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Sample records for gene expression classifiers

  1. Gene-expression Classifier in Papillary Thyroid Carcinoma

    DEFF Research Database (Denmark)

    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...

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

    Science.gov (United States)

    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.

  3. 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.

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

    Science.gov (United States)

    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.

  5. 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.

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

    Science.gov (United States)

    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

  7. Identification of novel predictor classifiers for inflammatory bowel disease by gene expression profiling.

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    Trinidad Montero-Meléndez

    Full Text Available BACKGROUND: Improvement of patient quality of life is the ultimate goal of biomedical research, particularly when dealing with complex, chronic and debilitating conditions such as inflammatory bowel disease (IBD. This is largely dependent on receiving an accurate and rapid diagnose, an effective treatment and in the prediction and prevention of side effects and complications. The low sensitivity and specificity of current markers burden their general use in the clinical practice. New biomarkers with accurate predictive ability are needed to achieve a personalized approach that take the inter-individual differences into consideration. METHODS: We performed a high throughput approach using microarray gene expression profiling of colon pinch biopsies from IBD patients to identify predictive transcriptional signatures associated with intestinal inflammation, differential diagnosis (Crohn's disease or ulcerative colitis, response to glucocorticoids (resistance and dependence or prognosis (need for surgery. Class prediction was performed with self-validating Prophet software package. RESULTS: Transcriptional profiling divided patients in two subgroups that associated with degree of inflammation. Class predictors were identified with predictive accuracy ranging from 67 to 100%. The expression accuracy was confirmed by real time-PCR quantification. Functional analysis of the predictor genes showed that they play a role in immune responses to bacteria (PTN, OLFM4 and LILRA2, autophagy and endocytocis processes (ATG16L1, DNAJC6, VPS26B, RABGEF1, ITSN1 and TMEM127 and glucocorticoid receptor degradation (STS and MMD2. CONCLUSIONS: We conclude that using analytical algorithms for class prediction discovery can be useful to uncover gene expression profiles and identify classifier genes with potential stratification utility of IBD patients, a major step towards personalized therapy.

  8. Swarm Intelligence Approach Based on Adaptive ELM Classifier with ICGA Selection for Microarray Gene Expression and Cancer Classification

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    T. Karthikeyan

    2014-05-01

    Full Text Available The aim of this research study is based on efficient gene selection and classification of microarray data analysis using hybrid machine learning algorithms. The beginning of microarray technology has enabled the researchers to quickly measure the position of thousands of genes expressed in an organic/biological tissue samples in a solitary experiment. One of the important applications of this microarray technology is to classify the tissue samples using their gene expression representation, identify numerous type of cancer. Cancer is a group of diseases in which a set of cells shows uncontrolled growth, instance that interrupts upon and destroys nearby tissues and spreading to other locations in the body via lymph or blood. Cancer has becomes a one of the major important disease in current scenario. DNA microarrays turn out to be an effectual tool utilized in molecular biology and cancer diagnosis. Microarrays can be measured to establish the relative quantity of mRNAs in two or additional organic/biological tissue samples for thousands/several thousands of genes at the same time. As the superiority of this technique become exactly analysis/identifying the suitable assessment of microarray data in various open issues. In the field of medical sciences multi-category cancer classification play a major important role to classify the cancer types according to the gene expression. The need of the cancer classification has been become indispensible, because the numbers of cancer victims are increasing steadily identified by recent years. To perform this proposed a combination of Integer-Coded Genetic Algorithm (ICGA and Artificial Bee Colony algorithm (ABC, coupled with an Adaptive Extreme Learning Machine (AELM, is used for gene selection and cancer classification. ICGA is used with ABC based AELM classifier to chose an optimal set of genes which results in an efficient hybrid algorithm that can handle sparse data and sample imbalance. The

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

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    Ryden Tobias

    2010-10-01

    Full Text Available Abstract Background 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. Results 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. Conclusions 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.

  10. 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.)

  11. Gene-expression profiling reveals distinct expression patterns for Classic versus Variant Merkel cell phenotypes and new classifier genes to distinguish Merkel cell from small-cell lung carcinoma.

    Science.gov (United States)

    Van Gele, Mireille; Boyle, Glen M; Cook, Anthony L; Vandesompele, Jo; Boonefaes, Tom; Rottiers, Pieter; Van Roy, Nadine; De Paepe, Anne; Parsons, Peter G; Leonard, J Helen; Speleman, Frank

    2004-04-08

    Merkel cell carcinoma (MCC) is a rare aggressive skin tumor which shares histopathological and genetic features with small-cell lung carcinoma (SCLC), both are of neuroendocrine origin. Comparable to SCLC, MCC cell lines are classified into two different biochemical subgroups designated as 'Classic' and 'Variant'. With the aim to identify typical gene-expression signatures associated with these phenotypically different MCC cell lines subgroups and to search for differentially expressed genes between MCC and SCLC, we used cDNA arrays to profile 10 MCC cell lines and four SCLC cell lines. Using significance analysis of microarrays, we defined a set of 76 differentially expressed genes that allowed unequivocal identification of Classic and Variant MCC subgroups. We assume that the differential expression levels of some of these genes reflect, analogous to SCLC, the different biological and clinical properties of Classic and Variant MCC phenotypes. Therefore, they may serve as useful prognostic markers and potential targets for the development of new therapeutic interventions specific for each subgroup. Moreover, our analysis identified 17 powerful classifier genes capable of discriminating MCC from SCLC. Real-time quantitative RT-PCR analysis of these genes on 26 additional MCC and SCLC samples confirmed their diagnostic classification potential, opening opportunities for new investigations into these aggressive cancers.

  12. 从肿瘤基因表达数据挖掘分类规则的研究%Mining Classifying Rules from Tumor Gene Expression Data

    Institute of Scientific and Technical Information of China (English)

    马猛; 汝颖; 马腾; 钮俊清; 李龙澍; 王煦法

    2009-01-01

    Establishing tumor prediction and classification models using methodology and technology of information science based on the tumor gene expression data is meaningful to the research of tumor gene expression patterns identification and tumor diagnosis and recognition as well. This paper presented a method to construct tumor classifier using the classifying rules directly mined from tumor gene expression data. According to this method, we extracted the experiment sample dataset and then searched classifying features that could respectively mark the tumor and normal sample from this dataset. Based on the classifying features mined, the classifying rules were generated and used to predict each unknown sample according to the principle of highest confidence. The experiment made on the prostate cancer gene expression data from Broad Institute showed that the prediction accuracy of this method was over 90% and a lot of classifying rules with transparent prediction structure were generated at the same time. The experimental results proved the feasibility and effectiveness of this method.%基于肿瘤基因表达数据,利用信息科学的方法和技术建立肿瘤预测分类模型,对肿瘤基因表达模式研究和肿瘤的诊断识别具有重要意义.本研究提出一种从肿瘤基因表达数据中直接挖掘分类规则建立肿瘤预测分类器的方法.该方法首先抽取实验样本集,分别找出标记肿瘤和正常组织样本的分类特征,由此生成可预测样本类别的分类规则,对每个未知类别样本,按照置信度最高原则,选择一个分类规则作为预测结构.本研究的实验数据来自Broad Institute的前列腺癌基因表达数据,实验结果显示该方法的预测精度在90%以上,且同时获得了大量结构透明的分类预测规则,表明本研究的方法是可行的和有效的.

  13. 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

    DEFF Research Database (Denmark)

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

    2016-01-01

    classification threshold that separated cervical cancer patients into a more and less hypoxic group with different outcome to chemoradiotherapy. EXPERIMENTAL DESIGN: A training cohort of 42 patients and two independent cohorts of 108 and 131 patients were included. Gene expression data were generated from tumor...... biopsies by two Illumina array generations (WG-6, HT-12). Technical transfer of the classifier to a reverse transcription quantitative PCR (RT-qPCR) platform was performed for 74 patients. The amplitude ABrix in the Brix pharmacokinetic model was extracted from DCE-MR images of 64 patients and used......-gene classifier was identified. The classifier separated the patients into two groups with different progression-free survival probability. The robustness of the classifier was demonstrated by successful validation of hypoxia association and prognostic value across cohorts, array generations, and assay...

  14. 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.

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

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    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.

  16. The fuzzy gene filter: A classifier performance assesment

    CERN Document Server

    Perez, Meir

    2011-01-01

    The Fuzzy Gene Filter (FGF) is an optimised Fuzzy Inference System designed to rank genes in order of differential expression, based on expression data generated in a microarray experiment. This paper examines the effectiveness of the FGF for feature selection using various classification architectures. The FGF is compared to three of the most common gene ranking algorithms: t-test, Wilcoxon test and ROC curve analysis. Four classification schemes are used to compare the performance of the FGF vis-a-vis the standard approaches: K Nearest Neighbour (KNN), Support Vector Machine (SVM), Naive Bayesian Classifier (NBC) and Artificial Neural Network (ANN). A nested stratified Leave-One-Out Cross Validation scheme is used to identify the optimal number top ranking genes, as well as the optimal classifier parameters. Two microarray data sets are used for the comparison: a prostate cancer data set and a lymphoma data set.

  17. Clinical application of modified bag-of-features coupled with hybrid neural-based classifier in dengue fever classification using gene expression data.

    Science.gov (United States)

    Chatterjee, Sankhadeep; Dey, Nilanjan; Shi, Fuqian; Ashour, Amira S; Fong, Simon James; Sen, Soumya

    2017-09-11

    Dengue fever detection and classification have a vital role due to the recent outbreaks of different kinds of dengue fever. Recently, the advancement in the microarray technology can be employed for such classification process. Several studies have established that the gene selection phase takes a significant role in the classifier performance. Subsequently, the current study focused on detecting two different variations, namely, dengue fever (DF) and dengue hemorrhagic fever (DHF). A modified bag-of-features method has been proposed to select the most promising genes in the classification process. Afterward, a modified cuckoo search optimization algorithm has been engaged to support the artificial neural (ANN-MCS) to classify the unknown subjects into three different classes namely, DF, DHF, and another class containing convalescent and normal cases. The proposed method has been compared with other three well-known classifiers, namely, multilayer perceptron feed-forward network (MLP-FFN), artificial neural network (ANN) trained with cuckoo search (ANN-CS), and ANN trained with PSO (ANN-PSO). Experiments have been carried out with different number of clusters for the initial bag-of-features-based feature selection phase. After obtaining the reduced dataset, the hybrid ANN-MCS model has been employed for the classification process. The results have been compared in terms of the confusion matrix-based performance measuring metrics. The experimental results indicated a highly statistically significant improvement with the proposed classifier over the traditional ANN-CS model.

  18. Facial Expression Recognition Using SVM Classifier

    OpenAIRE

    2015-01-01

    Facial feature tracking and facial actions recognition from image sequence attracted great attention in computer vision field. Computational facial expression analysis is a challenging research topic in computer vision. It is required by many applications such as human-computer interaction, computer graphic animation and automatic facial expression recognition. In recent years, plenty of computer vision techniques have been developed to track or recognize the facial activities in three levels...

  19. Discovery and validation of gene classifiers for endocrine-disrupting chemicals in zebrafish (danio rerio

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    Wang Rong-Lin

    2012-08-01

    Full Text Available Abstract Background Development and application of transcriptomics-based gene classifiers for ecotoxicological applications lag far behind those of biomedical sciences. Many such classifiers discovered thus far lack vigorous statistical and experimental validations. A combination of genetic algorithm/support vector machines and genetic algorithm/K nearest neighbors was used in this study to search for classifiers of endocrine-disrupting chemicals (EDCs in zebrafish. Searches were conducted on both tissue-specific and tissue-combined datasets, either across the entire transcriptome or within individual transcription factor (TF networks previously linked to EDC effects. Candidate classifiers were evaluated by gene set enrichment analysis (GSEA on both the original training data and a dedicated validation dataset. Results Multi-tissue dataset yielded no classifiers. Among the 19 chemical-tissue conditions evaluated, the transcriptome-wide searches yielded classifiers for six of them, each having approximately 20 to 30 gene features unique to a condition. Searches within individual TF networks produced classifiers for 15 chemical-tissue conditions, each containing 100 or fewer top-ranked gene features pooled from those of multiple TF networks and also unique to each condition. For the training dataset, 10 out of 11 classifiers successfully identified the gene expression profiles (GEPs of their targeted chemical-tissue conditions by GSEA. For the validation dataset, classifiers for prochloraz-ovary and flutamide-ovary also correctly identified the GEPs of corresponding conditions while no classifier could predict the GEP from prochloraz-brain. Conclusions The discrepancies in the performance of these classifiers were attributed in part to varying data complexity among the conditions, as measured to some degree by Fisher’s discriminant ratio statistic. This variation in data complexity could likely be compensated by adjusting sample size for

  20. 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.

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

    OpenAIRE

    Tsatsoulis Costas; Amthauer Heather A

    2010-01-01

    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 ce...

  2. 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.

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

    Science.gov (United States)

    Amthauer, Heather A; Tsatsoulis, Costas

    2010-05-28

    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. 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. 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.

  4. Classification of Cancer Gene Selection Using Random Forest and Neural Network Based Ensemble Classifier

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    Jogendra Kushwah

    2013-06-01

    Full Text Available The free radical gene classification of cancer diseases is challenging job in biomedical data engineering. The improving of classification of gene selection of cancer diseases various classifier are used, but the classification of classifier are not validate. So ensemble classifier is used for cancer gene classification using neural network classifier with random forest tree. The random forest tree is ensembling technique of classifier in this technique the number of classifier ensemble of their leaf node of class of classifier. In this paper we combined neural network with random forest ensemble classifier for classification of cancer gene selection for diagnose analysis of cancer diseases. The proposed method is different from most of the methods of ensemble classifier, which follow an input output paradigm of neural network, where the members of the ensemble are selected from a set of neural network classifier. the number of classifiers is determined during the rising procedure of the forest. Furthermore, the proposed method produces an ensemble not only correct, but also assorted, ensuring the two important properties that should characterize an ensemble classifier. For empirical evaluation of our proposed method we used UCI cancer diseases data set for classification. Our experimental result shows that better result in compression of random forest tree classification.

  5. 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...

  6. RFMirTarget: predicting human microRNA target genes with a random forest classifier.

    Directory of Open Access Journals (Sweden)

    Mariana R Mendoza

    Full Text Available MicroRNAs are key regulators of eukaryotic gene expression whose fundamental role has already been identified in many cell pathways. The correct identification of miRNAs targets is still a major challenge in bioinformatics and has motivated the development of several computational methods to overcome inherent limitations of experimental analysis. Indeed, the best results reported so far in terms of specificity and sensitivity are associated to machine learning-based methods for microRNA-target prediction. Following this trend, in the current paper we discuss and explore a microRNA-target prediction method based on a random forest classifier, namely RFMirTarget. Despite its well-known robustness regarding general classifying tasks, to the best of our knowledge, random forest have not been deeply explored for the specific context of predicting microRNAs targets. Our framework first analyzes alignments between candidate microRNA-target pairs and extracts a set of structural, thermodynamics, alignment, seed and position-based features, upon which classification is performed. Experiments have shown that RFMirTarget outperforms several well-known classifiers with statistical significance, and that its performance is not impaired by the class imbalance problem or features correlation. Moreover, comparing it against other algorithms for microRNA target prediction using independent test data sets from TarBase and starBase, we observe a very promising performance, with higher sensitivity in relation to other methods. Finally, tests performed with RFMirTarget show the benefits of feature selection even for a classifier with embedded feature importance analysis, and the consistency between relevant features identified and important biological properties for effective microRNA-target gene alignment.

  7. Grouping and classifying electrophysiologically-defined classes of neocortical neurons by single cell, whole-genome expression profiling

    Directory of Open Access Journals (Sweden)

    Tatiana Subkhankulova

    2010-04-01

    Full Text Available The diversity of neuronal cell types and how to classify them are perennial questions in neuroscience. The advent of global gene expression analysis raised the possibility that comprehensive transcription profiling will resolve neuronal cell types into groups that reflect some or all aspects of their phenotype. This approach has been successfully used to compare gene expression between groups of neurons defined by a common property. Here we extend this approach to ask whether single neuron gene expression profiling can prospectively resolve neuronal subtypes into groups, independent of any phenotypic information, and whether those groups reflect meaningful biological properties of those neurons. We applied methods we have developed to compare gene expression among single neural stem cells to study global gene expression in 18 randomly picked neurons from layer II/III of the early postnatal mouse neocortex. Cells were selected by morphology and by firing characteristics and electrical properties, enabling the definition of each cell as either fast- or regular-spiking, corresponding to a class of inhibitory interneurons or excitatory pyramidal cells. Unsupervised clustering of young neurons by global gene expression resolved the cells into two groups and those broadly corresponded with the two groups of fast- and regular-spiking neurons. Clustering of the entire, diverse group of 18 neurons of different developmental stages also successfully grouped neurons in accordance with the electrophysiological phenotypes, but with more cells misassigned among groups. Genes specifically enriched in regular spiking neurons were identified from the young neuron expression dataset. These results provide a proof of principle that single-cell gene expression profiling may be used to group and classify neurons in a manner reflecting their known biological properties and may be used to identify cell-specific transcripts.

  8. Combining classifiers generated by multi-gene genetic programming for protein fold recognition using genetic algorithm.

    Science.gov (United States)

    Bardsiri, Mahshid Khatibi; Eftekhari, Mahdi; Mousavi, Reza

    2015-01-01

    In this study the problem of protein fold recognition, that is a classification task, is solved via a hybrid of evolutionary algorithms namely multi-gene Genetic Programming (GP) and Genetic Algorithm (GA). Our proposed method consists of two main stages and is performed on three datasets taken from the literature. Each dataset contains different feature groups and classes. In the first step, multi-gene GP is used for producing binary classifiers based on various feature groups for each class. Then, different classifiers obtained for each class are combined via weighted voting so that the weights are determined through GA. At the end of the first step, there is a separate binary classifier for each class. In the second stage, the obtained binary classifiers are combined via GA weighting in order to generate the overall classifier. The final obtained classifier is superior to the previous works found in the literature in terms of classification accuracy.

  9. 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...Approved for Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT We identified a tumor microenvironment -based activated fibroblast

  10. Gene Expression Patterns in Ovarian Carcinomas

    Science.gov (United States)

    Schaner, Marci E.; Ross, Douglas T.; Ciaravino, Giuseppe; Sørlie, Therese; Troyanskaya, Olga; Diehn, Maximilian; Wang, Yan C.; Duran, George E.; Sikic, Thomas L.; Caldeira, Sandra; Skomedal, Hanne; Tu, I-Ping; Hernandez-Boussard, Tina; Johnson, Steven W.; O'Dwyer, Peter J.; Fero, Michael J.; Kristensen, Gunnar B.; Børresen-Dale, Anne-Lise; Hastie, Trevor; Tibshirani, Robert; van de Rijn, Matt; Teng, Nelson N.; Longacre, Teri A.; Botstein, David; Brown, Patrick O.; Sikic, Branimir I.

    2003-01-01

    We used DNA microarrays to characterize the global gene expression patterns in surface epithelial cancers of the ovary. We identified groups of genes that distinguished the clear cell subtype from other ovarian carcinomas, grade I and II from grade III serous papillary carcinomas, and ovarian from breast carcinomas. Six clear cell carcinomas were distinguished from 36 other ovarian carcinomas (predominantly serous papillary) based on their gene expression patterns. The differences may yield insights into the worse prognosis and therapeutic resistance associated with clear cell carcinomas. A comparison of the gene expression patterns in the ovarian cancers to published data of gene expression in breast cancers revealed a large number of differentially expressed genes. We identified a group of 62 genes that correctly classified all 125 breast and ovarian cancer specimens. Among the best discriminators more highly expressed in the ovarian carcinomas were PAX8 (paired box gene 8), mesothelin, and ephrin-B1 (EFNB1). Although estrogen receptor was expressed in both the ovarian and breast cancers, genes that are coregulated with the estrogen receptor in breast cancers, including GATA-3, LIV-1, and X-box binding protein 1, did not show a similar pattern of coexpression in the ovarian cancers. PMID:12960427

  11. Classification of Cancer Gene Selection Using Random Forest and Neural Network Based Ensemble Classifier

    Directory of Open Access Journals (Sweden)

    Jogendra Kushwah

    2013-06-01

    Full Text Available The free radical gene classification of cancerdiseasesis challenging job in biomedical dataengineering. The improving of classification of geneselection of cancer diseases various classifier areused, but the classification of classifier are notvalidate. So ensemble classifier is used for cancergene classification using neural network classifierwith random forest tree. The random forest tree isensembling technique of classifier in this techniquethe number of classifier ensemble of their leaf nodeof class of classifier. In this paper we combinedneuralnetwork with random forest ensembleclassifier for classification of cancer gene selectionfor diagnose analysis of cancer diseases.Theproposed method is different from most of themethods of ensemble classifier, which follow aninput output paradigm ofneural network, where themembers of the ensemble are selected from a set ofneural network classifier. the number of classifiersis determined during the rising procedure of theforest. Furthermore, the proposed method producesan ensemble not only correct, but also assorted,ensuring the two important properties that shouldcharacterize an ensemble classifier. For empiricalevaluation of our proposed method we used UCIcancer diseases data set for classification. Ourexperimental result shows that betterresult incompression of random forest tree classification

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

    Directory of Open Access Journals (Sweden)

    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

  13. Expression of polarity genes in human cancer.

    Science.gov (United States)

    Lin, Wan-Hsin; Asmann, Yan W; Anastasiadis, Panos Z

    2015-01-01

    Polarity protein complexes are crucial for epithelial apical-basal polarity and directed cell migration. Since alterations of these processes are common in cancer, polarity proteins have been proposed to function as tumor suppressors or oncogenic promoters. Here, we review the current understanding of polarity protein functions in epithelial homeostasis, as well as tumor formation and progression. As most previous studies focused on the function of single polarity proteins in simplified model systems, we used a genomics approach to systematically examine and identify the expression profiles of polarity genes in human cancer. The expression profiles of polarity genes were distinct in different human tissues and classified cancer types. Additionally, polarity expression profiles correlated with disease progression and aggressiveness, as well as with identified cancer types, where specific polarity genes were commonly altered. In the case of Scribble, gene expression analysis indicated its common amplification and upregulation in human cancer, suggesting a tumor promoting function.

  14. Statistical analysis of a Bayesian classifier based on the expression of miRNAs

    OpenAIRE

    Ricci, Leonardo; Del Vescovo, Valerio; Cantaloni, Chiara; Grasso, Margherita; Barbareschi, Mattia; Denti, Michela Alessandra

    2015-01-01

    Background During the last decade, many scientific works have concerned the possible use of miRNA levels as diagnostic and prognostic tools for different kinds of cancer. The development of reliable classifiers requires tackling several crucial aspects, some of which have been widely overlooked in the scientific literature: the distribution of the measured miRNA expressions and the statistical uncertainty that affects the parameters that characterize a classifier. In this paper, these topics ...

  15. Tumor-specific gene expression patterns with gene expression profiles

    Institute of Scientific and Technical Information of China (English)

    RUAN Xiaogang; LI Yingxin; LI Jiangeng; GONG Daoxiong; WANG Jinlian

    2006-01-01

    Gene expression profiles of 14 common tumors and their counterpart normal tissues were analyzed with machine learning methods to address the problem of selection of tumor-specific genes and analysis of their differential expressions in tumor tissues. First, a variation of the Relief algorithm, "RFE_Relief algorithm" was proposed to learn the relations between genes and tissue types. Then, a support vector machine was employed to find the gene subset with the best classification performance for distinguishing cancerous tissues and their counterparts. After tissue-specific genes were removed, cross validation experiments were employed to demonstrate the common deregulated expressions of the selected gene in tumor tissues. The results indicate the existence of a specific expression fingerprint of these genes that is shared in different tumor tissues, and the hallmarks of the expression patterns of these genes in cancerous tissues are summarized at the end of this paper.

  16. A 50-gene intrinsic subtype classifier for prognosis and prediction of benefit from adjuvant tamoxifen.

    Science.gov (United States)

    Chia, Stephen K; Bramwell, Vivien H; Tu, Dongsheng; Shepherd, Lois E; Jiang, Shan; Vickery, Tammi; Mardis, Elaine; Leung, Samuel; Ung, Karen; Pritchard, Kathleen I; Parker, Joel S; Bernard, Philip S; Perou, Charles M; Ellis, Matthew J; Nielsen, Torsten O

    2012-08-15

    Gene expression profiling classifies breast cancer into intrinsic subtypes based on the biology of the underlying disease pathways. We have used material from a prospective randomized trial of tamoxifen versus placebo in premenopausal women with primary breast cancer (NCIC CTG MA.12) to evaluate the prognostic and predictive significance of intrinsic subtypes identified by both the PAM50 gene set and by immunohistochemistry. Total RNA from 398 of 672 (59%) patients was available for intrinsic subtyping with a quantitative reverse transcriptase PCR (qRT-PCR) 50-gene predictor (PAM50) for luminal A, luminal B, HER-2-enriched, and basal-like subtypes. A tissue microarray was also constructed from 492 of 672 (73%) of the study population to assess a panel of six immunohistochemical IHC antibodies to define the same intrinsic subtypes. Classification into intrinsic subtypes by the PAM50 assay was prognostic for both disease-free survival (DFS; P = 0.0003) and overall survival (OS; P = 0.0002), whereas classification by the IHC panel was not. Luminal subtype by PAM50 was predictive of tamoxifen benefit [DFS: HR, 0.52; 95% confidence interval (CI), 0.32-0.86 vs. HR, 0.80; 95% CI, 0.50-1.29 for nonluminal subtypes], although the interaction test was not significant (P = 0.24), whereas neither subtyping by central immunohistochemistry nor by local estrogen receptor (ER) or progesterone receptor (PR) status were predictive. Risk of relapse (ROR) modeling with the PAM50 assay produced a continuous risk score in both node-negative and node-positive disease. In the MA.12 study, intrinsic subtype classification by qRT-PCR with the PAM50 assay was superior to IHC profiling for both prognosis and prediction of benefit from adjuvant tamoxifen.

  17. 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.

  18. Evaluation and integration of cancer gene classifiers: identification and ranking of plausible drivers.

    Science.gov (United States)

    Liu, Yang; Tian, Feng; Hu, Zhenjun; DeLisi, Charles

    2015-05-11

    The number of mutated genes in cancer cells is far larger than the number of mutations that drive cancer. The difficulty this creates for identifying relevant alterations has stimulated the development of various computational approaches to distinguishing drivers from bystanders. We develop and apply an ensemble classifier (EC) machine learning method, which integrates 10 classifiers that are publically available, and apply it to breast and ovarian cancer. In particular we find the following: (1) Using both standard and non-standard metrics, EC almost always outperforms single method classifiers, often by wide margins. (2) Of the 50 highest ranked genes for breast (ovarian) cancer, 34 (30) are associated with other cancers in either the OMIM, CGC or NCG database (P plausible. Biological implications are briefly discussed. Source codes and detailed results are available at http://www.visantnet.org/misi/driver_integration.zip.

  19. Prediction of Tumor Outcome Based on Gene Expression Data

    Institute of Scientific and Technical Information of China (English)

    Liu Juan; Hitoshi Iba

    2004-01-01

    Gene expression microarray data can be used to classify tumor types. We proposed a new procedure to classify human tumor samples based on microarray gene expressions by using a hybrid supervised learning method called MOEA+WV (Multi-Objective Evolutionary Algorithm+Weighted Voting). MOEA is used to search for a relatively few subsets of informative genes from the high-dimensional gene space, and WV is used as a classification tool. This new method has been applied to predicate the subtypes of lymphoma and outcomes of medulloblastoma. The results are relatively accurate and meaningful compared to those from other methods.

  20. Statistical analysis of genomic protein family and domain controlled annotations for functional investigation of classified gene lists

    Directory of Open Access Journals (Sweden)

    Masseroli Marco

    2007-03-01

    Full Text Available Abstract Background The increasing protein family and domain based annotations constitute important information to understand protein functions and gain insight into relations among their codifying genes. To allow analyzing of gene proteomic annotations, we implemented novel modules within GFINDer, a Web system we previously developed that dynamically aggregates functional and phenotypic annotations of user-uploaded gene lists and allows performing their statistical analysis and mining. Results Exploiting protein information in Pfam and InterPro databanks, we developed and added in GFINDer original modules specifically devoted to the exploration and analysis of functional signatures of gene protein products. They allow annotating numerous user-classified nucleotide sequence identifiers with controlled information on related protein families, domains and functional sites, classifying them according to such protein annotation categories, and statistically analyzing the obtained classifications. In particular, when uploaded nucleotide sequence identifiers are subdivided in classes, the Statistics Protein Families&Domains module allows estimating relevance of Pfam or InterPro controlled annotations for the uploaded genes by highlighting protein signatures significantly more represented within user-defined classes of genes. In addition, the Logistic Regression module allows identifying protein functional signatures that better explain the considered gene classification. Conclusion Novel GFINDer modules provide genomic protein family and domain analyses supporting better functional interpretation of gene classes, for instance defined through statistical and clustering analyses of gene expression results from microarray experiments. They can hence help understanding fundamental biological processes and complex cellular mechanisms influenced by protein domain composition, and contribute to unveil new biomedical knowledge about the codifying genes.

  1. A Classifier Model based on the Features Quantitative Analysis for Facial Expression Recognition

    Directory of Open Access Journals (Sweden)

    Amir Jamshidnezhad

    2011-01-01

    Full Text Available In recent decades computer technology has considerable developed in use of intelligent systems for classification. The development of HCI systems is highly depended on accurate understanding of emotions. However, facial expressions are difficult to classify by a mathematical models because of natural quality. In this paper, quantitative analysis is used in order to find the most effective features movements between the selected facial feature points. Therefore, the features are extracted not only based on the psychological studies, but also based on the quantitative methods to arise the accuracy of recognitions. Also in this model, fuzzy logic and genetic algorithm are used to classify facial expressions. Genetic algorithm is an exclusive attribute of proposed model which is used for tuning membership functions and increasing the accuracy.

  2. The flow of gene expression.

    Science.gov (United States)

    Misteli, Tom

    2004-03-01

    Gene expression is a highly interconnected multistep process. A recent meeting in Iguazu Falls, Argentina, highlighted the need to uncover both the molecular details of each single step as well as the mechanisms of coordination among processes in order to fully understand the expression of genes.

  3. Ascidian gene-expression profiles

    OpenAIRE

    Jeffery, William R.

    2002-01-01

    With the advent of gene-expression profiling, a large number of genes can now be investigated simultaneously during critical stages of development. This approach will be particularly informative in studies of ascidians, basal chordates whose genomes and embryology are uniquely suited for mapping developmental gene networks.

  4. iFish: predicting the pathogenicity of human nonsynonymous variants using gene-specific/family-specific attributes and classifiers.

    Science.gov (United States)

    Wang, Meng; Wei, Liping

    2016-08-16

    Accurate prediction of the pathogenicity of genomic variants, especially nonsynonymous single nucleotide variants (nsSNVs), is essential in biomedical research and clinical genetics. Most current prediction methods build a generic classifier for all genes. However, different genes and gene families have different features. We investigated whether gene-specific and family-specific customized classifiers could improve prediction accuracy. Customized gene-specific and family-specific attributes were selected with AIC, BIC, and LASSO, and Support Vector Machine classifiers were generated for 254 genes and 152 gene families, covering a total of 5,985 genes. Our results showed that the customized attributes reflected key features of the genes and gene families, and the customized classifiers achieved higher prediction accuracy than the generic classifier. The customized classifiers and the generic classifier for other genes and families were integrated into a new tool named iFish (integrated Functional inference of SNVs in human, http://ifish.cbi.pku.edu.cn). iFish outperformed other methods on benchmark datasets as well as on prioritization of candidate causal variants from whole exome sequencing. iFish provides a user-friendly web-based interface and supports other functionalities such as integration of genetic evidence. iFish would facilitate high-throughput evaluation and prioritization of nsSNVs in human genetics research.

  5. Human Lacrimal Gland Gene Expression

    Science.gov (United States)

    Aakalu, Vinay Kumar; Parameswaran, Sowmya; Maienschein-Cline, Mark; Bahroos, Neil; Shah, Dhara; Ali, Marwan; Krishnakumar, Subramanian

    2017-01-01

    Background The study of human lacrimal gland biology and development is limited. Lacrimal gland tissue is damaged or poorly functional in a number of disease states including dry eye disease. Development of cell based therapies for lacrimal gland diseases requires a better understanding of the gene expression and signaling pathways in lacrimal gland. Differential gene expression analysis between lacrimal gland and other embryologically similar tissues may be helpful in furthering our understanding of lacrimal gland development. Methods We performed global gene expression analysis of human lacrimal gland tissue using Affymetrix ® gene expression arrays. Primary data from our laboratory was compared with datasets available in the NLM GEO database for other surface ectodermal tissues including salivary gland, skin, conjunctiva and corneal epithelium. Results The analysis revealed statistically significant difference in the gene expression of lacrimal gland tissue compared to other ectodermal tissues. The lacrimal gland specific, cell surface secretory protein encoding genes and critical signaling pathways which distinguish lacrimal gland from other ectodermal tissues are described. Conclusions Differential gene expression in human lacrimal gland compared with other ectodermal tissue types revealed interesting patterns which may serve as the basis for future studies in directed differentiation among other areas. PMID:28081151

  6. 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

  7. 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

  8. Gene expression signature in peripheral blood detects thoracic aortic aneurysm.

    Directory of Open Access Journals (Sweden)

    Yulei Wang

    Full Text Available BACKGROUND: Thoracic aortic aneurysm (TAA is usually asymptomatic and associated with high mortality. Adverse clinical outcome of TAA is preventable by elective surgical repair; however, identifying at-risk individuals is difficult. We hypothesized that gene expression patterns in peripheral blood cells may correlate with TAA disease status. Our goal was to identify a distinct gene expression signature in peripheral blood that may identify individuals at risk for TAA. METHODS AND FINDINGS: Whole genome gene expression profiles from 94 peripheral blood samples (collected from 58 individuals with TAA and 36 controls were analyzed. Significance Analysis of Microarray (SAM identified potential signature genes characterizing TAA vs. normal, ascending vs. descending TAA, and sporadic vs. familial TAA. Using a training set containing 36 TAA patients and 25 controls, a 41-gene classification model was constructed for detecting TAA status and an overall accuracy of 78+/-6% was achieved. Testing this classifier on an independent validation set containing 22 TAA samples and 11 controls yielded an overall classification accuracy of 78%. These 41 classifier genes were further validated by TaqMan real-time PCR assays. Classification based on the TaqMan data replicated the microarray results and achieved 80% classification accuracy on the testing set. CONCLUSIONS: This study identified informative gene expression signatures in peripheral blood cells that can characterize TAA status and subtypes of TAA. Moreover, a 41-gene classifier based on expression signature can identify TAA patients with high accuracy. The transcriptional programs in peripheral blood leading to the identification of these markers also provide insights into the mechanism of development of aortic aneurysms and highlight potential targets for therapeutic intervention. The classifier genes identified in this study, and validated by TaqMan real-time PCR, define a set of promising potential

  9. Predicting gene expression from sequence: a reexamination.

    Directory of Open Access Journals (Sweden)

    Yuan Yuan

    2007-11-01

    Full Text Available Although much of the information regarding genes' expressions is encoded in the genome, deciphering such information has been very challenging. We reexamined Beer and Tavazoie's (BT approach to predict mRNA expression patterns of 2,587 genes in Saccharomyces cerevisiae from the information in their respective promoter sequences. Instead of fitting complex Bayesian network models, we trained naïve Bayes classifiers using only the sequence-motif matching scores provided by BT. Our simple models correctly predict expression patterns for 79% of the genes, based on the same criterion and the same cross-validation (CV procedure as BT, which compares favorably to the 73% accuracy of BT. The fact that our approach did not use position and orientation information of the predicted binding sites but achieved a higher prediction accuracy, motivated us to investigate a few biological predictions made by BT. We found that some of their predictions, especially those related to motif orientations and positions, are at best circumstantial. For example, the combinatorial rules suggested by BT for the PAC and RRPE motifs are not unique to the cluster of genes from which the predictive model was inferred, and there are simpler rules that are statistically more significant than BT's ones. We also show that CV procedure used by BT to estimate their method's prediction accuracy is inappropriate and may have overestimated the prediction accuracy by about 10%.

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

    Science.gov (United States)

    2015-06-01

    expression profile data from two datasets were screened for differentially expressed (DE) genes between patients with residual disease (RD) and...16), liver (17–22), head and neck (11,23,24), stomach (25), bladder (26), prostate (7), lung (27), brain (28) and bone (29). ADAM12 has not been...examined as a potential biomarker in ovarian cancer. However, ADAM12 was identified in an unbi- ased screen as one of the transmembrane proteins

  11. A prognosis classifier for breast cancer based on conserved gene regulation between mammary gland development and tumorigenesis: a multiscale statistical model.

    Science.gov (United States)

    Tian, Yingpu; Chen, Baozhen; Guan, Pengfei; Kang, Yujia; Lu, Zhongxian

    2013-01-01

    Identification of novel cancer genes for molecular therapy and diagnosis is a current focus of breast cancer research. Although a few small gene sets were identified as prognosis classifiers, more powerful models are still needed for the definition of effective gene sets for the diagnosis and treatment guidance in breast cancer. In the present study, we have developed a novel statistical approach for systematic analysis of intrinsic correlations of gene expression between development and tumorigenesis in mammary gland. Based on this analysis, we constructed a predictive model for prognosis in breast cancer that may be useful for therapy decisions. We first defined developmentally associated genes from a mouse mammary gland epithelial gene expression database. Then, we found that the cancer modulated genes were enriched in this developmentally associated genes list. Furthermore, the developmentally associated genes had a specific expression profile, which associated with the molecular characteristics and histological grade of the tumor. These result suggested that the processes of mammary gland development and tumorigenesis share gene regulatory mechanisms. Then, the list of regulatory genes both on the developmental and tumorigenesis process was defined an 835-member prognosis classifier, which showed an exciting ability to predict clinical outcome of three groups of breast cancer patients (the predictive accuracy 64∼72%) with a robust prognosis prediction (hazard ratio 3.3∼3.8, higher than that of other clinical risk factors (around 2.0-2.8)). In conclusion, our results identified the conserved molecular mechanisms between mammary gland development and neoplasia, and provided a unique potential model for mining unknown cancer genes and predicting the clinical status of breast tumors. These findings also suggested that developmental roles of genes may be important criteria for selecting genes for prognosis prediction in breast cancer.

  12. 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 p...... with a high frequency of loss of heterozygosity. The genes and ESTs presented in this study encode new potential tumor markers as well as potential novel therapeutic targets for prevention or therapy of CRC.......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...

  13. Zipf's Law in Gene Expression

    CERN Document Server

    Furusawa, C; Furusawa, Chikara; Kaneko, Kunihiko

    2002-01-01

    Using data from gene expression databases on various organisms and tissues, including yeast, nematodes, human normal and cancer tissues, and embryonic stem cells, we found that the abundances of expressed genes exhibit a power-law distribution with an exponent close to -1, i.e., they obey Zipf's law. Furthermore, by simulations of a simple model with an intra-cellular reaction network, we found that Zipf's law of chemical abundance is a universal feature of cells where such a network optimizes the efficiency and faithfulness of self-reproduction. These findings provide novel insights into the nature of the organization of reaction dynamics in living cells.

  14. Zipf's Law in Gene Expression

    Science.gov (United States)

    Furusawa, Chikara; Kaneko, Kunihiko

    2003-02-01

    Using data from gene expression databases on various organisms and tissues, including yeast, nematodes, human normal and cancer tissues, and embryonic stem cells, we found that the abundances of expressed genes exhibit a power-law distribution with an exponent close to -1; i.e., they obey Zipf’s law. Furthermore, by simulations of a simple model with an intracellular reaction network, we found that Zipf’s law of chemical abundance is a universal feature of cells where such a network optimizes the efficiency and faithfulness of self-reproduction. These findings provide novel insights into the nature of the organization of reaction dynamics in living cells.

  15. 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...... an analytical approach to examine the suitability of correction methods by considering the inter-treatment bias as well as the inter-replicate variance, which allows use of the best correction method with minimum residual bias. Analyses of RNA sequencing and microarray data showed that the efficiencies...

  16. Pairwise protein expression classifier for candidate biomarker discovery for early detection of human disease prognosis

    Directory of Open Access Journals (Sweden)

    Kaur Parminder

    2012-08-01

    Full Text Available Abstract Background An approach to molecular classification based on the comparative expression of protein pairs is presented. The method overcomes some of the present limitations in using peptide intensity data for class prediction for problems such as the detection of a disease, disease prognosis, or for predicting treatment response. Data analysis is particularly challenging in these situations due to sample size (typically tens being much smaller than the large number of peptides (typically thousands. Methods based upon high dimensional statistical models, machine learning or other complex classifiers generate decisions which may be very accurate but can be complex and difficult to interpret in simple or biologically meaningful terms. A classification scheme, called ProtPair, is presented that generates simple decision rules leading to accurate classification which is based on measurement of very few proteins and requires only relative expression values, providing specific targeted hypotheses suitable for straightforward validation. Results ProtPair has been tested against clinical data from 21 patients following a bone marrow transplant, 13 of which progress to idiopathic pneumonia syndrome (IPS. The approach combines multiple peptide pairs originating from the same set of proteins, with each unique peptide pair providing an independent measure of discriminatory power. The prediction rate of the ProtPair for IPS study as measured by leave-one-out CV is 69.1%, which can be very beneficial for clinical diagnosis as it may flag patients in need of closer monitoring. The “top ranked” proteins provided by ProtPair are known to be associated with the biological processes and pathways intimately associated with known IPS biology based on mouse models. Conclusions An approach to biomarker discovery, called ProtPair, is presented. ProtPair is based on the differential expression of pairs of peptides and the associated proteins. Using mass

  17. Homeobox gene expression in Brachiopoda

    DEFF Research Database (Denmark)

    Altenburger, Andreas; Martinez, Pedro; Wanninger, Andreas

    2011-01-01

    The molecular control that underlies brachiopod ontogeny is largely unknown. In order to contribute to this issue we analyzed the expression pattern of two homeobox containing genes, Not and Cdx, during development of the rhynchonelliform (i.e., articulate) brachiopod Terebratalia transversa. Not...

  18. Vascular Gene Expression: A Hypothesis

    Directory of Open Access Journals (Sweden)

    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.

  19. 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

  20. An Eighteen-Gene Classifier Predicts Locoregional Recurrence in Post-Mastectomy Breast Cancer Patients

    Directory of Open Access Journals (Sweden)

    Skye H. Cheng

    2016-03-01

    Full Text Available We previously identified 34 genes of interest (GOI in 2006 to aid the oncologists to determine whether post-mastectomy radiotherapy (PMRT is indicated for certain patients with breast cancer. At this time, an independent cohort of 135 patients having DNA microarray study available from the primary tumor tissue samples was chosen. Inclusion criteria were 1 mastectomy as the first treatment, 2 pathology stages I-III, 3 any locoregional recurrence (LRR and 4 no PMRT. After inter-platform data integration of Affymetrix U95 and U133 Plus 2.0 arrays and quantile normalization, in this paper we used 18 of 34 GOI to divide the mastectomy patients into high and low risk groups. The 5-year rate of freedom from LRR in the high-risk group was 30%. In contrast, in the low-risk group it was 99% (p<0.0001. Multivariate analysis revealed that the 18-gene classifier independently predicts rates of LRR regardless of nodal status or cancer subtype.

  1. Gene Expression in Trypanosomatid Parasites

    Directory of Open Access Journals (Sweden)

    Santiago Martínez-Calvillo

    2010-01-01

    Full Text Available The parasites Leishmania spp., Trypanosoma brucei, and Trypanosoma cruzi are the trypanosomatid protozoa that cause the deadly human diseases leishmaniasis, African sleeping sickness, and Chagas disease, respectively. These organisms possess unique mechanisms for gene expression such as constitutive polycistronic transcription of protein-coding genes and trans-splicing. Little is known about either the DNA sequences or the proteins that are involved in the initiation and termination of transcription in trypanosomatids. In silico analyses of the genome databases of these parasites led to the identification of a small number of proteins involved in gene expression. However, functional studies have revealed that trypanosomatids have more general transcription factors than originally estimated. Many posttranslational histone modifications, histone variants, and chromatin modifying enzymes have been identified in trypanosomatids, and recent genome-wide studies showed that epigenetic regulation might play a very important role in gene expression in this group of parasites. Here, we review and comment on the most recent findings related to transcription initiation and termination in trypanosomatid protozoa.

  2. Synthetic promoter libraries- tuning of gene expression

    DEFF Research Database (Denmark)

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

    2006-01-01

    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 ...

  3. Classification with binary gene expressions

    OpenAIRE

    Tuna, Salih; Niranjan, Mahesan

    2009-01-01

    Microarray gene expression measurements are reported, used and archived usually to high numerical precision. However, properties of mRNA molecules, such as their low stability and availability in small copy numbers, and the fact that measurements correspond to a population of cells, rather than a single cell, makes high precision meaningless. Recent work shows that reducing measurement precision leads to very little loss of information, right down to binary levels. In this paper we show how p...

  4. The Gene Expression Omnibus database

    Science.gov (United States)

    Clough, Emily; Barrett, Tanya

    2016-01-01

    The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome–protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/. PMID:27008011

  5. Gene expression throughout a vertebrate's embryogenesis

    Directory of Open Access Journals (Sweden)

    Hinton David E

    2011-02-01

    Full Text Available Abstract Background Describing the patterns of gene expression during embryonic development has broadened our understanding of the processes and patterns that define morphogenesis. Yet gene expression patterns have not been described throughout vertebrate embryogenesis. This study presents statistical analyses of gene expression during all 40 developmental stages in the teleost Fundulus heteroclitus using four biological replicates per stage. Results Patterns of gene expression for 7,000 genes appear to be important as they recapitulate developmental timing. Among the 45% of genes with significant expression differences between pairs of temporally adjacent stages, significant differences in gene expression vary from as few as five to more than 660. Five adjacent stages have disproportionately more significant changes in gene expression (> 200 genes relative to other stages: four to eight and eight to sixteen cell stages, onset of circulation, pre and post-hatch, and during complete yolk absorption. The fewest differences among adjacent stages occur during gastrulation. Yet, at stage 16, (pre-mid-gastrulation the largest number of genes has peak expression. This stage has an over representation of genes in oxidative respiration and protein expression (ribosomes, translational genes and proteases. Unexpectedly, among all ribosomal genes, both strong positive and negative correlations occur. Similar correlated patterns of expression occur among all significant genes. Conclusions These data provide statistical support for the temporal dynamics of developmental gene expression during all stages of vertebrate development.

  6. Antisense expression increases gene expression variability and locus interdependency

    OpenAIRE

    Xu, Zhenyu; Wei, Wu; Gagneur, Julien; Clauder-Münster, Sandra; Smolik, Miłosz; Huber, Wolfgang; Steinmetz, Lars M.

    2011-01-01

    Genome-wide transcription profiling has revealed extensive expression of non-coding RNAs antisense to genes, yet their functions, if any, remain to be understood. In this study, we perform a systematic analysis of sense–antisense expression in response to genetic and environmental changes in yeast. We find that antisense expression is associated with genes of larger expression variability. This is characterized by more ‘switching off' at low levels of expression for genes with antisense compa...

  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. Gene expression analysis identifies global gene dosage sensitivity in cancer

    DEFF Research Database (Denmark)

    Fehrmann, Rudolf S. N.; Karjalainen, Juha M.; Krajewska, Malgorzata;

    2015-01-01

    expression. We reanalyzed 77,840 expression profiles and observed a limited set of 'transcriptional components' that describe well-known biology, explain the vast majority of variation in gene expression and enable us to predict the biological function of genes. On correcting expression profiles...... for these components, we observed that the residual expression levels (in 'functional genomic mRNA' profiling) correlated strongly with copy number. DNA copy number correlated positively with expression levels for 99% of all abundantly expressed human genes, indicating global gene dosage sensitivity. By applying...

  9. Noise in eukaryotic gene expression

    Science.gov (United States)

    Blake, William J.; KÆrn, Mads; Cantor, Charles R.; Collins, J. J.

    2003-04-01

    Transcription in eukaryotic cells has been described as quantal, with pulses of messenger RNA produced in a probabilistic manner. This description reflects the inherently stochastic nature of gene expression, known to be a major factor in the heterogeneous response of individual cells within a clonal population to an inducing stimulus. Here we show in Saccharomyces cerevisiae that stochasticity (noise) arising from transcription contributes significantly to the level of heterogeneity within a eukaryotic clonal population, in contrast to observations in prokaryotes, and that such noise can be modulated at the translational level. We use a stochastic model of transcription initiation specific to eukaryotes to show that pulsatile mRNA production, through reinitiation, is crucial for the dependence of noise on transcriptional efficiency, highlighting a key difference between eukaryotic and prokaryotic sources of noise. Furthermore, we explore the propagation of noise in a gene cascade network and demonstrate experimentally that increased noise in the transcription of a regulatory protein leads to increased cell-cell variability in the target gene output, resulting in prolonged bistable expression states. This result has implications for the role of noise in phenotypic variation and cellular differentiation.

  10. Identification of four soybean reference genes for gene expression normalization

    Science.gov (United States)

    Gene expression analysis requires the use of reference genes stably expressed independently of specific tissues or environmental conditions. Housekeeping genes (e.g., actin, tubulin, ribosomal, polyubiquitin and elongation factor 1-alpha) are commonly used as reference genes with the assumption tha...

  11. Gene expression profiles of the developing human retina

    Institute of Scientific and Technical Information of China (English)

    WANG Feng; LI Huiming; LIU Wenwen; XU Ping; HU Gengxi; CHENG Yidong; JIA Libin; HUANG Qian

    2004-01-01

    Retina is a multilayer and highly specialized tissue important in converting light into neural signals. In humans, the critical period for the formation of complex multiplayer structure takes place during embryogenesis between 12 and 28 weeks. The morphologic changes during retinal development in humans have been studied but little is known about the molecular events essential for the formation of the retina. To gain further insights into this process, cDNA microarrays containing 16361 human gene probes were used to measure the gene expression levels in retinas. Of the 16361 genes, 68.7%, 71.4% and 69.7% showed positive hybridization with cDNAs made from 12-16 week fetal, 22-26 week fetal and adult retinas. A total of 814 genes showed a minimum of 3-fold changes between the lowest and highest expression levels among three time points and among them, 106 genes had expression levels with the hybridization intensity above 100 at one or more time points. The clustering analysis suggested that the majority of differentially expressed genes were down-regulated during the retinal development. The differentially expressed genes were further classified according to functions of known genes, and were ranked in decreasing order according to frequency: development, differentiation, signal transduction, protein synthesis and translation, metabolism, DNA binding and transcription, DNA synthesis-repair-recombination, immuno-response, ion channel- transport, cell receptor, cytoskeleton, cell cycle, pro-oncogene, stress and apoptosis related genes. Among these 106 differentially expressed genes, 60 are already present in NEI retina cDNA or EST Databank but the remaining 46 genes are absent and thus identified as "function unknown". To validate gene expression data from the microarray, real-time RT-PCR was performed for 46 "function unknown" genes and 6 known retina specific expression genes, and β-actin was used as internal control. Twenty-seven of these genes showed very similar

  12. MRI of Transgene Expression: Correlation to Therapeutic Gene Expression

    Directory of Open Access Journals (Sweden)

    Tomotsugu Ichikawa

    2002-01-01

    Full Text Available Magnetic resonance imaging (MRI can provide highresolution 3D maps of structural and functional information, yet its use of mapping in vivo gene expression has only recently been explored. A potential application for this technology is to noninvasively image transgene expression. The current study explores the latter using a nonregulatable internalizing engineered transferrin receptor (ETR whose expression can be probed for with a superparamagnetic Tf-CLIO probe. Using an HSV-based amplicon vector system for transgene delivery, we demonstrate that: 1 ETR is a sensitive MR marker gene; 2 several transgenes can be efficiently expressed from a single amplicon; 3 expression of each transgene results in functional gene product; and 4 ETR gene expression correlates with expression of therapeutic genes when the latter are contained within the same amplicon. These data, taken together, suggest that MRI of ETR expression can serve as a surrogate for measuring therapeutic transgene expression.

  13. Cancer classification based on gene expression using neural networks.

    Science.gov (United States)

    Hu, H P; Niu, Z J; Bai, Y P; Tan, X H

    2015-12-21

    Based on gene expression, we have classified 53 colon cancer patients with UICC II into two groups: relapse and no relapse. Samples were taken from each patient, and gene information was extracted. Of the 53 samples examined, 500 genes were considered proper through analyses by S-Kohonen, BP, and SVM neural networks. Classification accuracy obtained by S-Kohonen neural network reaches 91%, which was more accurate than classification by BP and SVM neural networks. The results show that S-Kohonen neural network is more plausible for classification and has a certain feasibility and validity as compared with BP and SVM neural networks.

  14. Correlating Expression Data with Gene Function Using Gene Ontology

    Institute of Scientific and Technical Information of China (English)

    LIU,Qi; DENG,Yong; WANG,Chuan; SHI,Tie-Liu; LI,Yi-Xue

    2006-01-01

    Clustering is perhaps one of the most widely used tools for microarray data analysis. Proposed roles for genes of unknown function are inferred from clusters of genes similarity expressed across many biological conditions.However, whether function annotation by similarity metrics is reliable or not and to what extent the similarity in gene expression patterns is useful for annotation of gene functions, has not been evaluated. This paper made a comprehensive research on the correlation between the similarity of expression data and of gene functions using Gene Ontology. It has been found that although the similarity in expression patterns and the similarity in gene functions are significantly dependent on each other, this association is rather weak. In addition, among the three categories of Gene Ontology, the similarity of expression data is more useful for cellular component annotation than for biological process and molecular function. The results presented are interesting for the gene functions prediction research area.

  15. 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.

  16. A functional profile of gene expression in ARPE-19 cells

    Directory of Open Access Journals (Sweden)

    Johnson Dianna A

    2005-11-01

    Full Text Available Abstract Background Retinal pigment epithelium cells play an important role in the pathogenesis of age related macular degeneration. Their morphological, molecular and functional phenotype changes in response to various stresses. Functional profiling of genes can provide useful information about the physiological state of cells and how this state changes in response to disease or treatment. In this study, we have constructed a functional profile of the genes expressed by the ARPE-19 cell line of retinal pigment epithelium. Methods Using Affymetrix MAS 5.0 microarray analysis, genes expressed by ARPE-19 cells were identified. Using GeneChip® annotations, these genes were classified according to their known functions to generate a functional gene expression profile. Results We have determined that of approximately 19,044 unique gene sequences represented on the HG-U133A GeneChip® , 6,438 were expressed in ARPE-19 cells irrespective of the substrate on which they were grown (plastic, fibronectin, collagen, or Matrigel. Rather than focus our subsequent analysis on the identity or level of expression of each individual gene in this large data set, we examined the number of genes expressed within 130 functional categories. These categories were selected from a library of HG-U133A GeneChip® annotations linked to the Affymetrix MAS 5.0 data sets. Using this functional classification scheme, we were able to categorize about 70% of the expressed genes and condense the original data set of over 6,000 data points into a format with 130 data points. The resulting ARPE-19 Functional Gene Expression Profile is displayed as a percentage of ARPE-19-expressed genes. Conclusion The Profile can readily be compared with equivalent microarray data from other appropriate samples in order to highlight cell-specific attributes or treatment-induced changes in gene expression. The usefulness of these analyses is based on the assumption that the numbers of genes

  17. Multiclass cancer classification based on gene expression comparison

    Science.gov (United States)

    Yang, Sitan; Naiman, Daniel Q.

    2016-01-01

    As the complexity and heterogeneity of cancer is being increasingly appreciated through genomic analyses, microarray-based cancer classification comprising multiple discriminatory molecular markers is an emerging trend. Such multiclass classification problems pose new methodological and computational challenges for developing novel and effective statistical approaches. In this paper, we introduce a new approach for classifying multiple disease states associated with cancer based on gene expression profiles. Our method focuses on detecting small sets of genes in which the relative comparison of their expression values leads to class discrimination. For an m-class problem, the classification rule typically depends on a small number of m-gene sets, which provide transparent decision boundaries and allow for potential biological interpretations. We first test our approach on seven common gene expression datasets and compare it with popular classification methods including support vector machines and random forests. We then consider an extremely large cohort of leukemia cancer to further assess its effectiveness. In both experiments, our method yields comparable or even better results to benchmark classifiers. In addition, we demonstrate that our approach can integrate pathway analysis of gene expression to provide accurate and biological meaningful classification. PMID:24918456

  18. Computerized system for recognition of autism on the basis of gene expression microarray data.

    Science.gov (United States)

    Latkowski, Tomasz; Osowski, Stanislaw

    2015-01-01

    The aim of this paper is to provide a means to recognize a case of autism using gene expression microarrays. The crucial task is to discover the most important genes which are strictly associated with autism. The paper presents an application of different methods of gene selection, to select the most representative input attributes for an ensemble of classifiers. The set of classifiers is responsible for distinguishing autism data from the reference class. Simultaneous application of a few gene selection methods enables analysis of the ill-conditioned gene expression matrix from different points of view. The results of selection combined with a genetic algorithm and SVM classifier have shown increased accuracy of autism recognition. Early recognition of autism is extremely important for treatment of children and increases the probability of their recovery and return to normal social communication. The results of this research can find practical application in early recognition of autism on the basis of gene expression microarray analysis.

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

    Directory of Open Access Journals (Sweden)

    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

  20. Classification and expression analyses of homeobox genes from Dictyostelium discoideum

    Indian Academy of Sciences (India)

    Himanshu Mishra; Shweta Saran

    2015-06-01

    Homeobox genes are compared between genomes in an attempt to understand the evolution of animal development. The ability of the protist, Dictyostelium discoideum, to shift between uni- and multicellularity makes this group ideal for studying the genetic changes that may have occurred during this transition. We present here the first genome-wide classification and comparative genomic analysis of the 14 homeobox genes present in D. discoideum. Based on the structural alignment of the homeodomains, they can be broadly divided into TALE and non-TALE classes. When individual homeobox genes were compared with members of known class or family, we could further classify them into 3 groups, namely, TALE, OTHER and NOVEL classes, but no HOX family was found. The 5 members of TALE class could be further divided into PBX, PKNOX, IRX and CUP families; 4 homeobox genes classified as NOVEL did not show any similarity to any known homeobox genes; while the remaining 5 were classified as OTHERS as they did show certain degree of similarity to few known homeobox genes. No unique RNA expression pattern during development of D. discoideum emerged for members of an individual group. Putative promoter analysis revealed binding sites for few homeobox transcription factors among many probable factors.

  1. Risk analysis of colorectal cancer incidence by gene expression analysis

    Science.gov (United States)

    Shangkuan, Wei-Chuan; Lin, Hung-Che; Chang, Yu-Tien; Jian, Chen-En; Fan, Hueng-Chuen; Chen, Kang-Hua; Liu, Ya-Fang; Hsu, Huan-Ming; Chou, Hsiu-Ling; Yao, Chung-Tay

    2017-01-01

    Background Colorectal cancer (CRC) is one of the leading cancers worldwide. Several studies have performed microarray data analyses for cancer classification and prognostic analyses. Microarray assays also enable the identification of gene signatures for molecular characterization and treatment prediction. Objective Microarray gene expression data from the online Gene Expression Omnibus (GEO) database were used to to distinguish colorectal cancer from normal colon tissue samples. Methods We collected microarray data from the GEO database to establish colorectal cancer microarray gene expression datasets for a combined analysis. Using the Prediction Analysis for Microarrays (PAM) method and the GSEA MSigDB resource, we analyzed the 14,698 genes that were identified through an examination of their expression values between normal and tumor tissues. Results Ten genes (ABCG2, AQP8, SPIB, CA7, CLDN8, SCNN1B, SLC30A10, CD177, PADI2, and TGFBI) were found to be good indicators of the candidate genes that correlate with CRC. From these selected genes, an average of six significant genes were obtained using the PAM method, with an accuracy rate of 95%. The results demonstrate the potential of utilizing a model with the PAM method for data mining. After a detailed review of the published reports, the results confirmed that the screened candidate genes are good indicators for cancer risk analysis using the PAM method. Conclusions Six genes were selected with 95% accuracy to effectively classify normal and colorectal cancer tissues. We hope that these results will provide the basis for new research projects in clinical practice that aim to rapidly assess colorectal cancer risk using microarray gene expression analysis. PMID:28229027

  2. 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

    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

  3. Sparse Representation for Classification of Tumors Using Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Xiyi Hang

    2009-01-01

    Full Text Available Personalized drug design requires the classification of cancer patients as accurate as possible. With advances in genome sequencing and microarray technology, a large amount of gene expression data has been and will continuously be produced from various cancerous patients. Such cancer-alerted gene expression data allows us to classify tumors at the genomewide level. However, cancer-alerted gene expression datasets typically have much more number of genes (features than that of samples (patients, which imposes a challenge for classification of tumors. In this paper, a new method is proposed for cancer diagnosis using gene expression data by casting the classification problem as finding sparse representations of test samples with respect to training samples. The sparse representation is computed by the l1-regularized least square method. To investigate its performance, the proposed method is applied to six tumor gene expression datasets and compared with various support vector machine (SVM methods. The experimental results have shown that the performance of the proposed method is comparable with or better than those of SVMs. In addition, the proposed method is more efficient than SVMs as it has no need of model selection.

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

    Directory of Open Access Journals (Sweden)

    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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Amplification of kinetic oscillations in gene expression

    Science.gov (United States)

    Zhdanov, V. P.

    2008-10-01

    Because of the feedbacks between the DNA transcription and mRNA translation, the gene expression in cells may exhibit bistability and oscillations. The deterministic and stochastic calculations presented illustrate how the bistable kinetics of expression of one gene in a cell can be influenced by the kinetic oscillations in the expression of another gene. Due to stability of the states of the bistable kinetics of gene 1 and the relatively small difference between the maximum and minimum protein amounts during the oscillations of gene 2, the induced oscillations of gene 1 are found to typically be related either to the low-or high-reactive state of this gene. The quality of the induced oscillations may be appreciably better than that of the inducing oscillations. This means that gene 1 can serve as an amplifier of the kinetic oscillations of gene 2.

  10. cis sequence effects on gene expression

    Directory of Open Access Journals (Sweden)

    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.

  11. Expression Patterns of Glucose Transporter-1 Gene and Thyroid Specific Genes in Human Papillary Thyroid Carcinoma

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sungeun; Chung, Junekey; Min Haesook and others

    2014-06-15

    The expression of glucose transporter-1 (Glut-1) gene and those of major thyroid-specific genes were examined in papillary carcinoma tissues, and the expressions of these genes were compared with cancer differentiation grades. Twenty-four human papillary carcinoma tissues were included in this study. The expressions of Glut-1- and thyroid-specific genes [sodium/iodide symporter (NIS), thyroid peroxidase, thyroglobulin, TSH receptor and pendrin] were analyzed by RT-PCR. Expression levels were expressed as ratios versus the expression of beta-actin. Pathologic differentiation of papillary carcinoma was classified into a relatively well-differentiated group (n=13) and relatively less differentiated group (n=11). Glut-1 gene expression was significantly higher in the less differentiated group (0.66±0.04) than in the well-differentiated group (0.59±0.07). The expression levels of the NIS, PD and TG genes were significantly higher in the well-differentiated group (NIS: 0.67±0.20, PD: 0.65±0.21, TG: 0.74±0.16) than in the less differentiated group (NIS: 0.36±0.05, PD: 0.49±0.08, TG: 0.60±0.11), respectively. A significant negative correlation was found between Glut-1 and NIS expression, and positive correlations were found between NIS and TG, and between NIS and PD. The NIS, PD and TG genes were highly expressed in well-differentiated thyroid carcinomas, whereas the Glut-1 gene was highly expressed in less differentiated thyroid carcinomas. These findings provide a molecular rationale for the management of papillary carcinoma, especially in the selection of FDG PET or radioiodine whole-body scan and I-131-based therapy.

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

    Directory of Open Access Journals (Sweden)

    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

  13. A Bayesian model for classifying all differentially expressed proteins simultaneously in 2D PAGE gels

    Directory of Open Access Journals (Sweden)

    Wu Steven H

    2012-06-01

    Full Text Available Abstract Background Two-dimensional polyacrylamide gel electrophoresis (2D PAGE is commonly used to identify differentially expressed proteins under two or more experimental or observational conditions. Wu et al (2009 developed a univariate probabilistic model which was used to identify differential expression between Case and Control groups, by applying a Likelihood Ratio Test (LRT to each protein on a 2D PAGE. In contrast to commonly used statistical approaches, this model takes into account the two possible causes of missing values in 2D PAGE: either (1 the non-expression of a protein; or (2 a level of expression that falls below the limit of detection. Results We develop a global Bayesian model which extends the previously described model. Unlike the univariate approach, the model reported here is able treat all differentially expressed proteins simultaneously. Whereas each protein is modelled by the univariate likelihood function previously described, several global distributions are used to model the underlying relationship between the parameters associated with individual proteins. These global distributions are able to combine information from each protein to give more accurate estimates of the true parameters. In our implementation of the procedure, all parameters are recovered by Markov chain Monte Carlo (MCMC integration. The 95% highest posterior density (HPD intervals for the marginal posterior distributions are used to determine whether differences in protein expression are due to differences in mean expression intensities, and/or differences in the probabilities of expression. Conclusions Simulation analyses showed that the global model is able to accurately recover the underlying global distributions, and identify more differentially expressed proteins than the simple application of a LRT. Additionally, simulations also indicate that the probability of incorrectly identifying a protein as differentially expressed (i.e., the False

  14. 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.

  15. Gene Expression Profiling of Gastric Cancer

    Science.gov (United States)

    Marimuthu, Arivusudar; Jacob, Harrys K.C.; Jakharia, Aniruddha; Subbannayya, Yashwanth; Keerthikumar, Shivakumar; Kashyap, Manoj Kumar; Goel, Renu; Balakrishnan, Lavanya; Dwivedi, Sutopa; Pathare, Swapnali; Dikshit, Jyoti Bajpai; Maharudraiah, Jagadeesha; Singh, Sujay; Sameer Kumar, Ghantasala S; Vijayakumar, M.; Veerendra Kumar, Kariyanakatte Veeraiah; Premalatha, Chennagiri Shrinivasamurthy; Tata, Pramila; Hariharan, Ramesh; Roa, Juan Carlos; Prasad, T.S.K; Chaerkady, Raghothama; Kumar, Rekha Vijay; Pandey, Akhilesh

    2015-01-01

    Gastric cancer is the second leading cause of cancer death worldwide, both in men and women. A genomewide gene expression analysis was carried out to identify differentially expressed genes in gastric adenocarcinoma tissues as compared to adjacent normal tissues. We used Agilent’s whole human genome oligonucleotide microarray platform representing ~41,000 genes to carry out gene expression analysis. Two-color microarray analysis was employed to directly compare the expression of genes between tumor and normal tissues. Through this approach, we identified several previously known candidate genes along with a number of novel candidate genes in gastric cancer. Testican-1 (SPOCK1) was one of the novel molecules that was 10-fold upregulated in tumors. Using tissue microarrays, we validated the expression of testican-1 by immunohistochemical staining. It was overexpressed in 56% (160/282) of the cases tested. Pathway analysis led to the identification of several networks in which SPOCK1 was among the topmost networks of interacting genes. By gene enrichment analysis, we identified several genes involved in cell adhesion and cell proliferation to be significantly upregulated while those corresponding to metabolic pathways were significantly downregulated. The differentially expressed genes identified in this study are candidate biomarkers for gastric adenoacarcinoma. PMID:27030788

  16. 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...... beta-glucuronidase, resulting in an operon structure in which both genes are transcribed from a common promoter. We show that there is a linear correlation between the expressions of the two genes, which facilitates screening for mutants with suitable enzyme activities. In a second example, we show......, overexpression was achieved by introducing an additional gene copy into a phage attachment site on the chromosome. This resulted in a series of strains with phosphofructokinase activities from 1.4 to 11 times the wild-type activity level. In this example, the pfk gene was cloned upstream of a gusA gene encoding...

  17. The usability of a 15-gene hypoxia classifier as a universal hypoxia profile in various cancer cell types

    DEFF Research Database (Denmark)

    Sørensen, Brita Singers; Knudsen, Anders Bisgård; Wittrup, Catja Foged

    2015-01-01

    genes, with BNIP3 not being upregulated at hypoxic conditions in 3 out of 6 colon cancer cell lines, and ALDOA in OE21 and FAM162A and SLC2A1 in SW116 only showing limited hypoxia induction. Furthermore, in the esophagus cell lines, the normoxic and hypoxic expression levels of LOX and BNIP3 were below......BACKGROUND AND PURPOSE: A 15-gene hypoxia profile has previously demonstrated to have both prognostic and predictive impact for hypoxic modification in squamous cell carcinoma of the head and neck. This gene expression profile may also have a prognostic value in other histological cancer types...... the tissue type dependency of hypoxia induced genes included in a 15-gene hypoxic profile in carcinoma cell lines from prostate, colon, and esophagus cancer, and demonstrated that in vitro, with minor fluctuations, the genes in the hypoxic profile are hypoxia inducible, and the hypoxia profile may...

  18. Gene expression profiling during murine tooth development

    Directory of Open Access Journals (Sweden)

    Maria A dos Santos silva Landin

    2012-07-01

    Full Text Available The aim of this study was to describe the expression of genes, including ameloblastin (Ambn, amelogenin X chromosome (Amelx and enamelin (Enam during early (pre-secretory tooth development. The expression of these genes has predominantly been studied at post-secretory stages. Deoxyoligonucleotide microarrays were used to study gene expression during development of the murine first molar tooth germ at 24h intervals, starting at the eleventh embryonic day (E11.5 and up to the seventh day after birth (P7. The profile search function of Spotfire software was used to select genes with similar expression profile as the enamel genes (Ambn, Amelx and Enam. Microarray results where validated using real-time Reverse Transcription-Polymerase Chain Reaction (real-time RT-PCR, and translated proteins identified by Western blotting. In situ localisation of the Ambn, Amelx and Enam mRNAs were monitored from E12.5 to E17.5 using deoxyoligonucleotide probes. Bioinformatics analysis was used to associate biological functions with differentially (p ≤0.05 expressed (DE genes.Microarray results showed a total of 4362 genes including Ambn, Amelx and Enam to be significant differentially expressed throughout the time-course. The expression of the three enamel genes was low at pre-natal stages (E11.5-P0 increasing after birth (P1-P7. Profile search lead to isolation of 87 genes with significantly similar expression to the three enamel proteins. The mRNAs expressed in dental epithelium and epithelium derived cells. Although expression of Ambn, Amelx and Enam were lower during early tooth development compared to secretory stages enamel proteins were detectable by Western blotting. Bioinformatic analysis associated the 87 genes with multiple biological functions. Around thirty-five genes were associated with fifteen transcription factors.

  19. Microanalysis of gene expression in cultured cells

    NARCIS (Netherlands)

    E. van der Veer (Eveliene)

    1982-01-01

    textabstractIn this thesis two aspects of gene expression in cultured cells have been studied: the heterogeneity in gene expression in relation with the development and application of microchemical techniques for the prenatal diagnosis of inborn errors of metabolism and the possibility of inducing g

  20. Arabidopsis gene expression patterns during spaceflight

    Science.gov (United States)

    Paul, A.-L.; Ferl, R. J.

    The exposure of Arabidopsis thaliana (Arabidopsis) plants to spaceflight environments resulted in the differential expression of hundreds of genes. A 5 day mission on orbiter Columbia in 1999 (STS-93) carried transgenic Arabidopsis plants engineered with a transgene composed of the alcohol dehydrogenase (Adh) gene promoter linked to the β -Glucuronidase (GUS) reporter gene. The plants were used to evaluate the effects of spaceflight on two fronts. First, expression patterns visualized with the Adh/GUS transgene were used to address specifically the possibility that spaceflight induces a hypoxic stress response, and to assess whether any spaceflight response was similar to control terrestrial hypoxia-induced gene expression patterns. (Paul et al., Plant Physiol. 2001, 126:613). Second, genome-wide patterns of native gene expression were evaluated utilizing the Affymetrix ATH1 GeneChip? array of 8,000 Arabidopsis genes. As a control for the veracity of the array analyses, a selection of genes identified with the arrays was further characterized with quantitative Real-Time RT PCR (ABI - TaqmanTM). Comparison of the patterns of expression for arrays of hybridized with RNA isolated from plants exposed to spaceflight compared to the control arrays revealed hundreds of genes that were differentially expressed in response to spaceflight, yet most genes that are hallmarks of hypoxic stress were unaffected. These results will be discussed in light of current models for plant responses to the spaceflight environment, and with regard to potential future flight opportunities.

  1. 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.

  2. 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

    2017-01-01

    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. PMID:26864488

  3. Gene set analysis for longitudinal gene expression data

    Directory of Open Access Journals (Sweden)

    Piepho Hans-Peter

    2011-07-01

    Full Text Available Abstract Background Gene set analysis (GSA has become a successful tool to interpret gene expression profiles in terms of biological functions, molecular pathways, or genomic locations. GSA performs statistical tests for independent microarray samples at the level of gene sets rather than individual genes. Nowadays, an increasing number of microarray studies are conducted to explore the dynamic changes of gene expression in a variety of species and biological scenarios. In these longitudinal studies, gene expression is repeatedly measured over time such that a GSA needs to take into account the within-gene correlations in addition to possible between-gene correlations. Results We provide a robust nonparametric approach to compare the expressions of longitudinally measured sets of genes under multiple treatments or experimental conditions. The limiting distributions of our statistics are derived when the number of genes goes to infinity while the number of replications can be small. When the number of genes in a gene set is small, we recommend permutation tests based on our nonparametric test statistics to achieve reliable type I error and better power while incorporating unknown correlations between and within-genes. Simulation results demonstrate that the proposed method has a greater power than other methods for various data distributions and heteroscedastic correlation structures. This method was used for an IL-2 stimulation study and significantly altered gene sets were identified. Conclusions The simulation study and the real data application showed that the proposed gene set analysis provides a promising tool for longitudinal microarray analysis. R scripts for simulating longitudinal data and calculating the nonparametric statistics are posted on the North Dakota INBRE website http://ndinbre.org/programs/bioinformatics.php. Raw microarray data is available in Gene Expression Omnibus (National Center for Biotechnology Information with

  4. 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

    BACKGROUND: Although, systematic analysis of gene annotation is a powerful tool for interpreting gene expression data, it sometimes is blurred by incomplete gene annotation, missing expression response of key genes and secondary gene expression responses. These shortcomings may be partially...... 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...

  5. The functional landscape of mouse gene expression

    Directory of Open Access Journals (Sweden)

    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.

  6. 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.

  7. Multivariate search for differentially expressed gene combinations

    Directory of Open Access Journals (Sweden)

    Klebanov Lev

    2004-10-01

    Full Text Available Abstract Background To identify differentially expressed genes, it is standard practice to test a two-sample hypothesis for each gene with a proper adjustment for multiple testing. Such tests are essentially univariate and disregard the multidimensional structure of microarray data. A more general two-sample hypothesis is formulated in terms of the joint distribution of any sub-vector of expression signals. Results By building on an earlier proposed multivariate test statistic, we propose a new algorithm for identifying differentially expressed gene combinations. The algorithm includes an improved random search procedure designed to generate candidate gene combinations of a given size. Cross-validation is used to provide replication stability of the search procedure. A permutation two-sample test is used for significance testing. We design a multiple testing procedure to control the family-wise error rate (FWER when selecting significant combinations of genes that result from a successive selection procedure. A target set of genes is composed of all significant combinations selected via random search. Conclusions A new algorithm has been developed to identify differentially expressed gene combinations. The performance of the proposed search-and-testing procedure has been evaluated by computer simulations and analysis of replicated Affymetrix gene array data on age-related changes in gene expression in the inner ear of CBA mice.

  8. Gene Expression Profiling in Porcine Fetal Thymus

    Institute of Scientific and Technical Information of China (English)

    Yanjiong Chen; Shengbin Li; Lin Ye; Jianing Geng; Yajun Deng; Songnian Hu

    2003-01-01

    obtain an initial overview of gene diversity and expression pattern in porcinethymus, 11,712 ESTs (Expressed Sequence Tags) from 100-day-old porcine thymus(FTY) were sequenced and 7,071 cleaned ESTs were used for gene expressionanalysis. Clustered by the PHRAP program, 959 contigs and 3,074 singlets wereobtained. Blast search showed that 806 contigs and 1,669 singlets (totally 5,442ESTs) had homologues in GenBank and 1,629 ESTs were novel. According to theGene Ontology classification, 36.99% ESTs were cataloged into the gene expressiongroup, indicating that although the functional gene (18.78% in defense group) ofthymus is expressed in a certain degree, the 100-day-old porcine thymus still existsin a developmental stage. Comparative analysis showed that the gene expressionpattern of the 100-day-old porcine thymus is similar to that of the human infantthymus.

  9. 基于随机森林的潜在k近邻算法及其在基因表达数据分类中的应用%Random forest based potential k nearest neighbor classifier and its application in gene expression data

    Institute of Scientific and Technical Information of China (English)

    杨帆; 林琛; 周绮凤; 符长虹; 罗林开

    2012-01-01

    随机森林被广泛应用于包括癌症诊断在内的生物信息学领域.从自适应k近邻的角度分析了随机森林的分类机理,分析其存在的信息损失,据此提出一种新的投票机制,称为基于随机森林的潜在k近邻算法RF-PN,铠够充分利用决策树上的OOB样本信息,显著改善随机森林的分类性能.6个癌症基因表达数据集上的对比实验表明,RF-PN的分类准确率优于原算法.%Random forests (RF) has been widely used in bioinformatics especially in cancer diagnosis. This paper studies the classification scheme of RF from the viewpoint of adaptive k nearest neighbors, analyzes the information loss in RF, and proposes a new voting method called RF-based potential nearest neighbor which can use the information of OOB samples in each tree and show significant improvement. Comparison result on 6 cancer gene expression datasets demonstrated that RF-PN got better predictive accuracy than RF.

  10. Phytochrome-regulated Gene Expression

    Institute of Scientific and Technical Information of China (English)

    Peter H. Quail

    2007-01-01

    Identification of all genes involved in the phytochrome (phy)-mediated responses of plants to their light environment is an important goal in providing an overall understanding of light-regulated growth and development. This article highlights and integrates the central findings of two recent comprehensive studies in Arabidopsis that have identified the genome-wide set of phy-regulated genes that respond rapidly to red-light signals upon first exposure of dark-grown seedlings, and have tested the functional relevance to normal seedling photomorphogenesis of an initial subset of these genes. The data: (a) reveal considerable complexity in the channeling of the light signals through the different phy-family members (phyA to phyE) to responsive genes; (b) identify a diversity of transcription-factor-encoding genes as major early, if not primary, targets of phy signaling, and, therefore, as potentially important regulators in the transcriptional-network hierarchy; and (c) identify auxin-related genes as the dominant class among rapidly-regulated, hormone-related genes. However, reverse-genetic functional profiling of a selected subset of these genes reveals that only a limited fraction are necessary for optimal phy-induced seedling deetiolation.

  11. Nucleosome repositioning underlies dynamic gene expression.

    Science.gov (United States)

    Nocetti, Nicolas; Whitehouse, Iestyn

    2016-03-15

    Nucleosome repositioning at gene promoters is a fundamental aspect of the regulation of gene expression. However, the extent to which nucleosome repositioning is used within eukaryotic genomes is poorly understood. Here we report a comprehensive analysis of nucleosome positions as budding yeast transit through an ultradian cycle in which expression of >50% of all genes is highly synchronized. We present evidence of extensive nucleosome repositioning at thousands of gene promoters as genes are activated and repressed. During activation, nucleosomes are relocated to allow sites of general transcription factor binding and transcription initiation to become accessible. The extent of nucleosome shifting is closely related to the dynamic range of gene transcription and generally related to DNA sequence properties and use of the coactivators TFIID or SAGA. However, dynamic gene expression is not limited to SAGA-regulated promoters and is an inherent feature of most genes. While nucleosome repositioning occurs pervasively, we found that a class of genes required for growth experience acute nucleosome shifting as cells enter the cell cycle. Significantly, our data identify that the ATP-dependent chromatin-remodeling enzyme Snf2 plays a fundamental role in nucleosome repositioning and the expression of growth genes. We also reveal that nucleosome organization changes extensively in concert with phases of the cell cycle, with large, regularly spaced nucleosome arrays being established in mitosis. Collectively, our data and analysis provide a framework for understanding nucleosome dynamics in relation to fundamental DNA-dependent transactions.

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

    Science.gov (United States)

    Teng, Shaolei; Yang, Jack Y; Wang, Liangjiang

    2013-01-01

    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. 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. 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.

  13. Using Ensemble Models to Classify the Sentiment Expressed in Suicide Notes

    Science.gov (United States)

    McCart, James A.; Finch, Dezon K.; Jarman, Jay; Hickling, Edward; Lind, Jason D.; Richardson, Matthew R.; Berndt, Donald J.; Luther, Stephen L.

    2012-01-01

    In 2007, suicide was the tenth leading cause of death in the U.S. Given the significance of this problem, suicide was the focus of the 2011 Informatics for Integrating Biology and the Bedside (i2b2) Natural Language Processing (NLP) shared task competition (track two). Specifically, the challenge concentrated on sentiment analysis, predicting the presence or absence of 15 emotions (labels) simultaneously in a collection of suicide notes spanning over 70 years. Our team explored multiple approaches combining regular expression-based rules, statistical text mining (STM), and an approach that applies weights to text while accounting for multiple labels. Our best submission used an ensemble of both rules and STM models to achieve a micro-averaged F1 score of 0.5023, slightly above the mean from the 26 teams that competed (0.4875). PMID:22879763

  14. Using ensemble models to classify the sentiment expressed in suicide notes.

    Science.gov (United States)

    McCart, James A; Finch, Dezon K; Jarman, Jay; Hickling, Edward; Lind, Jason D; Richardson, Matthew R; Berndt, Donald J; Luther, Stephen L

    2012-01-01

    In 2007, suicide was the tenth leading cause of death in the U.S. Given the significance of this problem, suicide was the focus of the 2011 Informatics for Integrating Biology and the Bedside (i2b2) Natural Language Processing (NLP) shared task competition (track two). Specifically, the challenge concentrated on sentiment analysis, predicting the presence or absence of 15 emotions (labels) simultaneously in a collection of suicide notes spanning over 70 years. Our team explored multiple approaches combining regular expression-based rules, statistical text mining (STM), and an approach that applies weights to text while accounting for multiple labels. Our best submission used an ensemble of both rules and STM models to achieve a micro-averaged F(1) score of 0.5023, slightly above the mean from the 26 teams that competed (0.4875).

  15. Soft Topographic Maps for Clustering and Classifying Bacteria Using Housekeeping Genes

    Directory of Open Access Journals (Sweden)

    Massimo La Rosa

    2011-01-01

    Full Text Available The Self-Organizing Map (SOM algorithm is widely used for building topographic maps of data represented in a vectorial space, but it does not operate with dissimilarity data. Soft Topographic Map (STM algorithm is an extension of SOM to arbitrary distance measures, and it creates a map using a set of units, organized in a rectangular lattice, defining data neighbourhood relationships. In the last years, a new standard for identifying bacteria using genotypic information began to be developed. In this new approach, phylogenetic relationships of bacteria could be determined by comparing a stable part of the bacteria genetic code, the so-called “housekeeping genes.” The goal of this work is to build a topographic representation of bacteria clusters, by means of self-organizing maps, starting from genotypic features regarding housekeeping genes.

  16. Digital gene expression signatures for maize development.

    Science.gov (United States)

    Eveland, Andrea L; Satoh-Nagasawa, Namiko; Goldshmidt, Alexander; Meyer, Sandra; Beatty, Mary; Sakai, Hajime; Ware, Doreen; Jackson, David

    2010-11-01

    Genome-wide expression signatures detect specific perturbations in developmental programs and contribute to functional resolution of key regulatory networks. In maize (Zea mays) inflorescences, mutations in the RAMOSA (RA) genes affect the determinacy of axillary meristems and thus alter branching patterns, an important agronomic trait. In this work, we developed and tested a framework for analysis of tag-based, digital gene expression profiles using Illumina's high-throughput sequencing technology and the newly assembled B73 maize reference genome. We also used a mutation in the RA3 gene to identify putative expression signatures specific to stem cell fate in axillary meristem determinacy. The RA3 gene encodes a trehalose-6-phosphate phosphatase and may act at the interface between developmental and metabolic processes. Deep sequencing of digital gene expression libraries, representing three biological replicate ear samples from wild-type and ra3 plants, generated 27 million 20- to 21-nucleotide reads with frequencies spanning 4 orders of magnitude. Unique sequence tags were anchored to 3'-ends of individual transcripts by DpnII and NlaIII digests, which were multiplexed during sequencing. We mapped 86% of nonredundant signature tags to the maize genome, which associated with 37,117 gene models and unannotated regions of expression. In total, 66% of genes were detected by at least nine reads in immature maize ears. We used comparative genomics to leverage existing information from Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) in functional analyses of differentially expressed maize genes. Results from this study provide a basis for the analysis of short-read expression data in maize and resolved specific expression signatures that will help define mechanisms of action for the RA3 gene.

  17. Gene expression profile of sprinter's muscle.

    Science.gov (United States)

    Yoshioka, M; Tanaka, H; Shono, N; Shindo, M; St-Amand, J

    2007-12-01

    We have characterized the global gene expression profile in left vastus lateralis muscles of sprinters and sedentary men. The gene expression profile was analyzed by using serial analysis of gene expression (SAGE) method. The abundantly expressed transcripts in the sprinter's muscle were mainly involved in contraction and energy metabolism, whereas six transcripts were corresponding to potentially novel transcripts. Thirty-eight transcripts were differentially expressed between the sprinter and sedentary individuals. Moreover, sprinters showed higher expressions of both uncharacterized and potentially novel transcripts. Sprinters also highly expressed seven transcripts, such as glycine-rich protein, myosin heavy polypeptide (MYH) 2, expressed sequence tag similar to (EST) fructose-bisphosphate aldolase 1 isoform A (ALDOA), glyceraldehyde-3-phosphate dehydrogenase and ATP synthase F0 subunit 6. On the other hand, 20 transcripts such as MYH1, tropomyosin 2 and 3, troponin C slow, C2 fast, I slow, T1 slow and T3 fast, myoglobin, creatine kinase, ALDOA, glycogen phosphorylase, cytochrome c oxidase II and III, and NADH dehydrogenase 1 and 2 showed lower expression levels in the sprinters than the sedentary controls. The current study has characterized the global gene expressions in sprinters and identified a number of transcripts that can be subjected to further mechanistic analysis.

  18. Kinetics of Kaposi’s Sarcoma-Associated Herpesvirus Gene Expression

    OpenAIRE

    Sun, Ren; Lin, Su-Fang; Staskus, Katherine; Gradoville, Lyndle; Grogan, Elizabeth; Haase, Ashley; Miller, George

    1999-01-01

    Herpesvirus gene expression can be classified into four distinct kinetic stages: latent, immediate early, early, and late. Here we characterize the kinetic class of a group of 16 Kaposi’s sarcoma-associated herpesvirus (KSHV)/human herpesvirus 8 genes in a cultured primary effusion cell line and examine the expression of a subset of these genes in KS biopsies. Expression of two latent genes, LANA and vFLIP, was constitutive and was not induced by chemicals that induce the lytic cycle in prima...

  19. Widespread ectopic expression of olfactory receptor genes

    Directory of Open Access Journals (Sweden)

    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.

  20. 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.

  1. Regulation of meiotic gene expression in plants

    Directory of Open Access Journals (Sweden)

    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.

  2. 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.

  3. 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...

  4. Bayesian modeling of differential gene expression.

    Science.gov (United States)

    Lewin, Alex; Richardson, Sylvia; Marshall, Clare; Glazier, Anne; Aitman, Tim

    2006-03-01

    We present a Bayesian hierarchical model for detecting differentially expressing genes that includes simultaneous estimation of array effects, and show how to use the output for choosing lists of genes for further investigation. We give empirical evidence that expression-level dependent array effects are needed, and explore different nonlinear functions as part of our model-based approach to normalization. The model includes gene-specific variances but imposes some necessary shrinkage through a hierarchical structure. Model criticism via posterior predictive checks is discussed. Modeling the array effects (normalization) simultaneously with differential expression gives fewer false positive results. To choose a list of genes, we propose to combine various criteria (for instance, fold change and overall expression) into a single indicator variable for each gene. The posterior distribution of these variables is used to pick the list of genes, thereby taking into account uncertainty in parameter estimates. In an application to mouse knockout data, Gene Ontology annotations over- and underrepresented among the genes on the chosen list are consistent with biological expectations.

  5. Perspectives: Gene Expression in Fisheries Management

    Science.gov (United States)

    Nielsen, Jennifer L.; Pavey, Scott A.

    2010-01-01

    Functional genes and gene expression have been connected to physiological traits linked to effective production and broodstock selection in aquaculture, selective implications of commercial fish harvest, and adaptive changes reflected in non-commercial fish populations subject to human disturbance and climate change. Gene mapping using single nucleotide polymorphisms (SNPs) to identify functional genes, gene expression (analogue microarrays and real-time PCR), and digital sequencing technologies looking at RNA transcripts present new concepts and opportunities in support of effective and sustainable fisheries. Genomic tools have been rapidly growing in aquaculture research addressing aspects of fish health, toxicology, and early development. Genomic technologies linking effects in functional genes involved in growth, maturation and life history development have been tied to selection resulting from harvest practices. Incorporating new and ever-increasing knowledge of fish genomes is opening a different perspective on local adaptation that will prove invaluable in wild fish conservation and management. Conservation of fish stocks is rapidly incorporating research on critical adaptive responses directed at the effects of human disturbance and climate change through gene expression studies. Genomic studies of fish populations can be generally grouped into three broad categories: 1) evolutionary genomics and biodiversity; 2) adaptive physiological responses to a changing environment; and 3) adaptive behavioral genomics and life history diversity. We review current genomic research in fisheries focusing on those that use microarrays to explore differences in gene expression among phenotypes and within or across populations, information that is critically important to the conservation of fish and their relationship to humans.

  6. Gene Expression Profiles of Inflammatory Myopathies

    Directory of Open Access Journals (Sweden)

    J Gordon Millichap

    2002-11-01

    Full Text Available The simultaneous expression of 10,000 genes was measured, using Affymetrix GeneChip microarrays, in muscle specimens from 45 patients with various myopathies (dystrophy, congenital myopathy, and inflammatory myopathy examined at Brigham and Women’s Hospital, and Children’s Hospital, Harvard Medical School, Boston, MA.

  7. Translational control of gene expression and disease

    NARCIS (Netherlands)

    Calkhoven, Cornelis F; Müller, Christine; Leutz, Achim

    2002-01-01

    In the past decade, translational control has been shown to be crucial in the regulation of gene expression. Research in this field has progressed rapidly, revealing new control mechanisms and adding constantly to the list of translationally regulated genes. There is accumulating evidence that trans

  8. 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.

  9. Gene expression studies using microarrays

    NARCIS (Netherlands)

    Burgess, Janette

    2001-01-01

    1. The rapid progression of the collaborative sequencing programmes that are unravelling the complete genome sequences of many organisms are opening pathways for new approaches to gene analysis. As the sequence data become available, the bottleneck in biological research will shift to understanding

  10. Insulin gene: organisation, expression and regulation.

    Science.gov (United States)

    Dumonteil, E; Philippe, J

    1996-06-01

    Insulin, a major hormone of the endocrine pancreas, plays a key role in the control of glucose homeostasis. This review discusses the mechanisms of cell-specific expression and regulation of the insulin gene. Whereas expression is restricted to islet beta-cells in adults, the insulin gene is more widely expressed at several embryonic stages, although the role of extrapancreatic expression is still unclear. beta-cell-specific expression relies on the interactions of 5'-flanking sequence motifs of the promoter with a number of ubiquitous and islet-specific transcription factors. IEF1 and IPF-1, by their binding to the E and A boxes, respectively, of the insulin gene promoter, appear to be the major determinants of beta-cell-specific expression. IEF1 is a heterodimer of the basic helix-loop-helix family of transcription factors, whereas IPF-1 belongs to the homeodomain-containing family. beta-cell specific determinants are conserved throughout evolution, although the human insulin gene 5'-flanking sequence also contains a polymorphic minisatellite which is unique to primates and may play a role in insulin gene regulation. Glucose modulates insulin gene transcription, with multiple elements of the promoter involved in glucose responsiveness. Remarkably, IPF-1 and IEF1 are involved in both beta-cell-specific expression and glucose regulation of the insulin gene. cAMP also regulates insulin gene transcription through a CRE, in response to various hormonal stimuli. On the whole, recent studies have provided a better understanding of beta-cell differentiation and function.

  11. Application of multidisciplinary analysis to gene expression.

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Xuefel (University of New Mexico, Albuquerque, NM); Kang, Huining (University of New Mexico, Albuquerque, NM); Fields, Chris (New Mexico State University, Las Cruces, NM); Cowie, Jim R. (New Mexico State University, Las Cruces, NM); Davidson, George S.; Haaland, David Michael; Sibirtsev, Valeriy (New Mexico State University, Las Cruces, NM); Mosquera-Caro, Monica P. (University of New Mexico, Albuquerque, NM); Xu, Yuexian (University of New Mexico, Albuquerque, NM); Martin, Shawn Bryan; Helman, Paul (University of New Mexico, Albuquerque, NM); Andries, Erik (University of New Mexico, Albuquerque, NM); Ar, Kerem (University of New Mexico, Albuquerque, NM); Potter, Jeffrey (University of New Mexico, Albuquerque, NM); Willman, Cheryl L. (University of New Mexico, Albuquerque, NM); Murphy, Maurice H. (University of New Mexico, Albuquerque, NM)

    2004-01-01

    Molecular analysis of cancer, at the genomic level, could lead to individualized patient diagnostics and treatments. The developments to follow will signal a significant paradigm shift in the clinical management of human cancer. Despite our initial hopes, however, it seems that simple analysis of microarray data cannot elucidate clinically significant gene functions and mechanisms. Extracting biological information from microarray data requires a complicated path involving multidisciplinary teams of biomedical researchers, computer scientists, mathematicians, statisticians, and computational linguists. The integration of the diverse outputs of each team is the limiting factor in the progress to discover candidate genes and pathways associated with the molecular biology of cancer. Specifically, one must deal with sets of significant genes identified by each method and extract whatever useful information may be found by comparing these different gene lists. Here we present our experience with such comparisons, and share methods developed in the analysis of an infant leukemia cohort studied on Affymetrix HG-U95A arrays. In particular, spatial gene clustering, hyper-dimensional projections, and computational linguistics were used to compare different gene lists. In spatial gene clustering, different gene lists are grouped together and visualized on a three-dimensional expression map, where genes with similar expressions are co-located. In another approach, projections from gene expression space onto a sphere clarify how groups of genes can jointly have more predictive power than groups of individually selected genes. Finally, online literature is automatically rearranged to present information about genes common to multiple groups, or to contrast the differences between the lists. The combination of these methods has improved our understanding of infant leukemia. While the complicated reality of the biology dashed our initial, optimistic hopes for simple answers from

  12. Gene expression profiling: can we identify the right target genes?

    Directory of Open Access Journals (Sweden)

    J. E. Loyd

    2008-12-01

    Full Text Available Gene expression profiling allows the simultaneous monitoring of the transcriptional behaviour of thousands of genes, which may potentially be involved in disease development. Several studies have been performed in idiopathic pulmonary fibrosis (IPF, which aim to define genetic links to the disease in an attempt to improve the current understanding of the underlying pathogenesis of the disease and target pathways for intervention. Expression profiling has shown a clear difference in gene expression between IPF and normal lung tissue, and has identified a wide range of candidate genes, including those known to encode for proteins involved in extracellular matrix formation and degradation, growth factors and chemokines. Recently, familial pulmonary fibrosis cohorts have been examined in an attempt to detect specific genetic mutations associated with IPF. To date, these studies have identified families in which IPF is associated with mutations in the gene encoding surfactant protein C, or with mutations in genes encoding components of telomerase. Although rare and clearly not responsible for the disease in all individuals, the nature of these mutations highlight the importance of the alveolar epithelium in disease pathogenesis and demonstrate the potential for gene expression profiling in helping to advance the current understanding of idiopathic pulmonary fibrosis.

  13. Regulation of immunoglobulin gene rearrangement and expression.

    Science.gov (United States)

    Taussig, M J; Sims, M J; Krawinkel, U

    1989-05-01

    The molecular genetic events leading to Ig expression and their control formed the topic of a recent EMBO workshop. This report by Michael Taussig, Martin Sims and Ulrich Krawinkel discusses contributions dealing with genes expressed in early pre-B cells, the mechanism of rearrangement, aberrant rearrangements seen in B cells of SCID mice, the feedback control of rearrangement as studied in transgenic mice, the control of Ig expression at the transcriptional and post-transcriptional levels, and class switching.

  14. Vitamin D-mediated gene expression.

    Science.gov (United States)

    Lowe, K E; Maiyar, A C; Norman, A W

    1992-01-01

    The steroid hormone 1,25(OH)2D3 modulates the expression of a wide variety of genes in a tissue- and developmentally specific manner. It is well established that 1,25(OH)2D3 can up- or downregulate the expression of genes involved in cell proliferation, differentiation, and mineral homeostasis. The hormone exerts its genomic effects via interactions with the vitamin D receptor or VDR, a member of the superfamily of hormone-activated nuclear receptors which can regulate eukaryotic gene expression. The ligand-bound receptor acts as a transcription factor that binds to specific DNA sequences, HREs, in target gene promoters. The DNA-binding domains of the steroid hormone receptors are highly conserved and contain two zinc-finger motifs that recognize the HREs. The spacing and orientation of the HRE half-sites, as well as the HRE sequence, are critical for proper discrimination by the various receptors. Other nuclear factors such as fos and jun can influence vitamin D-mediated gene expression. A wide range of experimental techniques has been used to increase our understanding of how 1,25(OH)2D3 and its receptor play a central role in gene expression.

  15. Modulation of imprinted gene expression following superovulation.

    Science.gov (United States)

    Fortier, Amanda L; McGraw, Serge; Lopes, Flavia L; Niles, Kirsten M; Landry, Mylène; Trasler, Jacquetta M

    2014-05-05

    Although assisted reproductive technologies increase the risk of low birth weight and genomic imprinting disorders, the precise underlying causes remain unclear. Using a mouse model, we previously showed that superovulation alters the expression of imprinted genes in the placenta at 9.5days (E9.5) of gestation. Here, we investigate whether effects of superovulation on genomic imprinting persisted at later stages of development and assess the surviving fetuses for growth and morphological abnormalities. Superovulation, followed by embryo transfer at E3.5, as compared to spontaneous ovulation (controls), resulted in embryos of normal size and weight at 14.5 and 18.5days of gestation. The normal monoallelic expression of the imprinted genes H19, Snrpn and Kcnq1ot1 was unaffected in either the placentae or the embryos from the superovulated females at E14.5 or E18.5. However, for the paternally expressed imprinted gene Igf2, superovulation generated placentae with reduced production of the mature protein at E9.5 and significantly more variable mRNA levels at E14.5. We propose that superovulation results in the ovulation of abnormal oocytes with altered expression of imprinted genes, but that the coregulated genes of the imprinted gene network result in modulated expression. Copyright © 2014. Published by Elsevier Ireland Ltd.

  16. Kinetics of Kaposi's sarcoma-associated herpesvirus gene expression.

    Science.gov (United States)

    Sun, R; Lin, S F; Staskus, K; Gradoville, L; Grogan, E; Haase, A; Miller, G

    1999-03-01

    Herpesvirus gene expression can be classified into four distinct kinetic stages: latent, immediate early, early, and late. Here we characterize the kinetic class of a group of 16 Kaposi's sarcoma-associated herpesvirus (KSHV)/human herpesvirus 8 genes in a cultured primary effusion cell line and examine the expression of a subset of these genes in KS biopsies. Expression of two latent genes, LANA and vFLIP, was constitutive and was not induced by chemicals that induce the lytic cycle in primary effusion lymphoma (PEL) cell lines. An immediate-early gene, Rta (open reading frame 50 [ORF50]), was induced within 4 h of the addition of n-butyrate, and its 3.6-kb mRNA was resistant to inhibition by cycloheximide. Early genes, including K3 and K5 that are homologues of the "immediate-early" gene of bovine herpesvirus 4, K8 that is a positional homologue of Epstein-Barr virus BZLF1, vMIP II, vIL-6, and polyadenylated nuclear (PAN) RNA, appeared 8 to 13 h after chemical induction. A second group of early genes that were slightly delayed in their appearance included viral DHFR, thymidylate synthase, vMIP I, G protein-coupled receptor, K12, vBcl2, and a lytic transcript that overlapped LANA. The transcript of sVCA (ORF65), a late gene whose expression was abolished by Phosphonoacetic acid, an inhibitor of KSHV DNA replication, did not appear until 30 h after induction. Single-cell assays indicated that the induction of lytic cycle transcripts resulted from the recruitment of additional cells into the lytic cycle. In situ hybridization of KS biopsies showed that about 3% of spindle-shaped tumor cells expressed Rta, ORF K8, vIL-6, vMIP I, vBcl-2, PAN RNA, and sVCA. Our study shows that several KSHV-encoded homologues of cellular cytokines, chemokines, and antiapoptotic factors are expressed during the viral lytic cycle in PEL cell lines and in KS biopsies. The lytic cycle of KSHV, probably under the initial control of the KSHV/Rta gene, may directly contribute to tumor

  17. Gene expression of the endolymphatic sac.

    Science.gov (United States)

    Friis, Morten; Martin-Bertelsen, Tomas; Friis-Hansen, Lennart; Winther, Ole; Henao, Ricardo; Sørensen, Mads Sølvsten; Qvortrup, Klaus

    2011-12-01

    The endolymphatic sac is part of the membranous inner ear and is thought to play a role in the fluid homeostasis and immune defense of the inner ear; however, the exact function of the endolymphatic sac is not fully known. Many of the detected mRNAs in this study suggest that the endolymphatic sac has multiple and diverse functions in the inner ear. The objective of this study was to provide a comprehensive review of the genes expressed in the endolymphatic sac in the rat and perform a functional characterization based on measured mRNA abundance. Microarray technology was used to investigate the gene expression of the endolymphatic sac with the surrounding dura. Characteristic and novel endolymphatic sac genes were determined by comparing with expressions in pure dura. In all, 463 genes were identified specific for the endolymphatic sac. Functional annotation clustering revealed 29 functional clusters.

  18. A novel methodology for finding the regulation on gene expression data

    Institute of Scientific and Technical Information of China (English)

    Wei Liu; Bo Wang; Jarka Glassey; Elaine Martin; Jian Zhao

    2009-01-01

    DNA microarray technology is a high throughput and parallel technique for genomic investigation due to its advantages of simul-taneously surveying features of large scales complex data in biology. This paper aims to find feature subset to build the classifier for gene expression data analysis. At first, K-means clustering algorithm was carried out on the dataset of yeast cell cycle. Based on Rand cal-culation, a statistical method was used to pick out the data points (genes) for classifier design. Meanwhile, the principal component anal-ysis was applied to help to construct the classifier. For the validation of classifier built and prediction of a target subset of genes, discriminant analysis in terms of partial least square regression and artificial neural network were also performed.

  19. Regulation of gene expression in human tendinopathy

    Science.gov (United States)

    2011-01-01

    Background Chronic tendon injuries, also known as tendinopathies, are common among professional and recreational athletes. These injuries result in a significant amount of morbidity and health care expenditure, yet little is known about the molecular mechanisms leading to tendinopathy. Methods We have used histological evaluation and molecular profiling to determine gene expression changes in 23 human patients undergoing surgical procedures for the treatment of chronic tendinopathy. Results Diseased tendons exhibit altered extracellular matrix, fiber disorientation, increased cellular content and vasculature, and the absence of inflammatory cells. Global gene expression profiling identified 983 transcripts with significantly different expression patterns in the diseased tendons. Global pathway analysis further suggested altered expression of extracellular matrix proteins and the lack of an appreciable inflammatory response. Conclusions Identification of the pathways and genes that are differentially regulated in tendinopathy samples will contribute to our understanding of the disease and the development of novel therapeutics. PMID:21539748

  20. 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.

  1. 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.

  2. Paternally expressed genes predominate in the placenta.

    Science.gov (United States)

    Wang, Xu; Miller, Donald C; Harman, Rebecca; Antczak, Douglas F; Clark, Andrew G

    2013-06-25

    The discovery of genomic imprinting through studies of manipulated mouse embryos indicated that the paternal genome has a major influence on placental development. However, previous research has not demonstrated paternal bias in imprinted genes. We applied RNA sequencing to trophoblast tissue from reciprocal hybrids of horse and donkey, where genotypic differences allowed parent-of-origin identification of most expressed genes. Using this approach, we identified a core group of 15 ancient imprinted genes, of which 10 were paternally expressed. An additional 78 candidate imprinted genes identified by RNA sequencing also showed paternal bias. Pyrosequencing was used to confirm the imprinting status of six of the genes, including the insulin receptor (INSR), which may play a role in growth regulation with its reciprocally imprinted ligand, histone acetyltransferase-1 (HAT1), a gene involved in chromatin modification, and lymphocyte antigen 6 complex, locus G6C, a newly identified imprinted gene in the major histocompatibility complex. The 78 candidate imprinted genes displayed parent-of-origin expression bias in placenta but not fetus, and most showed less than 100% silencing of the imprinted allele. Some displayed variability in imprinting status among individuals. This variability results in a unique epigenetic signature for each placenta that contributes to variation in the intrauterine environment and thus presents the opportunity for natural selection to operate on parent-of-origin differential regulation. Taken together, these features highlight the plasticity of imprinting in mammals and the central importance of the placenta as a target tissue for genomic imprinting.

  3. Gene expression profiling of solitary fibrous tumors.

    Directory of Open Access Journals (Sweden)

    François Bertucci

    Full Text Available BACKGROUND: Solitary fibrous tumors (SFTs are rare spindle-cell tumors. Their cell-of-origin and molecular basis are poorly known. They raise several clinical problems. Differential diagnosis may be difficult, prognosis is poorly apprehended by histoclinical features, and no effective therapy exists for advanced stages. METHODS: We profiled 16 SFT samples using whole-genome DNA microarrays and analyzed their expression profiles with publicly available profiles of 36 additional SFTs and 212 soft tissue sarcomas (STSs. Immunohistochemistry was applied to validate the expression of some discriminating genes. RESULTS: SFTs displayed whole-genome expression profiles more homogeneous and different from STSs, but closer to genetically-simple than genetically-complex STSs. The SFTs/STSs comparison identified a high percentage (∼30% of genes as differentially expressed, most of them without any DNA copy number alteration. One of the genes most overexpressed in SFTs encoded the ALDH1 stem cell marker. Several upregulated genes and associated ontologies were also related to progenitor/stem cells. SFTs also overexpressed genes encoding therapeutic targets such as kinases (EGFR, ERBB2, FGFR1, JAK2, histone deacetylases, or retinoic acid receptors. Their overexpression was found in all SFTs, regardless the anatomical location. Finally, we identified a 31-gene signature associated with the mitotic count, containing many genes related to cell cycle/mitosis, including AURKA. CONCLUSION: We established a robust repertoire of genes differentially expressed in SFTs. Certain overexpressed genes could provide new diagnostic (ALDH1A1, prognostic (AURKA and/or therapeutic targets.

  4. Soybean physiology and gene expression during drought.

    Science.gov (United States)

    Stolf-Moreira, R; Medri, M E; Neumaier, N; Lemos, N G; Pimenta, J A; Tobita, S; Brogin, R L; Marcelino-Guimarães, F C; Oliveira, M C N; Farias, J R B; Abdelnoor, R V; Nepomuceno, A L

    2010-10-05

    Soybean genotypes MG/BR46 (Conquista) and BR16, drought-tolerant and -sensitive, respectively, were compared in terms of morphophysiological and gene-expression responses to water stress during two stages of development. Gene-expression analysis showed differential responses in Gmdreb1a and Gmpip1b mRNA expression within 30 days of water-deficit initiation in MG/BR46 (Conquista) plants. Within 45 days of initiating stress, Gmp5cs and Gmpip1b had relatively higher expression. Initially, BR16 showed increased expression only for Gmdreb1a, and later (45 days) for Gmp5cs, Gmdefensin and Gmpip1b. Only BR16 presented down-regulated expression of genes, such as Gmp5cs and Gmpip1b, 30 days after the onset of moisture stress, and Gmgols after 45 days of stress. The faster perception of water stress in MG/BR46 (Conquista) and the better maintenance of up-regulated gene expression than in the sensitive BR16 genotype imply mechanisms by which the former is better adapted to tolerate moisture deficiency.

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

    Directory of Open Access Journals (Sweden)

    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

  6. Early gene expression changes with rush immunotherapy

    Directory of Open Access Journals (Sweden)

    Barnett Sherry

    2011-09-01

    Full Text Available Abstract Background To examine whether whole genome expression profiling could reveal changes in mRNA expression of peripheral blood mononuclear cells (PBMC from allergic patients undergoing rush immunotherapy (RIT that might be manifest within the first few months of treatment. Methods For this study, PBMC from three allergic patients undergoing RIT were assessed at four timepoints: prior to RIT, at 1 week and 7 week post-RIT, during build-up and at 4 months, after establishment of a maintenance dose. PBMC mRNA gene expression changes over time were determined by oligonucleotide microarrays using the Illumina Human-6 BeadChip Platform, which simultaneously interrogates expression profiles of > 47,000 transcripts. Differentially expressed genes were identified using well-established statistical analysis for microarrays. In addition, we analyzed peripheral blood basophil high-affinity IgE receptor (Fc epsilon RI expression and T-regulatory cell frequency as detected by expression of CD3+CD4+CD25bright cells at each timepoint using flow cytometry. Results In comparing the initial 2 timepoints with the final 2 timepoints and analyzing for genes with ≥1.5-fold expression change (p less than or equal to 0.05, BH-FDR, we identified 507 transcripts. At a 2-fold change (p less than or equal to 0.05, BH-FDR, we found 44 transcripts. Of these, 28 were up-regulated and 16 were down-regulated genes. From these datasets, we have identified changes in immunologically relevant genes from both the innate and adaptive response with upregulation of expressed genes for molecules including IL-1β, IL-8, CD40L, BTK and BCL6. At the 4 month timepoint, we noted a downward trend in Fc epsilon RI expression in each of the three patients and increased allergen-specific IgG4 levels. No change was seen in the frequency of peripheral T-regulatory cells expressed over the four timepoints. Conclusions We observed significant changes in gene expression early in peripheral

  7. Gene expression correlation analysis predicts involvement of high- and low-confidence risk genes in different stages of prostate carcinogenesis.

    Science.gov (United States)

    Yano, Kojiro

    2010-12-01

    Whole genome association studies have identified many loci associated with the risk of prostate cancer (PC). However, very few of the genes associated with these loci have been related to specific processes of prostate carcinogenesis. Therefore I inferred biological functions associated with these risk genes using gene expression correlation analysis. PC risk genes reported in the literature were classified as having high (Plow (Phigh-confidence genes and other genes in the microarray dataset, whereas correlation between low-confidence genes and other genes in PC showed smaller decrease. Genes involved in developmental processes were significantly correlated with all risk gene categories. Ectoderm development genes, which may be related to squamous metaplasia, and genes enriched in fetal prostate stem cells (PSCs) showed strong association with the high-confidence genes. The association between the PSC genes and the low-confidence genes was weak, but genes related to neural system genes showed strong association with low-confidence genes. The high-confidence risk genes may be associated with an early stage of prostate carcinogenesis, possibly involving PSCs and squamous metaplasia. The low-confidence genes may be involved in a later stage of carcinogenesis. © 2010 Wiley-Liss, Inc.

  8. 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

  9. 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.

  10. Alternative-splicing-mediated gene expression

    Science.gov (United States)

    Wang, Qianliang; Zhou, Tianshou

    2014-01-01

    Alternative splicing (AS) is a fundamental process during gene expression and has been found to be ubiquitous in eukaryotes. However, how AS impacts gene expression levels both quantitatively and qualitatively remains to be fully explored. Here, we analyze two common models of gene expression, each incorporating a simple splice mechanism that a pre-mRNA is spliced into two mature mRNA isoforms in a probabilistic manner. In the constitutive expression case, we show that the steady-state molecular numbers of two mature mRNA isoforms follow mutually independent Poisson distributions. In the bursting expression case, we demonstrate that the tail decay of the steady-state distribution for both mature mRNA isoforms that in general are not mutually independent can be characterized by the product of mean burst size and splicing probability. In both cases, we find that AS can efficiently modulate both the variability (measured by variance) and the noise level of the total mature mRNA, and in particular, the latter is always lower than the noise level of the pre-mRNA, implying that AS always reduces the noise. These results altogether reveal that AS is a mechanism of efficiently controlling the gene expression noise.

  11. Gene expression profiling for targeted cancer treatment.

    Science.gov (United States)

    Yuryev, Anton

    2015-01-01

    There is certain degree of frustration and discontent in the area of microarray gene expression data analysis of cancer datasets. It arises from the mathematical problem called 'curse of dimensionality,' which is due to the small number of samples available in training sets, used for calculating transcriptional signatures from the large number of differentially expressed (DE) genes, measured by microarrays. The new generation of causal reasoning algorithms can provide solutions to the curse of dimensionality by transforming microarray data into activity of a small number of cancer hallmark pathways. This new approach can make feature space dimensionality optimal for mathematical signature calculations. The author reviews the reasons behind the current frustration with transcriptional signatures derived from DE genes in cancer. He also provides an overview of the novel methods for signature calculations based on differentially variable genes and expression regulators. Furthermore, the authors provide perspectives on causal reasoning algorithms that use prior knowledge about regulatory events described in scientific literature to identify expression regulators responsible for the differential expression observed in cancer samples. The author advocates causal reasoning methods to calculate cancer pathway activity signatures. The current challenge for these algorithms is in ensuring quality of the knowledgebase. Indeed, the development of cancer hallmark pathway collections, together with statistical algorithms to transform activity of expression regulators into pathway activity, are necessary for causal reasoning to be used in cancer research.

  12. Predicting metastasized seminoma using gene expression.

    Science.gov (United States)

    Ruf, Christian G; Linbecker, Michael; Port, Matthias; Riecke, Armin; Schmelz, Hans U; Wagner, Walter; Meineke, Victor; Abend, Michael

    2012-07-01

    Treatment options for testis cancer depend on the histological subtype as well as on the clinical stage. An accurate staging is essential for correct treatment. The 'golden standard' for staging purposes is CT, but occult metastasis cannot be detected with this method. Currently, parameters such as primary tumour size, vessel invasion or invasion of the rete testis are used for predicting occult metastasis. Last year the association of these parameters with metastasis could not be validated in a new independent cohort. Gene expression analysis in testis cancer allowed discrimination between the different histological subtypes (seminoma and non-seminoma) as well as testis cancer and normal testis tissue. In a two-stage study design we (i) screened the whole genome (using human whole genome microarrays) for candidate genes associated with the metastatic stage in seminoma and (ii) validated and quantified gene expression of our candidate genes (real-time quantitative polymerase chain reaction) on another independent group. Gene expression measurements of two of our candidate genes (dopamine receptor D1 [DRD1] and family with sequence similarity 71, member F2 [FAM71F2]) examined in primary testis cancers made it possible to discriminate the metastasis status in seminoma. The discriminative ability of the genes exceeded the predictive significance of currently used histological/pathological parameters. Based on gene expression analysis the present study provides suggestions for improved individual decision making either in favour of early adjuvant therapy or increased surveillance. To evaluate the usefulness of gene expression profiling for predicting metastatic status in testicular seminoma at the time of first diagnosis compared with established clinical and pathological parameters. Total RNA was isolated from testicular tumours of metastasized patients (12 patients, clinical stage IIa-III), non-metastasized patients (40, clinical stage I) and adjacent 'normal' tissue

  13. Gene expression profiles in skeletal muscle after gene electrotransfer

    DEFF Research Database (Denmark)

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

    2007-01-01

    with the control muscles. Most interestingly, no changes in the expression of proteins involved in inflammatory responses or muscle regeneration was detected, indicating limited muscle damage and regeneration. Histological analysis revealed structural changes with loss of cell integrity and striation pattern......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......) 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...

  14. 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

  15. 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.

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

    DEFF Research Database (Denmark)

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

    2012-01-01

    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......¿=¿76) colon cancers, was reproduced. The stages II and III colon cancers were subsequently classified as either stage I-like (good prognosis) or stage IV-like (poor prognosis) and assessed by the 36 months cumulative incidence of relapse. RESULTS: In the GEO data set, results were reproducible in stage...... 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...

  17. Isolation and expression analysis of LEA genes in peanut (Arachis hypogaea L.)

    Indian Academy of Sciences (India)

    Lei Su; Chuan-Zhi Zhao; Yu-Ping Bi; Shu-Bo Wan; Han Xia; Xing-Jun Wang

    2011-06-01

    Late embryogenesis abundant (LEA) protein family is a large protein family that includes proteins accumulated at late stages of seed development or in vegetative tissues in response to drought, salinity, cold stress and exogenous application of abscisic acid. In order to isolate peanut genes, an expressed sequence tag (EST) sequencing project was carried out using a peanut seed cDNA library. From 6258 ESTs, 19 LEA-encoding genes were identified and could be classified into eight distinct groups. Expression of these genes in seeds at different developmental stages and in various peanut tissues was analysed by semi-quantitative RT-PCR. The results showed that expression levels of LEA genes were generally high in seeds. Some LEA protein genes were expressed at a high level in non-seed tissues such as root, stem, leaf, flower and gynophore. These results provided valuable information for the functional and regulatory studies on peanut LEA genes.

  18. Expression patterns and action analysis of genes associated with inflammatory responses during rat liver regeneration

    Institute of Scientific and Technical Information of China (English)

    Heng-Yi Shao; Li-Feng Zhao; Cun-Shuan Xu

    2007-01-01

    AIM: To study the relationship between inflammatory response and liver regeneration (LR) at transcriptional level.METHODS: After partial hepatectomy (PH) of rats,the genes associated with inflammatory response were obtained according to the databases, and the gene expression changes during LR were checked by the Rat Genome 230 2.0 array.RESULTS: Two hundred and thirty-nine genes were associated with liver regeneration. The initial and total expressing gene numbers found in initiation phase (0.5-4 h after PH), G0/G1 transition (4-6 h after PH),cell proliferation (6-66 h after PH), cell differentiation and structure-function reconstruction (66-168 h after PH) of liver regeneration were 107, 34, 126, 6 and 107,92, 233, 145 respectively, showing that the associated genes were mainly triggered at the beginning of liver regeneration, and worked at different phases. According to their expression similarity, these genes were classified into 5 groups: only up-regulated, predominantly up-,only down-, predominantly down-, up- and down-,involving 92, 25, 77, 14 and 31 genes, respectively. The total times of their up- and down-regulated expression were 975 and 494, respectively, demonstrating that the expressions of the majority of genes were increased,and that of a few genes were decreased. Their time relevance was classified into 13 groups, showing that the cellular physiological and biochemical activities were staggered during liver regeneration. According to gene expression patterns, they were classified into 33 types,suggesting that the activities were diverse and complex during liver regeneration.CONCLUSION: Inflammatory response is closely associated with liver regeneration, in which 239 LRassociated genes play an important role.

  19. Polyandry and sex-specific gene expression.

    Science.gov (United States)

    Mank, Judith E; Wedell, Nina; Hosken, David J

    2013-03-05

    Polyandry is widespread in nature, and has important evolutionary consequences for the evolution of sexual dimorphism and sexual conflict. Although many of the phenotypic consequences of polyandry have been elucidated, our understanding of the impacts of polyandry and mating systems on the genome is in its infancy. Polyandry can intensify selection on sexual characters and generate more intense sexual conflict. This has consequences for sequence evolution, but also for sex-biased gene expression, which acts as a link between mating systems, sex-specific selection and the evolution of sexual dimorphism. We discuss this and the remarkable confluence of sexual-conflict theory and patterns of gene expression, while also making predictions about transcription patterns, mating systems and sexual conflict. Gene expression is a key link in the genotype-phenotype chain, and although in its early stages, understanding the sexual selection-transcription relationship will provide significant insights into this critical association.

  20. Visualizing Gene Expression In Situ

    Energy Technology Data Exchange (ETDEWEB)

    Burlage, R.S.

    1998-11-02

    Visualizing bacterial cells and describing their responses to the environment are difficult tasks. Their small size is the chief reason for the difficulty, which means that we must often use many millions of cells in a sample in order to determine what the average response of the bacteria is. However, an average response can sometimes mask important events in bacterial physiology, which means that our understanding of these organisms will suffer. We have used a variety of instruments to visualize bacterial cells, all of which tell us something different about the sample. We use a fluorescence activated cell sorter to sort cells based on the fluorescence provided by bioreporter genes, and these can be used to select for particular genetic mutations. Cells can be visualized by epifluorescent microscopy, and sensitive photodetectors can be added that allow us to find a single bacterial cell that is fluorescent or bioluminescent. We have also used standard photomultipliers to examine cell aggregates as field bioreporter microorganisms. Examples of each of these instruments show how our understanding of bacterial physiology has changed with the technology.

  1. Gene expression profiles in irradiated cancer cells

    Science.gov (United States)

    Minafra, L.; Bravatà, V.; Russo, G.; Ripamonti, M.; Gilardi, M. C.

    2013-07-01

    Knowledge of the molecular and genetic mechanisms underlying cellular response to radiation may provide new avenues to develop innovative predictive tests of radiosensitivity of tumours and normal tissues and to improve individual therapy. Nowadays very few studies describe molecular changes induced by hadrontherapy treatments, therefore this field has to be explored and clarified. High-throughput methodologies, such as DNA microarray, allow us to analyse mRNA expression of thousands of genes simultaneously in order to discover new genes and pathways as targets of response to hadrontherapy. Our aim is to elucidate the molecular networks involved in the sensitivity/resistance of cancer cell lines subjected to hadrontherapy treatments with a genomewide approach by using cDNA microarray technology to identify gene expression profiles and candidate genes responsible of differential cellular responses.

  2. Gene expression profiles in irradiated cancer cells

    Energy Technology Data Exchange (ETDEWEB)

    Minafra, L.; Bravatà, V.; Russo, G.; Ripamonti, M.; Gilardi, M. C. [IBFM CNR - LATO, Cefalù, Segrate (Italy)

    2013-07-26

    Knowledge of the molecular and genetic mechanisms underlying cellular response to radiation may provide new avenues to develop innovative predictive tests of radiosensitivity of tumours and normal tissues and to improve individual therapy. Nowadays very few studies describe molecular changes induced by hadrontherapy treatments, therefore this field has to be explored and clarified. High-throughput methodologies, such as DNA microarray, allow us to analyse mRNA expression of thousands of genes simultaneously in order to discover new genes and pathways as targets of response to hadrontherapy. Our aim is to elucidate the molecular networks involved in the sensitivity/resistance of cancer cell lines subjected to hadrontherapy treatments with a genomewide approach by using cDNA microarray technology to identify gene expression profiles and candidate genes responsible of differential cellular responses.

  3. Gene Expression in the Human Endolymphatic Sac

    DEFF Research Database (Denmark)

    Møller, Martin Nue; Kirkeby, Svend; Vikeså, Jonas

    2015-01-01

    OBJECTIVES/HYPOTHESIS: The purpose of the present study is to explore, demonstrate, and describe the expression of genes related to the solute carrier (SLC) molecules of ion transporters in the human endolymphatic sac. STUDY DESIGN: cDNA microarrays and immunohistochemistry were used for analyses...... of fresh human endolymphatic sac tissue samples. METHODS: Twelve tissue samples of the human endolymphatic sac were obtained during translabyrinthine surgery for vestibular schwannoma. Microarray technology was used to investigate tissue sample expression of solute carrier family genes, using adjacent dura...... mater as control. Immunohistochemistry was used for verification of translation of selected genes, as well as localization of the specific protein within the sac. RESULTS: An extensive representation of the SLC family genes were upregulated in the human endolymphatic sac, including SLC26a4 Pendrin, SLC4...

  4. Extracting expression modules from perturbational gene expression compendia

    Directory of Open Access Journals (Sweden)

    Van Dijck Patrick

    2008-04-01

    Full Text Available Abstract Background Compendia of gene expression profiles under chemical and genetic perturbations constitute an invaluable resource from a systems biology perspective. However, the perturbational nature of such data imposes specific challenges on the computational methods used to analyze them. In particular, traditional clustering algorithms have difficulties in handling one of the prominent features of perturbational compendia, namely partial coexpression relationships between genes. Biclustering methods on the other hand are specifically designed to capture such partial coexpression patterns, but they show a variety of other drawbacks. For instance, some biclustering methods are less suited to identify overlapping biclusters, while others generate highly redundant biclusters. Also, none of the existing biclustering tools takes advantage of the staple of perturbational expression data analysis: the identification of differentially expressed genes. Results We introduce a novel method, called ENIGMA, that addresses some of these issues. ENIGMA leverages differential expression analysis results to extract expression modules from perturbational gene expression data. The core parameters of the ENIGMA clustering procedure are automatically optimized to reduce the redundancy between modules. In contrast to the biclusters produced by most other methods, ENIGMA modules may show internal substructure, i.e. subsets of genes with distinct but significantly related expression patterns. The grouping of these (often functionally related patterns in one module greatly aids in the biological interpretation of the data. We show that ENIGMA outperforms other methods on artificial datasets, using a quality criterion that, unlike other criteria, can be used for algorithms that generate overlapping clusters and that can be modified to take redundancy between clusters into account. Finally, we apply ENIGMA to the Rosetta compendium of expression profiles for

  5. Sequencing and Gene Expression Analysis of Leishmania tropica LACK Gene.

    Directory of Open Access Journals (Sweden)

    Nour Hammoudeh

    2014-12-01

    Full Text Available Leishmania Homologue of receptors for Activated C Kinase (LACK antigen is a 36-kDa protein, which provokes a very early immune response against Leishmania infection. There are several reports on the expression of LACK through different life-cycle stages of genus Leishmania, but only a few of them have focused on L.tropica.The present study provides details of the cloning, DNA sequencing and gene expression of LACK in this parasite species. First, several local isolates of Leishmania parasites were typed in our laboratory using PCR technique to verify of Leishmania parasite species. After that, LACK gene was amplified and cloned into a vector for sequencing. Finally, the expression of this molecule in logarithmic and stationary growth phase promastigotes, as well as in amastigotes, was evaluated by Reverse Transcription-PCR (RT-PCR technique.The typing result confirmed that all our local isolates belong to L.tropica. LACK gene sequence was determined and high similarity was observed with the sequences of other Leishmania species. Furthermore, the expression of LACK gene in both promastigotes and amastigotes forms was confirmed.Overall, the data set the stage for future studies of the properties and immune role of LACK gene products.

  6. Increased expression of PIN1 gene in papillary thyroid carcinoma

    Directory of Open Access Journals (Sweden)

    Lewiński Andrzej

    2011-01-01

    Full Text Available Abstract Background Peptidyl-prolyl cis/trans isomerase (Pin1, encoded by PIN1 gene with locus in chromosome 19p13, is an enzyme that catalytically induces conformational changes in proteins after phosphorylation on serine or threonine residues preceding proline (pSer/Thr-Pro motifs; in this way, it has an influence on protein interactions and intracellular localizations of proteins. The aim of the study were: 1 an assessment of PIN1 gene expression level in benign and malignant thyroid lesions; 2 the evaluation of possible correlations between gene expression and histopathological variants of papillary thyroid carcinoma (PTC or tumour size, classified according to TNM classification of primary tumours (in case of PTC only; 3 the estimation of possible relationships between expression of the gene in question and patients' sex or age. Methods Seventy (70 tissue samples were analyzed: 32 cases of PTC, 7 cases of medullary thyroid carcinoma (MTC, 7 cases of follicular adenoma (FA, and 24 cases of nodular goitre (NG. In real-time polymerase chain reaction (real-time PCR, two-step RT-PCR (reverse transcriptase-polymerase chain reaction in an ABI PRISM 7500 Sequence Detection System was employed. The PIN1 gene expression level was assessed, calculating the mean relative quantification rate (RQ rate increase for each sample. Results The level of PIN1 gene expression (compared to that in macroscopically unchanged thyroid tissue was higher in PTC group than those in FA, MTC and/or NG groups, but the statistical significance was noted for difference between PTC and NG groups only. On the other hand, the differences of RQ rate value between different PTC variants were statistically insignificant. No correlations were found between RQ values and tumour size, as well as between RQ values and patients' sex or age in PTC group. Conclusions The PIN1 gene expression may have - in future - an important meaning in the diagnostics of PTC and in understanding its

  7. Mechanical Feedback and Arrest in Gene Expression

    Science.gov (United States)

    Sevier, Stuart; Levine, Herbert

    The ability to watch biochemical events at the single-molecule level has increasingly revealed that stochasticity plays a leading role in many biological phenomena. One important and well know example is the noisy, ``bursty'' manner of transcription. Recent experiments have revealed relationships between the level and noise in gene expression hinting at deeper stochastic connections. In this talk we will discuss how the mechanical nature of transcription can explain this relationship and examine the limits that the physical aspects of transcription place on gene expression.

  8. Argudas: arguing with gene expression information

    CERN Document Server

    McLeod, Kenneth; Burger, Albert

    2010-01-01

    In situ hybridisation gene expression information helps biologists identify where a gene is expressed. However, the databases that republish the experimental information are often both incomplete and inconsistent. This paper examines a system, Argudas, designed to help tackle these issues. Argudas is an evolution of an existing system, and so that system is reviewed as a means of both explaining and justifying the behaviour of Argudas. Throughout the discussion of Argudas a number of issues will be raised including the appropriateness of argumentation in biology and the challenges faced when integrating apparently similar online biological databases.

  9. Optogenetics for gene expression in mammalian cells.

    Science.gov (United States)

    Müller, Konrad; Naumann, Sebastian; Weber, Wilfried; Zurbriggen, Matias D

    2015-02-01

    Molecular switches that are controlled by chemicals have evolved as central research instruments in mammalian cell biology. However, these tools are limited in terms of their spatiotemporal resolution due to freely diffusing inducers. These limitations have recently been addressed by the development of optogenetic, genetically encoded, and light-responsive tools that can be controlled with the unprecedented spatiotemporal precision of light. In this article, we first provide a brief overview of currently available optogenetic tools that have been designed to control diverse cellular processes. Then, we focus on recent developments in light-controlled gene expression technologies and provide the reader with a guideline for choosing the most suitable gene expression system.

  10. Genes Expressed in Human Tumor Endothelium

    Science.gov (United States)

    St. Croix, Brad; Rago, Carlo; Velculescu, Victor; Traverso, Giovanni; Romans, Katharine E.; Montgomery, Elizabeth; Lal, Anita; Riggins, Gregory J.; Lengauer, Christoph; Vogelstein, Bert; Kinzler, Kenneth W.

    2000-08-01

    To gain a molecular understanding of tumor angiogenesis, we compared gene expression patterns of endothelial cells derived from blood vessels of normal and malignant colorectal tissues. Of over 170 transcripts predominantly expressed in the endothelium, 79 were differentially expressed, including 46 that were specifically elevated in tumor-associated endothelium. Several of these genes encode extracellular matrix proteins, but most are of unknown function. Most of these tumor endothelial markers were expressed in a wide range of tumor types, as well as in normal vessels associated with wound healing and corpus luteum formation. These studies demonstrate that tumor and normal endothelium are distinct at the molecular level, a finding that may have significant implications for the development of anti-angiogenic therapies.

  11. [Imprinting genes and it's expression in Arabidopsis].

    Science.gov (United States)

    Zhang, Hong-Yu; Xu, Pei-Zhou; Yang, Hua; Wu, Xian-Jun

    2010-07-01

    Genomic imprinting refers to the phenomenon that the expression of a gene copy depends on its parent of origin. The Arabidopsis imprinted FIS (Fertilisation-independent seed) genes, mea, fis2, and fie, play essential roles in the repression of central cell and the regulation of early endosperm development. fis mutants display two phenotypes: autonomous diploid endosperm development when fertilization is absent and un-cellularised endosperm formation when fertilization occurs. The FIS Polycomb protein complex including the above three FIS proteins catalyzes histone H3 K27 tri-methylation on target loci. DME (DEMETER), a DNA glycosylase, and AtMET1 (Methyltransferase1), a DNA methyltransferase, are involved in the regulation of imprinted expression of both mea and fis2. This review summarizes the studies on the Arabidopsis imprinted FIS genes and other related genes. Recent works have shown that the insertion of transposons may affect nearby gene expression, which may be the main driving force behind the evolution of genomic imprinting. This summary covers the achievements on Arabidopsis imprinted genes will provide important information for studies on genomic imprinting in the important crops such as rice and maize.

  12. Designing genes for successful protein expression.

    Science.gov (United States)

    Welch, Mark; Villalobos, Alan; Gustafsson, Claes; Minshull, Jeremy

    2011-01-01

    DNA sequences are now far more readily available in silico than as physical DNA. De novo gene synthesis is an increasingly cost-effective method for building genetic constructs, and effectively removes the constraint of basing constructs on extant sequences. This allows scientists and engineers to experimentally test their hypotheses relating sequence to function. Molecular biologists, and now synthetic biologists, are characterizing and cataloging genetic elements with specific functions, aiming to combine them to perform complex functions. However, the most common purpose of synthetic genes is for the expression of an encoded protein. The huge number of different proteins makes it impossible to characterize and catalog each functional gene. Instead, it is necessary to abstract design principles from experimental data: data that can be generated by making predictions followed by synthesizing sequences to test those predictions. Because of the degeneracy of the genetic code, design of gene sequences to encode proteins is a high-dimensional problem, so there is no single simple formula to guarantee success. Nevertheless, there are several straightforward steps that can be taken to greatly increase the probability that a designed sequence will result in expression of the encoded protein. In this chapter, we discuss gene sequence parameters that are important for protein expression. We also describe algorithms for optimizing these parameters, and troubleshooting procedures that can be helpful when initial attempts fail. Finally, we show how many of these methods can be accomplished using the synthetic biology software tool Gene Designer.

  13. Genes of periodontopathogens expressed during human disease.

    Science.gov (United States)

    Song, Yo-Han; Kozarov, Emil V; Walters, Sheila M; Cao, Sam Linsen; Handfield, Martin; Hillman, Jeffrey D; Progulske-Fox, Ann

    2002-12-01

    Since many bacterial genes are environmentally regulated, the screening for virulence-associated factors using classical genetic and molecular biology approaches can be biased under laboratory growth conditions of a given pathogen, because the required conditions for expression of many virulence factors may not occur during in vitro growth. Thus, technologies have been developed during the past several years to identify genes that are expressed during disease using animal models of human disease. However, animal models are not always truly representative of human disease, and with many pathogens, there is no appropriate animal model. A new technology, in vivo-induced antigen technology (IVIAT) was thus engineered and tested in our laboratory to screen for genes of pathogenic organisms induced specifically in humans, without the use of animal or artificial models of infection. This technology uses pooled sera from patients to probe for genes expressed exclusively in vivo (or ivi, in vivo-induced genes). IVIAT was originally designed for the study of Actinobacillus actinomycetemcomitans pathogenesis, but we have now extended it to other oral pathogens including Porphyromonas gingivalis. One hundred seventy-one thousand (171,000) clones from P. gingivalis strain W83 were screened and 144 were confirmed positive. Over 300,000 A. actinomycetemcomitans clones were probed, and 116 were confirmed positive using a quantitative blot assay. MAT has proven useful in identifying previously unknown in vivo-induced genes that are likely involved in virulence and are thus excellent candidates for use in diagnostic : and therapeutic strategies, including vaccine design.

  14. Human gene correlation analysis (HGCA): a tool for the identification of transcriptionally co-expressed genes.

    Science.gov (United States)

    Michalopoulos, Ioannis; Pavlopoulos, Georgios A; Malatras, Apostolos; Karelas, Alexandros; Kostadima, Myrto-Areti; Schneider, Reinhard; Kossida, Sophia

    2012-06-06

    Bioinformatics and high-throughput technologies such as microarray studies allow the measure of the expression levels of large numbers of genes simultaneously, thus helping us to understand the molecular mechanisms of various biological processes in a cell. We calculate the Pearson Correlation Coefficient (r-value) between probe set signal values from Affymetrix Human Genome Microarray samples and cluster the human genes according to the r-value correlation matrix using the Neighbour Joining (NJ) clustering method. A hyper-geometric distribution is applied on the text annotations of the probe sets to quantify the term overrepresentations. The aim of the tool is the identification of closely correlated genes for a given gene of interest and/or the prediction of its biological function, which is based on the annotations of the respective gene cluster. Human Gene Correlation Analysis (HGCA) is a tool to classify human genes according to their coexpression levels and to identify overrepresented annotation terms in correlated gene groups. It is available at: http://biobank-informatics.bioacademy.gr/coexpression/.

  15. Sequence and gene expression evolution of paralogous genes in willows.

    Science.gov (United States)

    Harikrishnan, Srilakshmy L; Pucholt, Pascal; Berlin, Sofia

    2015-12-22

    Whole genome duplications (WGD) have had strong impacts on species diversification by triggering evolutionary novelties, however, relatively little is known about the balance between gene loss and forces involved in the retention of duplicated genes originating from a WGD. We analyzed putative Salicoid duplicates in willows, originating from the Salicoid WGD, which took place more than 45 Mya. Contigs were constructed by de novo assembly of RNA-seq data derived from leaves and roots from two genotypes. Among the 48,508 contigs, 3,778 pairs were, based on fourfold synonymous third-codon transversion rates and syntenic positions, predicted to be Salicoid duplicates. Both copies were in most cases expressed in both tissues and 74% were significantly differentially expressed. Mean Ka/Ks was 0.23, suggesting that the Salicoid duplicates are evolving by purifying selection. Gene Ontology enrichment analyses showed that functions related to DNA- and nucleic acid binding were over-represented among the non-differentially expressed Salicoid duplicates, while functions related to biosynthesis and metabolism were over-represented among the differentially expressed Salicoid duplicates. We propose that the differentially expressed Salicoid duplicates are regulatory neo- and/or subfunctionalized, while the non-differentially expressed are dose sensitive, hence, functionally conserved. Multiple evolutionary processes, thus drive the retention of Salicoid duplicates in willows.

  16. Reshaping of global gene expression networks and sex‐biased gene expression by integration of a young gene

    National Research Council Canada - National Science Library

    Chen, Sidi; Ni, Xiaochun; Krinsky, Benjamin H; Zhang, Yong E; Vibranovski, Maria D; White, Kevin P; Long, Manyuan

    2012-01-01

    ...‐biased gene expression in Drosophila . This 4–6 million‐year‐old factor, named Zeus for its role in male fecundity, originated through retroposition of a highly conserved housekeeping gene, Caf40...

  17. The TRANSFAC system on gene expression regulation.

    Science.gov (United States)

    Wingender, E; Chen, X; Fricke, E; Geffers, R; Hehl, R; Liebich, I; Krull, M; Matys, V; Michael, H; Ohnhäuser, R; Prüss, M; Schacherer, F; Thiele, S; Urbach, S

    2001-01-01

    The TRANSFAC database on transcription factors and their DNA-binding sites and profiles (http://www.gene-regulation.de/) has been quantitatively extended and supplemented by a number of modules. These modules give information about pathologically relevant mutations in regulatory regions and transcription factor genes (PathoDB), scaffold/matrix attached regions (S/MARt DB), signal transduction (TRANSPATH) and gene expression sources (CYTOMER). Altogether, these distinct database modules constitute the TRANSFAC system. They are accompanied by a number of program routines for identifying potential transcription factor binding sites or for localizing individual components in the regulatory network of a cell.

  18. A data mining approach for classifying DNA repair genes into ageing-related or non-ageing-related

    Directory of Open Access Journals (Sweden)

    Vasieva Olga

    2011-01-01

    Full Text Available Abstract Background The ageing of the worldwide population means there is a growing need for research on the biology of ageing. DNA damage is likely a key contributor to the ageing process and elucidating the role of different DNA repair systems in ageing is of great interest. In this paper we propose a data mining approach, based on classification methods (decision trees and Naive Bayes, for analysing data about human DNA repair genes. The goal is to build classification models that allow us to discriminate between ageing-related and non-ageing-related DNA repair genes, in order to better understand their different properties. Results The main patterns discovered by the classification methods are as follows: (a the number of protein-protein interactions was a predictor of DNA repair proteins being ageing-related; (b the use of predictor attributes based on protein-protein interactions considerably increased predictive accuracy of attributes based on Gene Ontology (GO annotations; (c GO terms related to "response to stimulus" seem reasonably good predictors of ageing-relatedness for DNA repair genes; (d interaction with the XRCC5 (Ku80 protein is a strong predictor of ageing-relatedness for DNA repair genes; and (e DNA repair genes with a high expression in T lymphocytes are more likely to be ageing-related. Conclusions The above patterns are broadly integrated in an analysis discussing relations between Ku, the non-homologous end joining DNA repair pathway, ageing and lymphocyte development. These patterns and their analysis support non-homologous end joining double strand break repair as central to the ageing-relatedness of DNA repair genes. Our work also showcases the use of protein interaction partners to improve accuracy in data mining methods and our approach could be applied to other ageing-related pathways.

  19. Gene expression profiling in porcine mammary gland during lactation and identification of breed- and developmental-stage-specific genes

    Institute of Scientific and Technical Information of China (English)

    SU; Zhixi; DONG; Xinjiao; ZHANG; Bing; ZENG; Yanwu; FU; Yan; YU; Jun; HU; Songnian

    2006-01-01

    A total of 28941 ESTs were sequenced from five 5(-directed non-normalized cDNA libraries, which were assembled into 2212 contigs and 5642 singlets using CAP3. These sequences were annotated and clustered into 6857 unique genes, 2072 of which having no functional annotations were considered as novel genes. These genes were further classified into Gene Ontology categories. By comparing the expression profiles, we identified some breed- and developmental-stage-specific gene groups. These genes may be relative to reproductive performance or play important roles in milk synthesis, secretion and mammary involution. The unknown EST sequences and expression profiles at different developmental stages and breeds are very important resources for further research.

  20. Expression patterns and action analysis of genes associated with blood coagulation responses during rat liver regeneration

    Institute of Scientific and Technical Information of China (English)

    Li-Feng Zhao; Wei-Min Zhang; Cun-Shuan Xu

    2006-01-01

    AIM:To study the blood coagulation response after partial hepatectomy (PH) at transcriptional level.METHODS:After PH of rats, the associated genes with blood coagulation were obtained through reference to the databases, and the gene expression changes in rat regenerating liver were analyzed by the Rat Genome 230 2.0 array.RESULTS: It was found that 107 genes were associated with liver regeneration. The initially and totally expressing gene numbers occurring in initiation phase of liver regeneration (0.5-4 h after PH), G0/G1 transition (4-6 h after PH), cell proliferation (6-66 h after PH), cell differentiation and structure-function reconstruction (66-168 h after PH) were 44, 11, 58, 7 and 44, 33,100, 71 respectively, showing that the associated genes were mainly triggered in the forepart and prophase, and worked at different phases. According to their expression similarity, these genes were classified into 5 groups:only up-, predominantly up-, only down-, predominantly down-, up- and down-regulation, involving 44, 8, 36,13 and 6 genes, respectively, and the total times of their up- and down-regulation expression were 342 and 253, respectively, demonstrating that the number of the up-regulated genes was more than that of the downregulated genes. Their time relevance was classified into 15 groups, showing that the cellular physiological and biochemical activities were staggered during liver regeneration. According to gene expression patterns,they were classified into 29 types, suggesting that their protein activities were diverse and complex during liver regeneration.CONCLUSION: The blood coagulation response is enhanced mainly in the forepart, prophase and anaphase of liver regeneration, in which the response in the forepart, prophase of liver regeneration can prevent the bleeding caused by partial hepatectomy, whereas that in the anaphase contributes to the structure-function reorganization of regenerating liver. In the process,107 genes associated with liver

  1. Stimulated Gene Expression Profiles as a Blood Marker of Major Depressive Disorder

    NARCIS (Netherlands)

    Spijker, Sabine; Van Zanten, Jeroen S.; De Jong, Simone; Penninx, Brenda; van Dyck, Richard; Zitman, Frans G.; Smit, Jan H.; Ylstra, Bauke; Smit, August B.; Hoogendijk, Witte J. G.

    2010-01-01

    Background: Major depressive disorder (MDD) is a moderately heritable disorder with a high lifetime prevalence. At present, laboratory blood tests to support MDD diagnosis are not available. Methods: We used a classifier approach on blood gene expression profiles of a unique set of unmedicated subje

  2. 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.

  3. The frustrated gene: origins of eukaryotic gene expression

    OpenAIRE

    Madhani, Hiten D.

    2013-01-01

    Eukarytotic gene expression is frustrated by a series of steps that are generally not observed in prokaryotes and are therefore not essential for the basic chemistry of transcription and translation. Their evolution may have been driven by the need to defend against parasitic nucleic acids.

  4. Classifying Microorganisms

    DEFF Research Database (Denmark)

    Sommerlund, Julie

    2006-01-01

    This paper describes the coexistence of two systems for classifying organisms and species: a dominant genetic system and an older naturalist system. The former classifies species and traces their evolution on the basis of genetic characteristics, while the latter employs physiological characteris......This paper describes the coexistence of two systems for classifying organisms and species: a dominant genetic system and an older naturalist system. The former classifies species and traces their evolution on the basis of genetic characteristics, while the latter employs physiological...... and integration possible, the field of molecular biology seems to be overwhelmingly homogeneous, and in need of heterogeneity and conflict to add drive and momentum to the work being carried out. The paper is based on observations of daily life in a molecular microbiology laboratory at the Technical University...

  5. Classifying Motion.

    Science.gov (United States)

    Duzen, Carl; And Others

    1992-01-01

    Presents a series of activities that utilizes a leveling device to classify constant and accelerated motion. Applies this classification system to uniform circular motion and motion produced by gravitational force. (MDH)

  6. The Low Noise Limit in Gene Expression.

    Directory of Open Access Journals (Sweden)

    Roy D Dar

    Full Text Available Protein noise measurements are increasingly used to elucidate biophysical parameters. Unfortunately noise analyses are often at odds with directly measured parameters. Here we show that these inconsistencies arise from two problematic analytical choices: (i the assumption that protein translation rate is invariant for different proteins of different abundances, which has inadvertently led to (ii the assumption that a large constitutive extrinsic noise sets the low noise limit in gene expression. While growing evidence suggests that transcriptional bursting may set the low noise limit, variability in translational bursting has been largely ignored. We show that genome-wide systematic variation in translational efficiency can-and in the case of E. coli does-control the low noise limit in gene expression. Therefore constitutive extrinsic noise is small and only plays a role in the absence of a systematic variation in translational efficiency. These results show the existence of two distinct expression noise patterns: (1 a global noise floor uniformly imposed on all genes by expression bursting; and (2 high noise distributed to only a select group of genes.

  7. Identification of genes expressed during myocardial development

    Institute of Scientific and Technical Information of China (English)

    陈小圆; 陈健宏; 张碧琪; 梁瑛; 梁平

    2003-01-01

    Objective To identify genes expressed in the fetal heart that are potentially important for myocardial development and cardiomyocyte proliferation.Methods mRNAs from fetal (29 weeks) and adult cardiomyocytes were use for suppression subtractive hybridization (SSH). Both forward (fetal as tester) and reverse (adult as driver) subtractions were performed. Clones confirmed by dot-blot analysis to be differentially expressed were sequenced and analyzed.Results Differential expressions were detected for 39 out of 96 (41%) clones on forward subtraction and 24 out of 80 (30%) clones on reverse. For fetal dominating genes, 28 clones matched to 10 known genes (COL1A2, COL3A1, endomucin, HBG1, HBG2, PCBP2, LOC51144, TGFBI, vinculin and PND), 9 clones to 5 cDNAs of unknown functions (accession AK021715, AF085867, AB040948, AB051460 and AB051512) and 2 clones had homology to hEST sequences. For the reverse subtraction, all clones showed homology to mitochondrial transcripts.Conclusions We successfully applied SSH to detect those genes differentially expressed in fetal cardiac myocytes, some of which have not been shown relative to myocardial development.

  8. Stochastic gene expression conditioned on large deviations

    Science.gov (United States)

    Horowitz, Jordan M.; Kulkarni, Rahul V.

    2017-06-01

    The intrinsic stochasticity of gene expression can give rise to large fluctuations and rare events that drive phenotypic variation in a population of genetically identical cells. Characterizing the fluctuations that give rise to such rare events motivates the analysis of large deviations in stochastic models of gene expression. Recent developments in non-equilibrium statistical mechanics have led to a framework for analyzing Markovian processes conditioned on rare events and for representing such processes by conditioning-free driven Markovian processes. We use this framework, in combination with approaches based on queueing theory, to analyze a general class of stochastic models of gene expression. Modeling gene expression as a Batch Markovian Arrival Process (BMAP), we derive exact analytical results quantifying large deviations of time-integrated random variables such as promoter activity fluctuations. We find that the conditioning-free driven process can also be represented by a BMAP that has the same form as the original process, but with renormalized parameters. The results obtained can be used to quantify the likelihood of large deviations, to characterize system fluctuations conditional on rare events and to identify combinations of model parameters that can give rise to dynamical phase transitions in system dynamics.

  9. Trigger finger, tendinosis, and intratendinous gene expression.

    Science.gov (United States)

    Lundin, A-C; Aspenberg, P; Eliasson, P

    2014-04-01

    The pathogenesis of trigger finger has generally been ascribed to primary changes in the first annular ligament. In contrast, we recently found histological changes in the tendons, similar to the findings in Achilles tendinosis or tendinopathy. We therefore hypothesized that trigger finger tendons would show differences in gene expression in comparison to normal tendons in a pattern similar to what is published for Achilles tendinosis. We performed quantitative real-time polymerase chain reaction on biopsies from finger flexor tendons, 13 trigger fingers and 13 apparently healthy control tendons, to assess the expression of 10 genes which have been described to be differently expressed in tendinosis (collagen type 1a1, collagen 3a1, MMP-2, MMP-3, ADAMTS-5, TIMP-3, aggrecan, biglycan, decorin, and versican). In trigger finger tendons, collagen types 1a1 and 3a1, aggrecan and biglycan were all up-regulated, and MMP-3and TIMP-3 were down-regulated. These changes were statistically significant and have been previously described for Achilles tendinosis. The remaining four genes were not significantly altered. The changes in gene expression support the hypothesis that trigger finger is a form of tendinosis. Because trigger finger is a common condition, often treated surgically, it could provide opportunities for clinical research on tendinosis. © 2012 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  10. Cluster Analysis of Gene Expression Data

    CERN Document Server

    Domany, E

    2002-01-01

    The expression levels of many thousands of genes can be measured simultaneously by DNA microarrays (chips). This novel experimental tool has revolutionized research in molecular biology and generated considerable excitement. A typical experiment uses a few tens of such chips, each dedicated to a single sample - such as tissue extracted from a particular tumor. The results of such an experiment contain several hundred thousand numbers, that come in the form of a table, of several thousand rows (one for each gene) and 50 - 100 columns (one for each sample). We developed a clustering methodology to mine such data. In this review I provide a very basic introduction to the subject, aimed at a physics audience with no prior knowledge of either gene expression or clustering methods. I explain what genes are, what is gene expression and how it is measured by DNA chips. Next I explain what is meant by "clustering" and how we analyze the massive amounts of data from such experiments, and present results obtained from a...

  11. Annotation of gene function in citrus using gene expression information and co-expression networks.

    Science.gov (United States)

    Wong, Darren C J; Sweetman, Crystal; Ford, Christopher M

    2014-07-15

    The genus Citrus encompasses major cultivated plants such as sweet orange, mandarin, lemon and grapefruit, among the world's most economically important fruit crops. With increasing volumes of transcriptomics data available for these species, Gene Co-expression Network (GCN) analysis is a viable option for predicting gene function at a genome-wide scale. GCN analysis is based on a "guilt-by-association" principle whereby genes encoding proteins involved in similar and/or related biological processes may exhibit similar expression patterns across diverse sets of experimental conditions. While bioinformatics resources such as GCN analysis are widely available for efficient gene function prediction in model plant species including Arabidopsis, soybean and rice, in citrus these tools are not yet developed. We have constructed a comprehensive GCN for citrus inferred from 297 publicly available Affymetrix Genechip Citrus Genome microarray datasets, providing gene co-expression relationships at a genome-wide scale (33,000 transcripts). The comprehensive citrus GCN consists of a global GCN (condition-independent) and four condition-dependent GCNs that survey the sweet orange species only, all citrus fruit tissues, all citrus leaf tissues, or stress-exposed plants. All of these GCNs are clustered using genome-wide, gene-centric (guide) and graph clustering algorithms for flexibility of gene function prediction. For each putative cluster, gene ontology (GO) enrichment and gene expression specificity analyses were performed to enhance gene function, expression and regulation pattern prediction. The guide-gene approach was used to infer novel roles of genes involved in disease susceptibility and vitamin C metabolism, and graph-clustering approaches were used to investigate isoprenoid/phenylpropanoid metabolism in citrus peel, and citric acid catabolism via the GABA shunt in citrus fruit. Integration of citrus gene co-expression networks, functional enrichment analysis and gene

  12. Gene expression profiling of human erythroid progenitors by micro-serial analysis of gene expression.

    Science.gov (United States)

    Fujishima, Naohito; Hirokawa, Makoto; Aiba, Namiko; Ichikawa, Yoshikazu; Fujishima, Masumi; Komatsuda, Atsushi; Suzuki, Yoshiko; Kawabata, Yoshinari; Miura, Ikuo; Sawada, Ken-ichi

    2004-10-01

    We compared the expression profiles of highly purified human CD34+ cells and erythroid progenitor cells by micro-serial analysis of gene expression (microSAGE). Human CD34+ cells were purified from granulocyte colony-stimulating factor-mobilized blood stem cells, and erythroid progenitors were obtained by cultivating these cells in the presence of stem cell factor, interleukin 3, and erythropoietin. Our 10,202 SAGE tags allowed us to identify 1354 different transcripts appearing more than once. Erythroid progenitor cells showed increased expression of LRBA, EEF1A1, HSPCA, PILRB, RANBP1, NACA, and SMURF. Overexpression of HSPCA was confirmed by real-time polymerase chain reaction analysis. MicroSAGE revealed an unexpected preferential expression of several genes in erythroid progenitor cells in addition to the known functional genes, including hemoglobins. Our results provide reference data for future studies of gene expression in various hematopoietic disorders, including myelodysplastic syndrome and leukemia.

  13. 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.

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

    Science.gov (United States)

    Seita, Jun; Sahoo, Debashis; Rossi, Derrick J; Bhattacharya, Deepta; Serwold, Thomas; Inlay, Matthew A; Ehrlich, Lauren I R; Fathman, John W; Dill, David L; Weissman, Irving L

    2012-01-01

    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.

  15. 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

  16. Regulation of noise in gene expression.

    Science.gov (United States)

    Sanchez, Alvaro; Choubey, Sandeep; Kondev, Jane

    2013-01-01

    The biochemical processes leading to the synthesis of new proteins are random, as they typically involve a small number of diffusing molecules. They lead to fluctuations in the number of proteins in a single cell as a function of time and to cell-to-cell variability of protein abundances. These in turn can lead to phenotypic heterogeneity in a population of genetically identical cells. Phenotypic heterogeneity may have important consequences for the development of multicellular organisms and the fitness of bacterial colonies, raising the question of how it is regulated. Here we review the experimental evidence that transcriptional regulation affects noise in gene expression, and discuss how the noise strength is encoded in the architecture of the promoter region. We discuss how models based on specific molecular mechanisms of gene regulation can make experimentally testable predictions for how changes to the promoter architecture are reflected in gene expression noise.

  17. Fluid Mechanics, Arterial Disease, and Gene Expression.

    Science.gov (United States)

    Tarbell, John M; Shi, Zhong-Dong; Dunn, Jessilyn; Jo, Hanjoong

    2014-01-01

    This review places modern research developments in vascular mechanobiology in the context of hemodynamic phenomena in the cardiovascular system and the discrete localization of vascular disease. The modern origins of this field are traced, beginning in the 1960s when associations between flow characteristics, particularly blood flow-induced wall shear stress, and the localization of atherosclerotic plaques were uncovered, and continuing to fluid shear stress effects on the vascular lining endothelial) cells (ECs), including their effects on EC morphology, biochemical production, and gene expression. The earliest single-gene studies and genome-wide analyses are considered. The final section moves from the ECs lining the vessel wall to the smooth muscle cells and fibroblasts within the wall that are fluid me chanically activated by interstitial flow that imposes shear stresses on their surfaces comparable with those of flowing blood on EC surfaces. Interstitial flow stimulates biochemical production and gene expression, much like blood flow on ECs.

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

    Directory of Open Access Journals (Sweden)

    Karlsson Per

    2008-09-01

    Full Text Available Abstract Background 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. Methods 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. Results 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. Conclusion 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. Trial

  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 clinical practice. The ANNs correctly classified all samples and identified the genes most relevant to the classification.

  20. 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.

  1. 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.

  2. Prediction of metastasis from low-malignant breast cancer by gene expression profiling

    DEFF Research Database (Denmark)

    Thomassen, Mads; Tan, Qihua; Eiriksdottir, Freyja;

    2007-01-01

    Promising results for prediction of outcome in breast cancer have been obtained by genome wide gene expression profiling. Some studies have suggested that an extensive overtreatment of breast cancer patients might be reduced by risk assessment with gene expression profiling. A patient group hardly...... examined in these studies is the low-risk patients for whom outcome is very difficult to predict with currently used methods. These patients do not receive adjuvant treatment according to the guidelines of the Danish Breast Cancer Cooperative Group (DBCG). In this study, 26 tumors from low-risk patients...... demonstrated high cross-platform consistency of the classifiers. Higher performance of HUMAC32 was demonstrated among the low-malignant cancers compared with the 70-gene classifier. This suggests that although the metastatic potential to some extend is determined by the same genes in groups of tumors...

  3. 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

  4. Topological features in cancer gene expression data.

    Science.gov (United States)

    Lockwood, S; Krishnamoorthy, B

    2015-01-01

    We present a new method for exploring cancer gene expression data based on tools from algebraic topology. Our method selects a small relevant subset from tens of thousands of genes while simultaneously identifying nontrivial higher order topological features, i.e., holes, in the data. We first circumvent the problem of high dimensionality by dualizing the data, i.e., by studying genes as points in the sample space. Then we select a small subset of the genes as landmarks to construct topological structures that capture persistent, i.e., topologically significant, features of the data set in its first homology group. Furthermore, we demonstrate that many members of these loops have been implicated for cancer biogenesis in scientific literature. We illustrate our method on five different data sets belonging to brain, breast, leukemia, and ovarian cancers.

  5. Coevolution of gene expression among interacting proteins

    Energy Technology Data Exchange (ETDEWEB)

    Fraser, Hunter B.; Hirsh, Aaron E.; Wall, Dennis P.; Eisen,Michael B.

    2004-03-01

    Physically interacting proteins or parts of proteins are expected to evolve in a coordinated manner that preserves proper interactions. Such coevolution at the amino acid-sequence level is well documented and has been used to predict interacting proteins, domains, and amino acids. Interacting proteins are also often precisely coexpressed with one another, presumably to maintain proper stoichiometry among interacting components. Here, we show that the expression levels of physically interacting proteins coevolve. We estimate average expression levels of genes from four closely related fungi of the genus Saccharomyces using the codon adaptation index and show that expression levels of interacting proteins exhibit coordinated changes in these different species. We find that this coevolution of expression is a more powerful predictor of physical interaction than is coevolution of amino acid sequence. These results demonstrate previously uncharacterized coevolution of gene expression, adding a different dimension to the study of the coevolution of interacting proteins and underscoring the importance of maintaining coexpression of interacting proteins over evolutionary time. Our results also suggest that expression coevolution can be used for computational prediction of protein protein interactions.

  6. Transcriptome-Level Signatures in Gene Expression and Gene Expression Variability during Bacterial Adaptive Evolution

    Science.gov (United States)

    Erickson, Keesha E.; Otoupal, Peter B.

    2017-01-01

    ABSTRACT Antibiotic-resistant bacteria are an increasingly serious public health concern, as strains emerge that demonstrate resistance to almost all available treatments. One factor that contributes to the crisis is the adaptive ability of bacteria, which exhibit remarkable phenotypic and gene expression heterogeneity in order to gain a survival advantage in damaging environments. This high degree of variability in gene expression across biological populations makes it a challenging task to identify key regulators of bacterial adaptation. Here, we research the regulation of adaptive resistance by investigating transcriptome profiles of Escherichia coli upon adaptation to disparate toxins, including antibiotics and biofuels. We locate potential target genes via conventional gene expression analysis as well as using a new analysis technique examining differential gene expression variability. By investigating trends across the diverse adaptation conditions, we identify a focused set of genes with conserved behavior, including those involved in cell motility, metabolism, membrane structure, and transport, and several genes of unknown function. To validate the biological relevance of the observed changes, we synthetically perturb gene expression using clustered regularly interspaced short palindromic repeat (CRISPR)-dCas9. Manipulation of select genes in combination with antibiotic treatment promotes adaptive resistance as demonstrated by an increased degree of antibiotic tolerance and heterogeneity in MICs. We study the mechanisms by which identified genes influence adaptation and find that select differentially variable genes have the potential to impact metabolic rates, mutation rates, and motility. Overall, this work provides evidence for a complex nongenetic response, encompassing shifts in gene expression and gene expression variability, which underlies adaptive resistance. IMPORTANCE Even initially sensitive bacteria can rapidly thwart antibiotic treatment

  7. Gene Expression Patterns Associated With Histopathology in Toxic Liver Fibrosis

    Science.gov (United States)

    2016-05-09

    coverage. Mass spectral data was proc- essed using Thermo Proteome Discoverer 1.4. These peak lists were searched by Sequest against a rat database...of average linkage. Random forest classifier . Random forest analysis was used to identify the top genes that contribute most to the classifier per...both the Bioplex and the microar- ray data were used to build the classifier . Histopathology was used to categorize the animals as true positives or

  8. Gene expression regulation in roots under drought.

    Science.gov (United States)

    Janiak, Agnieszka; Kwaśniewski, Mirosław; Szarejko, Iwona

    2016-02-01

    Stress signalling and regulatory networks controlling expression of target genes are the basis of plant response to drought. Roots are the first organs exposed to water deficiency in the soil and are the place of drought sensing. Signalling cascades transfer chemical signals toward the shoot and initiate molecular responses that lead to the biochemical and morphological changes that allow plants to be protected against water loss and to tolerate stress conditions. Here, we present an overview of signalling network and gene expression regulation pathways that are actively induced in roots under drought stress. In particular, the role of several transcription factor (TF) families, including DREB, AP2/ERF, NAC, bZIP, MYC, CAMTA, Alfin-like and Q-type ZFP, in the regulation of root response to drought are highlighted. The information provided includes available data on mutual interactions between these TFs together with their regulation by plant hormones and other signalling molecules. The most significant downstream target genes and molecular processes that are controlled by the regulatory factors are given. These data are also coupled with information about the influence of the described regulatory networks on root traits and root development which may translate to enhanced drought tolerance. This is the first literature survey demonstrating the gene expression regulatory machinery that is induced by drought stress, presented from the perspective of roots.

  9. Expression of MTLC gene in gastric carcinoma

    Institute of Scientific and Technical Information of China (English)

    Guang-Bin Qiu; Li-Guo Gong; Dong-Mei Hao; Zhi-Hong Zhen; Kai-Lai Sun

    2003-01-01

    AIM: To investigate the expression of c-myc target from laryngeal cancer cells (MTLC) gene in gastric carcinoma (GC)tissues and the effect of MTLC over-expression on gastric carcinoma cell line BGC823.METHODS: RT-PCR was performed to determine the expression of MTLC mRNA in GC and matched control tissues.BGC823 cells were transfected with an expression vector pcDNA3.1-MTLC by liposome and screened by G418. Growth of cells expressing MTLC was observed daily by manual counting. Apoptotic cells were determined by TdT-mediated dUTP nick-end labeling (TUNEL) assay.RESULTS: The expression of MTLC mRNAs was downregulated in 9(60%) of 15 cases of GC tissues. The growth rates of the BGC823 cells expressing MTLC were indistinguishable from that of control cells. A marked acceleration of apoptosis was observed in MTLC-expressing cells.CONCLUSION: MTLC was down-regulated in the majority of GC tissues and could promote apoptosis of GC cell lines,which suggests that MTLC may play an important role in the carcinogenesis of gastric carcinoma.

  10. Comprehensive profiling of EBV gene expression in nasopharyngeal carcinoma through paired-end transcriptome sequencing.

    Science.gov (United States)

    Hu, Lijuan; Lin, Zhirui; Wu, Yanheng; Dong, Juqin; Zhao, Bo; Cheng, Yanbing; Huang, Peiyu; Xu, Lihua; Xia, Tianliang; Xiong, Dan; Wang, Hongbo; Li, Manzhi; Guo, Ling; Kieff, Elliott; Zeng, Yixin; Zhong, Qian; Zeng, Musheng

    2016-03-01

    The latent expression pattern of Epstein-Barr Virus (EBV) genes in nasopharyngeal carcinoma (NPC) has been extensively investigated, and the expression of several lytic genes in NPC has been reported. However, comprehensive information through EBV transcriptome analysis in NPC is limited. We performed paired-end RNA-seq to systematically and comprehensively characterize the expression of EBV genes in NPC tissue and C666-1 NPC cell line, which consistently carries EBV. In addition to the transcripts restricted to type II latency infection, the type III latency EBNA3s genes and a substantial number of lytic genes, such as BZLF1, BRLF1, and BMRF1, were detected through RNA-seq and were further verified in C666-1 cells and NPC tissue through realtime PCR.We also performed clustering analysis to classify NPC patient groups in terms of EBV gene expression, which presented two subtypes of NPC samples. Results revealed interesting patterns of EBV gene expression in NPC patients. This clustering was correlated with many signaling pathways, such as those related to heterotrimeric G-protein signaling, inflammation mediated by chemokine and cytokine signaling, ribosomes, protein metabolism, influenza infection, and ECM-receptor interaction. Our combined findings suggested that the expression of EBV genes in NPC is restricted not only to type II latency genes but also to type III latency and lytic genes. This study provided further insights into the potential role of EBV in the development of NPC.

  11. The rice B-box zinc finger gene family: genomic identification, characterization, expression profiling and diurnal analysis.

    Directory of Open Access Journals (Sweden)

    Jianyan Huang

    Full Text Available BACKGROUND: The B-box (BBX -containing proteins are a class of zinc finger proteins that contain one or two B-box domains and play important roles in plant growth and development. The Arabidopsis BBX gene family has recently been re-identified and renamed. However, there has not been a genome-wide survey of the rice BBX (OsBBX gene family until now. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we identified 30 rice BBX genes through a comprehensive bioinformatics analysis. Each gene was assigned a uniform nomenclature. We described the chromosome localizations, gene structures, protein domains, phylogenetic relationship, whole life-cycle expression profile and diurnal expression patterns of the OsBBX family members. Based on the phylogeny and domain constitution, the OsBBX gene family was classified into five subfamilies. The gene duplication analysis revealed that only chromosomal segmental duplication contributed to the expansion of the OsBBX gene family. The expression profile of the OsBBX genes was analyzed by Affymetrix GeneChip microarrays throughout the entire life-cycle of rice cultivar Zhenshan 97 (ZS97. In addition, microarray analysis was performed to obtain the expression patterns of these genes under light/dark conditions and after three phytohormone treatments. This analysis revealed that the expression patterns of the OsBBX genes could be classified into eight groups. Eight genes were regulated under the light/dark treatments, and eleven genes showed differential expression under at least one phytohormone treatment. Moreover, we verified the diurnal expression of the OsBBX genes using the data obtained from the Diurnal Project and qPCR analysis, and the results indicated that many of these genes had a diurnal expression pattern. CONCLUSIONS/SIGNIFICANCE: The combination of the genome-wide identification and the expression and diurnal analysis of the OsBBX gene family should facilitate additional functional studies of the Os

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

    Directory of Open Access Journals (Sweden)

    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.

  13. Toward stable gene expression in CHO cells

    Science.gov (United States)

    Mariati; Koh, Esther YC; Yeo, Jessna HM; Ho, Steven CL; Yang, Yuansheng

    2014-01-01

    Maintaining high gene expression level during long-term culture is critical when producing therapeutic recombinant proteins using mammalian cells. Transcriptional silencing of promoters, most likely due to epigenetic events such as DNA methylation and histone modifications, is one of the major mechanisms causing production instability. Previous studies demonstrated that the core CpG island element (IE) from the hamster adenine phosphoribosyltransferase gene is effective to prevent DNA methylation. We generated one set of modified human cytomegalovirus (hCMV) promoters by insertion of one or two copies of IE in either forward or reverse orientations into different locations of the hCMV promoter. The modified hCMV with one copy of IE inserted between the hCMV enhancer and core promoter in reverse orientation (MR1) was most effective at enhancing expression stability in CHO cells without comprising expression level when compared with the wild type hCMV. We also found that insertion of IE into a chimeric murine CMV (mCMV) enhancer and human elongation factor-1α core (hEF) promoter in reverse orientation did not enhance expression stability, indicating that the effect of IE on expression stability is possibly promoter specific. PMID:25482237

  14. Gene expression in Pseudomonas aeruginosa swarming motility

    Directory of Open Access Journals (Sweden)

    Déziel Eric

    2010-10-01

    Full Text Available Abstract Background The bacterium Pseudomonas aeruginosa is capable of three types of motilities: swimming, twitching and swarming. The latter is characterized by a fast and coordinated group movement over a semi-solid surface resulting from intercellular interactions and morphological differentiation. A striking feature of swarming motility is the complex fractal-like patterns displayed by migrating bacteria while they move away from their inoculation point. This type of group behaviour is still poorly understood and its characterization provides important information on bacterial structured communities such as biofilms. Using GeneChip® Affymetrix microarrays, we obtained the transcriptomic profiles of both bacterial populations located at the tip of migrating tendrils and swarm center of swarming colonies and compared these profiles to that of a bacterial control population grown on the same media but solidified to not allow swarming motility. Results Microarray raw data were corrected for background noise with the RMA algorithm and quantile normalized. Differentially expressed genes between the three conditions were selected using a threshold of 1.5 log2-fold, which gave a total of 378 selected genes (6.3% of the predicted open reading frames of strain PA14. Major shifts in gene expression patterns are observed in each growth conditions, highlighting the presence of distinct bacterial subpopulations within a swarming colony (tendril tips vs. swarm center. Unexpectedly, microarrays expression data reveal that a minority of genes are up-regulated in tendril tip populations. Among them, we found energy metabolism, ribosomal protein and transport of small molecules related genes. On the other hand, many well-known virulence factors genes were globally repressed in tendril tip cells. Swarm center cells are distinct and appear to be under oxidative and copper stress responses. Conclusions Results reported in this study show that, as opposed to

  15. Engineering genes for predictable protein expression.

    Science.gov (United States)

    Gustafsson, Claes; Minshull, Jeremy; Govindarajan, Sridhar; Ness, Jon; Villalobos, Alan; Welch, Mark

    2012-05-01

    The DNA sequence used to encode a polypeptide can have dramatic effects on its expression. Lack of readily available tools has until recently inhibited meaningful experimental investigation of this phenomenon. Advances in synthetic biology and the application of modern engineering approaches now provide the tools for systematic analysis of the sequence variables affecting heterologous expression of recombinant proteins. We here discuss how these new tools are being applied and how they circumvent the constraints of previous approaches, highlighting some of the surprising and promising results emerging from the developing field of gene engineering.

  16. Gene expression changes associated with resistance to intravenous corticosteroid therapy in children with severe ulcerative colitis.

    Directory of Open Access Journals (Sweden)

    Boyko Kabakchiev

    Full Text Available BACKGROUND AND AIMS: Microarray analysis of RNA expression allows gross examination of pathways operative in inflammation. We aimed to determine whether genes expressed in whole blood early following initiation of intravenous corticosteroid treatment can be associated with response. METHODS: From a prospectively accrued cohort of 128 pediatric patients hospitalized for intravenous corticosteroid treatment of severe UC, we selected for analysis 20 corticosteroid responsive (hospital discharge or PUCAI ≤45 by day 5 and 20 corticosteroid resistant patients (need for second line medical therapy or colectomy, or PUCAI >45 by day 5. Total RNA was extracted from blood samples collected on day 3 of intravenous corticosteroid therapy. The eluted transcriptomes were quantified on Affymetrix Human Gene 1.0 ST arrays. The data was analysed by the local-pooled error method for discovery of differential gene expression and false discovery rate correction was applied to adjust for multiple comparisons. RESULTS: A total of 41 genes differentially expressed between responders and non-responders were detected with statistical significance. Two of these genes, CEACAM1 and MMP8, possibly inhibited by methylprednisolone through IL8, were both found to be over-expressed in non-responsive patients. ABCC4 (MRP4 as a member of the multi-drug resistance superfamily was a novel candidate gene for corticosteroid resistance. The expression pattern of a cluster of 10 genes selected from the 41 significant hits were able to classify the patients with 80% sensitivity and 80% specificity. CONCLUSIONS: Elevated expression of several genes involved in inflammatory pathways was associated with resistance to intravenous corticosteroid therapy early in the course of treatment. Gene expression profiles may be useful to classify resistance to intravenous corticosteroids in children with severe UC and assist with clinical management decisions.

  17. 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.

  18. Annotation of gene function in citrus using gene expression information and co-expression networks

    OpenAIRE

    Wong, Darren CJ; Sweetman, Crystal; Ford, Christopher M.

    2014-01-01

    Background The genus Citrus encompasses major cultivated plants such as sweet orange, mandarin, lemon and grapefruit, among the world’s most economically important fruit crops. With increasing volumes of transcriptomics data available for these species, Gene Co-expression Network (GCN) analysis is a viable option for predicting gene function at a genome-wide scale. GCN analysis is based on a “guilt-by-association” principle whereby genes encoding proteins involved in similar and/or related bi...

  19. Annotation of gene function in citrus using gene expression information and co-expression networks

    OpenAIRE

    Wong, Darren CJ; Sweetman, Crystal; Ford, Christopher M.

    2014-01-01

    Background The genus Citrus encompasses major cultivated plants such as sweet orange, mandarin, lemon and grapefruit, among the world’s most economically important fruit crops. With increasing volumes of transcriptomics data available for these species, Gene Co-expression Network (GCN) analysis is a viable option for predicting gene function at a genome-wide scale. GCN analysis is based on a “guilt-by-association” principle whereby genes encoding proteins involved in similar and/or related bi...

  20. Global gene expression in Escherichia coli biofilms

    DEFF Research Database (Denmark)

    Schembri, Mark; Kjærgaard, K.; Klemm, Per

    2003-01-01

    in expression have no current defined function. These genes, as well as those induced by stresses relevant to biofilm growth such as oxygen and nutrient limitation, may be important factors that trigger enhanced resistance mechanisms of sessile communities to antibiotics and hydrodynamic shear forces.......It is now apparent that microorganisms undergo significant changes during the transition from planktonic to biofilm growth. These changes result in phenotypic adaptations that allow the formation of highly organized and structured sessile communities, which possess enhanced resistance...... to antimicrobial treatments and host immune defence responses. Escherichia coli has been used as a model organism to study the mechanisms of growth within adhered communities. In this study, we use DNA microarray technology to examine the global gene expression profile of E. coli during sessile growth compared...

  1. Aberrant Gene Expression in Acute Myeloid Leukaemia

    DEFF Research Database (Denmark)

    Bagger, Frederik Otzen

    model to investigate the role of telomerase in AML, we were able to translate the observed effect into human AML patients and identify specific genes involved, which also predict survival patterns in AML patients. During these studies we have applied methods for investigating differentially expressed......Summary Acute Myeloid Leukaemia (AML) is an aggressive cancer of the bone marrow, affecting formation of blood cells during haematopoiesis. This thesis presents investigation of AML using mRNA gene expression profiles (GEP) of samples extracted from the bone marrow of healthy and diseased subjects....... Here GEPs from purified healthy haematopoietic populations, with different levels of differentiation, form the basis for comparison with diseased samples. We present a mathematical transformation of mRNA microarray data to make it possible to compare AML samples, carrying expanded aberrant...

  2. Combinatorial engineering for heterologous gene expression.

    Science.gov (United States)

    Zwick, Friederike; Lale, Rahmi; Valla, Svein

    2013-01-01

    Tools for strain engineering with predictable outcome are of crucial importance for the nascent field of synthetic biology. The success of combining different DNA biological parts is often restricted by poorly understood factors deriving from the complexity of the systems. We have previously identified variants for different regulatory elements of the expression cassette XylS/Pm. When such elements are combined they act in a manner consistent with their individual behavior, as long as they affect different functions, such as transcription and translation. Interestingly, sequence context does not seem to influence the final outcome significantly. Expression of reporter gene bla could be increased up to 75 times at the protein level by combining three variants in one cassette. For other tested reporter genes similar results were obtained, except that the stimulatory effect was quantitatively less. Combination of individually characterized DNA parts thus stands as suitable method to achieve a desired phenotype.

  3. Structure, expression and functions of MTA genes.

    Science.gov (United States)

    Kumar, Rakesh; Wang, Rui-An

    2016-05-15

    Metastatic associated proteins (MTA) are integrators of upstream regulatory signals with the ability to act as master coregulators for modifying gene transcriptional activity. The MTA family includes three genes and multiple alternatively spliced variants. The MTA proteins neither have their own enzymatic activity nor have been shown to directly interact with DNA. However, MTA proteins interact with a variety of chromatin remodeling factors and complexes with enzymatic activities for modulating the plasticity of nucleosomes, leading to the repression or derepression of target genes or other extra-nuclear and nucleosome remodeling and histone deacetylase (NuRD)-complex independent activities. The functions of MTA family members are driven by the steady state levels and subcellular localization of MTA proteins, the dynamic nature of modifying signals and enzymes, the structural features and post-translational modification of protein domains, interactions with binding proteins, and the nature of the engaged and resulting features of nucleosomes in the proximity of target genes. In general, MTA1 and MTA2 are the most upregulated genes in human cancer and correlate well with aggressive phenotypes, therapeutic resistance, poor prognosis and ultimately, unfavorable survival of cancer patients. Here we will discuss the structure, expression and functions of the MTA family of genes in the context of cancer cells.

  4. Combined microRNA and ER expression: a new classifier for familial and sporadic breast cancer patients.

    Science.gov (United States)

    Danza, Katia; De Summa, Simona; Pilato, Brunella; Carella, Massimo; Palumbo, Orazio; Popescu, Ondina; Paradiso, Angelo; Pinto, Rosamaria; Tommasi, Stefania

    2014-11-19

    The role of miRNAs in familial breast cancer (fBC) is poorly investigated as also in the BRCA-like tumors. To identify a specific miRNA expression pattern which could allow a better fBC classification not only based on clinico-pathological and immunophenotypical parameters we analyzed miRNA profile in familial and sporadic samples. Moreover since BRCA1 tumors and sporadic triple negative (TN) breast tumors share similarities regarding clinical outcomes and some histological characteristics, we focused on TN and not TN cases. The sample set included fresh frozen tissue samples, including 39 female fBCs (19 BRCA-related and 20 BRCAX) and 12 male fBC (BRCAX). Moreover, we considered TN and non TN (NTN), 21 BRCA-related and 27 sporadic BCs. MiRNA profiling was performed through GeneChip miRNA v.1.0 Array (Affymetrix). ANOVA, hierarchical and consensus clustering analyses allowed identification of pattern of expression of miRNAs and pathway enrichment analysis, considering validated target genes, was carried out to achieve a deeper biological understanding. ANOVA test led to the identification of 53 deregulated miRNAs; hierarchical and consensus clustering of female fBCs (fFBCs) and male fBCs (fMBCs) highlighted the presence of 3 sample clusters named FBC1, FBC2 and FBC3. We found a correlation between ER-status and the three sample clusters. The three clusters are distinct by a different expression of two clusters of miRNAs (CLU1 and CLU2), which resulted to be different in targeted pathways. In particular, CLU1 targets cellular pathways and CLU2 is involved in epigenetic activities. Considering TN and NTN BRCA-related and sporadic tumors, a hierarchical clustering identified two clusters of miRNAs, which were not so different from CLU1 and CLU2, both in miRNA content and targeted pathways. Our results highlighted the importance of miRNA regulation to better clarify similarities and differences between familial and sporadic BC groups.

  5. Proteomic and gene expression patterns of keratoconus

    Directory of Open Access Journals (Sweden)

    Arkasubhra Ghosh

    2013-01-01

    Full Text Available Keratoconus is a progressive corneal thinning disease associated with significant tissue remodeling activities and activation of a variety of signaling networks. However, it is not understood how differential gene and protein expression direct function in keratoconus corneas to drive the underlying pathology, ectasia. Research in the field has focused on discovering differentially expressed genes and proteins and quantifying their levels and activities in keratoconus patient samples. In this study, both microarray analysis of total ribonucleic acid (RNA and whole proteome analyses are carried out using corneal epithelium and tears from keratoconus patients and compared to healthy controls. A number of structural proteins, signaling molecules, cytokines, proteases, and enzymes have been found to be deregulated in keratoconus corneas. Together, the data provide clues to the complex process of corneal degradation which suggest novel ways to clinically diagnose and manage the disease. This review will focus on discussing these recent advances in the knowledge of keratoconus biology from a gene expression and function point-of-view.

  6. DNA copy-number alterations underlie gene expression differences between microsatellite stable and unstable colorectal cancers

    DEFF Research Database (Denmark)

    Jorissen, Robert N; Lipton, Lara; Gibbs, Peter

    2008-01-01

    Purpose: About 15% of colorectal cancers harbor microsatellite instability (MSI). MSI-associated gene expression changes have been identified in colorectal cancers, but little overlap exists between signatures hindering an assessment of overall consistency. Little is known about the causes...... and downstream effects of differential gene expression. Experimental Design: DNA microarray data on 89 MSI and 140 microsatellite-stable (MSS) colorectal cancers from this study and 58 MSI and 77 MSS cases from three published reports were randomly divided into test and training sets. MSI-associated gene...... expression changes were assessed for cross-study consistency using training samples and validated as MSI classifier using test samples. Differences in biological pathways were identified by functional category analysis. Causation of differential gene expression was investigated by comparison to DNA copy...

  7. Analysis of gene expression in rabbit muscle

    Directory of Open Access Journals (Sweden)

    Alena Gálová

    2014-02-01

    Full Text Available Increasing consumer knowledge of the link between diet and health has raised the demand for high quality food. Meat and meat products may be considered as irreplaceable in human nutrition. Breeding livestock to higher content of lean meat and the use of modern hybrids entails problems with the quality of meat. Analysing of livestock genomes could get us a great deal of important information, which may significantly affect the improvement process. Domestic animals are invaluable resources for study of the molecular architecture of complex traits. Although the mapping of quantitative trait loci (QTL responsible for economically important traits in domestic animals has achieved remarkable results in recent decades, not all of the genetic variation in the complex traits has been captured because of the low density of markers used in QTL mapping studies. The genome wide association study (GWAS, which utilizes high-density single-nucleotide polymorphism (SNP, provides a new way to tackle this issue. New technologies now allow producing microarrays containing thousands of hybridization probes on a single membrane or other solid support. We used microarray analysis to study gene expression in rabbit muscle during different developmental age stages. The outputs from GeneSpring GX sotware are presented in this work. After the evaluation of gene expression in rabbits, will be selected genes of interest in relation to meat quality parameters and will be further analyzed by the available methods of molecular biology and genetics.

  8. Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd

    Science.gov (United States)

    Wang, Zichen; Monteiro, Caroline D.; Jagodnik, Kathleen M.; Fernandez, Nicolas F.; Gundersen, Gregory W.; Rouillard, Andrew D.; Jenkins, Sherry L.; Feldmann, Axel S.; Hu, Kevin S.; McDermott, Michael G.; Duan, Qiaonan; Clark, Neil R.; Jones, Matthew R.; Kou, Yan; Goff, Troy; Woodland, Holly; Amaral, Fabio M. R.; Szeto, Gregory L.; Fuchs, Oliver; Schüssler-Fiorenza Rose, Sophia M.; Sharma, Shvetank; Schwartz, Uwe; Bausela, Xabier Bengoetxea; Szymkiewicz, Maciej; Maroulis, Vasileios; Salykin, Anton; Barra, Carolina M.; Kruth, Candice D.; Bongio, Nicholas J.; Mathur, Vaibhav; Todoric, Radmila D.; Rubin, Udi E.; Malatras, Apostolos; Fulp, Carl T.; Galindo, John A.; Motiejunaite, Ruta; Jüschke, Christoph; Dishuck, Philip C.; Lahl, Katharina; Jafari, Mohieddin; Aibar, Sara; Zaravinos, Apostolos; Steenhuizen, Linda H.; Allison, Lindsey R.; Gamallo, Pablo; de Andres Segura, Fernando; Dae Devlin, Tyler; Pérez-García, Vicente; Ma'Ayan, Avi

    2016-09-01

    Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO). Through a massive open online course on Coursera, over 70 participants from over 25 countries identify and annotate 2,460 single-gene perturbation signatures, 839 disease versus normal signatures, and 906 drug perturbation signatures. All these signatures are unique and are manually validated for quality. Global analysis of these signatures confirms known associations and identifies novel associations between genes, diseases and drugs. The manually curated signatures are used as a training set to develop classifiers for extracting similar signatures from the entire GEO repository. We develop a web portal to serve these signatures for query, download and visualization.

  9. Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd

    Science.gov (United States)

    Wang, Zichen; Monteiro, Caroline D.; Jagodnik, Kathleen M.; Fernandez, Nicolas F.; Gundersen, Gregory W.; Rouillard, Andrew D.; Jenkins, Sherry L.; Feldmann, Axel S.; Hu, Kevin S.; McDermott, Michael G.; Duan, Qiaonan; Clark, Neil R.; Jones, Matthew R.; Kou, Yan; Goff, Troy; Woodland, Holly; Amaral, Fabio M R.; Szeto, Gregory L.; Fuchs, Oliver; Schüssler-Fiorenza Rose, Sophia M.; Sharma, Shvetank; Schwartz, Uwe; Bausela, Xabier Bengoetxea; Szymkiewicz, Maciej; Maroulis, Vasileios; Salykin, Anton; Barra, Carolina M.; Kruth, Candice D.; Bongio, Nicholas J.; Mathur, Vaibhav; Todoric, Radmila D; Rubin, Udi E.; Malatras, Apostolos; Fulp, Carl T.; Galindo, John A.; Motiejunaite, Ruta; Jüschke, Christoph; Dishuck, Philip C.; Lahl, Katharina; Jafari, Mohieddin; Aibar, Sara; Zaravinos, Apostolos; Steenhuizen, Linda H.; Allison, Lindsey R.; Gamallo, Pablo; de Andres Segura, Fernando; Dae Devlin, Tyler; Pérez-García, Vicente; Ma'ayan, Avi

    2016-01-01

    Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO). Through a massive open online course on Coursera, over 70 participants from over 25 countries identify and annotate 2,460 single-gene perturbation signatures, 839 disease versus normal signatures, and 906 drug perturbation signatures. All these signatures are unique and are manually validated for quality. Global analysis of these signatures confirms known associations and identifies novel associations between genes, diseases and drugs. The manually curated signatures are used as a training set to develop classifiers for extracting similar signatures from the entire GEO repository. We develop a web portal to serve these signatures for query, download and visualization. PMID:27667448

  10. 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.

  11. Screening of differentially expressed genes in pathological scar tissues using expression microarray.

    Science.gov (United States)

    Huang, L P; Mao, Z; Zhang, L; Liu, X X; Huang, C; Jia, Z S

    2015-09-09

    Pathological scar tissues and normal skin tissues were differentiated by screening for differentially expressed genes in pathologic scar tissues via gene expression microarray. The differentially expressed gene data was analyzed by gene ontology and pathway analyses. There were 5001 up- or down-regulated genes in 2-fold differentially expressed genes, 956 up- or down-regulated genes in 5-fold differentially expressed genes, and 114 up- or down-regulated genes in 20-fold differentially expressed genes. Therefore, significant differences were observed in the gene expression in pathological scar tissues and normal foreskin tissues. The development of pathological scar tissues has been correlated to changes in multiple genes and pathways, which are believed to form a dynamic network connection.

  12. Identification of common prognostic gene expression signatures with biological meanings from microarray gene expression datasets.

    Directory of Open Access Journals (Sweden)

    Jun Yao

    Full Text Available Numerous prognostic gene expression signatures for breast cancer were generated previously with few overlap and limited insight into the biology of the disease. Here we introduce a novel algorithm named SCoR (Survival analysis using Cox proportional hazard regression and Random resampling to apply random resampling and clustering methods in identifying gene features correlated with time to event data. This is shown to reduce overfitting noises involved in microarray data analysis and discover functional gene sets linked to patient survival. SCoR independently identified a common poor prognostic signature composed of cell proliferation genes from six out of eight breast cancer datasets. Furthermore, a sequential SCoR analysis on highly proliferative breast cancers repeatedly identified T/B cell markers as favorable prognosis factors. In glioblastoma, SCoR identified a common good prognostic signature of chromosome 10 genes from two gene expression datasets (TCGA and REMBRANDT, recapitulating the fact that loss of one copy of chromosome 10 (which harbors the tumor suppressor PTEN is linked to poor survival in glioblastoma patients. SCoR also identified prognostic genes on sex chromosomes in lung adenocarcinomas, suggesting patient gender might be used to predict outcome in this disease. These results demonstrate the power of SCoR to identify common and biologically meaningful prognostic gene expression signatures.

  13. Identification of common prognostic gene expression signatures with biological meanings from microarray gene expression datasets.

    Science.gov (United States)

    Yao, Jun; Zhao, Qi; Yuan, Ying; Zhang, Li; Liu, Xiaoming; Yung, W K Alfred; Weinstein, John N

    2012-01-01

    Numerous prognostic gene expression signatures for breast cancer were generated previously with few overlap and limited insight into the biology of the disease. Here we introduce a novel algorithm named SCoR (Survival analysis using Cox proportional hazard regression and Random resampling) to apply random resampling and clustering methods in identifying gene features correlated with time to event data. This is shown to reduce overfitting noises involved in microarray data analysis and discover functional gene sets linked to patient survival. SCoR independently identified a common poor prognostic signature composed of cell proliferation genes from six out of eight breast cancer datasets. Furthermore, a sequential SCoR analysis on highly proliferative breast cancers repeatedly identified T/B cell markers as favorable prognosis factors. In glioblastoma, SCoR identified a common good prognostic signature of chromosome 10 genes from two gene expression datasets (TCGA and REMBRANDT), recapitulating the fact that loss of one copy of chromosome 10 (which harbors the tumor suppressor PTEN) is linked to poor survival in glioblastoma patients. SCoR also identified prognostic genes on sex chromosomes in lung adenocarcinomas, suggesting patient gender might be used to predict outcome in this disease. These results demonstrate the power of SCoR to identify common and biologically meaningful prognostic gene expression signatures.

  14. Gravity-Induced Gene Expression in Plants.

    Science.gov (United States)

    Sederoff, Heike; Heber, Steffen; Howard, Brian; Myburg-Nichols, Henrietta; Hammond, Rebecca; Salinas-Mondragon, Raul; Brown, Christopher S.

    Plants sense changes in their orientation towards the vector of gravity and respond with directional growth. Several metabolites in the signal transduction cascade have been identified. However, very little is known about the interaction between these sensing and signal transduction events and even less is known about their role in the differential growth response. Gravity induced changes in transcript abundance have been identified in Arabidopsis whole seedlings and root apices (Moseyko et al. 2002; Kimbrough et al. 2004). Gravity induced transcript abundance changes can be observed within less than 1 min after stimulation (Salinas-Mondragon et al. 2005). Gene expression however requires not only transcription but also translation of the mRNA. Translation can only occur when mRNA is associated with ribosomes, even though not all mRNA associated with ribosomes is actively translated. To approximate translational capacity we quantified whole genome transcript abundances in corn stem pulvini during the first hour after gravity stimulation in total and poly-ribosomal fractions. As in Arabidopsis root apices, transcript abundances of several clusters of genes responded to gravity stimulation. The vast majority of these transcripts were also found to associate with polyribosomes in the same temporal and quantitative pattern. These genes are transcriptionally regulated by gravity stimulation, but do not exhibit translational regulation. However, a small group of genes showed increased transcriptional regulation after gravity stimulation, but no association with polysomes. These transcripts likely are translationally repressed. The mechanism of translational repression for these transcripts is unknown. Based on the hypothesis that the genes essential for gravitropic responses should be expressed in most or all species, we compared the temporal gravity induced expression pattern of all orthologs identified between maize and Arabidopsis. A small group of genes showed high

  15. Gene expression regulators--MicroRNAs

    Institute of Scientific and Technical Information of China (English)

    CHEN Fang; YIN Q. James

    2005-01-01

    A large class of non-coding RNAs found in small molecule RNAs are closely associated with the regulation of gene expression, which are called microRNA (miRNA). MiRNAs are coded in intergenic or intronic regions and can be formed into foldback hairpin RNAs. These transcripts are cleaved by Dicer, generating mature miRNAs that can silence their target genes in different modes of action. Now, research on small molecule RNAs has gotten breakthrough advance in biology. To discover miRNA genes and their target genes has become hot topics in RNA research. This review attempts to look back the history of miRNA discovery, to introduce the methods of screening miRNAs, to localize miRNA loci in genome, to seek miRNA target genes and the biological function, and to discuss the working mechanisms of miRNAs. Finally, we will discuss the potential important roles of miRNAs in modulating the genesis, development, growth, and differentiation of organisms. Thus, it can be predicted that a complete understanding of miRNA functions will bring us some new concepts, approaches and strategies for the study of living beings.

  16. Cholinergic regulation of VIP gene expression in human neuroblastoma cells

    DEFF Research Database (Denmark)

    Kristensen, Bo; Georg, Birgitte; Fahrenkrug, Jan

    1997-01-01

    Vasoactive intestinal polypeptide, muscarinic receptor, neuroblastoma cell, mRNA, gene expression, peptide processing......Vasoactive intestinal polypeptide, muscarinic receptor, neuroblastoma cell, mRNA, gene expression, peptide processing...

  17. Gene Expression Profiling of Xeroderma Pigmentosum

    Directory of Open Access Journals (Sweden)

    Bowden Nikola A

    2006-05-01

    Full Text Available Abstract Xeroderma pigmentosum (XP is a rare recessive disorder that is characterized by extreme sensitivity to UV light. UV light exposure results in the formation of DNA damage such as cyclobutane dimers and (6-4 photoproducts. Nucleotide excision repair (NER orchestrates the removal of cyclobutane dimers and (6-4 photoproducts as well as some forms of bulky chemical DNA adducts. The disease XP is comprised of 7 complementation groups (XP-A to XP-G, which represent functional deficiencies in seven different genes, all of which are believed to be involved in NER. The main clinical feature of XP is various forms of skin cancers; however, neurological degeneration is present in XPA, XPB, XPD and XPG complementation groups. The relationship between NER and other types of DNA repair processes is now becoming evident but the exact relationships between the different complementation groups remains to be precisely determined. Using gene expression analysis we have identified similarities and differences after UV light exposure between the complementation groups XP-A, XP-C, XP-D, XP-E, XP-F, XP-G and an unaffected control. The results reveal that there is a graded change in gene expression patterns between the mildest, most similar to the control response (XP-E and the severest form (XP-A of the disease, with the exception of XP-D. Distinct differences between the complementation groups with neurological symptoms (XP-A, XP-D and XP-G and without (XP-C, XP-E and XP-F were also identified. Therefore, this analysis has revealed distinct gene expression profiles for the XP complementation groups and the first step towards understanding the neurological symptoms of XP.

  18. X chromosome regulation of autosomal gene expression in bovine blastocysts

    Science.gov (United States)

    Itoh, Yuichiro; Arnold, Arthur P.

    2014-01-01

    Although X chromosome inactivation in female mammals evolved to balance the expression of X chromosome and autosomal genes in the two sexes, female embryos pass through developmental stages in which both X chromosomes are active in somatic cells. Bovine blastocysts show higher expression of many X genes in XX than XY embryos, suggesting that X inactivation is not complete. Here we reanalyzed bovine blastocyst microarray expression data from a network perspective with a focus on interactions between X chromosome and autosomal genes. Whereas male to female ratios of expression of autosomal genes were distributed around a mean of 1, X chromosome genes were clearly shifted towards higher expression in females. We generated gene coexpression networks and identified a major module of genes with correlated gene expression that includes female-biased X genes and sexually dimorphic autosomal genes for which the sexual dimorphism is likely driven by the X genes. In this module, expression of X chromosome genes correlates with autosome genes, more than the expression of autosomal genes with each other. Our study identifies correlated patterns of autosomal and X-linked genes that are likely influenced by the sexual imbalance of X gene expression when X inactivation is inefficient. PMID:24817096

  19. Gene Identification and Expression Analysis of 86,136 Expressed Sequence Tags (EST) from the Rice Genome

    Institute of Scientific and Technical Information of China (English)

    Yan Zhou; Lin Ye; Li Lin; Jun Li; Xuegang Wang; Hao Xu; Yibin Pan; Wei Lin; Wei Tian; Jing Liu; Liping Wei; Jiabin Tang; Siqi Liu; Huanming Yang; Jun Yu; Jian Wang; Michael G. Walker; Xiuqing Zhang; Jun Wang; Songnian Hu; Huayong Xu; Yajun Deng; Jianhai Dong

    2003-01-01

    Expressed Sequence Tag (EST) analysis has pioneered genome-wide gene discovery and expression profiling. In order to establish a gene expression index in the rice cultivar indica, we sequenced and analyzed 86,136 ESTs from nine rice cDNA libraries from the super hybrid cultivar LYP9 and its parental cultivars. We assembled these ESTs into 13,232 contigs and leave 8,976 singletons. Overall, 7,497 sequences were found similar to the existing sequences in GenBank and 14,711 are novel. These sequences are classified by molecular function, biological process and pathways according to the Gene Ontology. We compared our sequenced ESTs with the publicly available 95,000 ESTs from japonica, and found little sequence variation, despite the large difference between genome sequences. We then assembled the combined 173,000 rice ESTs for further analysis. Using the pooled ESTs, we compared gene expression in metabolism pathway between rice and Avabidopsis according to KEGG. We further profiled gene expression patterns in different tis sues, developmental stages, and in a conditional sterile mutant, after checking the libraries are comparable by means of sequence coverage. We also identified some possible library specific genes and a number of enzymes and transcription factors that contribute to rice development.

  20. Gene Expression Profile of Human Skeletal Muscle and Adipose Tissue of Chinese Han Patients with Type 2 Diabetes Mellitus

    Institute of Scientific and Technical Information of China (English)

    YAN-LI YANG; RUO-LAN XIANG; CHANG YANG; XIAO-JUN LIU; WEN-JUN SHEN; JIN ZUO; YONG-SHENG CHANG; FU-DE FANG

    2009-01-01

    Objective To study the differential patterns of gene expression in skeletal muscle and adipose tissue between type 2 diabetes mellitus (T2DM) patients and healthy subjects using DNA microarray analysis. Methods T2DM patiens were divided into female group, young male group and old male group. DNA microarray analysis and quantitative real-time PCR were carried out to analyze the relation between gene expressions and T2DM. Results The mRNA expression of 298, 578, and 350 genes was changed in the skeletal muscle of diabetes mellitus patients compared with control subjects. The 1320, 1143, and 2847 genes were modified in adipose tissue of the three groups. Among the genes surveyed, the change of 25 and 39 gene transcripts in skeletal muscle and adipose tissue was ≥2 folds. These differentially expressed genes were classified into 15 categories according to their functions. Conclusion New genes are found and T2DM can be prevented or cured.

  1. Serial Analysis of Gene Expression in Plasmodium berghei salivary gland sporozoites

    Directory of Open Access Journals (Sweden)

    Ménard Robert

    2007-12-01

    Full Text Available Abstract Background The invasion of Anopheles salivary glands by Plasmodium sporozoites is an essential step for transmission of the parasite to the vertebrate host. Salivary gland sporozoites undergo a developmental programme to express genes required for their journey from the site of the mosquito bite to the liver and subsequent invasion of, and development within, hepatocytes. A Serial Analysis of Gene Expression was performed on Anopheles gambiae salivary glands infected or not with Plasmodium berghei and we report here the analysis of the Plasmodium sporozoite transcriptome. Results Annotation of 530 tag sequences homologous to Plasmodium berghei genomic sequences identified 123 genes expressed in salivary gland sporozoites and these genes were classified according to their transcript abundance. A subset of these genes was further studied by quantitative PCR to determine their expression profiles. This revealed that sporozoites modulate their RNA amounts not only between the midgut and salivary glands, but also during their storage within the latter. Among the 123 genes, the expression of 66 is described for the first time in sporozoites of rodent Plasmodium species. Conclusion These novel sporozoite expressed genes, especially those expressed at high levels in salivary gland sporozoites, are likely to play a role in Plasmodium infectivity in the mammalian host.

  2. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository.

    Science.gov (United States)

    Edgar, Ron; Domrachev, Michael; Lash, Alex E

    2002-01-01

    The Gene Expression Omnibus (GEO) project was initiated in response to the growing demand for a public repository for high-throughput gene expression data. GEO provides a flexible and open design that facilitates submission, storage and retrieval of heterogeneous data sets from high-throughput gene expression and genomic hybridization experiments. GEO is not intended to replace in house gene expression databases that benefit from coherent data sets, and which are constructed to facilitate a particular analytic method, but rather complement these by acting as a tertiary, central data distribution hub. The three central data entities of GEO are platforms, samples and series, and were designed with gene expression and genomic hybridization experiments in mind. A platform is, essentially, a list of probes that define what set of molecules may be detected. A sample describes the set of molecules that are being probed and references a single platform used to generate its molecular abundance data. A series organizes samples into the meaningful data sets which make up an experiment. The GEO repository is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

  3. Transcriptional profiling of host gene expression in chicken embryo lung cells infected with laryngotracheitis virus

    Directory of Open Access Journals (Sweden)

    Li Xianyao

    2010-07-01

    Full Text Available Abstract Background Infection by infectious laryngotracheitis virus (ILTV; gallid herpesvirus 1 causes acute respiratory diseases in chickens often with high mortality. To better understand host-ILTV interactions at the host transcriptional level, a microarray analysis was performed using 4 × 44 K Agilent chicken custom oligo microarrays. Results Microarrays were hybridized using the two color hybridization method with total RNA extracted from ILTV infected chicken embryo lung cells at 0, 1, 3, 5, and 7 days post infection (dpi. Results showed that 789 genes were differentially expressed in response to ILTV infection that include genes involved in the immune system (cytokines, chemokines, MHC, and NF-κB, cell cycle regulation (cyclin B2, CDK1, and CKI3, matrix metalloproteinases (MMPs and cellular metabolism. Differential expression for 20 out of 789 genes were confirmed by quantitative reverse transcription-PCR (qRT-PCR. A bioinformatics tool (Ingenuity Pathway Analysis used to analyze biological functions and pathways on the group of 789 differentially expressed genes revealed that 21 possible gene networks with intermolecular connections among 275 functionally identified genes. These 275 genes were classified into a number of functional groups that included cancer, genetic disorder, cellular growth and proliferation, and cell death. Conclusion The results of this study provide comprehensive knowledge on global gene expression, and biological functionalities of differentially expressed genes in chicken embryo lung cells in response to ILTV infections.

  4. Gene expression in developing watermelon fruit

    Science.gov (United States)

    Wechter, W Patrick; Levi, Amnon; Harris, Karen R; Davis, Angela R; Fei, Zhangjun; Katzir, Nurit; Giovannoni, James J; Salman-Minkov, Ayelet; Hernandez, Alvaro; Thimmapuram, Jyothi; Tadmor, Yaakov; Portnoy, Vitaly; Trebitsh, Tova

    2008-01-01

    Background Cultivated watermelon form large fruits that are highly variable in size, shape, color, and content, yet have extremely narrow genetic diversity. Whereas a plethora of genes involved in cell wall metabolism, ethylene biosynthesis, fruit softening, and secondary metabolism during fruit development and ripening have been identified in other plant species, little is known of the genes involved in these processes in watermelon. A microarray and quantitative Real-Time PCR-based study was conducted in watermelon [Citrullus lanatus (Thunb.) Matsum. & Nakai var. lanatus] in order to elucidate the flow of events associated with fruit development and ripening in this species. RNA from three different maturation stages of watermelon fruits, as well as leaf, were collected from field grown plants during three consecutive years, and analyzed for gene expression using high-density photolithography microarrays and quantitative PCR. Results High-density photolithography arrays, composed of probes of 832 EST-unigenes from a subtracted, fruit development, cDNA library of watermelon were utilized to examine gene expression at three distinct time-points in watermelon fruit development. Analysis was performed with field-grown fruits over three consecutive growing seasons. Microarray analysis identified three hundred and thirty-five unique ESTs that are differentially regulated by at least two-fold in watermelon fruits during the early, ripening, or mature stage when compared to leaf. Of the 335 ESTs identified, 211 share significant homology with known gene products and 96 had no significant matches with any database accession. Of the modulated watermelon ESTs related to annotated genes, a significant number were found to be associated with or involved in the vascular system, carotenoid biosynthesis, transcriptional regulation, pathogen and stress response, and ethylene biosynthesis. Ethylene bioassays, performed with a closely related watermelon genotype with a similar

  5. Gene expression in developing watermelon fruit

    Directory of Open Access Journals (Sweden)

    Hernandez Alvaro

    2008-06-01

    Full Text Available Abstract Background Cultivated watermelon form large fruits that are highly variable in size, shape, color, and content, yet have extremely narrow genetic diversity. Whereas a plethora of genes involved in cell wall metabolism, ethylene biosynthesis, fruit softening, and secondary metabolism during fruit development and ripening have been identified in other plant species, little is known of the genes involved in these processes in watermelon. A microarray and quantitative Real-Time PCR-based study was conducted in watermelon [Citrullus lanatus (Thunb. Matsum. & Nakai var. lanatus] in order to elucidate the flow of events associated with fruit development and ripening in this species. RNA from three different maturation stages of watermelon fruits, as well as leaf, were collected from field grown plants during three consecutive years, and analyzed for gene expression using high-density photolithography microarrays and quantitative PCR. Results High-density photolithography arrays, composed of probes of 832 EST-unigenes from a subtracted, fruit development, cDNA library of watermelon were utilized to examine gene expression at three distinct time-points in watermelon fruit development. Analysis was performed with field-grown fruits over three consecutive growing seasons. Microarray analysis identified three hundred and thirty-five unique ESTs that are differentially regulated by at least two-fold in watermelon fruits during the early, ripening, or mature stage when compared to leaf. Of the 335 ESTs identified, 211 share significant homology with known gene products and 96 had no significant matches with any database accession. Of the modulated watermelon ESTs related to annotated genes, a significant number were found to be associated with or involved in the vascular system, carotenoid biosynthesis, transcriptional regulation, pathogen and stress response, and ethylene biosynthesis. Ethylene bioassays, performed with a closely related watermelon

  6. Gene Expression Profile Changes in Germinating Rice

    Institute of Scientific and Technical Information of China (English)

    Dongli He; Chao Han; Pingfang Yang

    2011-01-01

    Water absorption is a prerequisite for seed germination.During imbibition,water influx causes the resumption of many physiological and metabolic processes in growing seed.In order to obtain more complete knowledge about the mechanism of seed germination,two-dimensional gel electrophoresis was applied to investigate the protein profile changes of rice seed during the first 48 h of imbibition.Thirtynine differentially expressed proteins were identified,including 19 down-regulated and 20 up-regulated proteins.Storage proteins and some seed development- and desiccation-associated proteins were down regulated.The changed patterns of these proteins indicated extensive mobilization of seed reserves.By contrast,catabolism-associated proteins were up regulated upon imbibition.Semi-quantitative real time polymerase chain reaction analysis showed that most of the genes encoding the down- or upregulated proteins were also down or up regulated at mRNA level.The expression of these genes was largely consistent at mRNA and protein levels.In providing additional information concerning gene regulation in early plant life,this study will facilitate understanding of the molecular mechanisms of seed germination.

  7. 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.

  8. Nuclear AXIN2 represses MYC gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Rennoll, Sherri A.; Konsavage, Wesley M.; Yochum, Gregory S., E-mail: gsy3@psu.edu

    2014-01-03

    Highlights: •AXIN2 localizes to cytoplasmic and nuclear compartments in colorectal cancer cells. •Nuclear AXIN2 represses the activity of Wnt-responsive luciferase reporters. •β-Catenin bridges AXIN2 to TCF transcription factors. •AXIN2 binds the MYC promoter and represses MYC gene expression. -- Abstract: The β-catenin transcriptional coactivator is the key mediator of the canonical Wnt signaling pathway. In the absence of Wnt, β-catenin associates with a cytosolic and multi-protein destruction complex where it is phosphorylated and targeted for proteasomal degradation. In the presence of Wnt, the destruction complex is inactivated and β-catenin translocates into the nucleus. In the nucleus, β-catenin binds T-cell factor (TCF) transcription factors to activate expression of c-MYC (MYC) and Axis inhibition protein 2 (AXIN2). AXIN2 is a member of the destruction complex and, thus, serves in a negative feedback loop to control Wnt/β-catenin signaling. AXIN2 is also present in the nucleus, but its function within this compartment is unknown. Here, we demonstrate that AXIN2 localizes to the nuclei of epithelial cells within normal and colonic tumor tissues as well as colorectal cancer cell lines. In the nucleus, AXIN2 represses expression of Wnt/β-catenin-responsive luciferase reporters and forms a complex with β-catenin and TCF. We demonstrate that AXIN2 co-occupies β-catenin/TCF complexes at the MYC promoter region. When constitutively localized to the nucleus, AXIN2 alters the chromatin structure at the MYC promoter and directly represses MYC gene expression. These findings suggest that nuclear AXIN2 functions as a rheostat to control MYC expression in response to Wnt/β-catenin signaling.

  9. 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

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

    Directory of Open Access Journals (Sweden)

    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.

  11. Differential gene expression profiles of hepatocellular carcinomas associated or not with viral infection

    Directory of Open Access Journals (Sweden)

    M. Bellodi-Privato

    2009-12-01

    Full Text Available Chronic hepatitis B (HBV and C (HCV virus infections are the most important factors associated with hepatocellular carcinoma (HCC, but tumor prognosis remains poor due to the lack of diagnostic biomarkers. In order to identify novel diagnostic markers and therapeutic targets, the gene expression profile associated with viral and non-viral HCC was assessed in 9 tumor samples by oligo-microarrays. The differentially expressed genes were examined using a z-score and KEGG pathway for the search of ontological biological processes. We selected a non-redundant set of 15 genes with the lowest P value for clustering samples into three groups using the non-supervised algorithm k-means. Fisher’s linear discriminant analysis was then applied in an exhaustive search of trios of genes that could be used to build classifiers for class distinction. Different transcriptional levels of genes were identified in HCC of different etiologies and from different HCC samples. When comparing HBV-HCC vs HCV-HCC, HBV-HCC/HCV-HCC vs non-viral (NV-HCC, HBC-HCC vs NV-HCC, and HCV-HCC vs NV-HCC of the 58 non-redundant differentially expressed genes, only 6 genes (IKBKβ, CREBBP, WNT10B, PRDX6, ITGAV, and IFNAR1 were found to be associated with hepatic carcinogenesis. By combining trios, classifiers could be generated, which correctly classified 100% of the samples. This expression profiling may provide a useful tool for research into the pathophysiology of HCC. A detailed understanding of how these distinct genes are involved in molecular pathways is of fundamental importance to the development of effective HCC chemoprevention and treatment.

  12. Minimising immunohistochemical false negative ER classification using a complementary 23 gene expression signature of ER status.

    Directory of Open Access Journals (Sweden)

    Qiyuan Li

    Full Text Available BACKGROUND: Expression of the oestrogen receptor (ER in breast cancer predicts benefit from endocrine therapy. Minimising the frequency of false negative ER status classification is essential to identify all patients with ER positive breast cancers who should be offered endocrine therapies in order to improve clinical outcome. In routine oncological practice ER status is determined by semi-quantitative methods such as immunohistochemistry (IHC or other immunoassays in which the ER expression level is compared to an empirical threshold. The clinical relevance of gene expression-based ER subtypes as compared to IHC-based determination has not been systematically evaluated. Here we attempt to reduce the frequency of false negative ER status classification using two gene expression approaches and compare these methods to IHC based ER status in terms of predictive and prognostic concordance with clinical outcome. METHODOLOGY/PRINCIPAL FINDINGS: Firstly, ER status was discriminated by fitting the bimodal expression of ESR1 to a mixed Gaussian model. The discriminative power of ESR1 suggested bimodal expression as an efficient way to stratify breast cancer; therefore we identified a set of genes whose expression was both strongly bimodal, mimicking ESR expression status, and highly expressed in breast epithelial cell lines, to derive a 23-gene ER expression signature-based classifier. We assessed our classifiers in seven published breast cancer cohorts by comparing the gene expression-based ER status to IHC-based ER status as a predictor of clinical outcome in both untreated and tamoxifen treated cohorts. In untreated breast cancer cohorts, the 23 gene signature-based ER status provided significantly improved prognostic power compared to IHC-based ER status (P = 0.006. In tamoxifen-treated cohorts, the 23 gene ER expression signature predicted clinical outcome (HR = 2.20, P = 0.00035. These complementary ER signature-based strategies

  13. Expressing exogenous genes in newts by transgenesis.

    Science.gov (United States)

    Casco-Robles, Martin Miguel; Yamada, Shouta; Miura, Tomoya; Nakamura, Kenta; Haynes, Tracy; Maki, Nobuyasu; Del Rio-Tsonis, Katia; Tsonis, Panagiotis A; Chiba, Chikafumi

    2011-05-01

    The great regenerative abilities of newts provide the impetus for studies at the molecular level. However, efficient methods for gene regulation have historically been quite limited. Here we describe a protocol for transgenically expressing exogenous genes in the newt Cynops pyrrhogaster. This method is simple: a reaction mixture of I-SceI meganuclease and a plasmid DNA carrying a transgene cassette flanked by the enzyme recognition sites is directly injected into fertilized eggs. The protocol achieves a high efficiency of transgenesis, comparable to protocols used in other animal systems, and it provides a practical number of transgenic newts (∼20% of injected embryos) that survive beyond metamorphosis and that can be applied to regenerative studies. The entire protocol for obtaining transgenic adult newts takes 4-5 months.

  14. Gene expression-targeted isoflavone therapy.

    Science.gov (United States)

    Węgrzyn, Alicja

    2012-04-01

    Lysosomal storage diseases (LSD) form a group of inherited metabolic disorders caused by dysfunction of one of the lysosomal proteins, resulting in the accumulation of certain compounds. Although these disorders are among first genetic diseases for which specific treatments were proposed, there are still serious unsolved problems that require development of novel therapeutic procedures. An example is neuronopathy, which develops in most of LSD and cannot be treated efficiently by currently approved therapies. Recently, a new potential therapy, called gene expression-targeted isoflavone therapy (GET IT), has been proposed for a group of LSD named mucopolysaccharidoses (MPS), in which storage of incompletely degraded glycosaminoglycans (GAGs) results in severe symptoms of virtually all tissues and organs, including central nervous system. The idea of this therapy is to inhibit synthesis of GAGs by modulating expression of genes coding for enzymes involved in synthesis of these compounds. Such a modulation is possible by using isoflavones, particularly genistein, which interfere with a signal transduction process necessary for stimulation of expression of certain genes. Results of in vitro experiments and studies on animal models indicated a high efficiency of GET IT, including correction of behavior of affected mice. However, clinical trials, performed with soy isoflavone extracts, revealed only limited efficacy. This caused a controversy about GET IT as a potential, effective treatment of patients suffering from MPS, especially neuronopathic forms of these diseases. It this critical review, I present possible molecular mechanisms of therapeutic action of isoflavones (particularly genistein) and suggest that efficacy of GET IT might be sufficiently high when using relatively high doses of synthetic genistein (which was employed in experiments on cell cultures and mouse models) rather than low doses of soy isoflavone extracts (which were used in clinical trials). This

  15. Gene expression profiling of cutaneous wound healing

    Directory of Open Access Journals (Sweden)

    Wang Ena

    2007-02-01

    Full Text Available Abstract Background Although the sequence of events leading to wound repair has been described at the cellular and, to a limited extent, at the protein level this process has yet to be fully elucidated. Genome wide transcriptional analysis tools promise to further define the global picture of this complex progression of events. Study Design This study was part of a placebo-controlled double-blind clinical trial in which basal cell carcinomas were treated topically with an immunomodifier – toll-like receptor 7 agonist: imiquimod. The fourteen patients with basal cell carcinoma in the placebo arm of the trial received placebo treatment consisting solely of vehicle cream. A skin punch biopsy was obtained immediately before treatment and at the end of the placebo treatment (after 2, 4 or 8 days. 17.5K cDNA microarrays were utilized to profile the biopsy material. Results Four gene signatures whose expression changed relative to baseline (before wound induction by the pre-treatment biopsy were identified. The largest group was comprised predominantly of inflammatory genes whose expression was increased throughout the study. Two additional signatures were observed which included preferentially pro-inflammatory genes in the early post-treatment biopsies (2 days after pre-treatment biopsies and repair and angiogenesis genes in the later (4 to 8 days biopsies. The fourth and smallest set of genes was down-regulated throughout the study. Early in wound healing the expression of markers of both M1 and M2 macrophages were increased, but later M2 markers predominated. Conclusion The initial response to a cutaneous wound induces powerful transcriptional activation of pro-inflammatory stimuli which may alert the host defense. Subsequently and in the absence of infection, inflammation subsides and it is replaced by angiogenesis and remodeling. Understanding this transition which may be driven by a change from a mixed macrophage population to predominately M2

  16. Network Completion for Static Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Natsu Nakajima

    2014-01-01

    Full Text Available We tackle the problem of completing and inferring genetic networks under stationary conditions from static data, where network completion is to make the minimum amount of modifications to an initial network so that the completed network is most consistent with the expression data in which addition of edges and deletion of edges are basic modification operations. For this problem, we present a new method for network completion using dynamic programming and least-squares fitting. This method can find an optimal solution in polynomial time if the maximum indegree of the network is bounded by a constant. We evaluate the effectiveness of our method through computational experiments using synthetic data. Furthermore, we demonstrate that our proposed method can distinguish the differences between two types of genetic networks under stationary conditions from lung cancer and normal gene expression data.

  17. Apopotic gene Bax expression in carotid plaque

    Institute of Scientific and Technical Information of China (English)

    Bao-Zhong MEN; Ding-Biao ZHOU; Huai-Yin SHI; Xiao-Ming ZHANG

    2006-01-01

    The expression of BAX in carotid atherosclerosis and its regulation is far from defined. Objectives To investigate BAX expression in stable/fibrous and instable/vulnerable carotid plaque and its clinical significance. Methods 25 cases of carotid plaque specimens obtained from endarterectomy were divided into two groups, stable/fibrous 14 cases, vulnerable/instable 11 cases; aortic artery and its branches from hepatic transplantation donors 6 case as control. The expression of proapoptotic BAX was detected by immunohistochemistry(IHC), in situ hybridization(ISH) and in situ TdT dUTP nick end labeling (TUNEL). Results 5 cases of BAX ( + ) were detected by ICH and ISH, 4 case of TUNEL ( + ) were detected by TUNEL in stable/fibrous carotid plaque , while 10 cases were BAX ( + )by IHC(P < 0.05) , 11case by ISH and 9 case by TUNEL were detected in instable/vulnerable carotid plaque ( P < 0.01 ), respectively. The intensity of BAX ( + ) cells by IHC and ISH was 8.63 ± 2.62 and 10.32 ± 3.12 in fibrous plaques, whereas 122 ± 21.64and 152 ± 23.35 in vulnerable plaques, respectively. No expression of BAX was found in controlled group. Conclusion The higher expression of Bax in vulnerable carotid plaque may be one mechanisms in molecular pathogenesis of carotid atherosclerosis which affect plaque stability and be the cause of higher incidence of stroke than fibrous carotid plaques, the regulation of BAX expression in different stage of atherosclerosis may provide targets in gene therapy for carotid atherosclerosis.

  18. Differentially expressed gene in osteosarcoma cell lines with different metastatic potentials

    Institute of Scientific and Technical Information of China (English)

    Xinzhi Li; Lin Meng; Anming Chen; Fengjin Guo; Zhenqiang Luo; Heng Zeng

    2009-01-01

    Objective: To study the expression of osteosarcoma metastasis associated gene using a cDNA microarray, and screen new candidate genes related'to the development, progress and osteosarcoma metastasis. Methods: Total RNA of a low metastatic osteosarcoma and a high metastatic osteosarcoma (M6 and M8 cell lines, respectively) was extracted, purified to mRNA and then reverse transcribed to cDNA. M6 was used as the experimental group and M8 as the control group, and the gene expression of cells from both of these two sublines was investigated using cDNA microarrays containig 8064 cDNA clones. The cDNA of M6 was labeled with cy3 and the cDNA of M8 was labeled with cy5. The two sublines were hybridized with the cDNA microarray. The hybridization signals were scanned with a Generation Ⅲ array scanner and analyzed by Imagequant 5.0 software. Results: There were 330 differentially expressed genes between M6 and M8. In the M6 subline,152 genes were up-regulated and 178 genes were down-regulated compared to the M8 subline. These genes could be classified according to their function. Cell growth-related genes that were down-regulated included CCNG1, CDC2, APCl0,and RPA3, while expression of the tumor suppressor genes, CDKN1A and CDKN2D, was up-regulated. Other genes that were differentially expressed included those that have been implicated in the regulation of signal transduction, metabolism and apoptosis. Conclusion: This study exploits a cDNA microarray approach to identifying genes that may be associated with metastasis. The gene expression profiles of osteosarcoma cell lines is a potentially important index in the search of new candidate genes related to tumor occurrence, development and metastasis.

  19. Gene expression profiling and endothelin in acute experimental pancreatitis

    Institute of Scientific and Technical Information of China (English)

    Helieh S Oz; Ying Lu; Louis P Vera-Portocarrero; Pei Ge; Ada Silos-Santiago; Karin N Westlund

    2012-01-01

    AIM:To analyze gene expression profiles in an experimental pancreatitis and provide functional reversal of hypersensitivity with candidate gene endothelin-1 antagonists.METHODS:Dibutyltin dichloride (DBTC) is a chemical used as a polyvinyl carbonate stabilizer/catalyzer,biocide in agriculture,antifouling agent in paint and fabric.DBTC induces an acute pancreatitis flare through generation of reactive oxygen species.Lewis-inbred rats received a single i.v.injection with either DBTC or vehicle.Spinal cord and dorsal root ganglia (DRG) were taken at the peak of inflammation and processed for transcriptional profiling with a cDNA microarray biased for rat brain-specific genes.In a second study,groups of animals with DBTC-induced pancreatitis were treated with endothelin (ET) receptor antagonists [ET-A (BQ123) and ET-B BQ788)].Spontaneous pain related mechanical and thermal hypersensitivity were measured.Immunohistochemical analysis was performed using anti-ET-A and ET-B antibodies on sections from pancreatic tissues and DRG of the T10-12 spinal segments.RESULTS:Animals developed acute pancreatic inflammation persisting 7-10 d as confirmed by pathological studies (edema in parenchyma,loss of pancreatic architecture and islets,infiltration of inflammatory cells,neutrophil and mononuclear cells,degeneration,vacuolization and necrosis of acinar cells) and the painrelated behaviors (cutaneous secondary mechanical and thermal hypersensitivity).Gene expression profile was different in the spinal cord from animals with pancreatitis compared to the vehicle control group.Over 260 up-regulated and 60 down-regulated unique genes could be classified into 8 functional gene families:circulatory/acute phase/immunomodulatory; extracellular matrix; structural; channel/receptor/transporter; signaling transduction; transcription/translation-related; antioxidants/chaperones/heat shock; pancreatic and other enzymes.ET-1 was among the 52 candidate genes upregulated greater than 2-fold in

  20. 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.

  1. Multiobjective binary biogeography based optimization for feature selection using gene expression data.

    Science.gov (United States)

    Li, Xiangtao; Yin, Minghao

    2013-12-01

    Gene expression data play an important role in the development of efficient cancer diagnoses and classification. However, gene expression data are usually redundant and noisy, and only a subset of them present distinct profiles for different classes of samples. Thus, selecting high discriminative genes from gene expression data has become increasingly interesting in the field of bioinformatics. In this paper, a multi-objective biogeography based optimization method is proposed to select the small subset of informative gene relevant to the classification. In the proposed algorithm, firstly, the Fisher-Markov selector is used to choose the 60 top gene expression data. Secondly, to make biogeography based optimization suitable for the discrete problem, binary biogeography based optimization, as called BBBO, is proposed based on a binary migration model and a binary mutation model. Then, multi-objective binary biogeography based optimization, as we called MOBBBO, is proposed by integrating the non-dominated sorting method and the crowding distance method into the BBBO framework. Finally, the MOBBBO method is used for gene selection, and support vector machine is used as the classifier with the leave-one-out cross-validation method (LOOCV). In order to show the effective and efficiency of the algorithm, the proposed algorithm is tested on ten gene expression dataset benchmarks. Experimental results demonstrate that the proposed method is better or at least comparable with previous particle swarm optimization (PSO) algorithm and support vector machine (SVM) from literature when considering the quality of the solutions obtained.

  2. Expression patterns and action analysis of genes associated with physiological responses during rat liver regeneration: Innate immune response

    Institute of Scientific and Technical Information of China (English)

    Guang-Wen Chen; Ming-Zhen Zhang; Li-Feng Zhao; Cun-Shuan Xu

    2006-01-01

    AIM: To study the relationship between innate immune response and liver regeneration (LR) at transcriptional level.METHODS: Genes associated with innate immunity response were obtained by collecting the data from databases and retrieving articles. Gene expression changes in rat regenerating liver were detected by rat genome 230 2.0 array.RESULTS: A total of 85 genes were found to be associated with LR. The initially and totally expressed number of genes at the phases of initiation [0.5-4 h after partial hepatectomy (PH)], transition from Go to G1 (4-6 h after PH), cell proliferation (6-66 h after PH),cell differentiation and structure-function reconstruction (66-168 h after PH) was 36, 9, 47, 4 and 36, 26, 78,50, respectively, illustrating that the associated genes were mainly triggered at the initial phase of LR and worked at different phases. According to their expression similarity, these genes were classified into 5 types: 41 up-regulated, 4 predominantly up-regulated, 26 downregulated, 6 predominantly down-regulated, and 8 approximately up/down-regulated genes, respectively.The expression of these genes was up-regulated 350 times and down-regulated 129 times respectively,demonstrating that the expression of most genes was enhanced while the expression of a small number of genes was decreased during LR. Their time relevance was classified into 14 groups, showing that the cellular physiological and biochemical activities during LR were staggered. According to the gene expression patterns,they were classified into 28 types, indicating that the cellular physiological and biochemical activities were diverse and complicated during LR.CONCLUSION: Congenital cellular immunity is enhanced mainly in the forepart, prophase and anaphase of LR while congenital molecular immunity is increased dominantly in the forepart and anaphase of LR. A total of 85 genes associated with LR play an important role in innate immunity.

  3. Expression profiles for six zebrafish genes during gonadal sex differentiation

    DEFF Research Database (Denmark)

    Jørgensen, Anne; Morthorst, Jane E.; Andersen, Ole;

    2008-01-01

    the precise timing of expression of six genes previously suggested to be associated with sex differentiation in zebrafish. The current study investigates the expression of all six genes in the same individual fish with extensive sampling dates during sex determination and -differentiation. RESULTS...... the same fish allowing comparison of the high and low expressers of genes that are expected to be highest expressed in either males or females. There were 78% high or low expressers of all three "male" genes (ar, sox9a and dmrt1) in the investigated period and 81% were high or low expressers of both...

  4. 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...

  5. Expression patterns and action analysis of genes associated with hepatitis virus infection during rat liver regeneration

    Institute of Scientific and Technical Information of China (English)

    Li-Juan Su; Guang-Wei Ding; Zhi-Li Yang; Shou-Bing Zhang; Yu-Xiu Yang; Cun-Shuan Xu

    2006-01-01

    AIM: To study the action of hepatitis virus infectionassociated genes at transcription level during liver regeneration (LR).METHODS: Hepatitis virus infection-associated genes were obtained by collecting the data from databases and retrieving the correlated articles, and their expression changes in the regenerating rat liver were detected with the rat genome 230 2.0 array.RESULTS: Eighty-eight genes were found to be associated with liver regeneration. The number of genes initially and totally expressed during initial LR [0.5-4 h after partial hepatectomy (PH)], transition from G0 to G1 (4-6 h after PH), cell proliferation (6-66 h after PH), cell differentiation and reorganization of structure-function (66-168 h after PH) was 37, 8, 48, 3 and 37,26, 80, 57, respectively, indicating that the genes were mainly triggered at the early stage of LR (0.5-4 h after PH), and worked at different phases. These genes were classified into 5 types according to their expression similarity, namely 37 up-regulated, 9 predominantly up-regulated, 34 down-regulated, 6 predominantly down-regulated and 2 up/down-regulated genes. Their total up- and down-regulation frequencies were 359 and 149 during LR, indicating that the expression of most genes was enhanced, while the expression of a small number of genes was attenuated during LR. According to time relevance, they were classified into 12 groups (0.5 and 1h, 2 and 4h, 6h, 8 and 12h, 16 and 96h, 18 and 24 h, 30 and 42 h, 36 and 48 h, 54 and 60 h, 66 and 72 h, 120 and 144 h, 168 h), demonstrating that the cellular physiological and biochemical activities during LR were fluctuated. According to expression changes of the genes, their expression patterns were classified into 23 types, suggesting that the cellular physiological and biochemical activities during LR were diverse and complicated.CONCLUSION: The anti-virus infection capacity of regenerating liver can be enhanced and 88 genes play an important role in LR.

  6. Spatiotemporal patterns of gene expression during fetal monkey brain development.

    Science.gov (United States)

    Redmond, D Eugene; Zhao, Ji-Liang; Randall, Jeffry D; Eklund, Aron C; Eusebi, Leonard O V; Roth, Robert H; Gullans, Steven R; Jensen, Roderick V

    2003-12-19

    Human DNA microarrays are used to study the spatiotemporal patterns of gene expression during the course of fetal monkey brain development. The 444 most dynamically expressed genes in four major brain areas are reported at five different fetal ages. The spatiotemporal profiles of gene expression show both regional specificity as well as waves of gene expression across the developing brain. These patterns of expression are used to identify statistically significant clusters of co-regulated genes. This study demonstrates for the first time in the primate the relevance, timing, and spatial locations of expression for many developmental genes identified in other animals and provides clues to the functions of many unknowns. Two different microarray platforms are used to provide high-throughput cross validation of the most important gene expression changes. These results may lead to new understanding of brain development and new strategies for treating and repairing disorders of brain function.

  7. Verdict Accuracy of Quick Reduct Algorithm using Clustering and Classification Techniques for Gene Expression Data

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    T.Chandrasekhar

    2012-01-01

    Full Text Available In most gene expression data, the number of training samples is very small compared to the large number of genes involved in the experiments. However, among the large amount of genes, only a small fraction is effective for performing a certain task. Furthermore, a small subset of genes is desirable in developing gene expression based diagnostic tools for delivering reliable and understandable results. With the gene selection results, the cost of biological experiment and decision can be greatly reduced by analyzing only the marker genes. An important application of gene expression data in functional genomics is to classify samples according to their gene expression profiles. Feature selection (FS is a process which attempts to select more informative features. It is one of the important steps in knowledge discovery. Conventional supervised FS methods evaluate various feature subsets using an evaluation function or metric to select only those features which are related to the decision classes of the data under consideration. This paper studies a feature selection method based on rough set theory. Further K-Means, Fuzzy C-Means (FCM algorithm have implemented for the reduced feature set without considering class labels. Then the obtained results are compared with the original class labels. Back Propagation Network (BPN has also been used for classification. Then the performance of K-Means, FCM, and BPN are analyzed through the confusion matrix. It is found that the BPN is performing well comparatively.

  8. Identification of Differentially Expressed Gene after Femoral Fracture via Microarray Profiling

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    Donggen Zhong

    2014-01-01

    Full Text Available We aimed to investigate differentially expressed genes (DEGs in different stages after femoral fracture based on rat models, providing the basis for the treatment of sport-related fractures. Gene expression data GSE3298 was downloaded from Gene Expression Omnibus (GEO, including 16 chips. All femoral fracture samples were classified into earlier fracture stage and later fracture stage. Total 87 DEGs simultaneously occurred in two stages, of which 4 genes showed opposite expression tendency. Out of the 4 genes, Rest and Cst8 were hub nodes in protein-protein interaction (PPI network. The GO (Gene Ontology function enrichment analysis verified that nutrition supply related genes were enriched in the earlier stage and neuron growth related genes were enriched in the later stage. Calcium signaling pathway was the most significant pathway in earlier stage; in later stage, DEGs were enriched into 2 neurodevelopment-related pathways. Analysis of Pearson's correlation coefficient showed that a total of 3,300 genes were significantly associated with fracture time, none of which was overlapped with identified DEGs. This study suggested that Rest and Cst8 might act as potential indicators for fracture healing. Calcium signaling pathway and neurodevelopment-related pathways might be deeply involved in bone healing after femoral fracture.

  9. The Effects of Hallucinogens on Gene Expression.

    Science.gov (United States)

    Martin, David A; Nichols, Charles D

    2017-07-05

    The classic serotonergic hallucinogens, or psychedelics, have the ability to profoundly alter perception and behavior. These can include visual distortions, hallucinations, detachment from reality, and mystical experiences. Some psychedelics, like LSD, are able to produce these effects with remarkably low doses of drug. Others, like psilocybin, have recently been demonstrated to have significant clinical efficacy in the treatment of depression, anxiety, and addiction that persist for at least several months after only a single therapeutic session. How does this occur? Much work has recently been published from imaging studies showing that psychedelics alter brain network connectivity. They facilitate a disintegration of the default mode network, producing a hyperconnectivity between brain regions that allow centers that do not normally communicate with each other to do so. The immediate and acute effects on both behaviors and network connectivity are likely mediated by effector pathways downstream of serotonin 5-HT2A receptor activation. These acute molecular processes also influence gene expression changes, which likely influence synaptic plasticity and facilitate more long-term changes in brain neurochemistry ultimately underlying the therapeutic efficacy of a single administration to achieve long-lasting effects. In this review, we summarize what is currently known about the molecular genetic responses to psychedelics within the brain and discuss how gene expression changes may contribute to altered cellular physiology and behaviors.

  10. 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

  11. 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

  12. Brief isoflurane anaesthesia affects differential gene expression, gene ontology and gene networks in rat brain.

    Science.gov (United States)

    Lowes, Damon A; Galley, Helen F; Moura, Alessandro P S; Webster, Nigel R

    2017-01-15

    Much is still unknown about the mechanisms of effects of even brief anaesthesia on the brain and previous studies have simply compared differential expression profiles with and without anaesthesia. We hypothesised that network analysis, in addition to the traditional differential gene expression and ontology analysis, would enable identification of the effects of anaesthesia on interactions between genes. Rats (n=10 per group) were randomised to anaesthesia with isoflurane in oxygen or oxygen only for 15min, and 6h later brains were removed. Differential gene expression and gene ontology analysis of microarray data was performed. Standard clustering techniques and principal component analysis with Bayesian rules were used along with social network analysis methods, to quantitatively model and describe the gene networks. Anaesthesia had marked effects on genes in the brain with differential regulation of 416 probe sets by at least 2 fold. Gene ontology analysis showed 23 genes were functionally related to the anaesthesia and of these, 12 were involved with neurotransmitter release, transport and secretion. Gene network analysis revealed much greater connectivity in genes from brains from anaesthetised rats compared to controls. Other importance measures were also altered after anaesthesia; median [range] closeness centrality (shortest path) was lower in anaesthetized animals (0.07 [0-0.30]) than controls (0.39 [0.30-0.53], pgenes after anaesthesia and suggests future targets for investigation. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Detection of gene expression pattern in the early stage after spinal cord injury by gene chip

    Institute of Scientific and Technical Information of China (English)

    刘成龙; 靳安民; 童斌辉

    2003-01-01

    Objective: To study the changes of the gene expression pattern of spinal cord tissues in the early stage after injury by DNA microarray (gene chip). Methods: The contusion model of rat spinal cord was established according to Allen's falling strike method and the gene expression patterns of normal and injured spinal cord tissues were studied by gene chip. Results: The expression of 45 genes was significantly changed in the early stage after spinal cord injury, in which 22 genes up-regulated and 23 genes down-regulated. Conclusions: The expression of some genes changes significantly in the early stage after spinal cord injury, which indicates the complexity of secondary spinal cord injury.

  14. Coactivators in PPAR-Regulated Gene Expression

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    Navin Viswakarma

    2010-01-01

    Full Text Available Peroxisome proliferator-activated receptor (PPARα, β (also known as δ, and γ function as sensors for fatty acids and fatty acid derivatives and control important metabolic pathways involved in the maintenance of energy balance. PPARs also regulate other diverse biological processes such as development, differentiation, inflammation, and neoplasia. In the nucleus, PPARs exist as heterodimers with retinoid X receptor-α bound to DNA with corepressor molecules. Upon ligand activation, PPARs undergo conformational changes that facilitate the dissociation of corepressor molecules and invoke a spatiotemporally orchestrated recruitment of transcription cofactors including coactivators and coactivator-associated proteins. While a given nuclear receptor regulates the expression of a prescribed set of target genes, coactivators are likely to influence the functioning of many regulators and thus affect the transcription of many genes. Evidence suggests that some of the coactivators such as PPAR-binding protein (PBP/PPARBP/thyroid hormone receptor-associated protein 220 (TRAP220/mediator complex subunit 1 (MED1 may exert a broader influence on the functions of several nuclear receptors and their target genes. Investigations into the role of coactivators in the function of PPARs should strengthen our understanding of the complexities of metabolic diseases associated with energy metabolism.

  15. 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.

  16. Gene expression in the adrenal glands of three spontaneously hypertensive rat substrains.

    Science.gov (United States)

    Ashenagar, Mohammad S; Tabuchi, Masaki; Kinoshita, Kosho; Ooshima, Kana; Niwa, Atsuko; Watanabe, Yuko; Yoshida, Momoko; Shimada, Kazunori; Yasunaga, Teruo; Yamanishi, Hiromichi; Higashino, Hideaki

    2010-01-01

    We examined gene expression profiles in rat adrenal glands using genome-wide microarray technology. Gene expression levels were determined in four rat strains, including one normotensive strain [Wistar-Kyoto (WKY)] and three substrains derived from WKY rats: spontaneously hypertensive rats (SHR), stroke-prone SHR (SHRSP) and malignant SHRSP (M-SHRSP). This study represents the first attempt at using microarrays to compare gene expression profiles in SHR, SHRSP and M-SHRSP adrenal glands, employing WKY as controls. Expression measurements were made in these four rat strains at 6 and 9 weeks of age; 6 weeks of age covers the pre-hypertensive period in SHR and SHRSP, and 9 weeks of age is the period of rapidly rising blood pressure (BP). Since the aim of this study was to identify candidate genes involved in the genesis of hypertension in the SHR substrains, we identified genes that were consistently different in their expression, isolating 87 up-regulated genes showing a more than 4-fold increase and 128 down-regulated genes showing a less than 1/4-fold decrease in at least two different experiments. We classified all these up- or down-regulated genes by their expression profiles, and searched for candidate genes. At 6 weeks of age, several BP-regulating genes including sparc/osteonectin (Spock2), kynureninase (Kynu), regulator of G-protein signaling 2 (Rgs2) and gap junction protein α1 (Gja1) were identified as up-regulated, and urotensin 2 (Uts2), cytoplasmic epoxide hydrolase 2 (Ephx2), apelin (Apln), insulin-like growth factor 1 receptor (Igf1r) and angiotensin II receptor-associated protein (Agtrap) were identified as down-regulated. The Kynu and Ephx2 genes have previously been reported by other groups to be responsible for hypertension in SHR; however, our present approach identified at least seven new candidate genes.

  17. Gene expression profiling of mouse embryos with microarrays

    OpenAIRE

    Sharov, Alexei A; Piao, Yulan; Minoru S.H. Ko

    2010-01-01

    Global expression profiling by DNA microarrays provides a snapshot of cell and tissue status and becomes an essential tool in biological and medical sciences. Typical questions that can be addressed by microarray analysis in developmental biology include: (1) to find a set of genes expressed in a specific cell type; (2) to identify genes expressed commonly in multiple cell types; (3) to follow the time-course changes of gene expression patterns; (4) to demonstrate cell’s identity by showing s...

  18. Changes in gene expression induced by Micro-Immunotherapy

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    Maurice Jeaner

    2012-09-01

    Full Text Available Background: Metabolic syndrome (MS is a metabolic disorder associated with obesity, type-II diabetes, and “low grade inflammation”, with the concomitant increased risk of cardiovascular events. As a chronic inflammatory process, MS results in a dysregulation of the cytokine profile. 2L®INFLAM, a Micro-immunotherapy (MI medication formulated with highly diluted cytokines, is currently prescribed in Belgium for inflammatory diseases and potentially may be helpful for MS patients. Aims: To investigate the impact of 2L®INFLAM on selected gene expression markers (mRNA in patients suffering from MS, in addition to biological and clinical parameters. Methodology: Four well characterized MS adult patients with stabilized body-weight were advised to take one capsule of 2L®INFLAM per day (by sublingual-oral route for 6 months (composition in table 1. Concomitantly to biological and clinical examination, genes expression status was assessed by a DNA microarray technology (Oxygen™ comprising 200 genes involved mainly in oxidative stress and inflammation. Whole blood collection was performed before and after treatment (3-6 months and mRNA levels measured. Gene expression was classified in 3 series (normally expressed, up or down-regulated and genes related to diabetes predisposition were scored by using a proprietary Diascore (Probiox. Results: Before MI medication, a significant percentage of dysregulated genes (median: 16.3% as well as a positive Diascore (median: 1.6 were noticed. Impressive correction of dysregulated genes (reaching 90% for one patient was observed after 3 months of treatment (median: 2.3% in addition to an improvement of Diascore in 3 MS patients out of 4 (median: 0.5. During the same period, both clinical and biological parameters remained unchanged. Conclusions: MS patients showing a high level of gene dysregulation efficiently normalized after 3 months of 2L

  19. Automation of gene assignments to metabolic pathways using high-throughput expression data

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    Yona Golan

    2005-08-01

    Full Text Available Abstract Background Accurate assignment of genes to pathways is essential in order to understand the functional role of genes and to map the existing pathways in a given genome. Existing algorithms predict pathways by extrapolating experimental data in one organism to other organisms for which this data is not available. However, current systems classify all genes that belong to a specific EC family to all the pathways that contain the corresponding enzymatic reaction, and thus introduce ambiguity. Results Here we describe an algorithm for assignment of genes to cellular pathways that addresses this problem by selectively assigning specific genes to pathways. Our algorithm uses the set of experimentally elucidated metabolic pathways from MetaCyc, together with statistical models of enzyme families and expression data to assign genes to enzyme families and pathways by optimizing correlated co-expression, while minimizing conflicts due to shared assignments among pathways. Our algorithm also identifies alternative ("backup" genes and addresses the multi-domain nature of proteins. We apply our model to assign genes to pathways in the Yeast genome and compare the results for genes that were assigned experimentally. Our assignments are consistent with the experimentally verified assignments and reflect characteristic properties of cellular pathways. Conclusion We present an algorithm for automatic assignment of genes to metabolic pathways. The algorithm utilizes expression data and reduces the ambiguity that characterizes assignments that are based only on EC numbers.

  20. 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

  1. Differentially expressed genes in pancreatic ductal adenocarcinomas identified through serial analysis of gene expression

    DEFF Research Database (Denmark)

    Hustinx, Steven R; Cao, Dengfeng; Maitra, Anirban;

    2004-01-01

    Serial analysis of gene expression (SAGE) is a powerful tool for the discovery of novel tumor markers. The publicly available online SAGE libraries of normal and neoplastic tissues (http://www.ncbi.nlm.nih.gov/SAGE/) have recently been expanded; in addition, a more complete annotation of the human...

  2. Expression patterns and action analysis of genes associated with physiological responses during rat liver regeneration: Cellular immune response

    Institute of Scientific and Technical Information of China (English)

    Lian-Xing Zhang; Li-Feng Zhao; An-Shi Zhang; Xiao-Guang Chen; Cun-Shuan Xu

    2006-01-01

    AIM: To study the cellular immune response during rat liver regeneration (LR) at a transcriptional level.METHODS: Genes associated with the cellular immune response were obtained by collecting the data from databases and retrieving articles. Gene expression changes during LR were detected by rat genome 230 2.0 array.RESULTS: A total of 127 genes were found to be associated with LR. The number of initially and totally expressing genes in the initial phase of LR [0.5-4 h after partial hepatectomy (PH)], transition from G0-G1(4-6 h after PH), cell proliferation (6-66 h after PH),cell differentiation and structure-function reconstruction (66-168 h after PH) was 54, 11, 34, 3 and 54, 49, 70, 49 respectively, illustrating that the associated genes were mainly triggered at the initiation of LR, and worked at different phases. According to their expression similarity,these genes were classified into 41 up-regulated, 21 predominantly up-regulated, 41 down-regulated, 14 predominantly down-regulated, 10 similarly up-regulated and down-regulated genes, respectively. The total upand down-regulated expression times were 419 and 274,respectively, demonstrating that the expression of most genes was increased while the expression of a small number of genes was decreased. Their time relevance was classified into 14 groups, showing that the cellular physiological and biochemical activities were staggered during LR. According to the gene expression patterns,they were classified into 21 types, showing the activities were diverse and complicated during LR.CONCLUSION: Antigen processing and presentation are enhanced mainly in the forepart, prophase and anaphase of LR. T-cell activation and antigen elimination are enhanced mainly in the forepart and prophase of LR. A total of 127 genes associated with LR play an important role in cellular immunity.

  3. 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

  4. Modeling of gap gene expression in Drosophila Kruppel mutants.

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    Konstantin Kozlov

    Full Text Available The segmentation gene network in Drosophila embryo solves the fundamental problem of embryonic patterning: how to establish a periodic pattern of gene expression, which determines both the positions and the identities of body segments. The gap gene network constitutes the first zygotic regulatory tier in this process. Here we have applied the systems-level approach to investigate the regulatory effect of gap gene Kruppel (Kr on segmentation gene expression. We acquired a large dataset on the expression of gap genes in Kr null mutants and demonstrated that the expression levels of these genes are significantly reduced in the second half of cycle 14A. To explain this novel biological result we applied the gene circuit method which extracts regulatory information from spatial gene expression data. Previous attempts to use this formalism to correctly and quantitatively reproduce gap gene expression in mutants for a trunk gap gene failed, therefore here we constructed a revised model and showed that it correctly reproduces the expression patterns of gap genes in Kr null mutants. We found that the remarkable alteration of gap gene expression patterns in Kr mutants can be explained by the dynamic decrease of activating effect of Cad on a target gene and exclusion of Kr gene from the complex network of gap gene interactions, that makes it possible for other interactions, in particular, between hb and gt, to come into effect. The successful modeling of the quantitative aspects of gap gene expression in mutant for the trunk gap gene Kr is a significant achievement of this work. This result also clearly indicates that the oversimplified representation of transcriptional regulation in the previous models is one of the reasons for unsuccessful attempts of mutant simulations.

  5. Cascaded Factor Analysis and Wavelet Transform Method for Tumor Classification Using Gene Expression Data

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    Jayakishan Meher

    2012-08-01

    Full Text Available Correlation between gene expression profiles to disease or different developmental stages of a cell through microarray data and its analysis has been a great deal in molecular biology. As the microarray data have thousands of genes and very few sample, thus efficient feature extraction and computational method development is necessary for the analysis. In this paper we have proposed an effective feature extraction method based on factor analysis (FA with discrete wavelet transform (DWT to detect informative genes. Radial basis function neural network (RBFNN classifier is used to efficiently predict the sample class which has a low complexity than other classifier. The potential of the proposed approach is evaluated through an exhaustive study by many benchmark datasets. The experimental results show that the proposed method can be a useful approach for cancer classification.

  6. Altered endometrial immune gene expression in beef heifers with retarded embryos.

    Science.gov (United States)

    Beltman, M E; Forde, N; Lonergan, P; Crowe, M A

    2013-01-01

    The aim of the present study was to compare endometrial gene expression profiles in a group of beef heifers yielding viable or retarded embryos on Day 7 after oestrus as a means of potentially explaining differences in embryo survival rates. Heifers were classified as either: (1) viable, when the embryo collected on Day 7 after oestrus was at the correct developmental stage (i.e. morula/early blastocyst); or (2) retarded, when the embryo was arrested at the 2-16-cell stage. The focus of the present study was on genes that were associated with either the pro- or anti-inflammatory immune response. Endometrial gene expression was determined using quantitative real-time polymerase chain reaction analysis. Expression of the β-defensin (DEFB1), interferon (IFN)-α (IFNA), IFN-γ (IFNG), interleukin (IL)-6 (IL6), IL-10 (IL10), forkhead box P3 (FOXP3) and natural cytotoxicity triggering receptor 1 (NCR1) genes was lower in endometria from viable than retarded heifers. Expression of the nuclear factor of kappa light polypeptide gene enhancer in B cells 1 (NKFB1), transforming growth factor (TGF)-β (TGFB), IFN-γ-inducible protein 16 (IFI16) and IL-21 (IL21) genes was higher in viable than retarded heifers. We propose that small disturbances in the expression of immune genes in the endometrium on Day 7 after oestrus can have detrimental effects on embryo survival.

  7. 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.

  8. Bioinformatics analysis of the gene expression profile in Bladder carcinoma

    Directory of Open Access Journals (Sweden)

    Jing Xiao

    2013-01-01

    Full Text Available Bladder carcinoma, which has the ninth highest incidence among malignant tumors in the world, is a complex, multifactorial disease. The malignant transformation of bladder cells results from DNA mutations and alterations in gene expression levels. In this work, we used a bioinformatics approach to investigate the molecular mechanisms of bladder carcinoma. Biochips downloaded from the Gene Expression Omnibus (GEO were used to analyze the gene expression profile in urinary bladder cells from individuals with carcinoma. The gene expression profile of normal genomes was used as a control. The analysis of gene expression revealed important alterations in genes involved in biological processes and metabolic pathways. We also identified some small molecules capable of reversing the altered gene expression in bladder carcinoma; these molecules could provide a basis for future therapies for the treatment of this disease.

  9. Integrating murine gene expression studies to understand obstructive lung disease due to chronic inhaled endotoxin.

    Directory of Open Access Journals (Sweden)

    Peggy S Lai

    Full Text Available RATIONALE: Endotoxin is a near ubiquitous environmental exposure that that has been associated with both asthma and chronic obstructive pulmonary disease (COPD. These obstructive lung diseases have a complex pathophysiology, making them difficult to study comprehensively in the context of endotoxin. Genome-wide gene expression studies have been used to identify a molecular snapshot of the response to environmental exposures. Identification of differentially expressed genes shared across all published murine models of chronic inhaled endotoxin will provide insight into the biology underlying endotoxin-associated lung disease. METHODS: We identified three published murine models with gene expression profiling after repeated low-dose inhaled endotoxin. All array data from these experiments were re-analyzed, annotated consistently, and tested for shared genes found to be differentially expressed. Additional functional comparison was conducted by testing for significant enrichment of differentially expressed genes in known pathways. The importance of this gene signature in smoking-related lung disease was assessed using hierarchical clustering in an independent experiment where mice were exposed to endotoxin, smoke, and endotoxin plus smoke. RESULTS: A 101-gene signature was detected in three murine models, more than expected by chance. The three model systems exhibit additional similarity beyond shared genes when compared at the pathway level, with increasing enrichment of inflammatory pathways associated with longer duration of endotoxin exposure. Genes and pathways important in both asthma and COPD were shared across all endotoxin models. Mice exposed to endotoxin, smoke, and smoke plus endotoxin were accurately classified with the endotoxin gene signature. CONCLUSIONS: Despite the differences in laboratory, duration of exposure, and strain of mouse used in three experimental models of chronic inhaled endotoxin, surprising similarities in gene

  10. Comprehensive analysis of trihelix genes and their expression under biotic and abiotic stresses in Populus trichocarpa

    Science.gov (United States)

    Wang, Zhanchao; Liu, Quangang; Wang, Hanzeng; Zhang, Haizhen; Xu, Xuemei; Li, Chenghao; Yang, Chuanping

    2016-01-01

    Trihelix genes play important roles in plant growth and development and responses to biotic and abiotic stresses. Here, we identified 56 full-length trihelix genes in Populus trichocarpa and classified them into five groups. Most genes within a given group had similar gene structures and conserved motifs. The trihelix genes were unequally distributed across 19 different linkage groups. Fifteen paralogous pairs were identified, 14 of which have undergone segmental duplication events. Promoter cis-element analysis indicated that most trihelix genes contain stress- or phytohormone-related cis-elements. The expression profiles of the trihelix genes suggest that they are primarily expressed in leaves and roots. Quantitative real-time reverse transcription polymerase chain reaction analysis indicated that members of the trihelix gene family are significantly induced in response to osmotic, abscisic acid, salicylic acid, methyl jasmonate and pathogen infection. PtrGT10 was identified as a target gene of miR172d, which is involved in the osmotic response. Repression of PtrGT10 could increase reactive oxygen species scavenging ability and decrease cell death. This study provides novel insights into the phylogenetic relationships and functions of the P. trichocarpa trihelix genes, which will aid future functional studies investigating the divergent roles of trihelix genes belonging to other species. PMID:27782188

  11. Gene expression during fruit ripening in avocado.

    Science.gov (United States)

    Christoffersen, R E; Warm, E; Laties, G G

    1982-06-01

    The poly(A) (+)RNA populations from avocado fruit (Persea americana Mill cv. Hass) at four stages of ripening were isolated by two cycles of oligo-dT-cellulose chromatography and examined by invitro translation, using the rabbit reticulocyte lysate system, followed by two-dimensional gel electrophoresis (isoelectric focusing followed by sodium dodecyl sulfate polyacrylamide gel electrophoresis) of the resulting translation products. Three mRNAs increased dramatically with the climacteric rise in respiration and ethylene production. The molecular weights of the corresponding translation products from the ripening-related mRNAs are 80,000, 36,000, and 16,500. These results indicate that ripening may be linked to the expression of specific genes.

  12. Evolution of Gene Expression Balance Among Homeologs of Natural Polyploids

    Directory of Open Access Journals (Sweden)

    Jasdeep S. Mutti

    2017-04-01

    Full Text Available Polyploidy is a major evolutionary process in eukaryotes, yet the expression balance of homeologs in natural polyploids is largely unknown. To study this expression balance, the expression patterns of 2180 structurally well-characterized genes of wheat were studied, of which 813 had the expected three copies and 375 had less than three. Copy numbers of the remaining 992 ranged from 4 to 14, including homeologs, orthologs, and paralogs. Of the genes with three structural copies corresponding to homeologs, 55% expressed from all three, 38% from two, and the remaining 7% expressed from only one of the three copies. Homeologs of 76–87% of the genes showed differential expression patterns in different tissues, thus have evolved different gene expression controls, possibly resulting in novel functions. Homeologs of 55% of the genes showed tissue-specific expression, with the largest percentage (14% in the anthers and the smallest (7% in the pistils. The highest number (1.72/3 of homeologs/gene expression was in the roots and the lowest (1.03/3 in the anthers. As the expression of homeologs changed with changes in structural copy number, about 30% of the genes showed dosage dependence. Chromosomal location also impacted expression pattern as a significantly higher proportion of genes in the proximal regions showed expression from all three copies compared to that present in the distal regions.

  13. Evolution of Gene Expression Balance Among Homeologs of Natural Polyploids.

    Science.gov (United States)

    Mutti, Jasdeep S; Bhullar, Ramanjot K; Gill, Kulvinder S

    2017-04-03

    Polyploidy is a major evolutionary process in eukaryotes, yet the expression balance of homeologs in natural polyploids is largely unknown. To study this expression balance, the expression patterns of 2180 structurally well-characterized genes of wheat were studied, of which 813 had the expected three copies and 375 had less than three. Copy numbers of the remaining 992 ranged from 4 to 14, including homeologs, orthologs, and paralogs. Of the genes with three structural copies corresponding to homeologs, 55% expressed from all three, 38% from two, and the remaining 7% expressed from only one of the three copies. Homeologs of 76-87% of the genes showed differential expression patterns in different tissues, thus have evolved different gene expression controls, possibly resulting in novel functions. Homeologs of 55% of the genes showed tissue-specific expression, with the largest percentage (14%) in the anthers and the smallest (7%) in the pistils. The highest number (1.72/3) of homeologs/gene expression was in the roots and the lowest (1.03/3) in the anthers. As the expression of homeologs changed with changes in structural copy number, about 30% of the genes showed dosage dependence. Chromosomal location also impacted expression pattern as a significantly higher proportion of genes in the proximal regions showed expression from all three copies compared to that present in the distal regions.

  14. Dissecting specific and global transcriptional regulation of bacterial gene expression

    NARCIS (Netherlands)

    Gerosa, Luca; Kochanowski, Karl; Heinemann, Matthias; Sauer, Uwe

    2013-01-01

    Gene expression is regulated by specific transcriptional circuits but also by the global expression machinery as a function of growth. Simultaneous specific and global regulation thus constitutes an additional-but often neglected-layer of complexity in gene expression. Here, we develop an experiment

  15. Phenotypic plasticity and divergence in gene expression.

    Science.gov (United States)

    Healy, Timothy M; Schulte, Patricia M

    2015-07-01

    The extent to which phenotypic plasticity, or the ability of a single genotype to produce different phenotypes in different environments, impedes or promotes genetic divergence has been a matter of debate within evolutionary biology for many decades (see, for example, Ghalambor et al. ; Pfennig et al. ). Similarly, the role of evolution in shaping phenotypic plasticity remains poorly understood (Pigliucci ). In this issue of Molecular Ecology, Dayan et al. () provide empirical data relevant to these questions by assessing the extent of plasticity and divergence in the expression levels of 2272 genes in muscle tissue from killifish (genus Fundulus) exposed to different temperatures. F. heteroclitus (Fig. A) and F. grandis are minnows that inhabit estuarine marshes (Fig. B) along the coasts of the Atlantic Ocean and Gulf of Mexico in North America. These habitats undergo large variations in temperature both daily and seasonally, and these fish are known to demonstrate substantial phenotypic plasticity in response to temperature change (e.g. Fangue et al. ). Furthermore, the range of F. heteroclitus spans a large latitudinal gradient of temperatures, such that northern populations experience temperatures that are on average ~10°C colder than do southern populations (Schulte ). By comparing gene expression patterns between populations of these fish from different thermal habitats held in the laboratory at three different temperatures, Dayan et al. () address two important questions regarding the interacting effects of plasticity and evolution: (i) How does phenotypic plasticity affect adaptive divergence? and (ii) How does adaptive divergence affect plasticity?

  16. Expression regulation of design process gene in product design

    DEFF Research Database (Denmark)

    Fang, Lusheng; Li, Bo; Tong, Shurong

    2011-01-01

    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......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...... 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. SVM-T-RFE: a novel gene selection algorithm for identifying metastasis-related genes in colorectal cancer using gene expression profiles.

    Science.gov (United States)

    Li, Xiaobo; Peng, Sihua; Chen, Jian; Lü, Bingjian; Zhang, Honghe; Lai, Maode

    2012-03-09

    Although metastasis is the principal cause of death cause for colorectal cancer (CRC) patients, the molecular mechanisms underlying CRC metastasis are still not fully understood. In an attempt to identify metastasis-related genes in CRC, we obtained gene expression profiles of 55 early stage primary CRCs, 56 late stage primary CRCs, and 34 metastatic CRCs from the expression project in Oncology (http://www.intgen.org/expo/). We developed a novel gene selection algorithm (SVM-T-RFE), which extends support vector machine recursive feature elimination (SVM-RFE) algorithm by incorporating T-statistic. We achieved highest classification accuracy (100%) with smaller gene subsets (10 and 6, respectively), when classifying between early and late stage primary CRCs, as well as between metastatic CRCs and late stage primary CRCs. We also compared the performance of SVM-T-RFE and SVM-RFE gene selection algorithms on another large-scale CRC dataset and the five public microarray datasets. SVM-T-RFE bestowed SVM-RFE algorithm in identifying more differentially expressed genes, and achieving highest prediction accuracy using equal or smaller number of selected genes. A fraction of selected genes have been reported to be associated with CRC development or metastasis.

  18. Monoallelic expression of the human FOXP2 speech gene.

    Science.gov (United States)

    Adegbola, Abidemi A; Cox, Gerald F; Bradshaw, Elizabeth M; Hafler, David A; Gimelbrant, Alexander; Chess, Andrew

    2015-06-02

    The recent descriptions of widespread random monoallelic expression (RMAE) of genes distributed throughout the autosomal genome indicate that there are more genes subject to RMAE on autosomes than the number of genes on the X chromosome where X-inactivation dictates RMAE of X-linked genes. Several of the autosomal genes that undergo RMAE have independently been implicated in human Mendelian disorders. Thus, parsing the relationship between allele-specific expression of these genes and disease is of interest. Mutations in the human forkhead box P2 gene, FOXP2, cause developmental verbal dyspraxia with profound speech and language deficits. Here, we show that the human FOXP2 gene undergoes RMAE. Studying an individual with developmental verbal dyspraxia, we identify a deletion 3 Mb away from the FOXP2 gene, which impacts FOXP2 gene expression in cis. Together these data suggest the intriguing possibility that RMAE impacts the haploinsufficiency phenotypes observed for FOXP2 mutations.

  19. Individual variation of adipose gene expression and identification of covariated genes by cDNA microarrays

    NARCIS (Netherlands)

    Boeuf, S.; Keijer, J.; Franssen-Hal, van N.L.W.; Klaus, S.

    2002-01-01

    Gene expression profiling through the application of microarrays provides comprehensive assessment of gene expression levels in a given tissue or cell population, as well as information on changes of gene expression in altered physiological or pathological situations. Microarrays are particularly su

  20. Modulation of R-gene expression across environments.

    Science.gov (United States)

    MacQueen, Alice; Bergelson, Joy

    2016-03-01

    Some environments are more conducive to pathogen growth than others, and, as a consequence, plants might be expected to invest more in resistance when pathogen growth is favored. Resistance (R-) genes in Arabidopsis thaliana have unusually extensive variation in basal expression when comparing the same R-gene among accessions collected from different environments. R-gene expression variation was characterized to explore whether R-gene expression is up-regulated in environments favoring pathogen proliferation and down-regulated when risks of infection are low; down-regulation would follow if costs of R-gene expression negatively impact plant fitness in the absence of disease. Quantitative reverse transcription-PCR was used to quantify the expression of 13 R-gene loci in plants grown in eight environmental conditions for each of 12 A. thaliana accessions, and large effects of the environment on R-gene expression were found. Surprisingly, almost every change in the environment--be it a change in biotic or abiotic conditions--led to an increase in R-gene expression, a response that was distinct from the average transcriptome response and from that of other stress response genes. These changes in expression are functional in that environmental change prior to infection affected levels of specific disease resistance to isolates of Pseudomonas syringae. In addition, there are strong latitudinal clines in basal R-gene expression and clines in R-gene expression plasticity correlated with drought and high temperatures. These results suggest that variation in R-gene expression across environments may be shaped by natural selection to reduce fitness costs of R-gene expression in permissive or predictable environments.

  1. Differential expression of genes during aflatoxin B1-induced hepatocarcinogenesis in tree shrews

    Institute of Scientific and Technical Information of China (English)

    Yuan Li; Dan Luo; Hui-Fen Yue; Li-Sheng Zhang; Jian-Ren Gu; Da-Fang Wan; Jian-Jia Su; Ji Cao; Chao Ou; Xiao-Kun Qiu; Ke-Chen Ban; Chun Yang; Liu-Liang Qin

    2004-01-01

    AIM: Through exploring the regulation of gene expression during hepatocarcinogenesis induced by aflatoxin B1 (AFB1),to find out the responsible genes for hepatocellular carcinoma (HCC) and to further understand the underlying molecular mechanism.METHODS: Tree shrews ( 7upaia belangeri chinensis)were treated with or without AFB1 for about 90 weeks. Liver biopsies were performed regularly during the animal experiment. Eight shares of total RNA were respectively isolated from 2 HCC tissues, 2 HCC-surrounding noncancerous liver tissues, 2 biopsied tissues at the early stage (30th week) of the experiment from the same animals as above, 1 mixed sample of three liver tissues biopsied at the beginning (0th week) of the experiment, and another 1 mixed sample of two liver tissues from the untreated control animals biopsied at the 90th week of the experiment. The samples were then tested with the method of AtlasTM cDNA microarray assay. The levels of gene expression in these tissues taken at different time points during hepatocarcinogenesis were compared.RESULTS: The profiles of differently expressed genes were quite different in different ways of comparison. At the same period of hepatocarcinogenesis, the genes in the same function group usually had the same tendency for up- or down-regulation. Among the checked 588 genes that were known to be related to human cancer, 89 genes (15.1%) were recognized as "important genes" because they showed frequent changes in different ways of comparison. The differentially expressed genes during hepatocarcinogenesis could be classified into four categories: genes up-regulated in HCC tissue, genes with similar expressing levels in both HCC and HCC-surrounding liver tissues which were higher than that in the tissues prior to the development of HCC,genes down-regulated in HCC tissue, and genes up-regulated prior to the development of HCC but down-regulated after the development of HCC.CONCLUSION: A considerable number of genes could change

  2. Radiolabeled PNAs for imaging gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Wickstrom, Eric; Sauter, Edward; Tian, Xianben; Rao, Sampath; Quin, Weyng; Thakur, Mathew [Thomas Jefferson Univ., PA (United States)

    2002-09-01

    Scintigraphic imaging of gene expression in vivo by non-invasive means could precisely direct physicians to appropriate intervention at the onset of disease and could contribute extensively to the management of patients. However no method is currently available to image specific over expressed oncogene mRNAs in vivo by scintigraphic imaging. Nevertheless, we have observed that Tc 99 m peptides can delineate tumors, and that PNA-peptides are specific for receptors on malignant cells and are taken up specifically and concentrated in nuclei. We hypothesize that antisense Tc 99 m PNA peptides will be taken up by human breast cancer cells, hybridize to complementary mRNA targets, and permit imaging of oncogene mRNAs in human breast cancer xenografts in a mouse model, providing a proof-of-principle for non-invasive detection of precancerous and invasive breast cancer. Oncogenes cyclin D1, erB-2, c-MYC and tumor suppressor p53 will be probed. If successful, this technique will be useful for diagnostic imaging of other solid tumors as well. (author)

  3. Screening and expression of genes from metagenomes.

    Science.gov (United States)

    Leis, Benedikt; Angelov, Angel; Liebl, Wolfgang

    2013-01-01

    Microorganisms are the most abundant and widely spread organisms on earth. They colonize a huge variety of natural and anthropogenic environments, including very specialized ecological niches and even extreme habitats, which are made possible by the immense metabolic diversity and genetic adaptability of microbes. As most of the organisms from environmental samples defy cultivation, cultivation-independent metagenomics approaches have been applied since more than one decade to access and characterize the phylogenetic diversity in microbial communities as well as their metabolic potential and ecological functions. Thereby, metagenomics has fully emerged as an own scientific field for mining new biocatalysts for many industrially relevant processes in biotechnology and pharmaceutics. This review summarizes common metagenomic approaches ranging from sampling, isolation of nucleic acids, construction of metagenomic libraries and their evaluation. Sequence-based screenings implement next-generation sequencing platforms, microarrays or PCR-based methods, while function-based analysis covers heterologous expression of metagenomic libraries in diverse screening setups. Major constraints and advantages of each strategy are described. The importance of alternative host-vector systems is discussed, and in order to underline the role of phylogenetic and physiological distance from the gene donor and the expression host employed, a case study is presented that describes the screening of a genomic library from an extreme thermophilic bacterium in both Escherichia coli and Thermus thermophilus. Metatranscriptomics, metaproteomics and single-cell-based methods are expected to complement metagenomic screening efforts to identify novel biocatalysts from environmental samples.

  4. Integrated analysis of gene expression by association rules discovery

    Directory of Open Access Journals (Sweden)

    Carazo Jose M

    2006-02-01

    Full Text Available Abstract Background Microarray technology is generating huge amounts of data about the expression level of thousands of genes, or even whole genomes, across different experimental conditions. To extract biological knowledge, and to fully understand such datasets, it is essential to include external biological information about genes and gene products to the analysis of expression data. However, most of the current approaches to analyze microarray datasets are mainly focused on the analysis of experimental data, and external biological information is incorporated as a posterior process. Results In this study we present a method for the integrative analysis of microarray data based on the Association Rules Discovery data mining technique. The approach integrates gene annotations and expression data to discover intrinsic associations among both data sources based on co-occurrence patterns. We applied the proposed methodology to the analysis of gene expression datasets in which genes were annotated with metabolic pathways, transcriptional regulators and Gene Ontology categories. Automatically extracted associations revealed significant relationships among these gene attributes and expression patterns, where many of them are clearly supported by recently reported work. Conclusion The integration of external biological information and gene expression data can provide insights about the biological processes associated to gene expression programs. In this paper we show that the proposed methodology is able to integrate multiple gene annotations and expression data in the same analytic framework and extract meaningful associations among heterogeneous sources of data. An implementation of the method is included in the Engene software package.

  5. 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...

  6. CDX2 gene expression in acute lymphoblastic leukemia

    Directory of Open Access Journals (Sweden)

    Hanaa H. Arnaoaut

    2014-06-01

    Full Text Available 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.

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

    Directory of Open Access Journals (Sweden)

    Wong YC

    2004-10-01

    Full Text Available Abstract Background 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. Method 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. Results 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

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

    Directory of Open Access Journals (Sweden)

    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.

  9. Molecular characterization and expression analysis of Triticum aestivum squamosa-promoter binding protein-box genes involved in ear development

    Institute of Scientific and Technical Information of China (English)

    Bin Zhang; a Xia Liu; a Guangyao Zhao; Xinguo Mao; Ang Li; Ruilian Jing

    2014-01-01

    Wheat (Triticum aestivum L.) is one of the most important crops in the world. Squamosa-promoter binding protein (SBP)-box genes play a critical role in regulating flower and fruit development. In this study, 10 novel SBP-box genes (TaSPL genes) were isolated from wheat ((Triticum aestivum L.) cultivar Yanzhan 4110). Phylogenetic analysis classified the TaSPL genes into five groups (G1-G5). The motif combinations and expression patterns of the TaSPL genes varied among the five groups with each having own distinctive characteristics: TaSPL20/21 in G1 and TaSPL17 in G2 mainly expressed in the shoot apical meristem and the young ear, and their expression levels responded to development of the ear; TaSPL6/15 belonging to G3 were upregulated and TaSPL1/23 in G4 were downregulated during grain development; the gene in G5 (TaSPL3) expressed constitutively. Thus, the consistency of the phylogenetic analysis, motif compositions, and expression patterns of the TaSPL genes revealed specific gene structures and functions. On the other hand, the diverse gene structures and different expression patterns suggested that wheat SBP-box genes have a wide range of functions. The results also suggest a potential role for wheat SBP-box genes in ear development. This study provides a significant beginning of functional analysis of SBP-box genes in wheat.

  10. Fully Bayesian mixture model for differential gene expression: simulations and model checks.

    Science.gov (United States)

    Lewin, Alex; Bochkina, Natalia; Richardson, Sylvia

    2007-01-01

    We present a Bayesian hierarchical model for detecting differentially expressed genes using a mixture prior on the parameters representing differential effects. We formulate an easily interpretable 3-component mixture to classify genes as over-expressed, under-expressed and non-differentially expressed, and model gene variances as exchangeable to allow for variability between genes. We show how the proportion of differentially expressed genes, and the mixture parameters, can be estimated in a fully Bayesian way, extending previous approaches where this proportion was fixed and empirically estimated. Good estimates of the false discovery rates are also obtained. Different parametric families for the mixture components can lead to quite different classifications of genes for a given data set. Using Affymetrix data from a knock out and wildtype mice experiment, we show how predictive model checks can be used to guide the choice between possible mixture priors. These checks show that extending the mixture model to allow extra variability around zero instead of the usual point mass null fits the data better. A software package for R is available.

  11. Knowledge-based analysis of microarray gene expression data by using support vector machines

    Energy Technology Data Exchange (ETDEWEB)

    William Grundy; Manuel Ares, Jr.; David Haussler

    2001-06-18

    The authors introduce a method of functionally classifying genes by using gene expression data from DNA microarray hybridization experiments. The method is based on the theory of support vector machines (SVMs). SVMs are considered a supervised computer learning method because they exploit prior knowledge of gene function to identify unknown genes of similar function from expression data. SVMs avoid several problems associated with unsupervised clustering methods, such as hierarchical clustering and self-organizing maps. SVMs have many mathematical features that make them attractive for gene expression analysis, including their flexibility in choosing a similarity function, sparseness of solution when dealing with large data sets, the ability to handle large feature spaces, and the ability to identify outliers. They test several SVMs that use different similarity metrics, as well as some other supervised learning methods, and find that the SVMs best identify sets of genes with a common function using expression data. Finally, they use SVMs to predict functional roles for uncharacterized yeast ORFs based on their expression data.

  12. 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

  13. Serial Analysis of Gene Expression: Applications in Human Studies

    OpenAIRE

    2004-01-01

    Serial analysis of gene expression (SAGE) is a powerful tool, which provides quantitative and comprehensive expression profile of genes in a given cell population. It works by isolating short fragments of genetic information from the expressed genes that are present in the cell being studied. These short sequences, called SAGE tags, are linked together for efficient sequencing. The frequency of each SAGE tag in the cloned multimers directly reflects the transcript abundance. Therefore, SAGE r...

  14. Identification of differentially expressed genes under drought stress in perennial ryegrass.

    Science.gov (United States)

    Liu, Shuwei; Jiang, Yiwei

    2010-08-01

    Perennial ryegrass (Lolium perenne L.) is a widely used cool-season forage and turf grass species. Drought stress can significantly affect the growth and development of grass plants. Identification of genes involved in drought tolerance facilitates genetic improvement of perennial ryegrass. A forward and a reverse cDNA library were constructed in drought-tolerant (PI 440474) and drought-susceptible (PI 204085) accessions by using suppression subtractive hybridization (SSH). A BLAST search revealed that 95 of 256 expressed sequence tags (ESTs) obtained from the two libraries showed significant sequence homologies to genes with known functions. They were classified into different putative functional groups including amino acid metabolism, lipid metabolism, carbohydrate metabolism, transcription, protein synthesis and destination, energy, photosynthesis, signal transduction, cellular transport and detoxification. Among them, 50 ESTs were from forward library (the drought tolerant over the susceptible accession). The expression patterns (reverse transcriptase polymerase chain reaction) of the selected genes encoding mitogen-activated protein kinase, superoxide dismutase and glutathione peroxidase (GPX) in additional accessions contrasting in drought tolerance were generally consistent with patterns of differentially expressed genes identified through SSH. The GPX fragment had a high degree of nucleotide diversity (pi = 0.0251) in the selected perennial ryegrass accessions. The results suggest that differentially expressed genes between drought tolerant and susceptible accessions may play an important role in the drought tolerance of perennial ryegrass. They can be used as candidate genes in examining nucleotide polymorphisms and conducting the association analysis of genes with drought tolerance.

  15. Expression of human skin-specific genes defined by transcriptomics and antibody-based profiling.

    Science.gov (United States)

    Edqvist, Per-Henrik D; Fagerberg, Linn; Hallström, Björn M; Danielsson, Angelika; Edlund, Karolina; Uhlén, Mathias; Pontén, Fredrik

    2015-02-01

    To increase our understanding of skin, it is important to define the molecular constituents of the cell types and epidermal layers that signify normal skin. We have combined a genome-wide transcriptomics analysis, using deep sequencing of mRNA from skin biopsies, with immunohistochemistry-based protein profiling to characterize the landscape of gene and protein expression in normal human skin. The transcriptomics and protein expression data of skin were compared to 26 (RNA) and 44 (protein) other normal tissue types. All 20,050 putative protein-coding genes were classified into categories based on patterns of expression. We found that 417 genes showed elevated expression in skin, with 106 genes expressed at least five-fold higher than that in other tissues. The 106 genes categorized as skin enriched encoded for well-known proteins involved in epidermal differentiation and proteins with unknown functions and expression patterns in skin, including the C1orf68 protein, which showed the highest relative enrichment in skin. In conclusion, we have applied a genome-wide analysis to identify the human skin-specific proteome and map the precise localization of the corresponding proteins in different compartments of the skin, to facilitate further functional studies to explore the molecular repertoire of normal skin and to identify biomarkers related to various skin diseases.

  16. 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.

  17. Differential expression of genes during aflatoxin B1-induced hepatocarcinogenesis in tree shrews

    Science.gov (United States)

    Li, Yuan; Wan, Da-Fang; Su, Jian-Jia; Cao, Ji; Ou, Chao; Qiu, Xiao-Kun; Ban, Ke-Chen; Yang, Chun; Qin, Liu-Liang; Luo, Dan; Yue, Hui-Fen; Zhang, Li-Sheng; Gu, Jian-Ren

    2004-01-01

    AIM: Through exploring the regulation of gene expression during hepatocarcinogenesis induced by aflatoxin B1 (AFB1), to find out the responsible genes for hepatocellular carcinoma (HCC) and to further understand the underlying molecular mechanism. METHODS: Tree shrews (Tupaia belangeri chinensis) were treated with or without AFB1 for about 90 weeks. Liver biopsies were performed regularly during the animal experiment. Eight shares of total RNA were respectively isolated from 2 HCC tissues, 2 HCC-surrounding non-cancerous liver tissues, 2 biopsied tissues at the early stage (30th week) of the experiment from the same animals as above, 1 mixed sample of three liver tissues biopsied at the beginning (0th week) of the experiment, and another 1 mixed sample of two liver tissues from the untreated control animals biopsied at the 90th week of the experiment. The samples were then tested with the method of AtlasTM cDNA microarray assay. The levels of gene expression in these tissues taken at different time points during hepatocarcinogenesis were compared. RESULTS: The profiles of differently expressed genes were quite different in different ways of comparison. At the same period of hepatocarcinogenesis, the genes in the same function group usually had the same tendency for up- or down-regulation. Among the checked 588 genes that were known to be related to human cancer, 89 genes (15.1%) were recognized as “important genes” because they showed frequent changes in different ways of comparison. The differentially expressed genes during hepatocarcinogenesis could be classified into four categories: genes up-regulated in HCC tissue, genes with similar expressing levels in both HCC and HCC-surrounding liver tissues which were higher than that in the tissues prior to the development of HCC, genes down-regulated in HCC tissue, and genes up-regulated prior to the development of HCC but down-regulated after the development of HCC. CONCLUSION: A considerable number of genes could

  18. Differential Expression of Salinity Resistance Gene on Cotton

    Institute of Scientific and Technical Information of China (English)

    YE Wu-wei; YU Shu-xun

    2008-01-01

    @@ Salinity resistance and differential gene expression associated with salinity in cotton germplasm were studied,because of the large scale area of salinity in China,and its significant negative effects on the cotton production.The salinityresisted genes and their differential expression were studied under the stress of NaCI on cotton.There were found,under the NaCI stress,1644 genes differentially expressed from the salinity-sensitive cotton and only 817 genes differentially expressed from the salinityresisted cotton.

  19. Identification of the differential expressive tumor associated genes in rectal cancers by cDNA microarray

    Institute of Scientific and Technical Information of China (English)

    Xue-Qin Gao; Jin-Xiang Han; Zhong-Fa Xu; Wei-Dong Zhang; Hua-Ning Zhang; Hai-Yan Huang

    2007-01-01

    AIM: To identify tumor associated genes of rectal cancer and to probe the application possibility of gene expression profiles for the classification of tumors.METHODS: Rectal cancer tissues and their paired normal mucosa were obtained from patients undergoing surgical resection of rectal cancer. Total RNA was extracted using Trizol reagents. First strand cDNA synthesis was indirectly labeled with aminoallyl-dUTP and coupled with Cy3 or Cy5 dye NHS mono-functional ester. After normalization to total spots, the genes which background subtracted intensity did not exceed 2 SD above the mean blank were excluded. The data were then sorted to obtain genes differentially expressed by≥ 2 fold up or down in at least 5 of the 21 patients.RESULTS: In the 21 rectal cancer patients, 23 genes were up-regulated in at least 5 samples and 15 genes were down-regulated in at least 5 patients. Hierachical cluster analysis classified the patients into two groups according to the clinicopathological stage, with one group being all above stage Ⅱ and one group all below stage Ⅱ.CONCLUSION: The up-regulated genes and downregulated genes may be molecular markers of rectal cancer. The expression profiles can be used for classification of rectal cancer.

  20. Evidence for mitochondrial genetic control of autosomal gene expression.

    Science.gov (United States)

    Kassam, Irfahan; Qi, Tuan; Lloyd-Jones, Luke; Holloway, Alexander; Jan Bonder, Marc; Henders, Anjali K; Martin, Nicholas G; Powell, Joseph E; Franke, Lude; Montgomery, Grant W; Visscher, Peter M; McRae, Allan F

    2016-10-18

    The mitochondrial and nuclear genomes coordinate and co-evolve in eukaryotes in order to adapt to environmental changes. Variation in the mitochondrial genome is capable of affecting expression of genes on the nuclear genome. Sex-specific mitochondrial genetic control of gene expression has been demonstrated in Drosophila melanogaster, where males were found to drive most of the total variation in gene expression. This has potential implications for male-related health and disease resulting from variation in mtDNA solely inherited from the mother. We used a family-based study comprised of 47,323 gene expression probes and 78 mitochondrial SNPs (mtSNPs) from n = 846 individuals to examine the extent of mitochondrial genetic control of gene expression in humans. This identified 15 significant probe-mtSNP associations (P[Formula: see text]) corresponding to 5 unique genes on the mitochondrial and nuclear genomes, with three of these genes corresponding to mitochondrial genetic control of gene expression in the nuclear genome. The associated mtSNPs for three genes (one cis and two trans associations) were replicated (P expression in any of these five probes. Sex-specific effects were examined by applying our analysis to males and females separately and testing for differences in effect size. The MEST gene was identified as having the most significantly different effect sizes across the sexes (P [Formula: see text]). MEST was similarly expressed in males and females with the G allele; however, males with the C allele are highly expressed for MEST, while females show no expression of the gene. This study provides evidence for the mitochondrial genetic control of expression of several genes in humans, with little evidence found for sex-specific effects.

  1. Quantitative modeling of a gene's expression from its intergenic sequence.

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    Md Abul Hassan Samee

    2014-03-01

    Full Text Available Modeling a gene's expression from its intergenic locus and trans-regulatory context is a fundamental goal in computational biology. Owing to the distributed nature of cis-regulatory information and the poorly understood mechanisms that integrate such information, gene locus modeling is a more challenging task than modeling individual enhancers. Here we report the first quantitative model of a gene's expression pattern as a function of its locus. We model the expression readout of a locus in two tiers: 1 combinatorial regulation by transcription factors bound to each enhancer is predicted by a thermodynamics-based model and 2 independent contributions from multiple enhancers are linearly combined to fit the gene expression pattern. The model does not require any prior knowledge about enhancers contributing toward a gene's expression. We demonstrate that the model captures the complex multi-domain expression patterns of anterior-posterior patterning genes in the early Drosophila embryo. Altogether, we model the expression patterns of 27 genes; these include several gap genes, pair-rule genes, and anterior, posterior, trunk, and terminal genes. We find that the model-selected enhancers for each gene overlap strongly with its experimentally characterized enhancers. Our findings also suggest the presence of sequence-segments in the locus that would contribute ectopic expression patterns and hence were "shut down" by the model. We applied our model to identify the transcription factors responsible for forming the stripe boundaries of the studied genes. The resulting network of regulatory interactions exhibits a high level of agreement with known regulatory influences on the target genes. Finally, we analyzed whether and why our assumption of enhancer independence was necessary for the genes we studied. We found a deterioration of expression when binding sites in one enhancer were allowed to influence the readout of another enhancer. Thus, interference

  2. Heterologous gene expression in filamentous fungi.

    Science.gov (United States)

    Su, Xiaoyun; Schmitz, George; Zhang, Meiling; Mackie, Roderick I; Cann, Isaac K O

    2012-01-01

    Filamentous fungi are critical to production of many commercial enzymes and organic compounds. Fungal-based systems have several advantages over bacterial-based systems for protein production because high-level secretion of enzymes is a common trait of their decomposer lifestyle. Furthermore, in the large-scale production of recombinant proteins of eukaryotic origin, the filamentous fungi become the vehicle of choice due to critical processes shared in gene expression with other eukaryotic organisms. The complexity and relative dearth of understanding of the physiology of filamentous fungi, compared to bacteria, have hindered rapid development of these organisms as highly efficient factories for the production of heterologous proteins. In this review, we highlight several of the known benefits and challenges in using filamentous fungi (particularly Aspergillus spp., Trichoderma reesei, and Neurospora crassa) for the production of proteins, especially heterologous, nonfungal enzymes. We review various techniques commonly employed in recombinant protein production in the filamentous fungi, including transformation methods, selection of gene regulatory elements such as promoters, protein secretion factors such as the signal peptide, and optimization of coding sequence. We provide insights into current models of host genomic defenses such as repeat-induced point mutation and quelling. Furthermore, we examine the regulatory effects of transcript sequences, including introns and untranslated regions, pre-mRNA (messenger RNA) processing, transcript transport, and mRNA stability. We anticipate that this review will become a resource for researchers who aim at advancing the use of these fascinating organisms as protein production factories, for both academic and industrial purposes, and also for scientists with general interest in the biology of the filamentous fungi. Copyright © 2012 Elsevier Inc. All rights reserved.

  3. Expressed genes in regenerating rat liver after partial hepatectomy

    Institute of Scientific and Technical Information of China (English)

    Cun-Shuan Xu; Salman Rahrnan; Jing-Bo Zhang; Cui-Fang Chang; Jin-Yun Yuan; Wen-Qiang Li; Hong-Peng Han; Ke-Jin Yang; Li-Feng Zhao; Yu-Chang Li; Hui-Yong Zhang

    2005-01-01

    AIM: To reveal the liver regeneration (LR) and its controlas well as the occurrence of liver disease and to study the gene expression profiles of 551 genes after partial hepatectomy (PH) in regenerating rat livers.METHODS: Five hundred and fifty-one expressed sequence tags screened by suppression subtractive hybridization were made into an in-house cDNA microarray, and the expressive genes and their expressive profiles in regenerating rat livers were analyzed by microarray and bioinformatics. RESULTS: Three hundred of the analyzed 551 genes were up- or downregulated more than twofolds at one or more time points during LR. Most of the genes were up- or downregulated 2-5 folds, but the highest reached 90 folds of the control. One hundred and thirty-nine of themshowed upregulation, 135 displayed downregulation, and up or down expression of 26 genes revealed a dependence on regenerating livers. The genes expressedin 24-h regenerating livers were much more than those in the others. Cluster analysis and generalization analysis showed that there were at least six distinct temporal patterns of gene expression in the regenerating livers, that is, genes were expressed in the immediate early phase, early phase, intermediate phase, early-late phase, late phase, terminal phase. CONCLUSION: In LR, the number of down-regulated genes was almost similar to that of the upregulated genes; the successively altered genes were more than the rapidly transient genes. The temporal patterns of gene expression were similar 2 and 4 h, 12 and 16 h, 48 and 96 h, 72 and 144 h after PH. Microarray combined with suppressive subtractive hybridization can effectively identify the genes related to LR.

  4. Faster-X Evolution of Gene Expression in Drosophila

    Science.gov (United States)

    Meisel, Richard P.; Malone, John H.; Clark, Andrew G.

    2012-01-01

    DNA sequences on X chromosomes often have a faster rate of evolution when compared to similar loci on the autosomes, and well articulated models provide reasons why the X-linked mode of inheritance may be responsible for the faster evolution of X-linked genes. We analyzed microarray and RNA–seq data collected from females and males of six Drosophila species and found that the expression levels of X-linked genes also diverge faster than autosomal gene expression, similar to the “faster-X” effect often observed in DNA sequence evolution. Faster-X evolution of gene expression was recently described in mammals, but it was limited to the evolutionary lineages shortly following the creation of the therian X chromosome. In contrast, we detect a faster-X effect along both deep lineages and those on the tips of the Drosophila phylogeny. In Drosophila males, the dosage compensation complex (DCC) binds the X chromosome, creating a unique chromatin environment that promotes the hyper-expression of X-linked genes. We find that DCC binding, chromatin environment, and breadth of expression are all predictive of the rate of gene expression evolution. In addition, estimates of the intraspecific genetic polymorphism underlying gene expression variation suggest that X-linked expression levels are not under relaxed selective constraints. We therefore hypothesize that the faster-X evolution of gene expression is the result of the adaptive fixation of beneficial mutations at X-linked loci that change expression level in cis. This adaptive faster-X evolution of gene expression is limited to genes that are narrowly expressed in a single tissue, suggesting that relaxed pleiotropic constraints permit a faster response to selection. Finally, we present a conceptional framework to explain faster-X expression evolution, and we use this framework to examine differences in the faster-X effect between Drosophila and mammals. PMID:23071459

  5. Effects of typical and atypical antipsychotic drugs on gene expression profiles in the liver of schizophrenia subjects

    Directory of Open Access Journals (Sweden)

    Song Jonathan

    2009-09-01

    Full Text Available Abstract Background Although much progress has been made on antipsychotic drug development, precise mechanisms behind the action of typical and atypical antipsychotics are poorly understood. Methods We performed genome-wide expression profiling to study effects of typical antipsychotics and atypical antipsychotics in the postmortem liver of schizophrenia patients using microarrays (Affymetrix U133 plus2.0. We classified the subjects into typical antipsychotics (n = 24 or atypical antipsychotics (n = 26 based on their medication history, and compared gene expression profiles with unaffected controls (n = 34. We further analyzed individual antipsychotic effects on gene expression by sub-classifying the subjects into four major antipsychotic groups including haloperidol, phenothiazines, olanzapine and risperidone. Results Typical antipsychotics affected genes associated with nuclear protein, stress responses and phosphorylation, whereas atypical antipsychotics affected genes associated with golgi/endoplasmic reticulum and cytoplasm transport. Comparison between typical antipsychotics and atypical antipsychotics further identified genes associated with lipid metabolism and mitochondrial function. Analyses on individual antipsychotics revealed a set of genes (151 transcripts, FDR adjusted p Conclusion Typical antipsychotics and atypical antipsychotics affect different genes and biological function in the liver. Typical antipsychotic phenothiazines exert robust effects on gene expression in the liver that may lead to liver toxicity. The genes found in the current study may benefit antipsychotic drug development with better therapeutic and side effect profiles.

  6. Genome-wide identification, characterization and expression profiling of LIM family genes in Solanum lycopersicum L.

    Science.gov (United States)

    Khatun, Khadiza; Robin, Arif Hasan Khan; Park, Jong-In; Ahmed, Nasar Uddin; Kim, Chang Kil; Lim, Ki-Byung; Kim, Min-Bae; Lee, Do-Jin; Nou, Ill Sup; Chung, Mi-Young

    2016-11-01

    LIM domain proteins, some of which have been shown to be actin binding proteins, are involved in various developmental activities and cellular processes in plants. To date, the molecular defense-related functions of LIM family genes have not been investigated in any solanaceous vegetable crop species. In this study, we identified 15 LIM family genes in tomato (Solanum lycopersicum L.) through genome-wide analysis and performed expression profiling in different organs of tomato, including fruits at six different developmental stages. We also performed expression profiling of selected tomato LIM genes in plants under ABA, drought, cold, NaCl and heat stress treatment. The encoded proteins of the 15 tomato LIM genes were classified into two main groups, i.e., proteins similar to cysteine-rich proteins and plant-specific DAR proteins, based on differences in functional domains and variability in their C-terminal regions. The DAR proteins contain a so far poorly characterized zinc-finger-like motif that we propose to call DAR-ZF. Six of the 15 LIM genes were expressed only in flowers, indicating that they play flower-specific roles in plants. The other nine genes were expressed in all organs and at various stages of fruit development. SlβLIM1b was expressed relatively highly at the later stage of fruit development, but three other genes, SlWLIM2a, SlDAR2 and SlDAR4, were expressed at the early stage of fruit development. Seven genes were induced by ABA, five by cold, seven by drought, eight by NaCl and seven by heat treatment respectively, indicating their possible roles in abiotic stress tolerance. Our results will be useful for functional analysis of LIM genes during fruit development in tomato plants under different abiotic stresses. Copyright © 2016. Published by Elsevier Masson SAS.

  7. 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.

  8. 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.

  9. An efficient rhythmic component expression and weighting synthesis strategy for classifying motor imagery EEG in a brain computer interface

    Science.gov (United States)

    Wang, Tao; He, Bin

    2004-03-01

    The recognition of mental states during motor imagery tasks is crucial for EEG-based brain computer interface research. We have developed a new algorithm by means of frequency decomposition and weighting synthesis strategy for recognizing imagined right- and left-hand movements. A frequency range from 5 to 25 Hz was divided into 20 band bins for each trial, and the corresponding envelopes of filtered EEG signals for each trial were extracted as a measure of instantaneous power at each frequency band. The dimensionality of the feature space was reduced from 200 (corresponding to 2 s) to 3 by down-sampling of envelopes of the feature signals, and subsequently applying principal component analysis. The linear discriminate analysis algorithm was then used to classify the features, due to its generalization capability. Each frequency band bin was weighted by a function determined according to the classification accuracy during the training process. The present classification algorithm was applied to a dataset of nine human subjects, and achieved a success rate of classification of 90% in training and 77% in testing. The present promising results suggest that the present classification algorithm can be used in initiating a general-purpose mental state recognition based on motor imagery tasks.

  10. Gene Expression Pattern of Signal Transduction in Chronic Myeloid Leukemia

    Institute of Scientific and Technical Information of China (English)

    LI Huiyu; JIE Shenghua; GUO Tiannan; HUANG Shi'ang

    2006-01-01

    To explore the transcriptional gene expression profiles of signaling pathway in Chronic myeloid leukemia (CML), a series of cDNA microarray chips were tested. The results showed that differentially expressed genes related to singal transduction in CML were screened out and the genes involved in Phosphoinositide 3-kinases (PI3K), Ras-MAPK (mitogen-activated protein kinase) and other signaling pathway genes simultaneously. The results also showed that most of these genes were up-expression genes , which suggested that signal transduction be overactivated in CML. Further analysis of these differentially expressed signal transduction genes will be helpful to understand the molecular mechanism of CML and find new targets of treatment.

  11. Gene expression profile is associated with chemoradiation resistance in rectal cancer.

    Science.gov (United States)

    Gantt, G A; Chen, Y; Dejulius, K; Mace, A G; Barnholtz-Sloan, J; Kalady, M F

    2014-01-01

    Patients with rectal cancer who achieve a complete pathological response after preoperative chemoradiation (CRT) have an improved oncological outcome. Identifying factors associated with a lack of response could help our understanding of the underlying biology of treatment resistance. This study aimed to develop a gene expression signature for CRT-resistant rectal cancer using high-throughput nucleotide microarrays. Pretreatment biopsies of rectal adenocarcinomas were prospectively collected and freshly frozen according to an institutional review board-approved protocol. Total tumour mRNA was extracted and gene expression levels were measured using microarrays. Patients underwent proctectomy after completing standard long-course CRT and the resected specimens were graded for treatment response. Gene expression profiles for nonresponders were compared with those of responders. Differentially expressed genes were analyzed for functional significance using the Ingenuity Pathway Analysis (IPA) software. Thirty-three patients treated between 2006 and 2009 were included. We derived 812-gene and 183-gene signatures separating nonresponders from responders. The classifiers were able to identify nonresponders with a sensitivity and specificity of 100% using the 812-gene signature, and sensitivity and specificity of 33% and 100% using the 183-gene signature. IPA canonical pathway analysis revealed a significant ratio of differentially expressed genes in the 'DNA double-strand break repair by homologous recombination' pathway. Certain rectal cancer gene profiles are associated with poor response to CRT. Alterations in the DNA double-strand break repair pathway could contribute to treatment resistance and provides an opportunity for further studies. Colorectal Disease © 2013 The Association of Coloproctology of Great Britain and Ireland.

  12. Xenoestrogenic gene expression: structural features of active polycyclic aromatic hydrocarbons.

    Science.gov (United States)

    Schultz, T Wayne; Sinks, Glendon D

    2002-04-01

    Estrogenicity was assessed using the Saccharomyces cerevisiae-based Lac-Z reporter assay and was reported as the logarithm of the inverse of the 50% molar beta-galactosidase activity (log[EC50(-1)]). In an effort to quantify the relationship between molecular structure of polycyclic aromatic hydrocarbons (PAHs) and estrogenic gene expression, a series of PAHs were evaluated. With noted exceptions, the results of these studies indicate that the initial two-dimensional structural warning for estrogenicity, the superpositioning of a hydroxylated aromatic system on the phenolic A-ring of 17-beta-estradiol, can be extended to the PAHs. This two-dimensional-alignment criterion correctly identified estrogenicity of 22 of the 29 PAHs evaluated. Moreover, the estrogenic potency of these compounds was directly related to the size of the hydrophobic backbone. The seven compounds classified incorrectly by this structural feature were either dihydroxylated naphthalenes or aromatic nitrogen-heterocyclic compounds; all such compounds were false positives. Results with dihydroxylated naphthalenes reveal derivatives that were nonestrogenic when superimposed on the phenolic A-ring of 17-beta-estradiol had the second hydroxyl group in the position of the C-ring or were catechol-like in structure. Structural alerts for nitrogen-heterocyclic compounds must take into account the position of the hydroxyl group and the in-ring nitrogen atom; compounds with the hydroxyl group and nitrogen atom involved with the same ring were observed to be nonactive.

  13. Social Regulation of Gene Expression in Threespine Sticklebacks.

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    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.

  14. Large Scale Gene Expression Meta-Analysis Reveals Tissue-Specific, Sex-Biased Gene Expression in Humans

    Science.gov (United States)

    Mayne, Benjamin T.; Bianco-Miotto, Tina; Buckberry, Sam; Breen, James; Clifton, Vicki; Shoubridge, Cheryl; Roberts, Claire T.

    2016-01-01

    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 analyzed 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.

  15. 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.

  16. 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.

  17. Regulating gene-expression by mechanical force

    Science.gov (United States)

    Visscher, Koen

    2008-10-01

    Initiation of transcription is an attractive target for controlling gene expression. Initiation typically involves binding of RNA polymerase to the DNA, followed by a rapid transition into a ``closed'' complex, and a subsequent transition into the ``open'' complex in which the DNA is locally melted. Nature makes good use of this target, for example in the form of repressor proteins that bind DNA and inhibit transcription. Here we will show that initiation of transcription is also dependent upon DNA tension and thus may be controlled by force alone, without the need for any accessory proteins. Using a three-bead assay in conjunction with optical tweezers we have shown that transient interactions of T7 RNA polymerase with the DNA promoter site shorten significantly, by up to a factor of ˜20, when DNA tension is increased. Experiments in the presence and absence of nucleotides have allowed us to conclude that force is likely to affect the rate constants into and/or out of the open complex, rather than the off-rate from the closed complex.

  18. Cell cycle gene expression under clinorotation

    Science.gov (United States)

    Artemenko, Olga

    2016-07-01

    Cyclins and cyclin-dependent kinase (CDK) are main regulators of the cell cycle of eukaryotes. It's assumes a significant change of their level in cells under microgravity conditions and by other physical factors actions. The clinorotation use enables to determine the influence of gravity on simulated events in the cell during the cell cycle - exit from the state of quiet stage and promotion presynthetic phase (G1) and DNA synthesis phase (S) of the cell cycle. For the clinorotation effect study on cell proliferation activity is the necessary studies of molecular mechanisms of cell cycle regulation and development of plants under altered gravity condition. The activity of cyclin D, which is responsible for the events of the cell cycle in presynthetic phase can be controlled by the action of endogenous as well as exogenous factors, but clinorotation is one of the factors that influence on genes expression that regulate the cell cycle.These data can be used as a model for further research of cyclin - CDK complex for study of molecular mechanisms regulation of growth and proliferation. In this investigation we tried to summarize and analyze known literature and own data we obtained relatively the main regulators of the cell cycle in altered gravity condition.

  19. Gene Expression Profiling in an in Vitro Model of Angiogenesis

    OpenAIRE

    Kahn, Jeanne; Mehraban, Fuad; Ingle, Gladys; Xin, Xiaohua; Bryant, Juliet E.; Vehar, Gordon; Schoenfeld, Jill; Grimaldi, Chrisopher J.; Peale, Franklin; Draksharapu, Aparna; Lewin, David A.; Gerritsen, Mary E.

    2000-01-01

    In the present study we have used a novel, comprehensive mRNA profiling technique (GeneCalling) for determining differential gene expression profiles of human endothelial cells undergoing differentiation into tubelike structures. One hundred fifteen cDNA fragments were identified and shown to represent 90 distinct genes. Although some of the genes identified have previously been implicated in angiogenesis, potential roles for many new genes, including OX-40, white protein homolog, KIAA0188, a...

  20. Expression Divergence of Tandemly Arrayed Genes in Human and Mouse

    Directory of Open Access Journals (Sweden)

    Valia Shoja

    2007-01-01

    Full Text Available Tandemly arrayed genes (TAGs account for about one third of the duplicated genes in eukaryotic genomes, yet there has not been any systematic study of their gene expression patterns. Taking advantage of recently published large-scale microarray data sets, we studied the expression divergence of 361 two-member TAGs in human and 212 two-member TAGs in mouse and examined the effect of sequence divergence, gene orientation, and chromosomal proximity on the divergence of TAG expression patterns. Our results show that there is a weak negative correlation between sequence divergence of TAG members and their expression similarity. There is also a weak negative correlation between chromosomal proximity of TAG members and their expression similarity. We did not detect any significant relationship between gene orientation and expression similarity. We also found that downstream TAG members do not show significantly narrower expression breadth than upstream members, contrary to what we predict based on TAG expression divergence hypothesis that we propose. Finally, we show that both chromosomal proximity and expression correlation in TAGs do not differ significantly from their neighboring non-TAG gene pairs, suggesting that tandem duplication is unlikely to be the cause for the higher-than-random expression association between neighboring genes on a chromosome in human and mouse.

  1. An ensemble classifier for eukaryotic protein subcellular location prediction using gene ontology categories and amino acid hydrophobicity.

    Directory of Open Access Journals (Sweden)

    Liqi Li

    Full Text Available With the rapid increase of protein sequences in the post-genomic age, it is challenging to develop accurate and automated methods for reliably and quickly predicting their subcellular localizations. Till now, many efforts have been tried, but most of which used only a single algorithm. In this paper, we proposed an ensemble classifier of KNN (k-nearest neighbor and SVM (support vector machine algorithms to predict the subcellular localization of eukaryotic proteins based on a voting system. The overall prediction accuracies by the one-versus-one strategy are 78.17%, 89.94% and 75.55% for three benchmark datasets of eukaryotic proteins. The improved prediction accuracies reveal that GO annotations and hydrophobicity of amino acids help to predict subcellular locations of eukaryotic proteins.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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

  4. Gene ordering in partitive clustering using microarray expressions.

    Science.gov (United States)

    Ray, Shubhra Sankar; Bandyopadhyay, Sanghamitra; Pal, Sankar K

    2007-08-01

    A central step in the analysis of gene expression data is the identification of groups of genes that exhibit similar expression patterns. Clustering and ordering the genes using gene expression data into homogeneous groups was shown to be useful in functional annotation, tissue classification, regulatory motif identification, and other applications. Although there is a rich literature on gene ordering in hierarchical clustering framework for gene expression analysis, there is no work addressing and evaluating the importance of gene ordering in partitive clustering framework, to the best knowledge of the authors. Outside the framework of hierarchical clustering, different gene ordering algorithms are applied on the whole data set, and the domain of partitive clustering is still unexplored with gene ordering approaches. A new hybrid method is proposed for ordering genes in each of the clusters obtained from partitive clustering solution, using microarray gene expressions.Two existing algorithms for optimally ordering cities in travelling salesman problem (TSP), namely, FRAG_GALK and Concorde, are hybridized individually with self organizing MAP to show the importance of gene ordering in partitive clustering framework. We validated our hybrid approach using yeast and fibroblast data and showed that our approach improves the result quality of partitive clustering solution, by identifying subclusters within big clusters, grouping functionally correlated genes within clusters, minimization of summation of gene expression distances, and the maximization of biological gene ordering using MIPS categorization. Moreover, the new hybrid approach, finds comparable or sometimes superior biological gene order in less computation time than those obtained by optimal leaf ordering in hierarchical clustering solution.

  5. Gene ordering in partitive clustering using microarray expressions

    Indian Academy of Sciences (India)

    Shubhra Sankar Ray; Sanghamitra Bandyopadhyay; Sankar K Pal

    2007-08-01

    A central step in the analysis of gene expression data is the identification of groups of genes that exhibit similar expression patterns. Clustering and ordering the genes using gene expression data into homogeneous groups was shown to be useful in functional annotation, tissue classification, regulatory motif identification, and other applications. Although there is a rich literature on gene ordering in hierarchical clustering framework for gene expression analysis, there is no work addressing and evaluating the importance of gene ordering in partitive clustering framework, to the best knowledge of the authors. Outside the framework of hierarchical clustering, different gene ordering algorithms are applied on the whole data set, and the domain of partitive clustering is still unexplored with gene ordering approaches. A new hybrid method is proposed for ordering genes in each of the clusters obtained from partitive clustering solution, using microarray gene expressions. Two existing algorithms for optimally ordering cities in travelling salesman problem (TSP), namely, FRAG_GALK and Concorde, are hybridized individually with self organizing MAP to show the importance of gene ordering in partitive clustering framework. We validated our hybrid approach using yeast and fibroblast data and showed that our approach improves the result quality of partitive clustering solution, by identifying subclusters within big clusters, grouping functionally correlated genes within clusters, minimization of summation of gene expression distances, and the maximization of biological gene ordering using MIPS categorization. Moreover, the new hybrid approach, finds comparable or sometimes superior biological gene order in less computation time than those obtained by optimal leaf ordering in hierarchical clustering solution.

  6. 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.

  7. Transgenic zebrafish recapitulating tbx16 gene early developmental expression.

    Directory of Open Access Journals (Sweden)

    Simon Wells

    Full Text Available We describe the creation of a transgenic zebrafish expressing GFP driven by a 7.5 kb promoter region of the tbx16 gene. This promoter segment is sufficient to recapitulate early embryonic expression of endogenous tbx16 in the presomitic mesoderm, the polster and, subsequently, in the hatching gland. Expression of GFP in the transgenic lines later in development diverges to some extent from endogenous tbx16 expression with the serendipitous result that one line expresses GFP specifically in commissural primary ascending (CoPA interneurons of the developing spinal cord. Using this line we demonstrate that the gene mafba (valentino is expressed in CoPA interneurons.

  8. Expression profiles for six zebrafish genes during gonadal sex differentiation

    Directory of Open Access Journals (Sweden)

    Rasmussen Lene J

    2008-06-01

    Full Text Available Abstract Background The mechanism of sex determination in zebrafish is largely unknown and neither sex chromosomes nor a sex-determining gene have been identified. This indicates that sex determination in zebrafish is mediated by genetic signals from autosomal genes. The aim of this study was to determine the precise timing of expression of six genes previously suggested to be associated with sex differentiation in zebrafish. The current study investigates the expression of all six genes in the same individual fish with extensive sampling dates during sex determination and -differentiation. Results In the present study, we have used quantitative real-time PCR to investigate the expression of ar, sox9a, dmrt1, fig alpha, cyp19a1a and cyp19a1b during the expected sex determination and gonadal sex differentiation period. The expression of the genes expected to be high in males (ar, sox9a and dmrt1a and high in females (fig alpha and cyp19a1a was segregated in two groups with more than 10 times difference in expression levels. All of the investigated genes showed peaks in expression levels during the time of sex determination and gonadal sex differentiation. Expression of all genes was investigated on cDNA from the same fish allowing comparison of the high and low expressers of genes that are expected to be highest expressed in either males or females. There were 78% high or low expressers of all three "male" genes (ar, sox9a and dmrt1 in the investigated period and 81% were high or low expressers of both "female" genes (fig alpha and cyp19a1a. When comparing all five genes with expected sex related expression 56% show expression expected for either male or female. Furthermore, the expression of all genes was investigated in different tissue of adult male and female zebrafish. Conclusion In zebrafish, the first significant peak in gene expression during the investigated period (2–40 dph was dmrt1 at 10 dph which indicates involvement of this gene

  9. 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.

  10. Transcriptional characteristics of gene expression in the midgut of domestic silkworms (Bombyx mori) exposed to phoxim.

    Science.gov (United States)

    Gu, Z Y; Sun, S S; Wang, Y H; Wang, B B; Xie, Y; Ma, L; Wang, J M; Shen, W D; Li, B

    2013-01-01

    Silkworm (Bombyx mori) is not only an economically important insect but also a model system for lepidoptera. As a vital organ of digestion and nutrient absorption, the midgut of insects also serves as the first physiological barrier to chemical pesticides. In this study, microarray was performed to profile the gene expression changes in the midgut of silkworms exposed to phoxim. After 24h of phoxim exposure (4.0μg/mL), 266 genes displayed at least 2.0-fold changes in expression levels. Among them, 192 genes were up-regulated, and 74 genes were down-regulated. The most significant changes were 14.88-fold up-regulation and 23.36-fold down-regulation. According to gene ontology annotation and pathway analysis, differentially expressed genes were mainly classified into different groups based on their potential involvements in detoxification, immunne response, stress response, energy metabolism and transport. Particularly, the transcription levels of detoxification-related genes were up-regulated, such as cytochrome P450s, esterases and glutathione-S-transferase (GST), indicating increased detoxification activity in the midgut. Our study provides new insights into the molecular mechanism of pesticide metabolism in the midgut of insects, which may promote the development of highly efficient insecticides.

  11. 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.

  12. Gene Expression Measurement Module (GEMM) - a fully automated, miniaturized instrument for measuring gene expression in space

    Science.gov (United States)

    Karouia, Fathi; Ricco, Antonio; Pohorille, Andrew; Peyvan, Kianoosh

    2012-07-01

    The capability to measure gene expression on board spacecrafts opens the doors to a large number of experiments on the influence of space environment on biological systems that will profoundly impact our ability to conduct safe and effective space travel, and might also shed light on terrestrial physiology or biological function and human disease and aging processes. Measurements of gene expression will help us to understand adaptation of terrestrial life to conditions beyond the planet of origin, identify deleterious effects of the space environment on a wide range of organisms from microbes to humans, develop effective countermeasures against these effects, determine metabolic basis of microbial pathogenicity and drug resistance, test our ability to sustain and grow in space organisms that can be used for life support and in situ resource utilization during long-duration space exploration, and monitor both the spacecraft environment and crew health. These and other applications hold significant potential for discoveries in space biology, biotechnology and medicine. Accordingly, supported by funding from the NASA Astrobiology Science and Technology Instrument Development Program, we are developing a fully automated, miniaturized, integrated fluidic system for small spacecraft capable of in-situ measuring microbial expression of thousands of genes from multiple samples. The instrument will be capable of (1) lysing bacterial cell walls, (2) extracting and purifying RNA released from cells, (3) hybridizing it on a microarray and (4) providing electrochemical readout, all in a microfluidics cartridge. The prototype under development is suitable for deployment on nanosatellite platforms developed by the NASA Small Spacecraft Office. The first target application is to cultivate and measure gene expression of the photosynthetic bacterium Synechococcus elongatus, i.e. a cyanobacterium known to exhibit remarkable metabolic diversity and resilience to adverse conditions

  13. Comparative study of leptin and leptin receptor gene expression in different swine breeds.

    Science.gov (United States)

    Georgescu, S E; Manea, M A; Dinescu, S; Costache, M

    2014-02-14

    Leptin is an important regulator of appetite, energy metabolism, and reproduction and is mainly synthesized in the adipocytes and then secreted into the bloodstream. The leptin receptor was classified as type I cytokine receptor due to its structural homology with IL-6 receptors and the signaling pathways in which they are both involved. The aim of our study is to comparatively assess the gene expression levels of leptin (lep) and leptin receptor (lepr) in different swine breeds specialized either in meat production (Duroc, Belgian Landrace, Large White, Synthetic Lines LS-345, and LSP-2000) or fat production (Mangalitsa) in order to correlate them with morphological and productivity characteristics. Additionally, lepr pattern of expression was evaluated comparatively between different tissue types in the Mangalitsa breed. Our results revealed high expression of the lep gene in Mangalitsa compared to those of all the other breeds, while for the lepr gene, average/medium levels were registered in Mangalitsa and increased pattern of expression was found in the synthetic lines LS-345 and LSP-2000. Regarding the comparative analysis of lepr gene expression in various tissues in the Mangalitsa breed, elevated levels were found in the liver and kidney, while the lowest expression was identified in the brain and muscles. Our results suggest that the Mangalitsa population exhibits leptin resistance, which might be correlated with atypical morpho-productive characteristics for this breed, such as below-average prolificacy and a strong tendency to accumulate fat.

  14. Gene Expression Profiles as Prognostic Marker in Women with Ovarian Cancer

    DEFF Research Database (Denmark)

    Jochumsen, Kirsten Marie; Tan, Qihua; Høgdall, EV;

    2009-01-01

    toward investigations for more individualized therapies and the use of gene expression profiles in the clinical practice. RNA from tumor tissue from 43 Danish patients with serous epithelial ovarian carcinoma (11 International Federation of Gynecology and Obstetrics [FIGO] stage I/II, 32 FIGO stage III......-term survivors (median overall survival of 32 months) from long-term survivors (median overall survival not yet reached after a median follow-up of 76 months) with a P value of 3.4 x 10 was found. The prognostic gene set was also able to distinguish short-term from long-term survival in patients with advanced......The purpose was to find a gene expression profile that could distinguish short-term from long-term survivors in our collection of serous epithelial ovarian carcinomas. Furthermore, it should be able to stratify in an external validation set. Such a classifier profile will take us a step forward...

  15. The Role of Multiple Transcription Factors In Archaeal Gene Expression

    Energy Technology Data Exchange (ETDEWEB)

    Charles J. Daniels

    2008-09-23

    Since the inception of this research program, the project has focused on two central questions: What is the relationship between the 'eukaryal-like' transcription machinery of archaeal cells and its counterparts in eukaryal cells? And, how does the archaeal cell control gene expression using its mosaic of eukaryal core transcription machinery and its bacterial-like transcription regulatory proteins? During the grant period we have addressed these questions using a variety of in vivo approaches and have sought to specifically define the roles of the multiple TATA binding protein (TBP) and TFIIB-like (TFB) proteins in controlling gene expression in Haloferax volcanii. H. volcanii was initially chosen as a model for the Archaea based on the availability of suitable genetic tools; however, later studies showed that all haloarchaea possessed multiple tbp and tfb genes, which led to the proposal that multiple TBP and TFB proteins may function in a manner similar to alternative sigma factors in bacterial cells. In vivo transcription and promoter analysis established a clear relationship between the promoter requirements of haloarchaeal genes and those of the eukaryal RNA polymerase II promoter. Studies on heat shock gene promoters, and the demonstration that specific tfb genes were induced by heat shock, provided the first indication that TFB proteins may direct expression of specific gene families. The construction of strains lacking tbp or tfb genes, coupled with the finding that many of these genes are differentially expressed under varying growth conditions, provided further support for this model. Genetic tools were also developed that led to the construction of insertion and deletion mutants, and a novel gene expression scheme was designed that allowed the controlled expression of these genes in vivo. More recent studies have used a whole genome array to examine the expression of these genes and we have established a linkage between the expression of

  16. Arabidopsis gene expression patterns are altered during spaceflight

    Science.gov (United States)

    Paul, Anna-Lisa; Popp, Michael P.; Gurley, William B.; Guy, Charles; Norwood, Kelly L.; Ferl, Robert J.

    The exposure of Arabidopsis thaliana (Arabidopsis) plants to spaceflight environments results in differential gene expression. A 5-day mission on orbiter Columbia in 1999 (STS-93) carried transgenic Arabidopsis plants engineered with a transgene composed of the alcohol dehydrogenase (Adh) gene promoter linked to the β-Glucuronidase (GUS) reporter gene. The plants were used to evaluate the effects of spaceflight on gene expression patterns initially by using the Adh/GUS transgene to address specifically the possibility that spaceflight induces a hypoxic stress response (Paul, A.L., Daugherty, C.J., Bihn, E.A., Chapman, D.K., Norwood, K.L., Ferl, R.J., 2001. Transgene expression patterns indicate that spaceflight affects stress signal perception and transduction in arabidopsis, Plant Physiol. 126, 613-621). As a follow-on to the reporter gene analysis, we report here the evaluation of genome-wide patterns of native gene expression within Arabidopsis shoots utilizing the Agilent DNA array of 21,000 Arabidopsis genes. As a control for the veracity of the array analyses, a selection of genes was further characterized with quantitative Real-Time RT PCR (ABI - Taqman®). Comparison of the patterns of expression for arrays probed with RNA isolated from plants exposed to spaceflight compared to RNA isolated from ground control plants revealed 182 genes that were differentially expressed in response to the spaceflight mission by more than 4-fold, and of those only 50 genes were expressed at levels chosen to support a conservative change call. None of the genes that are hallmarks of hypoxic stress were induced to this level. However, genes related to heat shock were dramatically induced - but in a pattern and under growth conditions that are not easily explained by elevated temperatures. These gene expression data are discussed in light of current models for plant responses to the spaceflight environment and with regard to potential future spaceflight experiment

  17. Gene expression profiling of mouse embryos with microarrays

    Science.gov (United States)

    Sharov, Alexei A.; Piao, Yulan; Ko, Minoru S. H.

    2011-01-01

    Global expression profiling by DNA microarrays provides a snapshot of cell and tissue status and becomes an essential tool in biological and medical sciences. Typical questions that can be addressed by microarray analysis in developmental biology include: (1) to find a set of genes expressed in a specific cell type; (2) to identify genes expressed commonly in multiple cell types; (3) to follow the time-course changes of gene expression patterns; (4) to demonstrate cell’s identity by showing similarities or differences among two or multiple cell types; (5) to find regulatory pathways and/or networks affected by gene manipulations, such as overexpression or repression of gene expression; (6) to find downstream target genes of transcription factors; (7) to find downstream target genes of cell signaling; (8) to examine the effects of environmental manipulation of cells on gene expression patterns; and (9) to find the effects of genetic manipulation in embryos and adults. Here we describe strategies for executing these experiments and monitoring changes of cell state with gene expression microarrays in application to mouse embryology. Both statistical assessment and interpretation of data are discussed. We also present a protocol for performing microarray analysis on a small amount of embryonic materials. PMID:20699157

  18. Genome-wide gene expression analysis of anguillid herpesvirus 1

    NARCIS (Netherlands)

    Beurden, van S.J.; Peeters, B.P.H.; Rottier, P.J.M.; Davison, A.A.; Engelsma, M.Y.

    2013-01-01

    Background Whereas temporal gene expression in mammalian herpesviruses has been studied extensively, little is known about gene expression in fish herpesviruses. Here we report a genome-wide transcription analysis of a fish herpesvirus, anguillid herpesvirus 1, in cell culture, studied during the

  19. Genetic architecture of gene expression in ovine skeletal muscle

    DEFF Research Database (Denmark)

    Kogelman, Lisette Johanna Antonia; Byrne, Keren; Vuocolo, Tony

    2011-01-01

    -based gene expression data we directly tested the hypothesis that there is genetic structure in the gene expression program in ovine skeletal muscle.Results: The genetic performance of six sires for a well defined muscling trait, longissimus lumborum muscle depth, was measured using extensive progeny testing...

  20. Application of four dyes in gene expression analyses by microarrays

    NARCIS (Netherlands)

    Staal, Y.; van Herwijnen, M.H.M.; van Schooten, F.J.; van Delft, J.H.M.

    2005-01-01

    BACKGROUND: DNA microarrays are widely used in gene expression analyses. To increase throughput and minimize costs without reducing gene expression data obtained, we investigated whether four mRNA samples can be analyzed simultaneously by applying four different fluorescent dyes. RESULTS: Following

  1. FGX : a frequentist gene expression index for Affymetrix arrays

    NARCIS (Netherlands)

    Purutçuoğlu, Vilda; Wit, Ernst

    2007-01-01

    We consider a new frequentist gene expression index for Affymetrix oligonucleotide DNA arrays, using a similar probe intensity model as suggested previously, called the Bayesian gene expression index (BGX). According to this model, the perfect match and mismatch values are assumed to be correlated a

  2. Genome organization and expression of the rat ACBP gene family

    DEFF Research Database (Denmark)

    Mandrup, S; Andreasen, P H; Knudsen, J

    1993-01-01

    pool former. We have molecularly cloned and characterized the rat ACBP gene family which comprises one expressed and four processed pseudogenes. One of these was shown to exist in two allelic forms. A comprehensive computer-aided analysis of the promoter region of the expressed ACBP gene revealed...

  3. 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 ampl...

  4. Gene expression during anthesis and senescence in Iris flowers

    NARCIS (Netherlands)

    Doorn, van W.G.; Balk, P.A.; Houwelingen, van A.M.; Hoebrechts, F.A.; Hall, R.D.; Vorst, O.; Schoot, van der C.; Wordragen, van M.F.

    2003-01-01

    We investigated changes in gene expression in Iris hollandicaflowers by microarray technology. Flag tepals were sampled daily, from three days prior to flower opening to the onset of visible senescence symptoms. Gene expression profiles were compared with biochemical data including lipid and protein

  5. Comparative genomics of the relationship between gene structure and expression

    NARCIS (Netherlands)

    Ren, X.

    2006-01-01

    The relationship between the structure of genes and their expression is a relatively new aspect of genome organization and regulation. With more genome sequences and expression data becoming available, bioinformatics approaches can help the further elucidation of the relationships between gene struc

  6. Global gene expression analysis and regulation of the principal genes expressed in bovine placenta in relation to the transcription factor AP-2 family

    Directory of Open Access Journals (Sweden)

    Kizaki Keiichiro

    2007-04-01

    Full Text Available Abstract Background Cell-cell communication is an important factor in feto-maternal units during placentogenesis. The placenta produces pivotal hormones and cytokines for communication between cotyledonary villi and the maternal caruncle. Gene expression in bovine placenta throughout pregnancy was comprehensively screened by a cDNA microarray, and we searched for a common transcription factor in a gene cluster that showed increasing expression throughout gestation in cotyledonary villi and caruncle. Methods Placentomal tissues (villi and caruncle were collected from Day 25 to Day 250 of gestation for microarray analysis. Global gene expression profiles were analyzed using the k-means clustering method. A consensus sequence cis-element that may control up-regulated genes in a characteristic cluster was examined in silico. The quantitative expression and localization of a specific transcription factor were investigated in each tissue using quantitative real-time RT-PCR and in situ hybridization. Results The microarray expression profiles were classified into ten clusters. The genes with most markedly increased expression became concentrated in cluster 2 as gestation proceeded. Cluster 2 included placental lactogen (CSH1, pregnancy-associated glycoprotein-1 (PAG1, and sulfotransferase family 1E estrogen-preferring member 1 (SULT1E1, which were mainly detected in giant trophoblast binucleate cells (BNC. Consensus sequence analysis identified transcription factor AP-2 binding sites in some genes in this cluster. Quantitative real-time RT-PCR analysis confirmed that high level expression of transcription factor AP-2 alpha (TFAP2A was common to cluster 2 genes during gestation. In contrast, the expression level of another AP-2 family gene, transcription factor AP-2 beta (TFAP2B, was extremely low over the same period. Another gene of the family, transcription factor AP-2 gamma (TFAP2C, was expressed at medium level compared with TFAP2A and TFAP2B. In

  7. 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.

  8. 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.

  9. Features of Gene Expression of Bacillus pumilus Metalloendopeptidase.

    Science.gov (United States)

    Rudakova, N L; Sabirova, A R; Balaban, N P; Tikhonova, A O; Sharipova, M R

    2016-08-01

    Features of gene expression of the secreted Bacillus pumilus metalloendopeptidase belonging to the adamalysin/reprolysin family were investigated. In the regulatory region of the gene, we identified hypothetical binding sites for transcription factors CcpA and TnrA. We found that the expression of the metalloendopeptidase gene is controlled by mechanisms of carbon and nitrogen catabolite repression. In experiments involving nitrogen metabolism regulatory protein mutant strains, we found that the control of the metalloendopeptidase gene expression involves proteins of ammonium transport GlnK and AmtB interacting with the TnrA-regulator.

  10. The effect of negative autoregulation on eukaryotic gene expression

    Science.gov (United States)

    Nevozhay, Dmitry; Adams, Rhys; Murphy, Kevin; Josic, Kresimir; Balázsi, G. Ábor

    2009-03-01

    Negative autoregulation is a frequent motif in gene regulatory networks, which has been studied extensively in prokaryotes. Nevertheless, some effects of negative feedback on gene expression in eukaryotic transcriptional networks remain unknown. We studied how the strength of negative feedback regulation affects the characteristics of gene expression in yeast cells carrying synthetic transcriptional cascades. We observed a drastic reduction of gene expression noise and a change in the shape of the dose-response curve. We explained these experimentally observed effects by stochastic simulations and a simple set of algebraic equations.

  11. Genetic architecture of gene expression in the chicken

    Directory of Open Access Journals (Sweden)

    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.

  12. Expression of genes related to tolerance to low temperature for maize seed germination.

    Science.gov (United States)

    Silva-Neta, I C; Pinho, E V; Veiga, A D; Pìnho, R G; Guimarães, R M; Caixeta, F; Santos, H O; Marques, T L

    2015-01-01

    The aim of this study was to characterize maize lines tolerant to cold temperatures during the germination process. Seeds from lines with different levels of tolerance to low temperatures were used; 3 lines were classified as tolerant and 3 as susceptible to low germination temperatures. A field was set up to multiply seeds from selected lines. After the seeds were harvested and classified, we conducted physiological tests and analyzed fatty acid content of palmitic, stearic, oleic, linoleic, linolenic, and eicosenoic acids. In proteomic analysis, the expression of heat-resistant proteins, including catalase, peroxidase, esterase, superoxide dismutase, and α-amylase, were evaluated. Transcript analysis was used to measure the expression of the genes AOX1, AOX2, ZmMPK-17, and ZmAN-13. The material showing the highest susceptibility to low germination temperatures contained high saturated fatty acid content. Expression of α-amylase in seeds soaked for 72 h at a temperature of 10°C was lower than expression of α-amylase when soaked at 25°C for the same amount of time. We observed variation in the expression of heat-resistant proteins in seeds of the lines evaluated. The genes AOX and Zm-AN13 were promising for use in identifying maize materials that are tolerant to low germination temperatures.

  13. Decreasing the stochasticity of mammalian gene expression by a synthetic gene circuit

    Science.gov (United States)

    Nevozhay, Dmitry; Zal, Tomasz; Balazsi, Gabor

    2012-02-01

    Gene therapy and functional genetic studies usually require precisely controlled and uniform gene expression in a population of cells for reliable level of protein production. Due to this requirement, stochastic gene expression is perceived as undesirable in these fields and ideally has to be minimized. The number of approaches for decreasing gene expression stochasticity in mammalian cells is limited. This creates an unmet need to develop new gene expression systems for this purpose. Based on earlier synthetic constructs in yeast, we developed and assessed a negative feedback-based mammalian gene circuit, with uniform and low level of stochasticity in gene expression at different levels of induction. In addition, this new synthetic construct enables highly precise gene expression control in mammalian cells, due to the linear dependence of gene expression on the inducer concentration applied to the system. This mammalian gene expression circuit has potential applicability for the development of new treatment modalities in gene therapy and research tools in functional genetics. In addition, this work creates a roadmap for moving synthetic gene circuits from microbes into mammalian cells.

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

    Directory of Open Access Journals (Sweden)

    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

  15. Transcriptomic analysis of gene expression profiles of stomach carcinoma reveal abnormal expression of mitotic components.

    Science.gov (United States)

    Tong, Hongfei; Wang, Jisheng; Chen, Hui; Wang, Zhaohong; Fan, Henwei; Ni, Zhonglin

    2017-02-01

    In order to explore the etiology of gastric cancer on global gene expression level, we developed advanced bioinformatic analysis to investigate the variations of global gene expression and the interactions among them. We downloaded the dataset GSE63288 from Gene Expression Omnibus (GEO) database which included 22 human gastric cancer and 22 healthy control samples. We identified the differential expression genes, and explored the Gene ontology (GO) and pathways of the differentially expressed genes. Furthermore, integrative interaction network and co-expression network were employed to identify the key genes which may contribute to gastric cancer progression. The results indicated that 5 kinases including BUB1, TTK protein kinase, Citron Rho-interacting kinase (CIT), ZAK and NEK2 were upregulated in gastric cancer. Interestingly, BUB1, TTK, CIT and NEK2 have shown high expression similarities and bound with each other, and participated in multiple phases of mitosis. Moreover, a subnet of co-expression genes e.g. KIF14, PRC1, CENPF and CENPI was also involved in mitosis which was functionally coupled with the kinases above. By validation assays, the results indicated that CIT, PRC1, TTK and KIF14 were significantly upregulated in gastric cancer. These evidences have suggested that aberrant expression of these genes may drive gastric cancer including progression, invasion and metastasis. Although the causal relationships between gastric cancer and the genes are still lacking, it was reasonable to take them as biomarkers for diagnosis of gastric cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

  16. Key aspects of analyzing microarray gene-expression data.

    Science.gov (United States)

    Chen, James J

    2007-05-01

    One major challenge with the use of microarray technology is the analysis of massive amounts of gene-expression data for various applications. This review addresses the key aspects of the microarray gene-expression data analysis for the two most common objectives: class comparison and class prediction. Class comparison mainly aims to select which genes are differentially expressed across experimental conditions. Gene selection is separated into two steps: gene ranking and assigning a significance level. Class prediction uses expression profiling analysis to develop a prediction model for patient selection, diagnostic prediction or prognostic classification. Development of a prediction model involves two components: model building and performance assessment. It also describes two additional data analysis methods: gene-class testing and multiple ordering criteria.

  17. Distribution of population-averaged observables in stochastic gene expression

    Science.gov (United States)

    Bhattacharyya, Bhaswati; Kalay, Ziya

    2014-01-01

    Observation of phenotypic diversity in a population of genetically identical cells is often linked to the stochastic nature of chemical reactions involved in gene regulatory networks. We investigate the distribution of population-averaged gene expression levels as a function of population, or sample, size for several stochastic gene expression models to find out to what extent population-averaged quantities reflect the underlying mechanism of gene expression. We consider three basic gene regulation networks corresponding to transcription with and without gene state switching and translation. Using analytical expressions for the probability generating function of observables and large deviation theory, we calculate the distribution and first two moments of the population-averaged mRNA and protein levels as a function of model parameters, population size, and number of measurements contained in a data set. We validate our results using stochastic simulations also report exact results on the asymptotic properties of population averages which show qualitative differences among different models.

  18. 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...

  19. 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...

  20. A predictive approach to identify genes differentially expressed

    Science.gov (United States)

    Saraiva, Erlandson F.; Louzada, Francisco; Milan, Luís A.; Meira, Silvana; Cobre, Juliana

    2012-10-01

    The main objective of gene expression data analysis is to identify genes that present significant changes in expression levels between a treatment and a control biological condition. In this paper, we propose a Bayesian approach to identify genes differentially expressed calculating credibility intervals from predictive densities which are constructed using sampled mean treatment effect from all genes in study excluding the treatment effect of genes previously identified with statistical evidence for difference. We compare our Bayesian approach with the standard ones based on the use of the t-test and modified t-tests via a simulation study, using small sample sizes which are common in gene expression data analysis. Results obtained indicate that the proposed approach performs better than standard ones, especially for cases with mean differences and increases in treatment variance in relation to control variance. We also apply the methodologies to a publicly available data set on Escherichia coli bacteria.

  1. 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.

  2. A riboswitch-based inducible gene expression system for mycobacteria.

    Directory of Open Access Journals (Sweden)

    Jessica C Seeliger

    Full Text Available Research on the human pathogen Mycobacterium tuberculosis (Mtb would benefit from novel tools for regulated gene expression. Here we describe the characterization and application of a synthetic riboswitch-based system, which comprises a mycobacterial promoter for transcriptional control and a riboswitch for translational control. The system was used to induce and repress heterologous protein overexpression reversibly, to create a conditional gene knockdown, and to control gene expression in a macrophage infection model. Unlike existing systems for controlling gene expression in Mtb, the riboswitch does not require the co-expression of any accessory proteins: all of the regulatory machinery is encoded by a short DNA segment directly upstream of the target gene. The inducible riboswitch platform has the potential to be a powerful general strategy for creating customized gene regulation systems in Mtb.

  3. Fundamental principles of energy consumption for gene expression

    Science.gov (United States)

    Huang, Lifang; Yuan, Zhanjiang; Yu, Jianshe; Zhou, Tianshou

    2015-12-01

    How energy is consumed in gene expression is largely unknown mainly due to complexity of non-equilibrium mechanisms affecting expression levels. Here, by analyzing a representative gene model that considers complexity of gene expression, we show that negative feedback increases energy consumption but positive feedback has an opposite effect; promoter leakage always reduces energy consumption; generating more bursts needs to consume more energy; and the speed of promoter switching is at the cost of energy consumption. We also find that the relationship between energy consumption and expression noise is multi-mode, depending on both the type of feedback and the speed of promoter switching. Altogether, these results constitute fundamental principles of energy consumption for gene expression, which lay a foundation for designing biologically reasonable gene modules. In addition, we discuss possible biological implications of these principles by combining experimental facts.

  4. Gene expression accurately distinguishes liver metastases of small bowel and pancreas neuroendocrine tumors.

    Science.gov (United States)

    Sherman, Scott K; Maxwell, Jessica E; Carr, Jennifer C; Wang, Donghong; Bellizzi, Andrew M; Sue O'Dorisio, M; O'Dorisio, Thomas M; Howe, James R

    2014-12-01

    Small bowel (SBNETs) and pancreatic neuroendocrine tumors (PNETs) often present with liver metastases. Although liver biopsy establishes a neuroendocrine diagnosis, the primary tumor site is frequently unknown without exploratory surgery. Gene expression differences in metastases may distinguish primary SBNETs and PNETs. This study sought to determine expression differences of four genes in neuroendocrine metastases and to create a gene expression algorithm to distinguish the primary site. Nodal and liver metastases from SBNETs and PNETs (n = 136) were collected at surgery under an Institutional Review Board-approved protocol. Quantitative PCR measured expression of bombesin-like receptor-3, opioid receptor kappa-1, oxytocin receptor, and secretin receptor in metastases. Logistic regression models defined an algorithm predicting the primary tumor site. Models were developed on a training set of 21 nodal metastases and performance was validated on an independent set of nodal and liver metastases. Expression of all four genes was significantly different in SBNET compared to PNET metastases. The optimal model employed expression of bombesin-like receptor-3 and opioid receptor kappa-1. When these genes did not amplify, the algorithm used oxytocin receptor and secretin receptor expression, which allowed classification of all 136 metastases with 94.1 % accuracy. In the independent liver metastasis validation set, 52/56 (92.9 %) were correctly classified. Positive predictive values were 92.5 % for SBNETs and 93.8 % for PNETs. This validated algorithm accurately distinguishes SBNET and PNET metastases based on their expression of four genes. High accuracy in liver metastases demonstrates applicability to the clinical setting. Studies assessing this algorithm's utility in prospective clinical decision-making are warranted.

  5. Mucin gene expression in human middle ear epithelium.

    Science.gov (United States)

    Kerschner, Joseph Edward

    2007-09-01

    To investigate the expression of recently identified human mucin genes in human middle ear epithelial (MEE) specimens from in vivo middle ear (ME) tissue and to compare this mucin gene expression with mucin gene expression in an immortalized cell culture in vitro source of human MEE. Human MEE was harvested as in vivo specimens, and human MEE cell cultures were established for in vitro experimentation. RNA was extracted from MEE and primers designed for reverse-transcription polymerase chain reaction to assess for mucin gene MUC1, MUC2, MUC3, MUC4, MUC5AC, MUC5B, MUC6, MUC7, MUC8, MUC9, MUC11, MUC12, MUC13, MUC15, MUC16, MUC18, MUC19, and MUC20 expression. Mucin gene expression in the in vivo and in vitro ME tissue was compared against tissues with known expression of the mucin genes in question. Mucin genes MUC1, MUC2, MUC3, MUC4, MUC5AC, MUC5B, MUC7, MUC8, MUC9, MUC11, MUC13, MUC15, MUC16, MUC18, MUC19, and MUC20 were identified and expressed in both the in vivo and in vitro samples of MEE. Mucin genes MUC6, MUC12, and MUC17 were not identified in either tissue samples. Many of the mucin genes that have been recently identified are expressed in human MEE. These genes are expressed in a similar manner in both in vivo and in vitro models. Understanding the mechanisms in which these genes regulate the physiology and pathophysiology of MEE will provide a more thorough understanding of the molecular mechanics of the MEE and disease conditions such as otitis media.

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

    Directory of Open Access Journals (Sweden)

    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.

  7. Gene expression profile analysis of human intervertebral disc degeneration

    OpenAIRE

    Kai Chen; Dajiang Wu; Xiaodong Zhu; Haijian Ni; Xianzhao Wei; Ningfang Mao; Yang Xie; Yunfei Niu; Ming Li

    2013-01-01

    In this study, we used microarray analysis to investigate the biogenesis and progression of intervertebral disc degeneration. The gene expression profiles of 37 disc tissue samples obtained from patients with herniated discs and degenerative disc disease collected by the National Cancer Institute Cooperative Tissue Network were analyzed. Differentially expressed genes between more and less degenerated discs were identified by significant analysis of microarray. A total of 555 genes were signi...

  8. Expression of protein-coding genes embedded in ribosomal DNA

    DEFF Research Database (Denmark)

    Johansen, Steinar D; Haugen, Peik; Nielsen, Henrik

    2007-01-01

    Ribosomal DNA (rDNA) is a specialised chromosomal location that is dedicated to high-level transcription of ribosomal RNA genes. Interestingly, rDNAs are frequently interrupted by parasitic elements, some of which carry protein genes. These are non-LTR retrotransposons and group II introns...... that encode reverse transcriptase-like genes, and group I introns and archaeal introns that encode homing endonuclease genes (HEGs). Although rDNA-embedded protein genes are widespread in nuclei, organelles and bacteria, there is surprisingly little information available on how these genes are expressed....... Exceptions include a handful of HEGs from group I introns. Recent studies have revealed unusual and essential roles of group I and group I-like ribozymes in the endogenous expression of HEGs. Here we discuss general aspects of rDNA-embedded protein genes and focus on HEG expression from group I introns...

  9. Protamine stimulates bone sialoprotein gene expression.

    Science.gov (United States)

    Zhou, Liming; Matsumura, Hiroyoshi; Mezawa, Masaru; Takai, Hideki; Nakayama, Yohei; Mitarai, Makoto; Ogata, Yorimasa

    2013-03-10

    Protamine is a small, arginine-rich, nuclear protein that replaces histone late in the haploid phase of spermatogenesis and is believed to be essential for sperm head condensation and DNA stabilization. Protamine has many biological activities and has roles in hematopoiesis, immune responses, the nervous system and bone metabolism. Bone sialoprotein (BSP) is a mineralized connective tissue-specific protein expressed in differentiated osteoblasts that appears to function in the initial mineralization of bone. Protamine (71.35 ng/ml) increased BSP mRNA levels by 6h in osteoblast-like ROS 17/2.8 cells. In a transient transfection assay, protamine (71.35 ng/ml) increased luciferase activity of the construct (-116 to +60) in ROS 17/2.8 cells and rat bone marrow stromal cells. Luciferase activities induced by protamine were blocked by protein kinase A, tyrosine kinase and ERK1/2 inhibitors. Introduction of 2 bp mutations to the luciferase constructs showed that the effects of protamine were mediated by a cAMP response element (CRE), a fibroblast growth factor 2 response element (FRE) and a homeodomain protein-binding site (HOX). Gel shift analyses showed that protamine (71.35 ng/ml) increased the nuclear protein binding to CRE, FRE and HOX. CREB, phospho-CREB, c-Fos, c-Jun, JunD and Fra2 antibodies disrupted the formation of CRE-protein complexes. Dlx5, Msx2, Runx2 and Smad1 antibodies disrupted FRE- and HOX-protein complex formations. These studies demonstrate that protamine induces BSP transcription by targeting CRE, FRE and HOX sites in the proximal promoter of the rat BSP gene. Moreover, phospho-CREB, c-Fos, c-Jun, JunD, Fra2, Dlx5, Msx2, Runx2 and Smadl transcription factors appear to be key regulators of protamine effects on BSP transcription.

  10. Binary gene induction and protein expression in individual cells

    Directory of Open Access Journals (Sweden)

    Conolly Rory B

    2006-04-01

    Full Text Available Abstract Background Eukaryotic gene transcription is believed to occur in either a binary or a graded fashion. With binary induction, a transcription activator (TA regulates the probability with which a gene template is switched from the inactive to the active state without affecting the rate at which RNA molecules are produced from the template. With graded, also called rheostat-like, induction the gene template has continuously varying levels of transcriptional activity, and the TA regulates the rate of RNA production. Support for each of these two mechanisms arises primarily from experimental studies measuring reporter proteins in individual cells, rather than from direct measurement of induction events at the gene template. Methods and results In this paper, using a computational model of stochastic gene expression, we have studied the biological and experimental conditions under which a binary induction mode operating at the gene template can give rise to differentially expressed "phenotypes" (i.e., binary, hybrid or graded at the protein level. We have also investigated whether the choice of reporter genes plays a significant role in determining the observed protein expression patterns in individual cells, given the diverse properties of commonly-used reporter genes. Our simulation confirmed early findings that the lifetimes of active/inactive promoters and half-lives of downstream mRNA/protein products are important determinants of various protein expression patterns, but showed that the induction time and the sensitivity with which the expressed genes are detected are also important experimental variables. Using parameter conditions representative of reporter genes including green fluorescence protein (GFP and β-galactosidase, we also demonstrated that graded gene expression is more likely to be observed with GFP, a longer-lived protein with low detection sensitivity. Conclusion The choice of reporter genes may determine whether protein

  11. Weighted gene co-expression based biomarker discovery for psoriasis detection.

    Science.gov (United States)

    Sundarrajan, Sudharsana; Arumugam, Mohanapriya

    2016-11-15

    Psoriasis is a chronic inflammatory disease of the skin with an unknown aetiology. The disease manifests itself as red and silvery scaly plaques distributed over the scalp, lower back and extensor aspects of the limbs. After receiving scant consideration for quite a few years, psoriasis has now become a prominent focus for new drug development. A group of closely connected and differentially co-expressed genes may act in a network and may serve as molecular signatures for an underlying phenotype. A weighted gene coexpression network analysis (WGCNA), a system biology approach has been utilized for identification of new molecular targets for psoriasis. Gene coexpression relationships were investigated in 58 psoriatic lesional samples resulting in five gene modules, clustered based on the gene coexpression patterns. The coexpression pattern was validated using three psoriatic datasets. 10 highly connected and informative genes from each module was selected and termed as psoriasis specific hub signatures. A random forest based binary classifier built using the expression profiles of signature genes robustly distinguished psoriatic samples from the normal samples in the validation set with an accuracy of 0.95 to 1. These signature genes may serve as potential candidates for biomarker discovery leading to new therapeutic targets. WGCNA, the network based approach has provided an alternative path to mine out key controllers and drivers of psoriasis. The study principle from the current work can be extended to other pathological conditions.

  12. 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.

  13. 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.

  14. Relating perturbation magnitude to temporal gene expression in biological systems

    Directory of Open Access Journals (Sweden)

    Pfrender Michael E

    2009-03-01

    Full Text Available Abstract Background Most transcriptional activity is a result of environmental variability. This cause (environment and effect (gene expression relationship is essential to survival in any changing environment. The specific relationship between environmental perturbation and gene expression – and stability of the response – has yet to be measured in detail. We describe a method to quantitatively relate perturbation magnitude to response at the level of gene expression. We test our method using Saccharomyces cerevisiae as a model organism and osmotic stress as an environmental stress. Results Patterns of gene expression were measured in response to increasing sodium chloride concentrations (0, 0.5, 0.7, 1.0, and 1.2 M for sixty genes impacted by osmotic shock. Expression of these genes was quantified over five time points using reverse transcriptase real-time polymerase chain reaction. Magnitudes of cumulative response for specific pathways, and the set of all genes, were obtained by combining the temporal response envelopes for genes exhibiting significant changes in expression with time. A linear relationship between perturbation magnitude and response was observed for the range of concentrations studied. Conclusion This study develops a quantitative approach to describe the stability of gene response and pathways to environmental perturbation and illustrates the utility of this approach. The approach should be applicable to quantitatively evaluate the response of organisms via the magnitude of response and stability of the transcriptome to environmental change.

  15. Clustering Algorithms: Their Application to Gene Expression Data

    Science.gov (United States)

    Oyelade, Jelili; Isewon, Itunuoluwa; Oladipupo, Funke; Aromolaran, Olufemi; Uwoghiren, Efosa; Ameh, Faridah; Achas, Moses; Adebiyi, Ezekiel

    2016-01-01

    Gene expression data hide vital information required to understand the biological process that takes place in a particular organism in relation to its environment. Deciphering the hidden patterns in gene expression data proffers a prodigious preference to strengthen the understanding of functional genomics. The complexity of biological networks and the volume of genes present increase the challenges of comprehending and interpretation of the resulting mass of data, which consists of millions of measurements; these data also inhibit vagueness, imprecision, and noise. Therefore, the use of clustering techniques is a first step toward addressing these challenges, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. The clustering of gene expression data has been proven to be useful in making known the natural structure inherent in gene expression data, understanding gene functions, cellular processes, and subtypes of cells, mining useful information from noisy data, and understanding gene regulation. The other benefit of clustering gene expression data is the identification of homology, which is very important in vaccine design. This review examines the various clustering algorithms applicable to the gene expression data in order to discover and provide useful knowledge of the appropriate clustering technique that will guarantee stability and high degree of accuracy in its analysis procedure. PMID:27932867

  16. Genome-wide patterns of Arabidopsis gene expression in nature.

    Directory of Open Access Journals (Sweden)

    Christina L Richards

    Full Text Available Organisms in the wild are subject to multiple, fluctuating environmental factors, and it is in complex natural environments that genetic regulatory networks actually function and evolve. We assessed genome-wide gene expression patterns in the wild in two natural accessions of the model plant Arabidopsis thaliana and examined the nature of transcriptional variation throughout its life cycle and gene expression correlations with natural environmental fluctuations. We grew plants in a natural field environment and measured genome-wide time-series gene expression from the plant shoot every three days, spanning the seedling to reproductive stages. We find that 15,352 genes were expressed in the A. thaliana shoot in the field, and accession and flowering status (vegetative versus flowering were strong components of transcriptional variation in this plant. We identified between ∼110 and 190 time-varying gene expression clusters in the field, many of which were significantly overrepresented by genes regulated by abiotic and biotic environmental stresses. The two main principal components of vegetative shoot gene expression (PC(veg correlate to temperature and precipitation occurrence in the field. The largest PC(veg axes included thermoregulatory genes while the second major PC(veg was associated with precipitation and contained drought-responsive genes. By exposing A. thaliana to natural environments in an open field, we provide a framework for further understanding the genetic networks that are deployed in natural environments, and we connect plant molecular genetics in the laboratory to plant organismal ecology in the wild.

  17. X chromosome regulation of autosomal gene expression in bovine blastocysts

    OpenAIRE

    Itoh, Yuichiro; Arnold, Arthur P.

    2014-01-01

    Although X chromosome inactivation in female mammals evolved to balance the expression of X chromosome and autosomal genes in the two sexes, female embryos pass through developmental stages in which both X chromosomes are active in somatic cells. Bovine blastocysts show higher expression of many X genes in XX than XY embryos, suggesting that X inactivation is not complete. Here we reanalyzed bovine blastocyst microarray expression data from a network perspective with a focus on interactions b...

  18. X chromosome regulation of autosomal gene expression in bovine blastocysts

    OpenAIRE

    Itoh, Yuichiro; Arnold, Arthur P.

    2014-01-01

    Although X chromosome inactivation in female mammals evolved to balance the expression of X chromosome and autosomal genes in the two sexes, female embryos pass through developmental stages in which both X chromosomes are active in somatic cells. Bovine blastocysts show higher expression of many X genes in XX than XY embryos, suggesting that X inactivation is not complete. Here we reanalyzed bovine blastocyst microarray expression data from a network perspective with a focus on interactions b...

  19. 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.

  20. 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.

  1. DNA microarray analysis of genes differentially expressed in adipocyte differentiation

    Indian Academy of Sciences (India)

    Chunyan Yin; Yanfeng Xiao; Wei Zhang; Erdi Xu; Weihua Liu; Xiaoqing Yi; Ming Chang

    2014-06-01

    In the present study, the human liposarcoma cell line SW872 was used to identify global changes in gene expression profiles occurring during adipogenesis. We further explored some of the genes expressed during the late phase of adipocyte differentiation. These genes may play a major role in promoting excessive proliferation and accumulation of lipid droplets, which contribute to the development of obesity. By using microarray-based technology, we examined differential gene expression in early differentiated adipocytes and late differentiated adipocytes. Validated genes exhibited a ≥ 10-fold increase in the late phase of adipocyte differentiation by polymerase chain reaction (RT-PCR). Compared with undifferentiated preadipocytes, we found that 763 genes were increased in early differentiated adipocytes, and 667 genes were increased in later differentiated adipocytes. Furthermore, 21 genes were found being expressed 10-fold higher in the late phase of adipocyte differentiation. The results were in accordance with the RT-PCR test, which validated 11 genes, namely, CIDEC, PID1, LYRM1, ADD1, PPAR2, ANGPTL4, ADIPOQ, ACOX1, FIP1L1, MAP3K2 and PEX14. Most of these genes were found being expressed in the later phase of adipocyte differentiation involved in obesity-related diseases. The findings may help to better understand the mechanism of obesity and related diseases.

  2. DNA microarray analysis of genes differentially expressed in adipocyte differentiation.

    Science.gov (United States)

    Yin, Chunyan; Xiao, Yanfeng; Zhang, Wei; Xu, Erdi; Liu, Weihua; Yi, Xiaoqing; Chang, Ming

    2014-06-01

    In the present study, the human liposarcoma cell line SW872 was used to identify global changes in gene expression profiles occurring during adipogenesis. We further explored some of the genes expressed during the late phase of adipocyte differentiation. These genes may play a major role in promoting excessive proliferation and accumulation of lipid droplets, which contribute to the development of obesity. By using microarray-based technology, we examined differential gene expression in early differentiated adipocytes and late differentiated adipocytes. Validated genes exhibited a greater than or equal to 10-fold increase in the late phase of adipocyte differentiation by polymerase chain reaction (RT-PCR). Compared with undifferentiated preadipocytes, we found that 763 genes were increased in early differentiated adipocytes, and 667 genes were increased in later differentiated adipocytes. Furthermore, 21 genes were found being expressed 10-fold higher in the late phase of adipocyte differentiation. The results were in accordance with the RTPCR test, which validated 11 genes, namely, CIDEC, PID1, LYRM1, ADD1, PPAR?2, ANGPTL4, ADIPOQ, ACOX1, FIP1L1, MAP3K2 and PEX14. Most of these genes were found being expressed in the later phase of adipocyte differentiation involved in obesity-related diseases. The findings may help to better understand the mechanism of obesity and related diseases.

  3. BPH gene expression profile associated to prostate gland volume.

    Science.gov (United States)

    Descazeaud, Aurelien; Rubin, Mark A; Hofer, Matthias; Setlur, Sunita; Nikolaief, Nathalie; Vacherot, Francis; Soyeux, Pascale; Kheuang, Laurence; Abbou, Claude C; Allory, Yves; de la Taille, Alexandre

    2008-12-01

    The aim of the current study was to analyze gene expression profiles in benign prostatic hyperplasia and to compare them with phenotypic properties. Thirty-seven specimens of benign prostatic hyperplasia were obtained from symptomatic patients undergoing surgery. RNA was extracted and hybridized to Affymetrix Chips containing 54,000 gene expression probes. Gene expression profiles were analyzed using cluster, TreeView, and significance analysis of microarrays softwares. In an initial unsupervised analysis, our 37 samples clustered hierarchically in 2 groups of 18 and 19 samples, respectively. Five clinical parameters were statistically different between the 2 groups: in group 1 compared with group 2, patients had larger prostate glands, had higher prostate specific antigen levels, were more likely to be treated by alpha blockers, to be operated by prostatectomy, and to have major irritative symptoms. The sole independent parameter associated with this dichotome clustering, however, was the prostate gland volume. Therefore, the role of prostate volume was explored in a supervised analysis. Gene expression of prostate glands 60 mL were compared using significance analysis of microarrays and 227 genes were found differentially expressed between the 2 groups (>2 change and false discovery rate of <5%). Several specific pathways including growth factors genes, cell cycle genes, apoptose genes, inflammation genes, and androgen regulated genes, displayed major differences between small and large prostate glands.

  4. Validation of housekeeping genes for studying differential gene expression in the bovine myometrium.

    Science.gov (United States)

    Rekawiecki, Robert; Kowalik, Magdalena K; Kotwica, Jan

    2013-12-01

    The aim of this study was to determine the steady-state expression of 13 selected housekeeping genes in the myometrium of cyclic and pregnant cows. Cells taken from bovine myometrium on days 1-5, 6-10, 11-16 and 17-20 of the oestrous cycle and in weeks 3-5, 6-8 and 9-12 of pregnancy were used. Reverse transcribed RNA was amplified in real-time PCR using designed primers. Reaction efficiency was determined with the Linreg programme. The geNorm and NormFinder programmes were used to select the best housekeeping genes. They calculate the expression stability factor for each used housekeeping gene with the smallest value for most stably expressed genes. According to geNorm, the most stable housekeeping genes in the myometrium were C2orf29, TPB and TUBB2B, while the least stably expressed genes were 18S RNA, HPRT1 and GAPDH. NormFinder identified the best genes in the myometrium as C2orf29, MRPL12 and TBP, while the worst genes were 18S RNA, B2M and SF3A1. Differences in stability factors between the two programmes may also indicate that the physiological status of the female, e.g. pregnancy, affects the stability of expression of housekeeping genes. The different expression stability of housekeeping genes did not affect progesterone receptor expression but it could be important if small differences in gene expression were measured between studies.

  5. Gene expression profile analysis of type 2 diabetic mouse liver.

    Directory of Open Access Journals (Sweden)

    Fang Zhang

    Full Text Available Liver plays a key role in glucose metabolism and homeostasis, and impaired hepatic glucose metabolism contributes to the development of type 2 diabetes. However, the precise gene expression profile of diabetic liver and its association with diabetes and related diseases are yet to be further elucidated. In this study, we detected the gene expression profile by high-throughput sequencing in 9-week-old normal and type 2 diabetic db/db mouse liver. Totally 12132 genes were detected, and 2627 genes were significantly changed in diabetic mouse liver. Biological process analysis showed that the upregulated genes in diabetic mouse liver were mainly enriched in metabolic processes. Surprisingly, the downregulated genes in diabetic mouse liver were mainly enriched in immune-related processes, although all the altered genes were still mainly enriched in metabolic processes. Similarly, KEGG pathway analysis showed that metabolic pathways were the major pathways altered in diabetic mouse liver, and downregulated genes were enriched in immune and cancer pathways. Analysis of the key enzyme genes in fatty acid and glucose metabolism showed that some key enzyme genes were significantly increased and none of the detected key enzyme genes were decreased. In addition, FunDo analysis showed that liver cancer and hepatitis were most likely to be associated with diabetes. Taken together, this study provides the digital gene expression profile of diabetic mouse liver, and demonstrates the main diabetes-associated hepatic biological processes, pathways, key enzyme genes in fatty acid and glucose metabolism and potential hepatic diseases.

  6. Expression of HOX C homeobox genes in lymphoid cells.

    Science.gov (United States)

    Lawrence, H J; Stage, K M; Mathews, C H; Detmer, K; Scibienski, R; MacKenzie, M; Migliaccio, E; Boncinelli, E; Largman, C

    1993-08-01

    The class I homeobox genes located in four clusters in mammalian genomes (HOX A, HOX B, HOX C, and HOX D) appear to play a major role in fetal development. Previous surveys of homeobox gene expression in human leukemic cell lines have shown that certain HOX A genes are expressed only in myeloid cell lines, whereas HOX B gene expression is largely restricted to cells with erythroid potential. We now report a survey of the expression patterns of 9 homeobox genes from the HOX C locus in a panel of 24 human and 7 murine leukemic cell lines. The most striking observation is the lymphoid-specific pattern of expression of HOX C4, located at the 3' end of the locus. A major transcript of 1.9 kilobases is observed in both T-cell and B-cell lines. HOX C4 expression is also detected in normal human marrow and peripheral blood lymphocytes, but not in mature granulocytes or monocytes. HOX C8 is also expressed in human lymphoid cells but is expressed in other blood cell types as well. However, the HOX C8 transcript pattern is lineage specific. These data, in conjunction with earlier findings, suggest that homeobox gene expression influences lineage determination during hematopoiesis.

  7. A gene expression signature that defines breast cancer metastases.

    Science.gov (United States)

    Ellsworth, Rachel E; Seebach, Jeff; Field, Lori A; Heckman, Caroline; Kane, Jennifer; Hooke, Jeffrey A; Love, Brad; Shriver, Craig D

    2009-01-01

    The most important predictor of prognosis in breast cancer is lymph node status, yet little is known about molecular changes associated with lymph node metastasis. Here, gene expression analysis was performed on primary breast (PBT) and corresponding metastatic lymph node (MLN) tumors to identify molecular signatures associated with nodal metastasis. RNA was isolated after laser microdissection from frozen PBT and MLN from 20 patients with positive lymph nodes and hybridized to the microarray chips. Differential expression was determined using Mann-Whitney testing; Bonferroni corrected P values of 0.05 and 0.001 were calculated. Results were validated using TaqMan assays. Fifty-one genes were differentially expressed (P 100-fold higher expression in MLT while COL11A1, KRT14, MMP13, TAC1 and WNT2 had >100-fold higher expression in PBT. Gene expression differences between PBT and MLN suggests that expression of a unique set of genes is required for successful lymph node colonization. Genes expressed at higher levels in PBT are involved in degradation of the extracellular matrix, enabling cells with metastatic potential to disseminate, while genes expressed at higher levels in metastases are involved in transcription, signal transduction and immune response, providing cells with proliferation and survival advantages. These data improve our understanding of the biological processes involved in successful metastatis and provide new targets to arrest tumor cell dissemination and metastatic colonization.

  8. 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

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  10. Regulation of gene expression by Goodwin's loop with many genes

    Science.gov (United States)

    Sielewiesiuk, Jan; Łopaciuk, Agata

    2012-01-01

    The paper presents a simple analysis of a long Goodwin's loop containing many genes. The genes form a closed series. The rate of transcription of any gene is up or down regulated by theprotein product of the preceding gene. We describe the loop with a system of ordinary differential equations of order s. Oscillatory solutions of the system are possible at the odd number of repressions and any number of inductions if the product of all Hill's coefficients, related to both repressions and inductions, is larger than:

  11. Mating alters gene expression patterns in Drosophila melanogaster male heads

    Directory of Open Access Journals (Sweden)

    Ellis Lisa L

    2010-10-01

    Full Text Available Abstract Background Behavior is a complex process resulting from the integration of genetic and environmental information. Drosophila melanogaster rely on multiple sensory modalities for reproductive success, and mating causes physiological changes in both sexes that affect reproductive output or behavior. Some of these effects are likely mediated by changes in gene expression. Courtship and mating alter female transcript profiles, but it is not known how mating affects male gene expression. Results We used Drosophila genome arrays to identify changes in gene expression profiles that occur in mated male heads. Forty-seven genes differed between mated and control heads 2 hrs post mating. Many mating-responsive genes are highly expressed in non-neural head tissues, including an adipose tissue called the fat body. One fat body-enriched gene, female-specific independent of transformer (fit, is a downstream target of the somatic sex-determination hierarchy, a genetic pathway that regulates Drosophila reproductive behaviors as well as expression of some fat-expressed genes; three other mating-responsive loci are also downstream components of this pathway. Another mating-responsive gene expressed in fat, Juvenile hormone esterase (Jhe, is necessary for robust male courtship behavior and mating success. Conclusions Our study demonstrates that mating causes changes in male head gene expression profiles and supports an increasing body of work implicating adipose signaling in behavior modulation. Since several mating-induced genes are sex-determination hierarchy target genes, additional mating-responsive loci may be downstream components of this pathway as well.

  12. The structure and expression of the human neuroligin-3 gene.

    Science.gov (United States)

    Philibert, R A; Winfield, S L; Sandhu, H K; Martin, B M; Ginns, E I

    2000-04-04

    The neuroligins are a family of proteins that are thought to mediate cell to cell interactions between neurons. During the sequencing at an Xq13 locus associated with a mental retardation syndrome in some studies, we discovered a portion of the human orthologue of the rat neuroligin-3 gene. We now report the structure and the expression of that gene. The gene spans approximately 30kb and contains eight exons. Unlike the rat gene, it codes for at least two mRNAs and at least one of which is expressed outside the CNS. Interestingly, the putative promoter for the gene overlaps the last exon of the neighboring HOPA gene and is located less than 1kb from an OPA element in which a polymorphism associated with mental retardation is found. These findings suggest a possible role for the neuroligin gene in mental retardation and that the role of the gene in humans may differ from its role in rats.

  13. Regulatory systems for hypoxia-inducible gene expression in ischemic heart disease gene therapy.

    Science.gov (United States)

    Kim, Hyun Ah; Rhim, Taiyoun; Lee, Minhyung

    2011-07-18

    Ischemic heart diseases are caused by narrowed coronary arteries that decrease the blood supply to the myocardium. In the ischemic myocardium, hypoxia-responsive genes are up-regulated by hypoxia-inducible factor-1 (HIF-1). Gene therapy for ischemic heart diseases uses genes encoding angiogenic growth factors and anti-apoptotic proteins as therapeutic genes. These genes increase blood supply into the myocardium by angiogenesis and protect cardiomyocytes from cell death. However, non-specific expression of these genes in normal tissues may be harmful, since growth factors and anti-apoptotic proteins may induce tumor growth. Therefore, tight gene regulation is required to limit gene expression to ischemic tissues, to avoid unwanted side effects. For this purpose, various gene expression strategies have been developed for ischemic-specific gene expression. Transcriptional, post-transcriptional, and post-translational regulatory strategies have been developed and evaluated in ischemic heart disease animal models. The regulatory systems can limit therapeutic gene expression to ischemic tissues and increase the efficiency of gene therapy. In this review, recent progresses in ischemic-specific gene expression systems are presented, and their applications to ischemic heart diseases are discussed.

  14. Systematic assessment of multi-gene predictors of pan-cancer cell line sensitivity to drugs exploiting gene expression data

    Science.gov (United States)

    Nguyen, Linh; Dang, Cuong C; Ballester, Pedro J.

    2017-01-01

    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 IC 50 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 drugs. These models

  15. Gene expression in the urinary bladder: a common carcinoma in situ gene expression signature exists disregarding histopathological classification

    DEFF Research Database (Denmark)

    Andersen, Lars Dyrskjøt; Kruhøffer, Mogens; Andersen, Thomas Thykjær

    2004-01-01

    The presence of carcinoma in situ (CIS) lesions in the urinary bladder is associated with a high risk of disease progression to a muscle invasive stage. In this study, we used microarray expression profiling to examine the gene expression patterns in superficial transitional cell carcinoma (s...... urothelium and urothelium with CIS lesions from the same urinary bladder revealed that the gene expression found in sTCC with surrounding CIS is found also in CIS biopsies as well as in histologically normal samples adjacent to the CIS lesions. Furthermore, we also identified similar gene expression changes...

  16. Efficient expression of the yeast metallothionein gene in Escherichia coli

    Energy Technology Data Exchange (ETDEWEB)

    Berka, T.; Shatzman, A.; Zimmerman, J.; Strickler, J.; Rosenberg, M.

    1988-01-01

    The yeast metallothionein gene CUP1 was cloned into a bacterial expression system to achieve efficient, controlled expression of the stable, unprocessed protein product. The Escherichia coli-synthesized yeast metallothionein bound copper, cadmium, zinc, indicating that the protein was functional. Furthermore, E. coli cells expressing CUP1 acquired a new, inducible ability to selectively sequester heavy metal ions from the growth medium.

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

    Directory of Open Access Journals (Sweden)

    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.

  18. Identifying the optimal gene and gene set in hepatocellular carcinoma based on differential expression and differential co-expression algorithm.

    Science.gov (United States)

    Dong, Li-Yang; Zhou, Wei-Zhong; Ni, Jun-Wei; Xiang, Wei; Hu, Wen-Hao; Yu, Chang; Li, Hai-Yan

    2017-02-01

    The objective of this study was to identify the optimal gene and gene set for hepatocellular carcinoma (HCC) utilizing differential expression and differential co-expression (DEDC) algorithm. The DEDC algorithm consisted of four parts: calculating differential expression (DE) by absolute t-value in t-statistics; computing differential co-expression (DC) based on Z-test; determining optimal thresholds on the basis of Chi-squared (χ2) maximization and the corresponding gene was the optimal gene; and evaluating functional relevance of genes categorized into different partitions to determine the optimal gene set with highest mean minimum functional information (FI) gain (Δ*G). The optimal thresholds divided genes into four partitions, high DE and high DC (HDE-HDC), high DE and low DC (HDE-LDC), low DE and high DC (LDE‑HDC), and low DE and low DC (LDE-LDC). In addition, the optimal gene was validated by conducting reverse transcription-polymerase chain reaction (RT-PCR) assay. The optimal threshold for DC and DE were 1.032 and 1.911, respectively. Using the optimal gene, the genes were divided into four partitions including: HDE-HDC (2,053 genes), HED-LDC (2,822 genes), LDE-HDC (2,622 genes), and LDE-LDC (6,169 genes). The optimal gene was microtubule‑associated protein RP/EB family member 1 (MAPRE1), and RT-PCR assay validated the significant difference between the HCC and normal state. The optimal gene set was nucleoside metabolic process (GO\\GO:0009116) with Δ*G = 18.681 and 24 HDE-HDC partitions in total. In conclusion, we successfully investigated the optimal gene, MAPRE1, and gene set, nucleoside metabolic process, which may be potential biomarkers for targeted therapy and provide significant insight for revealing the pathological mechanism underlying HCC.

  19. Comparative analysis of differentially expressed genes in normal and white spot syndrome virus infected Penaeus monodon

    Directory of Open Access Journals (Sweden)

    Juan Hsueh-Fen

    2007-05-01

    Full Text Available Abstract Background White spot syndrome (WSS is a viral disease that affects most of the commercially important shrimps and causes serious economic losses to the shrimp farming industry worldwide. However, little information is available in terms of the molecular mechanisms of the host-virus interaction. In this study, we used an expressed sequence tag (EST approach to observe global gene expression changes in white spot syndrome virus (WSSV-infected postlarvae of Penaeus monodon. Results Sequencing of the complementary DNA clones of two libraries constructed from normal and WSSV-infected postlarvae produced a total of 15,981 high-quality ESTs. Of these ESTs, 46% were successfully matched against annotated genes in National Center of Biotechnology Information (NCBI non-redundant (nr database and 44% were functionally classified using the Gene Ontology (GO scheme. Comparative EST analyses suggested that, in postlarval shrimp, WSSV infection strongly modulates the gene expression patterns in several organs or tissues, including the hepatopancreas, muscle, eyestalk and cuticle. Our data suggest that several basic cellular metabolic processes are likely to be affected, including oxidative phosphorylation, protein synthesis, the glycolytic pathway, and calcium ion balance. A group of immune-related chitin-binding protein genes is also likely to be strongly up regulated after WSSV infection. A database containing all the sequence data and analysis results is accessible at http://xbio.lifescience.ntu.edu.tw/pm/. Conclusion This study suggests that WSSV infection modulates expression of various kinds of genes. The predicted gene expression pattern changes not only reflect the possible responses of shrimp to the virus infection but also suggest how WSSV subverts cellular functions for virus multiplication. In addition, the ESTs reported in this study provide a rich source for identification of novel genes in shrimp.

  20. Building predictive gene signatures through simultaneous assessment of transcription factor activation and gene expression.

    Science.gov (United States)

    Building predictive gene signatures through simultaneous assessment of transcription factor activation and gene expression Exposure to many drugs and environmentally-relevant chemicals can cause adverse outcomes. These adverse outcomes, such as cancer, have been linked to mol...

  1. Predicting Autism Spectrum Disorder Using Blood-based Gene Expression Signatures and Machine Learning

    Science.gov (United States)

    Oh, Dong Hoon; Kim, Il Bin; Kim, Seok Hyeon; Ahn, Dong Hyun

    2017-01-01

    Objective The aim of this study was to identify a transcriptomic signature that could be used to classify subjects with autism spectrum disorder (ASD) compared to controls on the basis of blood gene expression profiles. The gene expression profiles could ultimately be used as diagnostic biomarkers for ASD. Methods We used the published microarray data (GSE26415) from the Gene Expression Omnibus database, which included 21 young adults with ASD and 21 age- and sex-matched unaffected controls. Nineteen differentially expressed probes were identified from a training dataset (n=26, 13 ASD cases and 13 controls) using the limma package in R language (adjusted p value <0.05) and were further analyzed in a test dataset (n=16, 8 ASD cases and 8 controls) using machine learning algorithms. Results Hierarchical cluster analysis showed that subjects with ASD were relatively well-discriminated from controls. Based on the support vector machine and K-nearest neighbors analysis, validation of 19-DE probes with a test dataset resulted in an overall class prediction accuracy of 93.8% as well as a sensitivity and specificity of 100% and 87.5%, respectively. Conclusion The results of our exploratory study suggest that the gene expression profiles identified from the peripheral blood samples of young adults with ASD can be used to identify a biological signature for ASD. Further study using a larger cohort and more homogeneous datasets is required to improve the diagnostic accuracy. PMID:28138110

  2. The Longissimus and Semimembranosus muscles display marked differences in their gene expression profiles in pig.

    Directory of Open Access Journals (Sweden)

    Frederic Herault

    Full Text Available BACKGROUND: Meat quality depends on skeletal muscle structure and metabolic properties. While most studies carried on pigs focus on the Longissimus muscle (LM for fresh meat consumption, Semimembranosus (SM is also of interest because of its importance for cooked ham production. Even if both muscles are classified as glycolytic muscles, they exhibit dissimilar myofiber composition and metabolic characteristics. The comparison of LM and SM transcriptome profiles undertaken in this study may thus clarify the biological events underlying their phenotypic differences which might influence several meat quality traits. METHODOLOGY/PRINCIPAL FINDINGS: Muscular transcriptome analyses were performed using a custom pig muscle microarray: the 15 K Genmascqchip. A total of 3823 genes were differentially expressed between the two muscles (Benjamini-Hochberg adjusted P value ≤0.05, out of which 1690 and 2133 were overrepresented in LM and SM respectively. The microarray data were validated using the expression level of seven differentially expressed genes quantified by real-time RT-PCR. A set of 1047 differentially expressed genes with a muscle fold change ratio above 1.5 was used for functional characterization. Functional annotation emphasized five main clusters associated to transcriptome muscle differences. These five clusters were related to energy metabolism, cell cycle, gene expression, anatomical structure development and signal transduction/immune response. CONCLUSIONS/SIGNIFICANCE: This study revealed strong transcriptome differences between LM and SM. These results suggest that skeletal muscle discrepancies might arise essentially from different post-natal myogenic activities.

  3. Suppression subtractive hybridization reveals differential gene expression in sunflower grown in high P.

    Science.gov (United States)

    Padmanabhan, Priya; Sahi, Shivendra V

    2011-06-01

    Sunflower (Helianthus annuus L.) is a commercially important oilseed crop. Previous studies proved that this crop is a promising plant species for phytoextraction of excess soil phosphorus (P) because of its superior P accumulating characteristics. Suppression subtractive hybridization (SSH) strategy was employed to isolate and characterize genes that are induced in response to high P in this crop. SSH library was prepared using cDNA generated from plants treated with high P as the 'tester'. Based on the results of dot blot analysis, 360 positive cDNA clones were selected from the SSH library for sequencing. A total of 89 non-redundant expressed sequence tags (ESTs) were identified as high P-responsive genes and they were classified into 6 functional groups. Several genes involved in metabolism showed markedly preferential expression in the library. For further confirmation, thirteen of the representative ESTs were selected from all categories for RT-PCR analysis and the results showed up-regulation of these genes in response to high P-treatment. The gene expression data derived from this study suggested that several of the up-regulated genes identified under high P-treatment might be involved in P-accumulation and tolerance in this plant.

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

    Directory of Open Access Journals (Sweden)

    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

  5. Comparison of gene expression profiles predicting progression in breast cancer patients treated with tamoxifen.

    Science.gov (United States)

    Kok, Marleen; Linn, Sabine C; Van Laar, Ryan K; Jansen, Maurice P H M; van den Berg, Teun M; Delahaye, Leonie J M J; Glas, Annuska M; Peterse, Johannes L; Hauptmann, Michael; Foekens, John A; Klijn, Jan G M; Wessels, Lodewyk F A; Van't Veer, Laura J; Berns, Els M J J

    2009-01-01

    Molecular signatures that predict outcome in tamoxifen treated breast cancer patients have been identified. For the first time, we compared these response profiles in an independent cohort of (neo)adjuvant systemic treatment naïve breast cancer patients treated with first-line tamoxifen for metastatic disease. From a consecutive series of 246 estrogen receptor (ER) positive primary tumors, gene expression profiling was performed on available frozen tumors using 44K oligoarrays (n = 69). A 78-gene tamoxifen response profile (formerly consisting of 81 cDNA-clones), a 21-gene set (microarray-based Recurrence Score), as well as the HOXB13-IL17BR ratio (Two-Gene-Index, RT-PCR) were analyzed. Performance of signatures in relation to time to progression (TTP) was compared with standard immunohistochemical (IHC) markers: ER, progesterone receptor (PgR) and HER2. In univariate analyses, the 78-gene tamoxifen response profile, 21-gene set and HOXB13-IL17BR ratio were all significantly associated with TTP with hazard ratios of 2.2 (95% CI 1.3-3.7, P = 0.005), 2.3 (95% CI 1.3-4.0, P = 0.003) and 4.2 (95% CI 1.4-12.3, P = 0.009), respectively. The concordance among the three classifiers was relatively low, they classified only 45-61% of patients in the same category. In multivariate analyses, the association remained significant for the 78-gene profile and the 21-gene set after adjusting for ER and PgR. The 78-gene tamoxifen response profile, the 21-gene set and the HOXB13-IL17BR ratio were all significantly associated with TTP in an independent patient series treated with tamoxifen. The addition of multigene assays to ER (IHC) improves the prediction of outcome in tamoxifen treated patients and deserves incorporation in future clinical studies.

  6. A hammerhead ribozyme inhibits ADE1 gene expression in yeast.

    Science.gov (United States)

    Ferbeyre, G; Bratty, J; Chen, H; Cedergren, R

    1995-03-21

    To study factors that affect in vivo ribozyme (Rz) activity, a model system has been devised in Saccharomyces cerevisiae based on the inhibition of ADE1 gene expression. This gene was chosen because Rz action can be evaluated visually by the Red phenotype produced when the activity of the gene product is inhibited. Different plasmid constructs allowed the expression of the Rz either in cis or in trans with respect to ADE1. Rz-related inhibition of ADE1 expression was correlated with a Red phenotype and a diminution of ADE1 mRNA levels only when the Rz gene was linked 5' to ADE1. The presence of the expected 3' cleavage fragment was demonstrated using a technique combining RNA ligation and PCR. This yeast system and detection technique are suited to the investigation of general factors affecting Rz-catalyzed inhibition of gene expression under in vivo conditions.

  7. Gene expression and behaviour in mouse models of HD.

    Science.gov (United States)

    Bowles, K R; Brooks, S P; Dunnett, S B; Jones, L

    2012-06-01

    Huntington's disease (HD) is an autosomal dominant neurodegenerative disease, resulting in expansion of the CAG repeat in exon 1 of the HTT gene. The resulting mutant huntingtin protein has been implicated in the disruption of a variety of cellular functions, including transcription. Mouse models of HD have been central to the development of our understanding of gene expression changes in this disease, and are now beginning to elucidate the relationship between gene expression and behaviour. Here, we review current mouse models of HD and their characterisation in terms of gene expression. In addition, we look at how this can inform behaviours observed in mouse models of disease. The relationship between gene expression and behaviour in mouse models of HD is important, as this will further our knowledge of disease progression and its underlying molecular events, highlight new treatment targets, and potentially provide new biomarkers for therapeutic trials. Copyright © 2011 Elsevier Inc. All rights reserved.

  8. Selection and validation of reference genes for quantitative gene expression studies in Erythroxylum coca

    OpenAIRE

    2013-01-01

    Real-time quantitative PCR is a powerful technique for the investigation of comparative gene expression, but its accuracy and reliability depend on the reference genes used as internal standards. Only genes that show a high level of expression stability are suitable for use as reference genes, and these must be identified on a case-by-case basis. Erythroxylum coca produces and accumulates high amounts of the pharmacologically active tropane alkaloid cocaine (especially in the leaves), and is ...

  9. Gene expression profiles of Nitrosomonas europaea, an obligate chemolitotroph

    Energy Technology Data Exchange (ETDEWEB)

    Daniel J. Arp

    2005-05-25

    Nitrosomonas europaea is an aerobic lithoautotrophic bacterium that uses ammonia (NH3) as its energy source. As a nitrifier, it is an important participant in the nitrogen cycle, which can also influence the carbon cycle. The focus of this work was to explore the genetic structure and mechanisms underlying the lithoautotrophic growth style of N. europaea. Whole genome gene expression: The gene expression profile of cells in exponential growth and during starvation was analyzed using microarrays. During growth, 98% of the genes increased in expression at least two fold compared to starvation conditions. In growing cells, approximately 30% of the genes were expressed eight fold higher, Approximately 10% were expressed more than 15 fold higher. Approximately 3% (91 genes) were expressed to more than 20 fold of their levels in starved cells. Carbon fixation gene expression: N. europaea fixes carbon via the Calvin-Benson-Bassham (CBB) cycle via a type I ribulose bisphosphate carboxylase/oxygenase (RubisCO). This study showed that transcription of cbb genes was up-regulated when the carbon source was limited, while amo, hao and other energy harvesting related genes were down-regulated. Iron related gene expression: Because N. europaea has a relatively high content of hemes, sufficient Fe must be available in the medium for it to grow. The genome revealed that approximately 5% of the coding genes in N. europaea are dedicated to Fe transport and assimilation. Nonetheless, with the exception of citrate biosynthesis genes, N. europaea lacks genes for siderophore production. The Fe requirements for growth and the expression of the putative membrane siderophore receptors were determined. The N. europaea genome has over 100 putative genes ({approx}5% of the coding genes) related to Fe uptake and its siderophore receptors could be grouped phylogenetically in four clusters. Fe related genes, such as a number of TonB-dependent Fe-siderophore receptors for ferrichrome and

  10. Gene expression profiles of Nitrosomonas europaea, an obligate chemolitotroph

    Energy Technology Data Exchange (ETDEWEB)

    Daniel J Arp

    2005-06-15

    Nitrosomonas europaea is an aerobic lithoautotrophic bacterium that uses ammonia (NH3) as its energy source. As a nitrifier, it is an important participant in the nitrogen cycle, which can also influence the carbon cycle. The focus of this work was to explore the genetic structure and mechanisms underlying the lithoautotrophic growth style of N. europaea. Whole genome gene expression. The gene expression profile of cells in exponential growth and during starvation was analyzed using microarrays. During growth, 98% of the genes increased in expression at least two fold compared to starvation conditions. In growing cells, approximately 30% of the genes were expressed eight fold higher, Approximately 10% were expressed more than 15 fold higher. Approximately 3% (91 genes) were expressed to more than 20 fold of their levels in starved cells. Carbon fixation gene expression. N. europaea fixes carbon via the Calvin-Benson-Bassham (CBB) cycle via a type I ribulose bisphosphate carboxylase/oxygenase (RubisCO). This study showed that transcription of cbb genes was up-regulated when the carbon source was limited, while amo, hao and other energy harvesting related genes were down-regulated. Iron related gene expression. Because N. europaea has a relatively high content of hemes, sufficient Fe must be available in the medium for it to grow. The genome revealed that approximately 5% of the coding genes in N. europaea are dedicated to Fe transport and assimilation. Nonetheless, with the exception of citrate biosynthesis genes, N. europaea lacks genes for siderophore production. The Fe requirements for growth and the expression of the putative membrane siderophore receptors were determined. The N. europaea genome has over 100 putative genes ({approx}5% of the coding genes) related to Fe uptake and its siderophore receptors could be grouped phylogenetically in four clusters. Fe related genes, such as a number of TonB-dependent Fe-siderophore receptors for ferrichrome and

  11. 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.

  12. 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.

  13. Gene expression profiling predicts the development of oral cancer.

    Science.gov (United States)

    Saintigny, Pierre; Zhang, Li; Fan, You-Hong; El-Naggar, Adel K; Papadimitrakopoulou, Vassiliki A; Feng, Lei; Lee, J Jack; Kim, Edward S; Ki Hong, Waun; Mao, Li

    2011-02-01

    Patients with oral premalignant lesion (OPL) have a high risk of developing oral cancer. Although certain risk factors, such as smoking status and histology, are known, our ability to predict oral cancer risk remains poor. The study objective was to determine the value of gene expression profiling in predicting oral cancer development. Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. The median follow-up time was 6.08 years and 35 of the 86 patients developed oral cancer over the course. Gene expression profiles were associated with oral cancer-free survival and used to develop multivariate predictive models for oral cancer prediction. We developed a 29-transcript predictive model which showed marked improvement in terms of prediction accuracy (with 8% predicting error rate) over the models using previously known clinicopathologic risk factors. On the basis of the gene expression profile data, we also identified 2,182 transcripts significantly associated with oral cancer risk-associated genes (P value oral cancer risk. In multiple independent data sets, the expression profiles of the genes can differentiate head and neck cancer from normal mucosa. Our results show that gene expression profiles may improve the prediction of oral cancer risk in OPL patients and the significant genes identified may serve as potential targets for oral cancer chemoprevention. ©2011 AACR.

  14. On-Chip Integration of Cell-Free Gene Expression

    Science.gov (United States)

    Buxboim, Amnon; Morpurgo, Margherita; Bar-Dagan, Maya; Frydman, Veronica; Zbaida, David; Bar-Ziv, Roy

    2006-03-01

    We present a synthetic approach for the study of gene networks in vitro which is complementary to traditional in vivo methodologies. We have developed a technology for submicron integration of functional genes and on-chip protein synthesis using a cell-free transcription/translation system. The interaction between genes is facilitated by diffusion of on-chip gene expression products from `source' genes towards `acceptor' genes. Our technology is simple and inexpensive and can serve as an improved platform for a wide variety of protein and DNA biochip applications.

  15. A Marfan syndrome gene expression phenotype in cultured skin fibroblasts

    Directory of Open Access Journals (Sweden)

    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.

  16. A Marfan syndrome gene expression phenotype in cultured skin fibroblasts

    Science.gov (United States)

    Yao, Zizhen; Jaeger, Jochen C; Ruzzo, Walter L; Morale, Cecile Z; Emond, Mary; Francke, Uta; Milewicz, Dianna M; Schwartz, Stephen M; Mulvihill, Eileen R

    2007-01-01

    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 < 3 × 10-6 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. PMID:17850668

  17. Immune response gene expression increases in the aging murine hippocampus.

    Science.gov (United States)

    Terao, Akira; Apte-Deshpande, Anjali; Dousman, Linda; Morairty, Stephen; Eynon, Barrett P; Kilduff, Thomas S; Freund, Yvonne R

    2002-11-01

    Using GeneChips, basal and lipopolysaccharide (LPS)-induced