC patients who received curative surgery. We combined clinicopathologic parameters and gene expression data (from both tissue types) in predicting HCC prognosis. Cross-validation and independent studies were employed to assess prediction. HCC prognosis was significantly associated with six clinicopathologic parameters, which can partition the patients into good- and poor-prognosis groups. Within each group, gene expression data further divide patients into distinct prognostic subgroups. Our predictive genes significantly overlap with previously published gene sets predictive of prognosis. Moreover, the predictive genes were enriched for genes that underwent normal-to-tumor gene network transformation. Previously documented liver eSNPs underlying the HCC predictive gene signatures were enriched for SNPs that associated with HCC prognosis, providing support that these genes are involved in key processes of tumorigenesis. When applied individually, clinicopathologic parameters and gene expression offered similar predictive power for HCC prognosis. In contrast, a combination of the two types of data dramatically improved the power to predict HCC prognosis. Our results also provided a framework for understanding the impact of gene expression on the processes of tumorigenesis and clinical outcome

  13. Gene expression and adaptive noncoding changes during human evolution.

    Science.gov (United States)

    Babbitt, Courtney C; Haygood, Ralph; Nielsen, William J; Wray, Gregory A

    2017-06-05

    Despite evidence for adaptive changes in both gene expression and non-protein-coding, putatively regulatory regions of the genome during human evolution, the relationship between gene expression and adaptive changes in cis-regulatory regions remains unclear. Here we present new measurements of gene expression in five tissues of humans and chimpanzees, and use them to assess this relationship. We then compare our results with previous studies of adaptive noncoding changes, analyzing correlations at the level of gene ontology groups, in order to gain statistical power to detect correlations. Consistent with previous studies, we find little correlation between gene expression and adaptive noncoding changes at the level of individual genes; however, we do find significant correlations at the level of biological function ontology groups. The types of function include processes regulated by specific transcription factors, responses to genetic or chemical perturbations, and differentiation of cell types within the immune system. Among functional categories co-enriched with both differential expression and noncoding adaptation, prominent themes include cancer, particularly epithelial cancers, and neural development and function.

  14. The product of the ABC half-transporter gene ABCG2 (BCRP/MXR/ABCP) is expressed in the plasma membrane

    DEFF Research Database (Denmark)

    Rocchi, E; Khodjakov, A; Volk, E L

    2000-01-01

    by Western blot and immunohistochemistry. This protein is highly overexpressed in several drug-resistant cell lines and localizes predominantly to the plasma membrane, instead of to intracellular membranes as seen with all other known half-transporters. Therefore, BCRP/MXR is unique among the ABC half......The products of the ABC gene family can be generally classified as either full-transporters of half-transporters. Full-transporters are expressed in the plasma membrane, whereas half-transporters are usually found in intracellular membranes. Recently, an ABC half-transporter, the ABCG2 gene product......-transporters by being localized to the plasma membrane....

  15. Real-time PCR expression profiling of genes encoding potential virulence factors in Candida albicans biofilms: identification of model-dependent and -independent gene expression

    Directory of Open Access Journals (Sweden)

    Řičicová Markéta

    2010-04-01

    Full Text Available Abstract Background Candida albicans infections are often associated with biofilm formation. Previous work demonstrated that the expression of HWP1 (hyphal wall protein and of genes belonging to the ALS (agglutinin-like sequence, SAP (secreted aspartyl protease, PLB (phospholipase B and LIP (lipase gene families is associated with biofilm growth on mucosal surfaces. We investigated using real-time PCR whether genes encoding potential virulence factors are also highly expressed in biofilms associated with abiotic surfaces. For this, C. albicans biofilms were grown on silicone in microtiter plates (MTP or in the Centres for Disease Control (CDC reactor, on polyurethane in an in vivo subcutaneous catheter rat (SCR model, and on mucosal surfaces in the reconstituted human epithelium (RHE model. Results HWP1 and genes belonging to the ALS, SAP, PLB and LIP gene families were constitutively expressed in C. albicans biofilms. ALS1-5 were upregulated in all model systems, while ALS9 was mostly downregulated. ALS6 and HWP1 were overexpressed in all models except in the RHE and MTP, respectively. The expression levels of SAP1 were more pronounced in both in vitro models, while those of SAP2, SAP4 and SAP6 were higher in the in vivo model. Furthermore, SAP5 was highly upregulated in the in vivo and RHE models. For SAP9 and SAP10 similar gene expression levels were observed in all model systems. PLB genes were not considerably upregulated in biofilms, while LIP1-3, LIP5-7 and LIP9-10 were highly overexpressed in both in vitro models. Furthermore, an elevated lipase activity was detected in supernatans of biofilms grown in the MTP and RHE model. Conclusions Our findings show that HWP1 and most of the genes belonging to the ALS, SAP and LIP gene families are upregulated in C. albicans biofilms. Comparison of the fold expression between the various model systems revealed similar expression levels for some genes, while for others model-dependent expression

  16. Gene expression profiling of placentas affected by pre-eclampsia

    DEFF Research Database (Denmark)

    Hoegh, Anne Mette; Borup, Rehannah; Nielsen, Finn Cilius

    2010-01-01

    Several studies point to the placenta as the primary cause of pre-eclampsia. Our objective was to identify placental genes that may contribute to the development of pre-eclampsia. RNA was purified from tissue biopsies from eleven pre-eclamptic placentas and eighteen normal controls. Messenger RNA...... expression from pooled samples was analysed by microarrays. Verification of the expression of selected genes was performed using real-time PCR. A surprisingly low number of genes (21 out of 15,000) were identified as differentially expressed. Among these were genes not previously associated with pre-eclampsia...... as bradykinin B1 receptor and a 14-3-3 protein, but also genes that have already been connected with pre-eclampsia, for example, inhibin beta A subunit and leptin. A low number of genes were repeatedly identified as differentially expressed, because they may represent the endpoint of a cascade of events...

  17. Over-expression of Eph and ephrin genes in advanced ovarian cancer: ephrin gene expression correlates with shortened survival

    Directory of Open Access Journals (Sweden)

    Lincoln Douglas

    2006-06-01

    Full Text Available Abstract Background Increased expression of Eph receptor tyrosine kinases and their ephrin ligands has been implicated in tumor progression in a number of malignancies. This report describes aberrant expression of these genes in ovarian cancer, the commonest cause of death amongst gynaecological malignancies. Methods Eph and ephrin expression was determined using quantitative real time RT-PCR. Correlation of gene expression was measured using Spearman's rho statistic. Survival was analysed using log-rank analysis and (was visualised by Kaplan-Meier survival curves. Results Greater than 10 fold over-expression of EphA1 and a more modest over-expression of EphA2 were observed in partially overlapping subsets of tumors. Over-expression of EphA1 strongly correlated (r = 0.801; p Conclusion These data imply that increased levels of ephrins A1 and A5 in the presence of high expression of Ephs A1 and A2 lead to a more aggressive tumor phenotype. The known functions of Eph/ephrin signalling in cell de-adhesion and movement may explain the observed correlation of ephrin expression with poor prognosis.

  18. Functional clustering of time series gene expression data by Granger causality

    Science.gov (United States)

    2012-01-01

    Background A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them. PMID:23107425

  19. Gene duplication, tissue-specific gene expression and sexual conflict in stalk-eyed flies (Diopsidae).

    Science.gov (United States)

    Baker, Richard H; Narechania, Apurva; Johns, Philip M; Wilkinson, Gerald S

    2012-08-19

    Gene duplication provides an essential source of novel genetic material to facilitate rapid morphological evolution. Traits involved in reproduction and sexual dimorphism represent some of the fastest evolving traits in nature, and gene duplication is intricately involved in the origin and evolution of these traits. Here, we review genomic research on stalk-eyed flies (Diopsidae) that has been used to examine the extent of gene duplication and its role in the genetic architecture of sexual dimorphism. Stalk-eyed flies are remarkable because of the elongation of the head into long stalks, with the eyes and antenna laterally displaced at the ends of these stalks. Many species are strongly sexually dimorphic for eyespan, and these flies have become a model system for studying sexual selection. Using both expressed sequence tag and next-generation sequencing, we have established an extensive database of gene expression in the developing eye-antennal imaginal disc, the adult head and testes. Duplicated genes exhibit narrower expression patterns than non-duplicated genes, and the testes, in particular, provide an abundant source of gene duplication. Within somatic tissue, duplicated genes are more likely to be differentially expressed between the sexes, suggesting gene duplication may provide a mechanism for resolving sexual conflict.

  20. Gene expression profiles reveal key genes for early diagnosis and treatment of adamantinomatous craniopharyngioma.

    Science.gov (United States)

    Yang, Jun; Hou, Ziming; Wang, Changjiang; Wang, Hao; Zhang, Hongbing

    2018-04-23

    Adamantinomatous craniopharyngioma (ACP) is an aggressive brain tumor that occurs predominantly in the pediatric population. Conventional diagnosis method and standard therapy cannot treat ACPs effectively. In this paper, we aimed to identify key genes for ACP early diagnosis and treatment. Datasets GSE94349 and GSE68015 were obtained from Gene Expression Omnibus database. Consensus clustering was applied to discover the gene clusters in the expression data of GSE94349 and functional enrichment analysis was performed on gene set in each cluster. The protein-protein interaction (PPI) network was built by the Search Tool for the Retrieval of Interacting Genes, and hubs were selected. Support vector machine (SVM) model was built based on the signature genes identified from enrichment analysis and PPI network. Dataset GSE94349 was used for training and testing, and GSE68015 was used for validation. Besides, RT-qPCR analysis was performed to analyze the expression of signature genes in ACP samples compared with normal controls. Seven gene clusters were discovered in the differentially expressed genes identified from GSE94349 dataset. Enrichment analysis of each cluster identified 25 pathways that highly associated with ACP. PPI network was built and 46 hubs were determined. Twenty-five pathway-related genes that overlapped with the hubs in PPI network were used as signatures to establish the SVM diagnosis model for ACP. The prediction accuracy of SVM model for training, testing, and validation data were 94, 85, and 74%, respectively. The expression of CDH1, CCL2, ITGA2, COL8A1, COL6A2, and COL6A3 were significantly upregulated in ACP tumor samples, while CAMK2A, RIMS1, NEFL, SYT1, and STX1A were significantly downregulated, which were consistent with the differentially expressed gene analysis. SVM model is a promising classification tool for screening and early diagnosis of ACP. The ACP-related pathways and signature genes will advance our knowledge of ACP pathogenesis

  1. Gastric Cancer Associated Genes Identified by an Integrative Analysis of Gene Expression Data

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    Bing Jiang

    2017-01-01

    Full Text Available Gastric cancer is one of the most severe complex diseases with high morbidity and mortality in the world. The molecular mechanisms and risk factors for this disease are still not clear since the cancer heterogeneity caused by different genetic and environmental factors. With more and more expression data accumulated nowadays, we can perform integrative analysis for these data to understand the complexity of gastric cancer and to identify consensus players for the heterogeneous cancer. In the present work, we screened the published gene expression data and analyzed them with integrative tool, combined with pathway and gene ontology enrichment investigation. We identified several consensus differentially expressed genes and these genes were further confirmed with literature mining; at last, two genes, that is, immunoglobulin J chain and C-X-C motif chemokine ligand 17, were screened as novel gastric cancer associated genes. Experimental validation is proposed to further confirm this finding.

  2. Monitoring expression profiles of rice (Oryza sativa L.) genes under abiotic stresses using cDNA Microarray Analysis (abstract)

    International Nuclear Information System (INIS)

    Rabbani, M.A.

    2005-01-01

    Transcript regulation in response to cold, drought, high salinity and ABA application was investigated in rice (Oryza sativa L., Nipponbare) with microarray analysis including approx. 1700 independent DNA elements derived from three cDNA libraries constructed from 15-day old rice seedlings stressed with drought, cold and high salinity. A total of 141 non-redundant genes were identified, whose expression ratios were more than three-fold compared with the control genes for at least one of stress treatments in microarray analysis. However, after RNA gel blot analysis, a total of 73 genes were identified, among them the transcripts of 36, 62, 57 and 43 genes were found increased after cold, drought, high salinity and ABA application, respectively. Sixteen of these identified genes have been reported previously to be stress inducible in rice, while 57 of which are novel that have not been reported earlier as stress responsive in rice. We observed a strong association in the expression patterns of stress responsive genes and found 15 stress inducible genes that responded to all four treatments. Based on Venn diagram analysis, 56 genes were induced by both drought and high salinity, whereas 22 genes were upregulated by both cold and high salinity stress. Similarly 43 genes were induced by both drought stress and ABA application, while only 17 genes were identified as cold and ABA inducible genes. These results indicated the existence of greater cross talk between drought, ABA and high salinity stress signaling processes than those between cold and ABA, and cold and high salinity stress signaling pathways. The cold, drought, high salinity and ABA inducible genes were classified into four gene groups from their expression profiles. Analysis of data enabled us to identify a number of promoters and possible cis-acting DNA elements of several genes induced by a variety of abiotic stresses by combining expression data with genomic sequence data of rice. Comparative analysis of

  3. GSMA: Gene Set Matrix Analysis, An Automated Method for Rapid Hypothesis Testing of Gene Expression Data

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    Chris Cheadle

    2007-01-01

    Full Text Available Background: Microarray technology has become highly valuable for identifying complex global changes in gene expression patterns. The assignment of functional information to these complex patterns remains a challenging task in effectively interpreting data and correlating results from across experiments, projects and laboratories. Methods which allow the rapid and robust evaluation of multiple functional hypotheses increase the power of individual researchers to data mine gene expression data more efficiently.Results: We have developed (gene set matrix analysis GSMA as a useful method for the rapid testing of group-wise up- or downregulation of gene expression simultaneously for multiple lists of genes (gene sets against entire distributions of gene expression changes (datasets for single or multiple experiments. The utility of GSMA lies in its flexibility to rapidly poll gene sets related by known biological function or as designated solely by the end-user against large numbers of datasets simultaneously.Conclusions: GSMA provides a simple and straightforward method for hypothesis testing in which genes are tested by groups across multiple datasets for patterns of expression enrichment.

  4. A Marfan syndrome gene expression phenotype in cultured skin fibroblasts

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    Emond Mary

    2007-09-01

    Full Text Available Abstract Background Marfan syndrome (MFS is a heritable connective tissue disorder caused by mutations in the fibrillin-1 gene. This syndrome constitutes a significant identifiable subtype of aortic aneurysmal disease, accounting for over 5% of ascending and thoracic aortic aneurysms. Results We used spotted membrane DNA macroarrays to identify genes whose altered expression levels may contribute to the phenotype of the disease. Our analysis of 4132 genes identified a subset with significant expression differences between skin fibroblast cultures from unaffected controls versus cultures from affected individuals with known fibrillin-1 mutations. Subsequently, 10 genes were chosen for validation by quantitative RT-PCR. Conclusion Differential expression of many of the validated genes was associated with MFS samples when an additional group of unaffected and MFS affected subjects were analyzed (p-value -6 under the null hypothesis that expression levels in cultured fibroblasts are unaffected by MFS status. An unexpected observation was the range of individual gene expression. In unaffected control subjects, expression ranges exceeding 10 fold were seen in many of the genes selected for qRT-PCR validation. The variation in expression in the MFS affected subjects was even greater.

  5. Estradiol-induced gene expression in largemouth bass (Micropterus salmoides)

    Science.gov (United States)

    Bowman, C.J.; Kroll, K.J.; Gross, T.G.; Denslow, N.D.

    2002-01-01

    Vitellogenin (Vtg) and estrogen receptor (ER) gene expression levels were measured in largemouth bass to evaluate the activation of the ER-mediated pathway by estradiol (E2). Single injections of E2 ranging from 0.0005 to 5 mg/kg up-regulated plasma Vtg in a dose-dependent manner. Vtg and ER mRNAs were measured using partial cDNA sequences corresponding to the C-terminal domain for Vtg and the ligand-binding domain of ER?? sequences. After acute E2-exposures (2 mg/kg), Vtg and ER mRNAs and plasma Vtg levels peaked after 2 days. The rate of ER mRNA accumulation peaked 36-42 h earlier than Vtg mRNA. The expression window for ER defines the primary response to E2 in largemouth bass and that for Vtg a delayed primary response. The specific effect of E2 on other estrogen-regulated genes was tested during these same time windows using differential display RT-PCR. Specific up-regulated genes that are expressed in the same time window as Vtg were ERp72 (a membrane-bound disulfide isomerase) and a gene with homology to an expressed gene identified in zebrafish. Genes that were expressed in a pattern that mimics the ER include the gene for zona radiata protein ZP2, and a gene with homology to an expressed gene found in winter flounder. One gene for fibrinogen ?? was down-regulated and an unidentified gene was transiently up-regulated after 12 h of exposure and returned to basal levels by 48 h. Taken together these studies indicate that the acute molecular response to E2 involves a complex network of responses over time. ?? 2002 Elsevier Science Ireland Ltd. All rights reserved.

  6. Population and sex differences in Drosophila melanogaster brain gene expression

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    Catalán Ana

    2012-11-01

    Full Text Available Abstract Background Changes in gene regulation are thought to be crucial for the adaptation of organisms to their environment. Transcriptome analyses can be used to identify candidate genes for ecological adaptation, but can be complicated by variation in gene expression between tissues, sexes, or individuals. Here we use high-throughput RNA sequencing of a single Drosophila melanogaster tissue to detect brain-specific differences in gene expression between the sexes and between two populations, one from the ancestral species range in sub-Saharan Africa and one from the recently colonized species range in Europe. Results Relatively few genes (Cyp6g1 and CHKov1. Conclusions Analysis of the brain transcriptome revealed many genes differing in expression between populations that were not detected in previous studies using whole flies. There was little evidence for sex-specific regulatory adaptation in the brain, as most expression differences between populations were observed in both males and females. The enrichment of genes with sexually dimorphic expression on the X chromosome is consistent with dosage compensation mechanisms affecting sex-biased expression in somatic tissues.

  7. Fungal and plant gene expression in arbuscular mycorrhizal symbiosis.

    Science.gov (United States)

    Balestrini, Raffaella; Lanfranco, Luisa

    2006-11-01

    Arbuscular mycorrhizas (AMs) are a unique example of symbiosis between two eukaryotes, soil fungi and plants. This association induces important physiological changes in each partner that lead to reciprocal benefits, mainly in nutrient supply. The symbiosis results from modifications in plant and fungal cell organization caused by specific changes in gene expression. Recently, much effort has gone into studying these gene expression patterns to identify a wider spectrum of genes involved. We aim in this review to describe AM symbiosis in terms of current knowledge on plant and fungal gene expression profiles.

  8. VESPUCCI: exploring patterns of gene expression in grapevine

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    Marco eMoretto

    2016-05-01

    Full Text Available Large-scale transcriptional studies aim to decipher the dynamic cellular responses to a stimulus, like different environmental conditions. In the era of high-throughput omics biology, the most used technologies for these purposes are microarray and RNA-Seq, whose data are usually required to be deposited in public repositories upon publication. Such repositories have the enormous potential to provide a comprehensive view of how different experimental conditions lead to expression changes, by comparing gene expression across all possible measured conditions. Unfortunately, this task is greatly impaired by differences among experimental platforms that make direct comparisons difficult.In this paper we present the Vitis Expression Studies Platform Using COLOMBOS Compendia Instances (VESPUCCI, a gene expression compendium for grapevine which was built by adapting an approach originally developed for bacteria, and show how it can be used to investigate complex gene expression patterns. We integrated nearly all publicly available microarray and RNA-Seq expression data: 1608 gene expression samples from 10 different technological platforms. Each sample has been manually annotated using a controlled vocabulary developed ad hoc to ensure both human readability and computational tractability. Expression data in the compendium can be visually explored using several tools provided by the web interface or can be programmatically accessed using the REST interface. VESPUCCI is freely accessible at http://vespucci.colombos.fmach.it.

  9. Gene expression profiling in autoimmune diseases

    DEFF Research Database (Denmark)

    Bovin, Lone Frier; Brynskov, Jørn; Hegedüs, Laszlo

    2007-01-01

    A central issue in autoimmune disease is whether the underlying inflammation is a repeated stereotypical process or whether disease specific gene expression is involved. To shed light on this, we analysed whether genes previously found to be differentially regulated in rheumatoid arthritis (RA...

  10. Large clusters of co-expressed genes in the Drosophila genome.

    Science.gov (United States)

    Boutanaev, Alexander M; Kalmykova, Alla I; Shevelyov, Yuri Y; Nurminsky, Dmitry I

    2002-12-12

    Clustering of co-expressed, non-homologous genes on chromosomes implies their co-regulation. In lower eukaryotes, co-expressed genes are often found in pairs. Clustering of genes that share aspects of transcriptional regulation has also been reported in higher eukaryotes. To advance our understanding of the mode of coordinated gene regulation in multicellular organisms, we performed a genome-wide analysis of the chromosomal distribution of co-expressed genes in Drosophila. We identified a total of 1,661 testes-specific genes, one-third of which are clustered on chromosomes. The number of clusters of three or more genes is much higher than expected by chance. We observed a similar trend for genes upregulated in the embryo and in the adult head, although the expression pattern of individual genes cannot be predicted on the basis of chromosomal position alone. Our data suggest that the prevalent mechanism of transcriptional co-regulation in higher eukaryotes operates with extensive chromatin domains that comprise multiple genes.

  11. Domestication rewired gene expression and nucleotide diversity patterns in tomato.

    Science.gov (United States)

    Sauvage, Christopher; Rau, Andrea; Aichholz, Charlotte; Chadoeuf, Joël; Sarah, Gautier; Ruiz, Manuel; Santoni, Sylvain; Causse, Mathilde; David, Jacques; Glémin, Sylvain

    2017-08-01

    Plant domestication has led to considerable phenotypic modifications from wild species to modern varieties. However, although changes in key traits have been well documented, less is known about the underlying molecular mechanisms, such as the reduction of molecular diversity or global gene co-expression patterns. In this study, we used a combination of gene expression and population genetics in wild and crop tomato to decipher the footprints of domestication. We found a set of 1729 differentially expressed genes (DEG) between the two genetic groups, belonging to 17 clusters of co-expressed DEG, suggesting that domestication affected not only individual genes but also regulatory networks. Five co-expression clusters were enriched in functional terms involving carbohydrate metabolism or epigenetic regulation of gene expression. We detected differences in nucleotide diversity between the crop and wild groups specific to DEG. Our study provides an extensive profiling of the rewiring of gene co-expression induced by the domestication syndrome in one of the main crop species. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

  12. Lymphangiogenesis in cervical cancer evaluated by expression of the VEGF-C gene in clinical stage IB-IIIB

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    Magdalena Franc

    2015-02-01

    Full Text Available Introduction : The aim of the present study was to evaluate the profile of VEGF-C gene expression in particular stages of cervical cancer (IB-IIIB and to estimate the correlation between VEGF-C mRNA quantity profile and clinical stage. Material and methods : Material for molecular analysis consisted of cervical cancer tissue specimens collected from 38 women (10, 15, 13 cases were classified as IB, IIB and IIIB, respectively. The control group was composed of normal cervical tissues collected from 10 women who underwent hysterectomy for non-oncological reasons. The number of VEGF-C mRNA copies in particular groups was estimated by the reverse transcription quantitative polymerase chain reaction (RT-qPCR method. Results: In the control group the average number of mRNA copies was 134 ± 36 (median: 106, in a group with stage IB it was 16 077 ± 7090 (median: 580, for stage IIB – 35 019 ± 8945 (median: 40 870. The highest number of mRNA VEGF-C copies was derived in a group of patients with cervical cancer of stage IIIB. The average quantity was 56 155 ± 12 470, whereas median 55 981. A statistically significantly higher level of VEGF-C gene expression was disclosed in cervical cancer specimens with stage IIB and IIIB than in the control group. In stage IIIB, the VEGF-C gene expression was significantly higher than in specimens derived from individuals in stage IB. Conclusions : In squamous cell carcinoma of the uterine cervix of stage IB-IIIB genes involved in lymphangio­genesis, especially VEGF-C , are expressed, which expression increases as the clinical stage of cervical cancer is higher.

  13. Heterologous gene expression driven by carbonic anhydrase gene promoter in Dunaliella salina

    Science.gov (United States)

    Yurong, Chai; Yumin, Lu; Tianyun, Wang; Weihong, Hou; Lexun, Xue

    2006-12-01

    Dunaliella salina, a halotolerant unicellular green alga without a rigid cell wall, can live in salinities ranging from 0.05 to 5 mol/L NaCl. These features of D. salina make it an ideal host for the production of antibodies, oral vaccine, and commercially valuable polypeptides. To produce high level of heterologous proteins from D. salina, highly efficient promoters are required to drive expression of target genes under controlled condition. In the present study, we cloned a 5' franking region of 1.4 kb from the carbonic anhydrase ( CAH) gene of D. salina by genomic walking and PCR. The fragment was ligated to the pMD18-T vector and characterized. Sequence analysis indicated that this region contained conserved motifs, including a TATA- like box and CAAT-box. Tandem (GT)n repeats that had a potential role of transcriptional control, were also found in this region. The transcription start site (TSS) of the CAH gene was determined by 5' RACE and nested PCR method. Transformation assays showed that the 1.4 kb fragment was able to drive expression of the selectable bar (bialaphos resistance) gene when the fusion was transformed into D. salina by biolistics. Northern blotting hybridizations showed that the bar transcript was most abundant in cells grown in 2 mol/L NaCl, and less abundant in 0.5 mol/L NaCl, indicating that expression of the bar gene was induced at high salinity. These results suggest the potential use of the CAH gene promoter to induce the expression of heterologous genes in D. salina under varied salt condition.

  14. Density based pruning for identification of differentially expressed genes from microarray data

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    Xu Jia

    2010-11-01

    Full Text Available Abstract Motivation Identification of differentially expressed genes from microarray datasets is one of the most important analyses for microarray data mining. Popular algorithms such as statistical t-test rank genes based on a single statistics. The false positive rate of these methods can be improved by considering other features of differentially expressed genes. Results We proposed a pattern recognition strategy for identifying differentially expressed genes. Genes are mapped to a two dimension feature space composed of average difference of gene expression and average expression levels. A density based pruning algorithm (DB Pruning is developed to screen out potential differentially expressed genes usually located in the sparse boundary region. Biases of popular algorithms for identifying differentially expressed genes are visually characterized. Experiments on 17 datasets from Gene Omnibus Database (GEO with experimentally verified differentially expressed genes showed that DB pruning can significantly improve the prediction accuracy of popular identification algorithms such as t-test, rank product, and fold change. Conclusions Density based pruning of non-differentially expressed genes is an effective method for enhancing statistical testing based algorithms for identifying differentially expressed genes. It improves t-test, rank product, and fold change by 11% to 50% in the numbers of identified true differentially expressed genes. The source code of DB pruning is freely available on our website http://mleg.cse.sc.edu/degprune

  15. Characterization of transcriptome in the Indian meal moth Plodia interpunctella (Lepidoptera: Pyralidae) and gene expression analysis during developmental stages.

    Science.gov (United States)

    Tang, Pei-An; Wu, Hai-Jing; Xue, Hao; Ju, Xing-Rong; Song, Wei; Zhang, Qi-Lin; Yuan, Ming-Long

    2017-07-30

    The Indian meal moth Plodia interpunctella (Lepidoptera: Pyralidae) is a worldwide pest that causes serious damage to stored foods. Although many efforts have been conducted on this species due to its economic importance, the study of genetic basis of development, behavior and insecticide resistance has been greatly hampered due to lack of genomic information. In this study, we used high throughput sequencing platform to perform a de novo transcriptome assembly and tag-based digital gene expression profiling (DGE) analyses across four different developmental stages of P. interpunctella (egg, third-instar larvae, pupae and adult). We obtained approximate 9gigabyte (GB) of clean data and recovered 84,938 unigenes, including 37,602 clusters and 47,336 singletons. These unigenes were annotated using BLAST against the non-redundant protein databases and then functionally classified based on Gene Ontology (GO), Clusters of Orthologous Groups (COG), and Kyoto Encyclopedia of Genes and Genomes databases (KEGG). A large number of differentially expressed genes were identified by pairwise comparisons among different developmental stages. Gene expression profiles dramatically changed between developmental stage transitions. Some of these differentially expressed genes were related to digestion and cuticularization. Quantitative real-time PCR results of six randomly selected genes conformed the findings in the DGEs. Furthermore, we identified over 8000 microsatellite markers and 97,648 single nucleotide polymorphisms which will be useful for population genetics studies of P. interpunctella. This transcriptomic information provided insight into the developmental basis of P. interpunctella and will be helpful for establishing integrated management strategies and developing new targets of insecticides for this serious pest. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. The gene expressions of DNA methylation/demethylation enzymes ...

    African Journals Online (AJOL)

    A decrease in mRNA levels for cytochrome c oxidase (COX) subunits was observed in skeletal muscle of hypothyroid rats. However, the precise expression mechanisms of the related genes in hypothyroid state still remain unclear. This study investigated gene expressions of DNA methyltransferases (Dnmts), DNA ...

  17. Global gene expression analysis for evaluation and design of biomaterials

    Directory of Open Access Journals (Sweden)

    Nobutaka Hanagata, Taro Takemura and Takashi Minowa

    2010-01-01

    Full Text Available Comprehensive gene expression analysis using DNA microarrays has become a widespread technique in molecular biological research. In the biomaterials field, it is used to evaluate the biocompatibility or cellular toxicity of metals, polymers and ceramics. Studies in this field have extracted differentially expressed genes in the context of differences in cellular responses among multiple materials. Based on these genes, the effects of materials on cells at the molecular level have been examined. Expression data ranging from several to tens of thousands of genes can be obtained from DNA microarrays. For this reason, several tens or hundreds of differentially expressed genes are often present in different materials. In this review, we outline the principles of DNA microarrays, and provide an introduction to methods of extracting information which is useful for evaluating and designing biomaterials from comprehensive gene expression data.

  18. Global gene expression analysis for evaluation and design of biomaterials

    International Nuclear Information System (INIS)

    Hanagata, Nobutaka; Takemura, Taro; Minowa, Takashi

    2010-01-01

    Comprehensive gene expression analysis using DNA microarrays has become a widespread technique in molecular biological research. In the biomaterials field, it is used to evaluate the biocompatibility or cellular toxicity of metals, polymers and ceramics. Studies in this field have extracted differentially expressed genes in the context of differences in cellular responses among multiple materials. Based on these genes, the effects of materials on cells at the molecular level have been examined. Expression data ranging from several to tens of thousands of genes can be obtained from DNA microarrays. For this reason, several tens or hundreds of differentially expressed genes are often present in different materials. In this review, we outline the principles of DNA microarrays, and provide an introduction to methods of extracting information which is useful for evaluating and designing biomaterials from comprehensive gene expression data. (topical review)

  19. Neonatal maternal deprivation response and developmental changes in gene expression revealed by hypothalamic gene expression profiling in mice.

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    Feng Ding

    Full Text Available Neonatal feeding problems are observed in several genetic diseases including Prader-Willi syndrome (PWS. Later in life, individuals with PWS develop hyperphagia and obesity due to lack of appetite control. We hypothesized that failure to thrive in infancy and later-onset hyperphagia are related and could be due to a defect in the hypothalamus. In this study, we performed gene expression microarray analysis of the hypothalamic response to maternal deprivation in neonatal wild-type and Snord116del mice, a mouse model for PWS in which a cluster of imprinted C/D box snoRNAs is deleted. The neonatal starvation response in both strains was dramatically different from that reported in adult rodents. Genes that are affected by adult starvation showed no expression change in the hypothalamus of 5 day-old pups after 6 hours of maternal deprivation. Unlike in adult rodents, expression levels of Nanos2 and Pdk4 were increased, and those of Pgpep1, Ndp, Brms1l, Mett10d, and Snx1 were decreased after neonatal deprivation. In addition, we compared hypothalamic gene expression profiles at postnatal days 5 and 13 and observed significant developmental changes. Notably, the gene expression profiles of Snord116del deletion mice and wild-type littermates were very similar at all time points and conditions, arguing against a role of Snord116 in feeding regulation in the neonatal period.

  20. Drosophila Myc is required for normal DREF gene expression

    International Nuclear Information System (INIS)

    Dang Thi Phuong Thao; Seto, Hirokazu; Yamaguchi, Masamitsu

    2008-01-01

    The Drosophila DNA replication-related element-binding factor (dDREF) is required for the expression of many proliferation-related genes carrying the DRE sequence, 5'-TATCGATA. Finding a canonical E-box, 5'-CACGTG, in the dDREF gene promoter prompted us to explore the possibility that the dDREF gene is a target of Drosophila Myc (dMyc). Luciferase transient expression assays combined with RNA interference in Drosophila S2 cells revealed that knockdown of dmyc reduced dDREF gene promoter activity by 35% to 82%, an effect at least partly mediated by the E-box in the promoter. dm 4 /Y hemizygous mutant larvae demonstrated no maternal dMyc and severe impairment of dDREF mRNA transcription. dMyc loss of function in dm 2 /dm 2 homozygous mutant follicle cell clones also resulted in loss of anti-dDREF immunostaining in nuclei. In contrast, co-expression of dMyc-dMax up-regulated dDREF promoter activity in S2 cells. Furthermore, dMyc over-expressing clones exhibited a high level of dDREF gene expression in wing and eye discs. These results taken together indicate that dMyc is indeed required for dDREF gene expression

  1. Reproducibility of gene expression across generations of Affymetrix microarrays

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    Haslett Judith N

    2003-06-01

    Full Text Available Abstract Background The development of large-scale gene expression profiling technologies is rapidly changing the norms of biological investigation. But the rapid pace of change itself presents challenges. Commercial microarrays are regularly modified to incorporate new genes and improved target sequences. Although the ability to compare datasets across generations is crucial for any long-term research project, to date no means to allow such comparisons have been developed. In this study the reproducibility of gene expression levels across two generations of Affymetrix GeneChips® (HuGeneFL and HG-U95A was measured. Results Correlation coefficients were computed for gene expression values across chip generations based on different measures of similarity. Comparing the absolute calls assigned to the individual probe sets across the generations found them to be largely unchanged. Conclusion We show that experimental replicates are highly reproducible, but that reproducibility across generations depends on the degree of similarity of the probe sets and the expression level of the corresponding transcript.

  2. ANALYSES ON DIFFERENTIALLY EXPRESSED GENES ASSOCIATED WITH HUMAN BREAST CANCER

    Institute of Scientific and Technical Information of China (English)

    MENG Xu-li; DING Xiao-wen; XU Xiao-hong

    2006-01-01

    Objective: To investigate the molecular etiology of breast cancer by way of studying the differential expression and initial function of the related genes in the occurrence and development of breast cancer. Methods: Two hundred and eighty-eight human tumor related genes were chosen for preparation of the oligochips probe. mRNA was extracted from 16 breast cancer tissues and the corresponding normal breast tissues, and cDNA probe was prepared through reverse-transcription and hybridized with the gene chip. A laser focused fluorescent scanner was used to scan the chip. The different gene expressions were thereafter automatically compared and analyzed between the two sample groups. Cy3/Cy5>3.5 meant significant up-regulation. Cy3/Cy5<0.25 meant significant down-regulation. Results: The comparison between the breast cancer tissues and their corresponding normal tissues showed that 84 genes had differential expression in the Chip. Among the differently expressed genes, there were 4 genes with significant down-regulation and 6 with significant up-regulation. Compared with normal breast tissues, differentially expressed genes did partially exist in the breast cancer tissues. Conclusion: Changes in multi-gene expression regulations take place during the occurrence and development of breast cancer; and the research on related genes can help understanding the mechanism of tumor occurrence.

  3. Expression analysis of two gene subfamilies encoding the plasma membrane H+-ATPase in Nicotiana plumbaginifolia reveals the major transport functions of this enzyme.

    Science.gov (United States)

    Moriau, L; Michelet, B; Bogaerts, P; Lambert, L; Michel, A; Oufattole, M; Boutry, M

    1999-07-01

    The plasma membrane H+-ATPase couples ATP hydrolysis to proton transport, thereby establishing the driving force for solute transport across the plasma membrane. In Nicotiana plumbaginifolia, this enzyme is encoded by at least nine pma (plasma membrane H+-ATPase) genes. Four of these are classified into two gene subfamilies, pma1-2-3 and pma4, which are the most highly expressed in plant species. We have isolated genomic clones for pma2 and pma4. Mapping of their transcript 5' end revealed the presence of a long leader that contained small open reading frames, regulatory features typical of other pma genes. The gusA reporter gene was then used to determine the expression of pma2, pma3 and pma4 in N. tabacum. These data, together with those obtained previously for pma1, led to the following conclusions. (i) The four pma-gusA genes were all expressed in root, stem, leaf and flower organs, but each in a cell-type specific manner. Expression in these organs was confirmed at the protein level, using subfamily-specific antibodies. (ii) pma4-gusA was expressed in many cell types and notably in root hair and epidermis, in companion cells, and in guard cells, indicating that in N. plumbaginifolia the same H+-ATPase isoform might be involved in mineral nutrition, phloem loading and control of stomata aperture. (iii) The second gene subfamily is composed, in N. plumbaginifolia, of a single gene (pma4) with a wide expression pattern and, in Arabidopsis thaliana, of three genes (aha1, aha2, aha3), at least two of them having a more restrictive expression pattern. (iv) Some cell types expressed pma2 and pma4 at the same time, which encode H+-ATPases with different enzymatic properties.

  4. Exploring the key genes and pathways in enchondromas using a gene expression microarray.

    Science.gov (United States)

    Shi, Zhongju; Zhou, Hengxing; Pan, Bin; Lu, Lu; Kang, Yi; Liu, Lu; Wei, Zhijian; Feng, Shiqing

    2017-07-04

    Enchondromas are the most common primary benign osseous neoplasms that occur in the medullary bone; they can undergo malignant transformation into chondrosarcoma. However, enchondromas are always undetected in patients, and the molecular mechanism is unclear. To identify key genes and pathways associated with the occurrence and development of enchondromas, we downloaded the gene expression dataset GSE22855 and obtained the differentially expressed genes (DEGs) by analyzing high-throughput gene expression in enchondromas. In total, 635 genes were identified as DEGs. Of these, 225 genes (35.43%) were up-regulated, and the remaining 410 genes (64.57%) were down-regulated. We identified the predominant gene ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways that were significantly over-represented in the enchondromas samples compared with the control samples. Subsequently the top 10 core genes were identified from the protein-protein interaction (PPI) network. The enrichment analyses of the genes mainly involved in two significant modules showed that the DEGs were principally related to ribosomes, protein digestion and absorption, ECM-receptor interaction, focal adhesion, amoebiasis and the PI3K-Akt signaling pathway.Together, these data elucidate the molecular mechanisms underlying the occurrence and development of enchondromas and provide promising candidates for therapeutic intervention and prognostic evaluation. However, further experimental studies are needed to confirm these results.

  5. Gene duplication, silencing and expression alteration govern the molecular evolution of PRC2 genes in plants.

    Science.gov (United States)

    Furihata, Hazuka Y; Suenaga, Kazuya; Kawanabe, Takahiro; Yoshida, Takanori; Kawabe, Akira

    2016-10-13

    PRC2 genes were analyzed for their number of gene duplications, d N /d S ratios and expression patterns among Brassicaceae and Gramineae species. Although both amino acid sequences and copy number of the PRC2 genes were generally well conserved in both Brassicaceae and Gramineae species, we observed that some rapidly evolving genes experienced duplications and expression pattern changes. After multiple duplication events, all but one or two of the duplicated copies tend to be silenced. Silenced copies were reactivated in the endosperm and showed ectopic expression in developing seeds. The results indicated that rapid evolution of some PRC2 genes is initially caused by a relaxation of selective constraint following the gene duplication events. Several loci could become maternally expressed imprinted genes and acquired functional roles in the endosperm.

  6. Radiation-modulated gene expression in C. elegans

    International Nuclear Information System (INIS)

    Nelson, G.A.; Bayeta, E.; Perez, C.; Lloyd, E.; Jones, T.; Smith, A.; Tian, J.

    2003-01-01

    Full text: We use the nematode C. elegans to characterize the genotoxic and cytotoxic effects of ionizing radiation with emphasis effects of charged particle radiation and have described the fluence vs. response relationships for mutation, chromosome aberration and certain developmental errors. These endpoints quantify the biological after repair and compensation pathways have completed their work. In order to address the control of these reactions we have turned to gene expression profiling to identify genes that uniquely respond to high LET species or respond differentially as a function of radiation properties. We have employed whole genome microarray methods to map gene expression following exposure to gamma rays, protons and accelerated iron ions. We found that 599 of 17871 genes analyzed showed differential expression 3 hrs after exposure to 3 Gy of at least one radiation types. 193 were up-regulated, 406 were down-regulated, and 90% were affected by only one species of radiation. Genes whose transcription levels responded significantly mapped to definite statistical clusters that were unique for each radiation type. We are now trying to establish the functional relationships of the genes their relevance to mitigation of radiation-induced damage. Three approaches are being used. First, bioinformatics tools are being used to determine the roles of genes in co-regulated gene sets. Second, we are applying the technique of RNA interference to determine whether our radiation-induced genes affect cell survival (measured in terms of embryo survival) and chromosome aberration (intestinal anaphase bridges). Finally we are focussing on the response of the most strongly-regulated gene in our data set. This is the autosomal gene, F36D3.9, whose predicted structure is that of a cysteine protease resembling cathepsin B. An enzymological approach is being used to characterize this gene at the protein level. This work was supported by NASA Cooperative Agreement NCC9-149

  7. Validation of reference genes for quantitative RT-PCR studies of gene expression in perennial ryegrass (Lolium perenne L.

    Directory of Open Access Journals (Sweden)

    Thrush Anthony

    2010-01-01

    Full Text Available Abstract Background Perennial ryegrass (Lolium perenne L. is an important pasture and turf crop. Biotechniques such as gene expression studies are being employed to improve traits in this temperate grass. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR is among the best methods available for determining changes in gene expression. Before analysis of target gene expression, it is essential to select an appropriate normalisation strategy to control for non-specific variation between samples. Reference genes that have stable expression at different biological and physiological states can be effectively used for normalisation; however, their expression stability must be validated before use. Results Existing Serial Analysis of Gene Expression data were queried to identify six moderately expressed genes that had relatively stable gene expression throughout the year. These six candidate reference genes (eukaryotic elongation factor 1 alpha, eEF1A; TAT-binding protein homolog 1, TBP-1; eukaryotic translation initiation factor 4 alpha, eIF4A; YT521-B-like protein family protein, YT521-B; histone 3, H3; ubiquitin-conjugating enzyme, E2 were validated for qRT-PCR normalisation in 442 diverse perennial ryegrass (Lolium perenne L. samples sourced from field- and laboratory-grown plants under a wide range of experimental conditions. Eukaryotic EF1A is encoded by members of a multigene family exhibiting differential expression and necessitated the expression analysis of different eEF1A encoding genes; a highly expressed eEF1A (h, a moderately, but stably expressed eEF1A (s, and combined expression of multigene eEF1A (m. NormFinder identified eEF1A (s and YT521-B as the best combination of two genes for normalisation of gene expression data in perennial ryegrass following different defoliation management in the field. Conclusions This study is unique in the magnitude of samples tested with the inclusion of numerous field-grown samples

  8. Analysis of multiplex gene expression maps obtained by voxelation

    OpenAIRE

    An, L; Xie, H; Chin, MH; Obradovic, Z; Smith, DJ; Megalooikonomou, V

    2009-01-01

    Abstract Background Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we presen...

  9. GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature

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    Ning Ye

    2015-01-01

    Full Text Available The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.

  10. Gene expression in cerebral ischemia: a new approach for neuroprotection.

    Science.gov (United States)

    Millán, Mónica; Arenillas, Juan

    2006-01-01

    Cerebral ischemia is one of the strongest stimuli for gene induction in the brain. Hundreds of genes have been found to be induced by brain ischemia. Many genes are involved in neurodestructive functions such as excitotoxicity, inflammatory response and neuronal apoptosis. However, cerebral ischemia is also a powerful reformatting and reprogramming stimulus for the brain through neuroprotective gene expression. Several genes may participate in both cellular responses. Thus, isolation of candidate genes for neuroprotection strategies and interpretation of expression changes have been proven difficult. Nevertheless, many studies are being carried out to improve the knowledge of the gene activation and protein expression following ischemic stroke, as well as in the development of new therapies that modify biochemical, molecular and genetic changes underlying cerebral ischemia. Owing to the complexity of the process involving numerous critical genes expressed differentially in time, space and concentration, ongoing therapeutic efforts should be based on multiple interventions at different levels. By modification of the acute gene expression induced by ischemia or the apoptotic gene program, gene therapy is a promising treatment but is still in a very experimental phase. Some hurdles will have to be overcome before these therapies can be introduced into human clinical stroke trials. Copyright 2006 S. Karger AG, Basel.

  11. dictyExpress: a Dictyostelium discoideum gene expression database with an explorative data analysis web-based interface

    Science.gov (United States)

    Rot, Gregor; Parikh, Anup; Curk, Tomaz; Kuspa, Adam; Shaulsky, Gad; Zupan, Blaz

    2009-01-01

    Background Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability. Results We have developed dictyExpress, a web application that features a graphical, highly interactive explorative interface to our database that consists of more than 1000 Dictyostelium discoideum gene expression experiments. In dictyExpress, the user can select experiments and genes, perform gene clustering, view gene expression profiles across time, view gene co-expression networks, perform analyses of Gene Ontology term enrichment, and simultaneously display expression profiles for a selected gene in various experiments. Most importantly, these tasks are achieved through web applications whose components are seamlessly interlinked and immediately respond to events triggered by the user, thus providing a powerful explorative data analysis environment. Conclusion dictyExpress is a precursor for a new generation of web-based bioinformatics applications with simple but powerful interactive interfaces that resemble that of the modern desktop. While dictyExpress serves mainly the Dictyostelium research community, it is relatively easy to adapt it to other datasets. We propose that the design ideas behind dictyExpress will influence the development of similar applications for other model organisms. PMID:19706156

  12. Coregulated expression of loline alkaloid-biosynthesis genes in Neotyphodium uncinatum cultures.

    Science.gov (United States)

    Zhang, Dong-Xiu; Stromberg, Arnold J; Spiering, Martin J; Schardl, Christopher L

    2009-08-01

    Epichloë endophytes (holomorphic Epichloë spp. and anamorphic Neotyphodium spp.) are systemic, often heritable symbionts of cool-season grasses (subfamily Pooideae). Many epichloae provide protection to their hosts by producing anti-insect compounds. Among these are the loline alkaloids (LA), which are toxic and deterrent to a broad range of herbivorous insects but not to mammalian herbivores. LOL, a gene cluster containing nine genes, is associated with LA biosynthesis. We investigated coordinate regulation between LOL-gene expression and LA production in minimal medium (MM) cultures of Neotyphodium uncinatum. Expression of all LOL genes significantly fit temporal quadratic patterns during LA production. LOL-gene expression started before LA were detectable, and increased while LA accumulated. The highest gene expression level was reached at close to the time of most rapid LA accumulation, and gene expression declined to a very low level as amounts of LA plateaued. Temporal expression profiles of the nine LOL genes were tightly correlated with each other, but not as tightly correlated with proC and metE (genes for biosynthesis of precursor amino acids). Furthermore, the start days and peak days of expression significantly correlated with the order of the LOL-cluster genes in the genome. Hierarchical cluster analysis indicated three pairs of genes-lolA and lolC, lolO and lolD, and lolT and lolE-expression of which was especially tightly correlated. Of these, lolA and lolC tended to be expressed early, and lolT and lolE tended to be expressed late, in keeping with the putative roles of the respective gene products in the LA-biosynthesis pathway. Several common transcriptional binding sites were discovered in the LOL upstream regions. However, low expression of P(lolC2)uidA and P(lolA2)uidA in N. uncinatum transformants suggested induced expression of LOL genes might be subject to position effect at the LOL locus.

  13. Expression of isgylation related genes in regenerating rat liver

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    Kuklin A. V.

    2015-10-01

    Full Text Available Our recent studies have revealed the early up-regulated expression of interferon alpha (IFNα in the liver, induced by partial hepatectomy. The role of this cytokine of innate immune response in liver regeneration is still controversial. Aim. To analyze expression of canonical interferon-stimulated genes Ube1l, Ube2l6, Trim25, Usp18 and Isg15 during the liver transition from quiescence to proliferation induced by partial hepatectomy, and acute phase response induced by laparotomy. These genes are responsible for posttranslational modification of proteins by ISGylation. The expression of genes encoding TATA binding protein (TBP and 18S rRNA served as indirect general markers of transcriptional and translational activities. Methods. The abundance of investigated RNAs was assessed in total liver RNA by real time RT–qPCR. Results. Partial hepatecomy induced steady upregulation of the Tbp and 18S rRNA genes expression during 12 hours post-surgery and downregulation or no change in expression of ISGylation-related genes during the first 3 hours followed by slight upregulation at 12 hours. The level of Isg15 transcripts was permanently below that of the control during the prereplicative period. Laparotomy induced a continuous downregulation of Tbp and 18S rRNA expression and early (1–3h upregulation of ISGylation–related transcripts followed by a sharp drop at 6 hours and slight increase/decrease at 12 hours. The changes in the abundance of Ifnα and ISGylation-related mRNAs were oppositely directed at each stage of the response to partial hepatectomy and laparotomy. Conclusion. We suggest that the expression of ISGylation-related genes does not depend on the expression of Ifnα gene after both surgeries. The indirect indices of transcription and translation as well as the expression of ISGylation-relaled genes are principally different in response to partial hepatectomy and laparotomy and argue for the high specificity of innate immune response.

  14. Characterization of gene expression associated with drought avoidance and tolerance traits in a perennial grass species.

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    Peng Zhou

    Full Text Available To understand molecular mechanisms of perennial grass adaptation to drought stress, genes associated with drought avoidance or tolerance traits were identified and their expression patterns were characterized in C4 hybrid bermudagrass [Cynodon dactylon (L. Pers.×C. transvaalensis Burtt Davy, cv. Tifway] and common bermudagrass (C. dactylon, cv. C299. Plants of drought-tolerant 'Tifway' and drought-sensitive 'C299' were exposed to drought for 5 d (mild stress and 10 d (severe stress by withholding irrigation in a growth chamber. 'Tifway' maintained significantly lower electrolyte leakage and higher relative water content than 'C299' at both 5 and 10 d of drought stress. Four cDNA libraries via suppression subtractive hybridization analysis were constructed and identified 277 drought-responsive genes in the two genotypes at 5 and 10 d of drought stress, which were mainly classified into the functional categories of stress defense, metabolism, osmoregulation, membrane system, signal and regulator, structural protein, protein synthesis and degradation, and energy metabolism. Quantitative-PCR analysis confirmed the expression of 36 drought up-regulated genes that were more highly expressed in drought-tolerant 'Tifway' than drought-sensitive 'C299', including those for drought avoidance traits, such as cuticle wax formation (CER1 and sterol desaturase, for drought tolerance traits, such as dehydration-protective proteins (dehydrins, HVA-22-like protein and oxidative stress defense (superoxide dismutase, dehydroascorbate reductase, 2-Cys peroxiredoxins, and for stress signaling (EREBP-4 like protein and WRKY transcription factor. The results suggest that the expression of genes for stress signaling, cuticle wax accumulation, antioxidant defense, and dehydration-protective protein accumulation could be critically important for warm-season perennial grass adaptation to long-term drought stress.

  15. The gene expressions of DNA methylation/demethylation enzymes ...

    African Journals Online (AJOL)

    user

    2011-01-31

    Jan 31, 2011 ... A decrease in mRNA levels for cytochrome c oxidase (COX) subunits was observed in skeletal muscle of hypothyroid rats. However, the precise expression mechanisms of the related genes in hypothyroid state still remain unclear. This study investigated gene expressions of DNA methyltransferases.

  16. Automatic Control of Gene Expression in Mammalian Cells.

    Science.gov (United States)

    Fracassi, Chiara; Postiglione, Lorena; Fiore, Gianfranco; di Bernardo, Diego

    2016-04-15

    Automatic control of gene expression in living cells is paramount importance to characterize both endogenous gene regulatory networks and synthetic circuits. In addition, such a technology can be used to maintain the expression of synthetic circuit components in an optimal range in order to ensure reliable performance. Here we present a microfluidics-based method to automatically control gene expression from the tetracycline-inducible promoter in mammalian cells in real time. Our approach is based on the negative-feedback control engineering paradigm. We validated our method in a monoclonal population of cells constitutively expressing a fluorescent reporter protein (d2EYFP) downstream of a minimal CMV promoter with seven tet-responsive operator motifs (CMV-TET). These cells also constitutively express the tetracycline transactivator protein (tTA). In cells grown in standard growth medium, tTA is able to bind the CMV-TET promoter, causing d2EYFP to be maximally expressed. Upon addition of tetracycline to the culture medium, tTA detaches from the CMV-TET promoter, thus preventing d2EYFP expression. We tested two different model-independent control algorithms (relay and proportional-integral (PI)) to force a monoclonal population of cells to express an intermediate level of d2EYFP equal to 50% of its maximum expression level for up to 3500 min. The control input is either tetracycline-rich or standard growth medium. We demonstrated that both the relay and PI controllers can regulate gene expression at the desired level, despite oscillations (dampened in the case of the PI controller) around the chosen set point.

  17. Identification of differentially expressed genes in childhood asthma.

    Science.gov (United States)

    Zhang, Nian-Zhen; Chen, Xiu-Juan; Mu, Yu-Hua; Wang, Hewen

    2018-05-01

    Asthma has been the most common chronic disease in children that places a major burden for affected people and their families.An integrated analysis of microarrays studies was performed to identify differentially expressed genes (DEGs) in childhood asthma compared with normal control. We also obtained the differentially methylated genes (DMGs) in childhood asthma according to GEO. The genes that were both differentially expressed and differentially methylated were identified. Functional annotation and protein-protein interaction network construction were performed to interpret biological functions of DEGs. We performed q-RT-PCR to verify the expression of selected DEGs.One DNA methylation and 3 gene expression datasets were obtained. Four hundred forty-one DEGs and 1209 DMGs in childhood asthma were identified. Among which, 16 genes were both differentially expressed and differentially methylated in childhood asthma. Natural killer cell mediated cytotoxicity pathway, Jak-STAT signaling pathway, and Wnt signaling pathway were 3 significantly enriched pathways in childhood asthma according to our KEGG enrichment analysis. The PPI network of top 20 up- and downregulated DEGs consisted of 822 nodes and 904 edges and 2 hub proteins (UBQLN4 and MID2) were identified. The expression of 8 DEGs (GZMB, FGFBP2, CLC, TBX21, ALOX15, IL12RB2, UBQLN4) was verified by qRT-PCR and only the expression of GZMB and FGFBP2 was inconsistent with our integrated analysis.Our finding was helpful to elucidate the underlying mechanism of childhood asthma and develop new potential diagnostic biomarker and provide clues for drug design.

  18. Screening key genes for abdominal aortic aneurysm based on gene expression omnibus dataset.

    Science.gov (United States)

    Wan, Li; Huang, Jingyong; Ni, Haizhen; Yu, Guanfeng

    2018-02-13

    Abdominal aortic aneurysm (AAA) is a common cardiovascular system disease with high mortality. The aim of this study was to identify potential genes for diagnosis and therapy in AAA. We searched and downloaded mRNA expression data from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) from AAA and normal individuals. Then, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, transcriptional factors (TFs) network and protein-protein interaction (PPI) network were used to explore the function of genes. Additionally, immunohistochemical (IHC) staining was used to validate the expression of identified genes. Finally, the diagnostic value of identified genes was accessed by receiver operating characteristic (ROC) analysis in GEO database. A total of 1199 DEGs (188 up-regulated and 1011 down-regulated) were identified between AAA and normal individual. KEGG pathway analysis displayed that vascular smooth muscle contraction and pathways in cancer were significantly enriched signal pathway. The top 10 up-regulated and top 10 down-regulated DEGs were used to construct TFs and PPI networks. Some genes with high degrees such as NELL2, CCR7, MGAM, HBB, CSNK2A2, ZBTB16 and FOXO1 were identified to be related to AAA. The consequences of IHC staining showed that CCR7 and PDGFA were up-regulated in tissue samples of AAA. ROC analysis showed that NELL2, CCR7, MGAM, HBB, CSNK2A2, ZBTB16, FOXO1 and PDGFA had the potential diagnostic value for AAA. The identified genes including NELL2, CCR7, MGAM, HBB, CSNK2A2, ZBTB16, FOXO1 and PDGFA might be involved in the pathology of AAA.

  19. Caffeine exposure alters cardiac gene expression in embryonic cardiomyocytes

    Science.gov (United States)

    Fang, Xiefan; Mei, Wenbin; Barbazuk, William B.; Rivkees, Scott A.

    2014-01-01

    Previous studies demonstrated that in utero caffeine treatment at embryonic day (E) 8.5 alters DNA methylation patterns, gene expression, and cardiac function in adult mice. To provide insight into the mechanisms, we examined cardiac gene and microRNA (miRNA) expression in cardiomyocytes shortly after exposure to physiologically relevant doses of caffeine. In HL-1 and primary embryonic cardiomyocytes, caffeine treatment for 48 h significantly altered the expression of cardiac structural genes (Myh6, Myh7, Myh7b, Tnni3), hormonal genes (Anp and BnP), cardiac transcription factors (Gata4, Mef2c, Mef2d, Nfatc1), and microRNAs (miRNAs; miR208a, miR208b, miR499). In addition, expressions of these genes were significantly altered in embryonic hearts exposed to in utero caffeine. For in utero experiments, pregnant CD-1 dams were treated with 20–60 mg/kg of caffeine, which resulted in maternal circulation levels of 37.3–65.3 μM 2 h after treatment. RNA sequencing was performed on embryonic ventricles treated with vehicle or 20 mg/kg of caffeine daily from E6.5-9.5. Differential expression (DE) analysis revealed that 124 genes and 849 transcripts were significantly altered, and differential exon usage (DEU) analysis identified 597 exons that were changed in response to prenatal caffeine exposure. Among the DE genes identified by RNA sequencing were several cardiac structural genes and genes that control DNA methylation and histone modification. Pathway analysis revealed that pathways related to cardiovascular development and diseases were significantly affected by caffeine. In addition, global cardiac DNA methylation was reduced in caffeine-treated cardiomyocytes. Collectively, these data demonstrate that caffeine exposure alters gene expression and DNA methylation in embryonic cardiomyocytes. PMID:25354728

  20. Multi-targeted priming for genome-wide gene expression assays

    Directory of Open Access Journals (Sweden)

    Adomas Aleksandra B

    2010-08-01

    Full Text Available Abstract Background Complementary approaches to assaying global gene expression are needed to assess gene expression in regions that are poorly assayed by current methodologies. A key component of nearly all gene expression assays is the reverse transcription of transcribed sequences that has traditionally been performed by priming the poly-A tails on many of the transcribed genes in eukaryotes with oligo-dT, or by priming RNA indiscriminately with random hexamers. We designed an algorithm to find common sequence motifs that were present within most protein-coding genes of Saccharomyces cerevisiae and of Neurospora crassa, but that were not present within their ribosomal RNA or transfer RNA genes. We then experimentally tested whether degenerately priming these motifs with multi-targeted primers improved the accuracy and completeness of transcriptomic assays. Results We discovered two multi-targeted primers that would prime a preponderance of genes in the genomes of Saccharomyces cerevisiae and Neurospora crassa while avoiding priming ribosomal RNA or transfer RNA. Examining the response of Saccharomyces cerevisiae to nitrogen deficiency and profiling Neurospora crassa early sexual development, we demonstrated that using multi-targeted primers in reverse transcription led to superior performance of microarray profiling and next-generation RNA tag sequencing. Priming with multi-targeted primers in addition to oligo-dT resulted in higher sensitivity, a larger number of well-measured genes and greater power to detect differences in gene expression. Conclusions Our results provide the most complete and detailed expression profiles of the yeast nitrogen starvation response and N. crassa early sexual development to date. Furthermore, our multi-targeting priming methodology for genome-wide gene expression assays provides selective targeting of multiple sequences and counter-selection against undesirable sequences, facilitating a more complete and

  1. Some ethylene biosynthesis and AP2/ERF genes reveal a specific pattern of expression during somatic embryogenesis in Hevea brasiliensis

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    Piyatrakul Piyanuch

    2012-12-01

    Full Text Available Abstract Background Ethylene production and signalling play an important role in somatic embryogenesis, especially for species that are recalcitrant in in vitro culture. The AP2/ERF superfamily has been identified and classified in Hevea brasiliensis. This superfamily includes the ERFs involved in response to ethylene. The relative transcript abundance of ethylene biosynthesis genes and of AP2/ERF genes was analysed during somatic embryogenesis for callus lines with different regeneration potential, in order to identify genes regulated during that process. Results The analysis of relative transcript abundance was carried out by real-time RT-PCR for 142 genes. The transcripts of ERFs from group I, VII and VIII were abundant at all stages of the somatic embryogenesis process. Forty genetic expression markers for callus regeneration capacity were identified. Fourteen markers were found for proliferating calli and 35 markers for calli at the end of the embryogenesis induction phase. Sixteen markers discriminated between normal and abnormal embryos and, lastly, there were 36 markers of conversion into plantlets. A phylogenetic analysis comparing the sequences of the AP2 domains of Hevea and Arabidopsis genes enabled us to predict the function of 13 expression marker genes. Conclusions This first characterization of the AP2/ERF superfamily in Hevea revealed dramatic regulation of the expression of AP2/ERF genes during the somatic embryogenesis process. The gene expression markers of proliferating callus capacity to regenerate plants by somatic embryogenesis should make it possible to predict callus lines suitable to be used for multiplication. Further functional characterization of these markers opens up prospects for discovering specific AP2/ERF functions in the Hevea species for which somatic embryogenesis is difficult.

  2. Ranking candidate disease genes from gene expression and protein interaction: a Katz-centrality based approach.

    Directory of Open Access Journals (Sweden)

    Jing Zhao

    Full Text Available Many diseases have complex genetic causes, where a set of alleles can affect the propensity of getting the disease. The identification of such disease genes is important to understand the mechanistic and evolutionary aspects of pathogenesis, improve diagnosis and treatment of the disease, and aid in drug discovery. Current genetic studies typically identify chromosomal regions associated specific diseases. But picking out an unknown disease gene from hundreds of candidates located on the same genomic interval is still challenging. In this study, we propose an approach to prioritize candidate genes by integrating data of gene expression level, protein-protein interaction strength and known disease genes. Our method is based only on two, simple, biologically motivated assumptions--that a gene is a good disease-gene candidate if it is differentially expressed in cases and controls, or that it is close to other disease-gene candidates in its protein interaction network. We tested our method on 40 diseases in 58 gene expression datasets of the NCBI Gene Expression Omnibus database. On these datasets our method is able to predict unknown disease genes as well as identifying pleiotropic genes involved in the physiological cellular processes of many diseases. Our study not only provides an effective algorithm for prioritizing candidate disease genes but is also a way to discover phenotypic interdependency, cooccurrence and shared pathophysiology between different disorders.

  3. Avian cytochrome P450 (CYP 1-3 family genes: isoforms, evolutionary relationships, and mRNA expression in chicken liver.

    Directory of Open Access Journals (Sweden)

    Kensuke P Watanabe

    Full Text Available Cytochrome P450 (CYP of chicken and other avian species have been studied primarily with microsomes or characterized by cloning and protein expression. However, the overall existing isoforms in avian CYP1-3 families or dominant isoforms in avian xenobiotic metabolism have not yet been elucidated. In this study, we aimed to clarify and classify all of the existing isoforms of CYP1-3 in avian species using available genome assemblies for chicken, zebra finch, and turkey. Furthermore, we performed qRT-PCR assay to identify dominant CYP genes in chicken liver. Our results suggested that avian xenobiotic-metabolizing CYP genes have undergone unique evolution such as CYP2C and CYP3A genes, which have undergone avian-specific gene duplications. qRT-PCR experiments showed that CYP2C45 was the most highly expressed isoform in chicken liver, while CYP2C23b was the most highly induced gene by phenobarbital. Considering together with the result of further enzymatic characterization, CYP2C45 may have a dominant role in chicken xenobiotic metabolism due to the constitutive high expression levels, while CYP2C23a and CYP2C23b can be greatly induced by chicken xenobiotic receptor (CXR activators. These findings will provide not only novel insights into avian xenobiotic metabolism, but also a basis for the further characterization of each CYP gene.

  4. Light-Dependent Expression of Four Cryptic Archaeal Circadian Gene Homologs

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    Michael eManiscalco

    2014-03-01

    Full Text Available Circadian rhythms are important biological signals that have been found in almost all major groups of life from bacteria to man, yet it remains unclear if any members of the second major prokaryotic domain of life, the Archaea, also possess a biological clock. To investigate this question, we examined the regulation of four cyanobacterial-like circadian gene homologs present in the genome of the haloarchaeon Haloferax volcanii. These genes, designated cirA, cirB, cirC, and cirD, display similarity to the KaiC-family of cyanobacterial clock proteins, which act to regulate rhythmic gene expression and to control the timing of cell division. Quantitative RT-PCR analysis was used to examine the expression of each of the four cir genes in response to 12 h light/12 h dark cycles (LD 12:12 during balanced growth in H. volcanii. Our data reveal that there is an approximately two to sixteen-fold increase in cir gene expression when cells are shifted from light to constant darkness and this pattern of gene expression oscillates with the light conditions in a rhythmic manner. Targeted single- and double-gene knockouts in the H. volcanii cir genes results in disruption of light-dependent, rhythmic gene expression, although it does not lead to any significant effect on growth under these conditions. Restoration of light-dependent, rhythmic gene expression was demonstrated by introducing, in trans, a wild-type copy of individual cir genes into knockout strains. These results are noteworthy as this is the first attempt to characterize the transcriptional expression and regulation of the ubiquitous kaiC homologs found among archaeal genomes.

  5. Identification of differentially expressed genes in cutaneous squamous cell carcinoma by microarray expression profiling

    Directory of Open Access Journals (Sweden)

    Sterry Wolfram

    2006-08-01

    Full Text Available Abstract Background Carcinogenesis is a multi-step process indicated by several genes up- or down-regulated during tumor progression. This study examined and identified differentially expressed genes in cutaneous squamous cell carcinoma (SCC. Results Three different biopsies of 5 immunosuppressed organ-transplanted recipients each normal skin (all were pooled, actinic keratosis (AK (two were pooled, and invasive SCC and additionally 5 normal skin tissues from immunocompetent patients were analyzed. Thus, total RNA of 15 specimens were used for hybridization with Affymetrix HG-U133A microarray technology containing 22,283 genes. Data analyses were performed by prediction analysis of microarrays using nearest shrunken centroids with the threshold 3.5 and ANOVA analysis was independently performed in order to identify differentially expressed genes (p vs. AK and SCC were observed for 118 genes. Conclusion The majority of identified differentially expressed genes in cutaneous SCC were previously not described.

  6. Amplification biases: possible differences among deviating gene expressions

    Directory of Open Access Journals (Sweden)

    Piumi Francois

    2008-01-01

    Full Text Available Abstract Background Gene expression profiling has become a tool of choice to study pathological or developmental questions but in most cases the material is scarce and requires sample amplification. Two main procedures have been used: in vitro transcription (IVT and polymerase chain reaction (PCR, the former known as linear and the latter as exponential. Previous reports identified enzymatic pitfalls in PCR and IVT protocols; however the possible differences between the sequences affected by these amplification defaults were only rarely explored. Results Screening a bovine cDNA array dedicated to embryonic stages with embryonic (n = 3 and somatic tissues (n = 2, we proceeded to moderate amplifications starting from 1 μg of total RNA (global PCR or IVT one round. Whatever the tissue, 16% of the probes were involved in deviating gene expressions due to amplification defaults. These distortions were likely due to the molecular features of the affected sequences (position within a gene, GC content, hairpin number but also to the relative abundance of these transcripts within the tissues. These deviating genes mainly encoded housekeeping genes from physiological or cellular processes (70% and constituted 2 subsets which did not overlap (molecular features, signal intensities, gene ID. However, the differential expressions identified between embryonic stages were both reliable (minor intersect with biased expressions and relevant (biologically validated. In addition, the relative expression levels of those genes were biologically similar between amplified and unamplified samples. Conclusion Conversely to the most recent reports which challenged the use of intense amplification procedures on minute amounts of RNA, we chose moderate PCR and IVT amplifications for our gene profiling study. Conclusively, it appeared that systematic biases arose even with moderate amplification procedures, independently of (i the sample used: brain, ovary or embryos, (ii

  7. RNA preparation and characterization for gene expression studies

    DEFF Research Database (Denmark)

    Stangegaard, Michael

    2009-01-01

    Much information can be obtained from knowledge of the relative expression level of each gene in the transcriptome. With the current advances in technology as little as a single cell is required as starting material for gene expression experiments. The mRNA from a single cell may be linearly...

  8. Confidence in Phase Definition for Periodicity in Genes Expression Time Series.

    Science.gov (United States)

    El Anbari, Mohammed; Fadda, Abeer; Ptitsyn, Andrey

    2015-01-01

    Circadian oscillation in baseline gene expression plays an important role in the regulation of multiple cellular processes. Most of the knowledge of circadian gene expression is based on studies measuring gene expression over time. Our ability to dissect molecular events in time is determined by the sampling frequency of such experiments. However, the real peaks of gene activity can be at any time on or between the time points at which samples are collected. Thus, some genes with a peak activity near the observation point have their phase of oscillation detected with better precision then those which peak between observation time points. Separating genes for which we can confidently identify peak activity from ambiguous genes can improve the analysis of time series gene expression. In this study we propose a new statistical method to quantify the phase confidence of circadian genes. The numerical performance of the proposed method has been tested using three real gene expression data sets.

  9. Gene Expression Profile in the Early Stage of Angiotensin II-induced Cardiac Remodeling: a Time Series Microarray Study in a Mouse Model

    Directory of Open Access Journals (Sweden)

    Meng-Qiu Dang

    2015-01-01

    Full Text Available Background/Aims: Angiotensin II (Ang II plays a critical role in the cardiac remodeling contributing to heart failure. However, the gene expression profiles induced by Ang II in the early stage of cardiac remodeling remain unknown. Methods: Wild-type male mice (C57BL/6 background, 10-weeek-old were infused with Ang II (1500 ng/kg/min for 7 days. Blood pressure was measured. Cardiac function and remodeling were examined by echocardiography, H&E and Masson staining. The time series microarrays were then conducted to detected gene expression profiles. Results: Microarray results identified that 1,489 genes were differentially expressed in the hearts at day 1, 3 and 7 of Ang II injection. These genes were further classified into 26 profiles by hierarchical cluster analysis. Of them, 4 profiles were significant (No. 19, 8, 21 and 22 and contained 904 genes. Gene Ontology showed that these genes mainly participate in metabolic process, oxidation-reduction process, extracellular matrix organization, apoptotic process, immune response, and others. Significant pathways included focal adhesion, ECM-receptor interaction, cytokine-cytokine receptor interaction, MAPK and insulin signaling pathways, which were known to play important roles in Ang II-induced cardiac remodeling. Moreover, gene co-expression networks analysis suggested that serine/cysteine peptidase inhibitor, member 1 (Serpine1, also known as PAI-1 localized in the core of the network. Conclusions: Our results indicate that many genes are mainly involved in metabolism, inflammation, cardiac fibrosis and hypertrophy. Serpine1 may play a central role in the development of Ang II-induced cardiac remodeling at the early stage.

  10. Ethylene-Related Gene Expression Networks in Wood Formation

    Directory of Open Access Journals (Sweden)

    Carolin Seyfferth

    2018-03-01

    Full Text Available Thickening of tree stems is the result of secondary growth, accomplished by the meristematic activity of the vascular cambium. Secondary growth of the stem entails developmental cascades resulting in the formation of secondary phloem outwards and secondary xylem (i.e., wood inwards of the stem. Signaling and transcriptional reprogramming by the phytohormone ethylene modifies cambial growth and cell differentiation, but the molecular link between ethylene and secondary growth remains unknown. We addressed this shortcoming by analyzing expression profiles and co-expression networks of ethylene pathway genes using the AspWood transcriptome database which covers all stages of secondary growth in aspen (Populus tremula stems. ACC synthase expression suggests that the ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC is synthesized during xylem expansion and xylem cell maturation. Ethylene-mediated transcriptional reprogramming occurs during all stages of secondary growth, as deduced from AspWood expression profiles of ethylene-responsive genes. A network centrality analysis of the AspWood dataset identified EIN3D and 11 ERFs as hubs. No overlap was found between the co-expressed genes of the EIN3 and ERF hubs, suggesting target diversification and hence independent roles for these transcription factor families during normal wood formation. The EIN3D hub was part of a large co-expression gene module, which contained 16 transcription factors, among them several new candidates that have not been earlier connected to wood formation and a VND-INTERACTING 2 (VNI2 homolog. We experimentally demonstrated Populus EIN3D function in ethylene signaling in Arabidopsis thaliana. The ERF hubs ERF118 and ERF119 were connected on the basis of their expression pattern and gene co-expression module composition to xylem cell expansion and secondary cell wall formation, respectively. We hereby establish data resources for ethylene-responsive genes and

  11. Molecular subsets in the gene expression signatures of scleroderma skin.

    Directory of Open Access Journals (Sweden)

    Ausra Milano

    2008-07-01

    Full Text Available Scleroderma is a clinically heterogeneous disease with a complex phenotype. The disease is characterized by vascular dysfunction, tissue fibrosis, internal organ dysfunction, and immune dysfunction resulting in autoantibody production.We analyzed the genome-wide patterns of gene expression with DNA microarrays in skin biopsies from distinct scleroderma subsets including 17 patients with systemic sclerosis (SSc with diffuse scleroderma (dSSc, 7 patients with SSc with limited scleroderma (lSSc, 3 patients with morphea, and 6 healthy controls. 61 skin biopsies were analyzed in a total of 75 microarray hybridizations. Analysis by hierarchical clustering demonstrates nearly identical patterns of gene expression in 17 out of 22 of the forearm and back skin pairs of SSc patients. Using this property of the gene expression, we selected a set of 'intrinsic' genes and analyzed the inherent data-driven groupings. Distinct patterns of gene expression separate patients with dSSc from those with lSSc and both are easily distinguished from normal controls. Our data show three distinct patient groups among the patients with dSSc and two groups among patients with lSSc. Each group can be distinguished by unique gene expression signatures indicative of proliferating cells, immune infiltrates and a fibrotic program. The intrinsic groups are statistically significant (p<0.001 and each has been mapped to clinical covariates of modified Rodnan skin score, interstitial lung disease, gastrointestinal involvement, digital ulcers, Raynaud's phenomenon and disease duration. We report a 177-gene signature that is associated with severity of skin disease in dSSc.Genome-wide gene expression profiling of skin biopsies demonstrates that the heterogeneity in scleroderma can be measured quantitatively with DNA microarrays. The diversity in gene expression demonstrates multiple distinct gene expression programs in the skin of patients with scleroderma.

  12. Gene expression profiling reveals multiple toxicity endpoints induced by hepatotoxicants

    Energy Technology Data Exchange (ETDEWEB)

    Huang Qihong; Jin Xidong; Gaillard, Elias T.; Knight, Brian L.; Pack, Franklin D.; Stoltz, James H.; Jayadev, Supriya; Blanchard, Kerry T

    2004-05-18

    Microarray technology continues to gain increased acceptance in the drug development process, particularly at the stage of toxicology and safety assessment. In the current study, microarrays were used to investigate gene expression changes associated with hepatotoxicity, the most commonly reported clinical liability with pharmaceutical agents. Acetaminophen, methotrexate, methapyrilene, furan and phenytoin were used as benchmark compounds capable of inducing specific but different types of hepatotoxicity. The goal of the work was to define gene expression profiles capable of distinguishing the different subtypes of hepatotoxicity. Sprague-Dawley rats were orally dosed with acetaminophen (single dose, 4500 mg/kg for 6, 24 and 72 h), methotrexate (1 mg/kg per day for 1, 7 and 14 days), methapyrilene (100 mg/kg per day for 3 and 7 days), furan (40 mg/kg per day for 1, 3, 7 and 14 days) or phenytoin (300 mg/kg per day for 14 days). Hepatic gene expression was assessed using toxicology-specific gene arrays containing 684 target genes or expressed sequence tags (ESTs). Principal component analysis (PCA) of gene expression data was able to provide a clear distinction of each compound, suggesting that gene expression data can be used to discern different hepatotoxic agents and toxicity endpoints. Gene expression data were applied to the multiplicity-adjusted permutation test and significantly changed genes were categorized and correlated to hepatotoxic endpoints. Repression of enzymes involved in lipid oxidation (acyl-CoA dehydrogenase, medium chain, enoyl CoA hydratase, very long-chain acyl-CoA synthetase) were associated with microvesicular lipidosis. Likewise, subsets of genes associated with hepatotocellular necrosis, inflammation, hepatitis, bile duct hyperplasia and fibrosis have been identified. The current study illustrates that expression profiling can be used to: (1) distinguish different hepatotoxic endpoints; (2) predict the development of toxic endpoints; and

  13. Correlation of in vitro lymphocyte radiosensitivity and gene expression with late normal tissue reactions following curative radiotherapy for breast cancer

    International Nuclear Information System (INIS)

    Finnon, Paul; Kabacik, Sylwia; MacKay, Alan; Raffy, Claudine; A’Hern, Roger; Owen, Roger; Badie, Christophe; Yarnold, John; Bouffler, Simon

    2012-01-01

    Background and purpose: Identification of mechanisms of late normal tissue responses to curative radiotherapy that discriminate individuals with marked or mild responses would aid response prediction. This study aimed to identify differences in gene expression, apoptosis, residual DNA double strand breaks and chromosomal damage after in vitro irradiation of lymphocytes in a series of patients with marked (31 cases) or mild (28 controls) late adverse reaction to adjuvant breast radiotherapy. Materials and methods: Gene expression arrays, residual γH2AX, apoptosis, G2 chromosomal radiosensitivity and G0 micronucleus assay were used to compare case and control lymphocyte radiation responses. Results: Five hundred and thirty genes were up-regulated and 819 down-regulated by ionising radiation. Irradiated samples were identified with an overall cross-validated error rate of 3.4%. Prediction analyses to classify cases and controls using unirradiated (0 Gy), irradiated (4 Gy) or radiation response (4–0 Gy) expression profiles correctly identified samples with, respectively, 25%, 22% or 18.5% error rates. Significant inter-sample variation was observed for all cellular endpoints but cases and controls could not be distinguished. Conclusions: Variation in lymphocyte radiosensitivity does not necessarily correlate with normal tissue response to radiotherapy. Gene expression analysis can predict of radiation exposure and may in the future help prediction of normal tissue radiosensitivity.

  14. Serial Expression Analysis: a web tool for the analysis of serial gene expression data

    Science.gov (United States)

    Nueda, Maria José; Carbonell, José; Medina, Ignacio; Dopazo, Joaquín; Conesa, Ana

    2010-01-01

    Serial transcriptomics experiments investigate the dynamics of gene expression changes associated with a quantitative variable such as time or dosage. The statistical analysis of these data implies the study of global and gene-specific expression trends, the identification of significant serial changes, the comparison of expression profiles and the assessment of transcriptional changes in terms of cellular processes. We have created the SEA (Serial Expression Analysis) suite to provide a complete web-based resource for the analysis of serial transcriptomics data. SEA offers five different algorithms based on univariate, multivariate and functional profiling strategies framed within a user-friendly interface and a project-oriented architecture to facilitate the analysis of serial gene expression data sets from different perspectives. SEA is available at sea.bioinfo.cipf.es. PMID:20525784

  15. Genome polymorphism markers and stress genes expression for ...

    African Journals Online (AJOL)

    SAM

    2014-06-11

    Jun 11, 2014 ... RNA extraction and purification for SOD and PAL gene expression. Fresh leaf tissues (100 mg), from ... Data analysis. Gelquant program for quantification of protein, DNA and RNA gel. (version 1.8.2) was used for .... by reprogramming the expression of endogenous genes. Higher level of these antioxidant ...

  16. Transgenic Arabidopsis Gene Expression System

    Science.gov (United States)

    Ferl, Robert; Paul, Anna-Lisa

    2009-01-01

    The Transgenic Arabidopsis Gene Expression System (TAGES) investigation is one in a pair of investigations that use the Advanced Biological Research System (ABRS) facility. TAGES uses Arabidopsis thaliana, thale cress, with sensor promoter-reporter gene constructs that render the plants as biomonitors (an organism used to determine the quality of the surrounding environment) of their environment using real-time nondestructive Green Fluorescent Protein (GFP) imagery and traditional postflight analyses.

  17. Expression of an Msx homeobox gene in ascidians: insights into the archetypal chordate expression pattern.

    Science.gov (United States)

    Ma, L; Swalla, B J; Zhou, J; Dobias, S L; Bell, J R; Chen, J; Maxson, R E; Jeffery, W R

    1996-03-01

    The Msx homeobox genes are expressed in complex patterns during vertebrate development in conjunction with inductive tissue interactions. As a means of understanding the archetypal role of Msx genes in chordates, we have isolated and characterized an Msx gene in ascidians, protochordates with a relatively simple body plan. The Mocu Msx-a and McMsx-a genes, isolated from the ascidians Molgula oculata and Molgula citrina, respectively, have homeodomains that place them in the msh-like subclass of Msx genes. Therefore, the Molgula Msx-a genes are most closely related to the msh genes previously identified in a number of invertebrates. Southern blot analysis suggests that there are one or two copies of the Msx-a gene in the Molgula genome. Northern blot and RNase protection analysis indicate that Msx-a transcripts are restricted to the developmental stages of the life cycle. In situ hybridization showed that Msx-a mRNA first appears just before gastrulation in the mesoderm (presumptive notochord and muscle) and ectoderm (neural plate) cells. Transcript levels decline in mesoderm cells after the completion of gastrulation, but are enhanced in the folding neural plate during neurulation. Later, Msx-a mRNA is also expressed in the posterior ectoderm and in a subset of the tail muscle cells. The ectoderm and mesoderm cells that express Msx-a are undergoing morphogenetic movements during gastrulation, neurulation, and tail formation. Msx-a expression ceases after these cells stop migrating. The ascidian M. citrina, in which adult tissues and organs begin to develop precociously in the larva, was used to study Msx-a expression during adult development. Msx-a transcripts are expressed in the heart primordium and the rudiments of the ampullae, epidermal protrusions with diverse functions in the juvenile. The heart and ampullae develop in regions where mesenchyme cells interact with endodermal or epidermal epithelia. A comparison of the expression patterns of the Molgula genes

  18. TiGER: a database for tissue-specific gene expression and regulation.

    Science.gov (United States)

    Liu, Xiong; Yu, Xueping; Zack, Donald J; Zhu, Heng; Qian, Jiang

    2008-06-09

    Understanding how genes are expressed and regulated in different tissues is a fundamental and challenging question. However, most of currently available biological databases do not focus on tissue-specific gene regulation. The recent development of computational methods for tissue-specific combinational gene regulation, based on transcription factor binding sites, enables us to perform a large-scale analysis of tissue-specific gene regulation in human tissues. The results are stored in a web database called TiGER (Tissue-specific Gene Expression and Regulation). The database contains three types of data including tissue-specific gene expression profiles, combinatorial gene regulations, and cis-regulatory module (CRM) detections. At present the database contains expression profiles for 19,526 UniGene genes, combinatorial regulations for 7,341 transcription factor pairs and 6,232 putative CRMs for 2,130 RefSeq genes. We have developed and made publicly available a database, TiGER, which summarizes and provides large scale data sets for tissue-specific gene expression and regulation in a variety of human tissues. This resource is available at 1.

  19. TiGER: A database for tissue-specific gene expression and regulation

    Directory of Open Access Journals (Sweden)

    Zack Donald J

    2008-06-01

    Full Text Available Abstract Background Understanding how genes are expressed and regulated in different tissues is a fundamental and challenging question. However, most of currently available biological databases do not focus on tissue-specific gene regulation. Results The recent development of computational methods for tissue-specific combinational gene regulation, based on transcription factor binding sites, enables us to perform a large-scale analysis of tissue-specific gene regulation in human tissues. The results are stored in a web database called TiGER (Tissue-specific Gene Expression and Regulation. The database contains three types of data including tissue-specific gene expression profiles, combinatorial gene regulations, and cis-regulatory module (CRM detections. At present the database contains expression profiles for 19,526 UniGene genes, combinatorial regulations for 7,341 transcription factor pairs and 6,232 putative CRMs for 2,130 RefSeq genes. Conclusion We have developed and made publicly available a database, TiGER, which summarizes and provides large scale data sets for tissue-specific gene expression and regulation in a variety of human tissues. This resource is available at 1.

  20. Characterization of the global profile of genes expressed in cervical epithelium by Serial Analysis of Gene Expression (SAGE

    Directory of Open Access Journals (Sweden)

    Piña-Sanchez Patricia

    2005-09-01

    Full Text Available Abstract Background Serial Analysis of Gene Expression (SAGE is a new technique that allows a detailed and profound quantitative and qualitative knowledge of gene expression profile, without previous knowledge of sequence of analyzed genes. We carried out a modification of SAGE methodology (microSAGE, useful for the analysis of limited quantities of tissue samples, on normal human cervical tissue obtained from a donor without histopathological lesions. Cervical epithelium is constituted mainly by cervical keratinocytes which are the targets of human papilloma virus (HPV, where persistent HPV infection of cervical epithelium is associated with an increase risk for developing cervical carcinomas (CC. Results We report here a transcriptome analysis of cervical tissue by SAGE, derived from 30,418 sequenced tags that provide a wealth of information about the gene products involved in normal cervical epithelium physiology, as well as genes not previously found in uterine cervix tissue involved in the process of epidermal differentiation. Conclusion This first comprehensive and profound analysis of uterine cervix transcriptome, should be useful for the identification of genes involved in normal cervix uterine function, and candidate genes associated with cervical carcinoma.

  1. Transcriptome sequencing and differential gene expression analysis in Viola yedoensis Makino (Fam. Violaceae) responsive to cadmium (Cd) pollution

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Jian [Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Ministry of Agriculture, Maize Research Institute of Sichuan Agricultural University, Wenjiang, Sichuan (China); Luo, Mao [Drug Discovery Research Center of Luzhou Medical College, Luzhou, Sichuan (China); Zhu, Ye; He, Ying; Wang, Qin [Department of Pharmacy of Luzhou Medical College, Luzhou, Sichuan (China); Zhang, Chun, E-mail: zc83good@126.com [Department of Pharmacy of Luzhou Medical College, Luzhou, Sichuan (China)

    2015-03-27

    Viola yedoensis Makino is an important Chinese traditional medicine plant adapted to cadmium (Cd) pollution regions. Illumina sequencing technology was used to sequence the transcriptome of V. yedoensis Makino. We sequenced Cd-treated (VIYCd) and untreated (VIYCK) samples of V. yedoensis, and obtained 100,410,834 and 83,587,676 high quality reads, respectively. After de novo assembly and quantitative assessment, 109,800 unigenes were finally generated with an average length of 661 bp. We then obtained functional annotations by aligning unigenes with public protein databases including NR, NT, SwissProt, KEGG and COG. In addition, 892 differentially expressed genes (DEGs) were investigated between the two libraries of untreated (VIYCK) and Cd-treated (VIYCd) plants. Moreover, 15 randomly selected DEGs were further validated with qRT-PCR and the results were highly accordant with the Solexa analysis. This study firstly generated a successful global analysis of the V. yedoensis transcriptome and it will provide for further studies on gene expression, genomics, and functional genomics in Violaceae. - Highlights: • A de novo assembly generated 109,800 unigenes and 5,4479 of them were annotated. • 31,285 could be classified into 26 COG categories. • 263 biosynthesis pathways were predicted and classified into five categories. • 892 DEGs were detected and 15 of them were validated by qRT-PCR.

  2. Transcriptome sequencing and differential gene expression analysis in Viola yedoensis Makino (Fam. Violaceae) responsive to cadmium (Cd) pollution

    International Nuclear Information System (INIS)

    Gao, Jian; Luo, Mao; Zhu, Ye; He, Ying; Wang, Qin; Zhang, Chun

    2015-01-01

    Viola yedoensis Makino is an important Chinese traditional medicine plant adapted to cadmium (Cd) pollution regions. Illumina sequencing technology was used to sequence the transcriptome of V. yedoensis Makino. We sequenced Cd-treated (VIYCd) and untreated (VIYCK) samples of V. yedoensis, and obtained 100,410,834 and 83,587,676 high quality reads, respectively. After de novo assembly and quantitative assessment, 109,800 unigenes were finally generated with an average length of 661 bp. We then obtained functional annotations by aligning unigenes with public protein databases including NR, NT, SwissProt, KEGG and COG. In addition, 892 differentially expressed genes (DEGs) were investigated between the two libraries of untreated (VIYCK) and Cd-treated (VIYCd) plants. Moreover, 15 randomly selected DEGs were further validated with qRT-PCR and the results were highly accordant with the Solexa analysis. This study firstly generated a successful global analysis of the V. yedoensis transcriptome and it will provide for further studies on gene expression, genomics, and functional genomics in Violaceae. - Highlights: • A de novo assembly generated 109,800 unigenes and 5,4479 of them were annotated. • 31,285 could be classified into 26 COG categories. • 263 biosynthesis pathways were predicted and classified into five categories. • 892 DEGs were detected and 15 of them were validated by qRT-PCR

  3. Gene expression analysis of interferon-beta treatment in multiple sclerosis

    DEFF Research Database (Denmark)

    Sellebjerg, F.; Datta, P.; Larsen, J.

    2008-01-01

    by treatment with IFN-beta. We use DNA microarrays to study gene expression in 10 multiple sclerosis (MS) patients who began de novo treatment with IFN-beta. After the first injection of IFN-beta, the expression of 74 out of 3428 genes changed at least two-fold and statistically significantly (after Bonferroni......Treatment with interferon-beta (IFN-beta) induces the expression of hundreds of genes in blood mononuclear cells, and the expression of several genes has been proposed as a marker of the effect of treatment with IFN-beta. However, to date no molecules have been identified that are stably induced...

  4. Expression of Fox genes in the cephalochordate Branchiostoma lanceolatum

    Directory of Open Access Journals (Sweden)

    Daniel eAldea

    2015-07-01

    Full Text Available Forkhead box (Fox genes code for transcription factors that play important roles in different biological processes. They are found in a wide variety of organisms and appeared in unicellular eukaryotes. In metazoans, the gene family includes many members that can be subdivided into 24 classes. Cephalochordates are key organisms to understand the functional evolution of gene families in the chordate lineage due to their phylogenetic position as an early divergent chordate, their simple anatomy and genome structure. In the genome of the cephalochordate amphioxus Branchiostoma floridae, 32 Fox genes were identified, with at least one member for each of the classes that were present in the ancestor of bilaterians. In this work we describe the expression pattern of 13 of these genes during the embryonic development of the Mediterranean amphioxus, Branchiostoma lanceolatum. We found that FoxK and FoxM genes present an ubiquitous expression while all the others show specific expression patterns restricted to diverse embryonic territories. Many of these expression patterns are conserved with vertebrates, suggesting that the main functions of Fox genes in chordates were present in their common ancestor.

  5. Gene Expression and the Diversity of Identified Neurons

    OpenAIRE

    Buck, L.; Stein, R.; Palazzolo, M.; Anderson, D. J.; Axel, R.

    1983-01-01

    Nervous systems consist of diverse populations of neurons that are anatomically and functionally distinct. The diversity of neurons and the precision with which they are interconnected suggest that specific genes or sets of genes are activated in some neurons but not expressed in others. Experimentally, this problem may be considered at two levels. First, what is the total number of genes expressed in the brain, and how are they distributed among the different populations of neurons? Second, ...

  6. The evolution of gene expression QTL in Saccharomyces cerevisiae.

    Directory of Open Access Journals (Sweden)

    James Ronald

    2007-08-01

    Full Text Available Understanding the evolutionary forces that influence patterns of gene expression variation will provide insights into the mechanisms of evolutionary change and the molecular basis of phenotypic diversity. To date, studies of gene expression evolution have primarily been made by analyzing how gene expression levels vary within and between species. However, the fundamental unit of heritable variation in transcript abundance is the underlying regulatory allele, and as a result it is necessary to understand gene expression evolution at the level of DNA sequence variation. Here we describe the evolutionary forces shaping patterns of genetic variation for 1206 cis-regulatory QTL identified in a cross between two divergent strains of Saccharomyces cerevisiae. We demonstrate that purifying selection against mildly deleterious alleles is the dominant force governing cis-regulatory evolution in S. cerevisiae and estimate the strength of selection. We also find that essential genes and genes with larger codon bias are subject to slightly stronger cis-regulatory constraint and that positive selection has played a role in the evolution of major trans-acting QTL.

  7. Bovine mammary gene expression profiling during the onset of lactation.

    Directory of Open Access Journals (Sweden)

    Yuanyuan Gao

    Full Text Available BACKGROUND: Lactogenesis includes two stages. Stage I begins a few weeks before parturition. Stage II is initiated around the time of parturition and extends for several days afterwards. METHODOLOGY/PRINCIPAL FINDINGS: To better understand the molecular events underlying these changes, genome-wide gene expression profiling was conducted using digital gene expression (DGE on bovine mammary tissue at three time points (on approximately day 35 before parturition (-35 d, day 7 before parturition (-7 d and day 3 after parturition (+3 d. Approximately 6.2 million (M, 5.8 million (M and 6.1 million (M 21-nt cDNA tags were sequenced in the three cDNA libraries (-35 d, -7 d and +3 d, respectively. After aligning to the reference sequences, the three cDNA libraries included 8,662, 8,363 and 8,359 genes, respectively. With a fold change cutoff criteria of ≥ 2 or ≤-2 and a false discovery rate (FDR of ≤ 0.001, a total of 812 genes were significantly differentially expressed at -7 d compared with -35 d (stage I. Gene ontology analysis showed that those significantly differentially expressed genes were mainly associated with cell cycle, lipid metabolism, immune response and biological adhesion. A total of 1,189 genes were significantly differentially expressed at +3 d compared with -7 d (stage II, and these genes were mainly associated with the immune response and cell cycle. Moreover, there were 1,672 genes significantly differentially expressed at +3 d compared with -35 d. Gene ontology analysis showed that the main differentially expressed genes were those associated with metabolic processes. CONCLUSIONS: The results suggest that the mammary gland begins to lactate not only by a gain of function but also by a broad suppression of function to effectively push most of the cell's resources towards lactation.

  8. Whole-body gene expression pattern registration in Platynereis larvae.

    Science.gov (United States)

    Asadulina, Albina; Panzera, Aurora; Verasztó, Csaba; Liebig, Christian; Jékely, Gáspár

    2012-12-03

    Digital anatomical atlases are increasingly used in order to depict different gene expression patterns and neuronal morphologies within a standardized reference template. In evo-devo, a discipline in which the comparison of gene expression patterns is a widely used approach, such standardized anatomical atlases would allow a more rigorous assessment of the conservation of and changes in gene expression patterns during micro- and macroevolutionary time scales. Due to its small size and invariant early development, the annelid Platynereis dumerilii is particularly well suited for such studies. Recently a reference template with registered gene expression patterns has been generated for the anterior part (episphere) of the Platynereis trochophore larva and used for the detailed study of neuronal development. Here we introduce and evaluate a method for whole-body gene expression pattern registration for Platynereis trochophore and nectochaete larvae based on whole-mount in situ hybridization, confocal microscopy, and image registration. We achieved high-resolution whole-body scanning using the mounting medium 2,2'-thiodiethanol (TDE), which allows the matching of the refractive index of the sample to that of glass and immersion oil thereby reducing spherical aberration and improving depth penetration. This approach allowed us to scan entire whole-mount larvae stained with nitroblue tetrazolium/5-bromo-4-chloro-3-indolyl phosphate (NBT/BCIP) in situ hybridization and counterstained fluorescently with an acetylated-tubulin antibody and the nuclear stain 4'6-diamidino-2-phenylindole (DAPI). Due to the submicron isotropic voxel size whole-mount larvae could be scanned in any orientation. Based on the whole-body scans, we generated four different reference templates by the iterative registration and averaging of 40 individual image stacks using either the acetylated-tubulin or the nuclear-stain signal for each developmental stage. We then registered to these templates the

  9. Whole-body gene expression pattern registration in Platynereis larvae

    Directory of Open Access Journals (Sweden)

    Asadulina Albina

    2012-12-01

    Full Text Available Abstract Background Digital anatomical atlases are increasingly used in order to depict different gene expression patterns and neuronal morphologies within a standardized reference template. In evo-devo, a discipline in which the comparison of gene expression patterns is a widely used approach, such standardized anatomical atlases would allow a more rigorous assessment of the conservation of and changes in gene expression patterns during micro- and macroevolutionary time scales. Due to its small size and invariant early development, the annelid Platynereis dumerilii is particularly well suited for such studies. Recently a reference template with registered gene expression patterns has been generated for the anterior part (episphere of the Platynereis trochophore larva and used for the detailed study of neuronal development. Results Here we introduce and evaluate a method for whole-body gene expression pattern registration for Platynereis trochophore and nectochaete larvae based on whole-mount in situ hybridization, confocal microscopy, and image registration. We achieved high-resolution whole-body scanning using the mounting medium 2,2’-thiodiethanol (TDE, which allows the matching of the refractive index of the sample to that of glass and immersion oil thereby reducing spherical aberration and improving depth penetration. This approach allowed us to scan entire whole-mount larvae stained with nitroblue tetrazolium/5-bromo-4-chloro-3-indolyl phosphate (NBT/BCIP in situ hybridization and counterstained fluorescently with an acetylated-tubulin antibody and the nuclear stain 4’6-diamidino-2-phenylindole (DAPI. Due to the submicron isotropic voxel size whole-mount larvae could be scanned in any orientation. Based on the whole-body scans, we generated four different reference templates by the iterative registration and averaging of 40 individual image stacks using either the acetylated-tubulin or the nuclear-stain signal for each developmental

  10. VE-Cadherin-Mediated Epigenetic Regulation of Endothelial Gene Expression.

    Science.gov (United States)

    Morini, Marco F; Giampietro, Costanza; Corada, Monica; Pisati, Federica; Lavarone, Elisa; Cunha, Sara I; Conze, Lei L; O'Reilly, Nicola; Joshi, Dhira; Kjaer, Svend; George, Roger; Nye, Emma; Ma, Anqi; Jin, Jian; Mitter, Richard; Lupia, Michela; Cavallaro, Ugo; Pasini, Diego; Calado, Dinis P; Dejana, Elisabetta; Taddei, Andrea

    2018-01-19

    The mechanistic foundation of vascular maturation is still largely unknown. Several human pathologies are characterized by deregulated angiogenesis and unstable blood vessels. Solid tumors, for instance, get their nourishment from newly formed structurally abnormal vessels which present wide and irregular interendothelial junctions. Expression and clustering of the main endothelial-specific adherens junction protein, VEC (vascular endothelial cadherin), upregulate genes with key roles in endothelial differentiation and stability. We aim at understanding the molecular mechanisms through which VEC triggers the expression of a set of genes involved in endothelial differentiation and vascular stabilization. We compared a VEC-null cell line with the same line reconstituted with VEC wild-type cDNA. VEC expression and clustering upregulated endothelial-specific genes with key roles in vascular stabilization including claudin-5 , vascular endothelial-protein tyrosine phosphatase ( VE-PTP ), and von Willebrand factor ( vWf ). Mechanistically, VEC exerts this effect by inhibiting polycomb protein activity on the specific gene promoters. This is achieved by preventing nuclear translocation of FoxO1 (Forkhead box protein O1) and β-catenin, which contribute to PRC2 (polycomb repressive complex-2) binding to promoter regions of claudin-5 , VE-PTP , and vWf . VEC/β-catenin complex also sequesters a core subunit of PRC2 (Ezh2 [enhancer of zeste homolog 2]) at the cell membrane, preventing its nuclear translocation. Inhibition of Ezh2/VEC association increases Ezh2 recruitment to claudin-5 , VE-PTP , and vWf promoters, causing gene downregulation. RNA sequencing comparison of VEC-null and VEC-positive cells suggested a more general role of VEC in activating endothelial genes and triggering a vascular stability-related gene expression program. In pathological angiogenesis of human ovarian carcinomas, reduced VEC expression paralleled decreased levels of claudin-5 and VE-PTP. These

  11. Frequency-based time-series gene expression recomposition using PRIISM

    Directory of Open Access Journals (Sweden)

    Rosa Bruce A

    2012-06-01

    Full Text Available Abstract Background Circadian rhythm pathways influence the expression patterns of as much as 31% of the Arabidopsis genome through complicated interaction pathways, and have been found to be significantly disrupted by biotic and abiotic stress treatments, complicating treatment-response gene discovery methods due to clock pattern mismatches in the fold change-based statistics. The PRIISM (Pattern Recomposition for the Isolation of Independent Signals in Microarray data algorithm outlined in this paper is designed to separate pattern changes induced by different forces, including treatment-response pathways and circadian clock rhythm disruptions. Results Using the Fourier transform, high-resolution time-series microarray data is projected to the frequency domain. By identifying the clock frequency range from the core circadian clock genes, we separate the frequency spectrum to different sections containing treatment-frequency (representing up- or down-regulation by an adaptive treatment response, clock-frequency (representing the circadian clock-disruption response and noise-frequency components. Then, we project the components’ spectra back to the expression domain to reconstruct isolated, independent gene expression patterns representing the effects of the different influences. By applying PRIISM on a high-resolution time-series Arabidopsis microarray dataset under a cold treatment, we systematically evaluated our method using maximum fold change and principal component analyses. The results of this study showed that the ranked treatment-frequency fold change results produce fewer false positives than the original methodology, and the 26-hour timepoint in our dataset was the best statistic for distinguishing the most known cold-response genes. In addition, six novel cold-response genes were discovered. PRIISM also provides gene expression data which represents only circadian clock influences, and may be useful for circadian clock studies

  12. Muscle gene expression patterns in human rotator cuff pathology.

    Science.gov (United States)

    Choo, Alexander; McCarthy, Meagan; Pichika, Rajeswari; Sato, Eugene J; Lieber, Richard L; Schenk, Simon; Lane, John G; Ward, Samuel R

    2014-09-17

    Rotator cuff pathology is a common source of shoulder pain with variable etiology and pathoanatomical characteristics. Pathological processes of fatty infiltration, muscle atrophy, and fibrosis have all been invoked as causes for poor outcomes after rotator cuff tear repair. The aims of this study were to measure the expression of key genes associated with adipogenesis, myogenesis, and fibrosis in human rotator cuff muscle after injury and to compare the expression among groups of patients with varied severities of rotator cuff pathology. Biopsies of the supraspinatus muscle were obtained arthroscopically from twenty-seven patients in the following operative groups: bursitis (n = 10), tendinopathy (n = 7), full-thickness rotator cuff tear (n = 8), and massive rotator cuff tear (n = 2). Quantitative polymerase chain reaction (qPCR) was performed to characterize gene expression pathways involved in myogenesis, adipogenesis, and fibrosis. Patients with a massive tear demonstrated downregulation of the fibrogenic, adipogenic, and myogenic genes, indicating that the muscle was not in a state of active change and may have difficulty responding to stimuli. Patients with a full-thickness tear showed upregulation of fibrotic and adipogenic genes; at the tissue level, these correspond to the pathologies most detrimental to outcomes of surgical repair. Patients with bursitis or tendinopathy still expressed myogenic genes, indicating that the muscle may be attempting to accommodate the mechanical deficiencies induced by the tendon tear. Gene expression in human rotator cuff muscles varied according to tendon injury severity. Patients with bursitis and tendinopathy appeared to be expressing pro-myogenic genes, whereas patients with a full-thickness tear were expressing genes associated with fatty atrophy and fibrosis. In contrast, patients with a massive tear appeared to have downregulation of all gene programs except inhibition of myogenesis. These data highlight the

  13. Expression of KLK2 gene in prostate cancer

    Directory of Open Access Journals (Sweden)

    Sajad Shafai

    2018-01-01

    Conclusion: The expression of KLK2 gene in people with prostate cancer is the higher than the healthy person; finally, according to the results, it could be mentioned that the KLK2 gene considered as a useful factor in prostate cancer, whose expression is associated with progression and development of the prostate cancer.

  14. The evolution of gene expression levels in mammalian organs

    DEFF Research Database (Denmark)

    Brawand, David; Soumillon, Magali; Necsulea, Anamaria

    2011-01-01

    and chromosomes, owing to differences in selective pressures: transcriptome change was slow in nervous tissues and rapid in testes, slower in rodents than in apes and monotremes, and rapid for the X chromosome right after its formation. Although gene expression evolution in mammals was strongly shaped......Changes in gene expression are thought to underlie many of the phenotypic differences between species. However, large-scale analyses of gene expression evolution were until recently prevented by technological limitations. Here we report the sequencing of polyadenylated RNA from six organs across...... ten species that represent all major mammalian lineages (placentals, marsupials and monotremes) and birds (the evolutionary outgroup), with the goal of understanding the dynamics of mammalian transcriptome evolution. We show that the rate of gene expression evolution varies among organs, lineages...

  15. Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Xi Wang

    2015-05-01

    Full Text Available Kashin-Beck Disease (KBD is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published gene expression profile data on cartilage and peripheral blood mononuclear cells (PBMCs from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A gene expression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR algorithm and support vector machine (SVM algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD.

  16. Expression regulation of design process gene in product design

    DEFF Research Database (Denmark)

    Li, Bo; Fang, Lusheng; Li, Bo

    2011-01-01

    To improve the design process efficiency, this paper proposes the principle and methodology that design process gene controls the characteristics of design process under the framework of design process reuse and optimization based on design process gene. First, the concept of design process gene...... is proposed and analyzed, as well as its three categories i.e., the operator gene, the structural gene and the regulator gene. Second, the trigger mechanism that design objectives and constraints trigger the operator gene is constructed. Third, the expression principle of structural gene is analyzed...... with the example of design management gene. Last, the regulation mode that the regulator gene regulates the expression of the structural gene is established and it is illustrated by taking the design process management gene as an example. © (2011) Trans Tech Publications....

  17. Stochastic fluctuations and distributed control of gene expression impact cellular memory.

    Directory of Open Access Journals (Sweden)

    Guillaume Corre

    Full Text Available Despite the stochastic noise that characterizes all cellular processes the cells are able to maintain and transmit to their daughter cells the stable level of gene expression. In order to better understand this phenomenon, we investigated the temporal dynamics of gene expression variation using a double reporter gene model. We compared cell clones with transgenes coding for highly stable mRNA and fluorescent proteins with clones expressing destabilized mRNA-s and proteins. Both types of clones displayed strong heterogeneity of reporter gene expression levels. However, cells expressing stable gene products produced daughter cells with similar level of reporter proteins, while in cell clones with short mRNA and protein half-lives the epigenetic memory of the gene expression level was completely suppressed. Computer simulations also confirmed the role of mRNA and protein stability in the conservation of constant gene expression levels over several cell generations. These data indicate that the conservation of a stable phenotype in a cellular lineage may largely depend on the slow turnover of mRNA-s and proteins.

  18. Novel redox nanomedicine improves gene expression of polyion complex vector

    Directory of Open Access Journals (Sweden)

    Kazuko Toh, Toru Yoshitomi, Yutaka Ikeda and Yukio Nagasaki

    2011-01-01

    Full Text Available Gene therapy has generated worldwide attention as a new medical technology. While non-viral gene vectors are promising candidates as gene carriers, they have several issues such as toxicity and low transfection efficiency. We have hypothesized that the generation of reactive oxygen species (ROS affects gene expression in polyplex supported gene delivery systems. The effect of ROS on the gene expression of polyplex was evaluated using a nitroxide radical-containing nanoparticle (RNP as an ROS scavenger. When polyethyleneimine (PEI/pGL3 or PEI alone was added to the HeLa cells, ROS levels increased significantly. In contrast, when (PEI/pGL3 or PEI was added with RNP, the ROS levels were suppressed. The luciferase expression was increased by the treatment with RNP in a dose-dependent manner and the cellular uptake of pDNA was also increased. Inflammatory cytokines play an important role in ROS generation in vivo. In particular, tumor necrosis factor (TNF-α caused intracellular ROS generation in HeLa cells and decreased gene expression. RNP treatment suppressed ROS production even in the presence of TNF-α and increased gene expression. This anti-inflammatory property of RNP suggests that it may be used as an effective adjuvant for non-viral gene delivery systems.

  19. Effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies

    Science.gov (United States)

    2014-01-01

    Expression quantitative trait loci (eQTL) mapping is a tool that can systematically identify genetic variation affecting gene expression. eQTL mapping studies have shown that certain genomic locations, referred to as regulatory hotspots, may affect the expression levels of many genes. Recently, studies have shown that various confounding factors may induce spurious regulatory hotspots. Here, we introduce a novel statistical method that effectively eliminates spurious hotspots while retaining genuine hotspots. Applied to simulated and real datasets, we validate that our method achieves greater sensitivity while retaining low false discovery rates compared to previous methods. PMID:24708878

  20. Regulation of methane genes and genome expression

    Energy Technology Data Exchange (ETDEWEB)

    John N. Reeve

    2009-09-09

    At the start of this project, it was known that methanogens were Archaeabacteria (now Archaea) and were therefore predicted to have gene expression and regulatory systems different from Bacteria, but few of the molecular biology details were established. The goals were then to establish the structures and organizations of genes in methanogens, and to develop the genetic technologies needed to investigate and dissect methanogen gene expression and regulation in vivo. By cloning and sequencing, we established the gene and operon structures of all of the “methane” genes that encode the enzymes that catalyze methane biosynthesis from carbon dioxide and hydrogen. This work identified unique sequences in the methane gene that we designated mcrA, that encodes the largest subunit of methyl-coenzyme M reductase, that could be used to identify methanogen DNA and establish methanogen phylogenetic relationships. McrA sequences are now the accepted standard and used extensively as hybridization probes to identify and quantify methanogens in environmental research. With the methane genes in hand, we used northern blot and then later whole-genome microarray hybridization analyses to establish how growth phase and substrate availability regulated methane gene expression in Methanobacterium thermautotrophicus ΔH (now Methanothermobacter thermautotrophicus). Isoenzymes or pairs of functionally equivalent enzymes catalyze several steps in the hydrogen-dependent reduction of carbon dioxide to methane. We established that hydrogen availability determine which of these pairs of methane genes is expressed and therefore which of the alternative enzymes is employed to catalyze methane biosynthesis under different environmental conditions. As were unable to establish a reliable genetic system for M. thermautotrophicus, we developed in vitro transcription as an alternative system to investigate methanogen gene expression and regulation. This led to the discovery that an archaeal protein