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Sample records for based gene expression

  1. Correlation-based linear discriminant classification for gene expression data.

    Science.gov (United States)

    Pan, M; Zhang, J

    2017-01-23

    Microarray gene expression technology provides a systematic approach to patient classification. However, microarray data pose a great computational challenge owing to their large dimensionality, small sample sizes, and potential correlations among genes. A recent study has shown that gene-gene correlations have a positive effect on the accuracy of classification models, in contrast to some previous results. In this study, a recently developed correlation-based classifier, the ensemble of random subspace (RS) Fisher linear discriminants (FLDs), was utilized. The impact of gene-gene correlations on the performance of this classifier and other classifiers was studied using simulated datasets and real datasets. A cross-validation framework was used to evaluate the performance of each classifier using the simulated datasets or real datasets, and misclassification rates (MRs) were computed. Using the simulated data, the average MRs of the correlation-based classifiers decreased as the correlations increased when there were more correlated genes. Using real data, the correlation-based classifiers outperformed the non-correlation-based classifiers, especially when the gene-gene correlations were high. The ensemble RS-FLD classifier is a potential state-of-the-art computational method. The correlation-based ensemble RS-FLD classifier was effective and benefited from gene-gene correlations, particularly when the correlations were high.

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

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    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.

  3. Gene expression

    International Nuclear Information System (INIS)

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

    1983-01-01

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

  4. A Fisheye Viewer for microarray-based gene expression data.

    Science.gov (United States)

    Wu, Min; Thao, Cheng; Mu, Xiangming; Munson, Ethan V

    2006-10-13

    Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface--an electronic table (E-table) that uses fisheye distortion technology. The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site http://polaris.imt.uwm.edu:7777/fisheye/. The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table.

  5. A fisheye viewer for microarray-based gene expression data

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    Munson Ethan V

    2006-10-01

    Full Text Available Abstract Background Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface – an electronic table (E-table that uses fisheye distortion technology. Results The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site http://polaris.imt.uwm.edu:7777/fisheye/. The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. Conclusion This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table.

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

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    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.

  7. Gene-Expression Profiles in Generalized Aggressive Periodontitis: A Gene Network-Based Microarray Analysis.

    Science.gov (United States)

    Guzeldemir-Akcakanat, Esra; Sunnetci-Akkoyunlu, Deniz; Orucguney, Begum; Cine, Naci; Kan, Bahadır; Yılmaz, Elif Büsra; Gümüşlü, Esen; Savli, Hakan

    2016-01-01

    In this study, molecular biomarkers that play a role in the development of generalized aggressive periodontitis (GAgP) are investigated using gingival tissue samples through omics-based whole-genome transcriptomics while using healthy individuals as background controls. Gingival tissue biopsies from 23 patients with GAgP and 25 healthy individuals were analyzed using gene-expression microarrays with network and pathway analyses to identify gene-expression patterns. To substantiate the results of the microarray studies, real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was performed to assess the messenger RNA (mRNA) expression of MZB1 and DSC1. The microarrays and qRT-PCR resulted in similar gene-expression changes, confirming the reliability of the microarray results at the mRNA level. As a result of the gene-expression microarray studies, four significant gene networks were identified. The most upregulated genes were found as MZB1, TNFRSF17, PNOC, FCRL5, LAX1, BMS1P20, IGLL5, MMP7, SPAG4, and MEI1; the most downregulated genes were found as LOR, LAMB4, AADACL2, MAPT, ARG1, NPR3, AADAC, DSC1, LRRC4, and CHP2. Functions of the identified genes that were involved in gene networks were cellular development, cell growth and proliferation, cellular movement, cell-cell signaling and interaction, humoral immune response, protein synthesis, cell death and survival, cell population and organization, organismal injury and abnormalities, molecular transport, and small-molecule biochemistry. The data suggest new networks that have important functions as humoral immune response and organismal injury/abnormalities. Future analyses may facilitate proteomic profiling analyses to identify gene-expression patterns related to clinical outcome.

  8. Nearest Neighbor Networks: clustering expression data based on gene neighborhoods

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    Olszewski Kellen L

    2007-07-01

    Full Text Available Abstract Background The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both individual biological pathways and the integrated workings of the cell. However, translating this amount of data into biological insight remains a daunting task. An important initial step in the analysis of microarray data is clustering of genes with similar behavior. A number of classical techniques are commonly used to perform this task, particularly hierarchical and K-means clustering, and many novel approaches have been suggested recently. While these approaches are useful, they are not without drawbacks; these methods can find clusters in purely random data, and even clusters enriched for biological functions can be skewed towards a small number of processes (e.g. ribosomes. Results We developed Nearest Neighbor Networks (NNN, a graph-based algorithm to generate clusters of genes with similar expression profiles. This method produces clusters based on overlapping cliques within an interaction network generated from mutual nearest neighborhoods. This focus on nearest neighbors rather than on absolute distance measures allows us to capture clusters with high connectivity even when they are spatially separated, and requiring mutual nearest neighbors allows genes with no sufficiently similar partners to remain unclustered. We compared the clusters generated by NNN with those generated by eight other clustering methods. NNN was particularly successful at generating functionally coherent clusters with high precision, and these clusters generally represented a much broader selection of biological processes than those recovered by other methods. Conclusion The Nearest Neighbor Networks algorithm is a valuable clustering method that effectively groups genes that are likely to be functionally related. It is particularly attractive due to its simplicity, its success in the

  9. Modified gateway system for double shRNA expression and Cre/lox based gene expression

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    Leung Lisa

    2011-03-01

    Full Text Available Abstract Background The growing need for functional studies of genes has set the stage for the development of versatile tools for genetic manipulations. Results Aiming to provide tools for high throughput analysis of gene functions, we have developed a modified short hairpin RNA (shRNA and gene expression system based on Gateway Technology. The system contains a series of entry and destination vectors that enables easy transfer of shRNA or cDNA into lentiviral expression systems with a variety of selection or marker genes (i.e. puromycin, hygromycin, green fluorescent protein-EGFP, yellow fluorescent protein-YFP and red fluorescent protein-dsRed2. Our shRNA entry vector pENTR.hU6.hH1 containing two tandem human shRNA expression promoters, H1 and U6, was capable of co-expressing two shRNA sequences simultaneously. The entry vector for gene overexpression, pENTR.CMV.ON was constructed to contain CMV promoter with a multiple cloning site flanked by loxP sites allowing for subsequent Cre/lox recombination. Both shRNA and cDNA expression vectors also contained attL sites necessary for recombination with attR sites in our destination expression vectors. As proof of principle we demonstrate the functionality and efficiency of this system by testing expression of several cDNA and shRNA sequences in a number of cell lines. Conclusion Our system is a valuable addition to already existing library of Gateway based vectors and can be an essential tool for many aspects of gene functional studies.

  10. Modified gateway system for double shRNA expression and Cre/lox based gene expression.

    Science.gov (United States)

    Radulovich, Nikolina; Leung, Lisa; Tsao, Ming-Sound

    2011-03-22

    The growing need for functional studies of genes has set the stage for the development of versatile tools for genetic manipulations. Aiming to provide tools for high throughput analysis of gene functions, we have developed a modified short hairpin RNA (shRNA) and gene expression system based on Gateway Technology. The system contains a series of entry and destination vectors that enables easy transfer of shRNA or cDNA into lentiviral expression systems with a variety of selection or marker genes (i.e. puromycin, hygromycin, green fluorescent protein-EGFP, yellow fluorescent protein-YFP and red fluorescent protein-dsRed2). Our shRNA entry vector pENTR.hU6.hH1 containing two tandem human shRNA expression promoters, H1 and U6, was capable of co-expressing two shRNA sequences simultaneously. The entry vector for gene overexpression, pENTR.CMV.ON was constructed to contain CMV promoter with a multiple cloning site flanked by loxP sites allowing for subsequent Cre/lox recombination. Both shRNA and cDNA expression vectors also contained attL sites necessary for recombination with attR sites in our destination expression vectors. As proof of principle we demonstrate the functionality and efficiency of this system by testing expression of several cDNA and shRNA sequences in a number of cell lines. Our system is a valuable addition to already existing library of Gateway based vectors and can be an essential tool for many aspects of gene functional studies.

  11. Finding gene regulatory network candidates using the gene expression knowledge base.

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    Venkatesan, Aravind; Tripathi, Sushil; Sanz de Galdeano, Alejandro; Blondé, Ward; Lægreid, Astrid; Mironov, Vladimir; Kuiper, Martin

    2014-12-10

    Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

  12. Embryo quality predictive models based on cumulus cells gene expression

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    Devjak R

    2016-06-01

    Full Text Available Since the introduction of in vitro fertilization (IVF in clinical practice of infertility treatment, the indicators for high quality embryos were investigated. Cumulus cells (CC have a specific gene expression profile according to the developmental potential of the oocyte they are surrounding, and therefore, specific gene expression could be used as a biomarker. The aim of our study was to combine more than one biomarker to observe improvement in prediction value of embryo development. In this study, 58 CC samples from 17 IVF patients were analyzed. This study was approved by the Republic of Slovenia National Medical Ethics Committee. Gene expression analysis [quantitative real time polymerase chain reaction (qPCR] for five genes, analyzed according to embryo quality level, was performed. Two prediction models were tested for embryo quality prediction: a binary logistic and a decision tree model. As the main outcome, gene expression levels for five genes were taken and the area under the curve (AUC for two prediction models were calculated. Among tested genes, AMHR2 and LIF showed significant expression difference between high quality and low quality embryos. These two genes were used for the construction of two prediction models: the binary logistic model yielded an AUC of 0.72 ± 0.08 and the decision tree model yielded an AUC of 0.73 ± 0.03. Two different prediction models yielded similar predictive power to differentiate high and low quality embryos. In terms of eventual clinical decision making, the decision tree model resulted in easy-to-interpret rules that are highly applicable in clinical practice.

  13. Density based pruning for identification of differentially expressed genes from microarray data

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    Xu Jia

    2010-11-01

    Full Text Available Abstract Motivation Identification of differentially expressed genes from microarray datasets is one of the most important analyses for microarray data mining. Popular algorithms such as statistical t-test rank genes based on a single statistics. The false positive rate of these methods can be improved by considering other features of differentially expressed genes. Results We proposed a pattern recognition strategy for identifying differentially expressed genes. Genes are mapped to a two dimension feature space composed of average difference of gene expression and average expression levels. A density based pruning algorithm (DB Pruning is developed to screen out potential differentially expressed genes usually located in the sparse boundary region. Biases of popular algorithms for identifying differentially expressed genes are visually characterized. Experiments on 17 datasets from Gene Omnibus Database (GEO with experimentally verified differentially expressed genes showed that DB pruning can significantly improve the prediction accuracy of popular identification algorithms such as t-test, rank product, and fold change. Conclusions Density based pruning of non-differentially expressed genes is an effective method for enhancing statistical testing based algorithms for identifying differentially expressed genes. It improves t-test, rank product, and fold change by 11% to 50% in the numbers of identified true differentially expressed genes. The source code of DB pruning is freely available on our website http://mleg.cse.sc.edu/degprune

  14. Locally linear embedding and neighborhood rough set-based gene selection for gene expression data classification.

    Science.gov (United States)

    Sun, L; Xu, J-C; Wang, W; Yin, Y

    2016-08-30

    Cancer subtype recognition and feature selection are important problems in the diagnosis and treatment of tumors. Here, we propose a novel gene selection approach applied to gene expression data classification. First, two classical feature reduction methods including locally linear embedding (LLE) and rough set (RS) are summarized. The advantages and disadvantages of these algorithms were analyzed and an optimized model for tumor gene selection was developed based on LLE and neighborhood RS (NRS). Bhattacharyya distance was introduced to delete irrelevant genes, pair-wise redundant analysis was performed to remove strongly correlated genes, and the wavelet soft threshold was determined to eliminate noise in the gene datasets. Next, prior optimized search processing was carried out. A new approach combining dimension reduction of LLE and feature reduction of NRS (LLE-NRS) was developed for selecting gene subsets, and then an open source software Weka was applied to distinguish different tumor types and verify the cross-validation classification accuracy of our proposed method. The experimental results demonstrated that the classification performance of the proposed LLE-NRS for selecting gene subset outperforms those of other related models in terms of accuracy, and our proposed approach is feasible and effective in the field of high-dimensional tumor classification.

  15. gene structure, gene expression

    Indian Academy of Sciences (India)

    and seedling leaves were sampled at 6 h after the treatment. For cold stress, the seedlings were transferred to 4◦C growth chamber for 30 min. Control seedlings were exposed to none of these treatments. To examine the expression patterns of these predicted genes in Poplar and to further confirm their stress responsive-.

  16. The gene expression data of Mycobacterium tuberculosis based on Affymetrix gene chips provide insight into regulatory and hypothetical genes

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    Fu-Liu Casey S

    2007-05-01

    Full Text Available Abstract Background Tuberculosis remains a leading infectious disease with global public health threat. Its control and management have been complicated by multi-drug resistance and latent infection, which prompts scientists to find new and more effective drugs. With the completion of the genome sequence of the etiologic bacterium, Mycobacterium tuberculosis, it is now feasible to search for new drug targets by sieving through a large number of gene products and conduct genome-scale experiments based on microarray technology. However, the full potential of genome-wide microarray analysis in configuring interrelationships among all genes in M. tuberculosis has yet to be realized. To date, it is only possible to assign a function to 52% of proteins predicted in the genome. Results We conducted a functional-genomics study using the high-resolution Affymetrix oligonucleotide GeneChip. Approximately one-half of the genes were found to be always expressed, including more than 100 predicted conserved hypotheticals, in the genome of M. tuberculosis during the log phase of in vitro growth. The gene expression profiles were analyzed and visualized through cluster analysis to epitomize the full details of genomic behavior. Broad patterns derived from genome-wide expression experiments in this study have provided insight into the interrelationships among genes in the basic cellular processes of M. tuberculosis. Conclusion Our results have confirmed several known gene clusters in energy production, information pathways, and lipid metabolism, and also hinted at potential roles of hypothetical and regulatory proteins.

  17. A Model-Based Joint Identification of Differentially Expressed Genes and Phenotype-Associated Genes.

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    Samuel Sunghwan Cho

    Full Text Available Over the last decade, many analytical methods and tools have been developed for microarray data. The detection of differentially expressed genes (DEGs among different treatment groups is often a primary purpose of microarray data analysis. In addition, association studies investigating the relationship between genes and a phenotype of interest such as survival time are also popular in microarray data analysis. Phenotype association analysis provides a list of phenotype-associated genes (PAGs. However, it is sometimes necessary to identify genes that are both DEGs and PAGs. We consider the joint identification of DEGs and PAGs in microarray data analyses. The first approach we used was a naïve approach that detects DEGs and PAGs separately and then identifies the genes in an intersection of the list of PAGs and DEGs. The second approach we considered was a hierarchical approach that detects DEGs first and then chooses PAGs from among the DEGs or vice versa. In this study, we propose a new model-based approach for the joint identification of DEGs and PAGs. Unlike the previous two-step approaches, the proposed method identifies genes simultaneously that are DEGs and PAGs. This method uses standard regression models but adopts different null hypothesis from ordinary regression models, which allows us to perform joint identification in one-step. The proposed model-based methods were evaluated using experimental data and simulation studies. The proposed methods were used to analyze a microarray experiment in which the main interest lies in detecting genes that are both DEGs and PAGs, where DEGs are identified between two diet groups and PAGs are associated with four phenotypes reflecting the expression of leptin, adiponectin, insulin-like growth factor 1, and insulin. Model-based approaches provided a larger number of genes, which are both DEGs and PAGs, than other methods. Simulation studies showed that they have more power than other methods

  18. Human Kidney Tubule-Specific Gene Expression Based Dissection of Chronic Kidney Disease Traits

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    Pazit Beckerman

    2017-10-01

    We concluded that gene expression is a very sensitive sensor of fibrosis, as the expression of 1654 genes correlated with fibrosis even after adjusting to eGFR and other clinical parameters. The association between GFR and gene expression was mostly mediated by fibrosis. In conclusion, our transcriptome-based CKD trait dissection analysis suggests that the association between gene expression and renal function is mediated by structural changes and that there may be differences in pathways that lead to decline in kidney function and the development of fibrosis, respectively.

  19. 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...

  20. Single base resolution analysis of 5-hydroxymethylcytosine in 188 human genes: implications for hepatic gene expression

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    Ivanov, Maxim; Kals, Mart; Lauschke, Volker; Barragan, Isabel; Ewels, Philip; Käller, Max; Axelsson, Tomas; Lehtiö, Janne; Milani, Lili; Ingelman-Sundberg, Magnus

    2016-01-01

    To improve the epigenomic analysis of tissues rich in 5-hydroxymethylcytosine (hmC), we developed a novel protocol called TAB-Methyl-SEQ, which allows for single base resolution profiling of both hmC and 5-methylcytosine by targeted next-generation sequencing. TAB-Methyl-SEQ data were extensively validated by a set of five methodologically different protocols. Importantly, these extensive cross-comparisons revealed that protocols based on Tet1-assisted bisulfite conversion provided more precise hmC values than TrueMethyl-based methods. A total of 109 454 CpG sites were analyzed by TAB-Methyl-SEQ for mC and hmC in 188 genes from 20 different adult human livers. We describe three types of variability of hepatic hmC profiles: (i) sample-specific variability at 40.8% of CpG sites analyzed, where the local hmC values correlate to the global hmC content of livers (measured by LC-MS), (ii) gene-specific variability, where hmC levels in the coding regions positively correlate to expression of the respective gene and (iii) site-specific variability, where prominent hmC peaks span only 1 to 3 neighboring CpG sites. Our data suggest that both the gene- and site-specific components of hmC variability might contribute to the epigenetic control of hepatic genes. The protocol described here should be useful for targeted DNA analysis in a variety of applications. PMID:27131363

  1. Design-Based Learning for Biology: Genetic Engineering Experience Improves Understanding of Gene Expression

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    Ellefson, Michelle R.; Brinker, Rebecca A.; Vernacchio, Vincent J.; Schunn, Christian D.

    2008-01-01

    Gene expression is a difficult topic for students to learn and comprehend, at least partially because it involves various biochemical structures and processes occurring at the microscopic level. Designer Bacteria, a design-based learning (DBL) unit for high-school students, applies principles of DBL to the teaching of gene expression. Throughout…

  2. 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.

  3. Inferring nonlinear gene regulatory networks from gene expression data based on distance correlation.

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    Xiaobo Guo

    Full Text Available Nonlinear dependence is general in regulation mechanism of gene regulatory networks (GRNs. It is vital to properly measure or test nonlinear dependence from real data for reconstructing GRNs and understanding the complex regulatory mechanisms within the cellular system. A recently developed measurement called the distance correlation (DC has been shown powerful and computationally effective in nonlinear dependence for many situations. In this work, we incorporate the DC into inferring GRNs from the gene expression data without any underling distribution assumptions. We propose three DC-based GRNs inference algorithms: CLR-DC, MRNET-DC and REL-DC, and then compare them with the mutual information (MI-based algorithms by analyzing two simulated data: benchmark GRNs from the DREAM challenge and GRNs generated by SynTReN network generator, and an experimentally determined SOS DNA repair network in Escherichia coli. According to both the receiver operator characteristic (ROC curve and the precision-recall (PR curve, our proposed algorithms significantly outperform the MI-based algorithms in GRNs inference.

  4. Gene Expression Based Leukemia Sub-Classification Using Committee Neural Networks

    OpenAIRE

    Sewak, Mihir S.; Reddy, Narender P.; Duan, Zhong-Hui

    2009-01-01

    Analysis of gene expression data provides an objective and efficient technique for sub‑classification of leukemia. The purpose of the present study was to design a committee neural networks based classification systems to subcategorize leukemia gene expression data. In the study, a binary classification system was considered to differentiate acute lymphoblastic leukemia from acute myeloid leukemia. A ternary classification system which classifies leukemia expression data into three subclasses...

  5. Screening key genes for abdominal aortic aneurysm based on gene expression omnibus dataset.

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    Wan, Li; Huang, Jingyong; Ni, Haizhen; Yu, Guanfeng

    2018-02-13

    Abdominal aortic aneurysm (AAA) is a common cardiovascular system disease with high mortality. The aim of this study was to identify potential genes for diagnosis and therapy in AAA. We searched and downloaded mRNA expression data from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) from AAA and normal individuals. Then, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, transcriptional factors (TFs) network and protein-protein interaction (PPI) network were used to explore the function of genes. Additionally, immunohistochemical (IHC) staining was used to validate the expression of identified genes. Finally, the diagnostic value of identified genes was accessed by receiver operating characteristic (ROC) analysis in GEO database. A total of 1199 DEGs (188 up-regulated and 1011 down-regulated) were identified between AAA and normal individual. KEGG pathway analysis displayed that vascular smooth muscle contraction and pathways in cancer were significantly enriched signal pathway. The top 10 up-regulated and top 10 down-regulated DEGs were used to construct TFs and PPI networks. Some genes with high degrees such as NELL2, CCR7, MGAM, HBB, CSNK2A2, ZBTB16 and FOXO1 were identified to be related to AAA. The consequences of IHC staining showed that CCR7 and PDGFA were up-regulated in tissue samples of AAA. ROC analysis showed that NELL2, CCR7, MGAM, HBB, CSNK2A2, ZBTB16, FOXO1 and PDGFA had the potential diagnostic value for AAA. The identified genes including NELL2, CCR7, MGAM, HBB, CSNK2A2, ZBTB16, FOXO1 and PDGFA might be involved in the pathology of AAA.

  6. Comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates.

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    Liu, Fang; Jenssen, Tor-Kristian; Trimarchi, Jeff; Punzo, Claudio; Cepko, Connie L; Ohno-Machado, Lucila; Hovig, Eivind; Kuo, Winston Patrick

    2007-06-07

    High-throughput systems for gene expression profiling have been developed and have matured rapidly through the past decade. Broadly, these can be divided into two categories: hybridization-based and sequencing-based approaches. With data from different technologies being accumulated, concerns and challenges are raised about the level of agreement across technologies. As part of an ongoing large-scale cross-platform data comparison framework, we report here a comparison based on identical samples between one-dye DNA microarray platforms and MPSS (Massively Parallel Signature Sequencing). The DNA microarray platforms generally provided highly correlated data, while moderate correlations between microarrays and MPSS were obtained. Disagreements between the two types of technologies can be attributed to limitations inherent to both technologies. The variation found between pooled biological replicates underlines the importance of exercising caution in identification of differential expression, especially for the purposes of biomarker discovery. Based on different principles, hybridization-based and sequencing-based technologies should be considered complementary to each other, rather than competitive alternatives for measuring gene expression, and currently, both are important tools for transcriptome profiling.

  7. Comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates

    Directory of Open Access Journals (Sweden)

    Cepko Connie L

    2007-06-01

    Full Text Available Abstract Background High-throughput systems for gene expression profiling have been developed and have matured rapidly through the past decade. Broadly, these can be divided into two categories: hybridization-based and sequencing-based approaches. With data from different technologies being accumulated, concerns and challenges are raised about the level of agreement across technologies. As part of an ongoing large-scale cross-platform data comparison framework, we report here a comparison based on identical samples between one-dye DNA microarray platforms and MPSS (Massively Parallel Signature Sequencing. Results The DNA microarray platforms generally provided highly correlated data, while moderate correlations between microarrays and MPSS were obtained. Disagreements between the two types of technologies can be attributed to limitations inherent to both technologies. The variation found between pooled biological replicates underlines the importance of exercising caution in identification of differential expression, especially for the purposes of biomarker discovery. Conclusion Based on different principles, hybridization-based and sequencing-based technologies should be considered complementary to each other, rather than competitive alternatives for measuring gene expression, and currently, both are important tools for transcriptome profiling.

  8. Human Kidney Tubule-Specific Gene Expression Based Dissection of Chronic Kidney Disease Traits.

    Science.gov (United States)

    Beckerman, Pazit; Qiu, Chengxiang; Park, Jihwan; Ledo, Nora; Ko, Yi-An; Park, Ae-Seo Deok; Han, Sang-Youb; Choi, Peter; Palmer, Matthew; Susztak, Katalin

    2017-10-01

    Chronic kidney disease (CKD) has diverse phenotypic manifestations including structural (such as fibrosis) and functional (such as glomerular filtration rate and albuminuria) alterations. Gene expression profiling has recently gained popularity as an important new tool for precision medicine approaches. Here we used unbiased and directed approaches to understand how gene expression captures different CKD manifestations in patients with diabetic and hypertensive CKD. Transcriptome data from ninety-five microdissected human kidney samples with a range of demographics, functional and structural changes were used for the primary analysis. Data obtained from 41 samples were available for validation. Using the unbiased Weighted Gene Co-Expression Network Analysis (WGCNA) we identified 16 co-expressed gene modules. We found that modules that strongly correlated with eGFR primarily encoded genes with metabolic functions. Gene groups that mainly encoded T-cell receptor and collagen pathways, showed the strongest correlation with fibrosis level, suggesting that these two phenotypic manifestations might have different underlying mechanisms. Linear regression models were then used to identify genes whose expression showed significant correlation with either structural (fibrosis) or functional (eGFR) manifestation and mostly corroborated the WGCNA findings. We concluded that gene expression is a very sensitive sensor of fibrosis, as the expression of 1654 genes correlated with fibrosis even after adjusting to eGFR and other clinical parameters. The association between GFR and gene expression was mostly mediated by fibrosis. In conclusion, our transcriptome-based CKD trait dissection analysis suggests that the association between gene expression and renal function is mediated by structural changes and that there may be differences in pathways that lead to decline in kidney function and the development of fibrosis, respectively. Copyright © 2017 The Authors. Published by

  9. Gene expression and gene therapy imaging

    International Nuclear Information System (INIS)

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

    2007-01-01

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

  10. A family-based test for correlation between gene expression and trait values.

    Science.gov (United States)

    Kraft, Peter; Schadt, Eric; Aten, Jason; Horvath, Steve

    2003-05-01

    Advances in microarray technology have made it attractive to combine information on clinical traits, marker genotypes, and comprehensive gene expression from family studies to dissect complex disease genetics. Without accounting for family structure, methods that test for association between a trait and gene-expression levels can be misleading. We demonstrate that the standard unstratified test based on Pearson's correlation coefficient can produce spurious results when applied to family data, and we present a stratified family expression association test (FEXAT). We illustrate the utility of the FEXAT via simulation and an application to gene-expression data from lymphoblastoid cell lines from four CEPH families. The FEXAT has a smaller estimated false-discovery rate than the standard test when within-family correlations are of interest, and it detects biologically plausible correlations between beta catenin and genes in the WNT-activation pathway in humans that the standard test does not.

  11. A DNA vector-based RNAi technology to suppress gene expression in mammalian cells.

    Science.gov (United States)

    Sui, Guangchao; Soohoo, Christina; Affar, El Bachir; Gay, Frédérique; Shi, Yujiang; Forrester, William C; Shi, Yang

    2002-04-16

    Double-stranded RNA-mediated interference (RNAi) has recently emerged as a powerful reverse genetic tool to silence gene expression in multiple organisms including plants, Caenorhabditis elegans, and Drosophila. The discovery that synthetic double-stranded, 21-nt small interfering RNA triggers gene-specific silencing in mammalian cells has further expanded the utility of RNAi into mammalian systems. Here we report a technology that allows synthesis of small interfering RNAs from DNA templates in vivo to efficiently inhibit endogenous gene expression. Significantly, we were able to use this approach to demonstrate, in multiple cell lines, robust inhibition of several endogenous genes of diverse functions. These findings highlight the general utility of this DNA vector-based RNAi technology in suppressing gene expression in mammalian cells.

  12. A robust approach based on Weibull distribution for clustering gene expression data

    Directory of Open Access Journals (Sweden)

    Gong Binsheng

    2011-05-01

    Full Text Available Abstract Background Clustering is a widely used technique for analysis of gene expression data. Most clustering methods group genes based on the distances, while few methods group genes according to the similarities of the distributions of the gene expression levels. Furthermore, as the biological annotation resources accumulated, an increasing number of genes have been annotated into functional categories. As a result, evaluating the performance of clustering methods in terms of the functional consistency of the resulting clusters is of great interest. Results In this paper, we proposed the WDCM (Weibull Distribution-based Clustering Method, a robust approach for clustering gene expression data, in which the gene expressions of individual genes are considered as the random variables following unique Weibull distributions. Our WDCM is based on the concept that the genes with similar expression profiles have similar distribution parameters, and thus the genes are clustered via the Weibull distribution parameters. We used the WDCM to cluster three cancer gene expression data sets from the lung cancer, B-cell follicular lymphoma and bladder carcinoma and obtained well-clustered results. We compared the performance of WDCM with k-means and Self Organizing Map (SOM using functional annotation information given by the Gene Ontology (GO. The results showed that the functional annotation ratios of WDCM are higher than those of the other methods. We also utilized the external measure Adjusted Rand Index to validate the performance of the WDCM. The comparative results demonstrate that the WDCM provides the better clustering performance compared to k-means and SOM algorithms. The merit of the proposed WDCM is that it can be applied to cluster incomplete gene expression data without imputing the missing values. Moreover, the robustness of WDCM is also evaluated on the incomplete data sets. Conclusions The results demonstrate that our WDCM produces clusters

  13. Analyzing Plasmodium falciparum erythrocyte membrane protein 1 gene expression by a next generation sequencing based method

    DEFF Research Database (Denmark)

    Jespersen, Jakob S.; Petersen, Bent; Seguin-Orlando, Andaine

    2013-01-01

    at identifying PfEMP1 features associated with high virulence. Here we present the first effective method for sequence analysis of var genes expressed in field samples: a sequential PCR and next generation sequencing based technique applied on expressed var sequence tags and subsequently on long range PCR......, encoded by ~60 highly variable 'var' genes per haploid genome. PfEMP1 is exported to the surface of infected erythrocytes and is thought to be fundamental to immune evasion by adhesion to host and parasite factors. The highly variable nature has constituted a roadblock in var expression studies aimed...

  14. A network-based gene expression signature informs prognosis and treatment for colorectal cancer patients.

    Directory of Open Access Journals (Sweden)

    Mingguang Shi

    Full Text Available Several studies have reported gene expression signatures that predict recurrence risk in stage II and III colorectal cancer (CRC patients with minimal gene membership overlap and undefined biological relevance. The goal of this study was to investigate biological themes underlying these signatures, to infer genes of potential mechanistic importance to the CRC recurrence phenotype and to test whether accurate prognostic models can be developed using mechanistically important genes.We investigated eight published CRC gene expression signatures and found no functional convergence in Gene Ontology enrichment analysis. Using a random walk-based approach, we integrated these signatures and publicly available somatic mutation data on a protein-protein interaction network and inferred 487 genes that were plausible candidate molecular underpinnings for the CRC recurrence phenotype. We named the list of 487 genes a NEM signature because it integrated information from Network, Expression, and Mutation. The signature showed significant enrichment in four biological processes closely related to cancer pathophysiology and provided good coverage of known oncogenes, tumor suppressors, and CRC-related signaling pathways. A NEM signature-based Survival Support Vector Machine prognostic model was trained using a microarray gene expression dataset and tested on an independent dataset. The model-based scores showed a 75.7% concordance with the real survival data and separated patients into two groups with significantly different relapse-free survival (p = 0.002. Similar results were obtained with reversed training and testing datasets (p = 0.007. Furthermore, adjuvant chemotherapy was significantly associated with prolonged survival of the high-risk patients (p = 0.006, but not beneficial to the low-risk patients (p = 0.491.The NEM signature not only reflects CRC biology but also informs patient prognosis and treatment response. Thus, the network-based

  15. Cytomegalovirus replicon-based regulation of gene expression in vitro and in vivo.

    Directory of Open Access Journals (Sweden)

    Hermine Mohr

    Full Text Available There is increasing evidence for a connection between DNA replication and the expression of adjacent genes. Therefore, this study addressed the question of whether a herpesvirus origin of replication can be used to activate or increase the expression of adjacent genes. Cell lines carrying an episomal vector, in which reporter genes are linked to the murine cytomegalovirus (MCMV origin of lytic replication (oriLyt, were constructed. Reporter gene expression was silenced by a histone-deacetylase-dependent mechanism, but was resolved upon lytic infection with MCMV. Replication of the episome was observed subsequent to infection, leading to the induction of gene expression by more than 1000-fold. oriLyt-based regulation thus provided a unique opportunity for virus-induced conditional gene expression without the need for an additional induction mechanism. This principle was exploited to show effective late trans-complementation of the toxic viral protein M50 and the glycoprotein gO of MCMV. Moreover, the application of this principle for intracellular immunization against herpesvirus infection was demonstrated. The results of the present study show that viral infection specifically activated the expression of a dominant-negative transgene, which inhibited viral growth. This conditional system was operative in explant cultures of transgenic mice, but not in vivo. Several applications are discussed.

  16. Hessian regularization based non-negative matrix factorization for gene expression data clustering.

    Science.gov (United States)

    Liu, Xiao; Shi, Jun; Wang, Congzhi

    2015-01-01

    Since a key step in the analysis of gene expression data is to detect groups of genes that have similar expression patterns, clustering technique is then commonly used to analyze gene expression data. Data representation plays an important role in clustering analysis. The non-negative matrix factorization (NMF) is a widely used data representation method with great success in machine learning. Although the traditional manifold regularization method, Laplacian regularization (LR), can improve the performance of NMF, LR still suffers from the problem of its weak extrapolating power. Hessian regularization (HR) is a newly developed manifold regularization method, whose natural properties make it more extrapolating, especially for small sample data. In this work, we propose the HR-based NMF (HR-NMF) algorithm, and then apply it to represent gene expression data for further clustering task. The clustering experiments are conducted on five commonly used gene datasets, and the results indicate that the proposed HR-NMF outperforms LR-based NMM and original NMF, which suggests the potential application of HR-NMF for gene expression data.

  17. 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.

  18. Accurate Gene Expression-Based Biodosimetry Using a Minimal Set of Human Gene Transcripts

    Energy Technology Data Exchange (ETDEWEB)

    Tucker, James D., E-mail: jtucker@biology.biosci.wayne.edu [Department of Biological Sciences, Wayne State University, Detroit, Michigan (United States); Joiner, Michael C. [Department of Radiation Oncology, Wayne State University, Detroit, Michigan (United States); Thomas, Robert A.; Grever, William E.; Bakhmutsky, Marina V. [Department of Biological Sciences, Wayne State University, Detroit, Michigan (United States); Chinkhota, Chantelle N.; Smolinski, Joseph M. [Department of Electrical and Computer Engineering, Wayne State University, Detroit, Michigan (United States); Divine, George W. [Department of Public Health Sciences, Henry Ford Hospital, Detroit, Michigan (United States); Auner, Gregory W. [Department of Electrical and Computer Engineering, Wayne State University, Detroit, Michigan (United States)

    2014-03-15

    Purpose: Rapid and reliable methods for conducting biological dosimetry are a necessity in the event of a large-scale nuclear event. Conventional biodosimetry methods lack the speed, portability, ease of use, and low cost required for triaging numerous victims. Here we address this need by showing that polymerase chain reaction (PCR) on a small number of gene transcripts can provide accurate and rapid dosimetry. The low cost and relative ease of PCR compared with existing dosimetry methods suggest that this approach may be useful in mass-casualty triage situations. Methods and Materials: Human peripheral blood from 60 adult donors was acutely exposed to cobalt-60 gamma rays at doses of 0 (control) to 10 Gy. mRNA expression levels of 121 selected genes were obtained 0.5, 1, and 2 days after exposure by reverse-transcriptase real-time PCR. Optimal dosimetry at each time point was obtained by stepwise regression of dose received against individual gene transcript expression levels. Results: Only 3 to 4 different gene transcripts, ASTN2, CDKN1A, GDF15, and ATM, are needed to explain ≥0.87 of the variance (R{sup 2}). Receiver-operator characteristics, a measure of sensitivity and specificity, of 0.98 for these statistical models were achieved at each time point. Conclusions: The actual and predicted radiation doses agree very closely up to 6 Gy. Dosimetry at 8 and 10 Gy shows some effect of saturation, thereby slightly diminishing the ability to quantify higher exposures. Analyses of these gene transcripts may be advantageous for use in a field-portable device designed to assess exposures in mass casualty situations or in clinical radiation emergencies.

  19. Comparison of approaches for efficient gene silencing induced by microRNA-based short hairpin RNA and indicator gene expression.

    Science.gov (United States)

    Shan, Z X; Lin, Q X; Deng, C Y; Zhou, Z L; Tan, H H; Fu, Y H; Li, X H; Zhu, J N; Mai, L P; Kuang, S J; Lin, S G; Yu, X Y

    2010-04-01

    MicroRNA-based short hairpin RNAs (shRNAs) are natural inducers of RNA interference and have been increasingly used in shRNA expression strategies. In the present study, we compared the efficiencies of exogenous green fluorescence protein (GFP) and endogenous glyceraldehyde-3-phosphate dehydrogenase (GAPDH) knockdown and red fluorescent protein (RFP) indicator expression mediated by three differently designed plasmids. RFP was introduced either at the 5' end, at the 3' end of the human mir155-based target gene (TG) (e.g., GFP or GAPDH) shRNA expression cassette (EC), or at the 3' end of the chimeric intron-containing TG shRNA EC. Comparisons with the control vector showed an obvious reduction of GFP or GAPDH expression with the various shRNA expression plasmids (P < 0.05). When RFP was located at the 5' end or at the 3' end of the TG shRNA EC, RFP expression was low; whereas when RFP was connected with the chimeric intron-containing TG shRNA EC, RFP expression was high. Taken together, this study demonstrated an efficient plasmid design for both TG silencing induced by microRNA-based shRNA and indicator gene expression in vitro.

  20. Locally linear representation Fisher criterion based tumor gene expressive data classification.

    Science.gov (United States)

    Li, Bo; Tian, Bei-Bei; Zhang, Xiao-Long; Zhang, Xiao-Ping

    2014-10-01

    Tumor gene expressive data are characterized by a large amount of genes with only a small amount of observations, which always appear with high dimensionality. So it is necessary to reduce the dimensionality before identifying their genre. In this paper, a discriminant manifold learning method, named locally linear representation Fisher criterion (LLRFC), is applied to extract features from tumor gene expressive data. In LLRFC, an inter-class graph and an intra-class graph are constructed based on their genre information, where any tumor gene expressive data in the inter-class graph should select k nearest neighbors with different class labels and in the intra-class graph the k nearest neighbors for any tumor gene expressive data must be sampled from those with the same class. And then the locally least linear reconstruction is introduced to optimize the corresponding weights in both graphs. Moreover, a Fisher criterion is modeled to explore a low dimensional subspace where the reconstruction errors in the inter-class graph can be maximized and the reconstruction errors in the intra-class graph can be minimized, simultaneously. Experiments on some benchmark tumor gene expressive data have been conducted with some related algorithms, by which the proposed LLRFC has been validated to be efficient. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. Gene expression based leukemia sub-classification using committee neural networks.

    Science.gov (United States)

    Sewak, Mihir S; Reddy, Narender P; Duan, Zhong-Hui

    2009-09-03

    Analysis of gene expression data provides an objective and efficient technique for sub-classification of leukemia. The purpose of the present study was to design a committee neural networks based classification systems to subcategorize leukemia gene expression data. In the study, a binary classification system was considered to differentiate acute lymphoblastic leukemia from acute myeloid leukemia. A ternary classification system which classifies leukemia expression data into three subclasses including B-cell acute lymphoblastic leukemia, T-cell acute lymphoblastic leukemia and acute myeloid leukemia was also developed. In each classification system gene expression profiles of leukemia patients were first subjected to a sequence of simple preprocessing steps. This resulted in filtering out approximately 95 percent of the non-informative genes. The remaining 5 percent of the informative genes were used to train a set of artificial neural networks with different parameters and architectures. The networks that gave the best results during initial testing were recruited into a committee. The committee decision was by majority voting. The committee neural network system was later evaluated using data not used in training. The binary classification system classified microarray gene expression profiles into two categories with 100 percent accuracy and the ternary system correctly predicted the three subclasses of leukemia in over 97 percent of the cases.

  2. Gene Expression Based Leukemia Sub‑Classification Using Committee Neural Networks

    Directory of Open Access Journals (Sweden)

    Mihir S. Sewak

    2009-09-01

    Full Text Available Analysis of gene expression data provides an objective and efficient technique for sub‑classification of leukemia. The purpose of the present study was to design a committee neural networks based classification systems to subcategorize leukemia gene expression data. In the study, a binary classification system was considered to differentiate acute lymphoblastic leukemia from acute myeloid leukemia. A ternary classification system which classifies leukemia expression data into three subclasses including B‑cell acute lymphoblastic leukemia, T‑cell acute lymphoblastic leukemia and acute myeloid leukemia was also developed. In each classification system gene expression profiles of leukemia patients were first subjected to a sequence of simple preprocessing steps. This resulted in filtering out approximately 95 percent of the non‑informative genes. The remaining 5 percent of the informative genes were used to train a set of artificial neural networks with different parameters and architectures. The networks that gave the best results during initial testing were recruited into a committee. The committee decision was by majority voting. The committee neural network system was later evaluated using data not used in training. The binary classification system classified microarray gene expression profiles into two categories with 100 percent accuracy and the ternary system correctly predicted the three subclasses of leukemia in over 97 percent of the cases.

  3. A resampling-based meta-analysis for detection of differential gene expression in breast cancer

    Directory of Open Access Journals (Sweden)

    Ergul Gulusan

    2008-12-01

    Full Text Available Abstract Background Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures. Methods A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC, and invasive lobular carcinoma (ILC samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis. Results The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively. The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real

  4. A resampling-based meta-analysis for detection of differential gene expression in breast cancer

    International Nuclear Information System (INIS)

    Gur-Dedeoglu, Bala; Konu, Ozlen; Kir, Serkan; Ozturk, Ahmet Rasit; Bozkurt, Betul; Ergul, Gulusan; Yulug, Isik G

    2008-01-01

    Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures. A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC), and invasive lobular carcinoma (ILC) samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis. The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively). The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real-time qRT-PCR supported the meta-analysis results. The

  5. Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data

    Directory of Open Access Journals (Sweden)

    Simpson David

    2006-03-01

    Full Text Available Abstract Background Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfunction of the rod and cone photoreceptor cells. Development and maintenance of photoreceptors requires appropriate regulation of the many genes specifically or highly expressed in these cells. Over the last decades, different experimental approaches have been developed to identify photoreceptor enriched genes. Recent progress in RNA analysis technology has generated large amounts of gene expression data relevant to retinal development. This paper assesses a machine learning methodology for supporting the identification of photoreceptor enriched genes based on expression data. Results Based on the analysis of publicly-available gene expression data from the developing mouse retina generated by serial analysis of gene expression (SAGE, this paper presents a predictive methodology comprising several in silico models for detecting key complex features and relationships encoded in the data, which may be useful to distinguish genes in terms of their functional roles. In order to understand temporal patterns of photoreceptor gene expression during retinal development, a two-way cluster analysis was firstly performed. By clustering SAGE libraries, a hierarchical tree reflecting relationships between developmental stages was obtained. By clustering SAGE tags, a more comprehensive expression profile for photoreceptor cells was revealed. To demonstrate the usefulness of machine learning-based models in predicting functional associations from the SAGE data, three supervised classification models were compared. The results indicated that a relatively simple instance-based model (KStar model performed significantly better than relatively more complex algorithms, e.g. neural networks. To deal with the problem of functional class imbalance occurring in the dataset, two data re

  6. Enhancing the Lasso Approach for Developing a Survival Prediction Model Based on Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Shuhei Kaneko

    2015-01-01

    Full Text Available In the past decade, researchers in oncology have sought to develop survival prediction models using gene expression data. The least absolute shrinkage and selection operator (lasso has been widely used to select genes that truly correlated with a patient’s survival. The lasso selects genes for prediction by shrinking a large number of coefficients of the candidate genes towards zero based on a tuning parameter that is often determined by a cross-validation (CV. However, this method can pass over (or fail to identify true positive genes (i.e., it identifies false negatives in certain instances, because the lasso tends to favor the development of a simple prediction model. Here, we attempt to monitor the identification of false negatives by developing a method for estimating the number of true positive (TP genes for a series of values of a tuning parameter that assumes a mixture distribution for the lasso estimates. Using our developed method, we performed a simulation study to examine its precision in estimating the number of TP genes. Additionally, we applied our method to a real gene expression dataset and found that it was able to identify genes correlated with survival that a CV method was unable to detect.

  7. PINTA: a web server for network-based gene prioritization from expression data

    DEFF Research Database (Denmark)

    Nitsch, Daniela; Tranchevent, Léon-Charles; Goncalves, Joana P.

    2011-01-01

    PINTA (available at http://www.esat.kuleuven.be/ pinta/; this web site is free and open to all users and there is no login requirement) is a web resource for the prioritization of candidate genes based on the differential expression of their neighborhood in a genome-wide protein–protein interacti...

  8. Comparison of linear discriminant analysis methods for the classification of cancer based on gene expression data.

    Science.gov (United States)

    Huang, Desheng; Quan, Yu; He, Miao; Zhou, Baosen

    2009-12-10

    More studies based on gene expression data have been reported in great detail, however, one major challenge for the methodologists is the choice of classification methods. The main purpose of this research was to compare the performance of linear discriminant analysis (LDA) and its modification methods for the classification of cancer based on gene expression data. The classification performance of linear discriminant analysis (LDA) and its modification methods was evaluated by applying these methods to six public cancer gene expression datasets. These methods included linear discriminant analysis (LDA), prediction analysis for microarrays (PAM), shrinkage centroid regularized discriminant analysis (SCRDA), shrinkage linear discriminant analysis (SLDA) and shrinkage diagonal discriminant analysis (SDDA). The procedures were performed by software R 2.80. PAM picked out fewer feature genes than other methods from most datasets except from Brain dataset. For the two methods of shrinkage discriminant analysis, SLDA selected more genes than SDDA from most datasets except from 2-class lung cancer dataset. When comparing SLDA with SCRDA, SLDA selected more genes than SCRDA from 2-class lung cancer, SRBCT and Brain dataset, the result was opposite for the rest datasets. The average test error of LDA modification methods was lower than LDA method. The classification performance of LDA modification methods was superior to that of traditional LDA with respect to the average error and there was no significant difference between theses modification methods.

  9. SPSNet: subpopulation-sensitive network-based analysis of heterogeneous gene expression data.

    Science.gov (United States)

    Belorkar, Abha; Vadigepalli, Rajanikanth; Wong, Limsoon

    2018-03-19

    Transcriptomic datasets often contain undeclared heterogeneity arising from biological variation such as diversity of disease subtypes, treatment subgroups, time-series gene expression, nested experimental conditions, as well as technical variation due to batch effects, platform differences in integrated meta-analyses, etc. However, current analysis approaches are primarily designed to handle comparisons between experimental conditions represented by homogeneous samples, thus precluding the discovery of underlying subphenotypes. Unsupervised methods for subtype identification are typically based on individual gene level analysis, which often result in irreproducible gene signatures for potential subtypes. Emerging methods to study heterogeneity have been largely developed in the context of single-cell datasets containing hundreds to thousands of samples, limiting their use to select contexts. We present a novel analysis method, SPSNet, which identifies subtype-specific gene expression signatures based on the activity of subnetworks in biological pathways. SPSNet identifies the gene subnetworks capturing the diversity of underlying biological mechanisms, indicating potential sample subphenotypes. In the presence of extrinsic or non-biological heterogeneity (e.g. batch effects), SPSNet identifies subnetworks that are particularly affected by such variation, thus helping eliminate factors irrelevant to the biology of the phenotypes under study. Using multiple publicly available datasets, we illustrate that SPSNet is able to consistently uncover patterns within gene expression data that correspond to meaningful heterogeneity of various origins. We also demonstrate the performance of SPSNet as a sensitive and reliable tool for understanding the structure and nature of such heterogeneity.

  10. The prediction of interferon treatment effects based on time series microarray gene expression profiles

    Directory of Open Access Journals (Sweden)

    Wei Chao-Chun

    2008-08-01

    Full Text Available Abstract Background The status of a disease can be reflected by specific transcriptional profiles resulting from the induction or repression activity of a number of genes. Here, we proposed a time-dependent diagnostic model to predict the treatment effects of interferon and ribavirin to HCV infected patients by using time series microarray gene expression profiles of a published study. Methods In the published study, 33 African-American (AA and 36 Caucasian American (CA patients with chronic HCV genotype 1 infection received pegylated interferon and ribavirin therapy for 28 days. HG-U133A GeneChip containing 22283 probes was used to analyze the global gene expression in peripheral blood mononuclear cells (PBMC of all the patients on day 0 (pretreatment, 1, 2, 7, 14, and 28. According to the decrease of HCV RNA levels on day 28, two categories of responses were defined: good and poor. A voting method based on Student's t test, Wilcoxon test, empirical Bayes test and significance analysis of microarray was used to identify differentially expressed genes. A time-dependent diagnostic model based on C4.5 decision tree was constructed to predict the treatment outcome. This model not only utilized the gene expression profiles before the treatment, but also during the treatment. Leave-one-out cross validation was used to evaluate the performance of the model. Results The model could correctly predict all Caucasian American patients' treatment effects at very early time point. The prediction accuracy of African-American patients achieved 85.7%. In addition, thirty potential biomarkers which may play important roles in response to interferon and ribavirin were identified. Conclusion Our method provides a way of using time series gene expression profiling to predict the treatment effect of pegylated interferon and ribavirin therapy on HCV infected patients. Similar experimental and bioinformatical strategies may be used to improve treatment decisions for

  11. Recombinant gene expression protocols

    National Research Council Canada - National Science Library

    Tuan, Rocky S

    1997-01-01

    .... A fundamental requirement for successful recombinant gene expression is the design of the cloning vector and the choice of the host organism for expression. Recombinant Gene Expression Protocols grows out of the need for a laboratory manual that provides the reader the background and rationale, as well as the practical protocols for the preparation of...

  12. Biclustering of Gene Expression Data by Correlation-Based Scatter Search

    Science.gov (United States)

    2011-01-01

    Background The analysis of data generated by microarray technology is very useful to understand how the genetic information becomes functional gene products. Biclustering algorithms can determine a group of genes which are co-expressed under a set of experimental conditions. Recently, new biclustering methods based on metaheuristics have been proposed. Most of them use the Mean Squared Residue as merit function but interesting and relevant patterns from a biological point of view such as shifting and scaling patterns may not be detected using this measure. However, it is important to discover this type of patterns since commonly the genes can present a similar behavior although their expression levels vary in different ranges or magnitudes. Methods Scatter Search is an evolutionary technique that is based on the evolution of a small set of solutions which are chosen according to quality and diversity criteria. This paper presents a Scatter Search with the aim of finding biclusters from gene expression data. In this algorithm the proposed fitness function is based on the linear correlation among genes to detect shifting and scaling patterns from genes and an improvement method is included in order to select just positively correlated genes. Results The proposed algorithm has been tested with three real data sets such as Yeast Cell Cycle dataset, human B-cells lymphoma dataset and Yeast Stress dataset, finding a remarkable number of biclusters with shifting and scaling patterns. In addition, the performance of the proposed method and fitness function are compared to that of CC, OPSM, ISA, BiMax, xMotifs and Samba using Gene the Ontology Database. PMID:21261986

  13. Analysis of ripening-related gene expression in papaya using an Arabidopsis-based microarray

    Science.gov (United States)

    2012-01-01

    Background Papaya (Carica papaya L.) is a commercially important crop that produces climacteric fruits with a soft and sweet pulp that contain a wide range of health promoting phytochemicals. Despite its importance, little is known about transcriptional modifications during papaya fruit ripening and their control. In this study we report the analysis of ripe papaya transcriptome by using a cross-species (XSpecies) microarray technique based on the phylogenetic proximity between papaya and Arabidopsis thaliana. Results Papaya transcriptome analyses resulted in the identification of 414 ripening-related genes with some having their expression validated by qPCR. The transcription profile was compared with that from ripening tomato and grape. There were many similarities between papaya and tomato especially with respect to the expression of genes encoding proteins involved in primary metabolism, regulation of transcription, biotic and abiotic stress and cell wall metabolism. XSpecies microarray data indicated that transcription factors (TFs) of the MADS-box, NAC and AP2/ERF gene families were involved in the control of papaya ripening and revealed that cell wall-related gene expression in papaya had similarities to the expression profiles seen in Arabidopsis during hypocotyl development. Conclusion The cross-species array experiment identified a ripening-related set of genes in papaya allowing the comparison of transcription control between papaya and other fruit bearing taxa during the ripening process. PMID:23256600

  14. Monoterpenoid-based preparations in beehives affect learning, memory, and gene expression in the bee brain.

    Science.gov (United States)

    Bonnafé, Elsa; Alayrangues, Julie; Hotier, Lucie; Massou, Isabelle; Renom, Allan; Souesme, Guillaume; Marty, Pierre; Allaoua, Marion; Treilhou, Michel; Armengaud, Catherine

    2017-02-01

    Bees are exposed in their environment to contaminants that can weaken the colony and contribute to bee declines. Monoterpenoid-based preparations can be introduced into hives to control the parasitic mite Varroa destructor. The long-term effects of monoterpenoids are poorly investigated. Olfactory conditioning of the proboscis extension reflex (PER) has been used to evaluate the impact of stressors on cognitive functions of the honeybee such as learning and memory. The authors tested the PER to odorants on bees after exposure to monoterpenoids in hives. Octopamine receptors, transient receptor potential-like (TRPL), and γ-aminobutyric acid channels are thought to play a critical role in the memory of food experience. Gene expression levels of Amoa1, Rdl, and trpl were evaluated in parallel in the bee brain because these genes code for the cellular targets of monoterpenoids and some pesticides and neural circuits of memory require their expression. The miticide impaired the PER to odors in the 3 wk following treatment. Short-term and long-term olfactory memories were improved months after introduction of the monoterpenoids into the beehives. Chronic exposure to the miticide had significant effects on Amoa1, Rdl, and trpl gene expressions and modified seasonal changes in the expression of these genes in the brain. The decrease of expression of these genes in winter could partly explain the improvement of memory. The present study has led to new insights into alternative treatments, especially on their effects on memory and expression of selected genes involved in this cognitive function. Environ Toxicol Chem 2017;36:337-345. © 2016 SETAC. © 2016 SETAC.

  15. Expression-based clustering of CAZyme-encoding genes of Aspergillus niger.

    Science.gov (United States)

    Gruben, Birgit S; Mäkelä, Miia R; Kowalczyk, Joanna E; Zhou, Miaomiao; Benoit-Gelber, Isabelle; De Vries, Ronald P

    2017-11-23

    The Aspergillus niger genome contains a large repertoire of genes encoding carbohydrate active enzymes (CAZymes) that are targeted to plant polysaccharide degradation enabling A. niger to grow on a wide range of plant biomass substrates. Which genes need to be activated in certain environmental conditions depends on the composition of the available substrate. Previous studies have demonstrated the involvement of a number of transcriptional regulators in plant biomass degradation and have identified sets of target genes for each regulator. In this study, a broad transcriptional analysis was performed of the A. niger genes encoding (putative) plant polysaccharide degrading enzymes. Microarray data focusing on the initial response of A. niger to the presence of plant biomass related carbon sources were analyzed of a wild-type strain N402 that was grown on a large range of carbon sources and of the regulatory mutant strains ΔxlnR, ΔaraR, ΔamyR, ΔrhaR and ΔgalX that were grown on their specific inducing compounds. The cluster analysis of the expression data revealed several groups of co-regulated genes, which goes beyond the traditionally described co-regulated gene sets. Additional putative target genes of the selected regulators were identified, based on their expression profile. Notably, in several cases the expression profile puts questions on the function assignment of uncharacterized genes that was based on homology searches, highlighting the need for more extensive biochemical studies into the substrate specificity of enzymes encoded by these non-characterized genes. The data also revealed sets of genes that were upregulated in the regulatory mutants, suggesting interaction between the regulatory systems and a therefore even more complex overall regulatory network than has been reported so far. Expression profiling on a large number of substrates provides better insight in the complex regulatory systems that drive the conversion of plant biomass by fungi. In

  16. Lineage relationship of prostate cancer cell types based on gene expression

    Directory of Open Access Journals (Sweden)

    Ware Carol B

    2011-05-01

    Full Text Available Abstract Background Prostate tumor heterogeneity is a major factor in disease management. Heterogeneity could be due to multiple cancer cell types with distinct gene expression. Of clinical importance is the so-called cancer stem cell type. Cell type-specific transcriptomes are used to examine lineage relationship among cancer cell types and their expression similarity to normal cell types including stem/progenitor cells. Methods Transcriptomes were determined by Affymetrix DNA array analysis for the following cell types. Putative prostate progenitor cell populations were characterized and isolated by expression of the membrane transporter ABCG2. Stem cells were represented by embryonic stem and embryonal carcinoma cells. The cancer cell types were Gleason pattern 3 (glandular histomorphology and pattern 4 (aglandular sorted from primary tumors, cultured prostate cancer cell lines originally established from metastatic lesions, xenografts LuCaP 35 (adenocarcinoma phenotype and LuCaP 49 (neuroendocrine/small cell carcinoma grown in mice. No detectable gene expression differences were detected among serial passages of the LuCaP xenografts. Results Based on transcriptomes, the different cancer cell types could be clustered into a luminal-like grouping and a non-luminal-like (also not basal-like grouping. The non-luminal-like types showed expression more similar to that of stem/progenitor cells than the luminal-like types. However, none showed expression of stem cell genes known to maintain stemness. Conclusions Non-luminal-like types are all representatives of aggressive disease, and this could be attributed to the similarity in overall gene expression to stem and progenitor cell types.

  17. Pairwise gene GO-based measures for biclustering of high-dimensional expression data.

    Science.gov (United States)

    Nepomuceno, Juan A; Troncoso, Alicia; Nepomuceno-Chamorro, Isabel A; Aguilar-Ruiz, Jesús S

    2018-01-01

    Biclustering algorithms search for groups of genes that share the same behavior under a subset of samples in gene expression data. Nowadays, the biological knowledge available in public repositories can be used to drive these algorithms to find biclusters composed of groups of genes functionally coherent. On the other hand, a distance among genes can be defined according to their information stored in Gene Ontology (GO). Gene pairwise GO semantic similarity measures report a value for each pair of genes which establishes their functional similarity. A scatter search-based algorithm that optimizes a merit function that integrates GO information is studied in this paper. This merit function uses a term that addresses the information through a GO measure. The effect of two possible different gene pairwise GO measures on the performance of the algorithm is analyzed. Firstly, three well known yeast datasets with approximately one thousand of genes are studied. Secondly, a group of human datasets related to clinical data of cancer is also explored by the algorithm. Most of these data are high-dimensional datasets composed of a huge number of genes. The resultant biclusters reveal groups of genes linked by a same functionality when the search procedure is driven by one of the proposed GO measures. Furthermore, a qualitative biological study of a group of biclusters show their relevance from a cancer disease perspective. It can be concluded that the integration of biological information improves the performance of the biclustering process. The two different GO measures studied show an improvement in the results obtained for the yeast dataset. However, if datasets are composed of a huge number of genes, only one of them really improves the algorithm performance. This second case constitutes a clear option to explore interesting datasets from a clinical point of view.

  18. An EST-based analysis identifies new genes and reveals distinctive gene expression features of Coffea arabica and Coffea canephora

    Directory of Open Access Journals (Sweden)

    Colombo Carlos A

    2011-02-01

    Full Text Available Abstract Background Coffee is one of the world's most important crops; it is consumed worldwide and plays a significant role in the economy of producing countries. Coffea arabica and C. canephora are responsible for 70 and 30% of commercial production, respectively. C. arabica is an allotetraploid from a recent hybridization of the diploid species, C. canephora and C. eugenioides. C. arabica has lower genetic diversity and results in a higher quality beverage than C. canephora. Research initiatives have been launched to produce genomic and transcriptomic data about Coffea spp. as a strategy to improve breeding efficiency. Results Assembling the expressed sequence tags (ESTs of C. arabica and C. canephora produced by the Brazilian Coffee Genome Project and the Nestlé-Cornell Consortium revealed 32,007 clusters of C. arabica and 16,665 clusters of C. canephora. We detected different GC3 profiles between these species that are related to their genome structure and mating system. BLAST analysis revealed similarities between coffee and grape (Vitis vinifera genes. Using KA/KS analysis, we identified coffee genes under purifying and positive selection. Protein domain and gene ontology analyses suggested differences between Coffea spp. data, mainly in relation to complex sugar synthases and nucleotide binding proteins. OrthoMCL was used to identify specific and prevalent coffee protein families when compared to five other plant species. Among the interesting families annotated are new cystatins, glycine-rich proteins and RALF-like peptides. Hierarchical clustering was used to independently group C. arabica and C. canephora expression clusters according to expression data extracted from EST libraries, resulting in the identification of differentially expressed genes. Based on these results, we emphasize gene annotation and discuss plant defenses, abiotic stress and cup quality-related functional categories. Conclusion We present the first comprehensive

  19. Ontology based molecular signatures for immune cell types via gene expression analysis

    Science.gov (United States)

    2013-01-01

    Background New technologies are focusing on characterizing cell types to better understand their heterogeneity. With large volumes of cellular data being generated, innovative methods are needed to structure the resulting data analyses. Here, we describe an ‘Ontologically BAsed Molecular Signature’ (OBAMS) method that identifies novel cellular biomarkers and infers biological functions as characteristics of particular cell types. This method finds molecular signatures for immune cell types based on mapping biological samples to the Cell Ontology (CL) and navigating the space of all possible pairwise comparisons between cell types to find genes whose expression is core to a particular cell type’s identity. Results We illustrate this ontological approach by evaluating expression data available from the Immunological Genome project (IGP) to identify unique biomarkers of mature B cell subtypes. We find that using OBAMS, candidate biomarkers can be identified at every strata of cellular identity from broad classifications to very granular. Furthermore, we show that Gene Ontology can be used to cluster cell types by shared biological processes in order to find candidate genes responsible for somatic hypermutation in germinal center B cells. Moreover, through in silico experiments based on this approach, we have identified genes sets that represent genes overexpressed in germinal center B cells and identify genes uniquely expressed in these B cells compared to other B cell types. Conclusions This work demonstrates the utility of incorporating structured ontological knowledge into biological data analysis – providing a new method for defining novel biomarkers and providing an opportunity for new biological insights. PMID:24004649

  20. Characteristics and Validation Techniques for PCA-Based Gene-Expression Signatures

    Directory of Open Access Journals (Sweden)

    Anders E. Berglund

    2017-01-01

    Full Text Available Background. Many gene-expression signatures exist for describing the biological state of profiled tumors. Principal Component Analysis (PCA can be used to summarize a gene signature into a single score. Our hypothesis is that gene signatures can be validated when applied to new datasets, using inherent properties of PCA. Results. This validation is based on four key concepts. Coherence: elements of a gene signature should be correlated beyond chance. Uniqueness: the general direction of the data being examined can drive most of the observed signal. Robustness: if a gene signature is designed to measure a single biological effect, then this signal should be sufficiently strong and distinct compared to other signals within the signature. Transferability: the derived PCA gene signature score should describe the same biology in the target dataset as it does in the training dataset. Conclusions. The proposed validation procedure ensures that PCA-based gene signatures perform as expected when applied to datasets other than those that the signatures were trained upon. Complex signatures, describing multiple independent biological components, are also easily identified.

  1. Imaging gene expression in gene therapy

    International Nuclear Information System (INIS)

    Wiebe, Leonard I.

    1997-01-01

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

  2. A contribution to the study of plant development evolution based on gene co-expression networks

    Directory of Open Access Journals (Sweden)

    Francisco J. Romero-Campero

    2013-08-01

    Full Text Available Phototrophic eukaryotes are among the most successful organisms on Earth due to their unparalleled efficiency at capturing light energy and fixing carbon dioxide to produce organic molecules. A conserved and efficient network of light-dependent regulatory modules could be at the bases of this success. This regulatory system conferred early advantages to phototrophic eukaryotes that allowed for specialization, complex developmental processes and modern plant characteristics. We have studied light-dependent gene regulatory modules from algae to plants employing integrative-omics approaches based on gene co-expression networks. Our study reveals some remarkably conserved ways in which eukaryotic phototrophs deal with day length and light signaling. Here we describe how a family of Arabidopsis transcription factors involved in photoperiod response has evolved from a single algal gene according to the innovation, amplification and divergence theory of gene evolution by duplication. These modifications of the gene co-expression networks from the ancient unicellular green algae Chlamydomonas reinhardtii to the modern brassica Arabidopsis thaliana may hint on the evolution and specialization of plants and other organisms.

  3. Genomic DNA-based absolute quantification of gene expression in Vitis.

    Science.gov (United States)

    Gambetta, Gregory A; McElrone, Andrew J; Matthews, Mark A

    2013-07-01

    Many studies in which gene expression is quantified by polymerase chain reaction represent the expression of a gene of interest (GOI) relative to that of a reference gene (RG). Relative expression is founded on the assumptions that RG expression is stable across samples, treatments, organs, etc., and that reaction efficiencies of the GOI and RG are equal; assumptions which are often faulty. The true variability in RG expression and actual reaction efficiencies are seldom determined experimentally. Here we present a rapid and robust method for absolute quantification of expression in Vitis where varying concentrations of genomic DNA were used to construct GOI standard curves. This methodology was utilized to absolutely quantify and determine the variability of the previously validated RG ubiquitin (VvUbi) across three test studies in three different tissues (roots, leaves and berries). In addition, in each study a GOI was absolutely quantified. Data sets resulting from relative and absolute methods of quantification were compared and the differences were striking. VvUbi expression was significantly different in magnitude between test studies and variable among individual samples. Absolute quantification consistently reduced the coefficients of variation of the GOIs by more than half, often resulting in differences in statistical significance and in some cases even changing the fundamental nature of the result. Utilizing genomic DNA-based absolute quantification is fast and efficient. Through eliminating error introduced by assuming RG stability and equal reaction efficiencies between the RG and GOI this methodology produces less variation, increased accuracy and greater statistical power. © 2012 Scandinavian Plant Physiology Society.

  4. Microarray-Based Gene Expression Profiling to Elucidate Effectiveness of Fermented Codonopsis lanceolata in Mice

    Science.gov (United States)

    Choi, Woon Yong; Kim, Ji Seon; Park, Sung Jin; Ma, Choong Je; Lee, Hyeon Yong

    2014-01-01

    In this study, the effect of Codonopsis lanceolata fermented by lactic acid on controlling gene expression levels related to obesity was observed in an oligonucleotide chip microarray. Among 8170 genes, 393 genes were up regulated and 760 genes were down regulated in feeding the fermented C. lanceolata (FCL). Another 374 genes were up regulated and 527 genes down regulated without feeding the sample. The genes were not affected by the FCL sample. It was interesting that among those genes, Chytochrome P450, Dmbt1, LOC76487, and thyroid hormones, etc., were mostly up or down regulated. These genes are more related to lipid synthesis. We could conclude that the FCL possibly controlled the gene expression levels related to lipid synthesis, which resulted in reducing obesity. However, more detailed protein expression experiments should be carried out. PMID:24717412

  5. Microarray-Based Gene Expression Profiling to Elucidate Effectiveness of Fermented Codonopsis lanceolata in Mice

    Directory of Open Access Journals (Sweden)

    Woon Yong Choi

    2014-04-01

    Full Text Available In this study, the effect of Codonopsis lanceolata fermented by lactic acid on controlling gene expression levels related to obesity was observed in an oligonucleotide chip microarray. Among 8170 genes, 393 genes were up regulated and 760 genes were down regulated in feeding the fermented C. lanceolata (FCL. Another 374 genes were up regulated and 527 genes down regulated without feeding the sample. The genes were not affected by the FCL sample. It was interesting that among those genes, Chytochrome P450, Dmbt1, LOC76487, and thyroid hormones, etc., were mostly up or down regulated. These genes are more related to lipid synthesis. We could conclude that the FCL possibly controlled the gene expression levels related to lipid synthesis, which resulted in reducing obesity. However, more detailed protein expression experiments should be carried out.

  6. Co-expressed Pathways DataBase for Tomato: a database to predict pathways relevant to a query gene.

    Science.gov (United States)

    Narise, Takafumi; Sakurai, Nozomu; Obayashi, Takeshi; Ohta, Hiroyuki; Shibata, Daisuke

    2017-06-05

    Gene co-expression, the similarity of gene expression profiles under various experimental conditions, has been used as an indicator of functional relationships between genes, and many co-expression databases have been developed for predicting gene functions. These databases usually provide users with a co-expression network and a list of strongly co-expressed genes for a query gene. Several of these databases also provide functional information on a set of strongly co-expressed genes (i.e., provide biological processes and pathways that are enriched in these strongly co-expressed genes), which is generally analyzed via over-representation analysis (ORA). A limitation of this approach may be that users can predict gene functions only based on the strongly co-expressed genes. In this study, we developed a new co-expression database that enables users to predict the function of tomato genes from the results of functional enrichment analyses of co-expressed genes while considering the genes that are not strongly co-expressed. To achieve this, we used the ORA approach with several thresholds to select co-expressed genes, and performed gene set enrichment analysis (GSEA) applied to a ranked list of genes ordered by the co-expression degree. We found that internal correlation in pathways affected the significance levels of the enrichment analyses. Therefore, we introduced a new measure for evaluating the relationship between the gene and pathway, termed the percentile (p)-score, which enables users to predict functionally relevant pathways without being affected by the internal correlation in pathways. In addition, we evaluated our approaches using receiver operating characteristic curves, which concluded that the p-score could improve the performance of the ORA. We developed a new database, named Co-expressed Pathways DataBase for Tomato, which is available at http://cox-path-db.kazusa.or.jp/tomato . The database allows users to predict pathways that are relevant to a

  7. Blood-based gene-expression predictors of PTSD risk and resilience among deployed marines: a pilot study.

    Science.gov (United States)

    Glatt, Stephen J; Tylee, Daniel S; Chandler, Sharon D; Pazol, Joel; Nievergelt, Caroline M; Woelk, Christopher H; Baker, Dewleen G; Lohr, James B; Kremen, William S; Litz, Brett T; Tsuang, Ming T

    2013-06-01

    Susceptibility to PTSD is determined by both genes and environment. Similarly, gene-expression levels in peripheral blood are influenced by both genes and environment, and expression levels of many genes show good correspondence between peripheral blood and brain. Therefore, our objectives were to test the following hypotheses: (1) pre-trauma expression levels of a gene subset (particularly immune-system genes) in peripheral blood would differ between trauma-exposed Marines who later developed PTSD and those who did not; (2) a predictive biomarker panel of the eventual emergence of PTSD among high-risk individuals could be developed based on gene expression in readily assessable peripheral blood cells; and (3) a predictive panel based on expression of individual exons would surpass the accuracy of a model based on expression of full-length gene transcripts. Gene-expression levels were assayed in peripheral blood samples from 50 U.S. Marines (25 eventual PTSD cases and 25 non-PTSD comparison subjects) prior to their deployment overseas to war-zones in Iraq or Afghanistan. The panel of biomarkers dysregulated in peripheral blood cells of eventual PTSD cases prior to deployment was significantly enriched for immune genes, achieved 70% prediction accuracy in an independent sample based on the expression of 23 full-length transcripts, and attained 80% accuracy in an independent sample based on the expression of one exon from each of five genes. If the observed profiles of pre-deployment mRNA-expression in eventual PTSD cases can be further refined and replicated, they could suggest avenues for early intervention and prevention among individuals at high risk for trauma exposure. Copyright © 2013 Wiley Periodicals, Inc.

  8. Principal component analysis based unsupervised feature extraction applied to budding yeast temporally periodic gene expression.

    Science.gov (United States)

    Taguchi, Y-H

    2016-01-01

    The recently proposed principal component analysis (PCA) based unsupervised feature extraction (FE) has successfully been applied to various bioinformatics problems ranging from biomarker identification to the screening of disease causing genes using gene expression/epigenetic profiles. However, the conditions required for its successful use and the mechanisms involved in how it outperforms other supervised methods is unknown, because PCA based unsupervised FE has only been applied to challenging (i.e. not well known) problems. In this study, PCA based unsupervised FE was applied to an extensively studied organism, i.e., budding yeast. When applied to two gene expression profiles expected to be temporally periodic, yeast metabolic cycle (YMC) and yeast cell division cycle (YCDC), PCA based unsupervised FE outperformed simple but powerful conventional methods, with sinusoidal fitting with regards to several aspects: (i) feasible biological term enrichment without assuming periodicity for YMC; (ii) identification of periodic profiles whose period was half as long as the cell division cycle for YMC; and (iii) the identification of no more than 37 genes associated with the enrichment of biological terms related to cell division cycle for the integrated analysis of seven YCDC profiles, for which sinusoidal fittings failed. The explantation for differences between methods used and the necessary conditions required were determined by comparing PCA based unsupervised FE with fittings to various periodic (artificial, thus pre-defined) profiles. Furthermore, four popular unsupervised clustering algorithms applied to YMC were not as successful as PCA based unsupervised FE. PCA based unsupervised FE is a useful and effective unsupervised method to investigate YMC and YCDC. This study identified why the unsupervised method without pre-judged criteria outperformed supervised methods requiring human defined criteria.

  9. Tissue-Based Microarray Expression of Genes Predictive of Metastasis in Uveal Melanoma and Differentially Expressed in Metastatic Uveal Melanoma

    Directory of Open Access Journals (Sweden)

    Hakan Demirci

    2013-01-01

    Full Text Available Purpose: To screen the microarray expression of CDH1, ECM1, EIF1B, FXR1, HTR2B, ID2, LMCD1, LTA4H, MTUS1, RAB31, ROBO1, and SATB1 genes which are predictive of primary uveal melanoma metastasis, and NFKB2, PTPN18, MTSS1, GADD45B, SNCG, HHIP, IL12B, CDK4, RPLP0, RPS17, RPS12 genes that are differentially expressed in metastatic uveal melanoma in normal whole human blood and tissues prone to metastatic involvement by uveal melanoma. Methods: We screened the GeneNote and GNF BioGPS databases for microarray analysis of genes predictive of primary uveal melanoma metastasis and those differentially expressed in metastatic uveal melanoma in normal whole blood, liver, lung and skin. Results: Microarray analysis showed expression of all 22 genes in normal whole blood, liver, lung and skin, which are the most common sites of metastases. In the GNF BioGPS database, data for expression of the HHIP gene in normal whole blood and skin was not complete. Conclusions: Microarray analysis of genes predicting systemic metastasis of uveal melanoma and genes differentially expressed in metastatic uveal melanoma may not be used as a biomarker for metastasis in whole blood, liver, lung, and skin. Their expression in tissues prone to metastasis may suggest that they play a role in tropism of uveal melanoma metastasis to these tissues.

  10. A gene expression microarray for Nicotiana benthamiana based on de novo transcriptome sequence assembly.

    Science.gov (United States)

    Goralski, Michal; Sobieszczanska, Paula; Obrepalska-Steplowska, Aleksandra; Swiercz, Aleksandra; Zmienko, Agnieszka; Figlerowicz, Marek

    2016-01-01

    Nicotiana benthamiana has been widely used in laboratories around the world for studying plant-pathogen interactions and posttranscriptional gene expression silencing. Yet the exploration of its transcriptome has lagged behind due to the lack of both adequate sequence information and genome-wide analysis tools, such as DNA microarrays. Despite the increasing use of high-throughput sequencing technologies, the DNA microarrays still remain a popular gene expression tool, because they are cheaper and less demanding regarding bioinformatics skills and computational effort. We designed a gene expression microarray with 103,747 60-mer probes, based on two recently published versions of N. benthamiana transcriptome (v.3 and v.5). Both versions were reconstructed from RNA-Seq data of non-strand-specific pooled-tissue libraries, so we defined the sense strand of the contigs prior to designing the probe. To accomplish this, we combined a homology search against Arabidopsis thaliana proteins and hybridization to a test 244k microarray containing pairs of probes, which represented individual contigs. We identified the sense strand in 106,684 transcriptome contigs and used this information to design an Nb-105k microarray on an Agilent eArray platform. Following hybridization of RNA samples from N. benthamiana roots and leaves we demonstrated that the new microarray had high specificity and sensitivity for detection of differentially expressed transcripts. We also showed that the data generated with the Nb-105k microarray may be used to identify incorrectly assembled contigs in the v.5 transcriptome, by detecting inconsistency in the gene expression profiles, which is indicated using multiple microarray probes that match the same v.5 primary transcripts. We provided a complete design of an oligonucleotide microarray that may be applied to the research of N. benthamiana transcriptome. This, in turn, will allow the N. benthamiana research community to take full advantage of

  11. A robust gene expression-based prognostic risk score predicts overall survival of lung adenocarcinoma patients.

    Science.gov (United States)

    Chen, En-Guo; Wang, Pin; Lou, Haizhou; Wang, Yunshan; Yan, Hong; Bi, Lei; Liu, Liang; Li, Bin; Snijders, Antoine M; Mao, Jian-Hua; Hang, Bo

    2018-01-23

    Identification of reliable predictive biomarkers and new therapeutic targets is a critical step for significant improvement in patient outcomes. Here, we developed a multi-step bioinformatics analytic strategy to mine large omics and clinical data to build a prognostic scoring system for predicting the overall survival (OS) of lung adenocarcinoma (LuADC) patients. In latter we first identified 1327 significantly and robustly deregulated genes, 600 of which were significantly associated with the OS of LuADC patients. Gene co-expression network analysis revealed the biological functions of these 600 genes in normal lung and LuADCs, which were found to be enriched for cell cycle-related processes, blood vessel development, cell-matrix adhesion and metabolic processes. Finally, we implemented a multiple resampling method combined with Cox regression analysis to identify a 27-gene signature associated with OS, and then created a prognostic scoring system based on this signature. This scoring system robustly predicted OS of LuADC patients in 100 sampling test sets and was further validated in four independent LuADC cohorts. In addition, in comparison to other existing prognostic gene signatures published in the literature, our signature was significantly superior in predicting OS of LuADC patients. In summary, our multi-omics and clinical data integration study created a 27-gene prognostic risk score that can predict OS of LuADC patients independent of age, gender and clinical stage. This score could guide therapeutic selection and allow stratification in clinical trials.

  12. Interpretable gene expression classifier with an accurate and compact fuzzy rule base for microarray data analysis.

    Science.gov (United States)

    Ho, Shinn-Ying; Hsieh, Chih-Hung; Chen, Hung-Ming; Huang, Hui-Ling

    2006-09-01

    An accurate classifier with linguistic interpretability using a small number of relevant genes is beneficial to microarray data analysis and development of inexpensive diagnostic tests. Several frequently used techniques for designing classifiers of microarray data, such as support vector machine, neural networks, k-nearest neighbor, and logistic regression model, suffer from low interpretabilities. This paper proposes an interpretable gene expression classifier (named iGEC) with an accurate and compact fuzzy rule base for microarray data analysis. The design of iGEC has three objectives to be simultaneously optimized: maximal classification accuracy, minimal number of rules, and minimal number of used genes. An "intelligent" genetic algorithm IGA is used to efficiently solve the design problem with a large number of tuning parameters. The performance of iGEC is evaluated using eight commonly-used data sets. It is shown that iGEC has an accurate, concise, and interpretable rule base (1.1 rules per class) on average in terms of test classification accuracy (87.9%), rule number (3.9), and used gene number (5.0). Moreover, iGEC not only has better performance than the existing fuzzy rule-based classifier in terms of the above-mentioned objectives, but also is more accurate than some existing non-rule-based classifiers.

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

    International Nuclear Information System (INIS)

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

    2008-01-01

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

  14. 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......' C, and clustered Dukes' D separately. Real-time PCR of 10 known genes and 5 ESTs demonstrated excellent reproducibility of the array-based findings. The most frequently altered genes belonged to functional categories of metabolism (22%), transcription and translation (11%), and cellular processes (9...

  15. In vivo imaging of inducible tyrosinase gene expression with an ultrasound array-based photoacoustic system

    Science.gov (United States)

    Harrison, Tyler; Paproski, Robert J.; Zemp, Roger J.

    2012-02-01

    Tyrosinase, a key enzyme in the production of melanin, has shown promise as a reporter of genetic activity. While green fluorescent protein has been used extensively in this capacity, it is limited in its ability to provide information deep in tissue at a reasonable resolution. As melanin is a strong absorber of light, it is possible to image gene expression using tyrosinase with photoacoustic imaging technologies, resulting in excellent resolutions at multiple-centimeter depths. While our previous work has focused on creating and imaging MCF-7 cells with doxycycline-controlled tyrosinase expression, we have now established the viability of these cells in a murine model. Using an array-based photoacoustic imaging system with 5 MHz center frequency, we capture interleaved ultrasound and photoacoustic images of tyrosinase-expressing MCF-7 tumors both in a tissue mimicking phantom, and in vivo. Images of both the tyrosinase-expressing tumor and a control tumor are presented as both coregistered ultrasound-photoacoustic B-scan images and 3-dimensional photoacoustic volumes created by mechanically scanning the transducer. We find that the tyrosinase-expressing tumor is visible with a signal level 12dB greater than that of the control tumor in vivo. Phantom studies with excised tumors show that the tyrosinase-expressing tumor is visible at depths in excess of 2cm, and have suggested that our imaging system is sensitive to a transfection rate of less than 1%.

  16. Sex-based differences in gene expression in hippocampus following postnatal lead exposure

    International Nuclear Information System (INIS)

    Schneider, J.S.; Anderson, D.W.; Sonnenahalli, H.; Vadigepalli, R.

    2011-01-01

    The influence of sex as an effect modifier of childhood lead poisoning has received little systematic attention. Considering the paucity of information available concerning the interactive effects of lead and sex on the brain, the current study examined the interactive effects of lead and sex on gene expression patterns in the hippocampus, a structure involved in learning and memory. Male or female rats were fed either 1500 ppm lead-containing chow or control chow for 30 days beginning at weaning.Blood lead levels were 26.7 ± 2.1 μg/dl and 27.1 ± 1.7 μg/dl for females and males, respectively. The expression of 175 unique genes was differentially regulated between control male and female rats. A total of 167 unique genes were differentially expressed in response to lead in either males or females. Lead exposure had a significant effect without a significant difference between male and female responses in 77 of these genes. In another set of 71 genes, there were significant differences in male vs. female response. A third set of 30 genes was differentially expressed in opposite directions in males vs. females, with the majority of genes expressed at a lower level in females than in males. Highly differentially expressed genes in males and females following lead exposure were associated with diverse biological pathways and functions. These results show that a brief exposure to lead produced significant changes in expression of a variety of genes in the hippocampus and that the response of the brain to a given lead exposure may vary depending on sex. - Highlights: → Postnatal lead exposure has a significant effect on hippocampal gene expression patterns. → At least one set of genes was affected in opposite directions in males and females. → Differentially expressed genes were associated with diverse biological pathways.

  17. Problem-Based Test: The Effect of Fibroblast Growth Factor on Gene Expression

    Science.gov (United States)

    Szeberenyi, Jozsef

    2011-01-01

    This paper shows the results of an experiment in which the effects of fibroblast growth factor (FGF), actinomycin D (Act D; an inhibitor of transcription), and cycloheximide (CHX; an inhibitor of translation) were studied on the expression of two genes: a gene called "Fnk" and the gene coding for glyceraldehyde-3-phosphate dehydrogenase (GAPDH).…

  18. Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

    Directory of Open Access Journals (Sweden)

    Eils Roland

    2005-11-01

    Full Text Available Abstract Background The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods. Results In contrast to a meta-analysis approach where results of different studies are combined on an interpretative level, we investigate here how to directly integrate raw microarray data from different studies for the purpose of supervised classification analysis. We use median rank scores and quantile discretization to derive numerically comparable measures of gene expression from different platforms. These transformed data are then used for training of classifiers based on support vector machines. We apply this approach to six publicly available cancer microarray gene expression data sets, which consist of three pairs of studies, each examining the same type of cancer, i.e. breast cancer, prostate cancer or acute myeloid leukemia. For each pair, one study was performed by means of cDNA microarrays and the other by means of oligonucleotide microarrays. In each pair, high classification accuracies (> 85% were achieved with training and testing on data instances randomly chosen from both data sets in a cross-validation analysis. To exemplify the potential of this cross-platform classification analysis, we use two leukemia microarray data sets to show that important genes with regard to the biology of leukemia are selected in an integrated analysis, which are missed in either single-set analysis. Conclusion Cross-platform classification of multiple cancer microarray data sets yields discriminative gene expression signatures that are found and validated on a large number of microarray samples, generated by different laboratories and

  19. Ecdysone Receptor-based Singular Gene Switches for Regulated Transgene Expression in Cells and Adult Rodent Tissues

    Directory of Open Access Journals (Sweden)

    Seoghyun Lee

    2016-01-01

    Full Text Available Controlled gene expression is an indispensable technique in biomedical research. Here, we report a convenient, straightforward, and reliable way to induce expression of a gene of interest with negligible background expression compared to the most widely used tetracycline (Tet-regulated system. Exploiting a Drosophila ecdysone receptor (EcR-based gene regulatory system, we generated nonviral and adenoviral singular vectors designated as pEUI(+ and pENTR-EUI, respectively, which contain all the required elements to guarantee regulated transgene expression (GAL4-miniVP16-EcR, termed GvEcR hereafter, and 10 tandem repeats of an upstream activation sequence promoter followed by a multiple cloning site. Through the transient and stable transfection of mammalian cell lines with reporter genes, we validated that tebufenozide, an ecdysone agonist, reversibly induced gene expression, in a dose- and time-dependent manner, with negligible background expression. In addition, we created an adenovirus derived from the pENTR-EUI vector that readily infected not only cultured cells but also rodent tissues and was sensitive to tebufenozide treatment for regulated transgene expression. These results suggest that EcR-based singular gene regulatory switches would be convenient tools for the induction of gene expression in cells and tissues in a tightly controlled fashion.

  20. Human Lacrimal Gland Gene Expression.

    Directory of Open Access Journals (Sweden)

    Vinay Kumar Aakalu

    Full Text Available 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.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.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.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.

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

    International Nuclear Information System (INIS)

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

    2004-01-01

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

  2. GOurmet: A tool for quantitative comparison and visualization of gene expression profiles based on gene ontology (GO) distributions

    OpenAIRE

    Doherty, Jason M; Carmichael, Lynn K; Mills, Jason C

    2006-01-01

    Abstract Background The ever-expanding population of gene expression profiles (EPs) from specified cells and tissues under a variety of experimental conditions is an important but difficult resource for investigators to utilize effectively. Software tools have been recently developed to use the distribution of gene ontology (GO) terms associated with the genes in an EP to identify specific biological functions or processes that are over- or under-represented in that EP relative to other EPs. ...

  3. A Host-Based RT-PCR Gene Expression Signature to Identify Acute Respiratory Viral Infection

    Science.gov (United States)

    Zaas, Aimee K.; Burke, Thomas; Chen, Minhua; McClain, Micah; Nicholson, Bradly; Veldman, Timothy; Tsalik, Ephraim L.; Fowler, Vance; Rivers, Emanuel P.; Otero, Ronny; Kingsmore, Stephen F.; Voora, Deepak; Lucas, Joseph; Hero, Alfred O.; Carin, Lawrence; Woods, Christopher W.; Ginsburg, Geoffrey S.

    2014-01-01

    Improved ways to diagnose acute respiratory viral infections could decrease inappropriate antibacterial use and serve as a vital triage mechanism in the event of a potential viral pandemic. Measurement of the host response to infection is an alternative to pathogen-based diagnostic testing and may improve diagnostic accuracy. We have developed a host-based assay with a reverse transcription polymerase chain reaction (RT-PCR) TaqMan low-density array (TLDA) platform for classifying respiratory viral infection. We developed the assay using two cohorts experimentally infected with influenza A H3N2/Wisconsin or influenza A H1N1/Brisbane, and validated the assay in a sample of adults presenting to the emergency department with fever (n = 102) and in healthy volunteers (n = 41). Peripheral blood RNA samples were obtained from individuals who underwent experimental viral challenge or who presented to the emergency department and had microbiologically proven viral respiratory infection or systemic bacterial infection. The selected gene set on the RT-PCR TLDA assay classified participants with experimentally induced influenza H3N2 and H1N1 infection with 100 and 87% accuracy, respectively. We validated this host gene expression signature in a cohort of 102 individuals arriving at the emergency department. The sensitivity of the RT-PCR test was 89% [95% confidence interval (CI), 72 to 98%], and the specificity was 94% (95% CI, 86 to 99%). These results show that RT-PCR–based detection of a host gene expression signature can classify individuals with respiratory viral infection and sets the stage for prospective evaluation of this diagnostic approach in a clinical setting. PMID:24048524

  4. ARNetMiT R Package: association rules based gene co-expression networks of miRNA targets.

    Science.gov (United States)

    Özgür Cingiz, M; Biricik, G; Diri, B

    2017-03-31

    miRNAs are key regulators that bind to target genes to suppress their gene expression level. The relations between miRNA-target genes enable users to derive co-expressed genes that may be involved in similar biological processes and functions in cells. We hypothesize that target genes of miRNAs are co-expressed, when they are regulated by multiple miRNAs. With the usage of these co-expressed genes, we can theoretically construct co-expression networks (GCNs) related to 152 diseases. In this study, we introduce ARNetMiT that utilize a hash based association rule algorithm in a novel way to infer the GCNs on miRNA-target genes data. We also present R package of ARNetMiT, which infers and visualizes GCNs of diseases that are selected by users. Our approach assumes miRNAs as transactions and target genes as their items. Support and confidence values are used to prune association rules on miRNA-target genes data to construct support based GCNs (sGCNs) along with support and confidence based GCNs (scGCNs). We use overlap analysis and the topological features for the performance analysis of GCNs. We also infer GCNs with popular GNI algorithms for comparison with the GCNs of ARNetMiT. Overlap analysis results show that ARNetMiT outperforms the compared GNI algorithms. We see that using high confidence values in scGCNs increase the ratio of the overlapped gene-gene interactions between the compared methods. According to the evaluation of the topological features of ARNetMiT based GCNs, the degrees of nodes have power-law distribution. The hub genes discovered by ARNetMiT based GCNs are consistent with the literature.

  5. Gene expression in colorectal cancer

    DEFF Research Database (Denmark)

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

    2002-01-01

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

  6. Prediction of operon-like gene clusters in the Arabidopsis thaliana genome based on co-expression analysis of neighboring genes.

    Science.gov (United States)

    Wada, Masayoshi; Takahashi, Hiroki; Altaf-Ul-Amin, Md; Nakamura, Kensuke; Hirai, Masami Y; Ohta, Daisaku; Kanaya, Shigehiko

    2012-07-15

    Operon-like arrangements of genes occur in eukaryotes ranging from yeasts and filamentous fungi to nematodes, plants, and mammals. In plants, several examples of operon-like gene clusters involved in metabolic pathways have recently been characterized, e.g. the cyclic hydroxamic acid pathways in maize, the avenacin biosynthesis gene clusters in oat, the thalianol pathway in Arabidopsis thaliana, and the diterpenoid momilactone cluster in rice. Such operon-like gene clusters are defined by their co-regulation or neighboring positions within immediate vicinity of chromosomal regions. A comprehensive analysis of the expression of neighboring genes therefore accounts a crucial step to reveal the complete set of operon-like gene clusters within a genome. Genome-wide prediction of operon-like gene clusters should contribute to functional annotation efforts and provide novel insight into evolutionary aspects acquiring certain biological functions as well. We predicted co-expressed gene clusters by comparing the Pearson correlation coefficient of neighboring genes and randomly selected gene pairs, based on a statistical method that takes false discovery rate (FDR) into consideration for 1469 microarray gene expression datasets of A. thaliana. We estimated that A. thaliana contains 100 operon-like gene clusters in total. We predicted 34 statistically significant gene clusters consisting of 3 to 22 genes each, based on a stringent FDR threshold of 0.1. Functional relationships among genes in individual clusters were estimated by sequence similarity and functional annotation of genes. Duplicated gene pairs (determined based on BLAST with a cutoff of EOperon-like clusters tend to include genes encoding bio-machinery associated with ribosomes, the ubiquitin/proteasome system, secondary metabolic pathways, lipid and fatty-acid metabolism, and the lipid transfer system. Copyright © 2012 Elsevier B.V. All rights reserved.

  7. A modified ABCDE model of flowering in orchids based on gene expression profiling studies of the moth orchid Phalaenopsis aphrodite.

    Directory of Open Access Journals (Sweden)

    Chun-Lin Su

    Full Text Available Previously we developed genomic resources for orchids, including transcriptomic analyses using next-generation sequencing techniques and construction of a web-based orchid genomic database. Here, we report a modified molecular model of flower development in the Orchidaceae based on functional analysis of gene expression profiles in Phalaenopsis aphrodite (a moth orchid that revealed novel roles for the transcription factors involved in floral organ pattern formation. Phalaenopsis orchid floral organ-specific genes were identified by microarray analysis. Several critical transcription factors including AP3, PI, AP1 and AGL6, displayed distinct spatial distribution patterns. Phylogenetic analysis of orchid MADS box genes was conducted to infer the evolutionary relationship among floral organ-specific genes. The results suggest that gene duplication MADS box genes in orchid may have resulted in their gaining novel functions during evolution. Based on these analyses, a modified model of orchid flowering was proposed. Comparison of the expression profiles of flowers of a peloric mutant and wild-type Phalaenopsis orchid further identified genes associated with lip morphology and peloric effects. Large scale investigation of gene expression profiles revealed that homeotic genes from the ABCDE model of flower development classes A and B in the Phalaenopsis orchid have novel functions due to evolutionary diversification, and display differential expression patterns.

  8. A modified ABCDE model of flowering in orchids based on gene expression profiling studies of the moth orchid Phalaenopsis aphrodite.

    Science.gov (United States)

    Su, Chun-Lin; Chen, Wan-Chieh; Lee, Ann-Ying; Chen, Chun-Yi; Chang, Yao-Chien Alex; Chao, Ya-Ting; Shih, Ming-Che

    2013-01-01

    Previously we developed genomic resources for orchids, including transcriptomic analyses using next-generation sequencing techniques and construction of a web-based orchid genomic database. Here, we report a modified molecular model of flower development in the Orchidaceae based on functional analysis of gene expression profiles in Phalaenopsis aphrodite (a moth orchid) that revealed novel roles for the transcription factors involved in floral organ pattern formation. Phalaenopsis orchid floral organ-specific genes were identified by microarray analysis. Several critical transcription factors including AP3, PI, AP1 and AGL6, displayed distinct spatial distribution patterns. Phylogenetic analysis of orchid MADS box genes was conducted to infer the evolutionary relationship among floral organ-specific genes. The results suggest that gene duplication MADS box genes in orchid may have resulted in their gaining novel functions during evolution. Based on these analyses, a modified model of orchid flowering was proposed. Comparison of the expression profiles of flowers of a peloric mutant and wild-type Phalaenopsis orchid further identified genes associated with lip morphology and peloric effects. Large scale investigation of gene expression profiles revealed that homeotic genes from the ABCDE model of flower development classes A and B in the Phalaenopsis orchid have novel functions due to evolutionary diversification, and display differential expression patterns.

  9. Human Kidney Tubule-Specific Gene Expression Based Dissection of Chronic Kidney Disease Traits

    OpenAIRE

    Pazit Beckerman; Chengxiang Qiu; Jihwan Park; Nora Ledo; Yi-An Ko; Ae-Seo Deok Park; Sang-Youb Han; Peter Choi; Matthew Palmer; Katalin Susztak

    2017-01-01

    Chronic kidney disease (CKD) has diverse phenotypic manifestations including structural (such as fibrosis) and functional (such as glomerular filtration rate and albuminuria) alterations. Gene expression profiling has recently gained popularity as an important new tool for precision medicine approaches. Here we used unbiased and directed approaches to understand how gene expression captures different CKD manifestations in patients with diabetic and hypertensive CKD. Transcriptome data from ni...

  10. An Individual-Based Diploid Model Predicts Limited Conditions Under Which Stochastic Gene Expression Becomes Advantageous

    KAUST Repository

    Matsumoto, Tomotaka

    2015-11-24

    Recent studies suggest the existence of a stochasticity in gene expression (SGE) in many organisms, and its non-negligible effect on their phenotype and fitness. To date, however, how SGE affects the key parameters of population genetics are not well understood. SGE can increase the phenotypic variation and act as a load for individuals, if they are at the adaptive optimum in a stable environment. On the other hand, part of the phenotypic variation caused by SGE might become advantageous if individuals at the adaptive optimum become genetically less-adaptive, for example due to an environmental change. Furthermore, SGE of unimportant genes might have little or no fitness consequences. Thus, SGE can be advantageous, disadvantageous, or selectively neutral depending on its context. In addition, there might be a genetic basis that regulates magnitude of SGE, which is often referred to as “modifier genes,” but little is known about the conditions under which such an SGE-modifier gene evolves. In the present study, we conducted individual-based computer simulations to examine these conditions in a diploid model. In the simulations, we considered a single locus that determines organismal fitness for simplicity, and that SGE on the locus creates fitness variation in a stochastic manner. We also considered another locus that modifies the magnitude of SGE. Our results suggested that SGE was always deleterious in stable environments and increased the fixation probability of deleterious mutations in this model. Even under frequently changing environmental conditions, only very strong natural selection made SGE adaptive. These results suggest that the evolution of SGE-modifier genes requires strict balance among the strength of natural selection, magnitude of SGE, and frequency of environmental changes. However, the degree of dominance affected the condition under which SGE becomes advantageous, indicating a better opportunity for the evolution of SGE in different genetic

  11. Identification of human circadian genes based on time course gene expression profiles by using a deep learning method.

    Science.gov (United States)

    Cui, Peng; Zhong, Tingyan; Wang, Zhuo; Wang, Tao; Zhao, Hongyu; Liu, Chenglin; Lu, Hui

    2017-12-12

    Circadian genes express periodically in an approximate 24-h period and the identification and study of these genes can provide deep understanding of the circadian control which plays significant roles in human health. Although many circadian gene identification algorithms have been developed, large numbers of false positives and low coverage are still major problems in this field. In this study we constructed a novel computational framework for circadian gene identification using deep neural networks (DNN) - a deep learning algorithm which can represent the raw form of data patterns without imposing assumptions on the expression distribution. Firstly, we transformed time-course gene expression data into categorical-state data to denote the changing trend of gene expression. Two distinct expression patterns emerged after clustering of the state data for circadian genes from our manually created learning dataset. DNN was then applied to discriminate the aperiodic genes and the two subtypes of periodic genes. In order to assess the performance of DNN, four commonly used machine learning methods including k-nearest neighbors, logistic regression, naïve Bayes, and support vector machines were used for comparison. The results show that the DNN model achieves the best balanced precision and recall. Next, we conducted large scale circadian gene detection using the trained DNN model for the remaining transcription profiles. Comparing with JTK_CYCLE and a study performed by Möller-Levet et al. (doi: https://doi.org/10.1073/pnas.1217154110), we identified 1132 novel periodic genes. Through the functional analysis of these novel circadian genes, we found that the GTPase superfamily exhibits distinct circadian expression patterns and may provide a molecular switch of circadian control of the functioning of the immune system in human blood. Our study provides novel insights into both the circadian gene identification field and the study of complex circadian-driven biological

  12. Citrus plastid-related gene profiling based on expressed sequence tag analyses

    Directory of Open Access Journals (Sweden)

    Tercilio Calsa Jr.

    2007-01-01

    Full Text Available Plastid-related sequences, derived from putative nuclear or plastome genes, were searched in a large collection of expressed sequence tags (ESTs and genomic sequences from the Citrus Biotechnology initiative in Brazil. The identified putative Citrus chloroplast gene sequences were compared to those from Arabidopsis, Eucalyptus and Pinus. Differential expression profiling for plastid-directed nuclear-encoded proteins and photosynthesis-related gene expression variation between Citrus sinensis and Citrus reticulata, when inoculated or not with Xylella fastidiosa, were also analyzed. Presumed Citrus plastome regions were more similar to Eucalyptus. Some putative genes appeared to be preferentially expressed in vegetative tissues (leaves and bark or in reproductive organs (flowers and fruits. Genes preferentially expressed in fruit and flower may be associated with hypothetical physiological functions. Expression pattern clustering analysis suggested that photosynthesis- and carbon fixation-related genes appeared to be up- or down-regulated in a resistant or susceptible Citrus species after Xylella inoculation in comparison to non-infected controls, generating novel information which may be helpful to develop novel genetic manipulation strategies to control Citrus variegated chlorosis (CVC.

  13. Integrated Analysis of Expression Profile Based on Differentially Expressed Genes in Middle Cerebral Artery Occlusion Animal Models

    Directory of Open Access Journals (Sweden)

    Huaqiang Zhou

    2016-05-01

    Full Text Available Stroke is one of the most common causes of death, only second to heart disease. Molecular investigations about stroke are in acute shortage nowadays. This study is intended to explore a gene expression profile after brain ischemia reperfusion. Meta-analysis, differential expression analysis, and integrated analysis were employed on an eight microarray series. We explored the functions and pathways of target genes in gene ontology (GO enrichment analysis and constructed a protein-protein interaction network. Meta-analysis identified 360 differentially expressed genes (DEGs for Mus musculus and 255 for Rattus norvegicus. Differential expression analysis identified 44 DEGs for Mus musculus and 21 for Rattus norvegicus. Timp1 and Lcn2 were overexpressed in both species. The cytokine-cytokine receptor interaction and chemokine signaling pathway were highly enriched for the Kyoto Encyclopedia of Genes and Genomes (KEGG pathway. We have exhibited a global view of the potential molecular differences between middle cerebral artery occlusion (MCAO animal model and sham for Mus musculus or Rattus norvegicus, including the biological process and enriched pathways in DEGs. This research helps contribute to a clearer understanding of the inflammation process and accurate identification of ischemic infarction stages, which might be transformed into a therapeutic approach.

  14. Characterizing embryonic gene expression patterns in the mouse using nonredundant sequence-based selection

    DEFF Research Database (Denmark)

    Sousa-Nunes, Rita; Rana, Amer Ahmed; Kettleborough, Ross

    2003-01-01

    This article investigates the expression patterns of 160 genes that are expressed during early mouse development. The cDNAs were isolated from 7.5 d postcoitum (dpc) endoderm, a region that comprises visceral endoderm (VE), definitive endoderm, and the node-tissues that are required for the initi...

  15. A PSO-Based Approach for Pathway Marker Identification From Gene Expression Data.

    Science.gov (United States)

    Mandal, Monalisa; Mondal, Jyotirmay; Mukhopadhyay, Anirban

    2015-09-01

    In this article, a new and robust pathway activity inference scheme is proposed from gene expression data using Particle Swarm Optimization (PSO). From microarray gene expression data, the corresponding pathway information of the genes are collected from a public database. For identifying the pathway markers, the expression values of each pathway consisting of genes, termed as pathway activity, are summarized. To measure the goodness of a pathway activity vector, t-score is widely used in the existing literature. The weakness of existing techniques for inferring pathway activity is that they intend to consider all the member genes of a pathway. But in reality, all the member genes may not be significant to the corresponding pathway. Therefore, those genes, which are responsible in the corresponding pathway, should be included only. Motivated by this, in the proposed method, using PSO, important genes with respect to each pathway are identified. The objective is to maximize the average t-score. For the pathway activities inferred from different percentage of significant pathways, the average absolute t -scores are plotted. In addition, the top 50% pathway markers are evaluated using 10-fold cross validation and its performance is compared with that of other existing techniques. Biological relevance of the results is also studied.

  16. A new measure for gene expression biclustering based on non-parametric correlation.

    Science.gov (United States)

    Flores, Jose L; Inza, Iñaki; Larrañaga, Pedro; Calvo, Borja

    2013-12-01

    One of the emerging techniques for performing the analysis of the DNA microarray data known as biclustering is the search of subsets of genes and conditions which are coherently expressed. These subgroups provide clues about the main biological processes. Until now, different approaches to this problem have been proposed. Most of them use the mean squared residue as quality measure but relevant and interesting patterns can not be detected such as shifting, or scaling patterns. Furthermore, recent papers show that there exist new coherence patterns involved in different kinds of cancer and tumors such as inverse relationships between genes which can not be captured. The proposed measure is called Spearman's biclustering measure (SBM) which performs an estimation of the quality of a bicluster based on the non-linear correlation among genes and conditions simultaneously. The search of biclusters is performed by using a evolutionary technique called estimation of distribution algorithms which uses the SBM measure as fitness function. This approach has been examined from different points of view by using artificial and real microarrays. The assessment process has involved the use of quality indexes, a set of bicluster patterns of reference including new patterns and a set of statistical tests. It has been also examined the performance using real microarrays and comparing to different algorithmic approaches such as Bimax, CC, OPSM, Plaid and xMotifs. SBM shows several advantages such as the ability to recognize more complex coherence patterns such as shifting, scaling and inversion and the capability to selectively marginalize genes and conditions depending on the statistical significance. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  17. Identification of hub genes and pathways associated with bladder cancer based on co-expression network analysis.

    Science.gov (United States)

    Zhang, Dong-Qing; Zhou, Chang-Kuo; Chen, Shou-Zhen; Yang, Yue; Shi, Ben-Kang

    2017-07-01

    The aim of the present study was to identify hub genes and signaling pathways associated with bladder cancer (BC) utilizing centrality analysis and pathway enrichment analysis. The differentially expressed genes (DEGs) were screened from the ArrayExpress database between normal subjects and BC patients. Co-expression networks of BC were constructed using differentially co-expressed genes and links, and hub genes were investigated by degree centrality analysis of co-expression networks in BC. The enriched signaling pathways were investigated by Kyoto Encyclopedia of Genes and Genomes database analysis based on the DEGs. The hub gene expression in BC tissues was validated using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and western blotting. A total of 329 DEGs were screened, including 147 upregulated and 182 downregulated genes. The co-expression network constructed between BC and normal controls consisted of 182 nodes and 434 edges, and the two genes in each gene pair were differentially co-expressed genes. Centrality analysis of co-expression networks suggested that the top 5 hub genes with high degree included lectin, galactoside-binding, soluble, 4 (LGALS4), protein tyrosine phosphatase, receptor type N2 (PTPRN2), transmembrane protease, serine 11E (TMPRSS11E), tripartite motif containing 31 (TRIM31) and potassium voltage-gated channel subfamily D member 3 (KCND3) . Pathway analysis revealed that the 329 DEGs were significantly enriched in 5 terms (cell cycle, DNA replication, oocyte meiosis, p53 signaling pathway and peroxisome proliferator-activated receptor signaling pathway). According to RT-qPCR and western blot analysis, 4/5 hub genes were significantly expressed, including LGALS4, PTPRN2, TMPRSS11E, TRIM31 ; however, KCND3 was not significantly expressed. In the present study, 5 hub genes were successfully identified ( LGALS4, PTPRN2, TMPRSS11E, TRIM31 and KCND3 ) and 5 biological pathways that may be underlying biomarkers for

  18. Genome-Wide Constitutively Expressed Gene Analysis and New Reference Gene Selection Based on Transcriptome Data: A Case Study from Poplar/Canker Disease Interaction

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    Jiaping Zhao

    2017-10-01

    Full Text Available A number of transcriptome datasets for differential expression (DE genes have been widely used for understanding organismal biology, but these datasets also contain untapped information that can be used to develop more precise analytical tools. With the use of transcriptome data generated from poplar/canker disease interaction system, we describe a methodology to identify candidate reference genes from high-throughput sequencing data. This methodology will improve the accuracy of RT-qPCR and will lead to better standards for the normalization of expression data. Expression stability analysis from xylem and phloem of Populus bejingensis inoculated with the fungal canker pathogen Botryosphaeria dothidea revealed that 729 poplar transcripts (1.11% were stably expressed, at a threshold level of coefficient of variance (CV of FPKM < 20% and maximum fold change (MFC of FPKM < 2.0. Expression stability and bioinformatics analysis suggested that commonly used house-keeping (HK genes were not the most appropriate internal controls: 70 of the 72 commonly used HK genes were not stably expressed, 45 of the 72 produced multiple isoform transcripts, and some of their reported primers produced unspecific amplicons in PCR amplification. RT-qPCR analysis to compare and evaluate the expression stability of 10 commonly used poplar HK genes and 20 of the 729 newly-identified stably expressed transcripts showed that some of the newly-identified genes (such as SSU_S8e, LSU_L5e, and 20S_PSU had higher stability ranking than most of commonly used HK genes. Based on these results, we recommend a pipeline for deriving reference genes from transcriptome data. An appropriate candidate gene should have a unique transcript, constitutive expression, CV value of expression < 20% (or possibly 30% and MFC value of expression <2, and an expression level of 50–1,000 units. Lastly, when four of the newly identified HK genes were used in the normalization of expression data for 20

  19. ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis

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    Saurav Mallik

    2017-12-01

    Full Text Available For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures—weighted rank-based Jaccard and Cosine measures—and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm—RANWAR—was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.

  20. Classification of dengue fever patients based on gene expression data using support vector machines.

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    Ana Lisa V Gomes

    Full Text Available BACKGROUND: Symptomatic infection by dengue virus (DENV can range from dengue fever (DF to dengue haemorrhagic fever (DHF, however, the determinants of DF or DHF progression are not completely understood. It is hypothesised that host innate immune response factors are involved in modulating the disease outcome and the expression levels of genes involved in this response could be used as early prognostic markers for disease severity. METHODOLOGY/PRINCIPAL FINDINGS: mRNA expression levels of genes involved in DENV innate immune responses were measured using quantitative real time PCR (qPCR. Here, we present a novel application of the support vector machines (SVM algorithm to analyze the expression pattern of 12 genes in peripheral blood mononuclear cells (PBMCs of 28 dengue patients (13 DHF and 15 DF during acute viral infection. The SVM model was trained using gene expression data of these genes and achieved the highest accuracy of approximately 85% with leave-one-out cross-validation. Through selective removal of gene expression data from the SVM model, we have identified seven genes (MYD88, TLR7, TLR3, MDA5, IRF3, IFN-alpha and CLEC5A that may be central in differentiating DF patients from DHF, with MYD88 and TLR7 observed to be the most important. Though the individual removal of expression data of five other genes had no impact on the overall accuracy, a significant combined role was observed when the SVM model of the two main genes (MYD88 and TLR7 was re-trained to include the five genes, increasing the overall accuracy to approximately 96%. CONCLUSIONS/SIGNIFICANCE: Here, we present a novel use of the SVM algorithm to classify DF and DHF patients, as well as to elucidate the significance of the various genes involved. It was observed that seven genes are critical in classifying DF and DHF patients: TLR3, MDA5, IRF3, IFN-alpha, CLEC5A, and the two most important MYD88 and TLR7. While these preliminary results are promising, further

  1. Investigating a multigene prognostic assay based on significant pathways for Luminal A breast cancer through gene expression profile analysis.

    Science.gov (United States)

    Gao, Haiyan; Yang, Mei; Zhang, Xiaolan

    2018-04-01

    The present study aimed to investigate potential recurrence-risk biomarkers based on significant pathways for Luminal A breast cancer through gene expression profile analysis. Initially, the gene expression profiles of Luminal A breast cancer patients were downloaded from The Cancer Genome Atlas database. The differentially expressed genes (DEGs) were identified using a Limma package and the hierarchical clustering analysis was conducted for the DEGs. In addition, the functional pathways were screened using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and rank ratio calculation. The multigene prognostic assay was exploited based on the statistically significant pathways and its prognostic function was tested using train set and verified using the gene expression data and survival data of Luminal A breast cancer patients downloaded from the Gene Expression Omnibus. A total of 300 DEGs were identified between good and poor outcome groups, including 176 upregulated genes and 124 downregulated genes. The DEGs may be used to effectively distinguish Luminal A samples with different prognoses verified by hierarchical clustering analysis. There were 9 pathways screened as significant pathways and a total of 18 DEGs involved in these 9 pathways were identified as prognostic biomarkers. According to the survival analysis and receiver operating characteristic curve, the obtained 18-gene prognostic assay exhibited good prognostic function with high sensitivity and specificity to both the train and test samples. In conclusion the 18-gene prognostic assay including the key genes, transcription factor 7-like 2, anterior parietal cortex and lymphocyte enhancer factor-1 may provide a new method for predicting outcomes and may be conducive to the promotion of precision medicine for Luminal A breast cancer.

  2. Assessing and selecting gene expression signals based upon the quality of the measured dynamics

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    Androulakis Ioannis P

    2009-02-01

    Full Text Available Abstract Background One of the challenges with modeling the temporal progression of biological signals is dealing with the effect of noise and the limited number of replicates at each time point. Given the rising interest in utilizing predictive mathematical models to describe the biological response of an organism or analysis such as clustering and gene ontology enrichment, it is important to determine whether the dynamic progression of the data has been accurately captured despite the limited number of replicates, such that one can have confidence that the results of the analysis are capturing important salient dynamic features. Results By pre-selecting genes based upon quality before the identification of differential expression via algorithm such as EDGE, it was found that the percentage of statistically enriched ontologies (p Conclusion We have developed an algorithm that quantifies the quality of temporal biological signal rather than whether the signal illustrates a significant change over the experimental time course. Because the use of these temporal signals, whether it is in mathematical modeling or clustering, focuses upon the entire time series, it is necessary to develop a method to quantify and select for signals which conform to this ideal. By doing this, we have demonstrated a marked and consistent improvement in the results of a clustering exercise over multiple experiments, microarray platforms, and experimental designs.

  3. In Silico Analysis of Microarray-Based Gene Expression Profiles Predicts Tumor Cell Response to Withanolides

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    Thomas Efferth

    2012-05-01

    Full Text Available Withania somnifera (L. Dunal (Indian ginseng, winter cherry, Solanaceae is widely used in traditional medicine. Roots are either chewed or used to prepare beverages (aqueous decocts. The major secondary metabolites of Withania somnifera are the withanolides, which are C-28-steroidal lactone triterpenoids. Withania somnifera extracts exert chemopreventive and anticancer activities in vitro and in vivo. The aims of the present in silico study were, firstly, to investigate whether tumor cells develop cross-resistance between standard anticancer drugs and withanolides and, secondly, to elucidate the molecular determinants of sensitivity and resistance of tumor cells towards withanolides. Using IC50 concentrations of eight different withanolides (withaferin A, withaferin A diacetate, 3-azerininylwithaferin A, withafastuosin D diacetate, 4-B-hydroxy-withanolide E, isowithanololide E, withafastuosin E, and withaperuvin and 19 established anticancer drugs, we analyzed the cross-resistance profile of 60 tumor cell lines. The cell lines revealed cross-resistance between the eight withanolides. Consistent cross-resistance between withanolides and nitrosoureas (carmustin, lomustin, and semimustin was also observed. Then, we performed transcriptomic microarray-based COMPARE and hierarchical cluster analyses of mRNA expression to identify mRNA expression profiles predicting sensitivity or resistance towards withanolides. Genes from diverse functional groups were significantly associated with response of tumor cells to withaferin A diacetate, e.g. genes functioning in DNA damage and repair, stress response, cell growth regulation, extracellular matrix components, cell adhesion and cell migration, constituents of the ribosome, cytoskeletal organization and regulation, signal transduction, transcription factors, and others.

  4. Modulation of gene expression made easy

    DEFF Research Database (Denmark)

    Solem, Christian; Jensen, Peter Ruhdal

    2002-01-01

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

  5. A Double-Switch Cell Fusion-Inducible Transgene Expression System for Neural Stem Cell-Based Antiglioma Gene Therapy

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    Yumei Luo

    2015-01-01

    Full Text Available Recent progress in neural stem cell- (NSC- based tumor-targeted gene therapy showed that NSC vectors expressing an artificially engineered viral fusogenic protein, VSV-G H162R, could cause tumor cell death specifically under acidic tumor microenvironment by syncytia formation; however, the killing efficiency still had much room to improve. In the view that coexpression of another antitumoral gene with VSV-G can augment the bystander effect, a synthetic regulatory system that triggers transgene expression in a cell fusion-inducible manner has been proposed. Here we have developed a double-switch cell fusion-inducible transgene expression system (DoFIT to drive transgene expression upon VSV-G-mediated NSC-glioma cell fusion. In this binary system, transgene expression is coregulated by a glioma-specific promoter and targeting sequences of a microRNA (miR that is highly expressed in NSCs but lowly expressed in glioma cells. Thus, transgene expression is “switched off” by the miR in NSC vectors, but after cell fusion with glioma cells, the miR is diluted and loses its suppressive effect. Meanwhile, in the syncytia, transgene expression is “switched on” by the glioma-specific promoter. Our in vitro and in vivo experimental data show that DoFIT successfully abolishes luciferase reporter gene expression in NSC vectors but activates it specifically after VSV-G-mediated NSC-glioma cell fusion.

  6. Prioritization of candidate genes for cattle reproductive traits, based on protein-protein interactions, gene expression, and text-mining

    DEFF Research Database (Denmark)

    Hulsegge, Ina; Woelders, Henri; Smits, Mari

    2013-01-01

    Reproduction is of significant economic importance in dairy cattle. Improved understanding of mechanisms that control estrous behavior and other reproduction traits could help in developing strategies to improve and/or monitor these traits. The objective of this study was to predict and rank genes...... and processes in brain areas and pituitary involved in reproductive traits in cattle using information derived from three different data sources: gene expression, protein-protein interactions, and literature. We identified 59, 89, 53, 23, and 71 genes in bovine amygdala, dorsal hypothalamus, hippocampus......, pituitary, and ventral hypothalamus, respectively, potentially involved in processes underlying estrus and estrous behavior. Functional annotation of the candidate genes points to a number of tissue-specific processes of which the "neurotransmitter/ion channel/synapse" process in the amygdala, "steroid...

  7. Argudas: lessons for argumentation in biology based on a gene expression use case.

    Science.gov (United States)

    McLeod, Kenneth; Ferguson, Gus; Burger, Albert

    2012-01-25

    In situ hybridisation gene expression information helps biologists identify where a gene is expressed. However, the databases that republish the experimental information online are often both incomplete and inconsistent. Non-monotonic reasoning can help resolve such difficulties - one such form of reasoning is computational argumentation. Essentially this involves asking a computer to debate (i.e. reason about) the validity of a particular statement. Arguments are produced for both sides - the statement is true and, the statement is false - then the most powerful argument is used. In this work the computer is asked to debate whether or not a gene is expressed in a particular mouse anatomical structure. The information generated during the debate can be passed to the biological end-user, enabling their own decision-making process. This paper examines the evolution of a system, Argudas, which tests using computational argumentation in an in situ gene hybridisation gene expression use case. Argudas reasons using information extracted from several different online resources that publish gene expression information for the mouse. The development and evaluation of two prototypes is discussed. Throughout a number of issues shall be raised including the appropriateness of computational argumentation in biology and the challenges faced when integrating apparently similar online biological databases. From the work described in this paper it is clear that for argumentation to be effective in the biological domain the argumentation community need to develop further the tools and resources they provide. Additionally, the biological community must tackle the incongruity between overlapping and adjacent resources, thus facilitating the integration and modelling of biological information. Finally, this work highlights both the importance of, and difficulty in creating, a good model of the domain.

  8. Microarray‑based screening of differentially expressed genes in glucocorticoid‑induced avascular necrosis.

    Science.gov (United States)

    Huang, Gangyong; Wei, Yibing; Zhao, Guanglei; Xia, Jun; Wang, Siqun; Wu, Jianguo; Chen, Feiyan; Chen, Jie; Shi, Jingshen

    2017-06-01

    The underlying mechanisms of glucocorticoid (GC)‑induced avascular necrosis of the femoral head (ANFH) have yet to be fully understood, in particular the mechanisms associated with the change of gene expression pattern. The present study aimed to identify key genes with a differential expression pattern in GC‑induced ANFH. E‑MEXP‑2751 microarray data were downloaded from the ArrayExpress database. Differentially expressed genes (DEGs) were identified in 5 femoral head samples of steroid‑induced ANFH rats compared with 5 placebo‑treated rat samples. Gene Ontology (GO) and pathway enrichment analyses were performed upon these DEGs. A total 93 DEGs (46 upregulated and 47 downregulated genes) were identified in GC‑induced ANFH samples. These DEGs were enriched in different GO terms and pathways, including chondrocyte differentiation and detection of chemical stimuli. The enrichment map revealed that skeletal system development was interconnected with several other GO terms by gene overlap. The literature mined network analysis revealed that 5 upregulated genes were associated with femoral necrosis, including parathyroid hormone receptor 1 (PTHR1), vitamin D (1,25‑Dihydroxyvitamin D3) receptor (VDR), collagen, type II, α1, proprotein convertase subtilisin/kexin type 6 and zinc finger protein 354C (ZFP354C). In addition, ZFP354C and VDR were identified to transcription factors. Furthermore, PTHR1 was revealed to interact with VDR, and α‑2‑macroglobulin (A2M) interacted with fibronectin 1 (FN1) in the PPI network. PTHR1 may be involved in GC‑induced ANFH via interacting with VDR. A2M may also be involved in the development of GC‑induced ANFH through interacting with FN1. An improved understanding of the molecular mechanisms underlying GC‑induced ANFH may provide novel targets for diagnostics and therapeutic treatment.

  9. Microarray-based screening of differentially expressed genes in glucocorticoid-induced avascular necrosis

    Science.gov (United States)

    Huang, Gangyong; Wei, Yibing; Zhao, Guanglei; Xia, Jun; Wang, Siqun; Wu, Jianguo; Chen, Feiyan; Chen, Jie; Shi, Jingshen

    2017-01-01

    The underlying mechanisms of glucocorticoid (GC)-induced avascular necrosis of the femoral head (ANFH) have yet to be fully understood, in particular the mechanisms associated with the change of gene expression pattern. The present study aimed to identify key genes with a differential expression pattern in GC-induced ANFH. E-MEXP-2751 microarray data were downloaded from the ArrayExpress database. Differentially expressed genes (DEGs) were identified in 5 femoral head samples of steroid-induced ANFH rats compared with 5 placebo-treated rat samples. Gene Ontology (GO) and pathway enrichment analyses were performed upon these DEGs. A total 93 DEGs (46 upregulated and 47 downregulated genes) were identified in GC-induced ANFH samples. These DEGs were enriched in different GO terms and pathways, including chondrocyte differentiation and detection of chemical stimuli. The enrichment map revealed that skeletal system development was interconnected with several other GO terms by gene overlap. The literature mined network analysis revealed that 5 upregulated genes were associated with femoral necrosis, including parathyroid hormone receptor 1 (PTHR1), vitamin D (1,25-Dihydroxyvitamin D3) receptor (VDR), collagen, type II, α1, proprotein convertase subtilisin/kexin type 6 and zinc finger protein 354C (ZFP354C). In addition, ZFP354C and VDR were identified to transcription factors. Furthermore, PTHR1 was revealed to interact with VDR, and α-2-macroglobulin (A2M) interacted with fibronectin 1 (FN1) in the PPI network. PTHR1 may be involved in GC-induced ANFH via interacting with VDR. A2M may also be involved in the development of GC-induced ANFH through interacting with FN1. An improved understanding of the molecular mechanisms underlying GC-induced ANFH may provide novel targets for diagnostics and therapeutic treatment. PMID:28393228

  10. Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation.

    Science.gov (United States)

    Richard, Arianne C; Lyons, Paul A; Peters, James E; Biasci, Daniele; Flint, Shaun M; Lee, James C; McKinney, Eoin F; Siegel, Richard M; Smith, Kenneth G C

    2014-08-04

    Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray users lack important information regarding the complexities introduced in real-world experimental settings. The recent development of a multiplexed, digital technology for nucleic acid measurement enables counting of individual RNA molecules without amplification and, for the first time, permits such a study. Using a set of human leukocyte subset RNA samples, we compared previously acquired microarray expression values with RNA molecule counts determined by the nCounter Analysis System (NanoString Technologies) in selected genes. We found that gene measurements across samples correlated well between the two platforms, particularly for high-variance genes, while genes deemed unexpressed by the nCounter generally had both low expression and low variance on the microarray. Confirming previous findings from spike-in and dilution datasets, this "gold-standard" comparison demonstrated signal compression that varied dramatically by expression level and, to a lesser extent, by dataset. Most importantly, examination of three different cell types revealed that noise levels differed across tissues. Microarray measurements generally correlate with relative RNA molecule counts within optimal ranges but suffer from expression-dependent accuracy bias and precision that varies across datasets. We urge microarray users to consider expression-level effects in signal interpretation and to evaluate noise properties in each dataset independently.

  11. A novel mutual information-based Boolean network inference method from time-series gene expression data.

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    Shohag Barman

    Full Text Available Inferring a gene regulatory network from time-series gene expression data in systems biology is a challenging problem. Many methods have been suggested, most of which have a scalability limitation due to the combinatorial cost of searching a regulatory set of genes. In addition, they have focused on the accurate inference of a network structure only. Therefore, there is a pressing need to develop a network inference method to search regulatory genes efficiently and to predict the network dynamics accurately.In this study, we employed a Boolean network model with a restricted update rule scheme to capture coarse-grained dynamics, and propose a novel mutual information-based Boolean network inference (MIBNI method. Given time-series gene expression data as an input, the method first identifies a set of initial regulatory genes using mutual information-based feature selection, and then improves the dynamics prediction accuracy by iteratively swapping a pair of genes between sets of the selected regulatory genes and the other genes. Through extensive simulations with artificial datasets, MIBNI showed consistently better performance than six well-known existing methods, REVEAL, Best-Fit, RelNet, CST, CLR, and BIBN in terms of both structural and dynamics prediction accuracy. We further tested the proposed method with two real gene expression datasets for an Escherichia coli gene regulatory network and a fission yeast cell cycle network, and also observed better results using MIBNI compared to the six other methods.Taken together, MIBNI is a promising tool for predicting both the structure and the dynamics of a gene regulatory network.

  12. Molecular portrait of cisplatin induced response in human testis cancer cell lines based on gene expression profiles

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    Soderlund Erik J

    2007-08-01

    Full Text Available Abstract Background Testicular germ cell tumors (TGCTs respond well to cisplatin-based chemotherapy and show a low incidence of acquired resistance compared to most somatic tumors. The reasons for these specific characteristics are not known in detail but seem to be multifactorial. We have studied gene expression profiles of testicular and colon cancer derived cell lines treated with cisplatin. The main goal of this study was to identify novel gene expression profiles with their functional categories and the biochemical pathways that are associated with TGCT cells' response to cisplatin. Results Genes that were differentially expressed between the TGCT cell lines vs the (somatic HCT116 cell line, after cisplatin treatment, were identified using the significance analysis of microarrays (SAM method. The response of TGCT cells was strikingly different from that of HCT116, and we identified 1794 genes that were differentially expressed. Functional classification of these genes showed that they participate in a variety of different and widely distributed functional categories and biochemical pathways. Database mining showed significant association of genes (n = 41 induced by cisplatin in our study, and genes previously reported to by expressed in differentiated TGCT cells. We identified 37 p53-responsive genes that were altered after cisplatin exposure. We also identified 40 target genes for two microRNAs, hsa-mir-372 and 373 that may interfere with p53 signaling in TGCTs. The tumor suppressor genes NEO1 and LATS2, and the estrogen receptor gene ESR1, all have binding sites for p53 and hsa-mir-372/373. NEO1 and LATS2 were down-regulated in TGCT cells following cisplatin exposure, while ESR1 was up-regulated in TGCT cells. Cisplatin-induced genes associated with terminal growth arrest through senescence were identified, indicating associations which were not previously described for TGCT cells. Conclusion By linking our gene expression data to

  13. Integrating Colon Cancer Microarray Data: Associating Locus-Specific Methylation Groups to Gene Expression-Based Classifications

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    Ana Barat

    2015-11-01

    Full Text Available Recently, considerable attention has been paid to gene expression-based classifications of colorectal cancers (CRC and their association with patient prognosis. In addition to changes in gene expression, abnormal DNA-methylation is known to play an important role in cancer onset and development, and colon cancer is no exception to this rule. Large-scale technologies, such as methylation microarray assays and specific sequencing of methylated DNA, have been used to determine whole genome profiles of CpG island methylation in tissue samples. In this article, publicly available microarray-based gene expression and methylation data sets are used to characterize expression subtypes with respect to locus-specific methylation. A major objective was to determine whether integration of these data types improves previously characterized subtypes, or provides evidence for additional subtypes. We used unsupervised clustering techniques to determine methylation-based subgroups, which are subsequently annotated with three published expression-based classifications, comprising from three to six subtypes. Our results showed that, while methylation profiles provide a further basis for segregation of certain (Inflammatory and Goblet-like finer-grained expression-based subtypes, they also suggest that other finer-grained subtypes are not distinctive and can be considered as a single subtype.

  14. Digital Gene Expression Analysis Based on De Novo Transcriptome Assembly Reveals New Genes Associated with Floral Organ Differentiation of the Orchid Plant Cymbidium ensifolium.

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    Fengxi Yang

    Full Text Available Cymbidium ensifolium belongs to the genus Cymbidium of the orchid family. Owing to its spectacular flower morphology, C. ensifolium has considerable ecological and cultural value. However, limited genetic data is available for this non-model plant, and the molecular mechanism underlying floral organ identity is still poorly understood. In this study, we characterize the floral transcriptome of C. ensifolium and present, for the first time, extensive sequence and transcript abundance data of individual floral organs. After sequencing, over 10 Gb clean sequence data were generated and assembled into 111,892 unigenes with an average length of 932.03 base pairs, including 1,227 clusters and 110,665 singletons. Assembled sequences were annotated with gene descriptions, gene ontology, clusters of orthologous group terms, the Kyoto Encyclopedia of Genes and Genomes, and the plant transcription factor database. From these annotations, 131 flowering-associated unigenes, 61 CONSTANS-LIKE (COL unigenes and 90 floral homeotic genes were identified. In addition, four digital gene expression libraries were constructed for the sepal, petal, labellum and gynostemium, and 1,058 genes corresponding to individual floral organ development were identified. Among them, eight MADS-box genes were further investigated by full-length cDNA sequence analysis and expression validation, which revealed two APETALA1/AGL9-like MADS-box genes preferentially expressed in the sepal and petal, two AGAMOUS-like genes particularly restricted to the gynostemium, and four DEF-like genes distinctively expressed in different floral organs. The spatial expression of these genes varied distinctly in different floral mutant corresponding to different floral morphogenesis, which validated the specialized roles of them in floral patterning and further supported the effectiveness of our in silico analysis. This dataset generated in our study provides new insights into the molecular mechanisms

  15. Structure-based predictions broadly link transcription factor mutations to gene expression changes in cancers.

    Science.gov (United States)

    Ashworth, Justin; Bernard, Brady; Reynolds, Sheila; Plaisier, Christopher L; Shmulevich, Ilya; Baliga, Nitin S

    2014-12-01

    Thousands of unique mutations in transcription factors (TFs) arise in cancers, and the functional and biological roles of relatively few of these have been characterized. Here, we used structure-based methods developed specifically for DNA-binding proteins to systematically predict the consequences of mutations in several TFs that are frequently mutated in cancers. The explicit consideration of protein-DNA interactions was crucial to explain the roles and prevalence of mutations in TP53 and RUNX1 in cancers, and resulted in a higher specificity of detection for known p53-regulated genes among genetic associations between TP53 genotypes and genome-wide expression in The Cancer Genome Atlas, compared to existing methods of mutation assessment. Biophysical predictions also indicated that the relative prevalence of TP53 missense mutations in cancer is proportional to their thermodynamic impacts on protein stability and DNA binding, which is consistent with the selection for the loss of p53 transcriptional function in cancers. Structure and thermodynamics-based predictions of the impacts of missense mutations that focus on specific molecular functions may be increasingly useful for the precise and large-scale inference of aberrant molecular phenotypes in cancer and other complex diseases. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  16. Differential gene expression in an elite hybrid rice cultivar (Oryza sativa, L and its parental lines based on SAGE data

    Directory of Open Access Journals (Sweden)

    Chen Chen

    2007-09-01

    Full Text Available Abstract Background It was proposed that differentially-expressed genes, aside from genetic variations affecting protein processing and functioning, between hybrid and its parents provide essential candidates for studying heterosis or hybrid vigor. Based our serial analysis of gene expression (SAGE data from an elite Chinese super-hybrid rice (LYP9 and its parental cultivars (93-11 and PA64s in three major tissue types (leaves, roots and panicles at different developmental stages, we analyzed the transcriptome and looked for candidate genes related to rice heterosis. Results By using an improved strategy of tag-to-gene mapping and two recently annotated genome assemblies (93-11 and PA64s, we identified 10,268 additional high-quality tags, reaching a grand total of 20,595 together with our previous result. We further detected 8.5% and 5.9% physically-mapped genes that are differentially-expressed among the triad (in at least one of the three stages with P-values less than 0.05 and 0.01, respectively. These genes distributed in 12 major gene expression patterns; among them, 406 up-regulated and 469 down-regulated genes (P Conclusion We improved tag-to-gene mapping strategy by combining information from transcript sequences and rice genome annotation, and obtained a more comprehensive view on genes that related to rice heterosis. The candidates for heterosis-related genes among different genotypes provided new avenue for exploring the molecular mechanism underlying heterosis.

  17. Identification of co-expression gene networks, regulatory genes and pathways for obesity based on adipose tissue RNA Sequencing in a porcine model

    DEFF Research Database (Denmark)

    Kogelman, Lisette; Cirera Salicio, Susanna; Zhernakova, Daria V.

    2014-01-01

    interactions. Identification of co-expressed and regulatory genes in RNA extracted from relevant tissues representing lean and obese individuals provides an entry point for the identification of genes and pathways of importance to the development of obesity. The pig, an omnivorous animal, is an excellent model...... in a porcine model. Methods We selected 36 animals for RNA Sequencing from a previously created F2 pig population representing three extreme groups based on their predicted genetic risks for obesity. We applied Weighted Gene Co-expression Network Analysis (WGCNA) to detect clusters of highly co-expressed genes...... in humans and rodents, e.g. CSF1R and MARC2. Conclusions To our knowledge, this is the first study to apply systems biology approaches using porcine adipose tissue RNA-Sequencing data in a genetically characterized porcine model for obesity. We revealed complex networks, pathways, candidate and regulatory...

  18. Gene Expression in Bone

    Science.gov (United States)

    D'Ambrogio, A.

    Skeletal system has two main functions, to provide mechanical integrity for both locomotion and protection and to play an important role in mineral homeostasis. There is extensive evidence showing loss of bone mass during long-term Space-Flights. The loss is due to a break in the equilibrium between the activity of osteoblasts (the cells that forms bone) and the activity of osteoclasts (the cells that resorbs bone). Surprisingly, there is scanty information about the possible altered gene expression occurring in cells that form bone in microgravity.(Just 69 articles result from a "gene expression in microgravity" MedLine query.) Gene-chip or microarray technology allows to screen thousands of genes at the same time: the use of this technology on samples coming from cells exposed to microgravity could provide us with many important informations. For example, the identification of the molecules or structures which are the first sensors of the mechanical stress derived from lack of gravity, could help in understanding which is the first event leading to bone loss due to long-term exposure to microgravity. Consequently, this structure could become a target for a custom-designed drug. It is evident that bone mass loss, observed during long-time stay in Space, represents an accelerated model of what happens in aging osteoporosis. Therefore, the discovery and design of drugs able to interfere with the bone-loss process, could help also in preventing negative physiological processes normally observed on Earth. Considering the aims stated above, my research is designed to:

  19. Correction of gene expression data

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  20. Prediction of the gene expression in normal lung tissue by the gene expression in blood.

    Science.gov (United States)

    Halloran, Justin W; Zhu, Dakai; Qian, David C; Byun, Jinyoung; Gorlova, Olga Y; Amos, Christopher I; Gorlov, Ivan P

    2015-11-17

    Comparative analysis of gene expression in human tissues is important for understanding the molecular mechanisms underlying tissue-specific control of gene expression. It can also open an avenue for using gene expression in blood (which is the most easily accessible human tissue) to predict gene expression in other (less accessible) tissues, which would facilitate the development of novel gene expression based models for assessing disease risk and progression. Until recently, direct comparative analysis across different tissues was not possible due to the scarcity of paired tissue samples from the same individuals. In this study we used paired whole blood/lung gene expression data from the Genotype-Tissue Expression (GTEx) project. We built a generalized linear regression model for each gene using gene expression in lung as the outcome and gene expression in blood, age and gender as predictors. For ~18 % of the genes, gene expression in blood was a significant predictor of gene expression in lung. We found that the number of single nucleotide polymorphisms (SNPs) influencing expression of a given gene in either blood or lung, also known as the number of quantitative trait loci (eQTLs), was positively associated with efficacy of blood-based prediction of that gene's expression in lung. This association was strongest for shared eQTLs: those influencing gene expression in both blood and lung. In conclusion, for a considerable number of human genes, their expression levels in lung can be predicted using observable gene expression in blood. An abundance of shared eQTLs may explain the strong blood/lung correlations in the gene expression.

  1. Proposed method for dimensionality reduction based on framework in gene expression domain.

    Science.gov (United States)

    Macedo, D C; Ishikawa, E C M; Santos, C B; Matos, S N; Borges, H B; Francisco, A C

    2014-12-12

    The excessive use of attributes may affect the search for patterns and extraction of useful knowledge, because they harm the learning performance of algorithms in both speed and success rate. The use of dimensionality reduction methods is therefore an important alternative; however, these methods do not deal with the reduction of attributes in a specific area. This article presents a method based on framework concepts of domain for reducing attributes in a domain. The input method is a set of databases related to a domain, and the main process is the identification of common and variable attributes, plus the reduction of attributes in the original database. The proposed method was applied in the gene expression domain, using databases. The method can be used to analyze the most relevant attributes in a specific domain, granting greater confidence for models created for the application of a data mining task, thus, a previously known method in data mining. Attribute selection was also applied in the three databases for the comparison of the results. Analyses of the results using the criterion of cross-validation revealed that the employment of the methods resulted in the improvement of success rates compared to the databases containing the full range of attributes.

  2. Prediction of essential proteins based on subcellular localization and gene expression correlation.

    Science.gov (United States)

    Fan, Yetian; Tang, Xiwei; Hu, Xiaohua; Wu, Wei; Ping, Qing

    2017-12-01

    Essential proteins are indispensable to the survival and development process of living organisms. To understand the functional mechanisms of essential proteins, which can be applied to the analysis of disease and design of drugs, it is important to identify essential proteins from a set of proteins first. As traditional experimental methods designed to test out essential proteins are usually expensive and laborious, computational methods, which utilize biological and topological features of proteins, have attracted more attention in recent years. Protein-protein interaction networks, together with other biological data, have been explored to improve the performance of essential protein prediction. The proposed method SCP is evaluated on Saccharomyces cerevisiae datasets and compared with five other methods. The results show that our method SCP outperforms the other five methods in terms of accuracy of essential protein prediction. In this paper, we propose a novel algorithm named SCP, which combines the ranking by a modified PageRank algorithm based on subcellular compartments information, with the ranking by Pearson correlation coefficient (PCC) calculated from gene expression data. Experiments show that subcellular localization information is promising in boosting essential protein prediction.

  3. Hessian regularization based symmetric nonnegative matrix factorization for clustering gene expression and microbiome data.

    Science.gov (United States)

    Ma, Yuanyuan; Hu, Xiaohua; He, Tingting; Jiang, Xingpeng

    2016-12-01

    Nonnegative matrix factorization (NMF) has received considerable attention due to its interpretation of observed samples as combinations of different components, and has been successfully used as a clustering method. As an extension of NMF, Symmetric NMF (SNMF) inherits the advantages of NMF. Unlike NMF, however, SNMF takes a nonnegative similarity matrix as an input, and two lower rank nonnegative matrices (H, H T ) are computed as an output to approximate the original similarity matrix. Laplacian regularization has improved the clustering performance of NMF and SNMF. However, Laplacian regularization (LR), as a classic manifold regularization method, suffers some problems because of its weak extrapolating ability. In this paper, we propose a novel variant of SNMF, called Hessian regularization based symmetric nonnegative matrix factorization (HSNMF), for this purpose. In contrast to Laplacian regularization, Hessian regularization fits the data perfectly and extrapolates nicely to unseen data. We conduct extensive experiments on several datasets including text data, gene expression data and HMP (Human Microbiome Project) data. The results show that the proposed method outperforms other methods, which suggests the potential application of HSNMF in biological data clustering. Copyright © 2016. Published by Elsevier Inc.

  4. Gene expression-based biological test for major depressive disorder: an advanced study

    Directory of Open Access Journals (Sweden)

    Watanabe S

    2017-02-01

    Full Text Available Shin-ya Watanabe,1 Shusuke Numata,1 Jun-ichi Iga,2 Makoto Kinoshita,1 Hidehiro Umehara,1 Kazuo Ishii,3 Tetsuro Ohmori1 1Department of Psychiatry, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, 2Department of Neuropsychiatry, Molecules and Function, Ehime University Graduate School of Medicine, Ehime, 3Department of Applied Biological Science, Faculty of Agriculture, Tokyo University of Agriculture and Technology, Tokyo, Japan Purpose: Recently, we could distinguished patients with major depressive disorder (MDD from nonpsychiatric controls with high accuracy using a panel of five gene expression markers (ARHGAP24, HDAC5, PDGFC, PRNP, and SLC6A4 in leukocyte. In the present study, we examined whether this biological test is able to discriminate patients with MDD from those without MDD, including those with schizophrenia and bipolar disorder.Patients and methods: We measured messenger ribonucleic acid expression levels of the aforementioned five genes in peripheral leukocytes in 17 patients with schizophrenia and 36 patients with bipolar disorder using quantitative real-time polymerase chain reaction (PCR, and we combined these expression data with our previous expression data of 25 patients with MDD and 25 controls. Subsequently, a linear discriminant function was developed for use in discriminating between patients with MDD and without MDD.Results: This expression panel was able to segregate patients with MDD from those without MDD with a sensitivity and specificity of 64% and 67.9%, respectively.Conclusion: Further research to identify MDD-specific markers is needed to improve the performance of this biological test. Keywords: depressive disorder, biomarker, gene expression, schizophrenia, bipolar disorder

  5. A tree of life based on ninety-eight expressed genes conserved across diverse eukaryotic species.

    Directory of Open Access Journals (Sweden)

    Pawan Kumar Jayaswal

    Full Text Available Rapid advances in DNA sequencing technologies have resulted in the accumulation of large data sets in the public domain, facilitating comparative studies to provide novel insights into the evolution of life. Phylogenetic studies across the eukaryotic taxa have been reported but on the basis of a limited number of genes. Here we present a genome-wide analysis across different plant, fungal, protist, and animal species, with reference to the 36,002 expressed genes of the rice genome. Our analysis revealed 9831 genes unique to rice and 98 genes conserved across all 49 eukaryotic species analysed. The 98 genes conserved across diverse eukaryotes mostly exhibited binding and catalytic activities and shared common sequence motifs; and hence appeared to have a common origin. The 98 conserved genes belonged to 22 functional gene families including 26S protease, actin, ADP-ribosylation factor, ATP synthase, casein kinase, DEAD-box protein, DnaK, elongation factor 2, glyceraldehyde 3-phosphate, phosphatase 2A, ras-related protein, Ser/Thr protein phosphatase family protein, tubulin, ubiquitin and others. The consensus Bayesian eukaryotic tree of life developed in this study demonstrated widely separated clades of plants, fungi, and animals. Musa acuminata provided an evolutionary link between monocotyledons and dicotyledons, and Salpingoeca rosetta provided an evolutionary link between fungi and animals, which indicating that protozoan species are close relatives of fungi and animals. The divergence times for 1176 species pairs were estimated accurately by integrating fossil information with synonymous substitution rates in the comprehensive set of 98 genes. The present study provides valuable insight into the evolution of eukaryotes.

  6. A green fluorescent protein (GFP)-based plasmid system to study post-transcriptional control of gene expression in vivo.

    Science.gov (United States)

    Urban, Johannes H; Vogel, Jörg

    2009-01-01

    Small non-coding RNAs (sRNAs) are an emerging class of regulators of bacterial gene expression, which mainly modulate the translation of trans-encoded mRNAs. Typically, these molecules are 50-200 nucleotides in size and do not contain expressed open reading frames (ORFs). In Escherichia coli, about 70 members of this group have been identified to date and further estimates assume hundreds of sRNAs per bacterial genome. Regulation of gene expression by sRNAs is predominantly mediated by physical sRNA/target mRNA interactions that are based on short and imperfect complementarity. Although the contribution of sRNAs to overall bacterial gene regulation is now being appreciated, the function of many sRNAs is still unknown and their targets await to be uncovered. We recently developed a modular two-plasmid system, based on the green fluorescent protein (GFP) as non-invasive reporter of gene expression, to rapidly monitor the regulatory potential of sRNA/target mRNA pairs under investigation in vivo. The specialized reporter plasmid series also provides a suitable platform to study the function of cis-encoded riboregulators such as natural riboswitches, thermosensors, or engineered aptamer-based regulatory switches.

  7. A novel PCR-based method for high throughput prokaryotic expression of antimicrobial peptide genes

    Directory of Open Access Journals (Sweden)

    Ke Tao

    2012-03-01

    Full Text Available Abstract Background To facilitate the screening of large quantities of new antimicrobial peptides (AMPs, we describe a cost-effective method for high throughput prokaryotic expression of AMPs. EDDIE, an autoproteolytic mutant of the N-terminal autoprotease, Npro, from classical swine fever virus, was selected as a fusion protein partner. The expression system was used for high-level expression of six antimicrobial peptides with different sizes: Bombinin-like peptide 7, Temporin G, hexapeptide, Combi-1, human Histatin 9, and human Histatin 6. These expressed AMPs were purified and evaluated for antimicrobial activity. Results Two or four primers were used to synthesize each AMP gene in a single step PCR. Each synthetic gene was then cloned into the pET30a/His-EDDIE-GFP vector via an in vivo recombination strategy. Each AMP was then expressed as an Npro fusion protein in Escherichia coli. The expressed fusion proteins existed as inclusion bodies in the cytoplasm and the expression levels of the six AMPs reached up to 40% of the total cell protein content. On in vitro refolding, the fusion AMPs was released from the C-terminal end of the autoprotease by self-cleavage, leaving AMPs with an authentic N terminus. The released fusion partner was easily purified by Ni-NTA chromatography. All recombinant AMPs displayed expected antimicrobial activity against E. coli, Micrococcus luteus and S. cerevisia. Conclusions The method described in this report allows the fast synthesis of genes that are optimized for over-expression in E. coli and for the production of sufficiently large amounts of peptides for functional and structural characterization. The Npro partner system, without the need for chemical or enzymatic removal of the fusion tag, is a low-cost, efficient way of producing AMPs for characterization. The cloning method, combined with bioinformatic analyses from genome and EST sequence data, will also be useful for screening new AMPs. Plasmid pET30a

  8. The Arabidopsis co-expression tool (act): a WWW-based tool and database for microarray-based gene expression analysis

    DEFF Research Database (Denmark)

    Jen, C. H.; Manfield, I. W.; Michalopoulos, D. W.

    2006-01-01

    gene co-expression patterns. To demonstrate the ability of the software to develop testable hypotheses on gene function within a defined biological process we have used the example of cell wall biosynthesis genes. The resource is freely available at http://www.arabidopsis.leeds.ac.uk/ACT/......, and dissection into cliques of co-regulated genes. We illustrate the applications of the software by analysing genes encoding functionally related proteins, as well as pathways involved in plant responses to environmental stimuli. These analyses demonstrate novel biological relationships underlying the observed...

  9. Preprocessing and Quality Control Strategies for Illumina DASL Assay-Based Brain Gene Expression Studies with Semi-Degraded Samples

    Directory of Open Access Journals (Sweden)

    Maggie L Chow

    2012-02-01

    Full Text Available Available statistical preprocessing or quality control analysis tools for gene expression microarray datasets are known to greatly affect downstream data analysis, especially when degraded samples, unique tissue samples or novel expression assays are used. It is therefore important to assess the validity and impact of the assumptions built in to preprocessing schemes for a dataset. We developed and assessed a data preprocessing strategy for use with the Illumina DASL-based gene expression assay with partially degraded postmortem prefrontal cortex samples. The samples were obtained from individuals with autism as part of an investigation of the pathogenic factors contributing to autism.Using statistical analysis methods and metrics such as those associated with multivariate distance matrix regression (MDMR and mean inter-array correlation, we developed a DASL-based assay gene expression preprocessing pipeline to accommodate and detect problems with microarray-based gene expression values obtained with degraded brain samples. Key steps in the pipeline included outlier exclusion, data transformation and normalization, and batch effect and covariate corrections. Our goal was to produce a clean dataset for subsequent downstream differential expression analysis. We ultimately settled on available transformation and normalization algorithms in the R/Bioconductor package lumi based on an assessment of their use in various combinations. A log2-transformed, quantile-normalized, and batch and seizure-corrected procedure was likely the most appropriate for our data. We empirically tested different components of our proposed preprocessing strategy and believe that our results suggest that a preprocessing strategy that effectively identifies outliers, normalizes the data, and corrects for batch effects, like ours can be applied to all studies, even those pursued with degraded samples.

  10. Hexamerin-based regulation of juvenile hormone-dependent gene expression underlies phenotypic plasticity in a social insect.

    Science.gov (United States)

    Zhou, Xuguo; Tarver, Matthew R; Scharf, Michael E

    2007-02-01

    Worker termites of the genus Reticulitermes are temporally-arrested juvenile forms that can terminally differentiate into adultsoldier- or reproductive-caste phenotypes. Soldier-caste differentiation is a developmental transition that is induced by high juvenile hormone (JH) titers. Recently, a status quo hexamerin mechanism was identified, which reduces JH efficacy and maximizes colony fitness via the maintenance of high worker-caste proportions. Our goal in these studies was to investigate more thoroughly the influences of the hexamerins on JH-dependent gene expression in termite workers. Our approach involved RNA interference (RNAi), bioassays and quantification of gene expression. We first investigated the expression of 17 morphogenesis-associated genes in response to RNAi-based hexamerin silencing. Hexamerin silencing resulted in significant downstream impacts on 15 out of the 17 genes, suggesting that these genes are members of a JH-responsive genomic network. Next, we compared gene-expression profiles in workers after RNAi-based hexamerin silencing to that of (i) untreated workers that were held away from the colony; and (ii) workers that were also held away from the colony, but with ectopic JH. Here, although there was no correlation between hexamerin silencing and colony-release effects, we observed a significant correlation between hexamerin silencing and JH-treatment effects. These findings provide further evidence supporting the hypothesis that the hexamerins modulate JH availability, thus limiting the impacts of JH on termite caste polyphenism. Results are discussed in a context relative to outstanding questions on termite developmental biology, particularly on regulatory gene networks that respond to JH-, colony- and environmental-cues.

  11. Expression of Separate Proteins in the Same Plant Leaves and Cells Using Two Independent Virus-Based Gene Vectors

    Directory of Open Access Journals (Sweden)

    Maria R. Mendoza

    2017-11-01

    Full Text Available Plant viral vectors enable the expression of proteins at high levels in a relatively short time. For many purposes (e.g., cell biological interaction studies it may be desirable to express more than one protein in a single cell but that is often not feasible when using a single virus vector. Such a co-expression strategy requires the simultaneous delivery by two compatible and non-competitive viruses that can co-exist to each express a separate protein. Here, we report on the use of two agro-launchable coat-protein gene substitution GFP-expressing virus vector systems based on Tomato bushy stunt virus (TBSV referred to as TG, and Tobacco mosaic virus (TMV annotated as TRBO-G. TG expressed GFP in Nicotiana benthamiana, tomato, lettuce and cowpea, whereas expression from TRBO-G was detected only in the first two species. Upon co-infiltration of the two vectors co-expression was monitored by: molecular detection of the two slightly differently sized GFPs, suppressor-complementation assays, and using TG in combination with TRBO-RFP. All the results revealed that in N. benthamiana and tomato the TBSV and TMV vectors accumulated and expressed proteins in the same plants, the same leaves, and in the same cells. Therefore, co-expression by these two vectors provides a platform for fast and high level expression of proteins to study their cell biology or other properties.

  12. Identification of factors contributing to variability in a blood-based gene expression test.

    Directory of Open Access Journals (Sweden)

    Michael R Elashoff

    Full Text Available BACKGROUND: Corus CAD is a clinically validated test based on age, sex, and expression levels of 23 genes in whole blood that provides a score (1-40 points proportional to the likelihood of obstructive coronary disease. Clinical laboratory process variability was examined using whole blood controls across a 24 month period: Intra-batch variability was assessed using sample replicates; inter-batch variability examined as a function of laboratory personnel, equipment, and reagent lots. METHODS/RESULTS: To assess intra-batch variability, five batches of 132 whole blood controls were processed; inter-batch variability was estimated using 895 whole blood control samples. ANOVA was used to examine inter-batch variability at 4 process steps: RNA extraction, cDNA synthesis, cDNA addition to assay plates, and qRT-PCR. Operator, machine, and reagent lots were assessed as variables for all stages if possible, for a total of 11 variables. Intra- and inter-batch variations were estimated to be 0.092 and 0.059 Cp units respectively (SD; total laboratory variation was estimated to be 0.11 Cp units (SD. In a regression model including all 11 laboratory variables, assay plate lot and cDNA kit lot contributed the most to variability (p = 0.045; 0.009 respectively. Overall, reagent lots for RNA extraction, cDNA synthesis, and qRT-PCR contributed the most to inter-batch variance (52.3%, followed by operators and machines (18.9% and 9.2% respectively, leaving 19.6% of the variance unexplained. CONCLUSION: Intra-batch variability inherent to the PCR process contributed the most to the overall variability in the study while reagent lot showed the largest contribution to inter-batch variability.

  13. Surface EMG-based Sketching Recognition Using Two Analysis Windows and Gene Expression Programming

    Science.gov (United States)

    Yang, Zhongliang; Chen, Yumiao

    2016-01-01

    Sketching is one of the most important processes in the conceptual stage of design. Previous studies have relied largely on the analyses of sketching process and outcomes; whereas surface electromyographic (sEMG) signals associated with sketching have received little attention. In this study, we propose a method in which 11 basic one-stroke sketching shapes are identified from the sEMG signals generated by the forearm and upper arm muscles from 4 subjects. Time domain features such as integrated electromyography, root mean square and mean absolute value were extracted with analysis windows of two length conditions for pattern recognition. After reducing data dimensionality using principal component analysis, the shapes were classified using Gene Expression Programming (GEP). The performance of the GEP classifier was compared to the Back Propagation neural network (BPNN) and the Elman neural network (ENN). Feature extraction with the short analysis window (250 ms with a 250 ms increment) improved the recognition rate by around 6.4% averagely compared with the long analysis window (2500 ms with a 2500 ms increment). The average recognition rate for the eleven basic one-stroke sketching patterns achieved by the GEP classifier was 96.26% in the training set and 95.62% in the test set, which was superior to the performance of the BPNN and ENN classifiers. The results show that the GEP classifier is able to perform well with either length of the analysis window. Thus, the proposed GEP model show promise for recognizing sketching based on sEMG signals. PMID:27790083

  14. Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

    Directory of Open Access Journals (Sweden)

    Enrico Glaab

    Full Text Available Microarray data analysis has been shown to provide an effective tool for studying cancer and genetic diseases. Although classical machine learning techniques have successfully been applied to find informative genes and to predict class labels for new samples, common restrictions of microarray analysis such as small sample sizes, a large attribute space and high noise levels still limit its scientific and clinical applications. Increasing the interpretability of prediction models while retaining a high accuracy would help to exploit the information content in microarray data more effectively. For this purpose, we evaluate our rule-based evolutionary machine learning systems, BioHEL and GAssist, on three public microarray cancer datasets, obtaining simple rule-based models for sample classification. A comparison with other benchmark microarray sample classifiers based on three diverse feature selection algorithms suggests that these evolutionary learning techniques can compete with state-of-the-art methods like support vector machines. The obtained models reach accuracies above 90% in two-level external cross-validation, with the added value of facilitating interpretation by using only combinations of simple if-then-else rules. As a further benefit, a literature mining analysis reveals that prioritizations of informative genes extracted from BioHEL's classification rule sets can outperform gene rankings obtained from a conventional ensemble feature selection in terms of the pointwise mutual information between relevant disease terms and the standardized names of top-ranked genes.

  15. Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

    Science.gov (United States)

    Glaab, Enrico; Bacardit, Jaume; Garibaldi, Jonathan M; Krasnogor, Natalio

    2012-01-01

    Microarray data analysis has been shown to provide an effective tool for studying cancer and genetic diseases. Although classical machine learning techniques have successfully been applied to find informative genes and to predict class labels for new samples, common restrictions of microarray analysis such as small sample sizes, a large attribute space and high noise levels still limit its scientific and clinical applications. Increasing the interpretability of prediction models while retaining a high accuracy would help to exploit the information content in microarray data more effectively. For this purpose, we evaluate our rule-based evolutionary machine learning systems, BioHEL and GAssist, on three public microarray cancer datasets, obtaining simple rule-based models for sample classification. A comparison with other benchmark microarray sample classifiers based on three diverse feature selection algorithms suggests that these evolutionary learning techniques can compete with state-of-the-art methods like support vector machines. The obtained models reach accuracies above 90% in two-level external cross-validation, with the added value of facilitating interpretation by using only combinations of simple if-then-else rules. As a further benefit, a literature mining analysis reveals that prioritizations of informative genes extracted from BioHEL's classification rule sets can outperform gene rankings obtained from a conventional ensemble feature selection in terms of the pointwise mutual information between relevant disease terms and the standardized names of top-ranked genes.

  16. Microarray-Based Analysis of Differential Gene Expression between Infective and Noninfective Larvae of Strongyloides stercoralis

    Science.gov (United States)

    Ramanathan, Roshan; Varma, Sudhir; Ribeiro, José M. C.; Myers, Timothy G.; Nolan, Thomas J.; Abraham, David; Lok, James B.; Nutman, Thomas B.

    2011-01-01

    Background Differences between noninfective first-stage (L1) and infective third-stage (L3i) larvae of parasitic nematode Strongyloides stercoralis at the molecular level are relatively uncharacterized. DNA microarrays were developed and utilized for this purpose. Methods and Findings Oligonucleotide hybridization probes for the array were designed to bind 3,571 putative mRNA transcripts predicted by analysis of 11,335 expressed sequence tags (ESTs) obtained as part of the Nematode EST project. RNA obtained from S. stercoralis L3i and L1 was co-hybridized to each array after labeling the individual samples with different fluorescent tags. Bioinformatic predictions of gene function were developed using a novel cDNA Annotation System software. We identified 935 differentially expressed genes (469 L3i-biased; 466 L1-biased) having two-fold expression differences or greater and microarray signals with a p valuemicroarray tool for the examination of S. stercoralis biology has been developed and provides new and valuable insights regarding differences between infective and noninfective S. stercoralis larvae. Potential therapeutic and vaccine targets were identified for further study. PMID:21572524

  17. Evolution of gene expression after gene amplification.

    Science.gov (United States)

    Garcia, Nelson; Zhang, Wei; Wu, Yongrui; Messing, Joachim

    2015-04-24

    We took a rather unique approach to investigate the conservation of gene expression of prolamin storage protein genes across two different subfamilies of the Poaceae. We took advantage of oat plants carrying single maize chromosomes in different cultivars, called oat-maize addition (OMA) lines, which permitted us to determine whether regulation of gene expression was conserved between the two species. We found that γ-zeins are expressed in OMA7.06, which carries maize chromosome 7 even in the absence of the trans-acting maize prolamin-box-binding factor (PBF), which regulates their expression. This is likely because oat PBF can substitute for the function of maize PBF as shown in our transient expression data, using a γ-zein promoter fused to green fluorescent protein (GFP). Despite this conservation, the younger, recently amplified prolamin genes in maize, absent in oat, are not expressed in the corresponding OMAs. However, maize can express the oldest prolamin gene, the wheat high-molecular weight glutenin Dx5 gene, even when maize Pbf is knocked down (through PbfRNAi), and/or another maize transcription factor, Opaque-2 (O2) is knocked out (in maize o2 mutant). Therefore, older genes are conserved in their regulation, whereas younger ones diverged during evolution and eventually acquired a new repertoire of suitable transcriptional activators. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  18. Profiling Gene Expression in Germinating Brassica Roots.

    Science.gov (United States)

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

    2014-01-01

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

  19. Regulation of eucaryotic gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Brent, R.; Ptashne, M.S

    1989-05-23

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

  20. A New Method for the Evaluation of Vaccine Safety Based on Comprehensive Gene Expression Analysis

    Directory of Open Access Journals (Sweden)

    Haruka Momose

    2010-01-01

    Full Text Available For the past 50 years, quality control and safety tests have been used to evaluate vaccine safety. However, conventional animal safety tests need to be improved in several aspects. For example, the number of test animals used needs to be reduced and the test period shortened. It is, therefore, necessary to develop a new vaccine evaluation system. In this review, we show that gene expression patterns are well correlated to biological responses in vaccinated rats. Our findings and methods using experimental biology and genome science provide an important means of assessment for vaccine toxicity.

  1. Model-based deconvolution of cell cycle time-series data reveals gene expression details at high resolution.

    Directory of Open Access Journals (Sweden)

    Dan Siegal-Gaskins

    2009-08-01

    Full Text Available In both prokaryotic and eukaryotic cells, gene expression is regulated across the cell cycle to ensure "just-in-time" assembly of select cellular structures and molecular machines. However, present in all time-series gene expression measurements is variability that arises from both systematic error in the cell synchrony process and variance in the timing of cell division at the level of the single cell. Thus, gene or protein expression data collected from a population of synchronized cells is an inaccurate measure of what occurs in the average single-cell across a cell cycle. Here, we present a general computational method to extract "single-cell"-like information from population-level time-series expression data. This method removes the effects of 1 variance in growth rate and 2 variance in the physiological and developmental state of the cell. Moreover, this method represents an advance in the deconvolution of molecular expression data in its flexibility, minimal assumptions, and the use of a cross-validation analysis to determine the appropriate level of regularization. Applying our deconvolution algorithm to cell cycle gene expression data from the dimorphic bacterium Caulobacter crescentus, we recovered critical features of cell cycle regulation in essential genes, including ctrA and ftsZ, that were obscured in population-based measurements. In doing so, we highlight the problem with using population data alone to decipher cellular regulatory mechanisms and demonstrate how our deconvolution algorithm can be applied to produce a more realistic picture of temporal regulation in a cell.

  2. Gene Expression Levels as Predictive Markers of Outcome in Pancreatic Cancer after Gemcitabine-Based Adjuvant Chemotherapy

    Directory of Open Access Journals (Sweden)

    Hayato Fujita

    2010-10-01

    Full Text Available BACKGROUND AND AIMS: The standard palliative chemotherapy for pancreatic ductal adenocarcinoma (PDAC is gemcitabine-based chemotherapy; however, PDAC still presents a major therapeutic challenge. The aims of this study were to investigate the expression pattern of genes involved in gemcitabine sensitivity in resected PDAC tissues and to determine correlations of gene expression with treatment outcome. MATERIALS AND METHODS: We obtained formalin-fixed paraffin-embedded (FFPE tissue samples from 70 patients with PDAC. Of the 70 patients, 40 received gemcitabine-based adjuvant chemotherapy (AC. We measured hENT1, dCK, CDA, RRM1, and RRM2 messenger RNA (mRNA levels by quantitative real-time reverse transcription-polymerase chain reaction and determined the combined score (GEM score, based on the expression levels of hENT1, dCK, RRM1, and RRM2, to investigate the association with survival time. By determining the expression levels of these genes in endoscopic ultrasound-guided fine needle aspiration (EUS-FNA cytologic specimens, we investigated the feasibility of individualized chemotherapy. RESULTS: High dCK (P = .0067, low RRM2 (P = .003, and high GEM score (P = .0003 groups had a significantly longer disease-free survival in the gemcitabine-treated group. A low GEM score (<2 was an independent predictive marker for poor outcome to gemcitabine-based AC as shown by multivariate analysis (P = .0081. Altered expression levels of these genes were distinguishable in microdissected neoplastic cells from EUS-FNA cytologic specimens. CONCLUSIONS: Quantitative analyses of hENT1, dCK, RRM1, and RRM2 mRNA levels using FFPE tissue samples and microdissected neoplastic cells from EUS-FNA cytologic specimens may be useful in predicting the gemcitabine sensitivity of patients with PDAC.

  3. Digital gene expression analysis based on integrated de novo transcriptome assembly of sweet potato [Ipomoea batatas (L.) Lam].

    Science.gov (United States)

    Tao, Xiang; Gu, Ying-Hong; Wang, Hai-Yan; Zheng, Wen; Li, Xiao; Zhao, Chuan-Wu; Zhang, Yi-Zheng

    2012-01-01

    Sweet potato (Ipomoea batatas L. [Lam.]) ranks among the top six most important food crops in the world. It is widely grown throughout the world with high and stable yield, strong adaptability, rich nutrient content, and multiple uses. However, little is known about the molecular biology of this important non-model organism due to lack of genomic resources. Hence, studies based on high-throughput sequencing technologies are needed to get a comprehensive and integrated genomic resource and better understanding of gene expression patterns in different tissues and at various developmental stages. Illumina paired-end (PE) RNA-Sequencing was performed, and generated 48.7 million of 75 bp PE reads. These reads were de novo assembled into 128,052 transcripts (≥ 100 bp), which correspond to 41.1 million base pairs, by using a combined assembly strategy. Transcripts were annotated by Blast2GO and 51,763 transcripts got BLASTX hits, in which 39,677 transcripts have GO terms and 14,117 have ECs that are associated with 147 KEGG pathways. Furthermore, transcriptome differences of seven tissues were analyzed by using Illumina digital gene expression (DGE) tag profiling and numerous differentially and specifically expressed transcripts were identified. Moreover, the expression characteristics of genes involved in viral genomes, starch metabolism and potential stress tolerance and insect resistance were also identified. The combined de novo transcriptome assembly strategy can be applied to other organisms whose reference genomes are not available. The data provided here represent the most comprehensive and integrated genomic resources for cloning and identifying genes of interest in sweet potato. Characterization of sweet potato transcriptome provides an effective tool for better understanding the molecular mechanisms of cellular processes including development of leaves and storage roots, tissue-specific gene expression, potential biotic and abiotic stress response in sweet

  4. Digital Gene Expression Analysis Based on Integrated De Novo Transcriptome Assembly of Sweet Potato [Ipomoea batatas (L.) Lam.

    Science.gov (United States)

    Wang, Hai-Yan; Zheng, Wen; Li, Xiao; Zhao, Chuan-Wu; Zhang, Yi-Zheng

    2012-01-01

    Background Sweet potato (Ipomoea batatas L. [Lam.]) ranks among the top six most important food crops in the world. It is widely grown throughout the world with high and stable yield, strong adaptability, rich nutrient content, and multiple uses. However, little is known about the molecular biology of this important non-model organism due to lack of genomic resources. Hence, studies based on high-throughput sequencing technologies are needed to get a comprehensive and integrated genomic resource and better understanding of gene expression patterns in different tissues and at various developmental stages. Methodology/Principal Findings Illumina paired-end (PE) RNA-Sequencing was performed, and generated 48.7 million of 75 bp PE reads. These reads were de novo assembled into 128,052 transcripts (≥100 bp), which correspond to 41.1 million base pairs, by using a combined assembly strategy. Transcripts were annotated by Blast2GO and 51,763 transcripts got BLASTX hits, in which 39,677 transcripts have GO terms and 14,117 have ECs that are associated with 147 KEGG pathways. Furthermore, transcriptome differences of seven tissues were analyzed by using Illumina digital gene expression (DGE) tag profiling and numerous differentially and specifically expressed transcripts were identified. Moreover, the expression characteristics of genes involved in viral genomes, starch metabolism and potential stress tolerance and insect resistance were also identified. Conclusions/Significance The combined de novo transcriptome assembly strategy can be applied to other organisms whose reference genomes are not available. The data provided here represent the most comprehensive and integrated genomic resources for cloning and identifying genes of interest in sweet potato. Characterization of sweet potato transcriptome provides an effective tool for better understanding the molecular mechanisms of cellular processes including development of leaves and storage roots, tissue-specific gene

  5. Digital gene expression analysis based on integrated de novo transcriptome assembly of sweet potato [Ipomoea batatas (L. Lam].

    Directory of Open Access Journals (Sweden)

    Xiang Tao

    Full Text Available BACKGROUND: Sweet potato (Ipomoea batatas L. [Lam.] ranks among the top six most important food crops in the world. It is widely grown throughout the world with high and stable yield, strong adaptability, rich nutrient content, and multiple uses. However, little is known about the molecular biology of this important non-model organism due to lack of genomic resources. Hence, studies based on high-throughput sequencing technologies are needed to get a comprehensive and integrated genomic resource and better understanding of gene expression patterns in different tissues and at various developmental stages. METHODOLOGY/PRINCIPAL FINDINGS: Illumina paired-end (PE RNA-Sequencing was performed, and generated 48.7 million of 75 bp PE reads. These reads were de novo assembled into 128,052 transcripts (≥ 100 bp, which correspond to 41.1 million base pairs, by using a combined assembly strategy. Transcripts were annotated by Blast2GO and 51,763 transcripts got BLASTX hits, in which 39,677 transcripts have GO terms and 14,117 have ECs that are associated with 147 KEGG pathways. Furthermore, transcriptome differences of seven tissues were analyzed by using Illumina digital gene expression (DGE tag profiling and numerous differentially and specifically expressed transcripts were identified. Moreover, the expression characteristics of genes involved in viral genomes, starch metabolism and potential stress tolerance and insect resistance were also identified. CONCLUSIONS/SIGNIFICANCE: The combined de novo transcriptome assembly strategy can be applied to other organisms whose reference genomes are not available. The data provided here represent the most comprehensive and integrated genomic resources for cloning and identifying genes of interest in sweet potato. Characterization of sweet potato transcriptome provides an effective tool for better understanding the molecular mechanisms of cellular processes including development of leaves and storage roots

  6. Genome-based genetic tool development for Bacillus methanolicus: theta- and rolling circle-replicating plasmids for inducible gene expression and application to methanol-based cadaverine production

    Directory of Open Access Journals (Sweden)

    Marta Irla

    2016-09-01

    Full Text Available Bacillus methanolicus is a thermophilic methylotroph able to overproduce amino acids from methanol, a substrate not used for human or animal nutrition. Based on our previous RNA-seq analysis a mannitol inducible promoter and a putative mannitol activator gene mtlR were identified. The mannitol inducible promoter was applied for controlled gene expression using fluorescent reporter proteins and a flow cytometry analysis, and improved by changing the -35 promoter region and by co-expression of the mtlR regulator gene. For independent complementary gene expression control, the heterologous xylose-inducible system from B. megaterium was employed and a two-plasmid gene expression system was developed. Four different replicons for expression vectors were compared with respect to their copy number and stability. As an application example, methanol-based production of cadaverine was shown to be improved from 11.3 g/L to 17.5 g/L when a heterologous lysine decarboxylase gene cadA was expressed from a theta-replicating rather than a rolling-circle replicating vector. The current work on inducible promoter systems and compatible theta- or rolling circle-replicating vectors is an important extension of the poorly developed B. methanolicus genetic toolbox, valuable for genetic engineering and further exploration of this bacterium.

  7. MGEx-Udb: a mammalian uterus database for expression-based cataloguing of genes across conditions, including endometriosis and cervical cancer.

    Science.gov (United States)

    Bajpai, Akhilesh K; Davuluri, Sravanthi; Chandrashekar, Darshan S; Ilakya, Selvarajan; Dinakaran, Mahalakshmi; Acharya, Kshitish K

    2012-01-01

    Gene expression profiling of uterus tissue has been performed in various contexts, but a significant amount of the data remains underutilized as it is not covered by the existing general resources. We curated 2254 datasets from 325 uterus related mass scale gene expression studies on human, mouse, rat, cow and pig species. We then computationally derived a 'reliability score' for each gene's expression status (transcribed/dormant), for each possible combination of conditions and locations, based on the extent of agreement or disagreement across datasets. The data and derived information has been compiled into the Mammalian Gene Expression Uterus database (MGEx-Udb, http://resource.ibab.ac.in/MGEx-Udb/). The database can be queried with gene names/IDs, sub-tissue locations, as well as various conditions such as the cervical cancer, endometrial cycles and disorders, and experimental treatments. Accordingly, the output would be a) transcribed and dormant genes listed for the queried condition/location, or b) expression profile of the gene of interest in various uterine conditions. The results also include the reliability score for the expression status of each gene. MGEx-Udb also provides information related to Gene Ontology annotations, protein-protein interactions, transcripts, promoters, and expression status by other sequencing techniques, and facilitates various other types of analysis of the individual genes or co-expressed gene clusters. In brief, MGEx-Udb enables easy cataloguing of co-expressed genes and also facilitates bio-marker discovery for various uterine conditions.

  8. Seqinspector: position-based navigation through the ChIP-seq data landscape to identify gene expression regulators.

    Science.gov (United States)

    Piechota, Marcin; Korostynski, Michal; Ficek, Joanna; Tomski, Andrzej; Przewlocki, Ryszard

    2016-02-12

    The regulation of gene expression in eukaryotic cells is a complex process that involves epigenetic modifications and the interaction of DNA with multiple transcription factors. This process can be studied with unprecedented sensitivity using a combination of chromatin immunoprecipitation and next-generation DNA sequencing (ChIP-seq). Available ChIP-seq data can be further utilized to interpret new gene expression profiling experiments. Here, we describe seqinspector, a tool that accepts any set of genomic coordinates from ChIP-seq or RNA-seq studies to identify shared transcriptional regulators. The presented web resource includes a large collection of publicly available ChIP-seq and RNA-seq experiments (>1300 tracks) performed on transcription factors, histone modifications, RNA polymerases, enhancers and insulators in humans and mice. Over-representation is calculated based on the coverage computed directly from indexed files storing ChIP-seq data (bigwig). Therefore, seqinspector is not limited to pre-computed sets of gene promoters. The tool can be used to identify common gene expression regulators for sets of co-expressed transcripts (including miRNAs, lncRNAs or any novel unannotated RNAs) or for sets of ChIP-seq peaks to identify putative protein-protein interactions or transcriptional co-factors. The tool is available at http://seqinspector.cremag.org.

  9. Differential Gene Expression and Aging

    Directory of Open Access Journals (Sweden)

    Laurent Seroude

    2002-01-01

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

  10. A Link-Based Cluster Ensemble Approach For Improved Gene Expression Data Analysis

    Directory of Open Access Journals (Sweden)

    P.Balaji

    2015-01-01

    Full Text Available Abstract It is difficult from possibilities to select a most suitable effective way of clustering algorithm and its dataset for a defined set of gene expression data because we have a huge number of ways and huge number of gene expressions. At present many researchers are preferring to use hierarchical clustering in different forms this is no more totally optimal. Cluster ensemble research can solve this type of problem by automatically merging multiple data partitions from a wide range of different clusterings of any dimensions to improve both the quality and robustness of the clustering result. But we have many existing ensemble approaches using an association matrix to condense sample-cluster and co-occurrence statistics and relations within the ensemble are encapsulated only at raw level while the existing among clusters are totally discriminated. Finding these missing associations can greatly expand the capability of those ensemble methodologies for microarray data clustering. We propose general K-means cluster ensemble approach for the clustering of general categorical data into required number of partitions.

  11. Artificial Neural Networks and Gene Expression Programing based age estimation using facial features

    Directory of Open Access Journals (Sweden)

    Baddrud Z. Laskar

    2015-10-01

    Full Text Available This work is about estimating human age automatically through analysis of facial images. It has got a lot of real-world applications. Due to prompt advances in the fields of machine vision, facial image processing, and computer graphics, automatic age estimation via faces in computer is one of the dominant topics these days. This is due to widespread real-world applications, in areas of biometrics, security, surveillance, control, forensic art, entertainment, online customer management and support, along with cosmetology. As it is difficult to estimate the exact age, this system is to estimate a certain range of ages. Four sets of classifications have been used to differentiate a person’s data into one of the different age groups. The uniqueness about this study is the usage of two technologies i.e., Artificial Neural Networks (ANN and Gene Expression Programing (GEP to estimate the age and then compare the results. New methodologies like Gene Expression Programing (GEP have been explored here and significant results were found. The dataset has been developed to provide more efficient results by superior preprocessing methods. This proposed approach has been developed, tested and trained using both the methods. A public data set was used to test the system, FG-NET. The quality of the proposed system for age estimation using facial features is shown by broad experiments on the available database of FG-NET.

  12. Fine Needle Aspiration Biopsies for Gene Expression Ratio-based Diagnostic and Prognostic Tests in Malignant Pleural Mesothelioma

    Science.gov (United States)

    De Rienzo, Assunta; Dong, Lingsheng; Yeap, Beow Y.; Jensen, Roderick V.; Richards, William G.; Gordon, Gavin J.; Sugarbaker, David J.; Bueno, Raphael

    2010-01-01

    Purpose Malignant pleural mesothelioma (MPM) is an aggressive disease associated with median survival between 9 and 12 months. The correct diagnosis of MPM is sometimes challenging and usually requires solid tissue biopsies rather than fine needle aspiration biopsies (FNA). We postulated that the accuracy of FNA-based diagnosis might be improved by the addition of molecular tests using a gene expression ratio-based algorithm and that prognostic tests could be similarly performed. Experimental Design Two MPM and two lung cancer cell lines were used to establish the minimal RNA amount required for ratio tests. Based on these results, 276 ex-vivo FNA biopsies from 63 MPM patients, and 250 ex-vivo FNA samples from 92 lung cancer patients were analyzed using previously described diagnostic and prognostic tests based on gene expression ratios. Results We found that the sensitivity of the diagnostic test for MPM was 100% (95% CI: 95–100%), and the specificity in primary lung adenocarcinoma was 90% (95% CI: 81–95%). The FNA-based prognostic classification was concordant among 76% (95% CI: 65–87%) of patients with the risk assignment in a subset of the matched surgical specimens previously analyzed by the prognostic test. Conclusions Sufficient RNA can be extracted from most FNA biopsies to perform gene expression molecular tests. In particular, we show that the gene expression ratio algorithms performed well when applied to diagnosis and prognosis in MPM. This study provides support for the development of additional RNA molecular tests that may enhance the utility of FNA in the management of other solid cancers. PMID:21088255

  13. Transient expression of heterologous model gene in plants using Potato virusX-based vector

    Czech Academy of Sciences Publication Activity Database

    Čeřovská, Noemi; Pečenková, Tamara; Moravec, Tomáš; Velemínský, Jiří

    2004-01-01

    Roč. 79, č. 2 (2004), s. 147-152 ISSN 0167-6857 R&D Projects: GA ČR GA310/00/0381 Institutional research plan: CEZ:AV0Z5038910 Keywords : plant virus * based vector * transient expression Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 1.028, year: 2004

  14. First study on gene expression of cement proteins and potential adhesion-related genes of a membranous-based barnacle as revealed from Next-Generation Sequencing technology

    KAUST Repository

    Lin, Hsiu Chin

    2013-12-12

    This is the first study applying Next-Generation Sequencing (NGS) technology to survey the kinds, expression location, and pattern of adhesion-related genes in a membranous-based barnacle. A total of 77,528,326 and 59,244,468 raw sequence reads of total RNA were generated from the prosoma and the basis of Tetraclita japonica formosana, respectively. In addition, 55,441 and 67,774 genes were further assembled and analyzed. The combined sequence data from both body parts generates a total of 79,833 genes of which 47.7% were shared. Homologues of barnacle cement proteins - CP-19K, -52K, and -100K - were found and all were dominantly expressed at the basis where the cement gland complex is located. This is the main area where transcripts of cement proteins and other potential adhesion-related genes were detected. The absence of another common barnacle cement protein, CP-20K, in the adult transcriptome suggested a possible life-stage restricted gene function and/or a different mechanism in adhesion between membranous-based and calcareous-based barnacles. © 2013 © 2013 Taylor & Francis.

  15. Multi-step dimensionality reduction and semi-supervised graph-based tumor classification using gene expression data.

    Science.gov (United States)

    Gui, Jie; Wang, Shu-Lin; Lei, Ying-Ke

    2010-11-01

    Both supervised methods and unsupervised methods have been widely used to solve the tumor classification problem based on gene expression profiles. This paper introduces a semi-supervised graph-based method for tumor classification. Feature extraction plays a key role in tumor classification based on gene expression profiles, and can greatly improve the performance of a classifier. In this paper we propose a novel multi-step dimensionality reduction method for extracting tumor-related features. First the Wilcoxon rank-sum test is used for gene selection. Then gene ranking and discrete cosine transform are combined with principal component analysis for feature extraction. Finally, the performance is evaluated by semi-supervised learning algorithms. To show the validity of the proposed method, we apply it to classify four tumor datasets involving various human normal and tumor tissue samples. The experimental results show that the proposed method is efficient and feasible. Compared with other methods, our method can achieve relatively higher prediction accuracy. Particularly, it is found that semi-supervised method is superior to support vector machines in classification performance. The proposed approach can effectively improve the performance of tumor classification based on gene expression profiles. This work is a meaningful attempt to explore and apply multi-step dimensionality reduction and semi-supervised learning methods in the field of tumor classification. Considering the high classification accuracy, there should be much room for the application of multi-step dimensionality reduction and semi-supervised learning methods to perform tumor classification. Copyright © 2010 Elsevier B.V. All rights reserved.

  16. Modulation of radiation-induced base excision repair pathway gene expression by melatonin

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    Saeed Rezapoor

    2017-01-01

    Full Text Available Objective: Approximately 70% of all cancer patients receive radiotherapy. Although radiotherapy is effective in killing cancer cells, it has adverse effects on normal cells as well. Melatonin (MLT as a potent antioxidant and anti-inflammatory agent has been proposed to stimulate DNA repair capacity. We investigated the capability of MLT in the modification of radiation-induced DNA damage in rat peripheral blood cells. Materials and Methods: In this experimental study, male rats (n = 162 were divided into 27 groups (n = 6 in each group including: irradiation only, vehicle only, vehicle with irradiation, 100 mg/kg MLT alone, 100 mg/kg MLT plus irradiation in 3 different time points, and control. Subsequently, they were irradiated with a single whole-body X-ray radiation dose of 2 and 8 Gy at a dose rate of 200 MU/min. Rats were given an intraperitoneal injection of MLT or the same volume of vehicle alone 1 h prior to irradiation. Blood samples were also taken 8, 24, and 48 h postirradiation, in order to measure the 8-oxoguanine glycosylase1 (Ogg1, Apex1, and Xrcc1 expression using quantitative real-time-polymerase chain reaction. Results: Exposing to the ionizing radiation resulted in downregulation of Ogg1, Apex1, and Xrcc1 gene expression. The most obvious suppression was observed in 8 h after exposure. Pretreatments with MLT were able to upregulate these genes when compared to the irradiation-only and vehicle plus irradiation groups (P < 0.05 in all time points. Conclusion: Our results suggested that MLT in mentioned dose may result in modulation of Ogg1, Apex1, and Xrcc1 gene expression in peripheral blood cells to reduce X-ray irradiation-induced DNA damage. Therefore, administration of MLT may increase the normal tissue tolerance to radiation through enhancing the cell DNA repair capacity. We believed that MLT could play a radiation toxicity reduction role in patients who have undergone radiation treatment as a part of cancer radiotherapy.

  17. A yeast recombination-based cloning system to produce chimeric HIV-1 viruses and express HIV-1 genes.

    Science.gov (United States)

    Moore, Dawn M; Arts, Eric J; Gao, Yong; Marozsan, Andre J

    2005-01-01

    Differential phenotypes or properties of HIV-1 gene products in primary virus isolates are difficult to assess due to interference by the high degree of sequence variation across the entire genome. Thus, chimeric viruses provide a powerful tool to study the function of single gene products or genetic elements in the context of a neutral viral genomic backbone. In this chapter, we describe how to produce HIV-1 chimeric viruses utilizing a yeast-based homologous recombination cloning technique to insert env sequences first into a yeast cloning vector and then into the common pNL4-3 virus backbone. This technique is not limited to the env gene, but can be used to build chimeric viruses with any HIV-1 gene or genetic element. This cloning technique involves the use of a shuttle vector that can replicate in yeast and bacterial cells. Along with acting as a shuttle vector for subsequent subcloning into pNL4-3, this construct pRec/env can also be used to express to the env gene product, gp120/gp41, on the surface of mammalian cells. The chimeric viruses produced by this cloning method are capable of undergoing multiple rounds of replication and are therefore very useful to study drug sensitivity, coreceptor usage, and viral fitness as influenced by a single gene or gene fragment of a primary HIV-1 isolate from any group M subtype.

  18. Temperature based daily incoming solar radiation modeling based on gene expression programming, neuro-fuzzy and neural network computing techniques.

    Science.gov (United States)

    Landeras, G.; López, J. J.; Kisi, O.; Shiri, J.

    2012-04-01

    The correct observation/estimation of surface incoming solar radiation (RS) is very important for many agricultural, meteorological and hydrological related applications. While most weather stations are provided with sensors for air temperature detection, the presence of sensors necessary for the detection of solar radiation is not so habitual and the data quality provided by them is sometimes poor. In these cases it is necessary to estimate this variable. Temperature based modeling procedures are reported in this study for estimating daily incoming solar radiation by using Gene Expression Programming (GEP) for the first time, and other artificial intelligence models such as Artificial Neural Networks (ANNs), and Adaptive Neuro-Fuzzy Inference System (ANFIS). Traditional temperature based solar radiation equations were also included in this study and compared with artificial intelligence based approaches. Root mean square error (RMSE), mean absolute error (MAE) RMSE-based skill score (SSRMSE), MAE-based skill score (SSMAE) and r2 criterion of Nash and Sutcliffe criteria were used to assess the models' performances. An ANN (a four-input multilayer perceptron with ten neurons in the hidden layer) presented the best performance among the studied models (2.93 MJ m-2 d-1 of RMSE). A four-input ANFIS model revealed as an interesting alternative to ANNs (3.14 MJ m-2 d-1 of RMSE). Very limited number of studies has been done on estimation of solar radiation based on ANFIS, and the present one demonstrated the ability of ANFIS to model solar radiation based on temperatures and extraterrestrial radiation. By the way this study demonstrated, for the first time, the ability of GEP models to model solar radiation based on daily atmospheric variables. Despite the accuracy of GEP models was slightly lower than the ANFIS and ANN models the genetic programming models (i.e., GEP) are superior to other artificial intelligence models in giving a simple explicit equation for the

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

    Directory of Open Access Journals (Sweden)

    Ming-gang Du

    2009-01-01

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

  20. Comparative Analysis of RNAi-Based Methods to Down-Regulate Expression of Two Genes Expressed at Different Levels in Myzus persicae.

    Science.gov (United States)

    Mulot, Michaël; Boissinot, Sylvaine; Monsion, Baptiste; Rastegar, Maryam; Clavijo, Gabriel; Halter, David; Bochet, Nicole; Erdinger, Monique; Brault, Véronique

    2016-11-19

    With the increasing availability of aphid genomic data, it is necessary to develop robust functional validation methods to evaluate the role of specific aphid genes. This work represents the first study in which five different techniques, all based on RNA interference and on oral acquisition of double-stranded RNA (dsRNA), were developed to silence two genes, ALY and Eph , potentially involved in polerovirus transmission by aphids. Efficient silencing of only Eph transcripts, which are less abundant than those of ALY , could be achieved by feeding aphids on transgenic Arabidopsis thaliana expressing an RNA hairpin targeting Eph , on Nicotiana benthamiana infected with a Tobacco rattle virus (TRV)-Eph recombinant virus, or on in vitro-synthesized Eph -targeting dsRNA. These experiments showed that the silencing efficiency may differ greatly between genes and that aphid gut cells seem to be preferentially affected by the silencing mechanism after oral acquisition of dsRNA. In addition, the use of plants infected with recombinant TRV proved to be a promising technique to silence aphid genes as it does not require plant transformation. This work highlights the need to pursue development of innovative strategies to reproducibly achieve reduction of expression of aphid genes.

  1. De Novo Sequencing-Based Transcriptome and Digital Gene Expression Analysis Reveals Insecticide Resistance-Relevant Genes in Propylaea japonica (Thunberg) (Coleoptea: Coccinellidae)

    Science.gov (United States)

    Jin, Feng-Liang; Qiu, Bao-Li; Wu, Jian-Hui; Ren, Shun-Xiang

    2014-01-01

    The ladybird Propylaea japonica (Thunberg) is one of most important natural enemies of aphids in China. This species is threatened by the extensive use of insecticides but genomics-based information on the molecular mechanisms underlying insecticide resistance is limited. Hence, we analyzed the transcriptome and expression profile data of P. japonica in order to gain a deeper understanding of insecticide resistance in ladybirds. We performed de novo assembly of a transcriptome using Illumina's Solexa sequencing technology and short reads. A total of 27,243,552 reads were generated. These were assembled into 81,458 contigs and 33,647 unigenes (6,862 clusters and 26,785 singletons). Of the unigenes, 23,965 (71.22%) have putative homologues in the non-redundant (nr) protein database from NCBI, using BLASTX, with a cut-off E-value of 10−5. We examined COG, GO and KEGG annotations to better understand the functions of these unigenes. Digital gene expression (DGE) libraries showed differences in gene expression profiles between two insecticide resistant strains. When compared with an insecticide susceptible profile, a total of 4,692 genes were significantly up- or down- regulated in a moderately resistant strain. Among these genes, 125 putative insecticide resistance genes were identified. To confirm the DGE results, 16 selected genes were validated using quantitative real time PCR (qRT-PCR). This study is the first to report genetic information on P. japonica and has greatly enriched the sequence data for ladybirds. The large number of gene sequences produced from the transcriptome and DGE sequencing will greatly improve our understanding of this important insect, at the molecular level, and could contribute to the in-depth research into insecticide resistance mechanisms. PMID:24959827

  2. De novo sequencing-based transcriptome and digital gene expression analysis reveals insecticide resistance-relevant genes in Propylaea japonica (Thunberg (Coleoptea: Coccinellidae.

    Directory of Open Access Journals (Sweden)

    Liang-De Tang

    Full Text Available The ladybird Propylaea japonica (Thunberg is one of most important natural enemies of aphids in China. This species is threatened by the extensive use of insecticides but genomics-based information on the molecular mechanisms underlying insecticide resistance is limited. Hence, we analyzed the transcriptome and expression profile data of P. japonica in order to gain a deeper understanding of insecticide resistance in ladybirds. We performed de novo assembly of a transcriptome using Illumina's Solexa sequencing technology and short reads. A total of 27,243,552 reads were generated. These were assembled into 81,458 contigs and 33,647 unigenes (6,862 clusters and 26,785 singletons. Of the unigenes, 23,965 (71.22% have putative homologues in the non-redundant (nr protein database from NCBI, using BLASTX, with a cut-off E-value of 10(-5. We examined COG, GO and KEGG annotations to better understand the functions of these unigenes. Digital gene expression (DGE libraries showed differences in gene expression profiles between two insecticide resistant strains. When compared with an insecticide susceptible profile, a total of 4,692 genes were significantly up- or down- regulated in a moderately resistant strain. Among these genes, 125 putative insecticide resistance genes were identified. To confirm the DGE results, 16 selected genes were validated using quantitative real time PCR (qRT-PCR. This study is the first to report genetic information on P. japonica and has greatly enriched the sequence data for ladybirds. The large number of gene sequences produced from the transcriptome and DGE sequencing will greatly improve our understanding of this important insect, at the molecular level, and could contribute to the in-depth research into insecticide resistance mechanisms.

  3. Quantitative multiplex quantum dot in-situ hybridisation based gene expression profiling in tissue microarrays identifies prognostic genes in acute myeloid leukaemia

    Energy Technology Data Exchange (ETDEWEB)

    Tholouli, Eleni [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); MacDermott, Sarah [The Medical School, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Hoyland, Judith [School of Biomedicine, Faculty of Medical and Human Sciences, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Yin, John Liu [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); Byers, Richard, E-mail: richard.byers@cmft.nhs.uk [School of Cancer and Enabling Sciences, Faculty of Medical and Human Sciences, The University of Manchester, Stopford Building, Oxford Road, M13 9PT Manchester (United Kingdom)

    2012-08-24

    Highlights: Black-Right-Pointing-Pointer Development of a quantitative high throughput in situ expression profiling method. Black-Right-Pointing-Pointer Application to a tissue microarray of 242 AML bone marrow samples. Black-Right-Pointing-Pointer Identification of HOXA4, HOXA9, Meis1 and DNMT3A as prognostic markers in AML. -- Abstract: Measurement and validation of microarray gene signatures in routine clinical samples is problematic and a rate limiting step in translational research. In order to facilitate measurement of microarray identified gene signatures in routine clinical tissue a novel method combining quantum dot based oligonucleotide in situ hybridisation (QD-ISH) and post-hybridisation spectral image analysis was used for multiplex in-situ transcript detection in archival bone marrow trephine samples from patients with acute myeloid leukaemia (AML). Tissue-microarrays were prepared into which white cell pellets were spiked as a standard. Tissue microarrays were made using routinely processed bone marrow trephines from 242 patients with AML. QD-ISH was performed for six candidate prognostic genes using triplex QD-ISH for DNMT1, DNMT3A, DNMT3B, and for HOXA4, HOXA9, Meis1. Scrambled oligonucleotides were used to correct for background staining followed by normalisation of expression against the expression values for the white cell pellet standard. Survival analysis demonstrated that low expression of HOXA4 was associated with poorer overall survival (p = 0.009), whilst high expression of HOXA9 (p < 0.0001), Meis1 (p = 0.005) and DNMT3A (p = 0.04) were associated with early treatment failure. These results demonstrate application of a standardised, quantitative multiplex QD-ISH method for identification of prognostic markers in formalin-fixed paraffin-embedded clinical samples, facilitating measurement of gene expression signatures in routine clinical samples.

  4. Microarray-based analysis of the differential expression of melanin synthesis genes in dark and light-muzzle Korean cattle.

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    Sang Hwan Kim

    Full Text Available The coat color of mammals is determined by the melanogenesis pathway, which is responsible for maintaining the balance between black-brown eumelanin and yellow-reddish pheomelanin. It is also believed that the color of the bovine muzzle is regulated in a similar manner; however, the molecular mechanism underlying pigment deposition in the dark-muzzle has yet to be elucidated. The aim of the present study was to identify melanogenesis-associated genes that are differentially expressed in the dark vs. light muzzle of native Korean cows. Using microarray clustering and real-time polymerase chain reaction techniques, we observed that the expression of genes involved in the mitogen-activated protein kinase (MAPK and Wnt signaling pathways is distinctively regulated in the dark and light muzzle tissues. Differential expression of tyrosinase was also noticed, although the difference was not as distinct as those of MAPK and Wnt. We hypothesize that emphasis on the MAPK pathway in the dark-muzzle induces eumelanin synthesis through the activation of cAMP response element-binding protein and tyrosinase, while activation of Wnt signaling counteracts this process and raises the amount of pheomelanin in the light-muzzle. We also found 2 novel genes (GenBank No. NM-001076026 and XM-588439 with increase expression in the black nose, which may provide additional information about the mechanism of nose pigmentation. Regarding the increasing interest in the genetic diversity of cattle stocks, genes we identified for differential expression in the dark vs. light muzzle may serve as novel markers for genetic diversity among cows based on the muzzle color phenotype.

  5. Polycistronic gene expression in Aspergillus niger.

    Science.gov (United States)

    Schuetze, Tabea; Meyer, Vera

    2017-09-25

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

  6. Development of new USER-based cloning vectors for multiple genes expression in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Kildegaard, Kanchana Rueksomtawin; Jensen, Niels Bjerg; Maury, Jerome

    2013-01-01

    of shuttle vectors for convenience of use for high-throughput cloning and selectable marker recycling. The new USER-based cloning vectors consist of a unique USER site and a CRE-loxP-mediated marker recycling system. The USER site allows insertion of genes of interest along with a bidirectional promoter...... of choice into the vector backbone with time- and cost-effective. The selectable marker cassette is flanked by loxP recognition sites for the CreA recombinase to allow reutilization of the same selectable marker. Furthermore, our USER vector set provides a choice of different selectable markers both...

  7. Computational analysis of HIV-1 resistance based on gene expression profiles and the virus-host interaction network.

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    Tao Huang

    Full Text Available A very small proportion of people remain negative for HIV infection after repeated HIV-1 viral exposure, which is called HIV-1 resistance. Understanding the mechanism of HIV-1 resistance is important for the development of HIV-1 vaccines and Acquired Immune Deficiency Syndrome (AIDS therapies. In this study, we analyzed the gene expression profiles of CD4+ T cells from HIV-1-resistant individuals and HIV-susceptible individuals. One hundred eighty-five discriminative HIV-1 resistance genes were identified using the Minimum Redundancy-Maximum Relevance (mRMR and Incremental Feature Selection (IFS methods. The virus protein target enrichment analysis of the 185 HIV-1 resistance genes suggested that the HIV-1 protein nef might play an important role in HIV-1 infection. Moreover, we identified 29 infection information exchanger genes from the 185 HIV-1 resistance genes based on a virus-host interaction network analysis. The infection information exchanger genes are located on the shortest paths between virus-targeted proteins and are important for the coordination of virus infection. These proteins may be useful targets for AIDS prevention or therapy, as intervention in these pathways could disrupt communication with virus-targeted proteins and HIV-1 infection.

  8. Development of tobacco ringspot virus-based vectors for foreign gene expression and virus-induced gene silencing in a variety of plants.

    Science.gov (United States)

    Zhao, Fumei; Lim, Seungmo; Igori, Davaajargal; Yoo, Ran Hee; Kwon, Suk-Yoon; Moon, Jae Sun

    2016-05-01

    We report here the development of tobacco ringspot virus (TRSV)-based vectors for the transient expression of foreign genes and for the analysis of endogenous gene function in plants using virus-induced gene silencing. The jellyfish green fluorescent protein (GFP) gene was inserted between the TRSV movement protein (MP) and coat protein (CP) regions, resulting in high in-frame expression of the RNA2-encoded viral polyprotein. GFP was released from the polyprotein via an N-terminal homologous MP-CP cleavage site and a C-terminal foot-and-mouth disease virus (FMDV) 2 A catalytic peptide in Nicotiana benthamiana. The VIGS target gene was introduced in the sense and antisense orientations into a SnaBI site, which was created by mutating the sequence following the CP stop codon. VIGS of phytoene desaturase (PDS) in N. benthamiana, Arabidopsis ecotype Col-0, cucurbits and legumes led to obvious photo-bleaching phenotypes. A significant reduction in PDS mRNA levels in silenced plants was confirmed by semi-quantitative RT-PCR. Copyright © 2016 Elsevier Inc. All rights reserved.

  9. A Cross-Species Gene Expression Marker-Based Genetic Map and QTL Analysis in Bambara Groundnut

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    Hui Hui Chai

    2017-02-01

    Full Text Available Bambara groundnut (Vigna subterranea (L. Verdc. is an underutilised legume crop, which has long been recognised as a protein-rich and drought-tolerant crop, used extensively in Sub-Saharan Africa. The aim of the study was to identify quantitative trait loci (QTL involved in agronomic and drought-related traits using an expression marker-based genetic map based on major crop resources developed in soybean. The gene expression markers (GEMs were generated at the (unmasked probe-pair level after cross-hybridisation of bambara groundnut leaf RNA to the Affymetrix Soybean Genome GeneChip. A total of 753 markers grouped at an LOD (Logarithm of odds of three, with 527 markers mapped into linkage groups. From this initial map, a spaced expression marker-based genetic map consisting of 13 linkage groups containing 218 GEMs, spanning 982.7 cM (centimorgan of the bambara groundnut genome, was developed. Of the QTL detected, 46% were detected in both control and drought treatment populations, suggesting that they are the result of intrinsic trait differences between the parental lines used to construct the cross, with 31% detected in only one of the conditions. The present GEM map in bambara groundnut provides one technically feasible route for the translation of information and resources from major and model plant species to underutilised and resource-poor crops.

  10. A Cross-Species Gene Expression Marker-Based Genetic Map and QTL Analysis in Bambara Groundnut.

    Science.gov (United States)

    Chai, Hui Hui; Ho, Wai Kuan; Graham, Neil; May, Sean; Massawe, Festo; Mayes, Sean

    2017-02-22

    Bambara groundnut ( Vigna subterranea (L.) Verdc.) is an underutilised legume crop, which has long been recognised as a protein-rich and drought-tolerant crop, used extensively in Sub-Saharan Africa. The aim of the study was to identify quantitative trait loci (QTL) involved in agronomic and drought-related traits using an expression marker-based genetic map based on major crop resources developed in soybean. The gene expression markers (GEMs) were generated at the (unmasked) probe-pair level after cross-hybridisation of bambara groundnut leaf RNA to the Affymetrix Soybean Genome GeneChip. A total of 753 markers grouped at an LOD (Logarithm of odds) of three, with 527 markers mapped into linkage groups. From this initial map, a spaced expression marker-based genetic map consisting of 13 linkage groups containing 218 GEMs, spanning 982.7 cM (centimorgan) of the bambara groundnut genome, was developed. Of the QTL detected, 46% were detected in both control and drought treatment populations, suggesting that they are the result of intrinsic trait differences between the parental lines used to construct the cross, with 31% detected in only one of the conditions. The present GEM map in bambara groundnut provides one technically feasible route for the translation of information and resources from major and model plant species to underutilised and resource-poor crops.

  11. Lung cancer gene expression database analysis incorporating prior knowledge with support vector machine-based classification method

    Directory of Open Access Journals (Sweden)

    Huang Desheng

    2009-07-01

    Full Text Available Abstract Background A reliable and precise classification is essential for successful diagnosis and treatment of cancer. Gene expression microarrays have provided the high-throughput platform to discover genomic biomarkers for cancer diagnosis and prognosis. Rational use of the available bioinformation can not only effectively remove or suppress noise in gene chips, but also avoid one-sided results of separate experiment. However, only some studies have been aware of the importance of prior information in cancer classification. Methods Together with the application of support vector machine as the discriminant approach, we proposed one modified method that incorporated prior knowledge into cancer classification based on gene expression data to improve accuracy. A public well-known dataset, Malignant pleural mesothelioma and lung adenocarcinoma gene expression database, was used in this study. Prior knowledge is viewed here as a means of directing the classifier using known lung adenocarcinoma related genes. The procedures were performed by software R 2.80. Results The modified method performed better after incorporating prior knowledge. Accuracy of the modified method improved from 98.86% to 100% in training set and from 98.51% to 99.06% in test set. The standard deviations of the modified method decreased from 0.26% to 0 in training set and from 3.04% to 2.10% in test set. Conclusion The method that incorporates prior knowledge into discriminant analysis could effectively improve the capacity and reduce the impact of noise. This idea may have good future not only in practice but also in methodology.

  12. Gene set analysis for longitudinal gene expression data

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    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

  13. A novel approach to select differential pathways associated with hypertrophic cardiomyopathy based on gene co‑expression analysis.

    Science.gov (United States)

    Chen, Xiao-Min; Feng, Ming-Jun; Shen, Cai-Jie; He, Bin; Du, Xian-Feng; Yu, Yi-Bo; Liu, Jing; Chu, Hui-Min

    2017-07-01

    The present study was designed to develop a novel method for identifying significant pathways associated with human hypertrophic cardiomyopathy (HCM), based on gene co‑expression analysis. The microarray dataset associated with HCM (E‑GEOD‑36961) was obtained from the European Molecular Biology Laboratory‑European Bioinformatics Institute database. Informative pathways were selected based on the Reactome pathway database and screening treatments. An empirical Bayes method was utilized to construct co‑expression networks for informative pathways, and a weight value was assigned to each pathway. Differential pathways were extracted based on weight threshold, which was calculated using a random model. In order to assess whether the co‑expression method was feasible, it was compared with traditional pathway enrichment analysis of differentially expressed genes, which were identified using the significance analysis of microarrays package. A total of 1,074 informative pathways were screened out for subsequent investigations and their weight values were also obtained. According to the threshold of weight value of 0.01057, 447 differential pathways, including folding of actin by chaperonin containing T‑complex protein 1 (CCT)/T‑complex protein 1 ring complex (TRiC), purine ribonucleoside monophosphate biosynthesis and ubiquinol biosynthesis, were obtained. Compared with traditional pathway enrichment analysis, the number of pathways obtained from the co‑expression approach was increased. The results of the present study demonstrated that this method may be useful to predict marker pathways for HCM. The pathways of folding of actin by CCT/TRiC and purine ribonucleoside monophosphate biosynthesis may provide evidence of the underlying molecular mechanisms of HCM, and offer novel therapeutic directions for HCM.

  14. A Seasonal Time-Series Model Based on Gene Expression Programming for Predicting Financial Distress

    Directory of Open Access Journals (Sweden)

    Ching-Hsue Cheng

    2018-01-01

    Full Text Available The issue of financial distress prediction plays an important and challenging research topic in the financial field. Currently, there have been many methods for predicting firm bankruptcy and financial crisis, including the artificial intelligence and the traditional statistical methods, and the past studies have shown that the prediction result of the artificial intelligence method is better than the traditional statistical method. Financial statements are quarterly reports; hence, the financial crisis of companies is seasonal time-series data, and the attribute data affecting the financial distress of companies is nonlinear and nonstationary time-series data with fluctuations. Therefore, this study employed the nonlinear attribute selection method to build a nonlinear financial distress prediction model: that is, this paper proposed a novel seasonal time-series gene expression programming model for predicting the financial distress of companies. The proposed model has several advantages including the following: (i the proposed model is different from the previous models lacking the concept of time series; (ii the proposed integrated attribute selection method can find the core attributes and reduce high dimensional data; and (iii the proposed model can generate the rules and mathematical formulas of financial distress for providing references to the investors and decision makers. The result shows that the proposed method is better than the listing classifiers under three criteria; hence, the proposed model has competitive advantages in predicting the financial distress of companies.

  15. A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Nookaew, Intawat; Papini, Marta; Pornputtapong, Natapol

    2012-01-01

    of genetic variation on the estimation of gene expression level using three different aligners for read-mapping (Gsnap, Stampy and TopHat) on S288c genome, the capabilities of five different statistical methods to detect differential gene expression (baySeq, Cuffdiff, DESeq, edgeR and NOISeq) and we explored...... gene expression identification derived from the different statistical methods, as well as their integrated analysis results based on gene ontology annotation are in good agreement. Overall, our study provides a useful and comprehensive comparison between the two platforms (RNA-seq and microrrays...

  16. Improving sensitivity of linear regression-based cell type-specific differential expression deconvolution with per-gene vs. global significance threshold.

    Science.gov (United States)

    Glass, Edmund R; Dozmorov, Mikhail G

    2016-10-06

    The goal of many human disease-oriented studies is to detect molecular mechanisms different between healthy controls and patients. Yet, commonly used gene expression measurements from blood samples suffer from variability of cell composition. This variability hinders the detection of differentially expressed genes and is often ignored. Combined with cell counts, heterogeneous gene expression may provide deeper insights into the gene expression differences on the cell type-specific level. Published computational methods use linear regression to estimate cell type-specific differential expression, and a global cutoff to judge significance, such as False Discovery Rate (FDR). Yet, they do not consider many artifacts hidden in high-dimensional gene expression data that may negatively affect linear regression. In this paper we quantify the parameter space affecting the performance of linear regression (sensitivity of cell type-specific differential expression detection) on a per-gene basis. We evaluated the effect of sample sizes, cell type-specific proportion variability, and mean squared error on sensitivity of cell type-specific differential expression detection using linear regression. Each parameter affected variability of cell type-specific expression estimates and, subsequently, the sensitivity of differential expression detection. We provide the R package, LRCDE, which performs linear regression-based cell type-specific differential expression (deconvolution) detection on a gene-by-gene basis. Accounting for variability around cell type-specific gene expression estimates, it computes per-gene t-statistics of differential detection, p-values, t-statistic-based sensitivity, group-specific mean squared error, and several gene-specific diagnostic metrics. The sensitivity of linear regression-based cell type-specific differential expression detection differed for each gene as a function of mean squared error, per group sample sizes, and variability of the proportions

  17. Sphingoid Base Metabolism in Yeast: Mapping Gene Expression Patterns Into Qualitative Metabolite Time Course Predictions

    Directory of Open Access Journals (Sweden)

    Tomas Radivoyevitch

    2006-04-01

    Full Text Available Can qualitative metabolite time course predictions be inferred from measured mRNA expression patterns? Speaking against this possibility is the large number of ‘decoupling’ control points that lie between these variables, i.e. translation, protein degradation, enzyme inhibition and enzyme activation. Speaking for it is the notion that these control points might be coordinately regulated such that action exerted on the mRNA level is informative of action exerted on the protein and metabolite levels. A simple kinetic model of sphingoid base metabolism in yeast is postulated. When the enzyme activities in this model are modulated proportional to mRNA expression levels measured in heat shocked yeast, the model yields a transient rise and fall in sphingoid bases followed by a permanent rise in ceramide. This finding is in qualitative agreement with experiments and is thus consistent with the aforementioned coordinated control system hypothesis.

  18. Prediction of drug efficacy for cancer treatment based on comparative analysis of chemosensitivity and gene expression data

    DEFF Research Database (Denmark)

    Wan, Peng; Li, Qiyuan; Larsen, Jens Erik Pontoppidan

    2012-01-01

    , eight potential topoisomerase II inhibitors were identified using a structural similarity search. Finally, a set of genes with expression profiles that were significantly correlated with anti-cancer drug activity was identified. Our study demonstrates that the combined data sets, which provide...... comprehensive information on drug activity and gene expression profiles of tumor cell lines studied, are useful for identifying potential new active compounds....

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

    Directory of Open Access Journals (Sweden)

    Sun Hee Ahn

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

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

    Science.gov (United States)

    Ahn, Sun Hee; Tsalik, Ephraim L; Cyr, Derek D; Zhang, Yurong; van Velkinburgh, Jennifer C; Langley, Raymond J; Glickman, Seth W; Cairns, Charles B; Zaas, Aimee K; Rivers, Emanuel P; Otero, Ronny M; Veldman, Tim; Kingsmore, Stephen F; Lucas, Joseph; Woods, Christopher W; Ginsburg, Geoffrey S; Fowler, Vance G

    2013-01-01

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

  1. 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.

  2. DNA microarray-based experimental strategy for trustworthy expression profiling of the hippocampal genes by astaxanthin supplementation in adult mouse.

    Science.gov (United States)

    Yook, Jang Soo; Shibato, Junko; Rakwal, Randeep; Soya, Hideaki

    2016-03-01

    Naturally occurring astaxantin (ASX) is one of the noticeable carotenoid and dietary supplement, which has strong antioxidant and anti-inflammatory properties, and neuroprotective effects in the brain through crossing the blood-brain barrier. Specially, we are interested in the role of ASX as a brain food. Although ASX has been suggested to have potential benefit to the brain function, the underlying molecular mechanisms and events mediating such effect remain unknown. Here we examined molecular factors in the hippocampus of adult mouse fed ASX diets (0.1% and 0.5% doses) using DNA microarray (Agilent 4 × 44 K whole mouse genome chip) analysis. In this study, we described in detail our experimental workflow and protocol, and validated quality controls with the housekeeping gene expression (Gapdh and Beta-actin) on the dye-swap based approach to advocate our microarray data, which have been uploaded to Gene Expression Omnibus (accession number GSE62197) as a gene resource for the scientific community. This data will also form an important basis for further detailed experiments and bioinformatics analysis with an aim to unravel the potential molecular pathways or mechanisms underlying the positive effects of ASX supplementation on the brain, in particular the hippocampus.

  3. DNA microarray-based experimental strategy for trustworthy expression profiling of the hippocampal genes by astaxanthin supplementation in adult mouse

    Directory of Open Access Journals (Sweden)

    Jang Soo Yook

    2016-03-01

    Full Text Available Naturally occurring astaxantin (ASX is one of the noticeable carotenoid and dietary supplement, which has strong antioxidant and anti-inflammatory properties, and neuroprotective effects in the brain through crossing the blood–brain barrier. Specially, we are interested in the role of ASX as a brain food. Although ASX has been suggested to have potential benefit to the brain function, the underlying molecular mechanisms and events mediating such effect remain unknown. Here we examined molecular factors in the hippocampus of adult mouse fed ASX diets (0.1% and 0.5% doses using DNA microarray (Agilent 4 × 44 K whole mouse genome chip analysis. In this study, we described in detail our experimental workflow and protocol, and validated quality controls with the housekeeping gene expression (Gapdh and Beta-actin on the dye-swap based approach to advocate our microarray data, which have been uploaded to Gene Expression Omnibus (accession number GSE62197 as a gene resource for the scientific community. This data will also form an important basis for further detailed experiments and bioinformatics analysis with an aim to unravel the potential molecular pathways or mechanisms underlying the positive effects of ASX supplementation on the brain, in particular the hippocampus.

  4. Predicting Recurrence and Progression of Noninvasive Papillary Bladder Cancer at Initial Presentation Based on Quantitative Gene Expression Profiles

    DEFF Research Database (Denmark)

    Birkhahn, M.; Mitra, A.P.; Williams, Johan

    2010-01-01

    % specificity. Since this is a small retrospective study using medium-throughput profiling, larger confirmatory studies are needed. Conclusions: Gene expression profiling across relevant cancer pathways appears to be a promising approach for Ta bladder tumor outcome prediction at initial diagnosis......Background: Currently, tumor grade is the best predictor of outcome at first presentation of noninvasive papillary (Ta) bladder cancer. However, reliable predictors of Ta tumor recurrence and progression for individual patients, which could optimize treatment and follow-up schedules based...... on specific tumor biology, are yet to be identified. Objective: To identify genes predictive for recurrence and progression in Ta bladder cancer at first presentation using a quantitative, pathway-specific approach. Design, setting, and participants: Retrospective study of patients with Ta G2/3 bladder tumors...

  5. Remote control of gene expression.

    Science.gov (United States)

    Long, Xiaochun; Miano, Joseph M

    2007-06-01

    The elucidation of a growing number of species' genomes heralds an unprecedented opportunity to ascertain functional attributes of non-coding sequences. In particular, cis regulatory modules (CRMs) controlling gene expression constitute a rich treasure trove of data to be defined and experimentally validated. Such information will provide insight into cell lineage determination and differentiation and the genetic basis of heritable diseases as well as the development of novel tools for restricting the inactivation of genes to specific cell types or conditions. Historically, the study of CRMs and their individual transcription factor binding sites has been limited to proximal regions around gene loci. Two important by-products of the genomics revolution, artificial chromosome vectors and comparative genomics, have fueled efforts to define an increasing number of CRMs acting remotely to control gene expression. Such regulation from a distance has challenged our perspectives of gene expression control and perhaps the very definition of a gene. This review summarizes current approaches to characterize remote control of gene expression in transgenic mice and inherent limitations for accurately interpreting the essential nature of CRM activity.

  6. 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.

  7. Inhibitory effect of live-attenuated Listeria monocytogenes-based vaccines expressing MIA gene on malignant melanoma.

    Science.gov (United States)

    Qian, Yue; Zhang, Na; Jiang, Ping; Chen, Siyuan; Chu, Shujuan; Hamze, Firas; Wu, Yan; Luo, Qin; Feng, Aiping

    2012-08-01

    Listeria monocytogenes (LM), a Gram-positive facultative intracellular bacterium, can be used as an effective exogenous antigen expression vector in tumor-target therapy. But for successful clinical application, it is necessary to construct attenuated LM stain that is safe yet retains the potency of LM based on the full virulent pathogen. In this study, attenuated LM and recombinants of LM expressing melanoma inhibitory activity (MIA) were constructed successfully. The median lethal dose (LD(50)) and invasion efficiency of attenuated LM strains were detected. The recombinants were utilized for immunotherapy of animal model of B16F10 melanoma. The level of MIA mRNA expression in tumor tissue was detected by using real-time polymerase chain reaction (PCR) with specific sequence, meanwhile the anti-tumor immune response was assayed by flow cytometric analysis and enzyme-linked immunosorbent spot (ELISPOT) assay. The results showed the toxicity and invasiveness of attenuated LM were decreased as compared with LM, and attenuated LM expressing MIA, especially the double-genes attenuated LM recombinant, could significantly induce anti-tumor immune response and inhibit tumor growth. This study implicates attenuated LM may be a safer and more effective vector for immunotherapy of melanoma.

  8. Microarray-based gene expression analysis of strong seed dormancy in rice cv. N22 and less dormant mutant derivatives.

    Science.gov (United States)

    Wu, Tao; Yang, Chunyan; Ding, Baoxu; Feng, Zhiming; Wang, Qian; He, Jun; Tong, Jianhua; Xiao, Langtao; Jiang, Ling; Wan, Jianmin

    2016-02-01

    Seed dormancy in rice is an important trait related to the pre-harvest sprouting resistance. In order to understand the molecular mechanisms of seed dormancy, gene expression was investigated by transcriptome analysis using seeds of the strongly dormant cultivar N22 and its less dormant mutants Q4359 and Q4646 at 24 days after heading (DAH). Microarray data revealed more differentially expressed genes in Q4359 than in Q4646 compared to N22. Most genes differing between Q4646 and N22 also differed between Q4359 and N22. GO analysis of genes differentially expressed in both Q4359 and Q4646 revealed that some genes such as those for starch biosynthesis were repressed, whereas metabolic genes such as those for carbohydrate metabolism were enhanced in Q4359 and Q4646 seeds relative to N22. Expression of some genes involved in cell redox homeostasis and chromatin remodeling differed significantly only between Q4359 and N22. The results suggested a close correlation between cell redox homeostasis, chromatin remodeling and seed dormancy. In addition, some genes involved in ABA signaling were down-regulated, and several genes involved in GA biosynthesis and signaling were up-regulated. These observations suggest that reduced seed dormancy in Q4359 was regulated by ABA-GA antagonism. A few differentially expressed genes were located in the regions containing qSdn-1 and qSdn-5 suggesting that they could be candidate genes underlying seed dormancy. Our work provides useful leads to further determine the underling mechanisms of seed dormancy and for cloning seed dormancy genes from N22. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  9. CRISPR/Cas9-based genome editing for simultaneous interference with gene expression and protein stability

    DEFF Research Database (Denmark)

    Martinez, Virginia; Lauritsen, Ida; Hobel, Tonja

    2017-01-01

    Interference with genes is the foundation of reverse genetics and is key to manipulation of living cells for biomedical and biotechnological applications. However, classical genetic knockout and transcriptional knockdown technologies have different drawbacks and offer no control over existing pro...

  10. A Study on Effect of Electroacupuncture on Gene Expression in Hypothalamus of Rats with Stress-Induced Prehypertension Based on Gene Chip Technology

    Directory of Open Access Journals (Sweden)

    Xiaojia Xie

    2015-01-01

    Full Text Available Objective. To explore the effect of electroacupuncture (EA on gene expression in the hypothalamus of rats with stress-induced prehypertension and try to reveal its biological mechanism with gene chip technology. Methods. The stress-induced hypertensive rat model was prepared by combining electric foot-shocks with generated noise. Molding cycle lasted for 14 days and EA intervention was applied on model + EA group during model preparation. Rat Gene 2.0 Array technology was used for the determination of gene expression profiles and the screened key genes were verified by real-time fluorescence quantitative PCR method. Results. Compared with the blank group, 234 genes were upregulated and 73 were downregulated in the model group. Compared with the model group, 110 genes were upregulated and 273 genes were downregulated in model + EA group. The PCR results of the key genes including HSPB1, P2RX4, PPP1R14A, and TH are consistent with that of gene chip test. Conclusion. EA could significantly lower blood pressure of stress-induced prehypertension rats and affect its gene expression profile in hypothalamus. Genes and their signal transduction pathway that related to the contraction of vascular smooth muscle, concentration of Ca2+, and excitability of sympathetic nerve may be involved in EA’s antihypertensive mechanism.

  11. Mining Temporal Protein Complex Based on the Dynamic PIN Weighted with Connected Affinity and Gene Co-Expression.

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    Xianjun Shen

    Full Text Available The identification of temporal protein complexes would make great contribution to our knowledge of the dynamic organization characteristics in protein interaction networks (PINs. Recent studies have focused on integrating gene expression data into static PIN to construct dynamic PIN which reveals the dynamic evolutionary procedure of protein interactions, but they fail in practice for recognizing the active time points of proteins with low or high expression levels. We construct a Time-Evolving PIN (TEPIN with a novel method called Deviation Degree, which is designed to identify the active time points of proteins based on the deviation degree of their own expression values. Owing to the differences between protein interactions, moreover, we weight TEPIN with connected affinity and gene co-expression to quantify the degree of these interactions. To validate the efficiencies of our methods, ClusterONE, CAMSE and MCL algorithms are applied on the TEPIN, DPIN (a dynamic PIN constructed with state-of-the-art three-sigma method and SPIN (the original static PIN to detect temporal protein complexes. Each algorithm on our TEPIN outperforms that on other networks in terms of match degree, sensitivity, specificity, F-measure and function enrichment etc. In conclusion, our Deviation Degree method successfully eliminates the disadvantages which exist in the previous state-of-the-art dynamic PIN construction methods. Moreover, the biological nature of protein interactions can be well described in our weighted network. Weighted TEPIN is a useful approach for detecting temporal protein complexes and revealing the dynamic protein assembly process for cellular organization.

  12. A Modified ABCDE Model of Flowering in Orchids Based on Gene Expression Profiling Studies of the Moth Orchid Phalaenopsis aphrodite

    Science.gov (United States)

    Lee, Ann-Ying; Chen, Chun-Yi; Chang, Yao-Chien Alex; Chao, Ya-Ting; Shih, Ming-Che

    2013-01-01

    Previously we developed genomic resources for orchids, including transcriptomic analyses using next-generation sequencing techniques and construction of a web-based orchid genomic database. Here, we report a modified molecular model of flower development in the Orchidaceae based on functional analysis of gene expression profiles in Phalaenopsis aphrodite (a moth orchid) that revealed novel roles for the transcription factors involved in floral organ pattern formation. Phalaenopsis orchid floral organ-specific genes were identified by microarray analysis. Several critical transcription factors including AP3, PI, AP1 and AGL6, displayed distinct spatial distribution patterns. Phylogenetic analysis of orchid MADS box genes was conducted to infer the evolutionary relationship among floral organ-specific genes. The results suggest that gene duplication MADS box genes in orchid may have resulted in their gaining novel functions during evolution. Based on these analyses, a modified model of orchid flowering was proposed. Comparison of the expression profiles of flowers of a peloric mutant and wild-type Phalaenopsis orchid further identified genes associated with lip morphology and peloric effects. Large scale investigation of gene expression profiles revealed that homeotic genes from the ABCDE model of flower development classes A and B in the Phalaenopsis orchid have novel functions due to evolutionary diversification, and display differential expression patterns. PMID:24265826

  13. A new essential protein discovery method based on the integration of protein-protein interaction and gene expression data

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    Li Min

    2012-03-01

    Full Text Available Abstract Background Identification of essential proteins is always a challenging task since it requires experimental approaches that are time-consuming and laborious. With the advances in high throughput technologies, a large number of protein-protein interactions are available, which have produced unprecedented opportunities for detecting proteins' essentialities from the network level. There have been a series of computational approaches proposed for predicting essential proteins based on network topologies. However, the network topology-based centrality measures are very sensitive to the robustness of network. Therefore, a new robust essential protein discovery method would be of great value. Results In this paper, we propose a new centrality measure, named PeC, based on the integration of protein-protein interaction and gene expression data. The performance of PeC is validated based on the protein-protein interaction network of Saccharomyces cerevisiae. The experimental results show that the predicted precision of PeC clearly exceeds that of the other fifteen previously proposed centrality measures: Degree Centrality (DC, Betweenness Centrality (BC, Closeness Centrality (CC, Subgraph Centrality (SC, Eigenvector Centrality (EC, Information Centrality (IC, Bottle Neck (BN, Density of Maximum Neighborhood Component (DMNC, Local Average Connectivity-based method (LAC, Sum of ECC (SoECC, Range-Limited Centrality (RL, L-index (LI, Leader Rank (LR, Normalized α-Centrality (NC, and Moduland-Centrality (MC. Especially, the improvement of PeC over the classic centrality measures (BC, CC, SC, EC, and BN is more than 50% when predicting no more than 500 proteins. Conclusions We demonstrate that the integration of protein-protein interaction network and gene expression data can help improve the precision of predicting essential proteins. The new centrality measure, PeC, is an effective essential protein discovery method.

  14. Transgenic Arabidopsis Gene Expression System

    Science.gov (United States)

    Ferl, Robert; Paul, Anna-Lisa

    2009-01-01

    The Transgenic Arabidopsis Gene Expression System (TAGES) investigation is one in a pair of investigations that use the Advanced Biological Research System (ABRS) facility. TAGES uses Arabidopsis thaliana, thale cress, with sensor promoter-reporter gene constructs that render the plants as biomonitors (an organism used to determine the quality of the surrounding environment) of their environment using real-time nondestructive Green Fluorescent Protein (GFP) imagery and traditional postflight analyses.

  15. Tackling heterogeneity: a leaf disc-based assay for the high-throughput screening of transient gene expression in tobacco.

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    Natalia Piotrzkowski

    Full Text Available Transient Agrobacterium-mediated gene expression assays for Nicotiana tabacum (N. tabacum are frequently used because they facilitate the comparison of multiple expression constructs regarding their capacity for maximum recombinant protein production. However, for three model proteins, we found that recombinant protein accumulation (rpa was significantly influenced by leaf age and leaf position effects. The ratio between the highest and lowest amount of protein accumulation (max/min ratio was found to be as high as 11. Therefore, construct-based impacts on the rpa level that are less than 11-fold will be masked by background noise. To address this problem, we developed a leaf disc-based screening assay and infiltration device that allows the rpa level in a whole tobacco plant to be reliably and reproducibly determined. The prototype of the leaf disc infiltration device allows 14 Agrobacterium-mediated infiltration events to be conducted in parallel. As shown for three model proteins, the average max/min rpa ratio was reduced to 1.4 using this method, which allows for a sensitive comparison of different genetic elements affecting recombinant protein expression.

  16. Human papillomavirus gene expression

    International Nuclear Information System (INIS)

    Chow, L.T.; Hirochika, H.; Nasseri, M.; Stoler, M.H.; Wolinsky, S.M.; Chin, M.T.; Hirochika, R.; Arvan, D.S.; Broker, T.R.

    1987-01-01

    To determine the role of tissue differentiation on expression of each of the papillomavirus mRNA species identified by electron microscopy, the authors prepared exon-specific RNA probes that could distinguish the alternatively spliced mRNA species. Radioactively labeled single-stranded RNA probes were generated from a dual promoter vector system and individually hybridized to adjacent serial sections of formalin-fixed, paraffin-embedded biopsies of condylomata. Autoradiography showed that each of the message species had a characteristic tissue distribution and relative abundance. The authors have characterized a portion of the regulatory network of the HPVs by showing that the E2 ORF encodes a trans-acting enhancer-stimulating protein, as it does in BPV-1 (Spalholz et al. 1985). The HPV-11 enhancer was mapped to a 150-bp tract near the 3' end of the URR. Portions of this region are duplicated in some aggressive strains of HPV-6 (Boshart and zur Hausen 1986; Rando et al. 1986). To test the possible biological relevance of these duplications, they cloned tandem arrays of the enhancer and demonstrated, using a chloramphenicol acetyltransferase (CAT) assay, that they led to dramatically increased transcription proportional to copy number. Using the CAT assays, the authors found that the E2 proteins of several papillomavirus types can cross-stimulate the enhancers of most other types. This suggests that prior infection of a tissue with one papillomavirus type may provide a helper effect for superinfection and might account fo the HPV-6/HPV-16 coinfections in condylomata that they have observed

  17. A SAGE-based screen for genes expressed in sub-populations of neurons in the mouse dorsal root ganglion

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    Garces Alain

    2007-11-01

    Full Text Available Abstract Background The different sensory modalities temperature, pain, touch and muscle proprioception are carried by somatosensory neurons of the dorsal root ganglia. Study of this system is hampered by the lack of molecular markers for many of these neuronal sub-types. In order to detect genes expressed in sub-populations of somatosensory neurons, gene profiling was carried out on wild-type and TrkA mutant neonatal dorsal root ganglia (DRG using SAGE (serial analysis of gene expression methodology. Thermo-nociceptors constitute up to 80 % of the neurons in the DRG. In TrkA mutant DRGs, the nociceptor sub-class of sensory neurons is lost due to absence of nerve growth factor survival signaling through its receptor TrkA. Thus, comparison of wild-type and TrkA mutants allows the identification of transcripts preferentially expressed in the nociceptor or mechano-proprioceptor subclasses, respectively. Results Our comparison revealed 240 genes differentially expressed between the two tissues (P Conclusion We have identified and characterized the detailed expression patterns of three genes in the developing DRG, placing them in the context of the known major neuronal sub-types defined by molecular markers. Further analysis of differentially expressed genes in this tissue promises to extend our knowledge of the molecular diversity of different cell types and forms the basis for understanding their particular functional specificities.

  18. A novel minicircle vector based system for inhibting the replication and gene expression of enterovirus 71 and coxsackievirus A16.

    Science.gov (United States)

    Yang, Zhuo; Li, Guodong; Zhang, Yingqiu; Liu, Xiaoman; Tien, Po

    2012-11-01

    Enterovirus 71 (EV 71) and Coxsackievirus A16 (CA 16) are two major causative agents of hand, foot and mouth disease (HFMD). They have been associated with severe neurological and cardiological complications worldwide, and have caused significant mortalities during large-scale outbreaks in China. Currently, there are no effective treatments against EV 71 and CA 16 infections. We now describe the development of a novel minicircle vector based RNA interference (RNAi) system as a therapeutic approach to inhibiting EV 71 and CA 16 replication. Small interfering RNA (siRNA) molecules targeting the conserved regions of the 3C(pro) and 3D(pol) function gene of the EV 71 and CA 16 China strains were designed based on their nucleotide sequences available in GenBank. This RNAi system was found to effectively block the replication and gene expression of these viruses in rhabdomyosarcoma (RD) cells and virus-infected mice model. The inhibitory effects were confirmed by a corresponding decrease in viral RNA, viral protein, and progeny virus production. In addition, no significant adverse off-target silencing or cytotoxic effects were observed. These results demonstrated the potential and feasibility of this novel minicircle vector based RNAi system for antiviral therapy against EV 71 and CA 16 infection. Copyright © 2012 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

    Sykacek, P

    2012-09-15

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

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

    Science.gov (United States)

    Sykacek, P.

    2012-01-01

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

  2. Mismatch repair gene expression in gastroesophageal cancers.

    Science.gov (United States)

    Dracea, Amelia; Angelescu, Cristina; Danciulescu, Mihaela; Ciurea, Marius; Ioana, Mihai; Burada, Florin

    2015-09-01

    Mismatch repair (MMR) genes play a critical role in maintaining genomic stability, and the impairment of MMR machinery is associated with different human cancers, mainly colorectal cancer. The purpose of our study was to analyze gene expression patterns of three MMR genes (MSH2, MHS6, and EXO1) in gastroesophageal cancers, a pathology in which the contribution of DNA repair genes remains essentially unclear. A total of 45 Romanian patients diagnosed with sporadic gastroesophageal cancers were included in this study. For each patient, MMR mRNA levels were measured in biopsied tumoral (T) and peritumoral (PT) tissues obtained by upper endoscopy. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) with specific TaqMan probes was used to measure gene expression levels for MSH2, MSH6, and EXO1 genes. A significant association was observed for the investigated MMR genes, all of which were detected to be upregulated in gastroesophageal tumor samples when compared with paired normal samples. In the stratified analysis, the association was limited to gastric adenocarcinoma samples. We found no statistically significant associations between MMR gene expression and tumor site or histological grade. In our study, MSH2, MSH6, and EXO1 genes were overexpressed in gastroesophageal cancers. Further investigations based on more samples are necessary to validate our findings.

  3. Novel subtractive transcription-based amplification of mRNA (STAR method and its application in search of rare and differentially expressed genes in AD brains

    Directory of Open Access Journals (Sweden)

    Walker P Roy

    2006-11-01

    Full Text Available Abstract Background Alzheimer's disease (AD is a complex disorder that involves multiple biological processes. Many genes implicated in these processes may be present in low abundance in the human brain. DNA microarray analysis identifies changed genes that are expressed at high or moderate levels. Complementary to this approach, we described here a novel technology designed specifically to isolate rare and novel genes previously undetectable by other methods. We have used this method to identify differentially expressed genes in brains affected by AD. Our method, termed Subtractive Transcription-based Amplification of mRNA (STAR, is a combination of subtractive RNA/DNA hybridization and RNA amplification, which allows the removal of non-differentially expressed transcripts and the linear amplification of the differentially expressed genes. Results Using the STAR technology we have identified over 800 differentially expressed sequences in AD brains, both up- and down- regulated, compared to age-matched controls. Over 55% of the sequences represent genes of unknown function and roughly half of them were novel and rare discoveries in the human brain. The expression changes of nearly 80 unique genes were further confirmed by qRT-PCR and the association of additional genes with AD and/or neurodegeneration was established using an in-house literature mining tool (LitMiner. Conclusion The STAR process significantly amplifies unique and rare sequences relative to abundant housekeeping genes and, as a consequence, identifies genes not previously linked to AD. This method also offers new opportunities to study the subtle changes in gene expression that potentially contribute to the development and/or progression of AD.

  4. 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...

  5. Plant Omics Data Center: an integrated web repository for interspecies gene expression networks with NLP-based curation.

    Science.gov (United States)

    Ohyanagi, Hajime; Takano, Tomoyuki; Terashima, Shin; Kobayashi, Masaaki; Kanno, Maasa; Morimoto, Kyoko; Kanegae, Hiromi; Sasaki, Yohei; Saito, Misa; Asano, Satomi; Ozaki, Soichi; Kudo, Toru; Yokoyama, Koji; Aya, Koichiro; Suwabe, Keita; Suzuki, Go; Aoki, Koh; Kubo, Yasutaka; Watanabe, Masao; Matsuoka, Makoto; Yano, Kentaro

    2015-01-01

    Comprehensive integration of large-scale omics resources such as genomes, transcriptomes and metabolomes will provide deeper insights into broader aspects of molecular biology. For better understanding of plant biology, we aim to construct a next-generation sequencing (NGS)-derived gene expression network (GEN) repository for a broad range of plant species. So far we have incorporated information about 745 high-quality mRNA sequencing (mRNA-Seq) samples from eight plant species (Arabidopsis thaliana, Oryza sativa, Solanum lycopersicum, Sorghum bicolor, Vitis vinifera, Solanum tuberosum, Medicago truncatula and Glycine max) from the public short read archive, digitally profiled the entire set of gene expression profiles, and drawn GENs by using correspondence analysis (CA) to take advantage of gene expression similarities. In order to understand the evolutionary significance of the GENs from multiple species, they were linked according to the orthology of each node (gene) among species. In addition to other gene expression information, functional annotation of the genes will facilitate biological comprehension. Currently we are improving the given gene annotations with natural language processing (NLP) techniques and manual curation. Here we introduce the current status of our analyses and the web database, PODC (Plant Omics Data Center; http://bioinf.mind.meiji.ac.jp/podc/), now open to the public, providing GENs, functional annotations and additional comprehensive omics resources. © The Author 2014. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.

  6. Blood-Based Gene Expression Signatures of Infants and Toddlers with Autism

    Science.gov (United States)

    Glatt, Stephen J.; Tsuang, Ming T.; Winn, Mary; Chandler, Sharon D.; Collins, Melanie; Lopez, Linda; Weinfeld, Melanie; Carter, Cindy; Schork, Nicholas; Pierce, Karen; Courchesne, Eric

    2012-01-01

    Objective: Autism spectrum disorders (ASDs) are highly heritable neurodevelopmental disorders that onset clinically during the first years of life. ASD risk biomarkers expressed early in life could significantly impact diagnosis and treatment, but no transcriptome-wide biomarker classifiers derived from fresh blood samples from children with…

  7. Vascular Gene Expression: A Hypothesis

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    Angélica Concepción eMartínez-Navarro

    2013-07-01

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

  8. Transcriptome-based identification of antioxidative gene expression after fish oil supplementation in normo- and dyslipidemic men

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    Schmidt Simone

    2012-05-01

    Full Text Available Abstract Background The beneficial effects of omega-3 polyunsaturated fatty acids (n-3 PUFAs, especially in dyslipidemic subjects with a high risk of cardiovascular disease, are widely described in the literature. A lot of effects of n-3 PUFAs and their oxidized metabolites are triggered by regulating the expression of genes. Currently, it is uncertain if the administration of n-3 PUFAs results in different expression changes of genes related to antioxidative mechanisms in normo- and dyslipidemic subjects, which may partly explain their cardioprotective effects. The aim of this study was to investigate the effects of n-3 PUFA supplementation on expression changes of genes involved in oxidative processes. Methods Ten normo- and ten dyslipidemic men were supplemented for twelve weeks with fish oil capsules, providing 1.14 g docosahexaenoic acid and 1.56 g eicosapentaenoic acid. Gene expression levels were determined by whole genome microarray analysis and quantitative real-time polymerase chain reaction (qRT-PCR. Results Using microarrays, we discovered an increased expression of antioxidative enzymes and a decreased expression of pro-oxidative and tissue enzymes, such as cytochrome P450 enzymes and matrix metalloproteinases, in both normo- and dyslipidemic men. An up-regulation of catalase and heme oxigenase 2 in both normo- and dyslipidemic subjects and an up-regulation of cytochrome P450 enzyme 1A2 only in dyslipidemic subjects could be observed by qRT-PCR analysis. Conclusions Supplementation of normo- and dyslipidemic subjects with n-3 PUFAs changed the expression of genes related to oxidative processes, which may suggest antioxidative and potential cardioprotective effects of n-3 PUFAs. Further studies combining genetic and metabolic endpoints are needed to verify the regulative effects of n-3 PUFAs in antioxidative gene expression to better understand their beneficial effects in health and disease prevention. Trial registration Clinical

  9. 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

  10. Visualizing spatiotemporal dynamics of apoptosis after G1 arrest by human T cell leukemia virus type 1 Tax and insights into gene expression changes using microarray-based gene expression analysis

    Directory of Open Access Journals (Sweden)

    Arainga Mariluz

    2012-06-01

    Full Text Available Abstract Background Human T cell leukemia virus type 1 (HTLV-1 Tax is a potent activator of viral and cellular gene expression that interacts with a number of cellular proteins. Many reports show that Tax is capable of regulating cell cycle progression and apoptosis both positively and negatively. However, it still remains to understand why the Tax oncoprotein induces cell cycle arrest and apoptosis, or whether Tax-induced apoptosis is dependent upon its ability to induce G1 arrest. The present study used time-lapse imaging to explore the spatiotemporal patterns of cell cycle dynamics in Tax-expressing HeLa cells containing the fluorescent ubiquitination-based cell cycle indicator, Fucci2. A large-scale host cell gene profiling approach was also used to identify the genes involved in Tax-mediated cell signaling events related to cellular proliferation and apoptosis. Results Tax-expressing apoptotic cells showed a rounded morphology and detached from the culture dish after cell cycle arrest at the G1 phase. Thus, it appears that Tax induces apoptosis through pathways identical to those involved in G1 arrest. To elucidate the mechanism(s by which Tax induces cell cycle arrest and apoptosis, regulation of host cellular genes by Tax was analyzed using a microarray containing approximately 18,400 human mRNA transcripts. Seventeen genes related to cell cycle regulation were identified as being up or downregulated > 2.0-fold in Tax-expressing cells. Several genes, including SMAD3, JUN, GADD45B, DUSP1 and IL8, were involved in cellular proliferation, responses to cellular stress and DNA damage, or inflammation and immune responses. Additionally, 23 pro- and anti-apoptotic genes were deregulated by Tax, including TNFAIP3, TNFRS9, BIRC3 and IL6. Furthermore, the kinetics of IL8, SMAD3, CDKN1A, GADD45A, GADD45B and IL6 expression were altered following the induction of Tax, and correlated closely with the morphological changes observed by time

  11. Visualizing spatiotemporal dynamics of apoptosis after G1 arrest by human T cell leukemia virus type 1 Tax and insights into gene expression changes using microarray-based gene expression analysis.

    Science.gov (United States)

    Arainga, Mariluz; Murakami, Hironobu; Aida, Yoko

    2012-06-22

    Human T cell leukemia virus type 1 (HTLV-1) Tax is a potent activator of viral and cellular gene expression that interacts with a number of cellular proteins. Many reports show that Tax is capable of regulating cell cycle progression and apoptosis both positively and negatively. However, it still remains to understand why the Tax oncoprotein induces cell cycle arrest and apoptosis, or whether Tax-induced apoptosis is dependent upon its ability to induce G1 arrest. The present study used time-lapse imaging to explore the spatiotemporal patterns of cell cycle dynamics in Tax-expressing HeLa cells containing the fluorescent ubiquitination-based cell cycle indicator, Fucci2. A large-scale host cell gene profiling approach was also used to identify the genes involved in Tax-mediated cell signaling events related to cellular proliferation and apoptosis. Tax-expressing apoptotic cells showed a rounded morphology and detached from the culture dish after cell cycle arrest at the G1 phase. Thus, it appears that Tax induces apoptosis through pathways identical to those involved in G1 arrest. To elucidate the mechanism(s) by which Tax induces cell cycle arrest and apoptosis, regulation of host cellular genes by Tax was analyzed using a microarray containing approximately 18,400 human mRNA transcripts. Seventeen genes related to cell cycle regulation were identified as being up or downregulated > 2.0-fold in Tax-expressing cells. Several genes, including SMAD3, JUN, GADD45B, DUSP1 and IL8, were involved in cellular proliferation, responses to cellular stress and DNA damage, or inflammation and immune responses. Additionally, 23 pro- and anti-apoptotic genes were deregulated by Tax, including TNFAIP3, TNFRS9, BIRC3 and IL6. Furthermore, the kinetics of IL8, SMAD3, CDKN1A, GADD45A, GADD45B and IL6 expression were altered following the induction of Tax, and correlated closely with the morphological changes observed by time-lapse imaging. Taken together, the results of this

  12. PCR-based amplification and heterologous expression of Pseudomonas alcohol dehydrogenase genes from the soil metagenome for biocatalysis.

    Science.gov (United States)

    Itoh, Nobuya; Isotani, Kentaro; Makino, Yoshihide; Kato, Masaki; Kitayama, Kouta; Ishimota, Tuyoshi

    2014-02-05

    The amplification of useful genes from metagenomes offers great biotechnological potential. We employed this approach to isolate alcohol dehydrogenase (adh) genes from Pseudomonas to aid in the synthesis of optically pure alcohols from various ketones. A PCR primer combination synthesized by reference to the adh sequences of known Pseudomonas genes was used to amplify full-length adh genes directly from 17 samples of DNA extracted from soil. Three such adh preparations were used to construct Escherichia coli plasmid libraries. Of the approximately 2800 colonies obtained, 240 putative adh-positive clones were identified by colony-PCR. Next, 23 functional adh genes named using the descriptors HBadh and HPadh were analyzed. The adh genes obtained via this metagenomic approach varied in their DNA and amino acid sequences. Expression of the gene products in E. coli indicated varying substrate specificity. Two representative genes, HBadh-1 and HPadh-24, expressed in E. coli and Pseudomonas putida, respectively, were purified and characterized in detail. The enzyme products of these genes were confirmed to be useful for producing anti-Prelog chiral alcohols. Copyright © 2013 Elsevier Inc. All rights reserved.

  13. Mapping in an apple (Malus x domestica) F1 segregating population based on physical clustering of differentially expressed genes.

    Science.gov (United States)

    Jensen, Philip J; Fazio, Gennaro; Altman, Naomi; Praul, Craig; McNellis, Timothy W

    2014-04-04

    Apple tree breeding is slow and difficult due to long generation times, self-incompatibility, and complex genetics. The identification of molecular markers linked to traits of interest is a way to expedite the breeding process. In the present study, we aimed to identify genes whose steady-state transcript abundance was associated with inheritance of specific traits segregating in an apple (Malus × domestica) rootstock F1 breeding population, including resistance to powdery mildew (Podosphaera leucotricha) disease and woolly apple aphid (Eriosoma lanigerum). Transcription profiling was performed for 48 individual F1 apple trees from a cross of two highly heterozygous parents, using RNA isolated from healthy, actively-growing shoot tips and a custom apple DNA oligonucleotide microarray representing 26,000 unique transcripts. Genome-wide expression profiles were not clear indicators of powdery mildew or woolly apple aphid resistance phenotype. However, standard differential gene expression analysis between phenotypic groups of trees revealed relatively small sets of genes with trait-associated expression levels. For example, thirty genes were identified that were differentially expressed between trees resistant and susceptible to powdery mildew. Interestingly, the genes encoding twenty-four of these transcripts were physically clustered on chromosome 12. Similarly, seven genes were identified that were differentially expressed between trees resistant and susceptible to woolly apple aphid, and the genes encoding five of these transcripts were also clustered, this time on chromosome 17. In each case, the gene clusters were in the vicinity of previously identified major quantitative trait loci for the corresponding trait. Similar results were obtained for a series of molecular traits. Several of the differentially expressed genes were used to develop DNA polymorphism markers linked to powdery mildew disease and woolly apple aphid resistance. Gene expression profiling

  14. Gene expression profile of pulpitis

    Science.gov (United States)

    Galicia, Johnah C.; Henson, Brett R.; Parker, Joel S.; Khan, Asma A.

    2016-01-01

    The cost, prevalence and pain associated with endodontic disease necessitate an understanding of the fundamental molecular aspects of its pathogenesis. This study was aimed to identify the genetic contributors to pulpal pain and inflammation. Inflamed pulps were collected from patients diagnosed with irreversible pulpitis (n=20). Normal pulps from teeth extracted for various reasons served as controls (n=20). Pain level was assessed using a visual analog scale (VAS). Genome-wide microarray analysis was performed using Affymetrix GeneTitan Multichannel Instrument. The difference in gene expression levels were determined by the Significance Analysis of Microarray program using a false discovery rate (q-value) of 5%. Genes involved in immune response, cytokine-cytokine receptor interaction and signaling, integrin cell surface interactions, and others were expressed at relatively higher levels in the in the pulpitis group. Moreover, several genes known to modulate pain and inflammation showed differential expression in asymptomatic and mild pain patients (≥30mm on VAS) compared to those with moderate to severe pain. This exploratory study provides a molecular basis for the clinical diagnosis of pulpitis. With an enhanced understanding of pulpal inflammation, future studies on treatment and management of pulpitis and on pain associated with it can have a biological reference to bridge treatment strategies with pulpal biology. PMID:27052691

  15. Gene expression profile of pulpitis.

    Science.gov (United States)

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

    2016-06-01

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

  16. 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.

  17. Application of Artificial Neural Networks in Cancer Classification and Diagnosis Prediction of a Subtype of Lymphoma Based on Gene Expression Profile

    Directory of Open Access Journals (Sweden)

    L Ziaei

    2006-01-01

    Full Text Available Background: Diffuse Large B-cell Lymphoma (DLBCL is the most common subtype of non-Hodgkin’s Lymphoma. DLBCL patients have different survivals after diagnosis. 40% of patients respond well to current therapy and have prolonged survival, whereas the remainders survive less than 5 years. In this study, we have applied artificial neural network to classify patients with DLBCL on the basis of their gene expression profiles. Finally, we have attempted to extract a number of genes that their differential expression were significant in DLBCL subtypes. Methods: We studied 40 patients and 4026 genes. In this study, genes were ranked based on their signal to noise (S/N ratios. After selecting a suitable threshold, some of them whose ratios were less than the threshold were removed. Then we used PCA for more reducing and Perceptron neural network for classification of these patients. We extracted some appropriate genes based on their prediction ability. Results: We considered various targets for patients classifying. Thus patients were classified based on their 5 years survival with accuracy of 93%, in regard to Alizadeh et al study results with accuracy of 100%, and regarding with their International Prognosis Index (IPI with accuracy of 89%. Conclusion: Combination of PCA and S/N ratio is an effective method for the reduction of the dimension and neural network is a robust tool for classification of patients according to their gene expression profile. Keywords: classification, gene expression, DLBCL, neural network, Perceptron

  18. A Cas9-based toolkit to program gene expression in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Apel, Amanda Reider; d'Espaux, Leo; Wehrs, Maren

    2017-01-01

    Despite the extensive use of Saccharomyces cere-visiae as a platform for synthetic biology, strain engineering remains slow and laborious. Here, we employ CRISPR/Cas9 technology to build a cloning-free toolkit that addresses commonly encountered obstacles in metabolic engineering, including...... chromosomal integration locus and promoter selection, as well as protein localization and solubility. The toolkit includes 23 Cas9-sgRNA plasmids, 37 promoters of various strengths and temporal expression profiles, and 10 protein-localization, degradation and solubility tags. We facilitated the use...

  19. 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.

  20. PERSPECTIVE: Toward an artificial cell based on gene expression in vesicles

    Science.gov (United States)

    Noireaux, Vincent; Bar-Ziv, Roy; Godefroy, Jeremy; Salman, Hanna; Libchaber, Albert

    2005-09-01

    We present a new experimental approach to build an artificial cell using the translation machinery of a cell-free expression system as the hardware and a DNA synthetic genome as the software. This approach, inspired by the self-replicating automata of von Neumann, uses cytoplasmic extracts, encapsulated in phospholipid vesicles, to assemble custom-made genetic circuits to develop the functions of a minimal cell. Although this approach can find applications, especially in biotechnology, the primary goal is to understand how a DNA algorithm can be designed to build an operating system that has some of the properties of life. We provide insights on this cell-free approach as well as new results to transform step by step a long-lived vesicle bioreactor into an artificial cell. We show how the green fluorescent protein can be anchored to the membrane and we give indications of a possible insertion mechanism of integral membrane proteins. With vesicles composed of different phospholipids, the fusion protein alpha-hemolysin-eGFP can be expressed to reveal patterns on the membrane. The specific degradation complex ClpXP from E. coli is introduced to create a sink for the synthesized proteins. Perspectives and subsequent limitations of this approach are discussed.

  1. Automatic Rule Identification for Agent-Based Crowd Models Through Gene Expression Programming

    NARCIS (Netherlands)

    Zhong, J.; Luo, L.; Cai, W.; Lees, M.; Lomuscio, A.; Scerri, P.; Bazzan, A.; Huhns, M.

    2014-01-01

    Agent-based modelling of human crowds has now become an important and active research field, with a wide range of applications such as military training, evacuation analysis and digital game. One of the significant and challenging tasks in agent-based crowd modelling is the design of decision rules

  2. Time-course investigation of the gene expression profile during Fasciola hepatica infection: A microarray-based study.

    Science.gov (United States)

    Rojas-Caraballo, Jose; López-Abán, Julio; Fernández-Soto, Pedro; Vicente, Belén; Collía, Francisco; Muro, Antonio

    2015-12-01

    Fasciolosis is listed as one of the most important neglected tropical diseases according with the World Health Organization and is also considered as a reemerging disease in the human beings. Despite there are several studies describing the immune response induced by Fasciola hepatica in the mammalian host, investigations aimed at identifying the expression profile of genes involved in inducing hepatic injury are currently scarce. Data presented here belong to a time-course investigation of the gene expression profile in the liver of BALB/c mice infected with F. hepatica metacercariae at 7 and 21 days after experimental infection. The data published here have been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE69588, previously published by Rojas-Caraballo et al. (2015) in PLoS One [1].

  3. Time-course investigation of the gene expression profile during Fasciola hepatica infection: A microarray-based study

    Directory of Open Access Journals (Sweden)

    Jose Rojas-Caraballo

    2015-12-01

    Full Text Available Fasciolosis is listed as one of the most important neglected tropical diseases according with the World Health Organization and is also considered as a reemerging disease in the human beings. Despite there are several studies describing the immune response induced by Fasciola hepatica in the mammalian host, investigations aimed at identifying the expression profile of genes involved in inducing hepatic injury are currently scarce. Data presented here belong to a time-course investigation of the gene expression profile in the liver of BALB/c mice infected with F. hepatica metacercariae at 7 and 21 days after experimental infection. The data published here have been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE69588, previously published by Rojas-Caraballo et al. (2015 in PLoS One [1].

  4. Expression Study of Banana Pathogenic Resistance Genes

    Directory of Open Access Journals (Sweden)

    Fenny M. Dwivany

    2016-10-01

    Full Text Available Banana is one of the world's most important trade commodities. However, infection of banana pathogenic fungi (Fusarium oxysporum race 4 is one of the major causes of decreasing production in Indonesia. Genetic engineering has become an alternative way to control this problem by isolating genes that involved in plant defense mechanism against pathogens. Two of the important genes are API5 and ChiI1, each gene encodes apoptosis inhibitory protein and chitinase enzymes. The purpose of this study was to study the expression of API5 and ChiI1 genes as candidate pathogenic resistance genes. The amplified fragments were then cloned, sequenced, and confirmed with in silico studies. Based on sequence analysis, it is showed that partial API5 gene has putative transactivation domain and ChiI1 has 9 chitinase family GH19 protein motifs. Data obtained from this study will contribute in banana genetic improvement.

  5. Exploring suppression subtractive hybridization (SSH) for discriminating Lactococcus lactis ssp. cremoris SK11 and ATCC 19257 in mixed culture based on the expression of strain-specific genes.

    Science.gov (United States)

    Ndoye, B; Lessard, M-H; LaPointe, G; Roy, D

    2011-02-01

    An approach based on quantitative reverse transcriptase PCR (RT-qPCR) was developed for monitoring two strains of lactococci in co-culture in milk by measuring the expression of specific genes identified by suppression subtractive hybridization (SSH). SSH was used to identify strain-specific genes of Lactococcus lactis ssp. cremoris SK11 and ATCC 19257. RT-qPCR was then employed to validate gene specificity and compare the expression of selected specific genes (glycosyltransferase and amidase genes for L. lactis ssp. cremoris ATCC 19257 and a hypothetical protein for SK11) identified by SSH. The time profile of changes in gene expression relative to ldh transcription differed between pure and mixed cultures as well as between media. At the stationary phase, gene expression of mixed cultures in GM17 attained the highest proportion of ldh transcription while mixed cultures in milk peaked at the postexponential phase. Strain ratios expressed as RNA proportion appear to favour SK11 in GM17 medium, while ATCC 19257 dominated in milk co-cultures. This approach was useful to determine the contribution of strain SK11 in relation to strain ATCC 19257 during co-culture in milk compared to rich medium. The ability to track the metabolic contribution of each lactococcal strain during fermentation of milk or cheese ripening will extend our understanding of the impact of process parameters on the production performance of strains. © 2010 The Authors. Journal of Applied Microbiology © 2010 The Society for Applied Microbiology.

  6. Transcriptome-based analysis of kidney gene expression changes associated with diabetes in OVE26 mice, in the presence and absence of losartan treatment.

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    Radko Komers

    Full Text Available Diabetes is among the most common causes of end-stage renal disease, although its pathophysiology is incompletely understood. We performed next-generation sequencing-based transcriptome analysis of renal gene expression changes in the OVE26 murine model of diabetes (age 15 weeks, relative to non-diabetic control, in the presence and absence of short-term (seven-day treatment with the angiotensin receptor blocker, losartan (n = 3-6 biological replicates per condition. We detected 1438 statistically significant changes in gene expression across conditions. Of the 638 genes dysregulated in diabetes relative to the non-diabetic state, >70% were downregulation events. Unbiased functional annotation of genes up- and down-regulated by diabetes strongly associated (p52-fold, encoded by the cationic amino acid transporter Slc7a12, and the gene product most highly downregulated by diabetes (>99%--encoded by the "pseudogene" Gm6300--are adjacent in the murine genome, are members of the SLC7 gene family, and are likely paralogous. Therefore, diabetes activates a near-total genetic switch between these two paralogs. Other individual-level changes in gene expression are potentially relevant to diabetic pathophysiology, and novel pathways are suggested. Genes unaffected by diabetes alone but exhibiting increased renal expression with losartan produced a signature consistent with malignant potential.

  7. Conversion of a molecular classifier obtained by gene expression profiling into a classifier based on real-time PCR: a prognosis predictor for gliomas.

    Science.gov (United States)

    Kawarazaki, Satoru; Taniguchi, Kazuya; Shirahata, Mitsuaki; Kukita, Yoji; Kanemoto, Manabu; Mikuni, Nobuhiro; Hashimoto, Nobuo; Miyamoto, Susumu; Takahashi, Jun A; Kato, Kikuya

    2010-11-10

    The advent of gene expression profiling was expected to dramatically improve cancer diagnosis. However, despite intensive efforts and several successful examples, the development of profile-based diagnostic systems remains a difficult task. In the present work, we established a method to convert molecular classifiers based on adaptor-tagged competitive PCR (ATAC-PCR) (with a data format that is similar to that of microarrays) into classifiers based on real-time PCR. Previously, we constructed a prognosis predictor for glioma using gene expression data obtained by ATAC-PCR, a high-throughput reverse-transcription PCR technique. The analysis of gene expression data obtained by ATAC-PCR is similar to the analysis of data from two-colour microarrays. The prognosis predictor was a linear classifier based on the first principal component (PC1) score, a weighted summation of the expression values of 58 genes. In the present study, we employed the delta-delta Ct method for measurement by real-time PCR. The predictor was converted to a Ct value-based predictor using linear regression. We selected UBL5 as the reference gene from the group of genes with expression patterns that were most similar to the median expression level from the previous profiling study. The number of diagnostic genes was reduced to 27 without affecting the performance of the prognosis predictor. PC1 scores calculated from the data obtained by real-time PCR showed a high linear correlation (r=0.94) with those obtained by ATAC-PCR. The correlation for individual gene expression patterns (r=0.43 to 0.91) was smaller than for PC1 scores, suggesting that errors of measurement were likely cancelled out during the weighted summation of the expression values. The classification of a test set (n=36) by the new predictor was more accurate than histopathological diagnosis (log rank p-values, 0.023 and 0.137, respectively) for predicting prognosis. We successfully converted a molecular classifier obtained by ATAC

  8. Gene expression profiling for pharmaceutical toxicology screening.

    Science.gov (United States)

    Bugelski, Peter J

    2002-01-01

    Advances in medicinal chemistry and high-throughput pharmacological screening are creating a multitude of potential lead compounds. There is also heightened concern about drug-induced toxicity, which is all too often uncovered late in development or at the post marketing stage. Together, these factors have created a need for novel approaches to screen for toxicity. There have been technological advances that enable study of changes in the gene expression profile caused by toxic insults and important steps made toward unraveling target organ toxicity at the molecular level. Thus, gene expression profile-based screens hold the promise to revolutionize the way in which compounds are selected for development. For screens focused on specific mechanisms of toxicity, reporter gene systems have proven utility, albeit modest because of our limited knowledge of which genes are true surrogate markers for toxicity. For broader forecasts of toxicity, DNA microarrays hold great promise for delivering practical gene expression profile screens (GEPS). For this promise to be realized, however, a number of technological hurdles must be cleared: (i) cost; (ii) reproducibility; (iii) throughput; and (iv) data analysis. Of equal if not greater importance, issues relating to the test systems used, the requisite number of genes to be studied and the size and scope of the database upon which forecasts will be based must be addressed. At present, the proof-of-concept for GEPS for toxicity is in hand, and we are poised to realize the goal of creating practical GEPS for application in compound prioritization.

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

    Directory of Open Access Journals (Sweden)

    Ellis Stephen G

    2011-03-01

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

  10. 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.

  11. Blood-Based Gene Expression Profiles Models for Classification of Subsyndromal Symptomatic Depression and Major Depressive Disorder

    Science.gov (United States)

    Yu, Shunying; Yuan, Chengmei; Hong, Wu; Wang, Zuowei; Cui, Jian; Shi, Tieliu; Fang, Yiru

    2012-01-01

    Subsyndromal symptomatic depression (SSD) is a subtype of subthreshold depressive and also lead to significant psychosocial functional impairment as same as major depressive disorder (MDD). Several studies have suggested that SSD is a transitory phenomena in the depression spectrum and is thus considered a subtype of depression. However, the pathophysioloy of depression remain largely obscure and studies on SSD are limited. The present study 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 controls (8 subjects in each group). Support vector machines (SVMs) were utilized for training and testing on candidate signature expression profiles from signature selection step. Firstly, we identified 63 differentially expressed SSD signatures in contrast to control (P< = 5.0E-4) and 30 differentially expressed MDD signatures in contrast to control, respectively. Then, 123 gene signatures were identified with significantly differential expression level between SSD and MDD. Secondly, in order to conduct priority selection for biomarkers for SSD and MDD together, we selected top gene signatures from each group of pair-wise comparison results, and merged the signatures together to generate better profiles used for clearly classify SSD and MDD sets in the same time. In details, we tried different combination of signatures from the three pair-wise compartmental results and finally determined 48 gene expression signatures with 100% accuracy. Our finding suggested that SSD and MDD did not exhibit the same expressed genome signature with peripheral blood leukocyte, and blood cell–derived RNA of these 48 gene models may have significant value for performing diagnostic functions and classifying SSD, MDD, and healthy controls. PMID:22348066

  12. 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

  13. A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data.

    Science.gov (United States)

    Kang, Tianyu; Ding, Wei; Zhang, Luoyan; Ziemek, Daniel; Zarringhalam, Kourosh

    2017-12-19

    Stratification of patient subpopulations that respond favorably to treatment or experience and adverse reaction is an essential step toward development of new personalized therapies and diagnostics. It is currently feasible to generate omic-scale biological measurements for all patients in a study, providing an opportunity for machine learning models to identify molecular markers for disease diagnosis and progression. However, the high variability of genetic background in human populations hampers the reproducibility of omic-scale markers. In this paper, we develop a biological network-based regularized artificial neural network model for prediction of phenotype from transcriptomic measurements in clinical trials. To improve model sparsity and the overall reproducibility of the model, we incorporate regularization for simultaneous shrinkage of gene sets based on active upstream regulatory mechanisms into the model. We benchmark our method against various regression, support vector machines and artificial neural network models and demonstrate the ability of our method in predicting the clinical outcomes using clinical trial data on acute rejection in kidney transplantation and response to Infliximab in ulcerative colitis. We show that integration of prior biological knowledge into the classification as developed in this paper, significantly improves the robustness and generalizability of predictions to independent datasets. We provide a Java code of our algorithm along with a parsed version of the STRING DB database. In summary, we present a method for prediction of clinical phenotypes using baseline genome-wide expression data that makes use of prior biological knowledge on gene-regulatory interactions in order to increase robustness and reproducibility of omic-scale markers. The integrated group-wise regularization methods increases the interpretability of biological signatures and gives stable performance estimates across independent test sets.

  14. Distinct gene expression responses of two anticonvulsant drugs in a novel human embryonic stem cell based neural differentiation assay protocol.

    Science.gov (United States)

    Schulpen, Sjors H W; de Jong, Esther; de la Fonteyne, Liset J J; de Klerk, Arja; Piersma, Aldert H

    2015-04-01

    Hazard assessment of chemicals and pharmaceuticals is increasingly gaining from knowledge about molecular mechanisms of toxic action acquired in dedicated in vitro assays. We have developed an efficient human embryonic stem cell neural differentiation test (hESTn) that allows the study of the molecular interaction of compounds with the neural differentiation process. Within the 11-day differentiation protocol of the assay, embryonic stem cells lost their pluripotency, evidenced by the reduced expression of stem cell markers Pou5F1 and Nanog. Moreover, stem cells differentiated into neural cells, with morphologically visible neural structures together with increased expression of neural differentiation-related genes such as βIII-tubulin, Map2, Neurogin1, Mapt and Reelin. Valproic acid (VPA) and carbamazepine (CBZ) exposure during hESTn differentiation led to concentration-dependent reduced expression of βIII-tubulin, Neurogin1 and Reelin. In parallel VPA caused an increased gene expression of Map2 and Mapt which is possibly related to the neural protective effect of VPA. These findings illustrate the added value of gene expression analysis for detecting compound specific effects in hESTn. Our findings were in line with and could explain effects observed in animal studies. This study demonstrates the potential of this assay protocol for mechanistic analysis of specific compound-induced inhibition of human neural cell differentiation. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Blood-based gene expression profiles models for classification of subsyndromal symptomatic depression and major depressive disorder.

    Science.gov (United States)

    Yi, Zhenghui; Li, Zezhi; Yu, Shunying; Yuan, Chengmei; Hong, Wu; Wang, Zuowei; Cui, Jian; Shi, Tieliu; Fang, Yiru

    2012-01-01

    Subsyndromal symptomatic depression (SSD) is a subtype of subthreshold depressive and also lead to significant psychosocial functional impairment as same as major depressive disorder (MDD). Several studies have suggested that SSD is a transitory phenomena in the depression spectrum and is thus considered a subtype of depression. However, the pathophysioloy of depression remain largely obscure and studies on SSD are limited. The present study 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 controls (8 subjects in each group). Support vector machines (SVMs) were utilized for training and testing on candidate signature expression profiles from signature selection step. Firstly, we identified 63 differentially expressed SSD signatures in contrast to control (Pbiomarkers for SSD and MDD together, we selected top gene signatures from each group of pair-wise comparison results, and merged the signatures together to generate better profiles used for clearly classify SSD and MDD sets in the same time. In details, we tried different combination of signatures from the three pair-wise compartmental results and finally determined 48 gene expression signatures with 100% accuracy. Our finding suggested that SSD and MDD did not exhibit the same expressed genome signature with peripheral blood leukocyte, and blood cell-derived RNA of these 48 gene models may have significant value for performing diagnostic functions and classifying SSD, MDD, and healthy controls.

  16. Genomics-based screening of differentially expressed genes in the brains of mice exposed to silver nanoparticles via inhalation

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Hye-Young; Choi, You-Jin; Jung, Eun-Jung; Yin, Hu-Quan [Seoul National University, College of Pharmacy and Research Institute of Pharmaceutical Sciences (Korea, Republic of); Kwon, Jung-Taek; Kim, Ji-Eun; Im, Hwang-Tae; Cho, Myung-Haing [Seoul National University, College of Veterinary Medicine (Korea, Republic of); Kim, Ju-Han [Seoul National University, College of Medicine (Korea, Republic of); Kim, Hyun-Young [Occupational Safety and Health Research Institute, Chemical Safety and Health Research Center (Korea, Republic of); Lee, Byung-Hoon, E-mail: lee@snu.ac.k [Seoul National University, College of Pharmacy and Research Institute of Pharmaceutical Sciences (Korea, Republic of)

    2010-06-15

    Silver nanoparticles (AgNP) are among the fastest growing product categories in the nanotechnology industry. Despite the importance of AgNP in consumer products and clinical applications, relatively little is known regarding AgNP toxicity and its associated risks. We investigated the effects of AgNP on gene expression in the mouse brain using Affymetrix Mouse Genome Arrays. C57BL/6 mice were exposed to AgNP (geometric mean diameter, 22.18 {+-} 1.72 nm; 1.91 x 10{sup 7} particles/cm{sup 3}) for 6 h/day, 5 days/week using the nose-only exposure system for 2 weeks. Total RNA isolated from the cerebrum and cerebellum was subjected to hybridization. From over 39,000 probe sets, 468 genes in the cerebrum and 952 genes in the cerebellum were identified as AgNP-responsive (one-way analysis of variance; p < 0.05). The largest groups of gene products affected by AgNP exposure included 73 genes in the cerebrum and 144 genes in the cerebellum. AgNP exposure modulated the expression of several genes associated with motor neuron disorders, neurodegenerative disease, and immune cell function, indicating potential neurotoxicity and immunotoxicity associated with AgNP exposure. Real-time PCR data for five genes analyzed from whole blood showed good correlation with the observed changes in the brain. Following rigorous validation and substantiation, these genes may assist in the development of surrogate markers for AgNP exposure and/or toxicity.

  17. Genomics-based screening of differentially expressed genes in the brains of mice exposed to silver nanoparticles via inhalation

    International Nuclear Information System (INIS)

    Lee, Hye-Young; Choi, You-Jin; Jung, Eun-Jung; Yin, Hu-Quan; Kwon, Jung-Taek; Kim, Ji-Eun; Im, Hwang-Tae; Cho, Myung-Haing; Kim, Ju-Han; Kim, Hyun-Young; Lee, Byung-Hoon

    2010-01-01

    Silver nanoparticles (AgNP) are among the fastest growing product categories in the nanotechnology industry. Despite the importance of AgNP in consumer products and clinical applications, relatively little is known regarding AgNP toxicity and its associated risks. We investigated the effects of AgNP on gene expression in the mouse brain using Affymetrix Mouse Genome Arrays. C57BL/6 mice were exposed to AgNP (geometric mean diameter, 22.18 ± 1.72 nm; 1.91 x 10 7 particles/cm 3 ) for 6 h/day, 5 days/week using the nose-only exposure system for 2 weeks. Total RNA isolated from the cerebrum and cerebellum was subjected to hybridization. From over 39,000 probe sets, 468 genes in the cerebrum and 952 genes in the cerebellum were identified as AgNP-responsive (one-way analysis of variance; p < 0.05). The largest groups of gene products affected by AgNP exposure included 73 genes in the cerebrum and 144 genes in the cerebellum. AgNP exposure modulated the expression of several genes associated with motor neuron disorders, neurodegenerative disease, and immune cell function, indicating potential neurotoxicity and immunotoxicity associated with AgNP exposure. Real-time PCR data for five genes analyzed from whole blood showed good correlation with the observed changes in the brain. Following rigorous validation and substantiation, these genes may assist in the development of surrogate markers for AgNP exposure and/or toxicity.

  18. Separate and combined effects of genetic variants and pre-treatment whole blood gene expression on response to exposure-based cognitive behavioural therapy for anxiety disorders.

    Science.gov (United States)

    Coleman, Jonathan R I; Lester, Kathryn J; Roberts, Susanna; Keers, Robert; Lee, Sang Hyuck; De Jong, Simone; Gaspar, Héléna; Teismann, Tobias; Wannemüller, André; Schneider, Silvia; Jöhren, Peter; Margraf, Jürgen; Breen, Gerome; Eley, Thalia C

    2017-04-01

    Exposure-based cognitive behavioural therapy (eCBT) is an effective treatment for anxiety disorders. Response varies between individuals. Gene expression integrates genetic and environmental influences. We analysed the effect of gene expression and genetic markers separately and together on treatment response. Adult participants (n ≤ 181) diagnosed with panic disorder or a specific phobia underwent eCBT as part of standard care. Percentage decrease in the Clinical Global Impression severity rating was assessed across treatment, and between baseline and a 6-month follow-up. Associations with treatment response were assessed using expression data from 3,233 probes, and expression profiles clustered in a data- and literature-driven manner. A total of 3,343,497 genetic variants were used to predict treatment response alone and combined in polygenic risk scores. Genotype and expression data were combined in expression quantitative trait loci (eQTL) analyses. Expression levels were not associated with either treatment phenotype in any analysis. A total of 1,492 eQTLs were identified with q genetic variants and treatment response did not affect expression levels significantly. Genetic variants did not significantly predict treatment response alone or in polygenic risk scores. We assessed gene expression alone and alongside genetic variants. No associations with treatment outcome were identified. Future studies require larger sample sizes to discover associations.

  19. 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

  20. Genome polymorphism markers and stress genes expression for ...

    African Journals Online (AJOL)

    SAM

    2014-06-11

    Jun 11, 2014 ... peroxide (H2O2) and molecular oxygen in the cell (Luna et al., 2008). In this study, we investigated the levels of expression of two genes in eight turf species. The levels of expression of PAL and SOD genes varied with the type of turf. Based on the differences in band intensity as a measure of gene.

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

    Science.gov (United States)

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

    2016-02-23

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

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

    Directory of Open Access Journals (Sweden)

    Ling Wei

    2016-02-01

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

  3. Differentiation between Acute Skin Rejection in Allotransplantation and T-Cell Mediated Skin Inflammation Based on Gene Expression Analysis

    Directory of Open Access Journals (Sweden)

    Dolores Wolfram

    2015-01-01

    Full Text Available Advances in microsurgical techniques and immunosuppressive medication have rendered transplantation of vascularized composite allografts possible, when autologous tissue is neither available nor sufficient for reconstruction. However, skin rejection and side effects of long-term immunosuppression still remain a major hurdle for wide adoption of this excellent reconstructive technique. Histopathologic changes during acute skin rejection in vascular composite allotransplantation often mimic inflammatory skin disorders and are hard to distinguish. Hence, the identification of diagnostic and therapeutic markers specific for skin rejection is of particular clinical need. Here we present novel markers allowing for early differentiation between rejection in hind limb allotransplantation and contact hypersensitivity. Assessment of Ccl7, Il18, and Il1b expression is most indicative of distinguishing skin rejection from skin inflammatory disorders. Gene expression levels varied significantly across skin types and regions, indicating localization specific mechanism of leukocyte migration and infiltration. Expression of Il12b, Il17a, and Il1b gene expression levels differed significantly between rejection and inflammation, independent of the skin type. In synopsis of the RNA expression profile and previously assessed protein expression, the Il1 family appears as a promising option for accurate skin rejection diagnosis and, as a following step, for development of novel rejection treatments.

  4. Harnessing gene expression networks to prioritize candidate epileptic encephalopathy genes.

    Science.gov (United States)

    Oliver, Karen L; Lukic, Vesna; Thorne, Natalie P; Berkovic, Samuel F; Scheffer, Ingrid E; Bahlo, Melanie

    2014-01-01

    We apply a novel gene expression network analysis to a cohort of 182 recently reported candidate Epileptic Encephalopathy genes to identify those most likely to be true Epileptic Encephalopathy genes. These candidate genes were identified as having single variants of likely pathogenic significance discovered in a large-scale massively parallel sequencing study. Candidate Epileptic Encephalopathy genes were prioritized according to their co-expression with 29 known Epileptic Encephalopathy genes. We utilized developing brain and adult brain gene expression data from the Allen Human Brain Atlas (AHBA) and compared this to data from Celsius: a large, heterogeneous gene expression data warehouse. We show replicable prioritization results using these three independent gene expression resources, two of which are brain-specific, with small sample size, and the third derived from a heterogeneous collection of tissues with large sample size. Of the nineteen genes that we predicted with the highest likelihood to be true Epileptic Encephalopathy genes, two (GNAO1 and GRIN2B) have recently been independently reported and confirmed. We compare our results to those produced by an established in silico prioritization approach called Endeavour, and finally present gene expression networks for the known and candidate Epileptic Encephalopathy genes. This highlights sub-networks of gene expression, particularly in the network derived from the adult AHBA gene expression dataset. These networks give clues to the likely biological interactions between Epileptic Encephalopathy genes, potentially highlighting underlying mechanisms and avenues for therapeutic targets.

  5. Codon usage and amino acid usage influence genes expression level.

    Science.gov (United States)

    Paul, Prosenjit; Malakar, Arup Kumar; Chakraborty, Supriyo

    2018-02-01

    Highly expressed genes in any species differ in the usage frequency of synonymous codons. The relative recurrence of an event of the favored codon pair (amino acid pairs) varies between gene and genomes due to varying gene expression and different base composition. Here we propose a new measure for predicting the gene expression level, i.e., codon plus amino bias index (CABI). Our approach is based on the relative bias of the favored codon pair inclination among the genes, illustrated by analyzing the CABI score of the Medicago truncatula genes. CABI showed strong correlation with all other widely used measures (CAI, RCBS, SCUO) for gene expression analysis. Surprisingly, CABI outperforms all other measures by showing better correlation with the wet-lab data. This emphasizes the importance of the neighboring codons of the favored codon in a synonymous group while estimating the expression level of a gene.

  6. Development of a predictor for human brain tumors based on gene expression values obtained from two types of microarray technologies.

    Science.gov (United States)

    Castells, Xavier; Acebes, Juan José; Boluda, Susana; Moreno-Torres, Angel; Pujol, Jesús; Julià-Sapé, Margarida; Candiota, Ana Paula; Ariño, Joaquín; Barceló, Anna; Arús, Carles

    2010-04-01

    Development of molecular diagnostics that can reliably differentiate amongst different subtypes of brain tumors is an important unmet clinical need in postgenomics medicine and clinical oncology. A simple linear formula derived from gene expression values of four genes (GFAP, PTPRZ1, GPM6B, and PRELP) measured from cDNA microarrays (n = 35) have distinguished glioblastoma and meningioma cases in a previous study. We herein extend this work further and report that the above predictor formula showed its robustness when applied to Affymetrix microarray data acquired prospectively in our laboratory (n = 80) as well as publicly available data (n = 98). Importantly, GFAP and GPM6B were both retained as being significant in the predictive model upon using the Affymetrix data obtained in our laboratory, whereas the other two predictor genes were SFRP2 and SLC6A2. These results collectively indicate the importance of the expression values of GFAP and GPM6B genes sampled from the two types of microarray technologies tested. The high prediction accuracy obtained in these instances demonstrates the robustness of the predictors across microarray platforms used. This result would require further validation with a larger population of meningioma and glioblastoma cases. At any rate, this study paves the way for further application of gene signatures to more stringent biopsy discrimination challenges.

  7. Effect of gene order in DNA constructs on gene expression upon integration into plant genome.

    Science.gov (United States)

    Aydın Akbudak, M; Srivastava, Vibha

    2017-06-01

    Several plant biotechnology applications are based on the expression of multiple genes located on a single transformation vector. The principles of stable expression of foreign genes in plant cells include integration of full-length gene fragments consisting of promoter and transcription terminator sequences, and avoiding converging orientation of the gene transcriptional direction. Therefore, investigators usually generate constructs in which genes are assembled in the same orientation. However, no specific information is available on the effect of the order in which genes should be assembled in the construct to support optimum expression of each gene upon integration in the genome. While many factors, including genomic position and the integration structure, could affect gene expression, the investigators judiciously design DNA constructs to avoid glitches. However, the gene order in a multigene assembly remains an open question. This study addressed the effect of gene order in the DNA construct on gene expression in rice using a simple design of two genes placed in two possible orders with respect to the genomic context. Transgenic rice lines containing green fluorescent protein (GFP) and β-glucuronidase (GUS) genes in two distinct orders were developed by Cre-lox-mediated site-specific integration. Gene expression analysis of transgenic lines showed that both genes were expressed at similar levels in either orientation, and different transgenic lines expressed each gene within 1-2× range. Thus, no significant effect of the gene order on gene expression was found in the transformed rice lines containing precise site-specific integrations and stable gene expression in plant cells could be obtained with altered gene orders. Therefore, gene orientation and integration structures are more important factors governing gene expression than gene orders in the genomic context.

  8. Mindfulness-Based Stress Reduction training reduces loneliness and pro-inflammatory gene expression in older adults: a small randomized controlled trial.

    Science.gov (United States)

    Creswell, J David; Irwin, Michael R; Burklund, Lisa J; Lieberman, Matthew D; Arevalo, Jesusa M G; Ma, Jeffrey; Breen, Elizabeth Crabb; Cole, Steven W

    2012-10-01

    Lonely older adults have increased expression of pro-inflammatory genes as well as increased risk for morbidity and mortality. Previous behavioral treatments have attempted to reduce loneliness and its concomitant health risks, but have had limited success. The present study tested whether the 8-week Mindfulness-Based Stress Reduction (MBSR) program (compared to a Wait-List control group) reduces loneliness and downregulates loneliness-related pro-inflammatory gene expression in older adults (N = 40). Consistent with study predictions, mixed effect linear models indicated that the MBSR program reduced loneliness, compared to small increases in loneliness in the control group (treatment condition × time interaction: F(1,35) = 7.86, p = .008). Moreover, at baseline, there was an association between reported loneliness and upregulated pro-inflammatory NF-κB-related gene expression in circulating leukocytes, and MBSR downregulated this NF-κB-associated gene expression profile at post-treatment. Finally, there was a trend for MBSR to reduce C Reactive Protein (treatment condition × time interaction: (F(1,33) = 3.39, p = .075). This work provides an initial indication that MBSR may be a novel treatment approach for reducing loneliness and related pro-inflammatory gene expression in older adults. Copyright © 2012 Elsevier Inc. All rights reserved.

  9. Analysis of baseline and cisplatin-inducible gene expression in Fanconi anemia cells using oligonucleotide-based microarrays

    Directory of Open Access Journals (Sweden)

    Liu Johnson M

    2002-11-01

    Full Text Available Abstract Background Patients with Fanconi anemia (FA suffer from multiple defects, most notably of the hematological compartment (bone marrow failure, and susceptibility to cancer. Cells from FA patients show increased spontaneous chromosomal damage, which is aggravated by exposure to low concentrations of DNA cross-linking agents such as mitomycin C or cisplatin. Five of the identified FA proteins form a nuclear core complex. However, the molecular function of these proteins remains obscure. Methods Oligonucleotide microarrays were used to compare the expression of approximately 12,000 genes from FA cells with matched controls. Expression profiles were studied in lymphoblastoid cell lines derived from three different FA patients, one from the FA-A and two from the FA-C complementation groups. The isogenic control cell lines were obtained by either transfecting the cells with vectors expressing the complementing cDNAs or by using a spontaneous revertant cell line derived from the same patient. In addition, we analyzed expression profiles from two cell line couples at several time points after a 1-hour pulse treatment with a discriminating dose of cisplatin. Results Analysis of the expression profiles showed differences in expression of a number of genes, many of which have unknown function or are difficult to relate to the FA defect. However, from a selected number of proteins involved in cell cycle regulation, DNA repair and chromatin structure, Western blot analysis showed that p21waf1/Cip1 was significantly upregulated after low dose cisplatin treatment in FA cells specifically (as well as being expressed at elevated levels in untreated FA cells. Conclusions The observed increase in expression of p21waf1/Cip1 after treatment of FA cells with crosslinkers suggests that the sustained elevated levels of p21waf1/Cip1 in untreated FA cells detected by Western blot analysis likely reflect increased spontaneous damage in these cells.

  10. Aberrant Gene Expression in Acute Myeloid Leukaemia

    DEFF Research Database (Denmark)

    Bagger, Frederik Otzen

    genes and genetic signatures and for reducing dimensionally of gene expression data. Next, we have used machine-learning methods to predict survival and to assess important predictors based on these results. General application of a number of these methods has been implemented into two public query......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...

  11. Differential Gene Expression during Larval Metamorphic Development in the Pearl Oyster, Pinctada fucata, Based on Transcriptome Analysis

    Directory of Open Access Journals (Sweden)

    Haimei Li

    2016-01-01

    Full Text Available P. fucata experiences a series of transformations in appearance, from swimming larvae to sessile juveniles, during which significant changes in gene expression likely occur. Thus, P. fucata could be an ideal model in which to study the molecular mechanisms of larval metamorphosis during development in invertebrates. To study the molecular driving force behind metamorphic development in larvae of P. fucata, transcriptomes of five larval stages (trochophore, D-shape, umbonal, eyespots, and spats were sequenced using an Illumina HiSeq™ 2000 system and assembled and characterized with the transcripts of six tissues. As a result, a total of 174,126 unique transcripts were assembled and 60,999 were annotated. The number of unigenes varied among the five larval stages. Expression profiles were distinctly different between trochophore, D-shape, umbonal, eyespots, and spats larvae. As a result, 29 expression trends were sorted, of which eight were significant. Among others, 80 development-related, differentially expressed unigenes (DEGs were identified, of which the majority were homeobox-containing genes. Most DEGs occurred among trochophore, D-shaped, and UES (umbonal, eyespots, and spats larvae as verified by qPCR. Principal component analysis (PCA also revealed significant differences in expression among trochophore, D-shaped, and UES larvae with ten transcripts identified but no matching annotations.

  12. Gene expression during normal and FSHD myogenesis

    Directory of Open Access Journals (Sweden)

    Sowden Janet

    2011-09-01

    Full Text Available Abstract Background Facioscapulohumeral muscular dystrophy (FSHD is a dominant disease linked to contraction of an array of tandem 3.3-kb repeats (D4Z4 at 4q35. Within each repeat unit is a gene, DUX4, that can encode a protein containing two homeodomains. A DUX4 transcript derived from the last repeat unit in a contracted array is associated with pathogenesis but it is unclear how. Methods Using exon-based microarrays, the expression profiles of myogenic precursor cells were determined. Both undifferentiated myoblasts and myoblasts differentiated to myotubes derived from FSHD patients and controls were studied after immunocytochemical verification of the quality of the cultures. To further our understanding of FSHD and normal myogenesis, the expression profiles obtained were compared to those of 19 non-muscle cell types analyzed by identical methods. Results Many of the ~17,000 examined genes were differentially expressed (> 2-fold, p DUX4 RNA isoform was detected by RT-PCR in FSHD myoblast and myotube preparations only at extremely low levels. Unique insights into myogenesis-specific gene expression were also obtained. For example, all four Argonaute genes involved in RNA-silencing were significantly upregulated during normal (but not FSHD myogenesis relative to non-muscle cell types. Conclusions DUX4's pathogenic effect in FSHD may occur transiently at or before the stage of myoblast formation to establish a cascade of gene dysregulation. This contrasts with the current emphasis on toxic effects of experimentally upregulated DUX4 expression at the myoblast or myotube stages. Our model could explain why DUX4's inappropriate expression was barely detectable in myoblasts and myotubes but nonetheless linked to FSHD.

  13. Network-based integration of GWAS and gene expression identifies a HOX-centric network associated with serous ovarian cancer risk

    Science.gov (United States)

    Kar, Siddhartha P.; Tyrer, Jonathan P.; Li, Qiyuan; Lawrenson, Kate; Aben, Katja K.H.; Anton-Culver, Hoda; Antonenkova, Natalia; Chenevix-Trench, Georgia; Baker, Helen; Bandera, Elisa V.; Bean, Yukie T.; Beckmann, Matthias W.; Berchuck, Andrew; Bisogna, Maria; Bjørge, Line; Bogdanova, Natalia; Brinton, Louise; Brooks-Wilson, Angela; Butzow, Ralf; Campbell, Ian; Carty, Karen; Chang-Claude, Jenny; Chen, Yian Ann; Chen, Zhihua; Cook, Linda S.; Cramer, Daniel; Cunningham, Julie M.; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A.; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas F.; Edwards, Robert P.; Ekici, Arif B.; Fasching, Peter A.; Fridley, Brooke L.; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G.; Glasspool, Rosalind; Goode, Ellen L.; Goodman, Marc T.; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A.T.; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus K.; Hosono, Satoyo; Iversen, Edwin S.; Jakubowska, Anna; Paul, James; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kjaer, Susanne K.; Kelemen, Linda E.; Kellar, Melissa; Kelley, Joseph; Kiemeney, Lambertus A.; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D.; Lee, Alice W.; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A.; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R.; McNeish, Iain A.; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B.; Narod, Steven A.; Nedergaard, Lotte; Ness, Roberta B.; Nevanlinna, Heli; Odunsi, Kunle; Olson, Sara H.; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M.; Permuth-Wey, Jennifer; Phelan, Catherine M.; Pike, Malcolm C.; Poole, Elizabeth M.; Ramus, Susan J.; Risch, Harvey A.; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H.; Rudolph, Anja; Runnebaum, Ingo B.; Rzepecka, Iwona K.; Salvesen, Helga B.; Schildkraut, Joellen M.; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C.; Sucheston-Campbell, Lara E.; Tangen, Ingvild L.; Teo, Soo-Hwang; Terry, Kathryn L.; Thompson, Pamela J; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S.; van Altena, Anne M.; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A.; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S.; Wicklund, Kristine G.; Wilkens, Lynne R.; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A.; Monteiro, Alvaro N. A.; Freedman, Matthew L.; Gayther, Simon A.; Pharoah, Paul D. P.

    2015-01-01

    Background Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by co-expression may also be enriched for additional EOC risk associations. Methods We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly co-expressed with each selected TF gene in the unified microarray data set of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this data set were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Results Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P<0.05 and FDR<0.05). These results were replicated (P<0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. Conclusion We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Impact Network analysis integrating large, context-specific data sets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. PMID:26209509

  14. Cerebrovascular gene expression in spontaneously hypertensive rats

    DEFF Research Database (Denmark)

    Grell, Anne-Sofie; Frederiksen, Simona Denise; Edvinsson, Lars

    2017-01-01

    in the middle cerebral arteries from hypertensive compared to normotensive rats. The gene expression of 72 genes was decreased and the gene expression of 97 genes was increased. The following genes with a fold difference ≥1.40 were verified by quantitative PCR; Postn, Olr1, Fas, Vldlr, Mmp2, Timp1, Serpine1......, Mmp11, Cd34, Ptgs1 and Ptgs2. The gene expression of Postn, Olr1, Fas, Vldlr, Mmp2, Timp1 and Serpine1 and the protein expression of LOX1 (also known as OLR1) were significantly increased in the middle cerebral arteries from spontaneously hypertensive rats compared to Wistar-Kyoto rats. In conclusion...

  15. Alpha-plane based automatic general type-2 fuzzy clustering based on simulated annealing meta-heuristic algorithm for analyzing gene expression data.

    Science.gov (United States)

    Doostparast Torshizi, Abolfazl; Fazel Zarandi, Mohammad Hossein

    2015-09-01

    This paper considers microarray gene expression data clustering using a novel two stage meta-heuristic algorithm based on the concept of α-planes in general type-2 fuzzy sets. The main aim of this research is to present a powerful data clustering approach capable of dealing with highly uncertain environments. In this regard, first, a new objective function using α-planes for general type-2 fuzzy c-means clustering algorithm is represented. Then, based on the philosophy of the meta-heuristic optimization framework 'Simulated Annealing', a two stage optimization algorithm is proposed. The first stage of the proposed approach is devoted to the annealing process accompanied by its proposed perturbation mechanisms. After termination of the first stage, its output is inserted to the second stage where it is checked with other possible local optima through a heuristic algorithm. The output of this stage is then re-entered to the first stage until no better solution is obtained. The proposed approach has been evaluated using several synthesized datasets and three microarray gene expression datasets. Extensive experiments demonstrate the capabilities of the proposed approach compared with some of the state-of-the-art techniques in the literature. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Gene expression analysis of zebrafish heart regeneration.

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    Ching-Ling Lien

    2006-08-01

    Full Text Available Mammalian hearts cannot regenerate. In contrast, zebrafish hearts regenerate even when up to 20% of the ventricle is amputated. The mechanism of zebrafish heart regeneration is not understood. To systematically characterize this process at the molecular level, we generated transcriptional profiles of zebrafish cardiac regeneration by microarray analyses. Distinct gene clusters were identified based on temporal expression patterns. Genes coding for wound response/inflammatory factors, secreted molecules, and matrix metalloproteinases are expressed in regenerating heart in sequential patterns. Comparisons of gene expression profiles between heart and fin regeneration revealed a set of regeneration core molecules as well as tissue-specific factors. The expression patterns of several secreted molecules around the wound suggest that they play important roles in heart regeneration. We found that both platelet-derived growth factor-a and -b (pdgf-a and pdgf-b are upregulated in regenerating zebrafish hearts. PDGF-B homodimers induce DNA synthesis in adult zebrafish cardiomyocytes. In addition, we demonstrate that a chemical inhibitor of PDGF receptor decreases DNA synthesis of cardiomyocytes both in vitro and in vivo during regeneration. Our data indicate that zebrafish heart regeneration is associated with sequentially upregulated wound healing genes and growth factors and suggest that PDGF signaling is required.

  17. Gene and enhancer trap tagging of vascular-expressed genes in poplar trees

    Science.gov (United States)

    Andrew Groover; Joseph R. Fontana; Gayle Dupper; Caiping Ma; Robert Martienssen; Steven Strauss; Richard Meilan

    2004-01-01

    We report a gene discovery system for poplar trees based on gene and enhancer traps. Gene and enhancer trap vectors carrying the β-glucuronidase (GUS) reporter gene were inserted into the poplar genome via Agrobacterium tumefaciens transformation, where they reveal the expression pattern of genes at or near the insertion sites. Because GUS...

  18. [A classification method of gene expression profile based on a locally linear embedding algorism with improved distance].

    Science.gov (United States)

    Cai, Xianfa; Wei, Jia; Wen, Guihua; Li, Jie

    2011-12-01

    With its high dimensionalities, small samples and great noise, feature reduction of gene expression profile becomes quite necessary. The most common form of gene expression profile is nonlinear, and traditional dimensionality reduction methods can not project high dimensional data, whose initial dimensionalities are low, into low dimensional space. In this work, an improved distance locally linear embedding (LLE ) algorism was proposed to reduce the dimensionalities. LLE method is very sensitive to the closely-neighboring parameters. In order to enhance the robustness to the number of neighbors, in the paper we presented a novel distance to measure the distance between the samples for the purpose of reducing-the influence of distribution of samples. Experimental results demonstrated that the improved distance LLE can effectively extract information of classification features and greatly reduce the dimensionalities of data while maintaining a higher classification accuracy.

  19. Adaptive Evolution of Gene Expression in Drosophila

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    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.

  20. Gene expression patterns regulating embryogenesis based on the integrated de novo transcriptome assembly of the Japanese flounder.

    Science.gov (United States)

    Fu, Yuanshuai; Jia, Liang; Shi, Zhiyi; Zhang, Junling; Li, Wenjuan

    2017-06-01

    The Japanese flounder (Paralichthys olivaceus) is one of the most important commercial and biological marine fishes. However, the molecular biology involved during embryogenesis and early development of the Japanese flounder remains largely unknown due to a lack of genomic resources. A comprehensive and integrated transcriptome is necessary to study the molecular mechanisms of early development and to allow for the detailed characterization of gene expression patterns during embryogenesis; this approach is critical to understanding the processes that occur prior to mesectoderm formation during early embryonic development. In this study, more than 117.8 million 100bp PE reads were generated from pooled RNA extracted from unfertilized eggs to 41dph (days post-hatching) embryos and were sequenced using Illumina pair-end sequencing technology. In total, 121,513 transcripts (≥200bp) were obtained using de novo assembly. A sequence similarity search indicated that 52,338 transcripts show significant similarity to 22,462 known proteins from the NCBI non-redundant database and the Swiss-Prot protein database and were annotated using Blast2GO. GO terms were assigned to 44,627 transcripts with 12,006 functional terms, and 10,024 transcripts were assigned to 133 KEGG pathways. Furthermore, gene expression differences between the unfertilized egg and the gastrula embryo were analysed using Illumina RNA-Seq with single-read sequencing technology, and 24,837 differentially and specifically expressed transcripts were identified and included 5,286 annotated transcripts and 19,569 non-annotated transcripts. All of the expressed transcripts in the unfertilized egg and gastrula embryo were further classified as maternal, zygotic, or maternal-zygotic transcripts, which may help us to understand the roles of these transcripts during the embryonic development of the Japanese flounder. Thus, the results will contribute to an improved understanding of the gene expression patterns and

  1. 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.

  2. Comparative Analysis of Predicted Gene Expression among Crenarchaeal Genomes

    Directory of Open Access Journals (Sweden)

    Shibsankar Das

    2017-03-01

    Full Text Available Research into new methods for identifying highly expressed genes in anonymous genome sequences has been going on for more than 15 years. We presented here an alternative approach based on modified score of relative codon usage bias to identify highly expressed genes in crenarchaeal genomes. The proposed algorithm relies exclusively on sequence features for identifying the highly expressed genes. In this study, a comparative analysis of predicted highly expressed genes in five crenarchaeal genomes was performed using the score of Modified Relative Codon Bias Strength (MRCBS as a numerical estimator of gene expression level. We found a systematic strong correlation between Codon Adaptation Index and MRCBS. Additionally, MRCBS correlated well with other expression measures. Our study indicates that MRCBS can consistently capture the highly expressed genes.

  3. Development and Validation of a Gene-Based Model for Outcome Prediction in Germ Cell Tumors Using a Combined Genomic and Expression Profiling Approach.

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    James E Korkola

    Full Text Available Germ Cell Tumors (GCT have a high cure rate, but we currently lack the ability to accurately identify the small subset of patients who will die from their disease. We used a combined genomic and expression profiling approach to identify genomic regions and underlying genes that are predictive of outcome in GCT patients. We performed array-based comparative genomic hybridization (CGH on 53 non-seminomatous GCTs (NSGCTs treated with cisplatin based chemotherapy and defined altered genomic regions using Circular Binary Segmentation. We identified 14 regions associated with two year disease-free survival (2yDFS and 16 regions associated with five year disease-specific survival (5yDSS. From corresponding expression data, we identified 101 probe sets that showed significant changes in expression. We built several models based on these differentially expressed genes, then tested them in an independent validation set of 54 NSGCTs. These predictive models correctly classified outcome in 64-79.6% of patients in the validation set, depending on the endpoint utilized. Survival analysis demonstrated a significant separation of patients with good versus poor predicted outcome when using a combined gene set model. Multivariate analysis using clinical risk classification with the combined gene model indicated that they were independent prognostic markers. This novel set of predictive genes from altered genomic regions is almost entirely independent of our previously identified set of predictive genes for patients with NSGCTs. These genes may aid in the identification of the small subset of patients who are at high risk of poor outcome.

  4. Expression of Human Immunodeficiency Virus type 1 (HIV-1) coat protein genes in plants using cotton leaf curl Multan betasatellite-based vector

    Science.gov (United States)

    Ataie Kachoie, Elham; Kharazmi, Sara

    2018-01-01

    It has already been demonstrated that a betasatellite associated with cotton leaf curl Multan virus (CLCuMB) can be used as a plant and animal gene delivery vector to plants. To examine the ability of CLCuMB as a tool to transfer coat protein genes of HIV-1 to plants, two recombinant CLCuMB constructs in which the CLCuMB βC1 ORF was replaced with two HIV-1 genes fractions including a 696 bp DNA fragment related to the HIV-1 p24 gene and a 1501 bp DNA fragment related to the HIV-1 gag gene were constructed. Gag is the HIV-1 coat protein gene and p24 is a component of the particle capsid. Gag and p24 are used for vaccine production. Recombinant constructs were inoculated to Nicotiana glutinosa and N. benthamiana plants in the presence of an Iranian isolate of Tomato yellow leaf curl virus (TYLCV-[Ab]) as a helper virus. PCR analysis of inoculated plants indicated that p24 gene was successfully replicated in inoculated plants, but the gag gene was not. Real-time PCR and ELISA analysis of N. glutinosa and N. benthamiana plants containing the replicative forms of recombinant construct of CLCuMB/p24 indicated that p24 was expressed in these plants. This CLCuMB-based expression system offers the possibility of mass production of recombinant HIV-1 p24 protein in plants. PMID:29304063

  5. Nonlinear dimensionality reduction of gene expression data

    OpenAIRE

    Nilsson, Jens

    2006-01-01

    Using microarray measurements techniques, it is possible to measure the activity of genes simultaneously across the whole genome. Since genes influence each others activity levels through complex regulatory networks, such gene expression measurements are state samples of a dynamical system. Gene expression data has proven useful for diagnosis and definition of disease subgroups, for inference of the functional role of a given gene or for the deciphering of complex disease mechanisms. However,...

  6. Molecular Characterization of Heterologous HIV-1gp120 Gene Expression Disruption in Mycobacterium bovis BCG Host Strain: A Critical Issue for Engineering Mycobacterial Based-Vaccine Vectors

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    Joan Joseph

    2010-01-01

    Full Text Available Mycobacterium bovis Bacillus Calmette-Guérin (BCG as a live vector of recombinant bacterial vaccine is a promising system to be used. In this study, we evaluate the disrupted expression of heterologous HIV-1gp120 gene in BCG Pasteur host strain using replicative vectors pMV261 and pJH222. pJH222 carries a lysine complementing gene in BCG lysine auxotrophs. The HIV-1 gp120 gene expression was regulated by BCG hsp60 promoter (in plasmid pMV261 and Mycobacteria spp. α-antigen promoter (in plasmid pJH222. Among 14 rBCG:HIV-1gp120 (pMV261 colonies screened, 12 showed a partial deletion and two showed a complete deletion. However, deletion was not observed in all 10 rBCG:HIV-1gp120 (pJH222 colonies screened. In this study, we demonstrated that E. coli/Mycobacterial expression vectors bearing a weak promoter and lysine complementing gene in a recombinant lysine auxotroph of BCG could prevent genetic rearrangements and disruption of HIV 1gp120 gene expression, a key issue for engineering Mycobacterial based vaccine vectors.

  7. A combined blood based gene expression and plasma protein abundance signature for diagnosis of epithelial ovarian cancer - a study of the OVCAD consortium

    International Nuclear Information System (INIS)

    Pils, Dietmar; Sehouli, Jalid; Braicu, Ioana; Vergote, Ignace; Van Gorp, Toon; Mahner, Sven; Concin, Nicole; Speiser, Paul; Zeillinger, Robert; Tong, Dan; Hager, Gudrun; Obermayr, Eva; Aust, Stefanie; Heinze, Georg; Kohl, Maria; Schuster, Eva; Wolf, Andrea

    2013-01-01

    The immune system is a key player in fighting cancer. Thus, we sought to identify a molecular ‘immune response signature’ indicating the presence of epithelial ovarian cancer (EOC) and to combine this with a serum protein biomarker panel to increase the specificity and sensitivity for earlier detection of EOC. Comparing the expression of 32,000 genes in a leukocytes fraction from 44 EOC patients and 19 controls, three uncorrelated shrunken centroid models were selected, comprised of 7, 14, and 6 genes. A second selection step using RT-qPCR data and significance analysis of microarrays yielded 13 genes (AP2A1, B4GALT1, C1orf63, CCR2, CFP, DIS3, NEAT1, NOXA1, OSM, PAPOLG, PRIC285, ZNF419, and BC037918) which were finally used in 343 samples (90 healthy, six cystadenoma, eight low malignant potential tumor, 19 FIGO I/II, and 220 FIGO III/IV EOC patients). Using new 65 controls and 224 EOC patients (thereof 14 FIGO I/II) the abundances of six plasma proteins (MIF, prolactin, CA125, leptin, osteopondin, and IGF2) was determined and used in combination with the expression values from the 13 genes for diagnosis of EOC. Combined diagnostic models using either each five gene expression and plasma protein abundance values or 13 gene expression and six plasma protein abundance values can discriminate controls from patients with EOC with Receiver Operator Characteristics Area Under the Curve values of 0.998 and bootstrap .632+ validated classification errors of 3.1% and 2.8%, respectively. The sensitivities were 97.8% and 95.6%, respectively, at a set specificity of 99.6%. The combination of gene expression and plasma protein based blood derived biomarkers in one diagnostic model increases the sensitivity and the specificity significantly. Such a diagnostic test may allow earlier diagnosis of epithelial ovarian cancer

  8. Identification of common biological pathways and drug targets across multiple respiratory viruses based on human host gene expression analysis.

    Directory of Open Access Journals (Sweden)

    Steven B Smith

    Full Text Available Pandemic and seasonal respiratory viruses are a major global health concern. Given the genetic diversity of respiratory viruses and the emergence of drug resistant strains, the targeted disruption of human host-virus interactions is a potential therapeutic strategy for treating multi-viral infections. The availability of large-scale genomic datasets focused on host-pathogen interactions can be used to discover novel drug targets as well as potential opportunities for drug repositioning.In this study, we performed a large-scale analysis of microarray datasets involving host response to infections by influenza A virus, respiratory syncytial virus, rhinovirus, SARS-coronavirus, metapneumonia virus, coxsackievirus and cytomegalovirus. Common genes and pathways were found through a rigorous, iterative analysis pipeline where relevant host mRNA expression datasets were identified, analyzed for quality and gene differential expression, then mapped to pathways for enrichment analysis. Possible repurposed drugs targets were found through database and literature searches. A total of 67 common biological pathways were identified among the seven different respiratory viruses analyzed, representing fifteen laboratories, nine different cell types, and seven different array platforms. A large overlap in the general immune response was observed among the top twenty of these 67 pathways, adding validation to our analysis strategy. Of the top five pathways, we found 53 differentially expressed genes affected by at least five of the seven viruses. We suggest five new therapeutic indications for existing small molecules or biological agents targeting proteins encoded by the genes F3, IL1B, TNF, CASP1 and MMP9. Pathway enrichment analysis also identified a potential novel host response, the Parkin-Ubiquitin Proteasomal System (Parkin-UPS pathway, which is known to be involved in the progression of neurodegenerative Parkinson's disease.Our study suggests that

  9. BCDForest: a boosting cascade deep forest model towards the classification of cancer subtypes based on gene expression data.

    Science.gov (United States)

    Guo, Yang; Liu, Shuhui; Li, Zhanhuai; Shang, Xuequn

    2018-04-11

    The classification of cancer subtypes is of great importance to cancer disease diagnosis and therapy. Many supervised learning approaches have been applied to cancer subtype classification in the past few years, especially of deep learning based approaches. Recently, the deep forest model has been proposed as an alternative of deep neural networks to learn hyper-representations by using cascade ensemble decision trees. It has been proved that the deep forest model has competitive or even better performance than deep neural networks in some extent. However, the standard deep forest model may face overfitting and ensemble diversity challenges when dealing with small sample size and high-dimensional biology data. In this paper, we propose a deep learning model, so-called BCDForest, to address cancer subtype classification on small-scale biology datasets, which can be viewed as a modification of the standard deep forest model. The BCDForest distinguishes from the standard deep forest model with the following two main contributions: First, a named multi-class-grained scanning method is proposed to train multiple binary classifiers to encourage diversity of ensemble. Meanwhile, the fitting quality of each classifier is considered in representation learning. Second, we propose a boosting strategy to emphasize more important features in cascade forests, thus to propagate the benefits of discriminative features among cascade layers to improve the classification performance. Systematic comparison experiments on both microarray and RNA-Seq gene expression datasets demonstrate that our method consistently outperforms the state-of-the-art methods in application of cancer subtype classification. The multi-class-grained scanning and boosting strategy in our model provide an effective solution to ease the overfitting challenge and improve the robustness of deep forest model working on small-scale data. Our model provides a useful approach to the classification of cancer subtypes

  10. Immunogenicity of Semliki Forest virus based self-amplifying RNA expressing Indian HIV-1C genes in mice.

    Science.gov (United States)

    Ajbani, Seema P; Velhal, Shilpa M; Kadam, Ravindra B; Patel, Vainav V; Bandivdekar, Atmaram H

    2015-11-01

    Development of recombinant vaccines is considered as a promising approach to prevent transmission and eradication of HIV/AIDS. Candidate vaccines tested so far have shown poor to modest efficacy. Self-amplifying RNAs of positive strand alphaviruses are reported to be promising vectors for development of recombinant vaccines. This study describes the construction, in vitro expression and in vivo immunogenicity of recombinant RNA vaccines developed by individually cloning gag, env and polRT genes of primary HIV-1C Indian isolates using Semliki Forest virus (SFV) vector. HIV-1C specific T cell responses were detected in mice immunized with rSFV2gen/gag RNA by IFN-γ ELISPOT assay. Furthermore, using flow cytometry based intracellular cytokine staining (ICCS) assay HIV-1C specific IL-2 responses were detected in immunized mice that were mediated by both CD4(+) and CD8(+) T cells. Mice immunized with rSFV2gen/env RNA elicited HIV-1C Env-specific antibodies as detected by gp120 ELISA. The Env, Gag and Pol (RT) RNA constructs in combination elicited better HIV-1C Env-specific humoral responses compared to mice immunized with Env RNA alone. In conclusion, rSFV2gen RNA constructs encoding HIV-1C antigens elicited clear cell mediated and humoral immune responses in mice, thus demonstrating the potential of self-amplifying rSFV2gen RNA as a promising candidate for anti-HIV vaccine development. Copyright © 2015 Elsevier B.V. All rights reserved.

  11. Predicting gene expression from sequence: a reexamination.

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    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%.

  12. Signature Evaluation Tool (SET: a Java-based tool to evaluate and visualize the sample discrimination abilities of gene expression signatures

    Directory of Open Access Journals (Sweden)

    Lin Chi-Hung

    2008-01-01

    Full Text Available Abstract Background The identification of specific gene expression signature for distinguishing sample groups is a dominant field in cancer research. Although a number of tools have been developed to identify optimal gene expression signatures, the number of signature genes obtained is often overly large to be applied clinically. Furthermore, experimental verification is sometimes limited by the availability of wet-lab materials such as antibodies and reagents. A tool to evaluate the discrimination power of candidate genes is therefore in high demand by clinical researchers. Results Signature Evaluation Tool (SET is a Java-based tool adopting the Golub's weighted voting algorithm as well as incorporating the visual presentation of prediction strength for each array sample. SET provides a flexible and easy-to-follow platform to evaluate the discrimination power of a gene signature. Here, we demonstrated the application of SET for several purposes: (1 for signatures consisting of a large number of genes, SET offers the ability to rapidly narrow down the number of genes; (2 for a given signature (from third party analyses or user-defined, SET can re-evaluate and re-adjust its discrimination power by selecting/de-selecting genes repeatedly; (3 for multiple microarray datasets, SET can evaluate the classification capability of a signature among datasets; and (4 by providing a module to visualize the prediction strength for each sample, SET allows users to re-evaluate the discrimination power on mis-grouped or less-certain samples. Information obtained from the above applications could be useful in prognostic analyses or clinical management decisions. Conclusion Here we present SET to evaluate and visualize the sample-discrimination ability of a given gene expression signature. This tool provides a filtration function for signature identification and lies between clinical analyses and class prediction (or feature selection tools. The simplicity

  13. Nonfluorescent denaturing HPLC-based primer-extension method for allele-specific expression: application to analysis of mismatch repair genes.

    Science.gov (United States)

    Aceto, Gitana M; De Lellis, Laura; Catalano, Teresa; Veschi, Serena; Radice, Paolo; Di Iorio, Angelo; Mariani-Costantini, Renato; Cama, Alessandro; Curia, Maria Cristina

    2009-09-01

    Altered germline expression of genes may represent a powerful marker of genetic or epigenetic predisposition to cancer or other diseases. We developed and validated a method of nonfluorescent primer extension that uses a single dideoxynucleotide and denaturing HPLC (DHPLC) to analyze the relative allele expression. We devised 5 independent assays for measuring allele-specific expression (ASE) to exploit different markers of mismatch repair genes MLH1 [mutL homolog 1, colon cancer, nonpolyposis type 2 (E. coli)] and MSH2 [mutS homolog 2, colon cancer, nonpolyposis type 1 (E. coli)]. We initially confirmed method reproducibility with genomic DNA (gDNA) from individuals heterozygous for a frequent single-nucleotide polymorphism in the MLH1 gene. After this preliminary validation with gDNA, we confirmed assay reproducibility with cDNA templates from control individuals. Relative allele expression was estimated by comparing the heights of the peaks corresponding to the 2 alleles. Results obtained with gDNA templates were used to normalize cDNA results. With these DHPLC-based primer-extension assays, we detected and confirmed a 5-fold imbalance in MLH1 allele expression in a mutation-negative patient with hereditary nonpolyposis colorectal cancer and in another patient with a modest degree of imbalance in MLH1 expression. Among control individuals, the relative expression of MLH1 alleles displayed a narrow range of variation. Independent DHPLC-based primer-extension assays for measuring and confirming ASE can be developed for different sequence variants of interest. This DHPLC application provides a cost-effective method for detecting ASE in cases for which conventional screening fails to detect pathogenic mutations in candidate genes and may be applicable for confirming ASE revealed by other methods, such as those used for transcriptome-wide analyses. .

  14. Gene expression profiling of laterally spreading tumors.

    Science.gov (United States)

    Minemura, Shoko; Tanaka, Takeshi; Arai, Makoto; Okimoto, Kenichiro; Oyamada, Arata; Saito, Keiko; Maruoka, Daisuke; Matsumura, Tomoaki; Nakagawa, Tomoo; Katsuno, Tatsuro; Kishimoto, Takashi; Yokosuka, Osamu

    2015-06-06

    Laterally spreading tumors (LSTs) are generally defined as lesions >10 mm in diameter, are characterized by lateral expansion along the luminal wall with a low vertical axis. In contrast to other forms of tumor, LSTs are generally considered to have a superficial growth pattern and the potential for malignancy. We focused on this morphological character of LSTs, and analyzed the gene expression profile of LSTs. The expression of 168 genes in 41 colorectal tumor samples (17 LST-adenoma, 12 LST-carcinoma, 12 Ip [pedunculated type of the Paris classification)-adenoma, all of which were 10 mm or more in diameter] was analyzed by PCR array. Based on the results, we investigated the expression levels of genes up-regulated in LST-adenoma, compared to Ip-adenoma, by hierarchical and K-means clustering. To confirm the results of the array analysis, using an additional 60 samples (38 LST-adenoma, 22 Ip-adenoma), we determined the localization of the gene product by immunohistochemical staining. The expression of 129 genes differed in colorectal tumors from normal mucosa by PCR array analysis. As a result of K-means clustering, the expression levels of five genes, AKT1, BCL2L1, ERBB2, MTA2 and TNFRSF25, were found to be significantly up-regulated (p < 0.05) in LST-adenoma, compared to Ip-adenoma. Immunohistochemical analysis showed that the BCL2L1 protein was significantly and meaningfully up-regulated in LST-adenoma compared to Ip-adenoma (p = 0.010). With respect to apoptosis status in LST-Adenoma, it assumes that BCL2L1 is anti-apoptotic protein, the samples such as BCL2L1 positive and TUNEL negative, or BCL2L1 negative and TUNEL positive are consistent with the assumption. 63.2 % LST-adenoma samples were consistent with the assumption. LSTs have an unusual profile of gene expression compared to other tumors and BCL2L1 might be concerned in the organization of LSTs.

  15. Effects of high-sulphur water on hepatic gene expression of steers fed fibre-based diets.

    Science.gov (United States)

    Kessler, K L; Olson, K C; Wright, C L; Austin, K J; McInnerney, K; Johnson, P S; Cockrum, R R; Jons, A M; Cammack, K M

    2013-10-01

    Sulphur-induced polioencephalomalacia (sPEM), a neurological disorder affecting ruminants, is frequently associated with the consumption of high-sulphur (S) water and subsequent poor performance. Currently, there is no economical method for S removal from surface water sources, and alternative water sources are typically neither readily available nor cost-effective. Determination of genes differentially expressed in response to high-S water consumption may provide a better understanding of the physiology corresponding to high dietary S and ultimately lead to the development of treatment and prevention strategies. The objective of this study was to determine changes in gene expression in the liver, an organ important for S metabolism, of fibre-fed steers consuming high-S water. For this study, liver tissues were collected on the final day of a trial from yearling steers randomly assigned to low-S water control (566 mg/kg SO4 ; n = 24), high-S water (3651 mg/kg SO4 ; n = 24) or high-S water plus clinoptilolite supplemented at either 2.5% (n = 24) or 5.0% (n = 24) of diet dry matter (DM). Microarray analyses on randomly selected healthy low-S control (n = 4) and high-S (n = 4; no clinoptilolite) steers using the Affymetrix GeneChip Bovine Genome Array revealed 488 genes upregulated (p consumption. Real-time RT-PCR confirmed the upregulation (p < 0.10) of seven genes involved in inflammatory response and immune functions. Changes in such genes suggest that ruminant animals administered high-S water may be undergoing an inflammation or immune response, even if signs of sPEM or compromised health are not readily observed. Further study of these, and other affected genes, may deliver new insights into the physiology underlying the response to high dietary S, ultimately leading to the development of treatments for high S-affected ruminant livestock. © 2012 Blackwell Verlag GmbH.

  16. Microarray-based identification of differentially expressed genes in intracellular Brucella abortus within RAW264.7 cells.

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    Mingxing Tian

    Full Text Available Brucella spp. is a species of facultative intracellular Gram-negative bacteria that induces abortion and causes sterility in domesticated mammals and chronic undulant fever in humans. Important determinants of Brucella's virulence and potential for chronic infection include the ability to circumvent the host cell's internal surveillance system and the capability to proliferate within dedicated and non-dedicated phagocytes. Hence, identifying genes necessary for intracellular survival may hold the key to understanding Brucella infection. In the present study, microarray analysis reveals that 7.82% (244/3334 of all Brucella abortus genes were up-regulated and 5.4% (180/3334 were down-regulated in RAW264.7 cells, compared to free-living cells in TSB. qRT-PCR verification further confirmed a >5-fold up-regulation for fourteen genes. Functional analysis classified araC, ddp, and eryD as to partake in information storage and processing, alp, flgF and virB9 to be involved in cellular processes, hpcd and aldh to play a role in metabolism, mfs and nikC to be involved in both cellular processes and metabolism, and four hypothetical genes (bruAb1_1814, bruAb1_0475, bruAb1_1926, and bruAb1_0292 had unknown functions. Furthermore, we constructed a B. abortus 2308 mutant Δddp where the ddp gene is deleted in order to evaluate the role of ddp in intracellular survival. Infection assay indicated significantly higher adherence and invasion abilities of the Δddp mutant, however it does not survive well in RAW264.7 cells. Brucella may survive in hostile intracellular environment by modulating gene expression.

  17. Evaluation of the hormonal state of columnar apple trees (Malus x domestica) based on high throughput gene expression studies.

    Science.gov (United States)

    Krost, Clemens; Petersen, Romina; Lokan, Stefanie; Brauksiepe, Bastienne; Braun, Peter; Schmidt, Erwin R

    2013-02-01

    The columnar phenotype of apple trees (Malus x domestica) is characterized by a compact growth habit with fruit spurs instead of lateral branches. These properties provide significant economic advantages by enabling high density plantings. The columnar growth results from the presence of a dominant allele of the gene Columnar (Co) located on chromosome 10 which can appear in a heterozygous (Co/co) or homozygous (Co/Co) state. Although two deep sequencing approaches could shed some light on the transcriptome of columnar shoot apical meristems (SAMs), the molecular mechanisms of columnar growth are not yet elaborated. Since the influence of phytohormones is believed to have a pivotal role in the establishment of the phenotype, we performed RNA-Seq experiments to study genes associated with hormone homeostasis and clearly affected by the presence of Co. Our results provide a molecular explanation for earlier findings on the hormonal state of columnar apple trees. Additionally, they allow hypotheses on how the columnar phenotype might develop. Furthermore, we show a statistically approved enrichment of differentially regulated genes on chromosome 10 in the course of validating RNA-Seq results using additional gene expression studies.

  18. Visualization and Comparison of Single and Combined Parametric and Nonparametric Discriminant Methods for Leukemia Type Recognition Based on Gene Expression

    Directory of Open Access Journals (Sweden)

    Ćwiklińska-Jurkowska Małgorzata M.

    2015-12-01

    Full Text Available A gene expression data set, containing 3051 genes and 38 tumor mRNA training samples, from a leukemia microarray study, was used for differentiation between ALL and AML groups of leukemia. In this paper, single and combined discriminant methods were applied on the basis of the selected few most discriminative variables according to Wilks’ lambda or the leave-one-out error of first nearest neighbor classifier. For the linear, quadratic, regularized, uncorrelated discrimination, kernel, nearest neighbor and naive Bayesian classifiers, two-dimensional graphs of the boundaries and discriminant functions for diagnostics are presented. Cross-validation and leave-one-out errors were used as measures of classifier performance to support diagnosis coming from this genomic data set. A small number of best discriminating genes, from two to ten, was sufficient to build discriminant methods of good performance. Especially useful were nearest neighbor methods. The results presented herein were comparable with outcomes obtained by other authors for larger numbers of applied genes. The linear, quadratic, uncorrelated Bayesian and regularized discrimination methods were subjected to bagging or boosting in order to assess the accuracy of the fusion. A conclusion drawn from the analysis was that resampling ensembles were not beneficial for two-dimensional discrimination.

  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

    weighted gene co-expression network analysis and a differential gene co-expression network analysis. The modules of genes revealed by these analyses were enriched for a number of functional terms summarised as muscle sarcomere organisation and development, protein catabolism (proteosome), RNA processing...... has potential, amongst other mechanisms, to alter gene expression via cis- or trans-acting mechanisms in a manner that impacts the functional activities of specific pathways that contribute to muscling traits. By integrating sire-based genetic merit information for a muscling trait with progeny......-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. Moving Toward Integrating Gene Expression Profiling into ...

    Science.gov (United States)

    Microarray profiling of chemical-induced effects is being increasingly used in medium and high-throughput formats. In this study, we describe computational methods to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally-diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through ChIP-Seq analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression data sets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including “very weak” agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals,

  1. Mining Association Rules among Gene Functions in Clusters of Similar Gene Expression Maps.

    Science.gov (United States)

    An, Li; Obradovic, Zoran; Smith, Desmond; Bodenreider, Olivier; Megalooikonomou, Vasileios

    2009-11-01

    Association rules mining methods have been recently applied to gene expression data analysis to reveal relationships between genes and different conditions and features. However, not much effort has focused on detecting the relation between gene expression maps and related gene functions. Here we describe such an approach to mine association rules among gene functions in clusters of similar gene expression maps on mouse brain. The experimental results show that the detected association rules make sense biologically. By inspecting the obtained clusters and the genes having the gene functions of frequent itemsets, interesting clues were discovered that provide valuable insight to biological scientists. Moreover, discovered association rules can be potentially used to predict gene functions based on similarity of gene expression maps.

  2. RNA-Seq-based analysis of the physiologic cold shock-induced changes in Moraxella catarrhalis gene expression.

    Directory of Open Access Journals (Sweden)

    Violeta Spaniol

    Full Text Available BACKGROUND: Moraxella catarrhalis, a major nasopharyngeal pathogen of the human respiratory tract, is exposed to rapid downshifts of environmental temperature when humans breathe cold air. The prevalence of pharyngeal colonization and respiratory tract infections caused by M. catarrhalis is greatest in winter. We investigated how M. catarrhalis uses the physiologic exposure to cold air to regulate pivotal survival systems that may contribute to M. catarrhalis virulence. RESULTS: In this study we used the RNA-seq techniques to quantitatively catalogue the transcriptome of M. catarrhalis exposed to a 26 °C cold shock or to continuous growth at 37 °C. Validation of RNA-seq data using quantitative RT-PCR analysis demonstrated the RNA-seq results to be highly reliable. We observed that a 26 °C cold shock induces the expression of genes that in other bacteria have been related to virulence a strong induction was observed for genes involved in high affinity phosphate transport and iron acquisition, indicating that M. catarrhalis makes a better use of both phosphate and iron resources after exposure to cold shock. We detected the induction of genes involved in nitrogen metabolism, as well as several outer membrane proteins, including ompA, m35-like porin and multidrug efflux pump (acrAB indicating that M. catarrhalis remodels its membrane components in response to downshift of temperature. Furthermore, we demonstrate that a 26 °C cold shock enhances the induction of genes encoding the type IV pili that are essential for natural transformation, and increases the genetic competence of M. catarrhalis, which may facilitate the rapid spread and acquisition of novel virulence-associated genes. CONCLUSION: Cold shock at a physiologically relevant temperature of 26 °C induces in M. catarrhalis a complex of adaptive mechanisms that could convey novel pathogenic functions and may contribute to enhanced colonization and virulence.

  3. 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...... be met by using promoter libraries. This approach generally consists of inserting a library of promoters in front of the gene to be studied, whereby the individual promoters might deviate either in their spacer sequences or bear slight deviations from the consensus sequence of a vegetative promoter. Here......, we describe the two different methods for obtaining promoter libraries and compare their applicability....

  4. MASISH: a database for gene expression in maize seeds.

    Science.gov (United States)

    Miquel, M; López-Ribera, I; Ràmia, M; Casillas, S; Barbadilla, A; Vicient, C M

    2011-02-01

    Grass seeds are complex organs composed by multiple tissues and cell types that develop coordinately to produce a viable embryo. The identification of genes involved in seed development is of great interest, but systematic spatial analyses of gene expression on maize seeds at the cell level have not yet been performed. MASISH is an online database holding information for gene expression spatial patterns in maize seeds based on in situ hybridization experiments. The web-based query interface allows the execution of gene queries and provides hybridization images, published references and information of the analyzed genes. http://masish.uab.cat/.

  5. Subdivisions of the turtle Pseudemys scripta subpallium based on the expression of regulatory genes and neuronal markers.

    Science.gov (United States)

    Moreno, Nerea; Morona, Ruth; López, Jesús M; González, Agustín

    2010-12-15

    The patterns of distribution of a set of conserved brain developmental regulatory transcription factors and neuronal markers were analyzed in the subpallium of the juvenile turtle, Pseudemys scripta. Immunohistochemical techniques were used with a combination of primary antibodies for the identification of the main boundaries and subdivisions in the basal telencephalon. In the basal ganglia, the combinatorial expression on Pax6, Nkx2.1, and GABA was a powerful tool for the identification of the nucleus accumbens, the dorsal portion of the striatum, and the pallidal regions. It was also possible to suggest migratory streams of neurons from the pallidum into the striatal regions. On the basis of GABA, Pax6, Tbr1, tyrosine hydroxylase, Darpp32, and Nkx2.1 combinatorial expression patterns, the boundaries of the septal subdivisions and their embryological origin were assessed. In particular, the bed nucleus of the stria terminalis was identified. Within the amygdaloid complex, the striatal central amygdala was characterized by Pax6 expression, whereas Orthopedia gene expression highlighted, at least, a subdivision of the medial amygdala. A newly identified preoptic commissural area and the boundaries of the preoptic area were assessed, mainly by the localization of Nkx2.1 expression. Finally, additional data were obtained by combining immunohistochemistry and tracing techniques on the interneuronal nature of the cholinerginergic, nitrergic, and Nkx2.1-positive striatal cells. Taken together, all the results of the present study allowed recognizing main features in the organization of the subpallium in reptiles that, in most cases, are shared with other amniotes and amphibians. © 2010 Wiley-Liss, Inc.

  6. 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

  7. 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

  8. Selection and validation of potato candidate genes for maturity corrected resistance to Phytophthora infestans based on differential expression combined with SNP association and linkage mapping

    Directory of Open Access Journals (Sweden)

    Meki Shehabu Muktar

    2015-09-01

    Full Text Available Late blight of potato (Solanum tuberosum L. caused by the oomycete Phytophthora infestans (Mont. de Bary, is one of the most important bottlenecks of potato production worldwide. Cultivars with high levels of durable, race unspecific, quantitative resistance are part of a solution to this problem. However, breeding for quantitative resistance is hampered by the correlation between resistance and late plant maturity, which is an undesirable agricultural attribute. The objectives of our research are (i the identification of genes that condition quantitative resistance to P. infestans not compromised by late plant maturity and (ii the discovery of diagnostic single nucleotide polymorphism (SNP markers to be used as molecular tools to increase efficiency and precision of resistance breeding. Twenty two novel candidate genes were selected based on comparative transcript profiling by SuperSAGE (serial analysis of gene expression in groups of plants with contrasting levels of maturity corrected resistance (MCR. Reproducibility of differential expression was tested by quantitative real time PCR and allele specific pyrosequencing in four new sets of genotype pools with contrasting late blight resistance levels, at three infection time points and in three independent infection experiments. Reproducibility of expression patterns ranged from 28% to 97%. Association mapping in a panel of 184 tetraploid cultivars identified SNPs in five candidate genes that were associated with MCR. These SNPs can be used in marker-assisted resistance breeding. Linkage mapping in two half-sib families (n = 111 identified SNPs in three candidate genes that were linked with MCR. The differentially expressed genes that showed association and/or linkage with MCR putatively function in phytosterol synthesis, fatty acid synthesis, asparagine synthesis, chlorophyll synthesis, cell wall modification and in the response to pathogen elicitors.

  9. The Malus domestica sugar transporter gene family: identifications based on genome and expression profiling related to the accumulation of fruit sugars

    Directory of Open Access Journals (Sweden)

    Xiaoyu eWei

    2014-11-01

    Full Text Available In plants, sugar transporters are involved not only in long-distance transport, but also in sugar accumulations in sink cells. To identify members of sugar transporter gene families and to analyze their function in fruit sugar accumulation, we conducted a phylogenetic analysis of the Malus domestica genome. Expression profiling was performed with shoot tips, mature leaves, and developed fruit of ‘Gala’ apple. Genes for sugar alcohol (including 17 sorbitol transporters, sucrose, and monosaccharide transporters, plus SWEET genes, were selected as candidates in 31, 9, 50, and 27 loci, respectively, of the genome. The monosaccharide transporter family appears to include five subfamilies (30 MdHTs, 8 MdEDR6s, 5 MdTMTs, 3 MdvGTs, and 4 MdpGLTs. Phylogenetic analysis of the protein sequences indicated that orthologs exist among Malus, Vitis, and Arabidopsis. Investigations of transcripts revealed that 68 candidate transporters are expressed in apple, albeit to different extents. Here, we discuss their possible roles based on the relationship between their levels of expression and sugar concentrations. The high accumulation of fructose in apple fruit is possibly linked to the coordination and cooperation between MdTMT1/2 and MdEDR6. By contrast, these fruits show low MdSWEET4.1 expression and a high flux of fructose produced from sorbitol. Our study provides an exhaustive survey of sugar transporter genes and demonstrates that sugar transporter gene families in M. domestica are comparable to those in other species. Expression profiling of these transporters will likely contribute to improving our understanding of their physiological functions in fruit formation and the development of sweetness properties.

  10. The Malus domestica sugar transporter gene family: identifications based on genome and expression profiling related to the accumulation of fruit sugars.

    Science.gov (United States)

    Wei, Xiaoyu; Liu, Fengli; Chen, Cheng; Ma, Fengwang; Li, Mingjun

    2014-01-01

    In plants, sugar transporters are involved not only in long-distance transport, but also in sugar accumulations in sink cells. To identify members of sugar transporter gene families and to analyze their function in fruit sugar accumulation, we conducted a phylogenetic analysis of the Malus domestica genome. Expression profiling was performed with shoot tips, mature leaves, and developed fruit of "Gala" apple. Genes for sugar alcohol [including 17 sorbitol transporters (SOTs)], sucrose, and monosaccharide transporters, plus SWEET genes, were selected as candidates in 31, 9, 50, and 27 loci, respectively, of the genome. The monosaccharide transporter family appears to include five subfamilies (30 MdHTs, 8 MdEDR6s, 5 MdTMTs, 3 MdvGTs, and 4 MdpGLTs). Phylogenetic analysis of the protein sequences indicated that orthologs exist among Malus, Vitis, and Arabidopsis. Investigations of transcripts revealed that 68 candidate transporters are expressed in apple, albeit to different extents. Here, we discuss their possible roles based on the relationship between their levels of expression and sugar concentrations. The high accumulation of fructose in apple fruit is possibly linked to the coordination and cooperation between MdTMT1/2 and MdEDR6. By contrast, these fruits show low MdSWEET4.1 expression and a high flux of fructose produced from sorbitol. Our study provides an exhaustive survey of sugar transporter genes and demonstrates that sugar transporter gene families in M. domestica are comparable to those in other species. Expression profiling of these transporters will likely contribute to improving our understanding of their physiological functions in fruit formation and the development of sweetness properties.

  11. Superinduction of estrogen receptor mediated gene expression in luciferase based reporter gene assays is mediated by a post-transcriptional mechanism

    NARCIS (Netherlands)

    Sotoca Covaleda, A.M.; Bovee, T.F.H.; Brand, W.; Velikova, N.R.; Murk, A.J.; Vervoort, J.J.M.; Rietjens, I.M.C.M.

    2010-01-01

    Several estrogenic compounds including the isoflavonoid genistein have been reported to induce a higher maximal response than the natural estrogen 17ß-estradiol in in vitro luciferase based reporter gene bioassays for testing estrogenicity. The phenomenon has been referred to as superinduction. The

  12. Blood Gene Expression Predicts Bronchiolitis Obliterans Syndrome

    Directory of Open Access Journals (Sweden)

    Richard Danger

    2018-01-01

    Full Text Available Bronchiolitis obliterans syndrome (BOS, the main manifestation of chronic lung allograft dysfunction, leads to poor long-term survival after lung transplantation. Identifying predictors of BOS is essential to prevent the progression of dysfunction before irreversible damage occurs. By using a large set of 107 samples from lung recipients, we performed microarray gene expression profiling of whole blood to identify early biomarkers of BOS, including samples from 49 patients with stable function for at least 3 years, 32 samples collected at least 6 months before BOS diagnosis (prediction group, and 26 samples at or after BOS diagnosis (diagnosis group. An independent set from 25 lung recipients was used for validation by quantitative PCR (13 stables, 11 in the prediction group, and 8 in the diagnosis group. We identified 50 transcripts differentially expressed between stable and BOS recipients. Three genes, namely POU class 2 associating factor 1 (POU2AF1, T-cell leukemia/lymphoma protein 1A (TCL1A, and B cell lymphocyte kinase, were validated as predictive biomarkers of BOS more than 6 months before diagnosis, with areas under the curve of 0.83, 0.77, and 0.78 respectively. These genes allow stratification based on BOS risk (log-rank test p < 0.01 and are not associated with time posttransplantation. This is the first published large-scale gene expression analysis of blood after lung transplantation. The three-gene blood signature could provide clinicians with new tools to improve follow-up and adapt treatment of patients likely to develop BOS.

  13. DNA microarray analysis of genes differentially expressed in ...

    Indian Academy of Sciences (India)

    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 ...

  14. 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.

  15. In search of functional association from time-series microarray data based on the change trend and level of gene expression

    Directory of Open Access Journals (Sweden)

    Zeng An-Ping

    2006-02-01

    Full Text Available Abstract Background The increasing availability of time-series expression data opens up new possibilities to study functional linkages of genes. Present methods used to infer functional linkages between genes from expression data are mainly based on a point-to-point comparison. Change trends between consecutive time points in time-series data have been so far not well explored. Results In this work we present a new method based on extracting main features of the change trend and level of gene expression between consecutive time points. The method, termed as trend correlation (TC, includes two major steps: 1, calculating a maximal local alignment of change trend score by dynamic programming and a change trend correlation coefficient between the maximal matched change levels of each gene pair; 2, inferring relationships of gene pairs based on two statistical extraction procedures. The new method considers time shifts and inverted relationships in a similar way as the local clustering (LC method but the latter is merely based on a point-to-point comparison. The TC method is demonstrated with data from yeast cell cycle and compared with the LC method and the widely used Pearson correlation coefficient (PCC based clustering method. The biological significance of the gene pairs is examined with several large-scale yeast databases. Although the TC method predicts an overall lower number of gene pairs than the other two methods at a same p-value threshold, the additional number of gene pairs inferred by the TC method is considerable: e.g. 20.5% compared with the LC method and 49.6% with the PCC method for a p-value threshold of 2.7E-3. Moreover, the percentage of the inferred gene pairs consistent with databases by our method is generally higher than the LC method and similar to the PCC method. A significant number of the gene pairs only inferred by the TC method are process-identity or function-similarity pairs or have well-documented biological

  16. Microarray-based analysis of gene expression profiles in peripheral blood of patients with acute primary angle closure.

    Science.gov (United States)

    Jeoung, Jin Wook; Ko, Jung Hwa; Kim, Yu Jeong; Kim, Yong Woo; Park, Ki Ho; Oh, Joo Youn

    2017-12-01

    We investigated the expression of molecules in peripheral blood mononuclear cells (PBMCs) and plasma of patients with acute primary angle closure (APAC). Peripheral blood was collected from patients with APAC (n = 10) and age-matched controls (n = 5). The gene transcription profile was analyzed in PBMCs using microarrays and validated by real-time reverse transcription polymerase chain reaction (RT-PCR). The levels of secreted proteins were evaluated in plasma by ELISA. 347 gene transcripts were up-regulated by 2-fold or more, and 696 transcripts down-regulated 2-fold or more in PBMCs from patients compared to controls. The most highly up-regulated gene was thrombospondin-1 (TSP-1, 8.66-fold increase), and the most down-regulated gene was prostaglandin-endoperoxide synthase 2 (PTGS2, 9.09-fold decrease). Real-time RT-PCR assay confirmed the increase of TSP-1 and the decrease of PTGS2 in PBMCs of patients. ELISA revealed that the levels of TSP-1 and active transforming growth factor (TGF)-β1 that is activated by TSP-1 were elevated in plasma of patients, while the level of prostaglandin E2 (PGE2) that is converted by PTGS2 was reduced. The plasma level of TSP-1 was positively correlated with that of active TGF-β1. Our data suggest that the molecular network including TSP-1, TGF-β1, and PGE2 might be involved in the pathogenesis of APAC and PACG.

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

    Science.gov (United States)

    Stamova, Boryana S; Apperson, Michelle; Walker, Wynn L; Tian, Yingfang; Xu, Huichun; Adamczy, Peter; Zhan, Xinhua; Liu, Da-Zhi; Ander, Bradley P; Liao, Isaac H; Gregg, Jeffrey P; Turner, Renee J; Jickling, Glen; Lit, Lisa; Sharp, Frank R

    2009-08-05

    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. 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. 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). 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.

  18. 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.

  19. Graphene based gene transfection

    Science.gov (United States)

    Feng, Liangzhu; Zhang, Shuai; Liu, Zhuang

    2011-03-01

    Graphene as a star in materials research has been attracting tremendous attentions in the past few years in various fields including biomedicine. In this work, for the first time we successfully use graphene as a non-toxic nano-vehicle for efficient gene transfection. Graphene oxide (GO) is bound with cationic polymers, polyethyleneimine (PEI) with two different molecular weights at 1.2 kDa and 10 kDa, forming GO-PEI-1.2k and GO-PEG-10k complexes, respectively, both of which are stable in physiological solutions. Cellular toxicity tests reveal that our GO-PEI-10k complex exhibits significantly reduced toxicity to the treated cells compared to the bare PEI-10k polymer. The positively charged GO-PEI complexes are able to further bind with plasmid DNA (pDNA) for intracellular transfection of the enhanced green fluorescence protein (EGFP) gene in HeLa cells. While EGFP transfection with PEI-1.2k appears to be ineffective, high EGFP expression is observed using the corresponding GO-PEI-1.2k as the transfection agent. On the other hand, GO-PEI-10k shows similar EGFP transfection efficiency but lower toxicity compared with PEI-10k. Our results suggest graphene to be a novel gene delivery nano-vector with low cytotoxicity and high transfection efficiency, promising for future applications in non-viral based gene therapy.Graphene as a star in materials research has been attracting tremendous attentions in the past few years in various fields including biomedicine. In this work, for the first time we successfully use graphene as a non-toxic nano-vehicle for efficient gene transfection. Graphene oxide (GO) is bound with cationic polymers, polyethyleneimine (PEI) with two different molecular weights at 1.2 kDa and 10 kDa, forming GO-PEI-1.2k and GO-PEG-10k complexes, respectively, both of which are stable in physiological solutions. Cellular toxicity tests reveal that our GO-PEI-10k complex exhibits significantly reduced toxicity to the treated cells compared to the bare PEI

  20. Gene Expression and Microarray Investigation of Dendrobium ...

    African Journals Online (AJOL)

    Result: Between the diabetic rat group and the wild-type group, 1339 functional genes showed differences in expression levels (p < 0.05). ... Genes whose expression normalized were mainly those affected by the disease state and associated with glucose and lipid metabolism, cell growth, apoptosis, biosynthesis, olfactory ...

  1. Expression of conserved signalling pathway genes during

    Indian Academy of Sciences (India)

    Hence, we analysed the expression of Notch, Wnt and Sonic Hedgehog (Shh) pathway genes during differentiation of R1 cells into early vascular lineages. Notch-, Wnt-and Shh-mediated signalling is important during embryonic development. Regulation of gene expression through these signalling molecules is a frequently ...

  2. Serial analysis of gene expression (SAGE)

    NARCIS (Netherlands)

    van Ruissen, Fred; Baas, Frank

    2007-01-01

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

  3. 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.

  4. svdPPCS: an effective singular value decomposition-based method for conserved and divergent co-expression gene module identification

    Directory of Open Access Journals (Sweden)

    Zhu Dongxiao

    2010-06-01

    Full Text Available Abstract Background Comparative analysis of gene expression profiling of multiple biological categories, such as different species of organisms or different kinds of tissue, promises to enhance the fundamental understanding of the universality as well as the specialization of mechanisms and related biological themes. Grouping genes with a similar expression pattern or exhibiting co-expression together is a starting point in understanding and analyzing gene expression data. In recent literature, gene module level analysis is advocated in order to understand biological network design and system behaviors in disease and life processes; however, practical difficulties often lie in the implementation of existing methods. Results Using the singular value decomposition (SVD technique, we developed a new computational tool, named svdPPCS (SVD-based Pattern Pairing and Chart Splitting, to identify conserved and divergent co-expression modules of two sets of microarray experiments. In the proposed methods, gene modules are identified by splitting the two-way chart coordinated with a pair of left singular vectors factorized from the gene expression matrices of the two biological categories. Importantly, the cutoffs are determined by a data-driven algorithm using the well-defined statistic, SVD-p. The implementation was illustrated on two time series microarray data sets generated from the samples of accessory gland (ACG and malpighian tubule (MT tissues of the line W118 of M. drosophila. Two conserved modules and six divergent modules, each of which has a unique characteristic profile across tissue kinds and aging processes, were identified. The number of genes contained in these models ranged from five to a few hundred. Three to over a hundred GO terms were over-represented in individual modules with FDR Conclusions svdPPCS is a novel computational tool for the comparative analysis of transcriptional profiling. It especially fits the comparison of time

  5. Module Anchored Network Inference: A Sequential Module-Based Approach to Novel Gene Network Construction from Genomic Expression Data on Human Disease Mechanism

    Directory of Open Access Journals (Sweden)

    Annamalai Muthiah

    2017-01-01

    Full Text Available Different computational approaches have been examined and compared for inferring network relationships from time-series genomic data on human disease mechanisms under the recent Dialogue on Reverse Engineering Assessment and Methods (DREAM challenge. Many of these approaches infer all possible relationships among all candidate genes, often resulting in extremely crowded candidate network relationships with many more False Positives than True Positives. To overcome this limitation, we introduce a novel approach, Module Anchored Network Inference (MANI, that constructs networks by analyzing sequentially small adjacent building blocks (modules. Using MANI, we inferred a 7-gene adipogenesis network based on time-series gene expression data during adipocyte differentiation. MANI was also applied to infer two 10-gene networks based on time-course perturbation datasets from DREAM3 and DREAM4 challenges. MANI well inferred and distinguished serial, parallel, and time-dependent gene interactions and network cascades in these applications showing a superior performance to other in silico network inference techniques for discovering and reconstructing gene network relationships.

  6. Optimization of transient gene expression system in Gerbera jemosonii petals.

    Science.gov (United States)

    Hussein, Gihan M; Abu El-Heba, Ghada A; Abdou, Sara M; Abdallah, Naglaa A

    2013-01-01

    Low transformation efficiency and long generation time for production of transgenic Gerbera jemosonii plants leads to vulnerable gene function studies. Thus, transient expression of genes would be an efficient alternative. In this investigation, a transient expression system for gerbera petals based on the Agrobacterium infiltration protocol was developed using the reporter genes β-glucuronidase (gus) and green florescence protein (gfp). Results revealed the incapability of using the gfp gene as a reporter gene for transient expression study in gerbera flowers due to the detection of green fluorescent color in the non-infiltrated gerbera flower petals. However, the gus reporter gene was successfully utilized for optimizing and obtaining the suitable agroinfiltration system in gerbera flowers. The expression of GUS was detectable after three days of agroinfiltration in gerbera cultivars "Express" and "White Grizzly" with dark pink and white flower colors, respectively. The vacuum agroinfiltration protocol has been applied on the cultivar "Express" for evaluating the transient expression of the two genes involved in the anthocyanin pathway (iris-dfr and petunia-f3' 5'h), which is responsible for the color in flowers. In comparison to the control, transient expression results showed change in the anthocyanin pigment in all infiltrated flowers with color genes. Additionally, blue color was detected in the stigma and pollen grains in the infiltrated flowers. Moreover, blue colors with variant intensities were observed in produced calli during the routine work of stable transformation with f3' 5'h gene.

  7. 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.

  8. Determinants of human adipose tissue gene expression

    DEFF Research Database (Denmark)

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

    2012-01-01

    of environmental and individual factors controlling AT adaptation is therefore essential. Here, expression of 271 transcripts, selected for regulation according to obesity and weight changes, was determined in 515 individuals before, after 8-week low-calorie diet-induced weight loss, and after 26-week ad libitum...... interconnection between expression of genes involved in de novo lipogenesis and components of the metabolic syndrome. Sex had a marked influence on AT expression of 88 transcripts, which persisted during the entire dietary intervention and after control for fat mass. In women, the influence of body mass index...... on expression of a subset of genes persisted during the dietary intervention. Twenty-two genes revealed a metabolic syndrome signature common to men and women. Genetic control of AT gene expression by cis signals was observed for 46 genes. Dietary intervention, sex, and cis genetic variants independently...

  9. Positron emission tomography imaging of gene expression

    International Nuclear Information System (INIS)

    Tang Ganghua

    2001-01-01

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

  10. 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

  11. Introduction of β-d-mannuronic acid (M2000) as a novel NSAID with immunosuppressive property based on COX-1/COX-2 activity and gene expression.

    Science.gov (United States)

    Mirshafiey, Abbas; Taeb, Mahsa; Mortazavi-Jahromi, Seyed Shahabeddin; Jafarnezhad-Ansariha, Fahimeh; Rehm, Bernd H A; Esposito, Emanuela; Cuzzocrea, Salvatore; Matsuo, Hidenori

    2017-10-01

    The NSAIDs which inhibit the cyclooxygenase (COX) enzymes are among medications widely used to treat pain and inflammation. These drugs cause digestive complications resulting in inhibition of the COX-1 enzyme, while the inhibition of the COX-2 enzyme has therapeutic effects. Therefore research focuses on the production of medications that specifically inhibit the COX-2 enzyme. This study aimed to study the effects of β-d-mannuronic (M2000) acid on the gene expression and activity of COX-1/COX-2 enzymes in order to introduce a novel NSAID for treating inflammatory diseases. The mRNA expression levels of COXs were analyzed with qRT-PCR. Prostaglandin E 2 (PGE 2 ) concentration in culture media was determined using ELISA method. Our results indicated that the M2000 at low and high dose could significantly reduce the gene expression level of COX-2 compared to the LPS group (pCOX-1 compared to the LPS group. Moreover, it was noticed that this drug strongly and significantly reduced the activity of COX-1/COX-2 enzymes at the three concentrations of 5, 50 and 500 mMol/ml compared to the LPS and arachidonic acid groups (pCOX-1/COX-2 enzymes, with suppressing the gene expression of COX-2 specifically. Therefore, based on gene expression findings this drug might be categorized and introduced as a novel NSAID with selective COX-2 inhibitory effect. Copyright © 2017 Institute of Pharmacology, Polish Academy of Sciences. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

  12. RNAi and Homologous Over-Expression Based Functional Approaches Reveal Triterpenoid Synthase Gene-Cycloartenol Synthase Is Involved in Downstream Withanolide Biosynthesis in Withania somnifera.

    Directory of Open Access Journals (Sweden)

    Smrati Mishra

    Full Text Available Withania somnifera Dunal, is one of the most commonly used medicinal plant in Ayurvedic and indigenous medicine traditionally owing to its therapeutic potential, because of major chemical constituents, withanolides. Withanolide biosynthesis requires the activities of several enzymes in vivo. Cycloartenol synthase (CAS is an important enzyme in the withanolide biosynthetic pathway, catalyzing cyclization of 2, 3 oxidosqualene into cycloartenol. In the present study, we have cloned full-length WsCAS from Withania somnifera by homology-based PCR method. For gene function investigation, we constructed three RNAi gene-silencing constructs in backbone of RNAi vector pGSA and a full-length over-expression construct. These constructs were transformed in Agrobacterium strain GV3101 for plant transformation in W. somnifera. Molecular and metabolite analysis was performed in putative Withania transformants. The PCR and Southern blot results showed the genomic integration of these RNAi and overexpression construct(s in Withania genome. The qRT-PCR analysis showed that the expression of WsCAS gene was considerably downregulated in stable transgenic silenced Withania lines compared with the non-transformed control and HPLC analysis showed that withanolide content was greatly reduced in silenced lines. Transgenic plants over expressing CAS gene displayed enhanced level of CAS transcript and withanolide content compared to non-transformed controls. This work is the first full proof report of functional validation of any metabolic pathway gene in W. somnifera at whole plant level as per our knowledge and it will be further useful to understand the regulatory role of different genes involved in the biosynthesis of withanolides.

  13. RNAi and Homologous Over-Expression Based Functional Approaches Reveal Triterpenoid Synthase Gene-Cycloartenol Synthase Is Involved in Downstream Withanolide Biosynthesis in Withania somnifera.

    Science.gov (United States)

    Mishra, Smrati; Bansal, Shilpi; Mishra, Bhawana; Sangwan, Rajender Singh; Asha; Jadaun, Jyoti Singh; Sangwan, Neelam S

    2016-01-01

    Withania somnifera Dunal, is one of the most commonly used medicinal plant in Ayurvedic and indigenous medicine traditionally owing to its therapeutic potential, because of major chemical constituents, withanolides. Withanolide biosynthesis requires the activities of several enzymes in vivo. Cycloartenol synthase (CAS) is an important enzyme in the withanolide biosynthetic pathway, catalyzing cyclization of 2, 3 oxidosqualene into cycloartenol. In the present study, we have cloned full-length WsCAS from Withania somnifera by homology-based PCR method. For gene function investigation, we constructed three RNAi gene-silencing constructs in backbone of RNAi vector pGSA and a full-length over-expression construct. These constructs were transformed in Agrobacterium strain GV3101 for plant transformation in W. somnifera. Molecular and metabolite analysis was performed in putative Withania transformants. The PCR and Southern blot results showed the genomic integration of these RNAi and overexpression construct(s) in Withania genome. The qRT-PCR analysis showed that the expression of WsCAS gene was considerably downregulated in stable transgenic silenced Withania lines compared with the non-transformed control and HPLC analysis showed that withanolide content was greatly reduced in silenced lines. Transgenic plants over expressing CAS gene displayed enhanced level of CAS transcript and withanolide content compared to non-transformed controls. This work is the first full proof report of functional validation of any metabolic pathway gene in W. somnifera at whole plant level as per our knowledge and it will be further useful to understand the regulatory role of different genes involved in the biosynthesis of withanolides.

  14. Photosynthetic gene expression in higher plants.

    Science.gov (United States)

    Berry, James O; Yerramsetty, Pradeep; Zielinski, Amy M; Mure, Christopher M

    2013-11-01

    Within the chloroplasts of higher plants and algae, photosynthesis converts light into biological energy, fueling the assimilation of atmospheric carbon dioxide into biologically useful molecules. Two major steps, photosynthetic electron transport and the Calvin-Benson cycle, require many gene products encoded from chloroplast as well as nuclear genomes. The expression of genes in both cellular compartments is highly dynamic and influenced by a diverse range of factors. Light is the primary environmental determinant of photosynthetic gene expression. Working through photoreceptors such as phytochrome, light regulates photosynthetic genes at transcriptional and posttranscriptional levels. Other processes that affect photosynthetic gene expression include photosynthetic activity, development, and biotic and abiotic stress. Anterograde (from nucleus to chloroplast) and retrograde (from chloroplast to nucleus) signaling insures the highly coordinated expression of the many photosynthetic genes between these different compartments. Anterograde signaling incorporates nuclear-encoded transcriptional and posttranscriptional regulators, such as sigma factors and RNA-binding proteins, respectively. Retrograde signaling utilizes photosynthetic processes such as photosynthetic electron transport and redox signaling to influence the expression of photosynthetic genes in the nucleus. The basic C3 photosynthetic pathway serves as the default form used by most of the plant species on earth. High temperature and water stress associated with arid environments have led to the development of specialized C4 and CAM photosynthesis, which evolved as modifications of the basic default expression program. The goal of this article is to explain and summarize the many gene expression and regulatory processes that work together to support photosynthetic function in plants.

  15. 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

  16. Development of a new comprehensive and reliable endometrial receptivity map (ER Map/ER Grade) based on RT-qPCR gene expression analysis.

    Science.gov (United States)

    Enciso, M; Carrascosa, J P; Sarasa, J; Martínez-Ortiz, P A; Munné, S; Horcajadas, J A; Aizpurua, J

    2018-02-01

    comparing LH + 2 and LH + 7 samples (paired t-test, P terms in this group of genes. Principal component analysis and discriminant functional analysis showed that 40 of the differentially expressed genes allowed accurate classification of samples according to endometrial status (proliferative, pre-receptive, receptive and post-receptive) in both fertile and infertile groups. N/A. To evaluate the efficacy of this new tool to improve ART outcomes, further investigations such as non-selection studies and randomized controlled trials will also be required. A new comprehensive system for human endometrial receptivity evaluation based on gene expression analysis has been developed. The identification of the optimal time for embryo transfer is essential to maximize the effectiveness of ART. This study is a new step in the field of personalized medicine in human reproduction which may help in the management of endometrial preparation for embryo transfer, increasing the chances of pregnancy for many couples. The authors have no potential conflict of interest to declare. No external funding was obtained for this study. © The Author(s) 2018. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

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

    DEFF Research Database (Denmark)

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

    2004-01-01

    To study the pathogenic importance of the rheumatoid factor (RF) in rheumatoid arthritis (RA) and to identify genes differentially expressed in patients and healthy individuals, total RNA was isolated from peripheral blood mononuclear cells (PBMC) from eight RF-positive and six RF-negative RA...... patients, and seven healthy controls. Gene expression of about 10,000 genes were examined using oligonucleotide-based DNA chip microarrays. The analyses showed no significant differences in PBMC expression patterns from RF-positive and RF-negative patients. However, comparisons of gene expression patterns...

  18. Development of gene expression assays measuring immune ...

    African Journals Online (AJOL)

    Using qPCR, the relative expression stability of the reference genes ACTB, GAPDH, YWHAZ and TBP in these samples was determined as well as the mean fold change in the expression of IFNG, CXCL8, CXCL9, CXCL10 and CXCL11 in M. bovis-antigen stimulated blood. The expression of YWHAZ and TBP showed ...

  19. Array-based gene expression, CGH and tissue data defines a 12q24 gain in neuroblastic tumors with prognostic implication

    Directory of Open Access Journals (Sweden)

    Kilpinen Sami

    2010-05-01

    Full Text Available Abstract Background Neuroblastoma has successfully served as a model system for the identification of neuroectoderm-derived oncogenes. However, in spite of various efforts, only a few clinically useful prognostic markers have been found. Here, we present a framework, which integrates DNA, RNA and tissue data to identify and prioritize genetic events that represent clinically relevant new therapeutic targets and prognostic biomarkers for neuroblastoma. Methods A single-gene resolution aCGH profiling was integrated with microarray-based gene expression profiling data to distinguish genetic copy number alterations that were strongly associated with transcriptional changes in two neuroblastoma cell lines. FISH analysis using a hotspot tumor tissue microarray of 37 paraffin-embedded neuroblastoma samples and in silico data mining for gene expression information obtained from previously published studies including up to 445 healthy nervous system samples and 123 neuroblastoma samples were used to evaluate the clinical significance and transcriptional consequences of the detected alterations and to identify subsequently activated gene(s. Results In addition to the anticipated high-level amplification and subsequent overexpression of MYCN, MEIS1, CDK4 and MDM2 oncogenes, the aCGH analysis revealed numerous other genetic alterations, including microamplifications at 2p and 12q24.11. Most interestingly, we identified and investigated the clinical relevance of a previously poorly characterized amplicon at 12q24.31. FISH analysis showed low-level gain of 12q24.31 in 14 of 33 (42% neuroblastomas. Patients with the low-level gain had an intermediate prognosis in comparison to patients with MYCN amplification (poor prognosis and to those with no MYCN amplification or 12q24.31 gain (good prognosis (P = 0.001. Using the in silico data mining approach, we identified elevated expression of five genes located at the 12q24.31 amplicon in neuroblastoma (DIABLO, ZCCHC

  20. Analysis of gene expression profiles of soft tissue sarcoma using a combination of knowledge-based filtering with integration of multiple statistics.

    Directory of Open Access Journals (Sweden)

    Anna Takahashi

    Full Text Available The diagnosis and treatment of soft tissue sarcomas (STS have been difficult. Of the diverse histological subtypes, undifferentiated pleomorphic sarcoma (UPS is particularly difficult to diagnose accurately, and its classification per se is still controversial. Recent advances in genomic technologies provide an excellent way to address such problems. However, it is often difficult, if not impossible, to identify definitive disease-associated genes using genome-wide analysis alone, primarily because of multiple testing problems. In the present study, we analyzed microarray data from 88 STS patients using a combination method that used knowledge-based filtering and a simulation based on the integration of multiple statistics to reduce multiple testing problems. We identified 25 genes, including hypoxia-related genes (e.g., MIF, SCD1, P4HA1, ENO1, and STAT1 and cell cycle- and DNA repair-related genes (e.g., TACC3, PRDX1, PRKDC, and H2AFY. These genes showed significant differential expression among histological subtypes, including UPS, and showed associations with overall survival. STAT1 showed a strong association with overall survival in UPS patients (logrank p = 1.84 × 10(-6 and adjusted p value 2.99 × 10(-3 after the permutation test. According to the literature, the 25 genes selected are useful not only as markers of differential diagnosis but also as prognostic/predictive markers and/or therapeutic targets for STS. Our combination method can identify genes that are potential prognostic/predictive factors and/or therapeutic targets in STS and possibly in other cancers. These disease-associated genes deserve further preclinical and clinical validation.

  1. Molecular mechanisms of curcumin action: gene expression.

    Science.gov (United States)

    Shishodia, Shishir

    2013-01-01

    Curcumin derived from the tropical plant Curcuma longa has a long history of use as a dietary agent, food preservative, and in traditional Asian medicine. It has been used for centuries to treat biliary disorders, anorexia, cough, diabetic wounds, hepatic disorders, rheumatism, and sinusitis. The preventive and therapeutic properties of curcumin are associated with its antioxidant, anti-inflammatory, and anticancer properties. Extensive research over several decades has attempted to identify the molecular mechanisms of curcumin action. Curcumin modulates numerous molecular targets by altering their gene expression, signaling pathways, or through direct interaction. Curcumin regulates the expression of inflammatory cytokines (e.g., TNF, IL-1), growth factors (e.g., VEGF, EGF, FGF), growth factor receptors (e.g., EGFR, HER-2, AR), enzymes (e.g., COX-2, LOX, MMP9, MAPK, mTOR, Akt), adhesion molecules (e.g., ELAM-1, ICAM-1, VCAM-1), apoptosis related proteins (e.g., Bcl-2, caspases, DR, Fas), and cell cycle proteins (e.g., cyclin D1). Curcumin modulates the activity of several transcription factors (e.g., NF-κB, AP-1, STAT) and their signaling pathways. Based on its ability to affect multiple targets, curcumin has the potential for the prevention and treatment of various diseases including cancers, arthritis, allergies, atherosclerosis, aging, neurodegenerative disease, hepatic disorders, obesity, diabetes, psoriasis, and autoimmune diseases. This review summarizes the molecular mechanisms of modulation of gene expression by curcumin. Copyright © 2012 International Union of Biochemistry and Molecular Biology, Inc.

  2. 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.

  3. Caleydo: connecting pathways and gene expression.

    Science.gov (United States)

    Streit, Marc; Lex, Alexander; Kalkusch, Michael; Zatloukal, Kurt; Schmalstieg, Dieter

    2009-10-15

    Understanding the relationships between pathways and the altered expression of their components in disease conditions can be addressed in a visual data analysis process. Caleydo uses novel visualization techniques to support life science experts in their analysis of gene expression data in the context of pathways and functions of individual genes. Pathways and gene expression visualizations are placed in a 3D scene where selected entities (i.e. genes) are visually connected. This allows Caleydo to seamlessly integrate interactive gene expression visualization with cross-database pathway exploration. The Caleydo visualization framework is freely available on www.caleydo.org for non-commercial use. It runs on Windows and Linux and requires a 3D capable graphics card.

  4. Adaptive Evolution of Gene Expression in Drosophila.

    Science.gov (United States)

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

    2017-08-08

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

  5. Effects of nutritional level of concentrate-based diets on meat quality and expression levels of genes related to meat quality in Hainan black goats.

    Science.gov (United States)

    Wang, Dingfa; Zhou, Luli; Zhou, Hanlin; Hou, Guanyu; Shi, Liguang; Li, Mao; Huang, Xianzhou; Guan, Song

    2015-02-01

    The present study investigated the effects of the nutritional levels of diets on meat quality and related gene expression in Hainan black goat. Twenty-four goats were divided into six dietary treatments and were fed a concentrate-based diet with two levels of crude protein (CP) (15% or 17%) and three levels of digestive energy (DE) (11.72, 12.55 or 13.39 MJ/kg DM) for 90 days. Goats fed the concentrate-based diet with 17% CP had significantly (P conversion rates (FCR). The pH 24h value tended to decrease (P goats. © 2014 Japanese Society of Animal Science.

  6. 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.

  7. Transcription activator-like effector-mediated regulation of gene expression based on the inducible packaging and delivery via designed extracellular vesicles.

    Science.gov (United States)

    Lainšček, Duško; Lebar, Tina; Jerala, Roman

    2017-02-26

    Transcription activator-like effector (TALE) proteins present a powerful tool for genome editing and engineering, enabling introduction of site-specific mutations, gene knockouts or regulation of the transcription levels of selected genes. TALE nucleases or TALE-based transcription regulators are introduced into mammalian cells mainly via delivery of the coding genes. Here we report an extracellular vesicle-mediated delivery of TALE transcription regulators and their ability to upregulate the reporter gene in target cells. Designed transcriptional activator TALE-VP16 fused to the appropriate dimerization domain was enriched as a cargo protein within extracellular vesicles produced by mammalian HEK293 cells stimulated by Ca-ionophore and using blue light- or rapamycin-inducible dimerization systems. Blue light illumination or rapamycin increased the amount of the TALE-VP16 activator in extracellular vesicles and their addition to the target cells resulted in an increased expression of the reporter gene upon addition of extracellular vesicles to the target cells. This technology therefore represents an efficient delivery for the TALE-based transcriptional regulators. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. EXPRESSION OF BACTERIOOPSIN GENES IN ESCHERICHIA COLI

    OpenAIRE

    TSUJIUCHI, Yutaka; IWASA, Tatsuo; TOKUNAGA, Fumio

    1994-01-01

    An inducible expression vector pUBO was constructed with native codons in order to express the gene of Bacteriorhodopsin (BOP) in Escherichia coli (E. coli). Vector pUBO contains lac-promoter followed by the partial structural gene of lacZ and the structural gene of BOP. The expression of this fusion protein was detected by ELISA with anti-BOP antiserum. The fusion protein obtained from E. coli trnsformed with pUBO formed approximately 0.1% of the total protein of the E. coli membrane fraction.

  9. Differential expression of cell adhesion genes

    DEFF Research Database (Denmark)

    Stein, Wilfred D; Litman, Thomas; Fojo, Tito

    2005-01-01

    that compare cells grown in suspension to similar cells grown attached to one another as aggregates have suggested that it is adhesion to the extracellular matrix of the basal membrane that confers resistance to apoptosis and, hence, resistance to cytotoxins. The genes whose expression correlates with poor...... survival might, therefore, act through such a matrix-to-cell suppression of apoptosis. Indeed, correlative mining of gene expression and patient survival databases suggests that poor survival in patients with metastatic cancer correlates highly with tumor expression of a common theme: the genes involved...

  10. Using RNA-seq data to select reference genes for normalizing gene expression in apple roots.

    Directory of Open Access Journals (Sweden)

    Zhe Zhou

    Full Text Available 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 their potential use as reliable reference genes. These genes were selected based on their low variance of gene expression in apple root tissues from a recent RNA-seq data set, and a few previously reported apple reference genes for other tissue types. Four methods, Delta Ct, geNorm, NormFinder and BestKeeper, were used to evaluate their stability in apple root tissues of various genotypes and under different experimental conditions. A small panel of stably expressed genes, MDP0000095375, MDP0000147424, MDP0000233640, MDP0000326399 and MDP0000173025 were recommended for normalizing quantitative gene expression data in apple roots under various abiotic or biotic stresses. When the most stable and least stable reference genes were used for data normalization, significant differences were observed on the expression patterns of two target genes, MdLecRLK5 (MDP0000228426, a gene encoding a lectin receptor like kinase and MdMAPK3 (MDP0000187103, a gene encoding a mitogen-activated protein kinase. Our data also indicated that for those carefully validated reference genes, a single reference gene is sufficient for reliable normalization of the quantitative gene expression. Depending on the experimental conditions, the most suitable reference genes can be specific to the sample of interest for more reliable RT-qPCR data normalization.

  11. Salicin regulates the expression of functional 'youth gene clusters' to reflect a more youthful gene expression profile.

    Science.gov (United States)

    Gopaul, R; Knaggs, H E; Lephart, J

    2011-10-01

    There are a variety of biological mechanisms that contribute to specific characteristics of ageing skin; for example, the loss of skin structure proteins, increased susceptibility to UV-induced pigmentation and/or loss of hydration. Each of these biological processes is influenced by specific groups of genes. In this research, we have identified groups of genes associated with specific clinical signs of skin ageing and refer to these as functional 'youth gene clusters'. In this study, quantitative real-time polymerase chain reaction (qPCR) was used to investigate the effects of topical application of salicin in regulating the expression of functional 'youth gene clusters' to reflect a more youthful skin profile and reduce the appearance of attributes associated with skin ageing. Results showed that salicin significantly influences the gene expression profiles of treated human equivalent full-thickness skin, by regulating the expression of genes associated with various biological processes involving skin structure, skin hydration, pigmentation and cellular differentiation. Based on the findings from this experiment, salicin was identified as a key ingredient that may regulate functional 'youth gene clusters' to reflect a more youthful gene expression profile by increasing the expression of genes responsible for youthful skin and decreasing the expression of genes responsible for the appearance of aged skin. © 2011 The Authors. ICS © 2011 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

  12. An Interactive Database of Cocaine-Responsive Gene Expression

    Directory of Open Access Journals (Sweden)

    Willard M. Freeman

    2002-01-01

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

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

    Science.gov (United States)

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

    2017-11-17

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

  14. Drosophila melanogaster gene expression changes after spaceflight.

    Data.gov (United States)

    National Aeronautics and Space Administration — Gene expression levels were determined in 3rd instar and adult Drosophila melanogaster reared during spaceflight to elucidate the genetic and molecular mechanisms...

  15. Bioluminescence Imaging of Period1 Gene Expression in Utero

    Directory of Open Access Journals (Sweden)

    Meera T. Saxena

    2007-01-01

    Full Text Available The use of real-time reporters has accelerated our understanding of gene expression in vivo. This study examined the feasibility of a luciferase-based reporter to image spatiotemporal changes in fetal gene expression in utero. We chose to monitor Period1 (Per1 because it is expressed broadly in the body and plays a role in circadian rhythmicity. Using rats carrying a Per1::luc transgene, we repetitively imaged fetuses in utero throughout gestation. We found that bioluminescence was specific to transgenic pups, increased dramatically on embryonic day 10 (10 days after successful mating, and continued to increase logarithmically until birth. Diurnal fluctuations in Per1 expression were apparent several days prior to birth. These results demonstrate the feasibility of in utero imaging of mammalian gene expression, tracking of fetal gene expression from the same litter, and early detection of mammalian clock gene expression. We conclude that luciferase-based reporters can provide a sensitive, noninvasive measure of in utero gene expression.

  16. Dietary Bacillus subtilis-based direct-fed microbials alleviate LPS-induced intestinal immunological stress and improve intestinal barrier gene expression in commercial broiler chickens.

    Science.gov (United States)

    Gadde, Ujvala Deepthi; Oh, Sungtaek; Lee, Youngsub; Davis, Ellen; Zimmerman, Noah; Rehberger, Tom; Lillehoj, Hyun Soon

    2017-10-01

    This study investigated the effects of Bacillus subtilis-based probiotics on the performance, modulation of host inflammatory responses and intestinal barrier gene expression of broilers subjected to LPS challenge. Chickens were randomly allocated to one of the 3 dietary treatment groups - control, antibiotic, or probiotic. At 14days, half of the chickens in each treatment were injected with LPS (1mg/kg body weight), and the other half injected with sterile PBS. Chickens fed probiotics weighed significantly more than controls at 15days of age, irrespective of immune challenge. LPS challenge significantly reduced weight gain at 24h post-injection, and the probiotics did not alleviate the LPS-induced reduction of weight gain. Serum α-1-AGP levels were significantly higher in LPS-injected chickens, and probiotic supplementation significantly reduced their levels. The percentages of CD4+ lymphocytes were significantly increased in probiotic groups in the absence of immunological challenge but were reduced during LPS challenge compared to controls. CD8+ lymphocytes were significantly reduced in probiotic-fed birds. The LPS-induced increase in the expression of cytokines IL8 and TNFSF15 was reduced by probiotic supplementation, and IL17F, iNOS expression was found to be significantly elevated in probiotic-fed birds subjected to LPS challenge. The reduced gene expression of tight junction proteins (JAM2, occludin and ZO1) and MUC2 induced by LPS challenge was reversed by probiotic supplementation. The results indicate that B. subtilis-based probiotics differentially regulate intestinal immune and tight junction protein mRNA expression during states of LPS-mediated immunological challenge. Published by Elsevier Ltd.

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

    Science.gov (United States)

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

    2018-03-01

    Gene expression patterns can be used as prognostic biomarkers in various types of cancers. We aimed to identify a gene expression pattern for individual distant metastatic risk assessment in patients with locoregionally advanced nasopharyngeal carcinoma. In this multicentre, retrospective, cohort analysis, we included 937 patients with locoregionally advanced nasopharyngeal carcinoma from three Chinese hospitals: the Sun Yat-sen University Cancer Center (Guangzhou, China), the Affiliated Hospital of Guilin Medical University (Guilin, China), and the First People's Hospital of Foshan (Foshan, China). Using microarray analysis, we profiled mRNA gene expression between 24 paired locoregionally advanced nasopharyngeal carcinoma tumours from patients at Sun Yat-sen University Cancer Center with or without distant metastasis after radical treatment. Differentially expressed genes were examined using digital expression profiling in a training cohort (Guangzhou training cohort; n=410) to build a gene classifier using a penalised regression model. We validated the prognostic accuracy of this gene classifier in an internal validation cohort (Guangzhou internal validation cohort, n=204) and two external independent cohorts (Guilin cohort, n=165; Foshan cohort, n=158). The primary endpoint was distant metastasis-free survival. Secondary endpoints were disease-free survival and overall survival. We identified 137 differentially expressed genes between metastatic and non-metastatic locoregionally advanced nasopharyngeal carcinoma tissues. A distant metastasis gene signature for locoregionally advanced nasopharyngeal carcinoma (DMGN) that consisted of 13 genes was generated to classify patients into high-risk and low-risk groups in the training cohort. Patients with high-risk scores in the training cohort had shorter distant metastasis-free survival (hazard ratio [HR] 4·93, 95% CI 2·99-8·16; p<0·0001), disease-free survival (HR 3·51, 2·43-5·07; p<0·0001), and overall

  18. PRAME gene expression profile in medulloblastoma

    Directory of Open Access Journals (Sweden)

    Tânia Maria Vulcani-Freitas

    2011-02-01

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

  19. Deep sequencing-based transcriptional analysis of bovine mammary epithelial cells gene expression in response to in vitro infection with Staphylococcus aureus stains.

    Directory of Open Access Journals (Sweden)

    Xiao Wang

    Full Text Available Staphylococcus aureus (S. aureus is an important etiological organism in chronic and subclinical mastitis in lactating cows. Given the fundamental role the primary bovine mammary epithelial cells (pBMECs play as a major first line of defense against invading pathogens, their interactions with S. aureus was hypothesized to be crucial to the establishment of the latter's infection process. This hypothesis was tested by investigating the global transcriptional responses of pBMECs to three S. aureus strains (S56,S178 and S36 with different virulent factors, using a tag-based high-throughput transcriptome sequencing technique. Approximately 4.9 million total sequence tags were obtained from each of the three S. aureus-infected libraries and the control library. Referenced to the control, 1720, 219, and 427 differentially expressed unique genes were identified in the pBMECs infected with S56, S178 and S36 S. aureus strains respectively. Gene ontology (GO and pathway analysis of the S56-infected pBMECs referenced to those of the control revealed that the differentially expressed genes in S56-infected pBMECs were significantly involved in inflammatory response, cell signalling pathways and apoptosis. In the same vein, the clustered GO terms of the differentially expressed genes of the S178-infected pBMECs were found to comprise immune responses, metabolism transformation, and apoptosis, while those of the S36-infected pBMECs were primarily involved in cell cycle progression and immune responses. Furthermore, fundamental differences were observed in the levels of expression of immune-related genes in response to treatments with the three S. aureus strains. These differences were especially noted for the expression of important pro-inflammatory molecules, including IL-1α, TNF, EFNB1, IL-8, and EGR1. The transcriptional changes associated with cellular signaling and the inflammatory response in this study may reflect different immunomodulatory mechanisms

  20. Identification, expression profiling and fluorescence-based binding assays of a chemosensory protein gene from the Western flower thrips, Frankliniella occidentalis.

    Science.gov (United States)

    Zhang, Zhi-Ke; Lei, Zhong-Ren

    2015-01-01

    Using RT-PCR and RACE-PCR strategies, we cloned and identified a new chemosensory protein (FoccCSP) from the Western flower thrips, Frankliniella occidentalis, a species for which no chemosensory protein (CSP) has yet been identified. The FoccCSP gene contains a 387 bp open-reading frame encoding a putative protein of 128 amino acids with a molecular weight of 14.51 kDa and an isoelectric point of 5.41. The deduced amino acid sequence contains a putative signal peptide of 19 amino acid residues at the N-terminus, as well as the typical four-cysteine signature found in other insect CSPs. As FoccCSP is from a different order of insect than other known CSPs, the GenBank FoccCSP homolog showed only 31-50% sequence identity with them. A neighbor-joining tree was constructed and revealed that FoccCSP is in a group with CSPs from Homopteran insects (e.g., AgosCSP4, AgosCSP10, ApisCSP, and NlugCSP9), suggesting that these genes likely developed from a common ancestral gene. The FoccCSP gene expression profile of different tissues and development stages was measured by quantitative real-time PCR. The results of this analysis revealed this gene is predominantly expressed in the antennae and also highly expressed in the first instar nymph, suggesting a function for FoccCSP in olfactory reception and in particular life activities during the first instar nymph stage. We expressed recombinant FoccCSP protein in a prokaryotic expression system and purified FoccCSP protein by affinity chromatography using a Ni-NTA-Sepharose column. Using N-phenyl-1-naphthylamine (1-NPN) as a fluorescent probe in fluorescence-based competitive binding assay, we determined the binding affinities of 19 volatile substances for FoccCSP protein. This analysis revealed that anisic aldehyde, geraniol and methyl salicylate have high binding affinities for FoccCSP, with KD values of 10.50, 15.35 and 35.24 μM, respectively. Thus, our study indicates that FoccCSP may play an important role in regulating the

  1. Identification, expression profiling and fluorescence-based binding assays of a chemosensory protein gene from the Western flower thrips, Frankliniella occidentalis.

    Directory of Open Access Journals (Sweden)

    Zhi-Ke Zhang

    Full Text Available Using RT-PCR and RACE-PCR strategies, we cloned and identified a new chemosensory protein (FoccCSP from the Western flower thrips, Frankliniella occidentalis, a species for which no chemosensory protein (CSP has yet been identified. The FoccCSP gene contains a 387 bp open-reading frame encoding a putative protein of 128 amino acids with a molecular weight of 14.51 kDa and an isoelectric point of 5.41. The deduced amino acid sequence contains a putative signal peptide of 19 amino acid residues at the N-terminus, as well as the typical four-cysteine signature found in other insect CSPs. As FoccCSP is from a different order of insect than other known CSPs, the GenBank FoccCSP homolog showed only 31-50% sequence identity with them. A neighbor-joining tree was constructed and revealed that FoccCSP is in a group with CSPs from Homopteran insects (e.g., AgosCSP4, AgosCSP10, ApisCSP, and NlugCSP9, suggesting that these genes likely developed from a common ancestral gene. The FoccCSP gene expression profile of different tissues and development stages was measured by quantitative real-time PCR. The results of this analysis revealed this gene is predominantly expressed in the antennae and also highly expressed in the first instar nymph, suggesting a function for FoccCSP in olfactory reception and in particular life activities during the first instar nymph stage. We expressed recombinant FoccCSP protein in a prokaryotic expression system and purified FoccCSP protein by affinity chromatography using a Ni-NTA-Sepharose column. Using N-phenyl-1-naphthylamine (1-NPN as a fluorescent probe in fluorescence-based competitive binding assay, we determined the binding affinities of 19 volatile substances for FoccCSP protein. This analysis revealed that anisic aldehyde, geraniol and methyl salicylate have high binding affinities for FoccCSP, with KD values of 10.50, 15.35 and 35.24 μM, respectively. Thus, our study indicates that FoccCSP may play an important role in

  2. Selection and validation of reference genes for gene expression analysis in apomictic and sexual Cenchrus ciliaris

    Science.gov (United States)

    2013-01-01

    Background Apomixis is a naturally occurring asexual mode of seed reproduction resulting in offspring genetically identical to the maternal plant. Identifying differential gene expression patterns between apomictic and sexual plants is valuable to help deconstruct the trait. Quantitative RT-PCR (qRT-PCR) is a popular method for analyzing gene expression. Normalizing gene expression data using proper reference genes which show stable expression under investigated conditions is critical in qRT-PCR analysis. We used qRT-PCR to validate expression and stability of six potential reference genes (EF1alpha, EIF4A, UBCE, GAPDH, ACT2 and TUBA) in vegetative and reproductive tissues of B-2S and B-12-9 accessions of C. ciliaris. Findings Among tissue types evaluated, EF1alpha showed the highest level of expression while TUBA showed the lowest. When all tissue types were evaluated and compared between genotypes, EIF4A was the most stable reference gene. Gene expression stability for specific ovary stages of B-2S and B-12-9 was also determined. Except for TUBA, all other tested reference genes could be used for any stage-specific ovary tissue normalization, irrespective of the mode of reproduction. Conclusion Our gene expression stability assay using six reference genes, in sexual and apomictic accessions of C. ciliaris, suggests that EIF4A is the most stable gene across all tissue types analyzed. All other tested reference genes, with the exception of TUBA, could be used for gene expression comparison studies between sexual and apomictic ovaries over multiple developmental stages. This reference gene validation data in C. ciliaris will serve as an important base for future apomixis-related transcriptome data validation. PMID:24083672

  3. Prognostic Gene Expression Profiles in Breast Cancer

    DEFF Research Database (Denmark)

    Sørensen, Kristina Pilekær

    Each year approximately 4,800 Danish women are diagnosed with breast cancer. Several clinical and pathological factors are used as prognostic and predictive markers to categorize the patients into groups of high or low risk. Around 90% of all patients are allocated to the high risk group and offe......Each year approximately 4,800 Danish women are diagnosed with breast cancer. Several clinical and pathological factors are used as prognostic and predictive markers to categorize the patients into groups of high or low risk. Around 90% of all patients are allocated to the high risk group...... clinical courses, and they may be useful as novel prognostic biomarkers in breast cancer. The aim of the present project was to predict the development of metastasis in lymph node negative breast cancer patients by RNA profiling. We collected and analyzed 82 primary breast tumors from patients who...... developed metastasis and 82 primary breast tumors from patients who remained metastasis-free, by microarray gene expression profiling. We employed a nested case-control design, where samples were matched, in this study one-to-one, to exclude differences in gene expression based on tumor type, tumor size...

  4. Homeobox genes expressed during echinoderm arm regeneration.

    Science.gov (United States)

    Ben Khadra, Yousra; Said, Khaled; Thorndyke, Michael; Martinez, Pedro

    2014-04-01

    Regeneration in echinoderms has proved to be more amenable to study in the laboratory than the more classical vertebrate models, since the smaller genome size and the absence of multiple orthologs for different genes in echinoderms simplify the analysis of gene function during regeneration. In order to understand the role of homeobox-containing genes during arm regeneration in echinoderms, we isolated the complement of genes belonging to the Hox class that are expressed during this process in two major echinoderm groups: asteroids (Echinaster sepositus and Asterias rubens) and ophiuroids (Amphiura filiformis), both of which show an extraordinary capacity for regeneration. By exploiting the sequence conservation of the homeobox, putative orthologs of several Hox genes belonging to the anterior, medial, and posterior groups were isolated. We also report the isolation of a few Hox-like genes expressed in the same systems.

  5. Evaluation of suitable reference genes for gene expression studies ...

    Indian Academy of Sciences (India)

    2011-12-14

    Dec 14, 2011 ... MADS family of TFs control floral organ identity within each whorl of the flower by activating downstream genes. Measuring gene expression in different tissue types and developmental stages is of fundamental importance in TFs functional research. In last few years, quantitative real-time. PCR (qRT-PCR) ...

  6. 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.

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

    Directory of Open Access Journals (Sweden)

    Odelta dos Santos

    Full Text Available 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.

  8. 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.

  9. Expression of Deinococcus geothermalis trehalose synthase gene ...

    African Journals Online (AJOL)

    A novel trehalose synthase gene from Deinococcus geothermalis (DSMZ 11300) containing 1692 bp reading-frame encoding 564 amino acids was amplified using polymerase chain reaction (PCR). The gene was ligated into pET30Ek/LIC vector and expressed after isopropyl β-D-thiogalactopyranoside induction in ...

  10. Genomewide identification and expression analysis of the ARF gene ...

    Indian Academy of Sciences (India)

    Genomewide identification and expression analysis of the ARF gene family in apple. Xiao-Cui Luo, Mei-Hong Sun, Rui-Rui Xu, Huai-Rui Shu, Jia-Wei Wang and Shi-Zhong Zhang. J. Genet. 93, 785–797. Figure 1. Phylogenetic relation of apple ARF genes. The phylogenetic tree was constructed based on a complete protein ...

  11. Identification of salt-stress induced differentially expressed genes in ...

    African Journals Online (AJOL)

    Identification of salt-stress induced differentially expressed genes in barley leaves using the annealingcontrol- primer-based GeneFishing technique. S Lee, K Lee, K Kim, GJ Choi, SH Yoon, HC Ji, S Seo, YC Lim, N Ahsan ...

  12. Identification of genes showing differential expression profile ...

    Indian Academy of Sciences (India)

    in pig with genetic propensity for higher growth rate were identified by sequence analysis of 12 differentially expressed clones selected by differential screening following the generation of the subtracted cDNA population. Real-time PCR analysis con- firmed difference in expression profiles of the identified genes in ...

  13. In plants, expression breadth and expression level distinctly and non-linearly correlate with gene structure

    Directory of Open Access Journals (Sweden)

    Yang Hangxing

    2009-11-01

    Full Text Available Abstract Background Compactness of highly/broadly expressed genes in human has been explained as selection for efficiency, regional mutation biases or genomic design. However, highly expressed genes in flowering plants were shown to be less compact than lowly expressed ones. On the other hand, opposite facts have also been documented that pollen-expressed Arabidopsis genes tend to contain shorter introns and highly expressed moss genes are compact. This issue is important because it provides a chance to compare the selectionism and the neutralism views about genome evolution. Furthermore, this issue also helps to understand the fates of introns, from the angle of gene expression. Results In this study, I used expression data covering more tissues and employ new analytical methods to reexamine the correlations between gene expression and gene structure for two flowering plants, Arabidopsis thaliana and Oryza sativa. It is shown that, different aspects of expression pattern correlate with different parts of gene sequences in distinct ways. In detail, expression level is significantly negatively correlated with gene size, especially the size of non-coding regions, whereas expression breadth correlates with non-coding structural parameters positively and with coding region parameters negatively. Furthermore, the relationships between expression level and structural parameters seem to be non-linear, with the extremes of structural parameters possibly scale as power-laws or logrithmic functions of expression levels. Conclusion In plants, highly expressed genes are compact, especially in the non-coding regions. Broadly expressed genes tend to contain longer non-coding sequences, which may be necessary for complex regulations. In combination with previous studies about other plants and about animals, some common scenarios about the correlation between gene expression and gene structure begin to emerge. Based on the functional relationships between

  14. Imaging of Herpes Simplex Virus Type 1 Thymidine Kinase Gene Expression with Radiolabeled 5-(2-iodovinyl)-2'-deoxyuridine (IVDU) in Liver by Hydrodynamic-based Procedure

    Energy Technology Data Exchange (ETDEWEB)

    Song, In Ho; Lee, Tae Sup; Kang, Joo Hyun; Lee, Yong Jin; Kim, Kwang Il; An, Gwang Il; Chung, Wee Sup; Cheon, Gi Jeong; Choi, Chang Woon; Lim, Sang Moo [Korea Institute of Radiological and Medical Sciences, Seoul (Korea, Republic of)

    2009-10-15

    Hydrodynamic-based procedure is a simple and effective gene delivery method to lead a high gene expression in liver tissue. Non-invasive imaging reporter gene system has been used widely with herpes simplex virus type 1 thymidine kinase (HSV1-tk) and its various substrates. In the present study, we investigated to image the expression of HSV1-tk gene with 5-(2-iodovinyl)-2'-deoxyuridine (IVDU) in mouse liver by the hydrodynamicbased procedure. HSV1-tk or enhanced green fluorescence protein (EGFP) encoded plasmid DNA was transferred into the mouse liver by hydrodynamic injection. At 24 h post-injection, RT-PCR, biodistribution, fluorescence imaging, nuclear imaging and digital wholebody autoradiography (DWBA) were performed to confirm transferred gene expression. In RT-PCR assay using mRNA from the mouse liver, specific bands of HSV1-tk and EGFP gene were observed in HSV1-tk and EGFP expressing plasmid injected mouse, respectively. Higher uptake of radiolabeled IVDU was exhibited in liver of HSV1-tk gene transferred mouse by biodistribution study. In fluorescence imaging, the liver showed specific fluorescence signal in EGFP gene transferred mouse. Gamma-camera image and DWBA results showed that radiolabeled IVDU was accumulated in the liver of HSV1-tk gene transferred mouse. In this study, hydrodynamic-based procedure was effective in liver-specific gene delivery and it could be quantified with molecular imaging methods. Therefore, co-expression of HSV1-tk reporter gene and target gene by hydrodynamic-based procedure is expected to be a useful method for the evaluation of the target gene expression level with radiolabeled IVDU.

  15. Full design automation of multi-state RNA devices to program gene expression using energy-based optimization.

    Directory of Open Access Journals (Sweden)

    Guillermo Rodrigo

    Full Text Available Small RNAs (sRNAs can operate as regulatory agents to control protein expression by interaction with the 5' untranslated region of the mRNA. We have developed a physicochemical framework, relying on base pair interaction energies, to design multi-state sRNA devices by solving an optimization problem with an objective function accounting for the stability of the transition and final intermolecular states. Contrary to the analysis of the reaction kinetics of an ensemble of sRNAs, we solve the inverse problem of finding sequences satisfying targeted reactions. We show here that our objective function correlates well with measured riboregulatory activity of a set of mutants. This has enabled the application of the methodology for an extended design of RNA devices with specified behavior, assuming different molecular interaction models based on Watson-Crick interaction. We designed several YES, NOT, AND, and OR logic gates, including the design of combinatorial riboregulators. In sum, our de novo approach provides a new paradigm in synthetic biology to design molecular interaction mechanisms facilitating future high-throughput functional sRNA design.

  16. Regulation of gene expression in human tendinopathy

    Directory of Open Access Journals (Sweden)

    Archambault Joanne M

    2011-05-01

    Full Text Available Abstract 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.

  17. Gene expression profiling predicts survival in conventional renal cell carcinoma.

    Directory of Open Access Journals (Sweden)

    Hongjuan Zhao

    2006-01-01

    Full Text Available BACKGROUND: Conventional renal cell carcinoma (cRCC accounts for most of the deaths due to kidney cancer. Tumor stage, grade, and patient performance status are used currently to predict survival after surgery. Our goal was to identify gene expression features, using comprehensive gene expression profiling, that correlate with survival. METHODS AND FINDINGS: Gene expression profiles were determined in 177 primary cRCCs using DNA microarrays. Unsupervised hierarchical clustering analysis segregated cRCC into five gene expression subgroups. Expression subgroup was correlated with survival in long-term follow-up and was independent of grade, stage, and performance status. The tumors were then divided evenly into training and test sets that were balanced for grade, stage, performance status, and length of follow-up. A semisupervised learning algorithm (supervised principal components analysis was applied to identify transcripts whose expression was associated with survival in the training set, and the performance of this gene expression-based survival predictor was assessed using the test set. With this method, we identified 259 genes that accurately predicted disease-specific survival among patients in the independent validation group (p < 0.001. In multivariate analysis, the gene expression predictor was a strong predictor of survival independent of tumor stage, grade, and performance status (p < 0.001. CONCLUSIONS: cRCC displays molecular heterogeneity and can be separated into gene expression subgroups that correlate with survival after surgery. We have identified a set of 259 genes that predict survival after surgery independent of clinical prognostic factors.

  18. Gene Expression Profiling Predicts Survival in Conventional Renal Cell Carcinoma.

    Directory of Open Access Journals (Sweden)

    2005-12-01

    Full Text Available BACKGROUND: Conventional renal cell carcinoma (cRCC accounts for most of the deaths due to kidney cancer. Tumor stage, grade, and patient performance status are used currently to predict survival after surgery. Our goal was to identify gene expression features, using comprehensive gene expression profiling, that correlate with survival. METHODS AND FINDINGS: Gene expression profiles were determined in 177 primary cRCCs using DNA microarrays. Unsupervised hierarchical clustering analysis segregated cRCC into five gene expression subgroups. Expression subgroup was correlated with survival in long-term follow-up and was independent of grade, stage, and performance status. The tumors were then divided evenly into training and test sets that were balanced for grade, stage, performance status, and length of follow-up. A semisupervised learning algorithm (supervised principal components analysis was applied to identify transcripts whose expression was associated with survival in the training set, and the performance of this gene expression-based survival predictor was assessed using the test set. With this method, we identified 259 genes that accurately predicted disease-specific survival among patients in the independent validation group (p < 0.001. In multivariate analysis, the gene expression predictor was a strong predictor of survival independent of tumor stage, grade, and performance status (p < 0.001. CONCLUSIONS: cRCC displays molecular heterogeneity and can be separated into gene expression subgroups that correlate with survival after surgery. We have identified a set of 259 genes that predict survival after surgery independent of clinical prognostic factors.

  19. 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.

  20. Global gene expression in Escherichia coli biofilms

    DEFF Research Database (Denmark)

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

    2003-01-01

    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...... the transition to biofilm growth, and these included genes expressed under oxygen-limiting conditions, genes encoding (putative) transport proteins, putative oxidoreductases and genes associated with enhanced heavy metal resistance. Of particular interest was the observation that many of the genes altered...

  1. Gene expression pattern of adiponectin and adiponectin receptors in dominant and atretic follicles and oocytes screened based on brilliant cresyl blue staining.

    Science.gov (United States)

    Tabandeh, M R; Golestani, N; Kafi, M; Hosseini, A; Saeb, M; Sarkoohi, P

    2012-03-01

    Adiponectin and its receptors (AdipoR1 and AdipoR2) are novel endocrine systems that act at various levels to control male and female fertility. The aim of this study was to determine whether adiponectin and its receptors gene expression levels differ between dominant follicle (DF) and atretic follicle (AF) and also between oocytes which were stained positively and negatively with brilliant cresyl blue (BCB(+) and BCB(-)). Based on estradiol/progesterone ratio, follicles from ovaries were classified as AFs and DFs. The stages of estrous cycle (follicular or luteal phases) were defined by macroscopic observation of the ovaries and the uterus. Oocytes were stained with BCB for 90 min. The relative expression of adiponectin, AdipoR1 and AdipoR2 mRNA in theca and cumulus cells and oocytes of different follicles were determined by quantitative real time PCR. Adiponectin and its receptors genes were clearly expressed higher (PBCB(+) oocytes showed a higher (PBCB(-) counterparts. Positive correlation (r>0.725, P<0.001) was observed between adiponectin mRNA level in ovarian cells of DFs and follicular fluid E2 concentration in follicular phase. Adiponectin mRNA abundance in ovarian cells of AFs showed a significant negative correlation with follicular fluid progesterone concentration in follicular and luteal phases (r<-0.731, P<0.001). This work has revealed the novel association of adiponectin and its receptors genes with follicular dominance and oocyte competence, thereby opening several new avenues of research into the mechanisms of dominance and competence in animal and human. Copyright © 2012 Elsevier B.V. All rights reserved.

  2. An in vivo transfection system for inducible gene expression and gene silencing in murine hepatocytes.

    Science.gov (United States)

    Hubner, Eric K; Lechler, Christian; Kohnke-Ertel, Birgit; Zmoos, Anne-Flore; Sage, Julien; Schmid, Roland M; Ehmer, Ursula

    2017-01-01

    Hydrodynamic tail vein injection (HTVI) of transposon-based integration vectors is an established system for stably transfecting mouse hepatocytes in vivo that has been successfully employed to study key questions in liver biology and cancer. Refining the vectors for transposon-mediated hepatocyte transfection will further expand the range of applications of this technique in liver research. In the present study, we report an advanced transposon-based system for manipulating gene expression in hepatocytes in vivo. Transposon-based vector constructs were generated to enable the constitutive expression of inducible Cre recombinase (CreER) together with tetracycline-inducible transgene or miR-small hairpin RNA (shRNA) expression (Tet-ON system). Transposon and transposase expression vectors were co-injected into R26R-mTmG reporter mice by HTVI. Cre-mediated gene recombination was induced by tamoxifen, followed by the administration of doxycycline to drive tetracycline-inducible gene or shRNA expression. Expression was visualized by immunofluorescence staining in livers of injected mice. After HTVI, Cre recombination by tamoxifen led to the expression of membrane-bound green fluorescent protein in transfected hepatocytes. Activation of inducible gene or shRNA expression was detected by immunostaining in up to one-third of transfected hepatocytes, with an efficiency dependent on the promoter driving the Tet-ON system. Our vector system combines Cre-lox mediated gene mutation with inducible gene expression or gene knockdown, respectively. It provides the opportunity for rapid and specific modification of hepatocyte gene expression and can be a useful tool for genetic screening approaches and analysis of target genes specifically in genetically engineered mouse models. Copyright © 2016 John Wiley & Sons, Ltd.

  3. Whole-body gene expression pattern registration in Platynereis larvae.

    Science.gov (United States)

    Asadulina, Albina; Panzera, Aurora; Verasztó, Csaba; Liebig, Christian; Jékely, Gáspár

    2012-12-03

    Digital anatomical atlases are increasingly used in order to depict different gene expression patterns and neuronal morphologies within a standardized reference template. In evo-devo, a discipline in which the comparison of gene expression patterns is a widely used approach, such standardized anatomical atlases would allow a more rigorous assessment of the conservation of and changes in gene expression patterns during micro- and macroevolutionary time scales. Due to its small size and invariant early development, the annelid Platynereis dumerilii is particularly well suited for such studies. Recently a reference template with registered gene expression patterns has been generated for the anterior part (episphere) of the Platynereis trochophore larva and used for the detailed study of neuronal development. Here we introduce and evaluate a method for whole-body gene expression pattern registration for Platynereis trochophore and nectochaete larvae based on whole-mount in situ hybridization, confocal microscopy, and image registration. We achieved high-resolution whole-body scanning using the mounting medium 2,2'-thiodiethanol (TDE), which allows the matching of the refractive index of the sample to that of glass and immersion oil thereby reducing spherical aberration and improving depth penetration. This approach allowed us to scan entire whole-mount larvae stained with nitroblue tetrazolium/5-bromo-4-chloro-3-indolyl phosphate (NBT/BCIP) in situ hybridization and counterstained fluorescently with an acetylated-tubulin antibody and the nuclear stain 4'6-diamidino-2-phenylindole (DAPI). Due to the submicron isotropic voxel size whole-mount larvae could be scanned in any orientation. Based on the whole-body scans, we generated four different reference templates by the iterative registration and averaging of 40 individual image stacks using either the acetylated-tubulin or the nuclear-stain signal for each developmental stage. We then registered to these templates the

  4. Whole-body gene expression pattern registration in Platynereis larvae

    Directory of Open Access Journals (Sweden)

    Asadulina Albina

    2012-12-01

    Full Text Available Abstract Background Digital anatomical atlases are increasingly used in order to depict different gene expression patterns and neuronal morphologies within a standardized reference template. In evo-devo, a discipline in which the comparison of gene expression patterns is a widely used approach, such standardized anatomical atlases would allow a more rigorous assessment of the conservation of and changes in gene expression patterns during micro- and macroevolutionary time scales. Due to its small size and invariant early development, the annelid Platynereis dumerilii is particularly well suited for such studies. Recently a reference template with registered gene expression patterns has been generated for the anterior part (episphere of the Platynereis trochophore larva and used for the detailed study of neuronal development. Results Here we introduce and evaluate a method for whole-body gene expression pattern registration for Platynereis trochophore and nectochaete larvae based on whole-mount in situ hybridization, confocal microscopy, and image registration. We achieved high-resolution whole-body scanning using the mounting medium 2,2’-thiodiethanol (TDE, which allows the matching of the refractive index of the sample to that of glass and immersion oil thereby reducing spherical aberration and improving depth penetration. This approach allowed us to scan entire whole-mount larvae stained with nitroblue tetrazolium/5-bromo-4-chloro-3-indolyl phosphate (NBT/BCIP in situ hybridization and counterstained fluorescently with an acetylated-tubulin antibody and the nuclear stain 4’6-diamidino-2-phenylindole (DAPI. Due to the submicron isotropic voxel size whole-mount larvae could be scanned in any orientation. Based on the whole-body scans, we generated four different reference templates by the iterative registration and averaging of 40 individual image stacks using either the acetylated-tubulin or the nuclear-stain signal for each developmental

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

    KAUST Repository

    Horiuchi, Youko

    2015-01-01

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

  6. SIGNATURE: A workbench for gene expression signature analysis

    Directory of Open Access Journals (Sweden)

    Chang Jeffrey T

    2011-11-01

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

  7. GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature

    Directory of Open Access Journals (Sweden)

    Ning Ye

    2015-01-01

    Full Text Available The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.

  8. GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature.

    Science.gov (United States)

    Ye, Ning; Yin, Hengfu; Liu, Jingjing; Dai, Xiaogang; Yin, Tongming

    2015-01-01

    The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI) toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.

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

    Directory of Open Access Journals (Sweden)

    Dunner Susana

    2008-09-01

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

  10. Human AZU-1 gene, variants thereof and expressed gene products

    Science.gov (United States)

    Chen, Huei-Mei; Bissell, Mina

    2004-06-22

    A human AZU-1 gene, mutants, variants and fragments thereof. Protein products encoded by the AZU-1 gene and homologs encoded by the variants of AZU-1 gene acting as tumor suppressors or markers of malignancy progression and tumorigenicity reversion. Identification, isolation and characterization of AZU-1 and AZU-2 genes localized to a tumor suppressive locus at chromosome 10q26, highly expressed in nonmalignant and premalignant cells derived from a human breast tumor progression model. A recombinant full length protein sequences encoded by the AZU-1 gene and nucleotide sequences of AZU-1 and AZU-2 genes and variant and fragments thereof. Monoclonal or polyclonal antibodies specific to AZU-1, AZU-2 encoded protein and to AZU-1, or AZU-2 encoded protein homologs.

  11. Gene expression profiling of Drosophila tracheal fusion cells.

    Science.gov (United States)

    Chandran, Rachana R; Iordanou, Ekaterini; Ajja, Crystal; Wille, Michael; Jiang, Lan

    2014-07-01

    The Drosophila trachea is a premier genetic system to investigate the fundamental mechanisms of tubular organ formation. Tracheal fusion cells lead the branch fusion process to form an interconnected tubular network. Therefore, fusion cells in the Drosophila trachea will be an excellent model to study branch fusion in mammalian tubular organs, such as kidneys and blood vessels. The fusion process is a dynamic cellular process involving cell migration, adhesion, vesicle trafficking, cytoskeleton rearrangement, and membrane fusion. To understand how these cellular events are coordinated, we initiated the critical step to assemble a gene expression profile of fusion cells. For this study, we analyzed the expression of 234 potential tracheal-expressed genes in fusion cells during fusion cell development. 143 Tracheal genes were found to encode transcription factors, signal proteins, cytoskeleton and matrix proteins, transporters, and proteins with unknown function. These genes were divided into four subgroups based on their levels of expression in fusion cells compared to neighboring non-fusion cells revealed by in situ hybridization: (1) genes that have relative high abundance in fusion cells, (2) genes that are dynamically expressed in fusion cells, (3) genes that have relative low abundance in fusion cells, and (4) genes that are expressed at similar levels in fusion cells and non-fusion tracheal cells. This study identifies the expression profile of fusion cells and hypothetically suggests genes which are necessary for the fusion process and which play roles in distinct stages of fusion, as indicated by the location and timing of expression. These data will provide the basis for a comprehensive understanding of the molecular and cellular mechanisms of branch fusion. Copyright © 2014 Elsevier B.V. All rights reserved.

  12. Gene Expression Profiling during Pregnancy in Rat Brain Tissue

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    Phyllis E. Mann

    2014-03-01

    Full Text Available The neurophysiological changes that occur during pregnancy in the female mammal have led to the coining of the phrases “expectant brain” and “maternal brain”. Although much is known of the hormonal changes during pregnancy, alterations in neurotransmitter gene expression have not been well-studied. We examined gene expression in the ventromedial nucleus of the hypothalamus (VMH during pregnancy based on the fact that this nucleus not only modulates the physiological changes that occur during pregnancy but is also involved in the development of maternal behavior. This study was designed to identify genes that are differentially expressed between mid- and late-pregnancy in order to determine which genes may be associated with the onset and display of maternal behavior and the development of the maternal brain. A commercially available PCR array containing 84 neurotransmitter receptor and regulator genes (RT2 Profiler PCR array was used. Brains were harvested from rats on days 12 and 21 of gestation, frozen, and micropunched to obtain the VMH. Total RNA was extracted, cDNA prepared, and SYBR Green qPCR was performed. In the VMH, expression of five genes were reduced on day 21 of gestation compared to day 12 (Chrna6, Drd5, Gabrr2, Prokr2, and Ppyr1 whereas Chat, Chrm5, Drd4, Gabra5, Gabrg2, LOC289606, Nmu5r2, and Npy5r expression was elevated. Five genes were chosen to be validated in an additional experiment based on their known involvement in maternal behavior onset. This experiment confirmed that gene expression for both the CCK-A receptor and the GABAAR γ2 receptor increases at the end of pregnancy. In general, these results identify genes possibly involved in the establishment of the maternal brain in rats and indicate possible new genes to be investigated.

  13. Classification across gene expression microarray studies

    Directory of Open Access Journals (Sweden)

    Kuner Ruprecht

    2009-12-01

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

  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. Gene expression analysis of flax seed development.

    Science.gov (United States)

    Venglat, Prakash; Xiang, Daoquan; Qiu, Shuqing; Stone, Sandra L; Tibiche, Chabane; Cram, Dustin; Alting-Mees, Michelle; Nowak, Jacek; Cloutier, Sylvie; Deyholos, Michael; Bekkaoui, Faouzi; Sharpe, Andrew; Wang, Edwin; Rowland, Gordon; Selvaraj, Gopalan; Datla, Raju

    2011-04-29

    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. 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. We have developed a foundational database of expressed sequences and collection of plasmid clones that comprise even low-expressed genes such as

  16. Gene expression profiles in skeletal muscle after gene electrotransfer

    DEFF Research Database (Denmark)

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

    2007-01-01

    ) 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...... 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...

  17. Isolation, identification and expression analysis of salt-induced genes in Suaeda maritima, a natural halophyte, using PCR-based suppression subtractive hybridization

    Directory of Open Access Journals (Sweden)

    Sahu Binod B

    2009-06-01

    Full Text Available Abstract Background Despite wealth of information generated on salt tolerance mechanism, its basics still remain elusive. Thus, there is a need of continued effort to understand the salt tolerance mechanism using suitable biotechnological techniques and test plants (species to enable development of salt tolerant cultivars of interest. Therefore, the present study was undertaken to generate information on salt stress responsive genes in a natural halophyte, Suaeda maritima, using PCR-based suppression subtractive hybridization (PCR-SSH technique. Results Forward and reverse SSH cDNA libraries were constructed after exposing the young plants to 425 mM NaCl for 24 h. From the forward SSH cDNA library, 429 high quality ESTs were obtained. BLASTX search and TIGR assembler programme revealed overexpression of 167 unigenes comprising 89 singletons and 78 contigs with ESTs redundancy of 81.8%. Among the unigenes, 32.5% were found to be of special interest, indicating novel function of these genes with regard to salt tolerance. Literature search for the known unigenes revealed that only 17 of them were salt-inducible. A comparative analysis of the existing SSH cDNA libraries for NaCl stress in plants showed that only a few overexpressing unigenes were common in them. Moreover, the present study also showed increased expression of phosphoethanolamine N-methyltransferase gene, indicating the possible accumulation of a much studied osmoticum, glycinebetaine, in halophyte under salt stress. Functional categorization of the proteins as per the Munich database in general revealed that salt tolerance could be largely determined by the proteins involved in transcription, signal transduction, protein activity regulation and cell differentiation and organogenesis. Conclusion The study provided a clear indication of possible vital role of glycinebetaine in the salt tolerance process in S. maritima. However, the salt-induced expression of a large number of genes

  18. Isolation, identification and expression analysis of salt-induced genes in Suaeda maritima, a natural halophyte, using PCR-based suppression subtractive hybridization.

    Science.gov (United States)

    Sahu, Binod B; Shaw, Birendra P

    2009-06-05

    Despite wealth of information generated on salt tolerance mechanism, its basics still remain elusive. Thus, there is a need of continued effort to understand the salt tolerance mechanism using suitable biotechnological techniques and test plants (species) to enable development of salt tolerant cultivars of interest. Therefore, the present study was undertaken to generate information on salt stress responsive genes in a natural halophyte, Suaeda maritima, using PCR-based suppression subtractive hybridization (PCR-SSH) technique. Forward and reverse SSH cDNA libraries were constructed after exposing the young plants to 425 mM NaCl for 24 h. From the forward SSH cDNA library, 429 high quality ESTs were obtained. BLASTX search and TIGR assembler programme revealed overexpression of 167 unigenes comprising 89 singletons and 78 contigs with ESTs redundancy of 81.8%. Among the unigenes, 32.5% were found to be of special interest, indicating novel function of these genes with regard to salt tolerance. Literature search for the known unigenes revealed that only 17 of them were salt-inducible. A comparative analysis of the existing SSH cDNA libraries for NaCl stress in plants showed that only a few overexpressing unigenes were common in them. Moreover, the present study also showed increased expression of phosphoethanolamine N-methyltransferase gene, indicating the possible accumulation of a much studied osmoticum, glycinebetaine, in halophyte under salt stress. Functional categorization of the proteins as per the Munich database in general revealed that salt tolerance could be largely determined by the proteins involved in transcription, signal transduction, protein activity regulation and cell differentiation and organogenesis. The study provided a clear indication of possible vital role of glycinebetaine in the salt tolerance process in S. maritima. However, the salt-induced expression of a large number of genes involved in a wide range of cellular functions was

  19. The RNA-Seq based high resolution gene expression atlas of chickpea (Cicer arietinum L.) reveals dynamic spatio-temporal changes associated with growth and development.

    Science.gov (United States)

    Kudapa, Himabindu; Garg, Vanika; Chitikineni, Annapurna; Varshney, Rajeev K

    2018-04-10

    Chickpea is one of the world's largest cultivated food legume and is an excellent source of high-quality protein to the human diet. Plant growth and development are controlled by programmed expression of a suite of genes at the given time, stage and tissue. Understanding how the underlying genome sequence translates into specific plant phenotypes at key developmental stages, information on gene expression patterns is crucial. Here we present a comprehensive Cicer arietinum Gene Expression Atlas (CaGEA) across the plant developmental stages and organs covering the entire life cycle of chickpea. One of the widely used drought tolerant cultivar, ICC 4958 has been used to generate RNA-Seq data from 27 samples at five major developmental stages of the plant. A total of 816 million raw reads were generated and of these, 794 million filtered reads after QC were subjected to downstream analysis. A total of 15,947 unique number of differentially expressed genes across different pairwise tissue combinations were identified. Significant differences in gene expression patterns contributing in the process of flowering, nodulation, seed and root development were inferred in this study. Furthermore, differentially expressed candidate genes from "QTL-hotspot" region associated with drought stress response in chickpea were validated. This article is protected by copyright. All rights reserved.

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

    Science.gov (United States)

    Hammoudeh, Nour; Kweider, Mahmoud; Abbady, Abdul-Qader; Soukkarieh, Chadi

    2014-01-01

    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.

  1. [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.

  2. Rice Expression Database (RED): An integrated RNA-Seq-derived gene expression database for rice.

    Science.gov (United States)

    Xia, Lin; Zou, Dong; Sang, Jian; Xu, Xingjian; Yin, Hongyan; Li, Mengwei; Wu, Shuangyang; Hu, Songnian; Hao, Lili; Zhang, Zhang

    2017-05-20

    Rice is one of the most important stable food as well as a monocotyledonous model organism for the plant research community. Here, we present RED (Rice Expression Database; http://expression.ic4r.org), an integrated database of rice gene expression profiles derived entirely from RNA-Seq data. RED features a comprehensive collection of 284 high-quality RNA-Seq experiments, integrates a large number of gene expression profiles and covers a wide range of rice growth stages as well as various treatments. Based on massive expression profiles, RED provides a list of housekeeping and tissue-specific genes and dynamically constructs co-expression networks for gene(s) of interest. Besides, it provides user-friendly web interfaces for querying, browsing and visualizing expression profiles of concerned genes. Together, as a core resource in BIG Data Center, RED bears great utility for characterizing the function of rice genes and better understanding important biological processes and mechanisms underlying complex agronomic traits in rice. Copyright © 2017 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.

  3. The Physcomitrella patens System for Transient Gene Expression Assays.

    Science.gov (United States)

    Thévenin, Johanne; Xu, Wenjia; Vaisman, Louise; Lepiniec, Loïc; Dubreucq, Bertrand; Dubos, Christian

    2016-01-01

    Transient expression assays are valuable techniques to study in vivo the transcriptional regulation of gene expression. These methods allow to assess the transcriptional properties of a given transcription factor (TF) or a complex of regulatory proteins against specific DNA motifs, called cis-regulatory elements. Here, we describe a fast, efficient, and reliable method based on the use of Physcomitrella patens protoplasts that allows the study of gene expression in a qualitative and quantitative manner by combining the advantage of GFP (green fluorescent protein) as a marker of promoter activity with flow cytometry for accurate measurement of fluorescence in individual cells.

  4. Field approach to three-dimensional gene expression pattern characterization

    Science.gov (United States)

    Costa, L. da F.; Travençolo, B. A. N.; Azeredo, A.; Beletti, M. E.; Müller, G. B.; Rasskin-Gutman, D.; Sternik, G.; Ibañes, M.; Izpisúa-Belmonte, J. C.

    2005-04-01

    We present a vector field method for obtaining the spatial organization of three-dimensional patterns of gene expression based on gradients and lines of force obtained by numerical integration. The convergence of these lines of force in local maxima are centers of gene expression, providing a natural and powerful framework to characterize the organization and dynamics of biological structures. We apply this methodology to analyze the expression pattern of the enhanced green fluorescent protein (EGFP) driven by the promoter of light chain myosin II during zebrafish heart formation.

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

    Science.gov (United States)

    Holec, Matěj; Kuželka, Ondřej; Železný, Filip

    2015-10-28

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

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

    Directory of Open Access Journals (Sweden)

    Hackett Perry B

    2006-06-01

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

  7. Serial Expression Analysis: a web tool for the analysis of serial gene expression data

    Science.gov (United States)

    Nueda, Maria José; Carbonell, José; Medina, Ignacio; Dopazo, Joaquín; Conesa, Ana

    2010-01-01

    Serial transcriptomics experiments investigate the dynamics of gene expression changes associated with a quantitative variable such as time or dosage. The statistical analysis of these data implies the study of global and gene-specific expression trends, the identification of significant serial changes, the comparison of expression profiles and the assessment of transcriptional changes in terms of cellular processes. We have created the SEA (Serial Expression Analysis) suite to provide a complete web-based resource for the analysis of serial transcriptomics data. SEA offers five different algorithms based on univariate, multivariate and functional profiling strategies framed within a user-friendly interface and a project-oriented architecture to facilitate the analysis of serial gene expression data sets from different perspectives. SEA is available at sea.bioinfo.cipf.es. PMID:20525784

  8. Mapping in an apple (Malus x domestica) F1 segregating population based on physical clustering of differentially expressed genes

    Science.gov (United States)

    Background: Apple tree breeding is slow and difficult due to long generation times, self incompatibility, and complex genetics. The identification of molecular markers linked to traits of interest is a way to expedite the breeding process. In the present study, we aimed to identify genes whose stead...

  9. Differential testicular gene expression in seasonal fertility

    Science.gov (United States)

    Maywood, Elizabeth S.; Chahad-Ehlers, Samira; Garabette, Martine L.; Pritchard, Claire; Underhill, Phillip; Greenfield, Andrew; Ebling, Francis J. P.; Kyriacou, Charalambos P.; Hastings, Michael H.; Reddy, Akhilesh B.

    2012-01-01

    Spermatogenesis is an essential precursor for successful sexual reproduction. Recently, there has been an expansion in our knowledge of the genes associated with particular stages of normal, physiological testicular development and pubertal activation. What has been lacking, however, is an understanding of those genes that are involved in specifically regulating sperm production, rather than in maturation and elaboration of the testis as an organ. By utilising the reversible (seasonal) fertility of the Syrian hamster as a model system, we sought to discover genes which are specifically involved in turning off sperm production and not in tissue specification and/or maturation. Using gene expression microarrays and in situ hybridisation in hamsters and genetically infertile mice, we have identified a variety of known and novel factors involved in reversible, transcriptional, translational and post-translational control of testicular function, as well those involved in cell division and macromolecular metabolism. The novel genes uncovered could be potential targets for therapies against fertility disorders. PMID:19346449

  10. Changes in skeletal muscle gene expression following clenbuterol administration

    Science.gov (United States)

    Spurlock, Diane M; McDaneld, Tara G; McIntyre, Lauren M

    2006-01-01

    Background Beta-adrenergic receptor agonists (BA) induce skeletal muscle hypertrophy, yet specific mechanisms that lead to this effect are not well understood. The objective of this research was to identify novel genes and physiological pathways that potentially facilitate BA induced skeletal muscle growth. The Affymetrix platform was utilized to identify gene expression changes in mouse skeletal muscle 24 hours and 10 days after administration of the BA clenbuterol. Results Administration of clenbuterol stimulated anabolic activity, as indicated by decreased blood urea nitrogen (BUN; P clenbuterol treatment. A total of 22,605 probesets were evaluated with 52 probesets defined as differentially expressed based on a false discovery rate of 10%. Differential mRNA abundance of four of these genes was validated in an independent experiment by quantitative PCR. Functional characterization of differentially expressed genes revealed several categories that participate in biological processes important to skeletal muscle growth, including regulators of transcription and translation, mediators of cell-signalling pathways, and genes involved in polyamine metabolism. Conclusion Global evaluation of gene expression after administration of clenbuterol identified changes in gene expression and overrepresented functional categories of genes that may regulate BA-induced muscle hypertrophy. Changes in mRNA abundance of multiple genes associated with myogenic differentiation may indicate an important effect of BA on proliferation, differentiation, and/or recruitment of satellite cells into muscle fibers to promote muscle hypertrophy. Increased mRNA abundance of genes involved in the initiation of translation suggests that increased levels of protein synthesis often associated with BA administration may result from a general up-regulation of translational initiators. Additionally, numerous other genes and physiological pathways were identified that will be important targets for

  11. GEM-TREND: a web tool for gene expression data mining toward relevant network discovery.

    Science.gov (United States)

    Feng, Chunlai; Araki, Michihiro; Kunimoto, Ryo; Tamon, Akiko; Makiguchi, Hiroki; Niijima, Satoshi; Tsujimoto, Gozoh; Okuno, Yasushi

    2009-09-03

    DNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database. GEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations are dynamically

  12. USAGE: a web-based approach towards the analysis of SAGE data. Serial Analysis of Gene Expression

    NARCIS (Netherlands)

    van Kampen, A. H.; van Schaik, B. D.; Pauws, E.; Michiels, E. M.; Ruijter, J. M.; Caron, H. N.; Versteeg, R.; Heisterkamp, S. H.; Leunissen, J. A.; Baas, F.; van der Mee, M.

    2000-01-01

    MOTIVATION: SAGE enables the determination of genome-wide mRNA expression profiles. A comprehensive analysis of SAGE data requires software, which integrates (statistical) data analysis methods with a database system. Furthermore, to facilitate data sharing between users, the application should

  13. A roadmap for zinc trafficking in the developing barley grain based on laser capture microdissection and gene expression profiling

    DEFF Research Database (Denmark)

    Tauris, Birgitte; Borg, Søren; Gregersen, Per L

    2009-01-01

    Nutrients destined for the developing cereal grain encounter several restricting barriers on their path towards their final storage sites in the grain. In order to identify transporters and chelating agents that may be involved in transport and deposition of zinc in the barley grain, expression...

  14. 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

    Many cancer-associated somatic copy number alterations (SCNAs) are known. Currently, one of the challenges is to identify the molecular downstream effects of these variants. Although several SCNAs are known to change gene expression levels, it is not clear whether each individual SCNA affects gen...

  15. 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.

  16. Bayesian Modeling of MPSS Data: Gene Expression Analysis of Bovine Salmonella Infection

    OpenAIRE

    Dhavala, Soma S.; Datta, Sujay; Mallick, Bani K.; Carroll, Raymond J.; Khare, Sangeeta; Lawhon, Sara D.; Adams, L. Garry

    2010-01-01

    Massively Parallel Signature Sequencing (MPSS) is a high-throughput counting-based technology available for gene expression profiling. It produces output that is similar to Serial Analysis of Gene Expression (SAGE) and is ideal for building complex relational databases for gene expression. Our goal is to compare the in vivo global gene expression profiles of tissues infected with different strains of Salmonella obtained using the MPSS technology. In this article, we develop an exact ANOVA typ...

  17. Gene expression in early stage cervical cancer

    NARCIS (Netherlands)

    Biewenga, Petra; Buist, Marrije R.; Moerland, Perry D.; van Thernaat, Emiel Ver Loren; van Kampen, Antoine H. C.; ten Kate, Fiebo J. W.; Baas, Frank

    2008-01-01

    Objective. Pelvic lymph node metastases are the main prognostic factor for survival in early stage cervical cancer, yet accurate detection methods before surgery are lacking. In this study, we examined whether gene expression profiling can predict the presence of lymph node metastasis in early stage

  18. Identification of genes showing differential expression profile

    Indian Academy of Sciences (India)

    Suppression subtractive hybridization was used to identify genes showing differential expression profile associated withgrowth rate in skeletal muscle tissue of Landrace weanling pig. Two subtracted cDNA populations were generated from mus-culus longissimus muscle tissues of selected pigs with extreme expected ...

  19. Identification of genes showing differential expression profile ...

    Indian Academy of Sciences (India)

    Abstract. Suppression subtractive hybridization was used to identify genes showing differential expression profile associated with growth rate in skeletal muscle tissue of Landrace weanling pig. Two subtracted cDNA populations were generated from mus- culus longissimus muscle tissues of selected pigs with extreme ...

  20. Gene Expression and Microarray Investigation of Dendrobium ...

    African Journals Online (AJOL)

    diet. The rats were continuously fed for 16 months, and blood glucose monitored by a glucose meter. One wild-type rat and 4 high- fat/high-glucose rats died during ..... therapy not only changed gene expression patterns in type 2 diabetes but also improved immune activity and reduced the likelihood of cancer development.

  1. Genomics analysis of genes expressed reveals differential ...

    African Journals Online (AJOL)

    Genomics analysis of genes expressed reveals differential responses to low chronic nitrogen stress in maize. ... Most induced clones were largely involved in various metabolism processes including physiological process, organelle regulation of biological process, nutrient reservoir activity, transcription regulator activity and ...

  2. Global gene expression in Escherichia coli biofilms

    DEFF Research Database (Denmark)

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

    2003-01-01

    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...

  3. Identification of genes showing differential expression profile ...

    Indian Academy of Sciences (India)

    Suppression subtractive hybridization was used to identify genes showing differential expression profile associated withgrowth rate in skeletal muscle tissue of Landrace weanling pig. Two subtracted cDNA populations were generated from mus-culus longissimus muscle tissues of selected pigs with extreme expected ...

  4. 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

    genome and better biocomputational techniques have substantially improved the assignment of differentially expressed SAGE "tags" to human genes. These improvements have provided us with an opportunity to re-evaluate global gene expression in pancreatic cancer using existing SAGE libraries. SAGE libraries...... generated from six pancreatic cancers were compared to SAGE libraries generated from 11 non-neoplastic tissues. Compared to normal tissue libraries, we identified 453 SAGE tags as differentially expressed in pancreatic cancer, including 395 that mapped to known genes and 58 "uncharacterized" tags....... Of the 395 SAGE tags assigned to known genes, 223 were overexpressed in pancreatic cancer, and 172 were underexpressed. In order to map the 58 uncharacterized differentially expressed SAGE tags to genes, we used a newly developed resource called TAGmapper (http://tagmapper.ibioinformatics.org), to identify...

  5. Genetic architecture of gene expression in ovine skeletal muscle.

    Science.gov (United States)

    Kogelman, Lisette J A; Byrne, Keren; Vuocolo, Tony; Watson-Haigh, Nathan S; Kadarmideen, Haja N; Kijas, James W; Oddy, Hutton V; Gardner, Graham E; Gondro, Cedric; Tellam, Ross L

    2011-12-15

    In livestock populations the genetic contribution to muscling is intensively monitored in the progeny of industry sires and used as a tool in selective breeding programs. The genes and pathways conferring this genetic merit are largely undefined. Genetic variation within a population has potential, amongst other mechanisms, to alter gene expression via cis- or trans-acting mechanisms in a manner that impacts the functional activities of specific pathways that contribute to muscling traits. By integrating sire-based genetic merit information for a muscling trait with progeny-based gene expression data we directly tested the hypothesis that there is genetic structure in the gene expression program in ovine skeletal muscle. The genetic performance of six sires for a well defined muscling trait, longissimus lumborum muscle depth, was measured using extensive progeny testing and expressed as an Estimated Breeding Value by comparison with contemporary sires. Microarray gene expression data were obtained for longissimus lumborum samples taken from forty progeny of the six sires (4-8 progeny/sire). Initial unsupervised hierarchical clustering analysis revealed strong genetic architecture to the gene expression data, which also discriminated the sire-based Estimated Breeding Value for the trait. An integrated systems biology approach was then used to identify the major functional pathways contributing to the genetics of enhanced muscling by using both Estimated Breeding Value weighted gene co-expression network analysis and a differential gene co-expression network analysis. The modules of genes revealed by these analyses were enriched for a number of functional terms summarised as muscle sarcomere organisation and development, protein catabolism (proteosome), RNA processing, mitochondrial function and transcriptional regulation. This study has revealed strong genetic structure in the gene expression program within ovine longissimus lumborum muscle. The balance between

  6. Gene expression: The missing link in evolutionary computation

    Energy Technology Data Exchange (ETDEWEB)

    Kargupta, H.

    1997-09-01

    This paper points out that the traditional perspective of evolutionary computation may not provide the complete picture of evolutionary search. This paper focuses on gene expression-- transformations of representation (DNA->RNA->Protein) from a the perspective of relation construction. It decomposes the complex process of gene expression into several steps, namely (1) expression control of DNA base pairs, (2) alphabet transformations during transcription and translation, and (3) folding of the proteins from sequence representation to Euclidean space. Each of these steps is investigated on grounds of relation construction and search efficiency. At the end these pieces of the puzzle are put together to develope a possibly crude and cartoon computational description of gene expression.

  7. 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

  8. Comparative gene expression of intestinal metabolizing enzymes.

    Science.gov (United States)

    Shin, Ho-Chul; Kim, Hye-Ryoung; Cho, Hee-Jung; Yi, Hee; Cho, Soo-Min; Lee, Dong-Goo; Abd El-Aty, A M; Kim, Jin-Suk; Sun, Duxin; Amidon, Gordon L

    2009-11-01

    The purpose of this study was to compare the expression profiles of drug-metabolizing enzymes in the intestine of mouse, rat and human. Total RNA was isolated from the duodenum and the mRNA expression was measured using Affymetrix GeneChip oligonucleotide arrays. Detected genes from the intestine of mouse, rat and human were ca. 60% of 22690 sequences, 40% of 8739 and 47% of 12559, respectively. Total genes of metabolizing enzymes subjected in this study were 95, 33 and 68 genes in mouse, rat and human, respectively. Of phase I enzymes, the mouse exhibited abundant gene expressions for Cyp3a25, Cyp4v3, Cyp2d26, followed by Cyp2b20, Cyp2c65 and Cyp4f14, whereas, the rat showed higher expression profiles of Cyp3a9, Cyp2b19, Cyp4f1, Cyp17a1, Cyp2d18, Cyp27a1 and Cyp4f6. However, the highly expressed P450 enzymes were CYP3A4, CYP3A5, CYP4F3, CYP2C18, CYP2C9, CYP2D6, CYP3A7, CYP11B1 and CYP2B6 in the human. For phase II enzymes, glucuronosyltransferase Ugt1a6, glutathione S-transferases Gstp1, Gstm3 and Gsta2, sulfotransferase Sult1b1 and acyltransferase Dgat1 were highly expressed in the mouse. The rat revealed predominant expression of glucuronosyltransferases Ugt1a1 and Ugt1a7, sulfotransferase Sult1b1, acetyltransferase Dlat and acyltransferase Dgat1. On the other hand, in human, glucuronosyltransferases UGT2B15 and UGT2B17, glutathione S-transferases MGST3, GSTP1, GSTA2 and GSTM4, sulfotransferases ST1A3 and SULT1A2, acetyltransferases SAT1 and CRAT, and acyltransferase AGPAT2 were dominantly detected. Therefore, current data indicated substantial interspecies differences in the pattern of intestinal gene expression both for P450 enzymes and phase II drug-metabolizing enzymes. This genomic database is expected to improve our understanding of interspecies variations in estimating intestinal prehepatic clearance of oral drugs.

  9. Differential expression and interaction of host factors augment HIV-1 gene expression in neonatal mononuclear cells

    International Nuclear Information System (INIS)

    Sundaravaradan, Vasudha; Mehta, Roshni; Harris, David T.; Zack, Jerome A.; Ahmad, Nafees

    2010-01-01

    We have previously shown a higher level of HIV-1 replication and gene expression in neonatal (cord) blood mononuclear cells (CBMC) compared with adult blood cells (PBMC), which could be due to differential expression of host factors. We performed the gene expression profile of CBMC and PBMC and found that 8013 genes were expressed at higher levels in CBMC than PBMC and 8028 genes in PBMC than CBMC, including 1181 and 1414 genes upregulated after HIV-1 infection in CBMC and PBMC, respectively. Several transcription factors (NF-κB, E2F, HAT-1, TFIIE, Cdk9, Cyclin T1), signal transducers (STAT3, STAT5A) and cytokines (IL-1β, IL-6, IL-10) were upregulated in CBMC than PBMC, which are known to influence HIV-1 replication. In addition, a repressor of HIV-1 transcription, YY1, was down regulated in CBMC than PBMC and several matrix metalloproteinase (MMP-7, -12, -14) were significantly upregulated in HIV-1 infected CBMC than PBMC. Furthermore, we show that CBMC nuclear extracts interacted with a higher extent to HIV-1 LTR cis-acting sequences, including NF-κB, NFAT, AP1 and NF-IL6 compared with PBMC nuclear extracts and retroviral based short hairpin RNA (shRNA) for STAT3 and IL-6 down regulated their own and HIV-1 gene expression, signifying that these factors influenced differential HIV-1 gene expression in CBMC than PBMC.

  10. Patterns of expression of cell wall related genes in sugarcane

    Directory of Open Access Journals (Sweden)

    Lima D.U.

    2001-01-01

    Full Text Available Our search for genes related to cell wall metabolism in the sugarcane expressed sequence tag (SUCEST database (http://sucest.lbi.dcc.unicamp.br resulted in 3,283 reads (1% of the total reads which were grouped into 459 clusters (potential genes with an average of 7.1 reads per cluster. To more clearly display our correlation coefficients, we constructed surface maps which we used to investigate the relationship between cell wall genes and the sugarcane tissues libraries from which they came. The only significant correlations that we found between cell wall genes and/or their expression within particular libraries were neutral or synergetic. Genes related to cellulose biosynthesis were from the CesA family, and were found to be the most abundant cell wall related genes in the SUCEST database. We found that the highest number of CesA reads came from the root and stem libraries. The genes with the greatest number of reads were those involved in cell wall hydrolases (e.g. beta-1,3-glucanases, xyloglucan endo-beta-transglycosylase, beta-glucosidase and endo-beta-mannanase. Correlation analyses by surface mapping revealed that the expression of genes related to biosynthesis seems to be associated with the hydrolysis of hemicelluloses, pectin hydrolases being mainly associated with xyloglucan hydrolases. The patterns of cell wall related gene expression in sugarcane based on the number of reads per cluster reflected quite well the expected physiological characteristics of the tissues. This is the first work to provide a general view on plant cell wall metabolism through the expression of related genes in almost all the tissues of a plant at the same time. For example, developing flowers behaved similarly to both meristematic tissues and leaf-root transition zone tissues. Besides providing a basis for future research on the mechanisms of plant development which involve the cell wall, our findings will provide valuable tools for plant engineering in the

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    Meizhen eWang

    2016-01-01

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

  13. Gene expression profiling in autoimmune diseases

    DEFF Research Database (Denmark)

    Bovin, Lone Frier; Brynskov, Jørn; Hegedüs, Laszlo

    2007-01-01

    ) patients and healthy individuals were specific for the arthritic process or likewise altered in other chronic inflammatory diseases such as chronic autoimmune thyroiditis (Hashimoto's thyroiditis, HT) and inflammatory bowel disease (IBD). Using qPCR for 18 RA-discriminative genes, there were no significant......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...... immunoinflammatory diseases, but only if accompanied by pronounced systemic manifestations. This suggests that at least some of the genes activated in RA are predominantly or solely related to general and disease-nonspecific autoimmune processes...

  14. 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.

  15. NNAT and DIRAS3 genes are paternally expressed in pigs

    Directory of Open Access Journals (Sweden)

    Lei Ming-Gang

    2007-09-01

    Full Text Available Abstract Although expression and epigenetic differences of imprinted genes have been extensively characterised in man and the mouse, little is known on livestock species. In this study, the polymorphism-based approach was used to detect the imprinting status of NNAT and DIRAS3 genes in five heterozygous pigs (based on SNP of Large White and Meishan F1 hybrids. The results show that both genes were paternally expressed in all the tested tissues (heart, liver, spleen, lung, kidney, stomach, small intestine, skeletal muscle, fat, uterus, ovary and pituitary. In addition, the NNAT gene had two transcripts in all tested tissues, which is consistent with its counterpart in man and cattle.

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

    Science.gov (United States)

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

    2015-01-27

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

  17. 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. © The Author 2015. Published by Oxford University Press on