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Sample records for gene microarray study

  1. Gene expression studies using microarrays

    NARCIS (Netherlands)

    Burgess, Janette

    2001-01-01

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

  2. A salmonid EST genomic study: genes, duplications, phylogeny and microarrays

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    Brahmbhatt Sonal

    2008-11-01

    Full Text Available Abstract Background Salmonids are of interest because of their relatively recent genome duplication, and their extensive use in wild fisheries and aquaculture. A comprehensive gene list and a comparison of genes in some of the different species provide valuable genomic information for one of the most widely studied groups of fish. Results 298,304 expressed sequence tags (ESTs from Atlantic salmon (69% of the total, 11,664 chinook, 10,813 sockeye, 10,051 brook trout, 10,975 grayling, 8,630 lake whitefish, and 3,624 northern pike ESTs were obtained in this study and have been deposited into the public databases. Contigs were built and putative full-length Atlantic salmon clones have been identified. A database containing ESTs, assemblies, consensus sequences, open reading frames, gene predictions and putative annotation is available. The overall similarity between Atlantic salmon ESTs and those of rainbow trout, chinook, sockeye, brook trout, grayling, lake whitefish, northern pike and rainbow smelt is 93.4, 94.2, 94.6, 94.4, 92.5, 91.7, 89.6, and 86.2% respectively. An analysis of 78 transcript sets show Salmo as a sister group to Oncorhynchus and Salvelinus within Salmoninae, and Thymallinae as a sister group to Salmoninae and Coregoninae within Salmonidae. Extensive gene duplication is consistent with a genome duplication in the common ancestor of salmonids. Using all of the available EST data, a new expanded salmonid cDNA microarray of 32,000 features was created. Cross-species hybridizations to this cDNA microarray indicate that this resource will be useful for studies of all 68 salmonid species. Conclusion An extensive collection and analysis of salmonid RNA putative transcripts indicate that Pacific salmon, Atlantic salmon and charr are 94–96% similar while the more distant whitefish, grayling, pike and smelt are 93, 92, 89 and 86% similar to salmon. The salmonid transcriptome reveals a complex history of gene duplication that is

  3. Are Gene Expression Microarray Analyses Reliable? A Review of Studies of Retinoic Acid Responsive Genes

    Institute of Scientific and Technical Information of China (English)

    PeterJ.vanderSpek; AndreasKremer; LynnMurry; MichaelG.Walker

    2003-01-01

    Microarray analyses of gene expression are widely used,but reports of the same analyses by different groups give widely divergent results,and raise questions regarding reproducibility and reliability.We take as an example recent published reports on microarray experiments that were designed to identify retinoic acid responsive genes.These reports show substantial differences in their results.In this article,we review the methodology,results,and potential causes of differences in these applications of microarrays.Finally,we suggest practices to improve the reliability and reproducibility of microarray experiments.

  4. Are Gene Expression Microarray Analyses Reliable? A Review of Studies of Retinoic Acid Responsive Genes

    Institute of Scientific and Technical Information of China (English)

    Peter J. van der Spek; Andreas Kremer; Lynn Murry; Michael G. Walker

    2003-01-01

    Microarray analyses of gene expression are widely used, but reports of the same analyses by different groups give widely divergent results, and raise questions regarding reproducibility and reliability. We take as an example recent published reports on microarray experiments that were designed to identify retinoic acid responsive genes. These reports show substantial differences in their results. In this article, we review the methodology, results, and potential causes of differences in these applications of microarrays. Finally, we suggest practices to improve the reliability and reproducibility of microarray experiments.

  5. A Combinatory Approach for Selecting Prognostic Genes in Microarray Studies of Tumour Survivals

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    Qihua Tan

    2009-01-01

    Full Text Available Different from significant gene expression analysis which looks for genes that are differentially regulated, feature selection in the microarray-based prognostic gene expression analysis aims at finding a subset of marker genes that are not only differentially expressed but also informative for prediction. Unfortunately feature selection in literature of microarray study is predominated by the simple heuristic univariate gene filter paradigm that selects differentially expressed genes according to their statistical significances. We introduce a combinatory feature selection strategy that integrates differential gene expression analysis with the Gram-Schmidt process to identify prognostic genes that are both statistically significant and highly informative for predicting tumour survival outcomes. Empirical application to leukemia and ovarian cancer survival data through-within- and cross-study validations shows that the feature space can be largely reduced while achieving improved testing performances.

  6. Using a cDNA microarray to study cellular gene expression altered by Mycobacterium tuberculosis

    Institute of Scientific and Technical Information of China (English)

    徐永忠; 谢建平; 李瑶; 乐军; 陈建平; 淳于利娟; 王洪海

    2003-01-01

    Objective To examine the global effects of Mycobacterium tuberculosis (M.tuberculosis) infection on macrophages. Methods The gene expression profiling of macrophage U937, in response to infection with M.tuberculosis H37Ra, was monitored using a high-density cDNA microarray. Results M.tuberculosis infection caused 463 differentially expressed genes, of which 366 genes are known genes registered in the Gene Bank. These genes function in various cellular processes including intracellular signalling, cytoskeletal rearrangement, apoptosis, transcriptional regulation, cell surface receptors, cell-mediated immunity as well as a variety of cellular metabolic pathways, and may play key roles in M.tuberculosis infection and intracellular survival. Conclusions M.tuberculosis infection alters the expression of host-cell genes, and these genes will provide a foundation for understanding the infection process of M.tuberculosis. The cDNA microarray is a powerful tool for studying pathogen-host cell interaction.

  7. Learning from microarray interlaboratory studies: measures of precision for gene expression

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    Reid Laura H

    2009-04-01

    Full Text Available Abstract Background The ability to demonstrate the reproducibility of gene expression microarray results is a critical consideration for the use of microarray technology in clinical applications. While studies have asserted that microarray data can be "highly reproducible" under given conditions, there is little ability to quantitatively compare amongst the various metrics and terminology used to characterize and express measurement performance. Use of standardized conceptual tools can greatly facilitate communication among the user, developer, and regulator stakeholders of the microarray community. While shaped by less highly multiplexed systems, measurement science (metrology is devoted to establishing a coherent and internationally recognized vocabulary and quantitative practice for the characterization of measurement processes. Results The two independent aspects of the metrological concept of "accuracy" are "trueness" (closeness of a measurement to an accepted reference value and "precision" (the closeness of measurement results to each other. A carefully designed collaborative study enables estimation of a variety of gene expression measurement precision metrics: repeatability, several flavors of intermediate precision, and reproducibility. The three 2004 Expression Analysis Pilot Proficiency Test collaborative studies, each with 13 to 16 participants, provide triplicate microarray measurements on each of two reference RNA pools. Using and modestly extending the consensus ISO 5725 documentary standard, we evaluate the metrological precision figures of merit for individual microarray signal measurement, building from calculations appropriate to single measurement processes, such as technical replicate expression values for individual probes on a microarray, to the estimation and display of precision functions representing all of the probes in a given platform. Conclusion With only modest extensions, the established metrological framework

  8. Study with microarrays of the differential gene expression profiles of glioblastoma

    Institute of Scientific and Technical Information of China (English)

    YANG Zhi-lin; XU Ru-xiang; JIANG Xiao-dan; KE Yi-quan; LUO Cheng-yi; JIN Ying; HU Gen-xi

    2001-01-01

    Objective: This study aims to screen the differentially expressed genes of glioblastoma using microarray technique. Methods: Specimens of glioblastoma and normal brain tissue were obtained from pathologically confirmed patients.A cDNA microarray comprising 14 000 clones covering the whole sets of the retro-transcriptional products of the mRNAs of various gliomas and those of normal brain tissues was established, with which the differences in gene expression between glioblastoma and normal brain tissues were investigated. Results: It was found that 94 genes were more than 3-fold differentially expressed with 298 more than doubled in the glioblastoma in comparison with the normal brain tissue. Some over-expressed genes in the glioblastoma were scarcely expressed in normal brain tissues, and several novel genes that may have biological relevance in the process ofglioma genesis were identified. Conclusion: Microarray technique combined with relevant cDNA repository can facilitate rapid large-scale identification of potential target genes for diagnosis and.therapy of glioma.

  9. Predicting survival outcomes using subsets of significant genes in prognostic marker studies with microarrays

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    Matsui Shigeyuki

    2006-03-01

    Full Text Available Abstract Background Genetic markers hold great promise for refining our ability to establish precise prognostic prediction for diseases. The development of comprehensive gene expression microarray technology has allowed the selection of relevant marker genes from a large pool of candidate genes in early-phased, developmental prognostic marker studies. The primary analytical task in such studies is to select a small fraction of relevant genes, typically from a list of significant genes, for further investigation in subsequent studies. Results We develop a methodology for predicting survival outcomes using subsets of significant genes in prognostic marker studies with microarrays. Key components in this methodology include building prediction models, assessing predictive performance of prediction models, and assessing significance of prediction results. As particular specifications, we assume Cox proportional hazard models with a compound covariate. For assessing predictive accuracy, we propose to use the cross-validated log partial likelihood. To assess significance of prediction results, we apply permutation procedures in cross-validated prediction. As an additional key component peculiar to prognostic prediction, we also consider incorporation of standard prognostic factors. The methodology is evaluated using both simulated and real data. Conclusion The developed methodology for prognostic prediction using a subset of significant genes can provide new insights based on predictive capability, possibly incorporating standard prognostic factors, in selecting a fraction of relevant genes for subsequent studies.

  10. Using microarrays to identify positional candidate genes for QTL: the case study of ACTH response in pigs

    DEFF Research Database (Denmark)

    Jouffe, Vincent; Rowe, Suzanne; Liaubet, Laurence

    2009-01-01

    of 237 differentially expressed cDNA clones in adrenal tissue from two pig breeds, before and after treatment with adrenocorticotropic hormone (ACTH) Microarray studies can supplement QTL studies by suggesting potential candidate genes in the QTL regions, which by themselves are too large to provide......Background: Microarray studies can supplement QTL studies by suggesting potential candidate. Microarray studies can supplement QTL studies by suggesting potential candidate genes in the QTL regions, which by themselves are too large to provide a limited selection of candidate genes. Here we provide...... a case study where we explore ways to integrate QTL data and microarray data for the pig, which has only a partial genome sequence. We outline various procedures to localize differentially expressed genes on the pig genome and link this with information on published QTL. The starting point is a set...

  11. A combined analysis of microarray gene expression studies of the human prefrontal cortex identifies genes implicated in schizophrenia.

    Science.gov (United States)

    Pérez-Santiago, Josué; Diez-Alarcia, Rebeca; Callado, Luis F; Zhang, Jin X; Chana, Gursharan; White, Cory H; Glatt, Stephen J; Tsuang, Ming T; Everall, Ian P; Meana, J Javier; Woelk, Christopher H

    2012-11-01

    Small cohort sizes and modest levels of gene expression changes in brain tissue have plagued the statistical approaches employed in microarray studies investigating the mechanism of schizophrenia. To combat these problems a combined analysis of six prior microarray studies was performed to facilitate the robust statistical analysis of gene expression data from the dorsolateral prefrontal cortex of 107 patients with schizophrenia and 118 healthy subjects. Multivariate permutation tests identified 144 genes that were differentially expressed between schizophrenia and control groups. Seventy of these genes were identified as differentially expressed in at least one component microarray study but none of these individual studies had the power to identify the remaining 74 genes, demonstrating the utility of a combined approach. Gene ontology terms and biological pathways that were significantly enriched for differentially expressed genes were related to neuronal cell-cell signaling, mesenchymal induction, and mitogen-activated protein kinase signaling, which have all previously been associated with the etiopathogenesis of schizophrenia. The differential expression of BAG3, C4B, EGR1, MT1X, NEUROD6, SST and S100A8 was confirmed by real-time quantitative PCR in an independent cohort using postmortem human prefrontal cortex samples. Comparison of gene expression between schizophrenic subjects with and without detectable levels of antipsychotics in their blood suggests that the modulation of MT1X and S100A8 may be the result of drug exposure. In conclusion, this combined analysis has resulted in a statistically robust identification of genes whose dysregulation may contribute to the mechanism of schizophrenia.

  12. Reproducibility-optimized test statistic for ranking genes in microarray studies.

    Science.gov (United States)

    Elo, Laura L; Filén, Sanna; Lahesmaa, Riitta; Aittokallio, Tero

    2008-01-01

    A principal goal of microarray studies is to identify the genes showing differential expression under distinct conditions. In such studies, the selection of an optimal test statistic is a crucial challenge, which depends on the type and amount of data under analysis. While previous studies on simulated or spike-in datasets do not provide practical guidance on how to choose the best method for a given real dataset, we introduce an enhanced reproducibility-optimization procedure, which enables the selection of a suitable gene- anking statistic directly from the data. In comparison with existing ranking methods, the reproducibilityoptimized statistic shows good performance consistently under various simulated conditions and on Affymetrix spike-in dataset. Further, the feasibility of the novel statistic is confirmed in a practical research setting using data from an in-house cDNA microarray study of asthma-related gene expression changes. These results suggest that the procedure facilitates the selection of an appropriate test statistic for a given dataset without relying on a priori assumptions, which may bias the findings and their interpretation. Moreover, the general reproducibilityoptimization procedure is not limited to detecting differential expression only but could be extended to a wide range of other applications as well.

  13. Association Study between BDNF Gene Polymorphisms and Autism by Three-Dimensional Gel-Based Microarray

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    Zuhong Lu

    2009-06-01

    Full Text Available Single nucleotide polymorphisms (SNPs are important markers which can be used in association studies searching for susceptible genes of complex diseases. High-throughput methods are needed for SNP genotyping in a large number of samples. In this study, we applied polyacrylamide gel-based microarray combined with dual-color hybridization for association study of four BDNF polymorphisms with autism. All the SNPs in both patients and controls could be analyzed quickly and correctly. Among four SNPs, only C270T polymorphism showed significant differences in the frequency of the allele (χ2 = 7.809, p = 0.005 and genotype (χ2 = 7.800, p = 0.020. In the haplotype association analysis, there was significant difference in global haplotype distribution between the groups (χ2 = 28.19,p = 3.44e-005. We suggest that BDNF has a possible role in the pathogenesis of autism. The study also show that the polyacrylamide gel-based microarray combined with dual-color hybridization is a rapid, simple and high-throughput method for SNPs genotyping, and can be used for association study of susceptible gene with disorders in large samples.

  14. Study on Wusan Granule Anti-tumor Related Target Gene Screened by Cdna Microarray

    Institute of Scientific and Technical Information of China (English)

    YOU Zi-li; SHI Jin-ping; CHEN Hai-hong

    2006-01-01

    To screen Wusan Granule anti-tumor related target gene using cDNA microarray technique, both mRNA from Lewis lung carcinoma tissues treated by Wusan Granule and untreated control are reversibly transcribed to prepare cDNA probes which are labeled by Cy5 and Cy3. Then, the probes are hybridized to the mice cDNA microarray type MGEC-20S. After hybridization, the cDNA microarray is scanned by ScanArray 3 000 scanner and the data is analyzed by ImaGene 3 software to screen the differentially expressed genes. There are 45 differentially expressed genes including 18 known genes and 27 unknown genes between the two groups, and among them, 20 elevated genes and 25 reduced genes are identified. Additionally, the genes related to invasion and metastasis of malignant carcinomas are down-regulated and the genes related to apoptosis are up-regulated. The cDNA microarray technique is a high-throughput approach to screen the Wusan Granule anti-tumor related target genes, which allow us to explore the molecular biological mechanism on a genomic scale.

  15. Identification of candidate genes in osteoporosis by integrated microarray analysis

    OpenAIRE

    Li, J J; Wang, B. Q.; Fei, Q.; Yang, Y; Li, D.

    2017-01-01

    Objectives In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. Methods We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed...

  16. Microarray studies on effects of Pneumocystis carinii infection on global gene expression in alveolar macrophages

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    Liao Chung-Ping

    2010-04-01

    Full Text Available Abstract Background Pneumocystis pneumonia is a common opportunistic disease in AIDS patients. The alveolar macrophage is an important effector cell in the clearance of Pneumocystis organisms by phagocytosis. However, both the number and phagocytic activity of alveolar macrophages are decreased in Pneumocystis infected hosts. To understand how Pneumocystis inactivates alveolar macrophages, Affymetrix GeneChip® RG-U34A DNA microarrays were used to study the difference in global gene expression in alveolar macrophages from uninfected and Pneumocystis carinii-infected Sprague-Dawley rats. Results Analyses of genes that were affected by Pneumocystis infection showed that many functions in the cells were affected. Antigen presentation, cell-mediated immune response, humoral immune response, and inflammatory response were most severely affected, followed by cellular movement, immune cell trafficking, immunological disease, cell-to-cell signaling and interaction, cell death, organ injury and abnormality, cell signaling, infectious disease, small molecular biochemistry, antimicrobial response, and free radical scavenging. Since rats must be immunosuppressed in order to develop Pneumocystis infection, alveolar macrophages from four rats of the same sex and age that were treated with dexamethasone for the entire eight weeks of the study period were also examined. With a filter of false-discovery rate less than 0.1 and fold change greater than 1.5, 200 genes were found to be up-regulated, and 144 genes were down-regulated by dexamethasone treatment. During Pneumocystis pneumonia, 115 genes were found to be up- and 137 were down-regulated with the same filtering criteria. The top ten genes up-regulated by Pneumocystis infection were Cxcl10, Spp1, S100A9, Rsad2, S100A8, Nos2, RT1-Bb, Lcn2, RT1-Db1, and Srgn with fold changes ranging between 12.33 and 5.34; and the top ten down-regulated ones were Lgals1, Psat1, Tbc1d23, Gsta1, Car5b, Xrcc5, Pdlim1, Alcam

  17. Cross-platform comparison of SYBR® Green real-time PCR with TaqMan PCR, microarrays and other gene expression measurement technologies evaluated in the MicroArray Quality Control (MAQC study

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    Dial Stacey L

    2008-07-01

    Full Text Available Abstract Background The MicroArray Quality Control (MAQC project evaluated the inter- and intra-platform reproducibility of seven microarray platforms and three quantitative gene expression assays in profiling the expression of two commercially available Reference RNA samples (Nat Biotechnol 24:1115-22, 2006. The tested microarrays were the platforms from Affymetrix, Agilent Technologies, Applied Biosystems, GE Healthcare, Illumina, Eppendorf and the National Cancer Institute, and quantitative gene expression assays included TaqMan® Gene Expression PCR Assay, Standardized (Sta RT-PCR™ and QuantiGene®. The data showed great consistency in gene expression measurements across different microarray platforms, different technologies and test sites. However, SYBR® Green real-time PCR, another common technique utilized by half of all real-time PCR users for gene expression measurement, was not addressed in the MAQC study. In the present study, we compared the performance of SYBR Green PCR with TaqMan PCR, microarrays and other quantitative technologies using the same two Reference RNA samples as the MAQC project. We assessed SYBR Green real-time PCR using commercially available RT2 Profiler™ PCR Arrays from SuperArray, containing primer pairs that have been experimentally validated to ensure gene-specificity and high amplification efficiency. Results The SYBR Green PCR Arrays exhibit good reproducibility among different users, PCR instruments and test sites. In addition, the SYBR Green PCR Arrays have the highest concordance with TaqMan PCR, and a high level of concordance with other quantitative methods and microarrays that were evaluated in this study in terms of fold-change correlation and overlap of lists of differentially expressed genes. Conclusion These data demonstrate that SYBR Green real-time PCR delivers highly comparable results in gene expression measurement with TaqMan PCR and other high-density microarrays.

  18. A Growth Curve Model with Fractional Polynomials for Analysing Incomplete Time-Course Data in Microarray Gene Expression Studies

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    Qihua Tan

    2011-01-01

    Full Text Available Identifying the various gene expression response patterns is a challenging issue in expression microarray time-course experiments. Due to heterogeneity in the regulatory reaction among thousands of genes tested, it is impossible to manually characterize a parametric form for each of the time-course pattern in a gene by gene manner. We introduce a growth curve model with fractional polynomials to automatically capture the various time-dependent expression patterns and meanwhile efficiently handle missing values due to incomplete observations. For each gene, our procedure compares the performances among fractional polynomial models with power terms from a set of fixed values that offer a wide range of curve shapes and suggests a best fitting model. After a limited simulation study, the model has been applied to our human in vivo irritated epidermis data with missing observations to investigate time-dependent transcriptional responses to a chemical irritant. Our method was able to identify the various nonlinear time-course expression trajectories. The integration of growth curves with fractional polynomials provides a flexible way to model different time-course patterns together with model selection and significant gene identification strategies that can be applied in microarray-based time-course gene expression experiments with missing observations.

  19. Extensive innate immune gene activation accompanies brain aging, increasing vulnerability to cognitive decline and neurodegeneration: a microarray study

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    Cribbs David H

    2012-07-01

    Full Text Available Abstract Background This study undertakes a systematic and comprehensive analysis of brain gene expression profiles of immune/inflammation-related genes in aging and Alzheimer’s disease (AD. Methods In a well-powered microarray study of young (20 to 59 years, aged (60 to 99 years, and AD (74 to 95 years cases, gene responses were assessed in the hippocampus, entorhinal cortex, superior frontal gyrus, and post-central gyrus. Results Several novel concepts emerge. First, immune/inflammation-related genes showed major changes in gene expression over the course of cognitively normal aging, with the extent of gene response far greater in aging than in AD. Of the 759 immune-related probesets interrogated on the microarray, approximately 40% were significantly altered in the SFG, PCG and HC with increasing age, with the majority upregulated (64 to 86%. In contrast, far fewer immune/inflammation genes were significantly changed in the transition to AD (approximately 6% of immune-related probesets, with gene responses primarily restricted to the SFG and HC. Second, relatively few significant changes in immune/inflammation genes were detected in the EC either in aging or AD, although many genes in the EC showed similar trends in responses as in the other brain regions. Third, immune/inflammation genes undergo gender-specific patterns of response in aging and AD, with the most pronounced differences emerging in aging. Finally, there was widespread upregulation of genes reflecting activation of microglia and perivascular macrophages in the aging brain, coupled with a downregulation of select factors (TOLLIP, fractalkine that when present curtail microglial/macrophage activation. Notably, essentially all pathways of the innate immune system were upregulated in aging, including numerous complement components, genes involved in toll-like receptor signaling and inflammasome signaling, as well as genes coding for immunoglobulin (Fc receptors and human

  20. The effect of oxythioquinox exposure on normal human mammary epithelial cell gene expression: A microarray analysis study

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    Weston Ainsley

    2004-09-01

    Full Text Available Abstract Background Inter-individual variation in normal human mammary epithelial cells in response to oxythioquinox (OTQ is reported. Gene expression signatures resulting from chemical exposures are generally created from analysis of exposures in rat, mouse or other genetically similar animal models, limiting information about inter-individual variations. This study focused on the effect of inter-individual variation in gene expression signatures. Methods Gene expression was studied in primary normal human mammary epithelial cells (NHMECs derived from four women undergoing reduction mammoplasty [Cooperative Human Tissue Network (National Cancer Institute and National Disease Research Interchange]. Gene transcription in each cell strain was analyzed using high-density oligonucleotide DNA microarrays (HuGeneFL, Affymetrix™ and changes in the expression of selected genes were verified by real-time polymerase chain reaction at extended time points (ABI. DNA microarrays were hybridized to materials prepared from total RNA that was collected after OTQ treatment for 15, 60 and 120 min. RNA was harvested from the vehicle control (DMSO at 120 min. The gene expression profile included all genes altered by at least a signal log ratio (SLR of ± 0.6 and p value ≤ 0.05 in three of four cell strains analyzed. Results RNA species were clustered in various patterns of expression highlighting genes with altered expression in one or more of the cell strains, including metabolic enzymes and transcription factors. Of the clustered RNA species, only 36 were found to be altered at one time point in three or more of the cell strains analyzed (13 up-regulated, 23 down-regulated. Cluster analysis examined the effects of OTQ on the cells with specific p53 polymorphisms. The two strains expressing the major variant of p53 had 83 common genes altered (35 increased, 48 decreased at one or more time point by at least a 0.6 signal log ratio (SLR. The intermediate variant

  1. A control study to evaluate a computer-based microarray experiment design recommendation system for gene-regulation pathways discovery.

    Science.gov (United States)

    Yoo, Changwon; Cooper, Gregory F; Schmidt, Martin

    2006-04-01

    The main topic of this paper is evaluating a system that uses the expected value of experimentation for discovering causal pathways in gene expression data. By experimentation we mean both interventions (e.g., a gene knock-out experiment) and observations (e.g., passively observing the expression level of a "wild-type" gene). We introduce a system called GEEVE (causal discovery in Gene Expression data using Expected Value of Experimentation), which implements expected value of experimentation in discovering causal pathways using gene expression data. GEEVE provides the following assistance, which is intended to help biologists in their quest to discover gene-regulation pathways: Recommending which experiments to perform (with a focus on "knock-out" experiments) using an expected value of experimentation (EVE) method. Recommending the number of measurements (observational and experimental) to include in the experimental design, again using an EVE method. Providing a Bayesian analysis that combines prior knowledge with the results of recent microarray experimental results to derive posterior probabilities of gene regulation relationships. In recommending which experiments to perform (and how many times to repeat them) the EVE approach considers the biologist's preferences for which genes to focus the discovery process. Also, since exact EVE calculations are exponential in time, GEEVE incorporates approximation methods. GEEVE is able to combine data from knock-out experiments with data from wild-type experiments to suggest additional experiments to perform and then to analyze the results of those microarray experimental results. It models the possibility that unmeasured (latent) variables may be responsible for some of the statistical associations among the expression levels of the genes under study. To evaluate the GEEVE system, we used a gene expression simulator to generate data from specified models of gene regulation. Using the simulator, we evaluated the GEEVE

  2. THE VALIDATION OF THE RESULTS OF MICROARRAY STUDIES OF ASSOCIATION BETWEEN GENE POLYMORPHISMS AND THE FREQUENCY OF RADIATION EXPOSURE MARKERS

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    M. V. Khalyuzova

    2014-01-01

    Full Text Available The results from the selective validation research into the association between genetic polymorphisms and the frequency of cytogenetic abnormalities on a large independent sample are analyzed. These polymorphisms have been identified previously during own microarray studies. It has been shown an association with the frequency of dicentric and ring chromosomes induced by radiation exposure. The study was conducted among Siberian Group of Chemical Enterprises healthy employees (n = 573 exposed to professional irradiation in a dose range of 40–400 mSv. We have found that 5 SNP are confirmed to be associated with the frequency of dicentric and ring: INSR rs1051690 – insulin receptor gene; WRNrs2725349 – Werner syndrome gene, RecQ helicase-like; VCAM1 rs1041163 – vascular cell adhesion molecule 1 gene; PCTP rs2114443 – phosphatidylcholine transfer protein gene; TNKS rs7462102 – tankyrase gene; TRF1-interacting ankyrin-related ADP-ribose polymerase. IGF1 rs2373721 – insulin-like growth factor 1 gene has not confirmed to be associated with the frequency of dicentric and ring chromosomes.

  3. Concordance analysis of microarray studies identifies representative gene expression changes in Parkinson's disease: a comparison of 33 human and animal studies.

    Science.gov (United States)

    Oerton, Erin; Bender, Andreas

    2017-03-23

    As the popularity of transcriptomic analysis has grown, the reported lack of concordance between different studies of the same condition has become a growing concern, raising questions as to the representativeness of different study types, such as non-human disease models or studies of surrogate tissues, to gene expression in the human condition. In a comparison of 33 microarray studies of Parkinson's disease, correlation and clustering analyses were used to determine the factors influencing concordance between studies, including agreement between different tissue types, different microarray platforms, and between neurotoxic and genetic disease models and human Parkinson's disease. Concordance over all studies is low, with correlation of only 0.05 between differential gene expression signatures on average, but increases within human patients and studies of the same tissue type, rising to 0.38 for studies of human substantia nigra. Agreement of animal models, however, is dependent on model type. Studies of brain tissue from Parkinson's disease patients (specifically the substantia nigra) form a distinct group, showing patterns of differential gene expression noticeably different from that in non-brain tissues and animal models of Parkinson's disease; while comparison with other brain diseases (Alzheimer's disease and brain cancer) suggests that the mixed study types display a general signal of neurodegenerative disease. A meta-analysis of these 33 microarray studies demonstrates the greater ability of studies in humans and highly-affected tissues to identify genes previously known to be associated with Parkinson's disease. The observed clustering and concordance results suggest the existence of a 'characteristic' signal of Parkinson's disease found in significantly affected human tissues in humans. These results help to account for the consistency (or lack thereof) so far observed in microarray studies of Parkinson's disease, and act as a guide to the selection of

  4. The Beta-Binomial Distribution for Estimating the Number of False Rejections in Microarray Gene Expression Studies.

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    Hunt, Daniel L; Cheng, Cheng; Pounds, Stanley

    2009-03-15

    In differential expression analysis of microarray data, it is common to assume independence among null hypotheses (and thus gene expression levels). The independence assumption implies that the number of false rejections V follows a binomial distribution and leads to an estimator of the empirical false discovery rate (eFDR). The number of false rejections V is modeled with the beta-binomial distribution. An estimator of the beta-binomial false discovery rate (bbFDR) is then derived. This approach accounts for how the correlation among non-differentially expressed genes influences the distribution of V. Permutations are used to generate the observed values for V under the null hypotheses and a beta-binomial distribution is fit to the values of V. The bbFDR estimator is compared to the eFDR estimator in simulation studies of correlated non-differentially expressed genes and is found to outperform the eFDR for certain scenarios. As an example, this method is also used to perform an analysis that compares the gene expression of soft tissue sarcoma samples to normal tissue samples.

  5. A newly designed 45 to 60 mer oligonucleotide Agilent platform microarray for global gene expression studies of Synechocystis PCC6803: example salt stress experiment

    NARCIS (Netherlands)

    Aguirre von Wobeser, E.; Huisman, J.; Ibelings, B.; Matthijs, H.C.P.; Matthijs, H.C.P.

    2005-01-01

    A newly designed 45 to 60 mer oligonucleotide Agilent platform microarray for global gene expression studies of Synechocystis PCC6803: example salt stress experiment Eneas Aguirre-von-Wobeser 1, Jef Huisman1, Bas Ibelings2 and Hans C.P. Matthijs1 1 Universiteit van Amsterdam, Amsterdam, The Netherla

  6. Parvalbumin-Neurons of the Ventrolateral Hypothalamic Parvafox Nucleus Receive a Glycinergic Input: A Gene-Microarray Study

    Science.gov (United States)

    Szabolcsi, Viktoria; Albisetti, Gioele W.; Celio, Marco R.

    2017-01-01

    The ventrolateral hypothalamic parvafox (formerly called PV1-Foxb1) nucleus is an anatomical entity of recent discovery and unknown function. With a view to gaining an insight into its putative functional role(s), we conducted a gene-microarray analysis and, armed with the forthcoming data, controlled the results with the Allen databases and the murine BrainStars (B*) database. The parvafox nucleus was specifically sampled by laser-capture microdissection and the transcriptome was subjected to a microarray analysis on Affymetrix chips. Eighty-two relevant genes were found to be potentially more expressed in this brain region than in either the cerebral cortex or the hippocampus. When the expression patterns of these genes were counterchecked in the Allen-Database of in-situ hybridizations and in the B*-microarray database, their localization in the parvafox region was confirmed for thirteen. For nine novel genes, which are particularly interesting because of their possible involvement in neuromodulation, the expression was verified by quantitative real time-PCR. Of particular functional importance may be the occurrence of glycine receptors, the presence of which indicates that the activity of the parvafox nucleus is under ascending inhibitory control. PMID:28167900

  7. Microarray data integration for genome-wide analysis of human tissue-selective gene expression

    OpenAIRE

    Wang, Liangjiang; Srivastava, Anand K; Schwartz, Charles E

    2010-01-01

    Background Microarray gene expression data are accumulating in public databases. The expression profiles contain valuable information for understanding human gene expression patterns. However, the effective use of public microarray data requires integrating the expression profiles from heterogeneous sources. Results In this study, we have compiled a compendium of microarray expression profiles of various human tissue samples. The microarray raw data generated in different research laboratorie...

  8. Comparative study of joint analysis of microarray gene expression data in survival prediction and risk assessment of breast cancer patients.

    Science.gov (United States)

    Yasrebi, Haleh

    2016-09-01

    Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-analysis, works better. In this article, three joint analysis methods, Z-score normalization, ComBat and the inverse normal method (meta-analysis) were selected for survival prognosis and risk assessment of breast cancer patients. The methods were applied to eight microarray gene expression data sets, totaling 1324 patients with two clinical endpoints, overall survival and relapse-free survival. The performance derived from the joint analysis methods was evaluated using Cox regression for survival analysis and independent validation used as bias estimation. Overall, Z-score normalization had a better performance than ComBat and meta-analysis. Higher Area Under the Receiver Operating Characteristic curve and hazard ratio were also obtained when independent validation was used as bias estimation. With a lower time and memory complexity, Z-score normalization is a simple method for joint analysis of microarray gene expression data sets. The derived findings suggest further assessment of this method in future survival prediction and cancer classification applications.

  9. Impact of Missing Value Imputation on Classification for DNA Microarray Gene Expression Data—A Model-Based Study

    Directory of Open Access Journals (Sweden)

    Sun Youting

    2009-01-01

    Full Text Available Many missing-value (MV imputation methods have been developed for microarray data, but only a few studies have investigated the relationship between MV imputation and classification accuracy. Furthermore, these studies are problematic in fundamental steps such as MV generation and classifier error estimation. In this work, we carry out a model-based study that addresses some of the issues in previous studies. Six popular imputation algorithms, two feature selection methods, and three classification rules are considered. The results suggest that it is beneficial to apply MV imputation when the noise level is high, variance is small, or gene-cluster correlation is strong, under small to moderate MV rates. In these cases, if data quality metrics are available, then it may be helpful to consider the data point with poor quality as missing and apply one of the most robust imputation algorithms to estimate the true signal based on the available high-quality data points. However, at large MV rates, we conclude that imputation methods are not recommended. Regarding the MV rate, our results indicate the presence of a peaking phenomenon: performance of imputation methods actually improves initially as the MV rate increases, but after an optimum point, performance quickly deteriorates with increasing MV rates.

  10. Independent component analysis of Alzheimer's DNA microarray gene expression data

    Directory of Open Access Journals (Sweden)

    Vanderburg Charles R

    2009-01-01

    Full Text Available Abstract Background Gene microarray technology is an effective tool to investigate the simultaneous activity of multiple cellular pathways from hundreds to thousands of genes. However, because data in the colossal amounts generated by DNA microarray technology are usually complex, noisy, high-dimensional, and often hindered by low statistical power, their exploitation is difficult. To overcome these problems, two kinds of unsupervised analysis methods for microarray data: principal component analysis (PCA and independent component analysis (ICA have been developed to accomplish the task. PCA projects the data into a new space spanned by the principal components that are mutually orthonormal to each other. The constraint of mutual orthogonality and second-order statistics technique within PCA algorithms, however, may not be applied to the biological systems studied. Extracting and characterizing the most informative features of the biological signals, however, require higher-order statistics. Results ICA is one of the unsupervised algorithms that can extract higher-order statistical structures from data and has been applied to DNA microarray gene expression data analysis. We performed FastICA method on DNA microarray gene expression data from Alzheimer's disease (AD hippocampal tissue samples and consequential gene clustering. Experimental results showed that the ICA method can improve the clustering results of AD samples and identify significant genes. More than 50 significant genes with high expression levels in severe AD were extracted, representing immunity-related protein, metal-related protein, membrane protein, lipoprotein, neuropeptide, cytoskeleton protein, cellular binding protein, and ribosomal protein. Within the aforementioned categories, our method also found 37 significant genes with low expression levels. Moreover, it is worth noting that some oncogenes and phosphorylation-related proteins are expressed in low levels. In

  11. Orally administered lactoperoxidase increases expression of the FK506 binding protein 5 gene in epithelial cells of the small intestine of mice: a DNA microarray study.

    Science.gov (United States)

    Wakabayashi, Hiroyuki; Miyauchi, Hirofumi; Shin, Kouichirou; Yamauchi, Koji; Matsumoto, Ichiro; Abe, Keiko; Takase, Mitsunori

    2007-09-01

    Lactoperoxidase (LPO) is a component of milk and other external secretions. To study the influence of ingested LPO on the digestive tract, we performed DNA microarray analysis of the small intestine of mice administered LPO. LPO administration upregulated 78 genes, including genes involved in metabolism, immunity, apoptosis, and the cell cycle, and downregulated nine genes, including immunity-related genes. The most upregulated gene was FK506 binding protein 5 (FKBP5), a glucocorticoid regulating immunophilin. The upregulation of this gene was confirmed by quantitative RT-PCR in other samples. In situ hybridization revealed that expression of the FKBP5 gene in the crypt epithelial cells of the small intestine was enhanced by LPO. These results suggest that ingested LPO modulates gene expression in the small intestine and especially increases FKBP5 gene expression in the epithelial cells of the intestine.

  12. Microarray Assisted Gene Discovery in Ulcerative Colitis

    DEFF Research Database (Denmark)

    Brusgaard, Klaus

    ), and microarray based expression studies. In IBD the increased production of chemo attractants from the inflamed microenvironment results in recruitment of activated CD4+ T lymphocytes which results in tissue damage. Where Th1 cell-derived cytokines has been reported to be essential mediators in CD with high (IFN...

  13. Putative psychosis genes in the prefrontal cortex: combined analysis of gene expression microarrays

    Directory of Open Access Journals (Sweden)

    Yolken Robert H

    2008-11-01

    Full Text Available Abstract Background Recent studies have shown similarities between schizophrenia and bipolar disorder in phenotypes and in genotypes, and those studies have contributed to an ongoing re-evaluation of the traditional dichotomy between schizophrenia and bipolar disorder. Bipolar disorder with psychotic features may be closely related to schizophrenia and therefore, psychosis may be an alternative phenotype compared to the traditional diagnosis categories. Methods We performed a cross-study analysis of 7 gene expression microarrays that include both psychosis and non-psychosis subjects. These studies include over 400 microarray samples (163 individual subjects on 3 different Affymetrix microarray platforms. Results We found that 110 transcripts are differentially regulated (p Conclusion This study demonstrates the advantages of cross-study analysis in detecting consensus changes in gene expression across multiple microarray studies. Differential gene expression between individuals with and without psychosis suggests that psychosis may be a useful phenotypic variable to complement the traditional diagnosis categories.

  14. Defining best practice for microarray analyses in nutrigenomic studies

    NARCIS (Netherlands)

    Garosi, P.; Filippo, C. de; Erk, M. van; Rocca-Serra, P.; Sansone, S.A.; Elliott, R.

    2005-01-01

    Microarrays represent a powerful tool for studies of diet-gene interactions. Their use is, however, associated with a number of technical challenges and potential pitfalls. The cost of microarrays continues to drop but is still comparatively high. This, coupled with the complex logistical issues

  15. Analytical approach for selecting normalizing genes from a cDNA microarray platform to be used in q-RT-PCR assays: a cnidarian case study.

    Science.gov (United States)

    Rodriguez-Lanetty, Mauricio; Phillips, Wendy S; Dove, Sophie; Hoegh-Guldberg, Ove; Weis, Virginia M

    2008-04-24

    Research in gene function using Quantitative Reverse Transcription PCR (q-RT-PCR) and microarray approaches are emerging and just about to explode in the field of coral and cnidarian biology. These approaches are showing the great potential to significantly advance our understanding of how corals respond to abiotic and biotic stresses, and how host cnidarians/dinoflagellates symbioses are maintained and regulated. With these genomic advances, however, new analytical challenges are also emerging, such as the normalization of gene expression data derived from q-RT-PCR. In this study, an effective analytical method is introduced to identify candidate housekeeping genes (HKG) from a sea anemone (Anthopleura elegantissima) cDNA microarray platform that can be used as internal control genes to normalize q-RT-PCR gene expression data. It is shown that the identified HKGs were stable among the experimental conditions tested in this study. The three most stables genes identified, in term of gene expression, were beta-actin, ribosomal protein L12, and a Poly(a) binding protein. The applications of these HKGs in other cnidarian systems are further discussed.

  16. Normalization strategy of microarray gene expression data

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Objective: To discuss strategies and methods of normalization on how to deal with and analyze data for different chips with the combination of statistics, mathematics and bioinformatics in order to find significant difference genes. Methods: With Excel and SPSS software, high or low density chips were analyzed through total intensity normalization (TIN) and locally weighted linear regression normalization (LWLRN). Results: These methods effectively reduced systemic errors and made data more comparable and reliable. Conclusion: These methods can search the genes of significant difference, although normalization methods are being developed and need to be improved further. Great breakthrough will be obtained in microarray data normalization analysis and transformation with the development of non-linear technology, software and hardware of computer.

  17. Gene Expression Network Reconstruction by LEP Method Using Microarray Data

    Directory of Open Access Journals (Sweden)

    Na You

    2012-01-01

    Full Text Available Gene expression network reconstruction using microarray data is widely studied aiming to investigate the behavior of a gene cluster simultaneously. Under the Gaussian assumption, the conditional dependence between genes in the network is fully described by the partial correlation coefficient matrix. Due to the high dimensionality and sparsity, we utilize the LEP method to estimate it in this paper. Compared to the existing methods, the LEP reaches the highest PPV with the sensitivity controlled at the satisfactory level. A set of gene expression data from the HapMap project is analyzed for illustration.

  18. Identification of candidate genes in osteoporosis by integrated microarray analysis

    Science.gov (United States)

    Li, J. J.; Wang, B. Q.; Yang, Y.; Li, D.

    2016-01-01

    Objectives In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. Methods We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. Results A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Conclusion Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and

  19. 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

    RNA-seq, has recently become an attractive method of choice in the studies of transcriptomes, promising several advantages compared with microarrays. In this study, we sought to assess the contribution of the different analytical steps involved in the analysis of RNA-seq data generated...... the consistency between RNA-seq analysis using reference genome and de novo assembly approach. High reproducibility among biological replicates (correlation ≥0.99) and high consistency between the two platforms for analysis of gene expression levels (correlation ≥0.91) are reported. The results from differential...... 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...

  20. HER2/neu (c-erbB-2) gene amplification and protein expression are rare in uterine cervical neoplasia: a tissue microarray study of 814 archival specimens

    DEFF Research Database (Denmark)

    Lesnikova, Iana; Lidang, Marianne; Hamilton-Dutoit, Stephen;

    2009-01-01

    Published studies have reported widely variable incidence of HER2/neu (c-erbB-2) protein expression and HER2/neu (c-erbB-2) gene amplification in cervical carcinoma. We examined tissue microarrays (TMAs) constructed from 814 formaldehyde-fixed paraffin-embedded archival specimens of cervical...... and invasive cervical carcinoma specimens. When present, Her-2/neu positivity is more commonly seen in higher grades of cervical dysplasia and in carcinoma. However, this large TMA study shows that HER2/neu oncoprotein expression and HER2/neu gene amplification overall are uncommon events in cervical neoplasia...... intraepithelial neoplasia (CIN)1 (n = 262), CIN2 (n = 230), CIN3 (n = 186) and invasive carcinoma (n = 136), for HER2/neu protein expression by immunohistochemistry (IHC) and for HER2/neu gene amplification by chromogenic in situ hybridization (CISH). We found moderate or strong immunohistochemical positivity...

  1. Assessment of fusion gene status in sarcomas using a custom made fusion gene microarray.

    Directory of Open Access Journals (Sweden)

    Marthe Løvf

    Full Text Available Sarcomas are relatively rare malignancies and include a large number of histological subgroups. Based on morphology alone, the differential diagnoses of sarcoma subtypes can be challenging, but the identification of specific fusion genes aids correct diagnostication. The presence of individual fusion products are routinely investigated in Pathology labs. However, the methods used are time-consuming and based on prior knowledge about the expected fusion gene and often the most likely break-point. In this study, 16 sarcoma samples, representing seven different sarcoma subtypes with known fusion gene status from a diagnostic setting, were investigated using a fusion gene microarray. The microarray was designed to detect all possible exon-exon breakpoints between all known fusion genes in a single analysis. An automated scoring of the microarray data from the 38 known sarcoma-related fusion genes identified the correct fusion gene among the top-three hits in 11 of the samples. The analytical sensitivity may be further optimised, but we conclude that a sarcoma-fusion gene microarray is suitable as a time-saving screening tool to identify the majority of the correct fusion genes.

  2. Gene expression profiling of mouse embryos with microarrays

    OpenAIRE

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

    2010-01-01

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

  3. Exhaustive Search for Fuzzy Gene Networks from Microarray Data

    Energy Technology Data Exchange (ETDEWEB)

    Sokhansanj, B A; Fitch, J P; Quong, J N; Quong, A A

    2003-07-07

    Recent technological advances in high-throughput data collection allow for the study of increasingly complex systems on the scale of the whole cellular genome and proteome. Gene network models are required to interpret large and complex data sets. Rationally designed system perturbations (e.g. gene knock-outs, metabolite removal, etc) can be used to iteratively refine hypothetical models, leading to a modeling-experiment cycle for high-throughput biological system analysis. We use fuzzy logic gene network models because they have greater resolution than Boolean logic models and do not require the precise parameter measurement needed for chemical kinetics-based modeling. The fuzzy gene network approach is tested by exhaustive search for network models describing cyclin gene interactions in yeast cell cycle microarray data, with preliminary success in recovering interactions predicted by previous biological knowledge and other analysis techniques. Our goal is to further develop this method in combination with experiments we are performing on bacterial regulatory networks.

  4. Microarray Analysis Reveals Higher Gestational Folic Acid Alters Expression of Genes in the Cerebellum of Mice Offspring—A Pilot Study

    Directory of Open Access Journals (Sweden)

    Subit Barua

    2015-01-01

    Full Text Available Folate is a water-soluble vitamin that is critical for nucleotide synthesis and can modulate methylation of DNA by altering one-carbon metabolism. Previous studies have shown that folate status during pregnancy is associated with various congenital defects including the risk of aberrant neural tube closure. Maternal exposure to a methyl supplemented diet also can alter DNA methylation and gene expression, which may influence the phenotype of offspring. We investigated if higher gestational folic acid (FA in the diet dysregulates the expression of genes in the cerebellum of offspring in C57BL/6 J mice. One week before gestation and throughout the pregnancy, groups of dams were supplemented with FA either at 2 mg/kg or 20 mg/kg of diet. Microarray analysis was used to investigate the genome wide gene expression profile in the cerebellum from day old pups. Our results revealed that exposure to the higher dose FA diet during gestation dysregulated expression of several genes in the cerebellum of both male and female pups. Several transcription factors, imprinted genes, neuro-developmental genes and genes associated with autism spectrum disorder exhibited altered expression levels. These findings suggest that higher gestational FA potentially dysregulates gene expression in the offspring brain and such changes may adversely alter fetal programming and overall brain development.

  5. 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

  6. Relationship between gene co-expression and probe localization on microarray slides

    Directory of Open Access Journals (Sweden)

    Qian Jiang

    2003-12-01

    Full Text Available Abstract Background Microarray technology allows simultaneous measurement of thousands of genes in a single experiment. This is a potentially useful tool for evaluating co-expression of genes and extraction of useful functional and chromosomal structural information about genes. Results In this work we studied the association between the co-expression of genes, their location on the chromosome and their location on the microarray slides by analyzing a number of eukaryotic expression datasets, derived from the S. cerevisiae, C. elegans, and D. melanogaster. We find that in several different yeast microarray experiments the distribution of the number of gene pairs with correlated expression profiles as a function of chromosomal spacing is peaked at short separations and has two superimposed periodicities. The longer periodicity has a spacing of 22 genes (~42 Kb, and the shorter periodicity is 2 genes (~4 Kb. Conclusion The relative positioning of DNA probes on microarray slides and source plates introduces subtle but significant correlations between pairs of genes. Careful consideration of this spatial artifact is important for analysis of microarray expression data. It is particularly relevant to recent microarray analyses that suggest that co-expressed genes cluster along chromosomes or are spaced by multiples of a fixed number of genes along the chromosome.

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

    Indian Academy of Sciences (India)

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

    2014-06-01

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

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

    Science.gov (United States)

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

    2014-06-01

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

  9. Microarray analysis of potential genes in the pathogenesis of recurrent oral ulcer.

    Science.gov (United States)

    Han, Jingying; He, Zhiwei; Li, Kun; Hou, Lu

    2015-01-01

    Recurrent oral ulcer seriously threatens patients' daily life and health. This study investigated potential genes and pathways that participate in the pathogenesis of recurrent oral ulcer by high throughput bioinformatic analysis. RT-PCR and Western blot were applied to further verify screened interleukins effect. Recurrent oral ulcer related genes were collected from websites and papers, and further found out from Human Genome 280 6.0 microarray data. Each pathway of recurrent oral ulcer related genes were got through chip hybridization. RT-PCR was applied to test four recurrent oral ulcer related genes to verify the microarray data. Data transformation, scatter plot, clustering analysis, and expression pattern analysis were used to analyze recurrent oral ulcer related gene expression changes. Recurrent oral ulcer gene microarray was successfully established. Microarray showed that 551 genes involved in recurrent oral ulcer activity and 196 genes were recurrent oral ulcer related genes. Of them, 76 genes up-regulated, 62 genes down-regulated, and 58 genes up-/down-regulated. Total expression level up-regulated 752 times (60%) and down-regulated 485 times (40%). IL-2 plays an important role in the occurrence, development and recurrence of recurrent oral ulcer on the mRNA and protein levels. Gene microarray can be used to analyze potential genes and pathways in recurrent oral ulcer. IL-2 may be involved in the pathogenesis of recurrent oral ulcer.

  10. Development of gene microarray in screening differently expressed genes in keloid and normal-control skin

    Institute of Scientific and Technical Information of China (English)

    陈伟; 付小兵; 葛世丽; 孙晓庆; 周岗; 赵志力; 盛志勇

    2004-01-01

    Background Keloid is an intricate lesion that is probably regulated by many genes. In this study, the authors used the technique of complementary DNA (cDNA) microarray to analyse abnormal gene expression in keloids and normal control skins. Methods The polymerase chain reaction (PCR) products of 8400 genes were spotted in an array on chemical-material-coated-glass plates. The DNAs were fixed on the glass plates. The total RNAs were isolated from freshly excised human keloid and normal control skins, and the mRNAs were then purified. The mRNA from both keloid and normal control skins were reversely transcribed to cDNAs, with the incorporation of fluorescent dUTP, for preparing the hybridisation probes. The mixed probes were then hybridised to the cDNA microarray. After thorough washing, the cDNA microarray was scanned for differing fluorescent signals from two types of tissues. Gene expression of tissue growth factor-β1 (TGF-β1) and of c-myc was detected with both RT-PCR and Northern blot hybridisation to confirm the effectiveness of cDNA microarray. Results Among the 8400 human genes, 402 were detected with different expression levels between keloid and normal control skins. Two hundred and fifty genes, including TGF-β1 and c-myc, were up-regulated and 152 genes were down-regulated. Higher expressions of TGF-β1 and c-myc in keloid were also revealed using RT-PCR and Northern blot methods. Conclusion cDNA microarray analysis provides a powerful tool for investigating differential gene expression in keloid and normal control skins. Keloid is a complicated lesion with many genes involved.

  11. Gene set analyses for interpreting microarray experiments on prokaryotic organisms

    OpenAIRE

    Heffron Fred; Van Bruggen Dirk; DeJongh Matthew; Best Aaron A; Tintle Nathan L; Porwollik Steffen; Taylor Ronald C

    2008-01-01

    Abstract Background Despite the widespread usage of DNA microarrays, questions remain about how best to interpret the wealth of gene-by-gene transcriptional levels that they measure. Recently, methods have been proposed which use biologically defined sets of genes in interpretation, instead of examining results gene-by-gene. Despite a serious limitation, a method based on Fisher's exact test remains one of the few plausible options for gene set analysis when an experiment has few replicates, ...

  12. Large scale comparison of gene expression levels by microarrays and RNAseq using TCGA data.

    Science.gov (United States)

    Guo, Yan; Sheng, Quanhu; Li, Jiang; Ye, Fei; Samuels, David C; Shyr, Yu

    2013-01-01

    RNAseq and microarray methods are frequently used to measure gene expression level. While similar in purpose, there are fundamental differences between the two technologies. Here, we present the largest comparative study between microarray and RNAseq methods to date using The Cancer Genome Atlas (TCGA) data. We found high correlations between expression data obtained from the Affymetrix one-channel microarray and RNAseq (Spearman correlations coefficients of ∼0.8). We also observed that the low abundance genes had poorer correlations between microarray and RNAseq data than high abundance genes. As expected, due to measurement and normalization differences, Agilent two-channel microarray and RNAseq data were poorly correlated (Spearman correlations coefficients of only ∼0.2). By examining the differentially expressed genes between tumor and normal samples we observed reasonable concordance in directionality between Agilent two-channel microarray and RNAseq data, although a small group of genes were found to have expression changes reported in opposite directions using these two technologies. Overall, RNAseq produces comparable results to microarray technologies in term of expression profiling. The RNAseq normalization methods RPKM and RSEM produce similar results on the gene level and reasonably concordant results on the exon level. Longer exons tended to have better concordance between the two normalization methods than shorter exons.

  13. Mitochondrial and oxidative stress genes are differentially expressed in neutrophils of sJIA patients treated with tocilizumab: a pilot microarray study.

    Science.gov (United States)

    Omoyinmi, Ebun; Hamaoui, Raja; Bryant, Annette; Jiang, Mike Chao; Athigapanich, Trin; Eleftheriou, Despina; Hubank, Mike; Brogan, Paul; Woo, Patricia

    2016-02-09

    Various pathways involved in the pathogenesis of sJIA have been identified through gene expression profiling in peripheral blood mononuclear cells (PBMC), but not in neutrophils. Since neutrophils are important in tissue damage during inflammation, and are elevated as part of the acute phase response, we hypothesised that neutrophil pathways could also be important in the pathogenesis of sJIA. We therefore studied the gene profile in both PBMC and neutrophils of sJIA patients treated with tocilizumab. We studied the transcriptomes of peripheral blood mononuclear cells (PBMC) and neutrophils from eight paired samples obtained from 4 sJIA patients taken before and after treatment, selected on the basis that they achieved ACR90 responses within 12 weeks of therapy initiation with tocilizumab. RNA was extracted and gene expression profiling was performed using Affymetrix GeneChip Human Genome U133 Plus 2.0 microarray platform. A longitudinal analysis using paired t-test (p ontology analysis in neutrophils revealed that response to tocilizumab significantly altered genes regulating mitochondrial dysfunction and oxidative stress (p = 4.6E-05). This was independently verified with GSEA, by identifying a set of oxidative genes whose expression correlated with response to tocilizumab. In PBMC, treatment of sJIA with tocilizumab appeared to affect genes in Oncostatin M signalling and B cell pathways. For the first time we demonstrate that neutrophils from sJIA patients responding to tocilizumab showed significantly different changes in gene expression. These data could highlight the importance of mitochondrial genes that modulate oxidative stress in the pathogenesis of sJIA.

  14. Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Alina Sîrbu

    2015-05-01

    Full Text Available Microarray technologies have been the basis of numerous important findings regarding gene expression in the few last decades. Studies have generated large amounts of data describing various processes, which, due to the existence of public databases, are widely available for further analysis. Given their lower cost and higher maturity compared to newer sequencing technologies, these data continue to be produced, even though data quality has been the subject of some debate. However, given the large volume of data generated, integration can help overcome some issues related, e.g., to noise or reduced time resolution, while providing additional insight on features not directly addressed by sequencing methods. Here, we present an integration test case based on public Drosophila melanogaster datasets (gene expression, binding site affinities, known interactions. Using an evolutionary computation framework, we show how integration can enhance the ability to recover transcriptional gene regulatory networks from these data, as well as indicating which data types are more important for quantitative and qualitative network inference. Our results show a clear improvement in performance when multiple datasets are integrated, indicating that microarray data will remain a valuable and viable resource for some time to come.

  15. A genome-wide 20 K citrus microarray for gene expression analysis.

    Science.gov (United States)

    Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose

    2008-07-03

    Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database 1 was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global studies in citrus by using it to catalogue genes expressed in

  16. A genome-wide 20 K citrus microarray for gene expression analysis

    Directory of Open Access Journals (Sweden)

    Gadea Jose

    2008-07-01

    Full Text Available Abstract Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database 1 was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. Conclusion This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global

  17. Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Xi Wang

    2015-05-01

    Full Text Available Kashin-Beck Disease (KBD is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published gene expression profile data on cartilage and peripheral blood mononuclear cells (PBMCs from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A gene expression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR algorithm and support vector machine (SVM algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD.

  18. Meta-analysis of studies using suppression subtractive hybridization and microarrays to investigate the effects of environmental stress on gene transcription in oysters.

    Directory of Open Access Journals (Sweden)

    Kelli Anderson

    Full Text Available Many microarray and suppression subtractive hybridization (SSH studies have analyzed the effects of environmental stress on gene transcription in marine species. However, there have been no unifying analyses of these data to identify common stress response pathways. To address this shortfall, we conducted a meta-analysis of 14 studies that investigated the effects of different environmental stressors on gene expression in oysters. The stressors tested included chemical contamination, hypoxia and infection, as well as extremes of temperature, pH and turbidity. We found that the expression of over 400 genes in a range of oyster species changed significantly after exposure to environmental stress. A repeating pattern was evident in these transcriptional responses, regardless of the type of stress applied. Many of the genes that responded to environmental stress encoded proteins involved in translation and protein processing (including molecular chaperones, the mitochondrial electron transport chain, anti-oxidant activity and the cytoskeleton. In light of these findings, we put forward a consensus model of sub-cellular stress responses in oysters.

  19. Meta-analysis of studies using suppression subtractive hybridization and microarrays to investigate the effects of environmental stress on gene transcription in oysters.

    Science.gov (United States)

    Anderson, Kelli; Taylor, Daisy A; Thompson, Emma L; Melwani, Aroon R; Nair, Sham V; Raftos, David A

    2015-01-01

    Many microarray and suppression subtractive hybridization (SSH) studies have analyzed the effects of environmental stress on gene transcription in marine species. However, there have been no unifying analyses of these data to identify common stress response pathways. To address this shortfall, we conducted a meta-analysis of 14 studies that investigated the effects of different environmental stressors on gene expression in oysters. The stressors tested included chemical contamination, hypoxia and infection, as well as extremes of temperature, pH and turbidity. We found that the expression of over 400 genes in a range of oyster species changed significantly after exposure to environmental stress. A repeating pattern was evident in these transcriptional responses, regardless of the type of stress applied. Many of the genes that responded to environmental stress encoded proteins involved in translation and protein processing (including molecular chaperones), the mitochondrial electron transport chain, anti-oxidant activity and the cytoskeleton. In light of these findings, we put forward a consensus model of sub-cellular stress responses in oysters.

  20. 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].

  1. A growth curve model with fractional polynomials for analysing incomplete time-course data in microarray gene expression studies

    DEFF Research Database (Denmark)

    Tan, Qihua; Thomassen, Mads; Hjelmborg, Jacob V B

    2011-01-01

    among fractional polynomial models with power terms from a set of fixed values that offer a wide range of curve shapes and suggests a best fitting model. After a limited simulation study, the model has been applied to our human in vivo irritated epidermis data with missing observations to investigate......-course pattern in a gene by gene manner. We introduce a growth curve model with fractional polynomials to automatically capture the various time-dependent expression patterns and meanwhile efficiently handle missing values due to incomplete observations. For each gene, our procedure compares the performances...... time-dependent transcriptional responses to a chemical irritant. Our method was able to identify the various nonlinear time-course expression trajectories. The integration of growth curves with fractional polynomials provides a flexible way to model different time-course patterns together with model...

  2. Evaluation of a gene information summarization system by users during the analysis process of microarray datasets.

    Science.gov (United States)

    Yang, Jianji; Cohen, Aaron; Hersh, William

    2009-02-05

    Summarization of gene information in the literature has the potential to help genomics researchers translate basic research into clinical benefits. Gene expression microarrays have been used to study biomarkers for disease and discover novel types of therapeutics and the task of finding information in journal articles on sets of genes is common for translational researchers working with microarray data. However, manually searching and scanning the literature references returned from PubMed is a time-consuming task for scientists. We built and evaluated an automatic summarizer of information on genes studied in microarray experiments. The Gene Information Clustering and Summarization System (GICSS) is a system that integrates two related steps of the microarray data analysis process: functional gene clustering and gene information gathering. The system evaluation was conducted during the process of genomic researchers analyzing their own experimental microarray datasets. The clusters generated by GICSS were validated by scientists during their microarray analysis process. In addition, presenting sentences in the abstract provided significantly more important information to the users than just showing the title in the default PubMed format. The evaluation results suggest that GICSS can be useful for researchers in genomic area. In addition, the hybrid evaluation method, partway between intrinsic and extrinsic system evaluation, may enable researchers to gauge the true usefulness of the tool for the scientists in their natural analysis workflow and also elicit suggestions for future enhancements. GICSS can be accessed online at: http://ir.ohsu.edu/jianji/index.html.

  3. Gene expression profiling of mouse embryos with microarrays

    Science.gov (United States)

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

    2011-01-01

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

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

    NARCIS (Netherlands)

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

    2005-01-01

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

  5. Construction of citrus gene coexpression networks from microarray data using random matrix theory.

    Science.gov (United States)

    Du, Dongliang; Rawat, Nidhi; Deng, Zhanao; Gmitter, Fred G

    2015-01-01

    After the sequencing of citrus genomes, gene function annotation is becoming a new challenge. Gene coexpression analysis can be employed for function annotation using publicly available microarray data sets. In this study, 230 sweet orange (Citrus sinensis) microarrays were used to construct seven coexpression networks, including one condition-independent and six condition-dependent (Citrus canker, Huanglongbing, leaves, flavedo, albedo, and flesh) networks. In total, these networks contain 37 633 edges among 6256 nodes (genes), which accounts for 52.11% measurable genes of the citrus microarray. Then, these networks were partitioned into functional modules using the Markov Cluster Algorithm. Significantly enriched Gene Ontology biological process terms and KEGG pathway terms were detected for 343 and 60 modules, respectively. Finally, independent verification of these networks was performed using another expression data of 371 genes. This study provides new targets for further functional analyses in citrus.

  6. Reproducibility of gene expression across generations of Affymetrix microarrays

    Directory of Open Access Journals (Sweden)

    Haslett Judith N

    2003-06-01

    Full Text Available Abstract Background The development of large-scale gene expression profiling technologies is rapidly changing the norms of biological investigation. But the rapid pace of change itself presents challenges. Commercial microarrays are regularly modified to incorporate new genes and improved target sequences. Although the ability to compare datasets across generations is crucial for any long-term research project, to date no means to allow such comparisons have been developed. In this study the reproducibility of gene expression levels across two generations of Affymetrix GeneChips® (HuGeneFL and HG-U95A was measured. Results Correlation coefficients were computed for gene expression values across chip generations based on different measures of similarity. Comparing the absolute calls assigned to the individual probe sets across the generations found them to be largely unchanged. Conclusion We show that experimental replicates are highly reproducible, but that reproducibility across generations depends on the degree of similarity of the probe sets and the expression level of the corresponding transcript.

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

    NARCIS (Netherlands)

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

    2002-01-01

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

  8. Differential adipose tissue gene expression profiles in abacavir treated patients that may contribute to the understanding of cardiovascular risk: a microarray study.

    Science.gov (United States)

    Shahmanesh, Mohsen; Phillips, Kenneth; Boothby, Meg; Tomlinson, Jeremy W

    2015-01-01

    To compare changes in gene expression by microarray from subcutaneous adipose tissue from HIV treatment naïve patients treated with efavirenz based regimens containing abacavir (ABC), tenofovir (TDF) or zidovidine (AZT). Subcutaneous fat biopsies were obtained before, at 6- and 18-24-months after treatment, and from HIV negative controls. Groups were age, ethnicity, weight, biochemical profile, and pre-treatment CD4 count matched. Microarray data was generated using the Agilent Whole Human Genome Microarray. Identification of differentially expressed genes and genomic response pathways was performed using limma and gene set enrichment analysis. There were significant divergences between ABC and the other two groups 6 months after treatment in genes controlling cell adhesion and environmental information processing, with some convergence at 18-24 months. Compared to controls the ABC group, but not AZT or TDF showed enrichment of genes controlling adherence junction, at 6 months and 18-24 months (adjusted ptissue. If similar changes are also taking place in other tissues including the coronary vasculature they may contribute to the increased risk of cardiovascular events reported in patients recently started on abacavir-containing regimens.

  9. Membrane gene ontology bias in sequencing and microarray obtained by housekeeping-gene analysis.

    Science.gov (United States)

    Zhang, Yijuan; Akintola, Oluwafemi S; Liu, Ken J A; Sun, Bingyun

    2016-01-10

    Microarray (MA) and high-throughput sequencing are two commonly used detection systems for global gene expression profiling. Although these two systems are frequently used in parallel, the differences in their final results have not been examined thoroughly. Transcriptomic analysis of housekeeping (HK) genes provides a unique opportunity to reliably examine the technical difference between these two systems. We investigated here the structure, genome location, expression quantity, microarray probe coverage, as well as biological functions of differentially identified human HK genes by 9 MA and 6 sequencing studies. These in-depth analyses allowed us to discover, for the first time, a subset of transcripts encoding membrane, cell surface and nuclear proteins that were prone to differential identification by the two platforms. We hope that the discovery can aid the future development of these technologies for comprehensive transcriptomic studies. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. Identifying genes relevant to specific biological conditions in time course microarray experiments.

    Science.gov (United States)

    Singh, Nitesh Kumar; Repsilber, Dirk; Liebscher, Volkmar; Taher, Leila; Fuellen, Georg

    2013-01-01

    Microarrays have been useful in understanding various biological processes by allowing the simultaneous study of the expression of thousands of genes. However, the analysis of microarray data is a challenging task. One of the key problems in microarray analysis is the classification of unknown expression profiles. Specifically, the often large number of non-informative genes on the microarray adversely affects the performance and efficiency of classification algorithms. Furthermore, the skewed ratio of sample to variable poses a risk of overfitting. Thus, in this context, feature selection methods become crucial to select relevant genes and, hence, improve classification accuracy. In this study, we investigated feature selection methods based on gene expression profiles and protein interactions. We found that in our setup, the addition of protein interaction information did not contribute to any significant improvement of the classification results. Furthermore, we developed a novel feature selection method that relies exclusively on observed gene expression changes in microarray experiments, which we call "relative Signal-to-Noise ratio" (rSNR). More precisely, the rSNR ranks genes based on their specificity to an experimental condition, by comparing intrinsic variation, i.e. variation in gene expression within an experimental condition, with extrinsic variation, i.e. variation in gene expression across experimental conditions. Genes with low variation within an experimental condition of interest and high variation across experimental conditions are ranked higher, and help in improving classification accuracy. We compared different feature selection methods on two time-series microarray datasets and one static microarray dataset. We found that the rSNR performed generally better than the other methods.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    Chen, James J

    2007-05-01

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

  13. The bioinformatics of microarrays to study cancer: Advantages and disadvantages

    Science.gov (United States)

    Rodríguez-Segura, M. A.; Godina-Nava, J. J.; Villa-Treviño, S.

    2012-10-01

    Microarrays are devices designed to analyze simultaneous expression of thousands of genes. However, the process will adds noise into the information at each stage of the study. To analyze these thousands of data is necessary to use bioinformatics tools. The traditional analysis begins by normalizing data, but the obtained results are highly dependent on how it is conducted the study. It is shown the need to develop new strategies to analyze microarray. Liver tissue taken from an animal model in which is chemically induced cancer is used as an example.

  14. Gene order computation using Alzheimer's DNA microarray gene expression data and the Ant Colony Optimisation algorithm.

    Science.gov (United States)

    Pang, Chaoyang; Jiang, Gang; Wang, Shipeng; Hu, Benqiong; Liu, Qingzhong; Deng, Youping; Huang, Xudong

    2012-01-01

    As Alzheimer's Disease (AD) is the most common form of dementia, the study of AD-related genes via biocomputation is an important research topic. One method of studying AD-related gene is to cluster similar genes together into a gene order. Gene order is a good clustering method as the results can be optimal globally while other clustering methods are only optimal locally. Herein we use the Ant Colony Optimisation (ACO)-based algorithm to calculate the gene order from an Alzheimer's DNA microarray dataset. We test it with four distance measurements: Pearson distance, Spearmen distance, Euclidean distance, and squared Euclidean distance. Our computing results indicate: a different distance formula generated a different quality of gene order, the squared Euclidean distance approach produced the optimal AD-related gene order.

  15. Fast Gene Ontology based clustering for microarray experiments

    OpenAIRE

    Ovaska Kristian; Laakso Marko; Hautaniemi Sampsa

    2008-01-01

    Abstract Background Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. Results We present fa...

  16. SIMAGE: simulation of DNA-microarray gene expression data

    Directory of Open Access Journals (Sweden)

    Kuipers Oscar P

    2006-04-01

    Full Text Available Abstract Background Simulation of DNA-microarray data serves at least three purposes: (i optimizing the design of an intended DNA microarray experiment, (ii comparing existing pre-processing and processing methods for best analysis of a given DNA microarray experiment, (iii educating students, lab-workers and other researchers by making them aware of the many factors influencing DNA microarray experiments. Results Our model has multiple layers of factors influencing the experiment. The relative influence of such factors can differ significantly between labs, experiments within labs, etc. Therefore, we have added a module to roughly estimate their parameters from a given data set. This guarantees that our simulated data mimics real data as closely as possible. Conclusion We introduce a model for the simulation of dual-dye cDNA-microarray data closely resembling real data and coin the model and its software implementation "SIMAGE" which stands for simulation of microarray gene expression data. The software is freely accessible at: http://bioinformatics.biol.rug.nl/websoftware/simage.

  17. Differential adipose tissue gene expression profiles in abacavir treated patients that may contribute to the understanding of cardiovascular risk: a microarray study.

    Directory of Open Access Journals (Sweden)

    Mohsen Shahmanesh

    Full Text Available To compare changes in gene expression by microarray from subcutaneous adipose tissue from HIV treatment naïve patients treated with efavirenz based regimens containing abacavir (ABC, tenofovir (TDF or zidovidine (AZT.Subcutaneous fat biopsies were obtained before, at 6- and 18-24-months after treatment, and from HIV negative controls. Groups were age, ethnicity, weight, biochemical profile, and pre-treatment CD4 count matched. Microarray data was generated using the Agilent Whole Human Genome Microarray. Identification of differentially expressed genes and genomic response pathways was performed using limma and gene set enrichment analysis.There were significant divergences between ABC and the other two groups 6 months after treatment in genes controlling cell adhesion and environmental information processing, with some convergence at 18-24 months. Compared to controls the ABC group, but not AZT or TDF showed enrichment of genes controlling adherence junction, at 6 months and 18-24 months (adjusted p<0.05 and focal adhesions and tight junction at 6 months (p<0.5. Genes controlling leukocyte transendothelial migration (p<0.05 and ECM-receptor interactions (p = 0.04 were over-expressed in ABC compared to TDF and AZT at 6 months but not at 18-24 months. Enrichment of pathways and individual genes controlling cell adhesion and environmental information processing were specifically dysregulated in the ABC group in comparison with other treatments. There was little difference between AZT and TDF.After initiating treatment, there is divergence in the expression of genes controlling cell adhesion and environmental information processing between ABC and both TDF and AZT in subcutaneous adipose tissue. If similar changes are also taking place in other tissues including the coronary vasculature they may contribute to the increased risk of cardiovascular events reported in patients recently started on abacavir-containing regimens.

  18. Microarray gene expression analysis of uterosacral ligaments in uterine prolapse.

    Science.gov (United States)

    Ak, Handan; Zeybek, Burak; Atay, Sevcan; Askar, Niyazi; Akdemir, Ali; Aydin, Hikmet Hakan

    2016-11-01

    Pelvic organ prolapse (POP) is a major health problem that impairs the quality of life with a wide clinical spectrum. Since the uterosacral ligaments provide primary support for the uterus and the upper vagina, we hypothesize that the disruption of these ligaments may lead to a loss of support and eventually contribute to POP. In this study, we therefore investigated whether there are any differences in the transcription profile of uterosacral ligaments in patients with POP when compared to those of the control samples. Seventeen women with POP and 8 non-POP controls undergoing hysterectomy for benign conditions were included in the study. Affymetrix® Gene Chip microarrays (Human Hu 133 plus 2.0) were used for whole genome gene expression profiling analysis. There was 1 significantly down-regulated gene, NKX2-3 in patients with POP compared to the controls (p=4.28464e-013). KIF11 gene was found to be significantly down-regulated in patients with ≥3 deliveries compared to patients with <3 deliveries (p=0.0156237). UGT1A1 (p=2.43388e-005), SCARB1 (p=1.19001e-006) and NKX2-3 (p=2.17966e-013) genes were found to be significantly down-regulated in the premenopausal patients compared to the premenopausal controls. UGT1A1 gene was also found to be significantly down-regulated in the post menopausal patients compared to the postmenopausal controls (p=0.0005). This study provides evidence for a significant down-regulation of the genes that take role in cell cycle, proliferation and embryonic development along with cell adhesion process on the development of POP for the first time. Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  19. Discovery and analysis of pancreatic adenocarcinoma genes using cDNA microarrays

    Institute of Scientific and Technical Information of China (English)

    Gang Jin; Xian-Gui Hu; Kang Ying; Yan Tang; Rui Liu; Yi-Jie Zhang; Zai-Ping Jing; Yi Xie; Yu-Min Mao

    2005-01-01

    AIM: To study the pathogenetic processes and the role of gene expression by microarray analyses in expediting our understanding of the molecular pathophysiology of pancreatic adenocarcinoma, and to identify the novel cancer-associated genes.METHODS: Nine histologically defined pancreatic head adenocarcinoma specimens associated with clinical data were studied. Total RNA and mRNA were isolated and labeled by reverse transcription reaction with Cy5 and Cy3 for cDNA probe. The cDNA microarrays that represent a set of 4 096 human genes were hybridized with labeled cDNA probe and screened for molecular profiling analyses.RESULTS: Using this methodology, 184 genes were screened out for differences in gene expression level after nine couples of hybridizations. Of the 184 genes,87 were upregulated and 97 downregulated, including 11 novel human genes. In pancreatic adenocarcinoma tissue, several invasion and metastasis related genes showed their high expression levels, suggesting that poor prognosis of pancreatic adenocarcinoma might have a solid molecular biological basis.CONCLUSION: The application of cDNA microarray technique for analysis of gene expression patterns is a powerful strategy to identify novel cancer-associated genes, and to rapidly explore their role in clinical pancreatic adenocarcinoma. Microarray profiles provide us new insights into the carcinogenesis and invasive process of pancreatic adenocarcinoma. Our results suggest that a highly organized and structured process of tumor invasion exists in the pancreas.

  20. Random forest for gene selection and microarray data classification.

    Science.gov (United States)

    Moorthy, Kohbalan; Mohamad, Mohd Saberi

    2011-01-01

    A random forest method has been selected to perform both gene selection and classification of the microarray data. In this embedded method, the selection of smallest possible sets of genes with lowest error rates is the key factor in achieving highest classification accuracy. Hence, improved gene selection method using random forest has been proposed to obtain the smallest subset of genes as well as biggest subset of genes prior to classification. The option for biggest subset selection is done to assist researchers who intend to use the informative genes for further research. Enhanced random forest gene selection has performed better in terms of selecting the smallest subset as well as biggest subset of informative genes with lowest out of bag error rates through gene selection. Furthermore, the classification performed on the selected subset of genes using random forest has lead to lower prediction error rates compared to existing method and other similar available methods.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2003-07-01

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

  2. Development, characterization and experimental validation of a cultivated sunflower (Helianthus annuus L. gene expression oligonucleotide microarray.

    Directory of Open Access Journals (Sweden)

    Paula Fernandez

    Full Text Available Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de. The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons. The resulting Sunflower Unigen Resource (SUR version 1.0 was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (p<0.01 allowed the detection of 558 differentially expressed genes between water stress and control conditions; from these, ten genes were further validated by qPCR. Over-represented ontologies were identified using FatiScan in the Babelomics suite. This work generated a curated and trustable sunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement.

  3. Development, characterization and experimental validation of a cultivated sunflower (Helianthus annuus L.) gene expression oligonucleotide microarray.

    Science.gov (United States)

    Fernandez, Paula; Soria, Marcelo; Blesa, David; DiRienzo, Julio; Moschen, Sebastian; Rivarola, Maximo; Clavijo, Bernardo Jose; Gonzalez, Sergio; Peluffo, Lucila; Príncipi, Dario; Dosio, Guillermo; Aguirrezabal, Luis; García-García, Francisco; Conesa, Ana; Hopp, Esteban; Dopazo, Joaquín; Heinz, Ruth Amelia; Paniego, Norma

    2012-01-01

    Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs) curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de). The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons). The resulting Sunflower Unigen Resource (SUR version 1.0) was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls) and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (p<0.01) allowed the detection of 558 differentially expressed genes between water stress and control conditions; from these, ten genes were further validated by qPCR. Over-represented ontologies were identified using FatiScan in the Babelomics suite. This work generated a curated and trustable sunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement.

  4. Gene set analyses for interpreting microarray experiments on prokaryotic organisms.

    Energy Technology Data Exchange (ETDEWEB)

    Tintle, Nathan; Best, Aaron; Dejongh, Matthew; VanBruggen, Dirk; Heffron, Fred; Porwollik, Steffen; Taylor, Ronald C.

    2008-11-05

    Background: Recent advances in microarray technology have brought with them the need for enhanced methods of biologically interpreting gene expression data. Recently, methods like Gene Set Enrichment Analysis (GSEA) and variants of Fisher’s exact test have been proposed which utilize a priori biological information. Typically, these methods are demonstrated with a priori biological information from the Gene Ontology. Results: Alternative gene set definitions are presented based on gene sets inferred from the SEED: open-source software environment for comparative genome annotation and analysis of microbial organisms. Many of these gene sets are then shown to provide consistent expression across a series of experiments involving Salmonella Typhimurium. Implementation of the gene sets in an analysis of microarray data is then presented for the Salmonella Typhimurium data. Conclusions: SEED inferred gene sets can be naturally defined based on subsystems in the SEED. The consistent expression values of these SEED inferred gene sets suggest their utility for statistical analyses of gene expression data based on a priori biological information

  5. Coupled Two-Way Clustering Analysis of Gene Microarray Data

    CERN Document Server

    Getz, G; Domany, E

    2000-01-01

    We present a novel coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant partitions emerge. The search for such subsets is a computationally complex task: we present an algorithm, based on iterative clustering, which performs such a search. This analysis is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on them we were able to discover partitions and correlations that were masked and hidden when the full dataset was used in the analysis. Some of these partitions have clear biological interpretation; others can serve to identify possible directions for future research.

  6. Coupled two-way clustering analysis of gene microarray data

    Science.gov (United States)

    Getz, Gad; Levine, Erel; Domany, Eytan

    2000-10-01

    We present a coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant partitions emerge. The search for such subsets is a computationally complex task. We present an algorithm, based on iterative clustering, that performs such a search. This analysis is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on them we were able to discover partitions and correlations that were masked and hidden when the full dataset was used in the analysis. Some of these partitions have clear biological interpretation; others can serve to identify possible directions for future research.

  7. Statistical Redundancy Testing for Improved Gene Selection in Cancer Classification Using Microarray Data

    Directory of Open Access Journals (Sweden)

    J. Sunil Rao

    2007-01-01

    Full Text Available In gene selection for cancer classifi cation using microarray data, we define an eigenvalue-ratio statistic to measure a gene’s contribution to the joint discriminability when this gene is included into a set of genes. Based on this eigenvalueratio statistic, we define a novel hypothesis testing for gene statistical redundancy and propose two gene selection methods. Simulation studies illustrate the agreement between statistical redundancy testing and gene selection methods. Real data examples show the proposed gene selection methods can select a compact gene subset which can not only be used to build high quality cancer classifiers but also show biological relevance.

  8. Identification of disease-causing genes using microarray data mining and Gene Ontology.

    Science.gov (United States)

    Mohammadi, Azadeh; Saraee, Mohammad H; Salehi, Mansoor

    2011-01-26

    One of the best and most accurate methods for identifying disease-causing genes is monitoring gene expression values in different samples using microarray technology. One of the shortcomings of microarray data is that they provide a small quantity of samples with respect to the number of genes. This problem reduces the classification accuracy of the methods, so gene selection is essential to improve the predictive accuracy and to identify potential marker genes for a disease. Among numerous existing methods for gene selection, support vector machine-based recursive feature elimination (SVMRFE) has become one of the leading methods, but its performance can be reduced because of the small sample size, noisy data and the fact that the method does not remove redundant genes. We propose a novel framework for gene selection which uses the advantageous features of conventional methods and addresses their weaknesses. In fact, we have combined the Fisher method and SVMRFE to utilize the advantages of a filtering method as well as an embedded method. Furthermore, we have added a redundancy reduction stage to address the weakness of the Fisher method and SVMRFE. In addition to gene expression values, the proposed method uses Gene Ontology which is a reliable source of information on genes. The use of Gene Ontology can compensate, in part, for the limitations of microarrays, such as having a small number of samples and erroneous measurement results. The proposed method has been applied to colon, Diffuse Large B-Cell Lymphoma (DLBCL) and prostate cancer datasets. The empirical results show that our method has improved classification performance in terms of accuracy, sensitivity and specificity. In addition, the study of the molecular function of selected genes strengthened the hypothesis that these genes are involved in the process of cancer growth. The proposed method addresses the weakness of conventional methods by adding a redundancy reduction stage and utilizing Gene

  9. Identification of disease-causing genes using microarray data mining and Gene Ontology

    Directory of Open Access Journals (Sweden)

    Saraee Mohammad H

    2011-01-01

    Full Text Available Abstract Background One of the best and most accurate methods for identifying disease-causing genes is monitoring gene expression values in different samples using microarray technology. One of the shortcomings of microarray data is that they provide a small quantity of samples with respect to the number of genes. This problem reduces the classification accuracy of the methods, so gene selection is essential to improve the predictive accuracy and to identify potential marker genes for a disease. Among numerous existing methods for gene selection, support vector machine-based recursive feature elimination (SVMRFE has become one of the leading methods, but its performance can be reduced because of the small sample size, noisy data and the fact that the method does not remove redundant genes. Methods We propose a novel framework for gene selection which uses the advantageous features of conventional methods and addresses their weaknesses. In fact, we have combined the Fisher method and SVMRFE to utilize the advantages of a filtering method as well as an embedded method. Furthermore, we have added a redundancy reduction stage to address the weakness of the Fisher method and SVMRFE. In addition to gene expression values, the proposed method uses Gene Ontology which is a reliable source of information on genes. The use of Gene Ontology can compensate, in part, for the limitations of microarrays, such as having a small number of samples and erroneous measurement results. Results The proposed method has been applied to colon, Diffuse Large B-Cell Lymphoma (DLBCL and prostate cancer datasets. The empirical results show that our method has improved classification performance in terms of accuracy, sensitivity and specificity. In addition, the study of the molecular function of selected genes strengthened the hypothesis that these genes are involved in the process of cancer growth. Conclusions The proposed method addresses the weakness of conventional

  10. Identification of disease-causing genes using microarray data mining and Gene Ontology

    Science.gov (United States)

    2011-01-01

    Background One of the best and most accurate methods for identifying disease-causing genes is monitoring gene expression values in different samples using microarray technology. One of the shortcomings of microarray data is that they provide a small quantity of samples with respect to the number of genes. This problem reduces the classification accuracy of the methods, so gene selection is essential to improve the predictive accuracy and to identify potential marker genes for a disease. Among numerous existing methods for gene selection, support vector machine-based recursive feature elimination (SVMRFE) has become one of the leading methods, but its performance can be reduced because of the small sample size, noisy data and the fact that the method does not remove redundant genes. Methods We propose a novel framework for gene selection which uses the advantageous features of conventional methods and addresses their weaknesses. In fact, we have combined the Fisher method and SVMRFE to utilize the advantages of a filtering method as well as an embedded method. Furthermore, we have added a redundancy reduction stage to address the weakness of the Fisher method and SVMRFE. In addition to gene expression values, the proposed method uses Gene Ontology which is a reliable source of information on genes. The use of Gene Ontology can compensate, in part, for the limitations of microarrays, such as having a small number of samples and erroneous measurement results. Results The proposed method has been applied to colon, Diffuse Large B-Cell Lymphoma (DLBCL) and prostate cancer datasets. The empirical results show that our method has improved classification performance in terms of accuracy, sensitivity and specificity. In addition, the study of the molecular function of selected genes strengthened the hypothesis that these genes are involved in the process of cancer growth. Conclusions The proposed method addresses the weakness of conventional methods by adding a redundancy

  11. A 3800 gene microarray for cattle functional genomics: comparison of gene expression in spleen, placenta, and brain.

    Science.gov (United States)

    Band, Mark R; Olmstead, Colleen; Everts, Robin E; Liu, Zonglin L; Lewin, Harris A

    2002-05-01

    A cDNA microarray representing approximately 3800 cattle genes was created for functional genomic studies. The array elements were selected from > 7000 cDNA clones identified in a large-scale expressed sequence tag (EST) project that utilized spleen and normalized and subtracted placenta cDNA libraries. Sequence similarity searches of the 3820 ESTs represented on the array using BLASTN identified 3290 (86.1%) as putative human orthologs, with the remainder consisting of "novel" genes or highly divergent orthologs. Experiments were conducted with a prototype 768 gene microarray created from spleen cDNAs and with the 3800 gene array that included genes from spleen and placenta. The 768 gene array was used to profile RNA transcripts expressed by adult and fetal spleen. The 3800 gene array was used to profile transcripts expressed by adult brain and placenta. Microarray analysis of RNA extracted from fetal and adult spleen identified 29 genes that were differentially expressed two-fold or more. Transcriptional differences of two of these genes, IGJ and CTSS, were confirmed using TaqMan technology. The comparison of brain and placenta revealed 400 genes expressed at higher levels in brain and 72 genes expressed at higher levels in placenta. These results demonstrate the potential power of microarrays for understanding the molecular mechanisms of cattle development, disease resistance, nutrition, fertility and production traits.

  12. Differential and correlation analyses of microarray gene expression data in the CEPH Utah families

    DEFF Research Database (Denmark)

    Tan, Qihua; Zhao, Jinghua; Li, Shuxia;

    2008-01-01

    The widespread microarray technology capable of analyzing global gene expression at the level of transcription is expanding its application not only in medicine but also in studies on basic biology. This paper presents our analysis on microarray gene expression data in the CEPH Utah families...... focusing on the demographic characteristics such as age and sex on differential gene expression patterns. Our results show that the differential gene expression pattern between age groups is dominated by down-regulated transcriptional activities in the old subjects. Functional analysis on age......-regulated genes identifies cell-cell signaling as an important functional category implicated in human aging. Sex-dependent gene expression is characterized by genes that may escape X-inactivation and, most interestingly, such a pattern is not affected by the aging process. Analysis on sibship correlation on gene...

  13. Extending the Interpretation of Gene Profiling Microarray Experiments to Pathway Analysis Through the Use of Gene Ontology Terms

    Science.gov (United States)

    Chatziioannou, Aristotelis; Moulos, Panagiotis

    Microarray technology allows the survey of gene expression at a global level by measuring mRNA abundance. However, the grand complexity characterizing a microarray experiment entails the development of computationally powerful tools apt for probing the biological problem studied. Here we propose a suite for flexible, adaptable to a wide range of possible needs of the biological end-user, data-driven interpretation of microarray experiments. The suite is implemented in MATLAB and is making use of two modules, able to perform all steps of typical microarray data analysis starting from data standardization and normalization up to statistical selection and pathway analysis utilizing Gene Ontology Term annotations for the species genomes interrogated, whereas due to its modular structure it is scalable thus enabling the incorporation or its seamless assembly with other existing tools.

  14. Evaluation of a gene information summarization system by users during the analysis process of microarray datasets

    Directory of Open Access Journals (Sweden)

    Cohen Aaron

    2009-02-01

    Full Text Available Abstract Background Summarization of gene information in the literature has the potential to help genomics researchers translate basic research into clinical benefits. Gene expression microarrays have been used to study biomarkers for disease and discover novel types of therapeutics and the task of finding information in journal articles on sets of genes is common for translational researchers working with microarray data. However, manually searching and scanning the literature references returned from PubMed is a time-consuming task for scientists. We built and evaluated an automatic summarizer of information on genes studied in microarray experiments. The Gene Information Clustering and Summarization System (GICSS is a system that integrates two related steps of the microarray data analysis process: functional gene clustering and gene information gathering. The system evaluation was conducted during the process of genomic researchers analyzing their own experimental microarray datasets. Results The clusters generated by GICSS were validated by scientists during their microarray analysis process. In addition, presenting sentences in the abstract provided significantly more important information to the users than just showing the title in the default PubMed format. Conclusion The evaluation results suggest that GICSS can be useful for researchers in genomic area. In addition, the hybrid evaluation method, partway between intrinsic and extrinsic system evaluation, may enable researchers to gauge the true usefulness of the tool for the scientists in their natural analysis workflow and also elicit suggestions for future enhancements. Availability GICSS can be accessed online at: http://ir.ohsu.edu/jianji/index.html

  15. Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays

    Directory of Open Access Journals (Sweden)

    Chan Frances

    2006-03-01

    Full Text Available Abstract Background DNA microarrays are rapidly becoming a fundamental tool in discovery-based genomic and biomedical research. However, the reliability of the microarray results is being challenged due to the existence of different technologies and non-standard methods of data analysis and interpretation. In the absence of a "gold standard"/"reference method" for the gene expression measurements, studies evaluating and comparing the performance of various microarray platforms have often yielded subjective and conflicting conclusions. To address this issue we have conducted a large scale TaqMan® Gene Expression Assay based real-time PCR experiment and used this data set as the reference to evaluate the performance of two representative commercial microarray platforms. Results In this study, we analyzed the gene expression profiles of three human tissues: brain, lung, liver and one universal human reference sample (UHR using two representative commercial long-oligonucleotide microarray platforms: (1 Applied Biosystems Human Genome Survey Microarrays (based on single-color detection; (2 Agilent Whole Human Genome Oligo Microarrays (based on two-color detection. 1,375 genes represented by both microarray platforms and spanning a wide dynamic range in gene expression levels, were selected for TaqMan® Gene Expression Assay based real-time PCR validation. For each platform, four technical replicates were performed on the same total RNA samples according to each manufacturer's standard protocols. For Agilent arrays, comparative hybridization was performed using incorporation of Cy5 for brain/lung/liver RNA and Cy3 for UHR RNA (common reference. Using the TaqMan® Gene Expression Assay based real-time PCR data set as the reference set, the performance of the two microarray platforms was evaluated focusing on the following criteria: (1 Sensitivity and accuracy in detection of expression; (2 Fold change correlation with real-time PCR data in pair

  16. Overview of Microarray Analysis of Gene Expression and its Applications to Cervical Cancer Investigation

    Directory of Open Access Journals (Sweden)

    Angel Chao

    2007-12-01

    Full Text Available Cervical cancer is one of the leading female cancers in Taiwan and ranks as the fifth cause of cancer death in the female population. Human papillomavirus has been established as the causative agent for cervical neoplasia and cervical cancer. However, the tumor biology involved in the prognoses of different cell types in early cancers and tumor responses to radiation in advanced cancers remain largely unknown. The introduction of microarray technologies in the 1990s has provided genome-wide strategies for searching tens of thousands of genes simultaneously. In this review, we first summarize the two types of microarrays: oligonucleotides microarray and cDNA microarray. Then, we review the studies of functional genomics in cervical cancer. Gene expression studies that involved cervical cancer cell lines, cervical cells of cancer versus normal ectocervix, cancer tissues of different histology, radioresistant versus radiosensitive patients, and the combinatorial gene expression associated with chromosomal amplifications are discussed. In particular, CEACAM5, TACSTD1, S100P, and MSLN have shown to be upregulated in adenocarcinoma, and increased expression levels of CEACAM5 and TACSTD1 were significantly correlated with poorer patient outcomes. On the other hand, 35 genes, including apoptotic genes (e.g. BIK, TEGT, SSI-3, hypoxia-inducible genes (e.g. HIF1A, CA12, and tumor cell invasion and metastasis genes (e.g. CTSL, CTSB, PLAU, CD44, have been noted to echo the hypothesis that increased tumor hypoxia leads to radiation resistance in cervical cancer during radiation.

  17. Senescent vs. non-senescent cells in the human annulus in vivo: Cell harvest with laser capture microdissection and gene expression studies with microarray analysis

    Directory of Open Access Journals (Sweden)

    Ingram Jane A

    2010-01-01

    Full Text Available Abstract Background Senescent cells are well-recognized in the aging/degenerating human disc. Senescent cells are viable, cannot divide, remain metabolically active and accumulate within the disc over time. Molecular analysis of senescent cells in tissue offers a special challenge since there are no cell surface markers for senescence which would let one use fluorescence-activated cell sorting as a method for separating out senescent cells. Methods We employed a novel laser capture microdissection (LCM design to selectively harvest senescent and non-senescent annulus cells in paraffin-embedded tissue, and compared their gene expression with microarray analysis. LCM was used to separately harvest senescent and non-senescent cells from 11 human annulus specimens. Results Microarray analysis revealed significant differences in expression levels in senescent cells vs non-senescent cells: 292 genes were upregulated, and 321 downregulated. Genes with established relationships to senescence were found to be significantly upregulated in senescent cells vs. non-senescent cells: p38 (MPAK14, RB-Associated KRAB zinc finger, Discoidin, CUB and LCCL domain, growth arrest and DNA-damage inducible beta, p28ING5, sphingosine-1-phosphate receptor 2 and somatostatin receptor 3; cyclin-dependent kinase 8 showed significant downregulation in senescent cells. Nitric oxidase synthase 1, and heat shock 70 kDa protein 6, both of which were significantly down-regulated in senescent cells, also showed significant changes. Additional genes related to cytokines, cell proliferation, and other processes were also identified. Conclusions Our LCM-microarray analyses identified a set of genes associated with senescence which were significantly upregulated in senescent vs non-senescent cells in the human annulus. These genes include p38 MAP kinase, discoidin, inhibitor of growth family member 5, and growth arrest and DNA-damage-inducible beta. Other genes, including genes

  18. Candidate genes for the progression of malignant gliomas identified by microarray analysis.

    Science.gov (United States)

    Bozinov, Oliver; Köhler, Sylvia; Samans, Birgit; Benes, Ludwig; Miller, Dorothea; Ritter, Markus; Sure, Ulrich; Bertalanffy, Helmut

    2008-01-01

    Malignant astrocytomas of World Health Organization (WHO) grade III or IV have a reduced median survival time, and possible pathways have been described for the progression of anaplastic astrocytomas and glioblastomas, but the molecular basis of malignant astrocytoma progression is still poorly understood. Microarray analysis provides the chance to accelerate studies by comparison of the expression of thousands of genes in these tumours and consequently identify targeting genes. We compared the transcriptional profile of 4,608 genes in tumours of 15 patients including 6 anaplastic astrocytomas (WHO grade III) and 9 glioblastomas (WHO grade IV) using microarray analysis. The microarray data were corroborated by real-time reverse transcription-polymerase chain reaction analysis of two selected genes. We identified 166 gene alterations with a fold change of 2 and higher whose mRNA levels differed (absolute value of the t statistic of 1.96) between the two malignant glioma groups. Further analyses confirmed same transcription directions for Olig2 and IL-13Ralpha2 in anaplastic astrocytomas as compared to glioblastomas. Microarray analyses with a close binary question reveal numerous interesting candidate genes, which need further histochemical testing after selection for confirmation. IL-13Ralpha2 and Olig2 have been identified and confirmed to be interesting candidate genes whose differential expression likely plays a role in malignant progression of astrocytomas.

  19. Functional clustering and lineage markers: insights into cellular differentiation and gene function from large-scale microarray studies of purified primary cell populations.

    Science.gov (United States)

    Hume, David A; Summers, Kim M; Raza, Sobia; Baillie, J Kenneth; Freeman, Thomas C

    2010-06-01

    Very large microarray datasets showing gene expression across multiple tissues and cell populations provide a window on the transcriptional networks that underpin the differences in functional activity between biological systems. Clusters of co-expressed genes provide lineage markers, candidate regulators of cell function and, by applying the principle of guilt by association, candidate functions for genes of currently unknown function. We have analysed a dataset comprising pure cell populations from hemopoietic and non-hemopoietic cell types (http://biogps.gnf.org). Using a novel network visualisation and clustering approach, we demonstrate that it is possible to identify very tight expression signatures associated specifically with embryonic stem cells, mesenchymal cells and hematopoietic lineages. Selected examples validate the prediction that gene function can be inferred by co-expression. One expression cluster was enriched in phagocytes, which, alongside endosome-lysosome constituents, contains genes that may make up a 'pathway' for phagocyte differentiation. Promoters of these genes are enriched for binding sites for the ETS/PU.1 and MITF families. Another cluster was associated with the production of a specific extracellular matrix, with high levels of gene expression shared by cells of mesenchymal origin (fibroblasts, adipocytes, osteoblasts and myoblasts). We discuss the limitations placed upon such data by the presence of alternative promoters with distinct tissue specificity within many protein-coding genes.

  20. Optimization based tumor classification from microarray gene expression data.

    Directory of Open Access Journals (Sweden)

    Onur Dagliyan

    Full Text Available BACKGROUND: An important use of data obtained from microarray measurements is the classification of tumor types with respect to genes that are either up or down regulated in specific cancer types. A number of algorithms have been proposed to obtain such classifications. These algorithms usually require parameter optimization to obtain accurate results depending on the type of data. Additionally, it is highly critical to find an optimal set of markers among those up or down regulated genes that can be clinically utilized to build assays for the diagnosis or to follow progression of specific cancer types. In this paper, we employ a mixed integer programming based classification algorithm named hyper-box enclosure method (HBE for the classification of some cancer types with a minimal set of predictor genes. This optimization based method which is a user friendly and efficient classifier may allow the clinicians to diagnose and follow progression of certain cancer types. METHODOLOGY/PRINCIPAL FINDINGS: We apply HBE algorithm to some well known data sets such as leukemia, prostate cancer, diffuse large B-cell lymphoma (DLBCL, small round blue cell tumors (SRBCT to find some predictor genes that can be utilized for diagnosis and prognosis in a robust manner with a high accuracy. Our approach does not require any modification or parameter optimization for each data set. Additionally, information gain attribute evaluator, relief attribute evaluator and correlation-based feature selection methods are employed for the gene selection. The results are compared with those from other studies and biological roles of selected genes in corresponding cancer type are described. CONCLUSIONS/SIGNIFICANCE: The performance of our algorithm overall was better than the other algorithms reported in the literature and classifiers found in WEKA data-mining package. Since it does not require a parameter optimization and it performs consistently very high prediction rate on

  1. Rasch-based high-dimensionality data reduction and class prediction with applications to microarray gene expression data

    CERN Document Server

    Kastrin, Andrej

    2010-01-01

    Class prediction is an important application of microarray gene expression data analysis. The high-dimensionality of microarray data, where number of genes (variables) is very large compared to the number of samples (obser- vations), makes the application of many prediction techniques (e.g., logistic regression, discriminant analysis) difficult. An efficient way to solve this prob- lem is by using dimension reduction statistical techniques. Increasingly used in psychology-related applications, Rasch model (RM) provides an appealing framework for handling high-dimensional microarray data. In this paper, we study the potential of RM-based modeling in dimensionality reduction with binarized microarray gene expression data and investigate its prediction ac- curacy in the context of class prediction using linear discriminant analysis. Two different publicly available microarray data sets are used to illustrate a general framework of the approach. Performance of the proposed method is assessed by re-randomization s...

  2. GenePublisher: automated analysis of DNA microarray data

    DEFF Research Database (Denmark)

    Knudsen, Steen; Workman, Christopher; Sicheritz-Ponten, T.

    2003-01-01

    GenePublisher, a system for automatic analysis of data from DNA microarray experiments, has been implemented with a web interface at http://www.cbs.dtu.dk/services/GenePublisher. Raw data are uploaded to the server together with aspecification of the data. The server performs normalization......, statistical analysis and visualization of the data. The results are run against databases of signal transduction pathways, metabolic pathways and promoter sequences in order to extract more information. The results of the entire analysis are summarized in report form and returned to the user....

  3. Sensitivity and fidelity of DNA microarray improved with integration of Amplified Differential Gene Expression (ADGE

    Directory of Open Access Journals (Sweden)

    Ile Kristina E

    2003-07-01

    Full Text Available Abstract Background The ADGE technique is a method designed to magnify the ratios of gene expression before detection. It improves the detection sensitivity to small change of gene expression and requires small amount of starting material. However, the throughput of ADGE is low. We integrated ADGE with DNA microarray (ADGE microarray and compared it with regular microarray. Results When ADGE was integrated with DNA microarray, a quantitative relationship of a power function between detected and input ratios was found. Because of ratio magnification, ADGE microarray was better able to detect small changes in gene expression in a drug resistant model cell line system. The PCR amplification of templates and efficient labeling reduced the requirement of starting material to as little as 125 ng of total RNA for one slide hybridization and enhanced the signal intensity. Integration of ratio magnification, template amplification and efficient labeling in ADGE microarray reduced artifacts in microarray data and improved detection fidelity. The results of ADGE microarray were less variable and more reproducible than those of regular microarray. A gene expression profile generated with ADGE microarray characterized the drug resistant phenotype, particularly with reference to glutathione, proliferation and kinase pathways. Conclusion ADGE microarray magnified the ratios of differential gene expression in a power function, improved the detection sensitivity and fidelity and reduced the requirement for starting material while maintaining high throughput. ADGE microarray generated a more informative expression pattern than regular microarray.

  4. Gene expression risk signatures maintain prognostic power in multiple myeloma despite microarray probe set translation

    DEFF Research Database (Denmark)

    Hermansen, N E U; Borup, R; Andersen, M K

    2016-01-01

    INTRODUCTION: Gene expression profiling (GEP) risk models in multiple myeloma are based on 3'-end microarrays. We hypothesized that GEP risk signatures could retain prognostic power despite being translated and applied to whole-transcript microarray data. METHODS: We studied CD138-positive bone...... marrow plasma cells in a prospective cohort of 59 samples from newly diagnosed patients eligible for high-dose therapy (HDT) and 67 samples from previous HDT patients with progressive disease. We used Affymetrix Human Gene 1.1 ST microarrays for GEP. Nine GEP risk signatures were translated by probe set......-87). Various translated GEP risk signatures or combinations hereof were significantly correlated with survival: among newly diagnosed patients mainly in combination with cytogenetic high-risk markers and among relapsed patients mainly in combination with ISS stage III. CONCLUSION: Translated GEP risk...

  5. Use of non-amplified RNA samples for microarray analysis of gene expression.

    Directory of Open Access Journals (Sweden)

    Hiroko Sudo

    Full Text Available Demand for high quality gene expression data has driven the development of revolutionary microarray technologies. The quality of the data is affected by the performance of the microarray platform as well as how the nucleic acid targets are prepared. The most common method for target nucleic acid preparation includes in vitro transcription amplification of the sample RNA. Although this method requires a small amount of starting material and is reported to have high reproducibility, there are also technical disadvantages such as amplification bias and the long, laborious protocol. Using RNA derived from human brain, breast and colon, we demonstrate that a non-amplification method, which was previously shown to be inferior, could be transformed to a highly quantitative method with a dynamic range of five orders of magnitude. Furthermore, the correlation coefficient calculated by comparing microarray assays using non-amplified samples with qRT-PCR assays was approximately 0.9, a value much higher than when samples were prepared using amplification methods. Our results were also compared with data from various microarray platforms studied in the MicroArray Quality Control (MAQC project. In combination with micro-columnar 3D-Gene™ microarray, this non-amplification method is applicable to a variety of genetic analyses, including biomarker screening and diagnostic tests for cancer.

  6. Optimization of gene expression microarray protocol for formalin-fixed paraffin-embedded tissues.

    Science.gov (United States)

    Belder, Nevin; Coşkun, Öznur; Erdoğan, Beyza Doğanay; Savaş, Berna; Ensari, Arzu; Özdağ, Hilal

    2016-03-01

    Formalin-fixed paraffin-embedded (FFPE) tissue is a widely available clinical specimen for retrospective studies. The possibility of long-term clinical follow-up of FFPE samples makes them a valuable source to evaluate links between molecular and clinical information. Working with FFPE samples in the molecular research area, especially using high-throughput molecular techniques such as microarray gene expression profiling, has come into prominence. Because of the harmful effects of formalin fixation process such as degradation of nucleic acids, cross-linking with proteins, and chemical modifications on DNA and RNA, there are some limitations in gene expression profiling studies using FFPE samples. To date many studies have been conducted to evaluate gene expression profiling using microarrays (Thomas et al., Thomas et al. (2013) [1]; Scicchitano et al., Scicchitano et al. (2006) [2]; Frank et al., Frank et al. (2007) [3]; Fedorowicz et al., Fedorowicz et al. (2009) [4]). However, there is still no generally accepted, efficient and standardized procedure for microarray analysis of FFPE samples. This paper describes the microarray data presented in our recently accepted to be published article showing a standard protocol from deparaffinization of FFPE tissue sections and RNA extraction to microarray gene expression analysis. Here we represent our data in detail, deposited in the gene expression omnibus (GEO) database with the accession number GSE73883. Four combinations of two different cRNA/cDNA preparation and labeling protocols with two different array platforms (Affymetrix Human Genome U133 Plus 2.0 and U133_X3P) were evaluated to determine which combination gives the best percentage of present call. The study presents a dataset for comparative analysis which has a potential in terms of providing a robust protocol for gene expression profiling with FFPE tissue samples.

  7. Optimization of gene expression microarray protocol for formalin-fixed paraffin-embedded tissues

    Directory of Open Access Journals (Sweden)

    Nevin Belder

    2016-03-01

    Full Text Available Formalin-fixed paraffin-embedded (FFPE tissue is a widely available clinical specimen for retrospective studies. The possibility of long-term clinical follow-up of FFPE samples makes them a valuable source to evaluate links between molecular and clinical information. Working with FFPE samples in the molecular research area, especially using high-throughput molecular techniques such as microarray gene expression profiling, has come into prominence. Because of the harmful effects of formalin fixation process such as degradation of nucleic acids, cross-linking with proteins, and chemical modifications on DNA and RNA, there are some limitations in gene expression profiling studies using FFPE samples. To date many studies have been conducted to evaluate gene expression profiling using microarrays (Thomas et al., Thomas et al. (2013 [1]; Scicchitano et al., Scicchitano et al. (2006 [2]; Frank et al., Frank et al. (2007 [3]; Fedorowicz et al., Fedorowicz et al. (2009 [4]. However, there is still no generally accepted, efficient and standardized procedure for microarray analysis of FFPE samples. This paper describes the microarray data presented in our recently accepted to be published article showing a standard protocol from deparaffinization of FFPE tissue sections and RNA extraction to microarray gene expression analysis. Here we represent our data in detail, deposited in the gene expression omnibus (GEO database with the accession number GSE73883. Four combinations of two different cRNA/cDNA preparation and labeling protocols with two different array platforms (Affymetrix Human Genome U133 Plus 2.0 and U133_X3P were evaluated to determine which combination gives the best percentage of present call. The study presents a dataset for comparative analysis which has a potential in terms of providing a robust protocol for gene expression profiling with FFPE tissue samples.

  8. Gene ordering in partitive clustering using microarray expressions.

    Science.gov (United States)

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

    2007-08-01

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

  9. Gene ordering in partitive clustering using microarray expressions

    Indian Academy of Sciences (India)

    Shubhra Sankar Ray; Sanghamitra Bandyopadhyay; Sankar K Pal

    2007-08-01

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

  10. Experimental genomics: The application of DNA microarrays in cellular and molecular biology studies

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The genome sequence information in combination with DNA microarrays promises to revolutionize the way of cellular and molecular biological research by allowing complex mixtures of RNA and DNA to interrogated in a parallel and quant itative fashion. DNA microarrays can be used to measure levels of gene expressio n for tens of thousands of gene simultaneously and take advantage of all availab le sequence information for experimental design and data interpretation in pursu it of biological understanding. Recent progress in experimental genomics allows DNA microarrays not simply to provide a catalogue of all the genes and informati on about their function, but to understand how the components work together to comprise functioning cells and organisms. This brief review gives a survey of DNA microarrays technology and its applications in genome and gene function analysis, gene expression studies, biological signal and defense system, cell cyclereg ulation, mechanism of transcriptional regulation, proteomics, and the functional ity of food component.

  11. Unsupervised Bayesian linear unmixing of gene expression microarrays.

    Science.gov (United States)

    Bazot, Cécile; Dobigeon, Nicolas; Tourneret, Jean-Yves; Zaas, Aimee K; Ginsburg, Geoffrey S; Hero, Alfred O

    2013-03-19

    This paper introduces a new constrained model and the corresponding algorithm, called unsupervised Bayesian linear unmixing (uBLU), to identify biological signatures from high dimensional assays like gene expression microarrays. The basis for uBLU is a Bayesian model for the data samples which are represented as an additive mixture of random positive gene signatures, called factors, with random positive mixing coefficients, called factor scores, that specify the relative contribution of each signature to a specific sample. The particularity of the proposed method is that uBLU constrains the factor loadings to be non-negative and the factor scores to be probability distributions over the factors. Furthermore, it also provides estimates of the number of factors. A Gibbs sampling strategy is adopted here to generate random samples according to the posterior distribution of the factors, factor scores, and number of factors. These samples are then used to estimate all the unknown parameters. Firstly, the proposed uBLU method is applied to several simulated datasets with known ground truth and compared with previous factor decomposition methods, such as principal component analysis (PCA), non negative matrix factorization (NMF), Bayesian factor regression modeling (BFRM), and the gradient-based algorithm for general matrix factorization (GB-GMF). Secondly, we illustrate the application of uBLU on a real time-evolving gene expression dataset from a recent viral challenge study in which individuals have been inoculated with influenza A/H3N2/Wisconsin. We show that the uBLU method significantly outperforms the other methods on the simulated and real data sets considered here. The results obtained on synthetic and real data illustrate the accuracy of the proposed uBLU method when compared to other factor decomposition methods from the literature (PCA, NMF, BFRM, and GB-GMF). The uBLU method identifies an inflammatory component closely associated with clinical symptom scores

  12. Production of DNA microarray and expression analysis of genes from Xylella fastidiosa in different culture media

    Directory of Open Access Journals (Sweden)

    Regiane de Fátima Travensolo

    2009-06-01

    Full Text Available DNA Microarray was developed to monitor the expression of many genes from Xylella fastidiosa, allowing the side by-side comparison of two situations in a single experiment. The experiments were performed using X. fastidiosa cells grown in two culture media: BCYE and XDM2. The primers were synthesized, spotted onto glass slides and the array was hybridized against fluorescently labeled cDNAs. The emitted signals were quantified, normalized and the data were statistically analyzed to verify the differentially expressed genes. According to the data, 104 genes were differentially expressed in XDM2 and 30 genes in BCYE media. The present study showed that DNA microarray technique efficiently differentiate the expressed genes under different conditions.DNA Microarray foi desenvolvida para monitorar a expressão de muitos genes de Xylella fastidiosa, permitindo a comparação de duas situações distintas em um único experimento. Os experimentos foram feitos utilizando células de X. fastidiosa cultivada em dois meios de cultura: BCYE e XDM2. Pares de oligonucleotídeos iniciadores foram sintetizados, depositados em lâminas de vidro e o arranjo foi hibridizado contra cDNAs marcados fluorescentemente. Os sinais emitidos foram quantificados, normalizados e os dados foram estatisticamente analisados para verificar os genes diferencialmente expressos. De acordo com nossos dados, 104 genes foram diferencialmente expressos para o meio de cultura XDM2 e 30 genes para o BCYE. No presente estudo, nós demonstramos que a técnica de DNA microarrays eficientemente diferencia genes expressos sob diferentes condições de cultivo.

  13. Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data.

    Science.gov (United States)

    Lewin, Alex; Grieve, Ian C

    2006-10-03

    Gene Ontology (GO) terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fisher's exact tests to find GO terms which are over-represented amongst the genes declared to be differentially expressed in the analysis of the microarray experiment. However, due to the high degree of dependence between GO terms, statistical testing is conservative, and interpretation is difficult. We propose testing groups of GO terms rather than individual terms, to increase statistical power, reduce dependence between tests and improve the interpretation of results. We use the publicly available package POSOC to group the terms. Our method finds groups of GO terms significantly over-represented amongst differentially expressed genes which are not found by Fisher's tests on individual GO terms. Grouping Gene Ontology terms improves the interpretation of gene set enrichment for microarray data.

  14. Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data

    Directory of Open Access Journals (Sweden)

    Grieve Ian C

    2006-10-01

    Full Text Available Abstract Background Gene Ontology (GO terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fisher's exact tests to find GO terms which are over-represented amongst the genes declared to be differentially expressed in the analysis of the microarray experiment. However, due to the high degree of dependence between GO terms, statistical testing is conservative, and interpretation is difficult. Results We propose testing groups of GO terms rather than individual terms, to increase statistical power, reduce dependence between tests and improve the interpretation of results. We use the publicly available package POSOC to group the terms. Our method finds groups of GO terms significantly over-represented amongst differentially expressed genes which are not found by Fisher's tests on individual GO terms. Conclusion Grouping Gene Ontology terms improves the interpretation of gene set enrichment for microarray data.

  15. Screening for candidate genes related to breast cancer with cDNA microarray analysis

    Institute of Scientific and Technical Information of China (English)

    Yu-Juan Xiang; Zhi-Gang Yu; Ming-Ming Guo; Qin-Ye Fu; Zhong-Bing Ma; De-Zong Gao; Qiang Zhang; Yu-Yang Li; Liang Li; Lu Liu; Chun-Miao Ye

    2015-01-01

    Objective: The aim of this study was to reveal the exact changes during the occurrence of breast cancer to explore significant new and promising genes or factors related to this disease. Methods: We compared the gene expression profiles of breast cancer tissues with its uninvolved normal breast tissues as controls using the cDNA microarray analysis in seven breast cancer patients. Further, one representative gene, named IFI30, was quanti-tatively analyzed by real-time PCR to confirm the result of the cDNA microarray analysis. Results: A total of 427 genes were identified with significantly differential expression, 221 genes were up-regulated and 206 genes were down-regulated. And the result of cDNA microarray analysis was validated by detection of IFI30 mRNA level changes by real-time PCR. Genes for cell proliferation, cell cycle, cell division, mitosis, apoptosis, and immune response were enriched in the up-regulated genes, while genes for cell adhesion, proteolysis, and transport were significantly enriched in the down-regulated genes in breast cancer tissues compared with normal breast tissues by a gene ontology analysis. Conclusion: Our present study revealed a range of differentially expressed genes between breast cancer tissues and normal breast tissues, and provide candidate genes for further study focusing on the pathogenesis and new biomarkers for breast cancer. Copyright © 2015, Chinese Medical Association Production. Production and hosting by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

  16. Gene selection and classification for cancer microarray data based on machine learning and similarity measures

    Directory of Open Access Journals (Sweden)

    Liu Qingzhong

    2011-12-01

    Full Text Available Abstract Background Microarray data have a high dimension of variables and a small sample size. In microarray data analyses, two important issues are how to choose genes, which provide reliable and good prediction for disease status, and how to determine the final gene set that is best for classification. Associations among genetic markers mean one can exploit information redundancy to potentially reduce classification cost in terms of time and money. Results To deal with redundant information and improve classification, we propose a gene selection method, Recursive Feature Addition, which combines supervised learning and statistical similarity measures. To determine the final optimal gene set for prediction and classification, we propose an algorithm, Lagging Prediction Peephole Optimization. By using six benchmark microarray gene expression data sets, we compared Recursive Feature Addition with recently developed gene selection methods: Support Vector Machine Recursive Feature Elimination, Leave-One-Out Calculation Sequential Forward Selection and several others. Conclusions On average, with the use of popular learning machines including Nearest Mean Scaled Classifier, Support Vector Machine, Naive Bayes Classifier and Random Forest, Recursive Feature Addition outperformed other methods. Our studies also showed that Lagging Prediction Peephole Optimization is superior to random strategy; Recursive Feature Addition with Lagging Prediction Peephole Optimization obtained better testing accuracies than the gene selection method varSelRF.

  17. Empirical Bayes ranking and selection methods via semiparametric hierarchical mixture models in microarray studies.

    Science.gov (United States)

    Noma, Hisashi; Matsui, Shigeyuki

    2013-05-20

    The main purpose of microarray studies is screening of differentially expressed genes as candidates for further investigation. Because of limited resources in this stage, prioritizing genes are relevant statistical tasks in microarray studies. For effective gene selections, parametric empirical Bayes methods for ranking and selection of genes with largest effect sizes have been proposed (Noma et al., 2010; Biostatistics 11: 281-289). The hierarchical mixture model incorporates the differential and non-differential components and allows information borrowing across differential genes with separation from nuisance, non-differential genes. In this article, we develop empirical Bayes ranking methods via a semiparametric hierarchical mixture model. A nonparametric prior distribution, rather than parametric prior distributions, for effect sizes is specified and estimated using the "smoothing by roughening" approach of Laird and Louis (1991; Computational statistics and data analysis 12: 27-37). We present applications to childhood and infant leukemia clinical studies with microarrays for exploring genes related to prognosis or disease progression.

  18. 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.

  19. Robust gene selection methods using weighting schemes for microarray data analysis.

    Science.gov (United States)

    Kang, Suyeon; Song, Jongwoo

    2017-09-02

    A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.

  20. Microarray analysis of differentially expressed genes in preeclamptic and normal placental tissues.

    Science.gov (United States)

    Ma, K; Lian, Y; Zhou, S; Hu, R; Xiong, Y; Ting, P; Xiong, Y; Li, X; Wang, X

    2014-01-01

    To detect the candidate genes for preeclampsia (PE). The gene expression profiles in preeclamptic and normal placental tissues were analyzed using cDNA microarray approach and the altered expression of important genes were further confirmed by real-time RT-PCR (reverse transcription polymerase chain reaction) technique. Total RNA was extracted from placental tissues of three cases with severe PE and from three cases with normal pregnancy. After scanning, differentially expressed genes were detected by software. In two experiments (the fluorescent labels were exchanged), a total of 111 differentially expressed genes were detected. In placental tissue ofpreeclamptic pregnancy, 68 differentially expressed genes were up-regulated, and 44 differentially expressed genes were down-regulated. Of these genes, 16 highly differentially expressed genes were confirmed by real-time fluorescent quantitative RT-PCR, and the result showed that the ratio of gene expression differences was comparable to that detected by cDNA microarray. The results of bioinformatic analysis showed that encoding products of differentially expressed genes were correlated to infiltration of placenta trophoblastic cells, immunomodulatory factors, pregnancy-associated plasma protein, signal transduction pathway, and cell adhesion. Further studies on the biological function and regulating mechanism of these genes will provide new clues for better understanding of etiology and pathogenesis of PE.

  1. Identification of differentially expressed genes in mouse kidney after irradiation using microarray analysis.

    Science.gov (United States)

    Kruse, Jacqueline J C M; te Poele, Johannes A M; Velds, Arno; Kerkhoven, Ron M; Boersma, Liesbeth J; Russell, Nicola S; Stewart, Fiona A

    2004-01-01

    Irradiation of the kidney induces dose-dependent, progressive renal functional impairment, which is partly mediated by vascular damage. The molecular mechanisms underlying the development of radiation-induced nephropathy are unclear. Given the complexity of radiation-induced responses, microarrays may offer new opportunities to identify a wider range of genes involved in the development of radiation injury. The aim of the present study was to determine whether microarrays are a useful tool for identifying time-related changes in gene expression and potential mechanisms of radiation-induced nephropathy. Microarray experiments were performed using amplified RNA from irradiated mouse kidneys (1 x 16 Gy) and from sham-irradiated control tissue at different intervals (1-30 weeks) after irradiation. After normalization procedures (using information from straight-color, color-reverse and self-self experiments), the differentially expressed genes were identified. Control and repeat experiments were done to confirm that the observations were not artifacts of the array procedure (RNA amplification, probe synthesis, hybridizations and data analysis). To provide independent confirmation of microarray data, semi-quantitative PCR was performed on a selection of genes. At 1 week after irradiation (before the onset of vascular and functional damage), 16 genes were significantly up-regulated and 9 genes were down-regulated. During the period of developing nephropathy (10 to 20 weeks), 31 and 42 genes were up-regulated and 9 and 4 genes were down-regulated. At the later time of 30 weeks, the vast majority of differentially expressed genes (191 out of 203) were down-regulated. Potential genes of interest included TSA-1 (also known as Ly6e) and Jagged 1 (Jag1). Increased expression of TSA-1, a member of the Ly-6 family, has previously been reported in response to proteinuria. Jagged 1, a ligand for the Notch receptor, is known to play a role in angiogenesis, and is particularly

  2. κMicroarray analysis of relative gene expression stability for selection of internal reference genes in the rhesus macaque brain

    Directory of Open Access Journals (Sweden)

    Urbanski Henryk F

    2010-06-01

    Full Text Available Abstract Background Normalization of gene expression data refers to the comparison of expression values using reference standards that are consistent across all conditions of an experiment. In PCR studies, genes designated as "housekeeping genes" have been used as internal reference genes under the assumption that their expression is stable and independent of experimental conditions. However, verification of this assumption is rarely performed. Here we assess the use of gene microarray analysis to facilitate selection of internal reference sequences with higher expression stability across experimental conditions than can be expected using traditional selection methods. We recently demonstrated that relative gene expression from qRT-PCR data normalized using GAPDH, ALG9 and RPL13A expression values mirrored relative expression using quantile normalization in Robust Multichip Analysis (RMA on the Affymetrix® GeneChip® rhesus Macaque Genome Array. Having shown that qRT-PCR and Affymetrix® GeneChip® data from the same hormone replacement therapy (HRT study yielded concordant results, we used quantile-normalized gene microarray data to identify the most stably expressed among probe sets for prospective internal reference genes across three brain regions from the HRT study and an additional study of normally menstruating rhesus macaques (cycle study. Gene selection was limited to 575 previously published human "housekeeping" genes. Twelve animals were used per study, and three brain regions were analyzed from each animal. Gene expression stabilities were determined using geNorm, NormFinder and BestKeeper software packages. Results Sequences co-annotated for ribosomal protein S27a (RPS27A, and ubiquitin were among the most stably expressed under all conditions and selection criteria used for both studies. Higher annotation quality on the human GeneChip® facilitated more targeted analysis than could be accomplished using the rhesus GeneChip®. In

  3. Elimination of laboratory ozone leads to a dramatic improvement in the reproducibility of microarray gene expression measurements

    Directory of Open Access Journals (Sweden)

    Scully Adam T

    2007-02-01

    Full Text Available Abstract Background Environmental ozone can rapidly degrade cyanine 5 (Cy5, a fluorescent dye commonly used in microarray gene expression studies. Cyanine 3 (Cy3 is much less affected by atmospheric ozone. Degradation of the Cy5 signal relative to the Cy3 signal in 2-color microarrays will adversely reduce the Cy5/Cy3 ratio resulting in unreliable microarray data. Results Ozone in central Arkansas typically ranges between ~22 ppb to ~46 ppb and can be as high as 60–100 ppb depending upon season, meteorological conditions, and time of day. These levels of ozone are common in many areas of the country during the summer. A carbon filter was installed in the laboratory air handling system to reduce ozone levels in the microarray laboratory. In addition, the airflow was balanced to prevent non-filtered air from entering the laboratory. These modifications reduced the ozone within the microarray laboratory to ~2–4 ppb. Data presented here document reductions in Cy5 signal on both in-house produced microarrays and commercial microarrays as a result of exposure to unfiltered air. Comparisons of identically hybridized microarrays exposed to either carbon-filtered or unfiltered air demonstrated the protective effect of carbon-filtration on microarray data as indicated by Cy5 and Cy3 intensities. LOWESS normalization of the data was not able to completely overcome the effect of ozone-induced reduction of Cy5 signal. Experiments were also conducted to examine the effects of high humidity on microarray quality. Modest, but significant, increases in Cy5 and Cy3 signal intensities were observed after 2 or 4 hours at 98–99% humidity compared to 42% humidity. Conclusion Simple installation of carbon filters in the laboratory air handling system resulted in low and consistent ozone levels. This allowed the accurate determination of gene expression by microarray using Cy5 and Cy3 fluorescent dyes.

  4. Gene Expression Profiling on Acute Rejected Transplant Kidneys with Microarray

    Institute of Scientific and Technical Information of China (English)

    Deping LI; Kang WANG; Yong DAI; Tianyu LV

    2008-01-01

    To investigate the gene expression profiles in acute allograft rejection of renal trans- plantation, and identify the markers for the early diagnosis of acute rejection, heterotopic kidney transplantation was performed by using F344 or Lewis donors and Lewis recipients. No immunosup- pressant was used. Renal grafts were harvested on days 3, 7, and 14. A commercial microarray was used to measure gene expression levels in day-7 grafts. The expression levels of 48 genes were up-regulated in the allograft in comparison with the isograft control, and interferon-y-induced GTPase gene was most significantly up-regulated in allografts. It is concluded that a variety of pathways are involved in organ transplant rejection which is dynamic and non-balanced. IFN-inducible genes, such as IGTP, may play an important role in the rejection. A lot of important factors involved in acute re- jection are unnecessary but sufficient conditions for the rejection. We are led to conclude that it is virtually impossible to make an early diagnosis based on a single gene marker, but it could he achieved on the basis of a set of markers.

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

    Directory of Open Access Journals (Sweden)

    Hu Xiaohua

    2011-07-01

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

  6. Microarray analysis of adipose tissue gene expression profiles between two chicken breeds

    Indian Academy of Sciences (India)

    Hongbao Wang; Hui Li; Qigui Wang; Yuxiang Wang; Huabin Han; Hui Shi

    2006-12-01

    The chicken is an important model organism that bridges the evolutionary gap between mammals and other vertebrates and provides a major protein source from meat and eggs throughout the world. Excessive accumulation of lipids in the adipose tissue is one of the main problems faced by the broiler industry nowadays. In order to visualize the mechanisms involved in the gene expression and regulation of lipid metabolism in adipose tissue, cDNA microarray containing 9 024 cDNA was used to construct gene expression profile and screen differentially expressed genes in adipose tissue between broilers and layers of 10 wk of age. Sixty-seven differentially expressed sequences were screened out, and 42 genes were found when blasted with the GenBank database. These genes are mainly related to lipid metabolism, energy metabolism, transcription and splicing factor, protein synthesis and degradation. The remained 25 sequences had no annotation available in the GenBank database. Furthermore, Northern blot and semi-quantitative RT-PCR were developed to confirm 4 differentially expressed genes screened by cDNA microarray, and it showed great consistency between the microarray data and Northern blot results or semi-quantitative RT-PCR results. The present study will be helpful for clarifying the molecular mechanism of obesity in chickens.

  7. The diagnosis of inherited metabolic diseases by microarray gene expression profiling

    Directory of Open Access Journals (Sweden)

    Taanman Jan-Willem

    2010-12-01

    Full Text Available Abstract Background Inherited metabolic diseases (IMDs comprise a diverse group of generally progressive genetic metabolic disorders of variable clinical presentations and severity. We have undertaken a study using microarray gene expression profiling of cultured fibroblasts to investigate 68 patients with a broad range of suspected metabolic disorders, including defects of lysosomal, mitochondrial, peroxisomal, fatty acid, carbohydrate, amino acid, molybdenum cofactor, and purine and pyrimidine metabolism. We aimed to define gene expression signatures characteristic of defective metabolic pathways. Methods Total mRNA extracted from cultured fibroblast cell lines was hybridized to Affymetrix U133 Plus 2.0 arrays. Expression data was analyzed for the presence of a gene expression signature characteristic of an inherited metabolic disorder and for genes expressing significantly decreased levels of mRNA. Results No characteristic signatures were found. However, in 16% of cases, disease-associated nonsense and frameshift mutations generating premature termination codons resulted in significantly decreased mRNA expression of the defective gene. The microarray assay detected these changes with high sensitivity and specificity. Conclusion In patients with a suspected familial metabolic disorder where initial screening tests have proven uninformative, microarray gene expression profiling may contribute significantly to the identification of the genetic defect, shortcutting the diagnostic cascade.

  8. Consistent Differential Expression Pattern (CDEP on microarray to identify genes related to metastatic behavior

    Directory of Open Access Journals (Sweden)

    Tsoi Lam C

    2011-11-01

    Full Text Available Abstract Background To utilize the large volume of gene expression information generated from different microarray experiments, several meta-analysis techniques have been developed. Despite these efforts, there remain significant challenges to effectively increasing the statistical power and decreasing the Type I error rate while pooling the heterogeneous datasets from public resources. The objective of this study is to develop a novel meta-analysis approach, Consistent Differential Expression Pattern (CDEP, to identify genes with common differential expression patterns across different datasets. Results We combined False Discovery Rate (FDR estimation and the non-parametric RankProd approach to estimate the Type I error rate in each microarray dataset of the meta-analysis. These Type I error rates from all datasets were then used to identify genes with common differential expression patterns. Our simulation study showed that CDEP achieved higher statistical power and maintained low Type I error rate when compared with two recently proposed meta-analysis approaches. We applied CDEP to analyze microarray data from different laboratories that compared transcription profiles between metastatic and primary cancer of different types. Many genes identified as differentially expressed consistently across different cancer types are in pathways related to metastatic behavior, such as ECM-receptor interaction, focal adhesion, and blood vessel development. We also identified novel genes such as AMIGO2, Gem, and CXCL11 that have not been shown to associate with, but may play roles in, metastasis. Conclusions CDEP is a flexible approach that borrows information from each dataset in a meta-analysis in order to identify genes being differentially expressed consistently. We have shown that CDEP can gain higher statistical power than other existing approaches under a variety of settings considered in the simulation study, suggesting its robustness and

  9. Microarray analysis of differentially expressed genes between cysts and trophozoites of Acanthamoeba castellanii.

    Science.gov (United States)

    Moon, Eun-Kyung; Xuan, Ying-Hua; Chung, Dong-Il; Hong, Yeonchul; Kong, Hyun-Hee

    2011-12-01

    Acanthamoeba infection is difficult to treat because of the resistance property of Acanthamoeba cyst against the host immune system, diverse antibiotics, and therapeutic agents. To identify encystation mediating factors of Acanthamoeba, we compared the transcription profile between cysts and trophozoites using microarray analysis. The DNA chip was composed of 12,544 genes based on expressed sequence tag (EST) from an Acanthamoeba ESTs database (DB) constructed in our laboratory, genetic information of Acanthamoeba from TBest DB, and all of Acanthamoeba related genes registered in the NCBI. Microarray analysis indicated that 701 genes showed higher expression than 2 folds in cysts than in trophozoites, and 859 genes were less expressed in cysts than in trophozoites. The results of real-time PCR analysis of randomly selected 9 genes of which expression was increased during cyst formation were coincided well with the microarray results. Eukaryotic orthologous groups (KOG) analysis showed an increment in T article (signal transduction mechanisms) and O article (posttranslational modification, protein turnover, and chaperones) whereas significant decrement of C article (energy production and conversion) during cyst formation. Especially, cystein proteinases showed high expression changes (282 folds) with significant increases in real-time PCR, suggesting a pivotal role of this proteinase in the cyst formation of Acanthamoeba. The present study provides important clues for the identification and characterization of encystation mediating factors of Acanthamoeba.

  10. SIMAGE : simulation of DNA-microarray gene expression data

    NARCIS (Netherlands)

    Albers, Casper J.; Jansen, Ritsert C.; Kok, Jan; Kuipers, Oscar P.; Hijum, Sacha A.F.T. van

    2006-01-01

    Simulation of DNA-microarray data serves at least three purposes: (i) optimizing the design of an intended DNA microarray experiment, (ii) comparing existing pre-processing and processing methods for best analysis of a given DNA microarray experiment, (iii) educating students, lab-workers and other

  11. Evaluating methods for ranking differentially expressed genes applied to microArray quality control data

    Directory of Open Access Journals (Sweden)

    Shimizu Kentaro

    2011-06-01

    Full Text Available Abstract Background Statistical methods for ranking differentially expressed genes (DEGs from gene expression data should be evaluated with regard to high sensitivity, specificity, and reproducibility. In our previous studies, we evaluated eight gene ranking methods applied to only Affymetrix GeneChip data. A more general evaluation that also includes other microarray platforms, such as the Agilent or Illumina systems, is desirable for determining which methods are suitable for each platform and which method has better inter-platform reproducibility. Results We compared the eight gene ranking methods using the MicroArray Quality Control (MAQC datasets produced by five manufacturers: Affymetrix, Applied Biosystems, Agilent, GE Healthcare, and Illumina. The area under the curve (AUC was used as a measure for both sensitivity and specificity. Although the highest AUC values can vary with the definition of "true" DEGs, the best methods were, in most cases, either the weighted average difference (WAD, rank products (RP, or intensity-based moderated t statistic (ibmT. The percentages of overlapping genes (POGs across different test sites were mainly evaluated as a measure for both intra- and inter-platform reproducibility. The POG values for WAD were the highest overall, irrespective of the choice of microarray platform. The high intra- and inter-platform reproducibility of WAD was also observed at a higher biological function level. Conclusion These results for the five microarray platforms were consistent with our previous ones based on 36 real experimental datasets measured using the Affymetrix platform. Thus, recommendations made using the MAQC benchmark data might be universally applicable.

  12. Algorithm for Finding Optimal Gene Sets in Microarray Prediction

    CERN Document Server

    Deutsch, J M

    2001-01-01

    Motivation: Microarray data has been recently been shown to be efficacious in distinguishing closely related cell types that often appear in the diagnosis of cancer. It is useful to determine the minimum number of genes needed to do such a diagnosis both for clinical use and to determine the importance of specific genes for cancer. Here a replication algorithm is used for this purpose. It evolves an ensemble of predictors, all using different combinations of genes to generate a set of optimal predictors. Results: We apply this method to the leukemia data of the Whitehead/MIT group that attempts to differentially diagnose two kinds of leukemia, and also to data of Khan et. al. to distinguish four different kinds of childhood cancers. In the latter case we were able to reduce the number of genes needed from 96 down to 15, while at the same time being able to perfectly classify all of their test data. Availability: http://stravinsky.ucsc.edu/josh/gesses/ Contact: josh@physics.ucsc.edu

  13. HER2/neu Expression and Gene Alterations in Pancreatic Ductal Adenocarcinoma: A Comparative mmunohistochemistry and Chromogenic in Situ Hybridization Study Based on Tissue Microarrays and Computerized Image Analysis

    Directory of Open Access Journals (Sweden)

    Evangelos Tsiambas

    2006-05-01

    Full Text Available Context: HER2/neu overexpression is observed in many cancers including pancreatic ductal adenocarcinoma. Although immunohistochemistry remains the basic method for evaluating HER2/neu protein expression, significant information regarding gene status cannot be assessed. Design: Using tissue microarray technology, fifty histologically confirmed pancreatic ductal adenocarcinomas were cored twice and re-embedded in one paraffin block. Immunohistochemistry (clone TAB 250 and chromogenic (HER2/neu amplification Spot Light kit in situ hybridization protocols were performed. The immunostained slides were evaluated by conventional eye microscopy and digital image analysis. The chi square test and the kappa statistic were applied by running the SPSS package. Main outcome measures :The levels of staining intensity were estimated by the performance of a semi automated image analysis system. Results :HER2/neu gene amplification was detected in 8/50 cases (16%. Chromosome 17 aneuploidy was detected in 19 cases (38%. Significant improvement in interobserver agreement (kappa=0.76 vs. 0.94 was achieved correlating the immunohistochemical results obtained by conventional eye and digital microscopy, especially in the cases of overexpression (2+, 3+. Finally, 29 (58%, 11 (22%, 6 (12% and 4 (8% cases were characterized as 0, 1+, 2+ and 3+, respectively. HER2/neu protein expression was significantly associated with grade (P=0.019, but not with stage (P=0.466. in addition, chromosome 17 and gene status were not correlated with stage and grade.. Conclusion :Our results indicate that a subset of pancreatic ductal adenocarcinomas is characterized by HER2/neu gene amplification. In contrast to breast cancer, protein overexpression does not predict this specific gene deregulation mechanism. This event may reflect the different biological role of the molecule in those two solid tumours, affecting the response to novel targeted agents, such as monoclonal anti-HER2/neu

  14. Gene Expression Profiling of Colorectal Tumors and Normal Mucosa by Microarrays Meta-Analysis Using Prediction Analysis of Microarray, Artificial Neural Network, Classification, and Regression Trees

    Directory of Open Access Journals (Sweden)

    Chi-Ming Chu

    2014-01-01

    Full Text Available Background. Microarray technology shows great potential but previous studies were limited by small number of samples in the colorectal cancer (CRC research. The aims of this study are to investigate gene expression profile of CRCs by pooling cDNA microarrays using PAM, ANN, and decision trees (CART and C5.0. Methods. Pooled 16 datasets contained 88 normal mucosal tissues and 1186 CRCs. PAM was performed to identify significant expressed genes in CRCs and models of PAM, ANN, CART, and C5.0 were constructed for screening candidate genes via ranking gene order of significances. Results. The first screening identified 55 genes. The test accuracy of each model was over 0.97 averagely. Less than eight genes achieve excellent classification accuracy. Combining the results of four models, we found the top eight differential genes in CRCs; suppressor genes, CA7, SPIB, GUCA2B, AQP8, IL6R and CWH43; oncogenes, SPP1 and TCN1. Genes of higher significances showed lower variation in rank ordering by different methods. Conclusion. We adopted a two-tier genetic screen, which not only reduced the number of candidate genes but also yielded good accuracy (nearly 100%. This method can be applied to future studies. Among the top eight genes, CA7, TCN1, and CWH43 have not been reported to be related to CRC.

  15. Microarray Applications in Cancer Research

    Science.gov (United States)

    Kim, Il-Jin; Kang, Hio Chung

    2004-01-01

    DNA microarray technology permits simultaneous analysis of thousands of DNA sequences for genomic research and diagnostics applications. Microarray technology represents the most recent and exciting advance in the application of hybridization-based technology for biological sciences analysis. This review focuses on the classification (oligonucleotide vs. cDNA) and application (mutation-genotyping vs. gene expression) of microarrays. Oligonucleotide microarrays can be used both in mutation-genotyping and gene expression analysis, while cDNA microarrays can only be used in gene expression analysis. We review microarray mutation analysis, including examining the use of three oligonucleotide microarrays developed in our laboratory to determine mutations in RET, β-catenin and K-ras genes. We also discuss the use of the Affymetrix GeneChip in mutation analysis. We review microarray gene expression analysis, including the classifying of such studies into four categories: class comparison, class prediction, class discovery and identification of biomarkers. PMID:20368836

  16. Development of a microarray for two rice subspecies: characterization and validation of gene expression in rice tissues.

    Science.gov (United States)

    Chen, Jia-Shing; Lin, Shang-Chi; Chen, Chia-Ying; Hsieh, Yen-Ting; Pai, Ping-Hui; Chen, Long-Kung; Lee, Shengwan

    2014-01-08

    Rice is one of the major crop species in the world helping to sustain approximately half of the global population's diet especially in Asia. However, due to the impact of extreme climate change and global warming, rice crop production and yields may be adversely affected resulting in a world food crisis. Researchers have been keen to understand the effects of drought, temperature and other environmental stress factors on rice plant growth and development. Gene expression microarray technology represents a key strategy for the identification of genes and their associated expression patterns in response to stress. Here, we report on the development of the rice OneArray® microarray platform which is suitable for two major rice subspecies, japonica and indica. The rice OneArray® 60-mer, oligonucleotide microarray consists of a total of 21,179 probes covering 20,806 genes of japonica and 13,683 genes of indica. Through a validation study, total RNA isolated from rice shoots and roots were used for comparison of gene expression profiles via microarray examination. The results were submitted to NCBI's Gene Expression Omnibus (GEO). Data can be found under the GEO accession number GSE50844 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE50844). A list of significantly differentially expressed genes was generated; 438 shoot-specific genes were identified among 3,138 up-regulated genes, and 463 root-specific genes were found among 3,845 down-regulated genes. GO enrichment analysis demonstrates these results are in agreement with the known physiological processes of the different organs/tissues. Furthermore, qRT-PCR validation was performed on 66 genes, and found to significantly correlate with the microarray results (R = 0.95, p microarray, the first rice microarray, covering both japonica and indica subspecies was designed and validated in a comprehensive study of gene expression in rice tissues. The rice OneArray® microarray platform revealed high specificity and

  17. Analysis of gene expression in resynthesized Brassica napus Allopolyploids using arabidopsis 70mer oligo microarrays.

    Directory of Open Access Journals (Sweden)

    Robert T Gaeta

    Full Text Available BACKGROUND: Studies in resynthesized Brassica napus allopolyploids indicate that homoeologous chromosome exchanges in advanced generations (S(5ratio6 alter gene expression through the loss and doubling of homoeologous genes within the rearrangements. Rearrangements may also indirectly affect global gene expression if homoeologous copies of gene regulators within rearrangements have differential affects on the transcription of genes in networks. METHODOLOGY/PRINCIPAL FINDINGS: We utilized Arabidopsis 70mer oligonucleotide microarrays for exploring gene expression in three resynthesized B. napus lineages at the S(0ratio1 and S(5ratio6 generations as well as their diploid progenitors B. rapa and B. oleracea. Differential gene expression between the progenitors and additive (midparent expression in the allopolyploids were tested. The S(5ratio6 lines differed in the number of genetic rearrangements, allowing us to test if the number of genes displaying nonadditive expression was related to the number of rearrangements. Estimates using per-gene and common variance ANOVA models indicated that 6-15% of 26,107 genes were differentially expressed between the progenitors. Individual allopolyploids showed nonadditive expression for 1.6-32% of all genes. Less than 0.3% of genes displayed nonadditive expression in all S(0ratio1 lines and 0.1-0.2% were nonadditive among all S(5ratio6 lines. Differentially expressed genes in the polyploids were over-represented by genes differential between the progenitors. The total number of differentially expressed genes was correlated with the number of genetic changes in S(5ratio6 lines under the common variance model; however, there was no relationship using a per-gene variance model, and many genes showed nonadditive expression in S(0ratio1 lines. CONCLUSIONS/SIGNIFICANCE: Few genes reproducibly demonstrated nonadditive expression among lineages, suggesting few changes resulted from a general response to polyploidization

  18. Hepatic gene expression changes in pigs experimentally infected with the lung pathogen Actinobacillus pleuropneumoniae as analysed with an innate immunity focused microarray

    DEFF Research Database (Denmark)

    Skovgaard, Kerstin; Mortensen, Shila; Boye, Mette

    2010-01-01

    response of genes associated with innate immune responses was studied in pigs 14–18 h after intranasal inoculation with Actinobacillus pleuropneumoniae, using innate immune focused microarrays and quantitative real-time PCR (qPCR). The microarray analysis of liver tissue established that 51 genes were...

  19. Immune and inflammatory gene signature in rat cerebrum in subarachnoid hemorrhage with microarray analysis.

    Science.gov (United States)

    Lee, Chu-I; Chou, An-Kuo; Lin, Ching-Chih; Chou, Chia-Hua; Loh, Joon-Khim; Lieu, Ann-Shung; Wang, Chih-Jen; Huang, Chi-Ying F; Howng, Shen-Long; Hong, Yi-Ren

    2012-01-01

    Cerebral vasospasm following subarachnoid hemorrhage (SAH) has been studied in terms of a contraction of the major cerebral arteries, but the effect of cerebrum tissue in SAH is not yet well understood. To gain insight into the biology of SAH-expressing cerebrum, we employed oligonucleotide microarrays to characterize the gene expression profiles of cerebrum tissue at the early stage of SAH. Functional gene expression in the cerebrum was analyzed 2 h following stage 1-hemorrhage in Sprague-Dawley rats. mRNA was investigated by performing microarray and quantitative real-time PCR analyses, and protein expression was determined by Western blot analysis. In this study, 18 upregulated and 18 downregulated genes displayed at least a 1.5-fold change. Five genes were verified by real-time PCR, including three upregulated genes [prostaglandin E synthase (PGES), CD14 antigen, and tissue inhibitor of metalloproteinase 1 (TIMP1)] as well as two downregulated genes [KRAB-zinc finger protein-2 (KZF-2) and γ-aminobutyric acid B receptor 1 (GABA B receptor)]. Notably, there were functional implications for the three upregulated genes involved in the inflammatory SAH process. However, the mechanisms leading to decreased KZF-2 and GABA B receptor expression in SAH have never been characterized. We conclude that oligonucleotide microarrays have the potential for use as a method to identify candidate genes associated with SAH and to provide novel investigational targets, including genes involved in the immune and inflammatory response. Furthermore, understanding the regulation of MMP9/TIMP1 during the early stages of SAH may elucidate the pathophysiological mechanisms in SAH rats.

  20. Identification of Differentially Expressed IGFBP5-Related Genes in Breast Cancer Tumor Tissues Using cDNA Microarray Experiments

    OpenAIRE

    2015-01-01

    IGFBP5 is an important regulatory protein in breast cancer progression. We tried to identify differentially expressed genes (DEGs) between breast tumor tissues with IGFBP5 overexpression and their adjacent normal tissues. In this study, thirty-eight breast cancer and adjacent normal breast tissue samples were used to determine IGFBP5 expression by qPCR. cDNA microarrays were applied to the highest IGFBP5 overexpressed tumor samples compared to their adjacent normal breast tissue. Microarray a...

  1. Gene Expression Profile Differences in Gastric Cancer and Normal Gastric Mucosa by Oligonucleotide Microarrays

    Institute of Scientific and Technical Information of China (English)

    Chuanding Yu; Shenhua Xu; HangZhou Mou; Zhiming Jiang; Chihong Zhu; Xianglin Liu

    2006-01-01

    OBJECTIVE To study the difference of gene expression in gastric cancer (T) and normal tissue of gastric mucosa (C), and to screen for associated novel genes in gastric cancers by oligonucleotide microarrays.METHODS U133A (Affymetrix, Santa Clara, CA) gene chip was used to detect the gene expression profile difference in T and C. Bioinformatics was used to analyze the detected results.RESULTS When gastric cancers were compared with normal gastric mucosa, a total of 270 genes were found with a difference of more than 9times in expression levels. Of the 270 genes, 157 were up-regulated (Signal Log Ratio [SLR] ≥3), and 113 were down-regulated (SLR ≤-3).Using a classification of function, the highest number of gene expression differences related to enzymes and their regulatory genes (67, 24.8%),followed by signal-transduction genes (43,15.9%). The third were nucleic acid binding genes (17, 6.3%), fourth were transporter genes (15, 5.5%)and fifth were protein binding genes (12, 4.4%). In addition there were 50genes of unknown function, accounting for 18.5%. The five above mentioned groups made up 56.9% of the total gene number.CONCLUSION The 5 gene groups (enzymes and their regulatory proteins, signal transduction proteins, nucleic acid binding proteins, transporter and protein binding) were abnormally expressed and are important genes for further study in gastric cancers.

  2. Improving oligonucleotide fingerprinting of rRNA genes by implementation of polony microarray technology

    Science.gov (United States)

    Ruegger, Paul M.; Bent, Elizabeth; Li, Wei; Jeske, Daniel R.; Cui, Xinping; Braun, Jonathan; Jiang, Tao; Borneman, James

    2012-01-01

    Improvements to oligonucleotide fingerprinting of rRNA genes (OFRG) were obtained by implementing polony microarray technology. OFRG is an array-based method for analyzing microbial community composition. Polonies are discrete clusters of DNA, produced by solid-phase PCR in hydrogels, and derived from individual, spatially isolated DNA molecules. The advantages of a polony-based OFRG method include higher throughput and reductions in the PCR-induced errors and compositional skew inherent in all other PCR-based community composition methods, including high throughput sequencing of rRNA genes. Given the similarities between polony microarrays and certain aspects of sequencing methods such as the Illumina platform, we suggest that if concepts presented in this study were implemented in high throughput sequencing protocols, a reduction of PCR-induced errors and compositional skew may be realized. PMID:22640891

  3. A custom microarray platform for analysis of microRNA gene expression.

    Science.gov (United States)

    Thomson, J Michael; Parker, Joel; Perou, Charles M; Hammond, Scott M

    2004-10-01

    MicroRNAs are short, noncoding RNA transcripts that post-transcriptionally regulate gene expression. Several hundred microRNA genes have been identified in Caenorhabditis elegans, Drosophila, plants and mammals. MicroRNAs have been linked to developmental processes in C. elegans, plants and humans and to cell growth and apoptosis in Drosophila. A major impediment in the study of microRNA function is the lack of quantitative expression profiling methods. To close this technological gap, we have designed dual-channel microarrays that monitor expression levels of 124 mammalian microRNAs. Using these tools, we observed distinct patterns of expression among adult mouse tissues and embryonic stem cells. Expression profiles of staged embryos demonstrate temporal regulation of a large class of microRNAs, including members of the let-7 family. This microarray technology enables comprehensive investigation of microRNA expression, and furthers our understanding of this class of recently discovered noncoding RNAs.

  4. Cerebellin and des-cerebellin exert ACTH-like effects on corticosterone secretion and the intracellular signaling pathway gene expression in cultured rat adrenocortical cells--DNA microarray and QPCR studies.

    Science.gov (United States)

    Rucinski, Marcin; Ziolkowska, Agnieszka; Szyszka, Marta; Malendowicz, Ludwik K

    2009-04-01

    Precerebellins (Cbln) belong to the C1q/TNF superfamily of secreted proteins which have diverse functions. They are abundantly expressed in the cerebellum, however, three of them are also expressed in the rat adrenal gland. All members of the Cbln family form homomeric and heteromeric complexes with each other in vitro and it was suggested that such complexes play a crucial role in normal development of the cerebellum. The aim of our study was to investigate whether Cbln1-derived peptides, cerebellin (CER) and des-Ser1-cerebellin (desCER) are involved in regulating biological functions of rat adrenocortical cells. In the primary culture of rat adrenocortical cells, 24 h exposure to CER or desCER notably stimulated corticosterone output and inhibited proliferative activity and similar effects were evoked by ACTH. To study gene transcript regulation by CER, desCER and ACTH, we applied Oligo GEArray DNA Microarray: Rat Signal Transduction Pathway Finder. In relation to the control culture, 13 of the 113 transcripts present on the array were differentially expressed. These transcripts were either up- or down-regulated by ACTH and/or CER or desCER treatment. Validation of DNA Microarray data by QPCR revealed that only 5 of 13 genes studied were differentially expressed. Of those genes, Fos and Icam1 were up-regulated and Egr1 was down-regulated by ACTH, CER and desCER. The remaining two genes, Fasn (insulin signaling pathway) and Hspb1 (HSP27) (stress signaling pathway), were regulated only by CER and desCER, but not by ACTH. Thus, both CER and desCER have effects similar to and different from corticotrophin on the intracellular signaling pathway gene expression in cultured rat adrenocortical cells.

  5. Microarray analysis of genes affected by salt stress in tomato | Zhou ...

    African Journals Online (AJOL)

    Microarray analysis of genes affected by salt stress in tomato. ... African Journal of Environmental Science and Technology ... key enzyme genes in the metabolic pathways of carbohydrates, amino acids, and fatty acids, were also affected by ...

  6. Microarray-Based Differential Expression Monitoring of 79 Novel Genes in Human Fetal Tissues

    Institute of Scientific and Technical Information of China (English)

    Ma; Shu-hua; Wang; Dun-cheng; 等

    2003-01-01

    79 ESTs fragments with represents corresponding novel genes were obtained by sequencing and bioinformatics analysis of human fetal kidney cDNA library. Microarray was prepared by using these novel EST fragments by automatic spotting. Expression patters of 79 ESTs of novel genes from human fetal kidney were analyzed in fetal brain and fetal heart tissues of 20-week-and 26-week-age fetus by performing of cDNA chip hybridization. This provides clues for studying exact functions of the novel genes. 8 genes were obtained which were expressed differentially in the fetal brain and heart of 20-week-and 26-week-age respectively. Then differentially expressed genes were identified by Northern analysis. The more exact function of the novel genes is under study.

  7. Analysis of differences of gene expressions in keloid and normal skin with the aid of cDNA microarray

    Institute of Scientific and Technical Information of China (English)

    Chen Wei; Fu Xiaobing; Sun Xiaoqing; Sun Tongzhu; Zhao Zhili; Yang Yinhui; Sheng Zhiyong

    2003-01-01

    Background: Microarray analysis is a popular tool to investigate the function of genes that are responsible for the phenotype of the disease. Keloid is a intricate lesion which is probably modulated by interplay of many genes. We ventured to study the differences of gene expressions between keloids and normal skins with the aid of cDNA microarray in order to explore the molecular mechanism underlying keloid formation. Methods: The PCR products of 8400 human genes were spotted on a chip in array. The DNAs were then fixed on the glass plate by a series of treatments. Total RNAs was isolated from freshly excised human keloids and normal skin, and then was purified to mRNA by Oligotex. Both the mRNA from keloids and normal skin was reversely transcribed to cDNAs with the incorporations of fluorescent dUTP, for preparing the hybridization probes. The mixed probes were then hybridized to the cDNA microarray. After highly stringent washing, the cDNA microarray was scanned for the fluorescent signals to display the differences between two kinds of tissues. Results: Among 8400 human genes, there were 402 genes (4.79%) with different expression levels between the keloids and normal skins in all cases, 250were up-regulated (2.98%) and 152 down-regulated (1.81%). Analyses of collagen, fibronectin, proteoglycan,growth factors and apoptosis related molecule gene expression confirmed that our molecular data obtained by cDNA microarray were consistent with published biochemical and clinical observations of keloids. Conclusions: DNA microarray technology is an effective technique in screening for differences in gene expression between keloid and normal skin. Many genes are involved in the formation of keloids. Further analysis of the obtained genes will help understand the molecular mechanism of keloid formation.

  8. Analysis of gene expression profiles in human systemic lupus erythematosus using oligonucleotide microarray.

    Science.gov (United States)

    Han, G-M; Chen, S-L; Shen, N; Ye, S; Bao, C-D; Gu, Y-Y

    2003-04-01

    Epidemiologic studies suggest a strong genetic component for susceptibility to systemic lupus erythematosus (SLE). To investigate the genetic mechanism of pathogenesis of SLE, we studied the difference in gene expression of peripheral blood cells between 10 SLE patients and 18 healthy controls using oligonucleotide microarray. When gene expression for patients was compared to the mean of normal controls, among the 3002 target genes, 61 genes were identified with greater than a two-fold change difference in expression level. Of these genes, 24 were upregulated and 37 downregulated in at least half of the patients. By the Welch's ANOVA/Welch's t-test, all these 61 genes were significantly different (PTSA-1/Sca-2) may play an important role in the mechanism of SLE pathogenesis. TSA-1 antigens may represent an important alternative pathway for T-cell activation that may be involved in IFN-mediated immunomodulation. Hierarchical clustering showed that patient samples were clearly separated from controls based on their gene expression profile. These results demonstrate that high-density oligonucleotide microarray has the potential to explore the mechanism of pathogenesis of systemic lupus erythematosus.

  9. Identification of Differentially Expressed Genes in Pituitary Adenomas by Integrating Analysis of Microarray Data

    Directory of Open Access Journals (Sweden)

    Peng Zhao

    2015-01-01

    Full Text Available Pituitary adenomas, monoclonal in origin, are the most common intracranial neoplasms. Altered gene expression as well as somatic mutations is detected frequently in pituitary adenomas. The purpose of this study was to detect differentially expressed genes (DEGs and biological processes during tumor formation of pituitary adenomas. We performed an integrated analysis of publicly available GEO datasets of pituitary adenomas to identify DEGs between pituitary adenomas and normal control (NC tissues. Gene function analysis including Gene Ontology (GO, Kyoto Encyclopedia of Genes and Genomes (KEGG pathway enrichment analysis, and protein-protein interaction (PPI networks analysis was conducted to interpret the biological role of those DEGs. In this study we detected 3994 DEGs (2043 upregulated and 1951 downregulated in pituitary adenoma through an integrated analysis of 5 different microarray datasets. Gene function analysis revealed that the functions of those DEGs were highly correlated with the development of pituitary adenoma. This integrated analysis of microarray data identified some genes and pathways associated with pituitary adenoma, which may help to understand the pathology underlying pituitary adenoma and contribute to the successful identification of therapeutic targets for pituitary adenoma.

  10. Discovery and analysis of inflammatory disease-related genes using cDNA microarrays

    OpenAIRE

    1997-01-01

    cDNA microarray technology is used to profile complex diseases and discover novel disease-related genes. In inflammatory disease such as rheumatoid arthritis, expression patterns of diverse cell types contribute to the pathology. We have monitored gene expression in this disease state with a microarray of selected human genes of probable significance in inflammation as well as with genes expressed in peripheral human blood cells. Messenger RNA from cultured macrophages, chondrocyte cell lines...

  11. Methods for interpreting lists of affected genes obtained in a DNA microarray experiment

    Directory of Open Access Journals (Sweden)

    Hedegaard Jakob

    2009-07-01

    Full Text Available Abstract Background The aim of this paper was to describe and compare the methods used and the results obtained by the participants in a joint EADGENE (European Animal Disease Genomic Network of Excellence and SABRE (Cutting Edge Genomics for Sustainable Animal Breeding workshop focusing on post analysis of microarray data. The participating groups were provided with identical lists of microarray probes, including test statistics for three different contrasts, and the normalised log-ratios for each array, to be used as the starting point for interpreting the affected probes. The data originated from a microarray experiment conducted to study the host reactions in broilers occurring shortly after a secondary challenge with either a homologous or heterologous species of Eimeria. Results Several conceptually different analytical approaches, using both commercial and public available software, were applied by the participating groups. The following tools were used: Ingenuity Pathway Analysis, MAPPFinder, LIMMA, GOstats, GOEAST, GOTM, Globaltest, TopGO, ArrayUnlock, Pathway Studio, GIST and AnnotationDbi. The main focus of the approaches was to utilise the relation between probes/genes and their gene ontology and pathways to interpret the affected probes/genes. The lack of a well-annotated chicken genome did though limit the possibilities to fully explore the tools. The main results from these analyses showed that the biological interpretation is highly dependent on the statistical method used but that some common biological conclusions could be reached. Conclusion It is highly recommended to test different analytical methods on the same data set and compare the results to obtain a reliable biological interpretation of the affected genes in a DNA microarray experiment.

  12. Integrated Microfluidic Devices for Automated Microarray-Based Gene Expression and Genotyping Analysis

    Science.gov (United States)

    Liu, Robin H.; Lodes, Mike; Fuji, H. Sho; Danley, David; McShea, Andrew

    Microarray assays typically involve multistage sample processing and fluidic handling, which are generally labor-intensive and time-consuming. Automation of these processes would improve robustness, reduce run-to-run and operator-to-operator variation, and reduce costs. In this chapter, a fully integrated and self-contained microfluidic biochip device that has been developed to automate the fluidic handling steps for microarray-based gene expression or genotyping analysis is presented. The device consists of a semiconductor-based CustomArray® chip with 12,000 features and a microfluidic cartridge. The CustomArray was manufactured using a semiconductor-based in situ synthesis technology. The micro-fluidic cartridge consists of microfluidic pumps, mixers, valves, fluid channels, and reagent storage chambers. Microarray hybridization and subsequent fluidic handling and reactions (including a number of washing and labeling steps) were performed in this fully automated and miniature device before fluorescent image scanning of the microarray chip. Electrochemical micropumps were integrated in the cartridge to provide pumping of liquid solutions. A micromixing technique based on gas bubbling generated by electrochemical micropumps was developed. Low-cost check valves were implemented in the cartridge to prevent cross-talk of the stored reagents. Gene expression study of the human leukemia cell line (K562) and genotyping detection and sequencing of influenza A subtypes have been demonstrated using this integrated biochip platform. For gene expression assays, the microfluidic CustomArray device detected sample RNAs with a concentration as low as 0.375 pM. Detection was quantitative over more than three orders of magnitude. Experiment also showed that chip-to-chip variability was low indicating that the integrated microfluidic devices eliminate manual fluidic handling steps that can be a significant source of variability in genomic analysis. The genotyping results showed

  13. Oligonucleotide microarray identifies genes differentially expressed during tumorigenesis of DMBA-induced pancreatic cancer in rats.

    Directory of Open Access Journals (Sweden)

    Jun-Chao Guo

    Full Text Available The extremely dismal prognosis of pancreatic cancer (PC is attributed, at least in part, to lack of early diagnosis. Therefore, identifying differentially expressed genes in multiple steps of tumorigenesis of PC is of great interest. In the present study, a 7,12-dimethylbenzanthraene (DMBA-induced PC model was established in male Sprague-Dawley rats. The gene expression profile was screened using an oligonucleotide microarray, followed by real-time quantitative polymerase chain reaction (qRT-PCR and immunohistochemical staining validation. A total of 661 differentially expressed genes were identified in stages of pancreatic carcinogenesis. According to GO classification, these genes were involved in multiple molecular pathways. Using two-way hierarchical clustering analysis, normal pancreas, acute and chronic pancreatitis, PanIN, early and advanced pancreatic cancer were completely discriminated. Furthermore, 11 upregulated and 142 downregulated genes (probes were found by Mann-Kendall trend Monotone test, indicating homologous genes of rat and human. The qRT-PCR and immunohistochemistry analysis of CXCR7 and UBe2c, two of the identified genes, confirmed the microarray results. In human PC cell lines, knockdown of CXCR7 resulted in decreased migration and invasion. Collectively, our data identified several promising markers and therapeutic targets of PC based on a comprehensive screening and systemic validation.

  14. Oligonucleotide microarray identifies genes differentially expressed during tumorigenesis of DMBA-induced pancreatic cancer in rats.

    Science.gov (United States)

    Guo, Jun-Chao; Li, Jian; Yang, Ying-Chi; Zhou, Li; Zhang, Tai-Ping; Zhao, Yu-Pei

    2013-01-01

    The extremely dismal prognosis of pancreatic cancer (PC) is attributed, at least in part, to lack of early diagnosis. Therefore, identifying differentially expressed genes in multiple steps of tumorigenesis of PC is of great interest. In the present study, a 7,12-dimethylbenzanthraene (DMBA)-induced PC model was established in male Sprague-Dawley rats. The gene expression profile was screened using an oligonucleotide microarray, followed by real-time quantitative polymerase chain reaction (qRT-PCR) and immunohistochemical staining validation. A total of 661 differentially expressed genes were identified in stages of pancreatic carcinogenesis. According to GO classification, these genes were involved in multiple molecular pathways. Using two-way hierarchical clustering analysis, normal pancreas, acute and chronic pancreatitis, PanIN, early and advanced pancreatic cancer were completely discriminated. Furthermore, 11 upregulated and 142 downregulated genes (probes) were found by Mann-Kendall trend Monotone test, indicating homologous genes of rat and human. The qRT-PCR and immunohistochemistry analysis of CXCR7 and UBe2c, two of the identified genes, confirmed the microarray results. In human PC cell lines, knockdown of CXCR7 resulted in decreased migration and invasion. Collectively, our data identified several promising markers and therapeutic targets of PC based on a comprehensive screening and systemic validation.

  15. Tests for differential gene expression using weights in oligonucleotide microarray experiments

    Directory of Open Access Journals (Sweden)

    Beyene Joseph

    2006-02-01

    Full Text Available Abstract Background Microarray data analysts commonly filter out genes based on a number of ad hoc criteria prior to any high-level statistical analysis. Such ad hoc approaches could lead to conflicting conclusions with no clear guidance as to which method is most likely to be reproducible. Furthermore, the number of tests performed with concomitant inflation in type I error also plagues the statistical analysis of microarray data, since the number of tested quantities in a study significantly affects the family-wise error rate. It would, therefore, be very useful to develop and adopt strategies that allow quantification of the quality of each probeset, to filter out or give little credence to low-quality or unexpressed probesets, and to incorporate these strategies into gene selection within a multiple testing framework. Results We have proposed a unified scheme for filtering and gene selection. For Affymetrix gene expression microarrays, we developed new methods for measuring the reliability of a particular probeset in a single array, and we used these to develop measures for a set of arrays. These measures are then used as weights in standard t-statistic calculations, and are incorporated into the multiple testing procedures. We demonstrated the advantages of our methods using simulated data, publicly available spiked-in data as well as data comparing normal muscle to muscle from patients with Duchenne muscular dystrophy (DMD, in which a set of truly differentially expressed genes is known. Conclusion Our quality measures provide convenient ways to search for individual genes of high quality. The quality weighting strategies we proposed for testing differential gene expression have demonstrable improvement on the traditional filtering methods, the standard t-statistic and a regularized t-statistic in Affymetrix data analysis.

  16. Variability of DNA Microarray Gene Expression Profiles in Cultured Rat Primary Hepatocytes

    Directory of Open Access Journals (Sweden)

    Jun Xu

    2007-01-01

    Full Text Available DNA microarray is a powerful tool in biomedical research. However, transcriptomic profiling using DNA microarray is subject to many variations including biological variability. To evaluate the different sources of variation in mRNA gene expression profiles, gene expression profiles were monitored using the Affymetrix RatTox U34 arrays in cultured primary hepatocytes derived from six rats over a 26 hour period at 6 time points (0h, 2h, 5h, 8h, 14h and 26h with two replicate arrays at each time point for each animal. In addition, the impact of sample size on the variability of differentially expressed gene lists and the consistency of biological responses were also investigated. Excellent intra-animal reproducibility was obtained at all time points with 0 out of 370 present probe sets across all time points showing significant difference between the 2 replicate arrays (3-way ANOVA, p 0.0001. However, large inter-animal biological variation in mRNA expression profi les was observed with 337 out of 370 present probe sets showing significant differences among 6 animals (3-way ANOVA, p 0.05. Principal Component Analysis (PCA revealed that time effect (PC1 in this data set accounted for 47.4% of total variance indicating the dynamics of transcriptomics. The second and third largest effects came from animal difference, which accounted for 16.9% (PC2 and PC3 of the total variance. The reproducibility of gene lists and their functional classification was declined considerably when the sample size was decreased. Overall, our results strongly support that there is significant inter-animal variability in the time-course gene expression profi les, which is a confounding factor that must be carefully evaluated to correctly interpret microarray gene expression studies. The consistency of the gene lists and their biological functional classification are also sensitive to sample size with the reproducibility decreasing considerably under small sample size.

  17. Uso de microarrays na busca de perfis de expressão gênica: aplicação no estudo de fenótipos complexos Use of microarrays in the search of gene expression patterns: application to the study of complex phenotypes

    Directory of Open Access Journals (Sweden)

    Camila Guindalini

    2007-12-01

    . By the simultaneous determination of the expression levels of thousands of genes, microarrays allow researchers to compare the molecular behaviour of different types of cells lines or specific tissues that have been exposed to pathological or experimental conditions. The method may provide insights into physiological processes and facilitate the identification of novel biological markers for diagnostic, prognostic and pharmacological treatments for a number of diseases. In this article, we present theoretical and methodological concepts underlying the microarray technology, as well as an overview of its advantages, perspectives and future scientific directions. In an attempt to demonstrate the applicability and efficiency of the method in the study of complex phenotypes, initial results on gene expression studies in post mortem brain samples of psychiatric patients and on the molecular and functional consequences of sleep disturbances, which is strongly associated with psychiatric illness, will be described and discussed.

  18. Comparative analysis of gene expression by microarray analysis of male and female flowers of Asparagus officinalis.

    Science.gov (United States)

    Gao, Wu-Jun; Li, Shu-Fen; Zhang, Guo-Jun; Wang, Ning-Na; Deng, Chuan-Liang; Lu, Long-Dou

    2013-01-01

    To identify rapidly a number of genes probably involved in sex determination and differentiation of the dioecious plant Asparagus officinalis, gene expression profiles in early flower development for male and female plants were investigated by microarray assay with 8,665 probes. In total, 638 male-biased and 543 female-biased genes were identified. These genes with biased-expression for male and female were involved in a variety of processes associated with molecular functions, cellular components, and biological processes, suggesting that a complex mechanism underlies the sex development of asparagus. Among the differentially expressed genes involved in the reproductive process, a number of genes associated with floral development were identified. Reverse transcription-PCR was performed for validation, and the results were largely consistent with those obtained by microarray analysis. The findings of this study might contribute to understanding of the molecular mechanisms of sex determination and differentiation in dioecious asparagus and provide a foundation for further studies of this plant.

  19. Quality control in microarray assessment of gene expression in human airway epithelium

    Directory of Open Access Journals (Sweden)

    Attiyeh Marc A

    2009-10-01

    Full Text Available Abstract Background Microarray technology provides a powerful tool for defining gene expression profiles of airway epithelium that lend insight into the pathogenesis of human airway disorders. The focus of this study was to establish rigorous quality control parameters to ensure that microarray assessment of the airway epithelium is not confounded by experimental artifact. Samples (total n = 223 of trachea, large and small airway epithelium were collected by fiberoptic bronchoscopy of 144 individuals and hybridized to Affymetrix microarrays. The pre- and post-chip quality control (QC criteria established, included: (1 RNA quality, assessed by RNA Integrity Number (RIN ≥ 7.0; (2 cRNA transcript integrity, assessed by signal intensity ratio of GAPDH 3' to 5' probe sets ≤ 3.0; and (3 the multi-chip normalization scaling factor ≤ 10.0. Results Of the 223 samples, all three criteria were assessed in 191; of these 184 (96.3% passed all three criteria. For the remaining 32 samples, the RIN was not available, and only the other two criteria were used; of these 29 (90.6% passed these two criteria. Correlation coefficients for pairwise comparisons of expression levels for 100 maintenance genes in which at least one array failed the QC criteria (average Pearson r = 0.90 ± 0.04 were significantly lower (p Conclusion Based on the aberrant maintenance gene data generated from samples failing the established QC criteria, we propose that the QC criteria outlined in this study can accurately distinguish high quality from low quality data, and can be used to delete poor quality microarray samples before proceeding to higher-order biological analyses and interpretation.

  20. Microarray based gene expression analysis of murine brown and subcutaneous adipose tissue: significance with human.

    Science.gov (United States)

    Baboota, Ritesh K; Sarma, Siddhartha M; Boparai, Ravneet K; Kondepudi, Kanthi Kiran; Mantri, Shrikant; Bishnoi, Mahendra

    2015-01-01

    Two types of adipose tissues, white (WAT) and brown (BAT) are found in mammals. Increasingly novel strategies are being proposed for the treatment of obesity and its associated complications by altering amount and/or activity of BAT using mouse models. The present study was designed to: (a) investigate the differential expression of genes in LACA mice subcutaneous WAT (sWAT) and BAT using mouse DNA microarray, (b) to compare mouse differential gene expression with previously published human data; to understand any inter- species differences between the two and (c) to make a comparative assessment with C57BL/6 mouse strain. In mouse microarray studies, over 7003, 1176 and 401 probe sets showed more than two-fold, five-fold and ten-fold change respectively in differential expression between murine BAT and WAT. Microarray data was validated using quantitative RT-PCR of key genes showing high expression in BAT (Fabp3, Ucp1, Slc27a1) and sWAT (Ms4a1, H2-Ob, Bank1) or showing relatively low expression in BAT (Pgk1, Cox6b1) and sWAT (Slc20a1, Cd74). Multi-omic pathway analysis was employed to understand possible links between the organisms. When murine two fold data was compared with published human BAT and sWAT data, 90 genes showed parallel differential expression in both mouse and human. Out of these 90 genes, 46 showed same pattern of differential expression whereas the pattern was opposite for the remaining 44 genes. Based on our microarray results and its comparison with human data, we were able to identify genes (targets) (a) which can be studied in mouse model systems to extrapolate results to human (b) where caution should be exercised before extrapolation of murine data to human. Our study provides evidence for inter species (mouse vs human) differences in differential gene expression between sWAT and BAT. Critical understanding of this data may help in development of novel ways to engineer one form of adipose tissue to another using murine model with focus on

  1. Mitochondrial and oxidative stress genes are differentially expressed in neutrophils of sJIA patients treated with tocilizumab: a pilot microarray study

    OpenAIRE

    Omoyinmi, E; Hamaoui, R.; Bryant, A.; Jiang, M. C.; Athigapanich, T.; Eleftheriou, D; Hubank, M; Brogan, P.; Woo, P.

    2016-01-01

    Background Various pathways involved in the pathogenesis of sJIA have been identified through gene expression profiling in peripheral blood mononuclear cells (PBMC), but not in neutrophils. Since neutrophils are important in tissue damage during inflammation, and are elevated as part of the acute phase response, we hypothesised that neutrophil pathways could also be important in the pathogenesis of sJIA. We therefore studied the gene profile in both PBMC and neutrophils of sJIA patients treat...

  2. A microarray screen for novel candidate genes in coeliac disease pathogenesis

    NARCIS (Netherlands)

    Diosdado, B; Wapenaar, MC; Franke, L; Duran, KJ; Goerres, MJ; Hadithi, M; Crusius, JBA; Meijer, JWR; Duggan, DJ; Mulder, CJJ; Holstege, FCP; Wijmenga, C

    Background and aims: The causative molecular pathways underlying the pathogenesis of coeliac disease are poorly understood. To unravel novel aspects of disease pathogenesis, we used microarrays to determine changes in gene expression of duodenal biopsies. Methods: cDNA microarrays representing 19

  3. Complete gene expression profiling of Saccharopolyspora erythraea using GeneChip DNA microarrays

    Directory of Open Access Journals (Sweden)

    Bordoni Roberta

    2007-11-01

    Full Text Available Abstract Background The Saccharopolyspora erythraea genome sequence, recently published, presents considerable divergence from those of streptomycetes in gene organization and function, confirming the remarkable potential of S. erythraea for producing many other secondary metabolites in addition to erythromycin. In order to investigate, at whole transcriptome level, how S. erythraea genes are modulated, a DNA microarray was specifically designed and constructed on the S. erythraea strain NRRL 2338 genome sequence, and the expression profiles of 6494 ORFs were monitored during growth in complex liquid medium. Results The transcriptional analysis identified a set of 404 genes, whose transcriptional signals vary during growth and characterize three distinct phases: a rapid growth until 32 h (Phase A; a growth slowdown until 52 h (Phase B; and another rapid growth phase from 56 h to 72 h (Phase C before the cells enter the stationary phase. A non-parametric statistical method, that identifies chromosomal regions with transcriptional imbalances, determined regional organization of transcription along the chromosome, highlighting differences between core and non-core regions, and strand specific patterns of expression. Microarray data were used to characterize the temporal behaviour of major functional classes and of all the gene clusters for secondary metabolism. The results confirmed that the ery cluster is up-regulated during Phase A and identified six additional clusters (for terpenes and non-ribosomal peptides that are clearly regulated in later phases. Conclusion The use of a S. erythraea DNA microarray improved specificity and sensitivity of gene expression analysis, allowing a global and at the same time detailed picture of how S. erythraea genes are modulated. This work underlines the importance of using DNA microarrays, coupled with an exhaustive statistical and bioinformatic analysis of the results, to understand the transcriptional

  4. A mixture model-based strategy for selecting sets of genes in multiclass response microarray experiments.

    Science.gov (United States)

    Broët, Philippe; Lewin, Alex; Richardson, Sylvia; Dalmasso, Cyril; Magdelenat, Henri

    2004-11-01

    Multiclass response (MCR) experiments are those in which there are more than two classes to be compared. In these experiments, though the null hypothesis is simple, there are typically many patterns of gene expression changes across the different classes that led to complex alternatives. In this paper, we propose a new strategy for selecting genes in MCR that is based on a flexible mixture model for the marginal distribution of a modified F-statistic. Using this model, false positive and negative discovery rates can be estimated and combined to produce a rule for selecting a subset of genes. Moreover, the method proposed allows calculation of these rates for any predefined subset of genes. We illustrate the performance our approach using simulated datasets and a real breast cancer microarray dataset. In this latter study, we investigate predefined subset of genes and point out interesting differences between three distinct biological pathways. http://www.bgx.org.uk/software.html

  5. Classification of microarrays; synergistic effects between normalization, gene selection and machine learning

    Science.gov (United States)

    2011-01-01

    Background Machine learning is a powerful approach for describing and predicting classes in microarray data. Although several comparative studies have investigated the relative performance of various machine learning methods, these often do not account for the fact that performance (e.g. error rate) is a result of a series of analysis steps of which the most important are data normalization, gene selection and machine learning. Results In this study, we used seven previously published cancer-related microarray data sets to compare the effects on classification performance of five normalization methods, three gene selection methods with 21 different numbers of selected genes and eight machine learning methods. Performance in term of error rate was rigorously estimated by repeatedly employing a double cross validation approach. Since performance varies greatly between data sets, we devised an analysis method that first compares methods within individual data sets and then visualizes the comparisons across data sets. We discovered both well performing individual methods and synergies between different methods. Conclusion Support Vector Machines with a radial basis kernel, linear kernel or polynomial kernel of degree 2 all performed consistently well across data sets. We show that there is a synergistic relationship between these methods and gene selection based on the T-test and the selection of a relatively high number of genes. Also, we find that these methods benefit significantly from using normalized data, although it is hard to draw general conclusions about the relative performance of different normalization procedures. PMID:21982277

  6. Analysis of gene expression profile of aspermia using cDNA microarray

    Institute of Scientific and Technical Information of China (English)

    杨波; 高晓康; 王禾; 刘贺亮; 陈宝琦; 秦荣良; 康福霞; 邵国兴; 邵晨

    2003-01-01

    Objective: To identify the differential gene expression profiles between the normal and aspermia human testes utilizing cDNA microarray. Methods: cDNA probes were prepared by labeling mRNA of aspermia testes tissues with Cy5-dUTP and mRNA of normal testes tissues with Cy3-dUTP respectively through reverse transcription. The mixed cDNA probes were then hybridized with 4096 cDNA arrays (4096 unique human cDNA sequences), and the fluorescent signals were scanned by ScanArray 3000 scanner (General Scanning, Inc.). The values of Cy5-dUTP and Cy3-dUTP on each spot were analyzed and calculated by ImaGene 3.0 software (BioDiscovery, Inc.). Differentially expressed genes were screened according to the criterion that the absolute value of natural logarithm of the ratio of Cy5-dUTP to Cy3-dUTP was greater-than 2.0 or less-than 0.5. A randomly chosen gene RAP1A was studied by in situ hybridization to evaluate the accuracy of the results. Results: 623 differential expressed genes related to aspermia were found. There were 303 up-expressed genes and 320 down-expressed genes. A distinct up-expressed gene RAP1A was confirmed by in situ hybridization. Conclusions: Screening the differential gene expression profiles between the normal and aspermia human testis by cDNA microarray can be used in the study of aspermia-related genes and the further research due to its properties, RAP1A may play some roles in the development and progression of aspermia.

  7. Whole-Genome Microarray and Gene Deletion Studies Reveal Regulation of the Polyhydroxyalkanoate Production Cycle by the Stringent Response in Ralstonia eutropha H16

    Energy Technology Data Exchange (ETDEWEB)

    Brigham, CJ; Speth, DR; Rha, C; Sinskey, AJ

    2012-10-22

    Poly(3-hydroxybutyrate) (PHB) production and mobilization in Ralstonia eutropha are well studied, but in only a few instances has PHB production been explored in relation to other cellular processes. We examined the global gene expression of wild-type R. eutropha throughout the PHB cycle: growth on fructose, PHB production using fructose following ammonium depletion, and PHB utilization in the absence of exogenous carbon after ammonium was resupplied. Our results confirm or lend support to previously reported results regarding the expression of PHB-related genes and enzymes. Additionally, genes for many different cellular processes, such as DNA replication, cell division, and translation, are selectively repressed during PHB production. In contrast, the expression levels of genes under the control of the alternative sigma factor sigma(54) increase sharply during PHB production and are repressed again during PHB utilization. Global gene regulation during PHB production is strongly reminiscent of the gene expression pattern observed during the stringent response in other species. Furthermore, a ppGpp synthase deletion mutant did not show an accumulation of PHB, and the chemical induction of the stringent response with DL-norvaline caused an increased accumulation of PHB in the presence of ammonium. These results indicate that the stringent response is required for PHB accumulation in R. eutropha, helping to elucidate a thus-far-unknown physiological basis for this process.

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

    Directory of Open Access Journals (Sweden)

    T. Karthikeyan

    2014-05-01

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

  9. Microarray profiles on age-related genes in the earlier postnatal rat visual cortex

    Institute of Scientific and Technical Information of China (English)

    YANG Liu; NIE Yu-hong; ZHOU Li-hua; LIN Shao-chun; WU Kai-li

    2011-01-01

    Background Accumulating evidence indicates that both innate and adaptive mechanisms are responsible for the postnatal development of the mammalian visual cortex. Most of the studies, including gene expression analysis, were performed on the visual cortex during the critical period; few efforts were made to elucidate the molecular changes in the visual cortex during much earlier postnatal stages. The current study aimed to gain a general insight into the molecular mechanisms in the developmental process of the rat visual cortex using microarray to display the gene expression profiles of the visual cortex on postnatal days.Methods All age-matched Sprague-Dawley rats in various groups including postnatal day 0 (PO, n=20), day 10 (P10,n=15), day 20 (P20, n=15) and day 45 (P45, n=10) were sacrificed respectively. Fresh visual cortex from the binocular area (Area 17) was dissected for extraction of total RNA for microarray analyses. Taking advantage of annotation information from the gene ontology and pathway database, the gene expression profiles were systematically and globally analyzed.Results Of the 31 042 gene sequences represented on the rat expression microarray, more than 4000 of the transcripts significantly altered at days 45,20 or 10 compared to day 0. The most obvious alteration of gene expression occurred in the first ten days of the postnatal period and the genomic activities of the visual cortex maintained a high level from birth to day 45. Compared to the gene expression at birth, there were 2630 changed transcripts that shared in three postnatal periods.The up-regulated genes in most signaling pathways were more than those of the down-regulated genes.Conclusions Analyzing gene expression patterns, we provide a detailed insight into the molecular organization of the developing visual cortex in the earlier postnatal rat. The most obvious alteration of gene expression in visual cortex occurred in the first ten days. Our data were a basis to identify new

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

    Directory of Open Access Journals (Sweden)

    Fabi João Paulo

    2012-12-01

    Full Text Available Abstract 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.

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

    Science.gov (United States)

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

    2013-01-01

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

  12. Exploring Mycobacterium tuberculosis infection-induced alterations in gene expression in macrophage by microarray hybridization

    Institute of Scientific and Technical Information of China (English)

    XIE; Jianping; (谢建平); LI; Yao; (李; 瑶); YUE; Jun; (乐; 军); XU; Yongzhong; (徐永忠); HUANG; Daqiang; (黄达蔷); LIANG; Li; (梁; 莉); WANG; Honghai; (王洪海)

    2003-01-01

    Tuberculosis remains a serious threat to public health. Its causative agent Mycobacte- rium tuberculosis is an intracellular pathogen which survives and replicates within cells of the host immune system, primarily macrophages. Knowledge of the bacteria-macrophage interaction can help to develop novel measures to combat the disease. The global gene expression of macro- phage following invasion by and growth of M. tuberculosis was studied by cDNA microarray. Of the 12800 human genes analyzed, totally 473 (3.7%) macrophage genes were differentially expressed after being infected by M. tuberculosis, among which, only 25 (5.2%, corresponding to less than 0.2% of the 12800 genes) genes were up-regulated, while others (94.8%) were down-regulated against the control. Of the 473 genes, 376 genes are registered in the GenBank, and 97 are novel genes. Expression of 5 up-regulated genes has been induced by more than 3-fold. 25 genes were down-regulated by more than 3-fold. Syndecan binding protein has been down-regu- lated up to 12.5-fold. The data gave an insight into the early gene expression in macrophage ensuing M. tuberculosis infection and a basis for further study.

  13. Sediment denitrifier community composition and nirS gene expression investigated with functional gene microarrays

    DEFF Research Database (Denmark)

    Francis, C.A.; Jackson, G.A.; Ward, B.B.

    2008-01-01

    total RNA extracts) targets were hybridized to the same array to compare the profiles of community composition at the DNA (relative abundance) and mRNA (gene expression) levels. Only the three dominant denitrifying groups (in terms of relative strength of DNA hybridization signal) were detected at the m......A functional gene microarray was used to investigate denitrifier community composition and nitrite reductase (nirS) gene expression in sediments along the estuarine gradient in Chesapeake Bay, USA. The nirS oligonucleotide probe set was designed to represent a sequence database containing 539...

  14. 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

  15. Observation of intermittency in gene expression on cDNA microarrays

    CERN Document Server

    Peterson, L E

    2002-01-01

    We used scaled factorial moments to search for intermittency in the log expression ratios (LERs) for thousands of genes spotted on cDNA microarrays (gene chips). Results indicate varying levels of intermittency in gene expression. The observation of intermittency in the data analyzed provides a complimentary handle on moderately expressed genes, generally not tackled by conventional techniques.

  16. SPERM RNA AMPLIFICATION FOR GENE EXPRESSION PROFILING BY DNA MICROARRAY TECHNOLOGY

    Science.gov (United States)

    Sperm RNA Amplification for Gene Expression Profiling by DNA Microarray TechnologyHongzu Ren, Kary E. Thompson, Judith E. Schmid and David J. Dix, Reproductive Toxicology Division, NHEERL, Office of Research and Development, US Environmental Protection Agency, Research Triang...

  17. Discovering gene expression patterns in time course microarray experiments by ANOVA-SCA

    NARCIS (Netherlands)

    Nueda, M.J.; Conesa, A.; Westerhuis, J.A.; Hoefsloot, H.C.J.; Smilde, A.K.; Talón, M.; Ferrer, A.

    2007-01-01

    Motivation: Designed microarray experiments are used to investigate the effects that controlled experimental factors have on gene expression and learn about the transcriptional responses associated with external variables. In these datasets, signals of interest coexist with varying sources of unwant

  18. A meta analysis of pancreatic microarray datasets yields new targets as cancer genes and biomarkers.

    Directory of Open Access Journals (Sweden)

    Nalin C W Goonesekere

    Full Text Available The lack of specific symptoms at early tumor stages, together with a high biological aggressiveness of the tumor contribute to the high mortality rate for pancreatic cancer (PC, which has a five year survival rate of less than 5%. Improved screening for earlier diagnosis, through the detection of diagnostic and prognostic biomarkers provides the best hope of increasing the rate of curatively resectable carcinomas. Though many serum markers have been reported to be elevated in patients with PC, so far, most of these markers have not been implemented into clinical routine due to low sensitivity or specificity. In this study, we have identified genes that are significantly upregulated in PC, through a meta-analysis of large number of microarray datasets. We demonstrate that the biological functions ascribed to these genes are clearly associated with PC and metastasis, and that that these genes exhibit a strong link to pathways involved with inflammation and the immune response. This investigation has yielded new targets for cancer genes, and potential biomarkers for pancreatic cancer. The candidate list of cancer genes includes protein kinase genes, new members of gene families currently associated with PC, as well as genes not previously linked to PC. In this study, we are also able to move towards developing a signature for hypomethylated genes, which could be useful for early detection of PC. We also show that the significantly upregulated 800+ genes in our analysis can serve as an enriched pool for tissue and serum protein biomarkers in pancreatic cancer.

  19. Hierarchical information representation and efficient classification of gene expression microarray data

    OpenAIRE

    Bosio, Mattia

    2014-01-01

    In the field of computational biology, microarryas are used to measure the activity of thousands of genes at once and create a global picture of cellular function. Microarrays allow scientists to analyze expression of many genes in a single experiment quickly and eficiently. Even if microarrays are a consolidated research technology nowadays and the trends in high-throughput data analysis are shifting towards new technologies like Next Generation Sequencing (NGS), an optimum method for sample...

  20. Combining SSH and cDNA microarrays for rapid identification of differentially expressed genes.

    Science.gov (United States)

    Yang, G P; Ross, D T; Kuang, W W; Brown, P O; Weigel, R J

    1999-03-15

    Comparing patterns of gene expression in cell lines and tissues has important applications in a variety of biological systems. In this study we have examined whether the emerging technology of cDNA microarrays will allow a high throughput analysis of expression of cDNA clones generated by suppression subtractive hybridization (SSH). A set of cDNA clones including 332 SSH inserts amplified by PCR was arrayed using robotic printing. The cDNA arrays were hybridized with fluorescent labeled probes prepared from RNA from ER-positive (MCF7 and T47D) and ER-negative (MDA-MB-231 and HBL-100) breast cancer cell lines. Ten clones were identified that were over-expressed by at least a factor of five in the ER-positive cell lines. Northern blot analysis confirmed over-expression of these 10 cDNAs. Sequence analysis identified four of these clones as cytokeratin 19, GATA-3, CD24 and glutathione-S-transferase mu-3. Of the remaining six cDNA clones, four clones matched EST sequences from two different genes and two clones were novel sequences. Flow cytometry and immunofluorescence confirmed that CD24 protein was over-expressed in the ER-positive cell lines. We conclude that SSH and microarray technology can be successfully applied to identify differentially expressed genes. This approach allowed the identification of differentially expressed genes without the need to obtain previously cloned cDNAs.

  1. Microarray Analysis of Bisphenol A-induced Changes in Gene Expression in Human Oral Epithelial Cells

    Institute of Scientific and Technical Information of China (English)

    Keisuke SEKI; Ryosuke KOSHI; Naoyuki SUGANO; Shigeyuki MASUTANI; Naoto YOSHINUMA; CUI SHI

    2007-01-01

    Bisphenol A (BPA) is a common ingredient in dental materials. However, its potential adverse effects on the oral cavity are unknown. The purpose of this study is to identify the genes responding to BPA in a human oral epithelial cell line using DNA microarray. Of the 10,368 genes examined, changes in mRNA levels were detected in seven genes: five were up-regulated and two were down-regulated. The expression levels of the calcium channel, voltage-dependent, L-type, alpha lC subunit (CACNA1C), cell death activator CIDE-3 (CIDE-3), haptoglobin-related protein (HPR), importin 4 (IPO4), and POU domain, class 2 and spermatogenesis-associated, serine-rich 2 (SPATS2) and HSPC049 protein (HSPC049) were significantly down-regulated. The detailed knowledge of the changes in gene expression obtained using microarray technology will provide a basis for further elucidating the molecular mechanisms of the toxic effects of BPA in the oral cavity.

  2. Microarray analysis of bisphenol A-induced changes in gene expression in human oral epithelial cells.

    Science.gov (United States)

    Seki, Keisuke; Koshi, Ryosuke; Sugano, Naoyuki; Masutani, Shigeyuki; Yoshinuma, Naoto; Ito, Koichi

    2007-11-01

    Bisphenol A (BPA) is a common ingredient in dental materials. However, its potential adverse effects on the oral cavity are unknown. The purpose of this study is to identify the genes responding to BPA in a human oral epithelial cell line using DNA microarray. Of the 10,368 genes examined, changes in mRNA levels were detected in seven genes: five were up-regulated and two were down-regulated. The expression levels of the calcium channel, voltage-dependent, L-type, alpha 1C subunit (CACNA1C), cell death activator CIDE-3 (CIDE-3), haptoglobin-related protein (HPR), importin 4 (IPO4), and POU domain, class 2 and transcription factor 3 (POU2F3) were significantly up-regulated in the cells exposed to 100 mM BPA. The spermatogenesis-associated, serine-rich 2 (SPATS2) and HSPC049 protein (HSPC049) were significantly down-regulated. The detailed knowledge of the changes in gene expression obtained using microarray technology will provide a basis for further elucidating the molecular mechanisms of the toxic effects of BPA in the oral cavity.

  3. Microarray analysis identifies a common set of cellular genes modulated by different HCV replicon clones

    Directory of Open Access Journals (Sweden)

    Gerosolimo Germano

    2008-06-01

    Full Text Available Abstract Background Hepatitis C virus (HCV RNA synthesis and protein expression affect cell homeostasis by modulation of gene expression. The impact of HCV replication on global cell transcription has not been fully evaluated. Thus, we analysed the expression profiles of different clones of human hepatoma-derived Huh-7 cells carrying a self-replicating HCV RNA which express all viral proteins (HCV replicon system. Results First, we compared the expression profile of HCV replicon clone 21-5 with both the Huh-7 parental cells and the 21-5 cured (21-5c cells. In these latter, the HCV RNA has been eliminated by IFN-α treatment. To confirm data, we also analyzed microarray results from both the 21-5 and two other HCV replicon clones, 22-6 and 21-7, compared to the Huh-7 cells. The study was carried out by using the Applied Biosystems (AB Human Genome Survey Microarray v1.0 which provides 31,700 probes that correspond to 27,868 human genes. Microarray analysis revealed a specific transcriptional program induced by HCV in replicon cells respect to both IFN-α-cured and Huh-7 cells. From the original datasets of differentially expressed genes, we selected by Venn diagrams a final list of 38 genes modulated by HCV in all clones. Most of the 38 genes have never been described before and showed high fold-change associated with significant p-value, strongly supporting data reliability. Classification of the 38 genes by Panther System identified functional categories that were significantly enriched in this gene set, such as histones and ribosomal proteins as well as extracellular matrix and intracellular protein traffic. The dataset also included new genes involved in lipid metabolism, extracellular matrix and cytoskeletal network, which may be critical for HCV replication and pathogenesis. Conclusion Our data provide a comprehensive analysis of alterations in gene expression induced by HCV replication and reveal modulation of new genes potentially useful

  4. A Network Partition Algorithm for Mining Gene Functional Modules of Colon Cancer from DNA Microarray Data

    Institute of Scientific and Technical Information of China (English)

    Xiao-Gang Ruan; Jin-Lian Wang; Jian-Geng Li

    2006-01-01

    Computational analysis is essential for transforming the masses of microarray data into a mechanistic understanding of cancer. Here we present a method for finding gene functional modules of cancer from microarray data and have applied it to colon cancer. First, a colon cancer gene network and a normal colon tissue gene network were constructed using correlations between the genes. Then the modules that tended to have a homogeneous functional composition were identified by splitting up the network. Analysis of both networks revealed that they are scale-free.Comparison of the gene functional modules for colon cancer and normal tissues showed that the modules' functions changed with their structures.

  5. 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.

  6. Improved detection of differentially expressed genes in microarray experiments through multiple scanning and image integration

    Science.gov (United States)

    Romualdi, Chiara; Trevisan, Silvia; Celegato, Barbara; Costa, Germano; Lanfranchi, Gerolamo

    2003-01-01

    The variability of results in microarray technology is in part due to the fact that independent scans of a single hybridised microarray give spot images that are not quite the same. To solve this problem and turn it to our advantage, we introduced the approach of multiple scanning and of image integration of microarrays. To this end, we have developed specific software that creates a virtual image that statistically summarises a series of consecutive scans of a microarray. We provide evidence that the use of multiple imaging (i) enhances the detection of differentially expressed genes; (ii) increases the image homogeneity; and (iii) reveals false-positive results such as differentially expressed genes that are detected by a single scan but not confirmed by successive scanning replicates. The increase in the final number of differentially expressed genes detected in a microarray experiment with this approach is remarkable; 50% more for microarrays hybridised with targets labelled by reverse transcriptase, and 200% more for microarrays developed with the tyramide signal amplification (TSA) technique. The results have been confirmed by semi-quantitative RT–PCR tests. PMID:14627839

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

    OpenAIRE

    2006-01-01

    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 ra...

  8. Microarray Expression Profiles of 20.000 Genes across 23 Healthy Porcine Tissues

    DEFF Research Database (Denmark)

    Hornshøj, Henrik; Conley, Lene Nagstrup; Hedegaard, Jakob

    2007-01-01

    Gene expression microarrays have been intensively applied to screen for genes involved in specific biological processes of interest such as diseases or responses to environmental stimuli. For mammalian species, cataloging of the global gene expression profiles in large tissue collections under...

  9. Monitoring the Expression of Maize Genes in Developing Kernels under Drought Stress using Oligo-microarray

    Institute of Scientific and Technical Information of China (English)

    Meng Luo; Jia Liu; R. Dewey Lee; Brian T. Scully; Baozhu Guo

    2010-01-01

    Preharvest aflatoxin contamination of grain grown on the US southeastern Coast Plain is provoked and aggravated by abiotic stress. The primary abiotic stress is drought along with high temperatures. The objectives of the present study were to monitor gene expression in developing kernels in response to drought stress and to identify drought-responsive genes for possible use in germplasm assessment. The maize breeding line Tex6 was used, and gene expression profiles were analyzed in developing kernels under drought stress verses well-watered conditions at the stages of 25, 30, 35, 40, 45 d after pollination (DAP) using the 70 mer maize oligo-arrays. A total of 9 573 positive array spots were detected with unique gene IDs, and 7 988 were common in both stressed and well-watered samples. Expression patterns of some genes in several stress response-associated pathways, including abscisic acid, jasmonic acid and phenylalanine ammonia-lyase, were examined, and these specific genes were responsive to drought stress positively. Real-time quantitative polymerase chain reaction validated microarray expression data.The comparison between Tex6 and B73 revealed that there were significant differences in specific gene expression, patterns and levels. Several defense-related genes had been downregulated, even though some defense-related or drought responsive genes were upregulated at the later stages.

  10. Microarray based gene expression analysis of Sus Scrofa duodenum exposed to zearalenone: significance to human health.

    Science.gov (United States)

    Braicu, Cornelia; Cojocneanu-Petric, Roxana; Jurj, Ancuta; Gulei, Diana; Taranu, Ionelia; Gras, Alexandru Mihail; Marin, Daniela Eliza; Berindan-Neagoe, Ioana

    2016-08-17

    Zearalenone (ZEA) is a secondary metabolite produced by Fusarium species. ZEA was proved to exert a wide range of unwanted side effects, but its mechanism of action, particularly at duodenum levels, remains unclear. In our study based on the microarray technology we assessed the alteration of gene expression pattern Sus scrofa duodenum which has been previously exposed to ZEA. Gene expression data was validated by qRT-PCR and ELISA. The gene expression data were further extrapolated the results to their human orthologues and analyzed the data in the context of human health using IPA (Ingenuity Pathways Analysis). Using Agilent microarray technology, we found that gene expression pattern was significantly affected by ZEA exposure, considering a 2-fold expression difference as a cut-off level and a p-value < 0.05. In total, we found 1576 upregulated and 2446 downregulated transcripts. About 1084 genes (764 downregulated and 751 overexpressed) were extrapolated to their human orthologues. IPA analysis showed various altered key cellular and molecular pathways. As expected, we observed a significant alteration of immune response related genes, MAPK (mitogen activate protein kinases) pathways or Toll-Like Receptors (TLRs). What captured our attention was the modulation of pathways related to the activation of early carcinogenesis. Our data demonstrate that ZEA has a complex effect at duodenum level. ZEA is able to activate not only the immune response related genes, but also those relate to colorectal carcinogenesis. The effects can be more dramatic when connected with the exposure to other environmental toxic agents or co-occurrence with different microorganisms.

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

    Directory of Open Access Journals (Sweden)

    Ying Li

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

  12. Dorsal horn-enriched genes identified by DNA microarray, in situ hybridization and immunohistochemistry

    Directory of Open Access Journals (Sweden)

    Koblan Kenneth S

    2002-08-01

    Full Text Available Abstract Background Neurons in the dorsal spinal cord play important roles in nociception and pain. These neurons receive input from peripheral sensory neurons and then transmit the signals to the brain, as well as receive and integrate descending control signals from the brain. Many molecules important for pain transmission have been demonstrated to be localized to the dorsal horn of the spinal cord. Further understanding of the molecular interactions and signaling pathways in the dorsal horn neurons will require a better knowledge of the molecular neuroanatomy in the dorsal spinal cord. Results A large scale screening was conducted for genes with enriched expression in the dorsal spinal cord using DNA microarray and quantitative real-time PCR. In addition to genes known to be specifically expressed in the dorsal spinal cord, other neuropeptides, receptors, ion channels, and signaling molecules were also found enriched in the dorsal spinal cord. In situ hybridization and immunohistochemistry revealed the cellular expression of a subset of these genes. The regulation of a subset of the genes was also studied in the spinal nerve ligation (SNL neuropathic pain model. In general, we found that the genes that are enriched in the dorsal spinal cord were not among those found to be up-regulated in the spinal nerve ligation model of neuropathic pain. This study also provides a level of validation of the use of DNA microarrays in conjunction with our novel analysis algorithm (SAFER for the identification of differences in gene expression. Conclusion This study identified molecules that are enriched in the dorsal horn of the spinal cord and provided a molecular neuroanatomy in the spinal cord, which will aid in the understanding of the molecular mechanisms important in nociception and pain.

  13. Biological data warehousing system for identifying transcriptional regulatory sites from gene expressions of microarray data.

    Science.gov (United States)

    Tsou, Ann-Ping; Sun, Yi-Ming; Liu, Chia-Lin; Huang, Hsien-Da; Horng, Jorng-Tzong; Tsai, Meng-Feng; Liu, Baw-Juine

    2006-07-01

    Identification of transcriptional regulatory sites plays an important role in the investigation of gene regulation. For this propose, we designed and implemented a data warehouse to integrate multiple heterogeneous biological data sources with data types such as text-file, XML, image, MySQL database model, and Oracle database model. The utility of the biological data warehouse in predicting transcriptional regulatory sites of coregulated genes was explored using a synexpression group derived from a microarray study. Both of the binding sites of known transcription factors and predicted over-represented (OR) oligonucleotides were demonstrated for the gene group. The potential biological roles of both known nucleotides and one OR nucleotide were demonstrated using bioassays. Therefore, the results from the wet-lab experiments reinforce the power and utility of the data warehouse as an approach to the genome-wide search for important transcription regulatory elements that are the key to many complex biological systems.

  14. A computer-based microarray experiment design-system for gene-regulation pathway discovery.

    Science.gov (United States)

    Yoo, Changwon; Cooper, Gregory F

    2003-01-01

    This paper reports the methods and evaluation of a computer-based system that recommends microarray experimental design for biologists - causal discovery in Gene Expression data using Expected Value of Experimentation (GEEVE). The GEEVE system uses causal Bayesian networks and generates a decision tree for recommendations. To evaluate the GEEVE system, we first built an expression simulation model based on a gene regulation model assessed by an expert biologist. Using the simulation model, we conducted a controlled study that involved 10 biologists, some of whom used GEEVE and some of whom did not. The results show that biologists who used GEEVE reached correct causal assessments about gene regulation more often than did those biologists who did not use GEEVE.

  15. Meta-Analysis of Multiple Sclerosis Microarray Data Reveals Dysregulation in RNA Splicing Regulatory Genes.

    Science.gov (United States)

    Paraboschi, Elvezia Maria; Cardamone, Giulia; Rimoldi, Valeria; Gemmati, Donato; Spreafico, Marta; Duga, Stefano; Soldà, Giulia; Asselta, Rosanna

    2015-09-30

    Abnormalities in RNA metabolism and alternative splicing (AS) are emerging as important players in complex disease phenotypes. In particular, accumulating evidence suggests the existence of pathogenic links between multiple sclerosis (MS) and altered AS, including functional studies showing that an imbalance in alternatively-spliced isoforms may contribute to disease etiology. Here, we tested whether the altered expression of AS-related genes represents a MS-specific signature. A comprehensive comparative analysis of gene expression profiles of publicly-available microarray datasets (190 MS cases, 182 controls), followed by gene-ontology enrichment analysis, highlighted a significant enrichment for differentially-expressed genes involved in RNA metabolism/AS. In detail, a total of 17 genes were found to be differentially expressed in MS in multiple datasets, with CELF1 being dysregulated in five out of seven studies. We confirmed CELF1 downregulation in MS (p=0.0015) by real-time RT-PCRs on RNA extracted from blood cells of 30 cases and 30 controls. As a proof of concept, we experimentally verified the unbalance in alternatively-spliced isoforms in MS of the NFAT5 gene, a putative CELF1 target. In conclusion, for the first time we provide evidence of a consistent dysregulation of splicing-related genes in MS and we discuss its possible implications in modulating specific AS events in MS susceptibility genes.

  16. Analysis of Gene Expression Profile in Lung Adenosquamous Carcinoma Using cDNA Microarray

    Institute of Scientific and Technical Information of China (English)

    YANG Fei; YANG Jiong; JIANG Man; YE Bo; ZHANG Yu-xia; CHEN Hong-lei; XIA Dong; LIU Ming-qiu

    2004-01-01

    Gene expression profile of the lung adenosquamous carcinoma was characterized by using cDNA microarray chip containing 4 096 human genes. Among target genes, 508 differentially expressed genes were identified in adenosquamous carcinoma of the lung, 232 genes were overexpressed and 276 genes were underexpressed. Among them, 92 genes are cell signals transduction genes, 34 genes are proto-oncogenes and tumor suppressor genes or cell cycle related genes or cell apoptosis related genes, 29 genes are cell skeleton genes, 28 genes are DNA synthesis, repair and recombination genes, 12 genes are DNA binding and transcription genes. These genes may be associated with the occurence and development of adenosquamous carinome of the lung.

  17. Jetset: selecting the optimal microarray probe set to represent a gene

    DEFF Research Database (Denmark)

    Li, Qiyuan; Birkbak, Nicolai Juul; Gyorffy, Balazs

    2011-01-01

    Background: Interpretation of gene expression microarrays requires a mapping from probe set to gene. On many Affymetrix gene expression microarrays, a given gene may be detected by multiple probe sets, which may deliver inconsistent or even contradictory measurements. Therefore, obtaining...... an unambiguous expression estimate of a pre-specified gene can be a nontrivial but essential task. Results: We developed scoring methods to assess each probe set for specificity, splice isoform coverage, and robustness against transcript degradation. We used these scores to select a single representative probe...... set for each gene, thus creating a simple one-to-one mapping between gene and probe set. To test this method, we evaluated concordance between protein measurements and gene expression values, and between sets of genes whose expression is known to be correlated. For both test cases, we identified genes...

  18. Comparison of Gene Expression in Peri-implant Soft Tissue and Oral Mucosal Tissue by Microarray Analysis.

    Science.gov (United States)

    Makabe, Yasushi; Sasaki, Hodaka; Mori, Gentaro; Sekine, Hideshi; Yoshinari, Masao; Yajima, Yasutomo

    2015-01-01

    Implant placement entails disruption of the epithelial continuity, which can lead to various complications. Therefore, the area of mucosal penetration is of particular interest clinically. The goal of the present study was to compare gene expression in peri-implant soft tissue (PIST) with that in oral mucosal tissue (OMT) using microarray analysis, and to investigate which genes were specifically expressed in PIST. The bilateral upper first molars were extracted from 4-week-old rats and titanium alloy implants placed only in the left-side extraction sockets. Four weeks after surgery, samples were harvested from the left-side PIST and right-side OMT and total RNA samples isolated. Microarray analysis was used to compare gene expression in PIST and OMT, which was then confirmed using quantitative real-time polymerase chain reaction. Immunohistochemical staining was also performed to confirm protein level expression. The number of genes expressed with more than a twofold change in PIST compared with OMT was 1,102, of which 750 genes were upregulated and 352 genes were downregulated. The messenger RNA (mRNA) expression of three selected genes-Ceacam1, Ifitm1, and MUC4-were more significantly expressed in PIST than in OMT(P microarray analysis showed that, because of implant placement, 750 genes were upregulated in PIST compared with OMT. CEACAM1, IFITM1, and MUC4 were specifically upregulated in PIST.

  19. From single gene to integrative molecular concept MAPS: pitfalls and potentials of microarray technology.

    Science.gov (United States)

    Chiorino, G; Mello Grand, M; Scatolini, M; Ostano, P

    2008-01-01

    Microarray experiments have a large variety of applications and several important achievements have been obtained by means of this technology, especially within the field of whole genome expression profiling, which undoubtedly is the most diffused world-wide. Nevertheless, care must be taken in unconditionally applying such high-throughput techniques and in extracting/interpreting their results. Both the validity and the reproducibility of microarray-based clinical research have recently been challenged. Pitfalls and potentials of the microarray technology for gene expression profiling are critically reviewed in this paper.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2001-07-01

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

  1. Improving the statistical detection of regulated genes from microarray data using intensity-based variance estimation

    Directory of Open Access Journals (Sweden)

    Natarajan Sripriya

    2004-02-01

    Full Text Available Abstract Background Gene microarray technology provides the ability to study the regulation of thousands of genes simultaneously, but its potential is limited without an estimate of the statistical significance of the observed changes in gene expression. Due to the large number of genes being tested and the comparatively small number of array replicates (e.g., N = 3, standard statistical methods such as the Student's t-test fail to produce reliable results. Two other statistical approaches commonly used to improve significance estimates are a penalized t-test and a Z-test using intensity-dependent variance estimates. Results The performance of these approaches is compared using a dataset of 23 replicates, and a new implementation of the Z-test is introduced that pools together variance estimates of genes with similar minimum intensity. Significance estimates based on 3 replicate arrays are calculated using each statistical technique, and their accuracy is evaluated by comparing them to a reliable estimate based on the remaining 20 replicates. The reproducibility of each test statistic is evaluated by applying it to multiple, independent sets of 3 replicate arrays. Two implementations of a Z-test using intensity-dependent variance produce more reproducible results than two implementations of a penalized t-test. Furthermore, the minimum intensity-based Z-statistic demonstrates higher accuracy and higher or equal precision than all other statistical techniques tested. Conclusion An intensity-based variance estimation technique provides one simple, effective approach that can improve p-value estimates for differentially regulated genes derived from replicated microarray datasets. Implementations of the Z-test algorithms are available at http://vessels.bwh.harvard.edu/software/papers/bmcg2004.

  2. Robust gene signatures from microarray data using genetic algorithms enriched with biological pathway keywords.

    Science.gov (United States)

    Luque-Baena, R M; Urda, D; Gonzalo Claros, M; Franco, L; Jerez, J M

    2014-06-01

    Genetic algorithms are widely used in the estimation of expression profiles from microarrays data. However, these techniques are unable to produce stable and robust solutions suitable to use in clinical and biomedical studies. This paper presents a novel two-stage evolutionary strategy for gene feature selection combining the genetic algorithm with biological information extracted from the KEGG database. A comparative study is carried out over public data from three different types of cancer (leukemia, lung cancer and prostate cancer). Even though the analyses only use features having KEGG information, the results demonstrate that this two-stage evolutionary strategy increased the consistency, robustness and accuracy of a blind discrimination among relapsed and healthy individuals. Therefore, this approach could facilitate the definition of gene signatures for the clinical prognosis and diagnostic of cancer diseases in a near future. Additionally, it could also be used for biological knowledge discovery about the studied disease.

  3. Detection of gene expression in an individual cell type within a cell mixture using microarray analysis.

    Directory of Open Access Journals (Sweden)

    Penelope A Bryant

    Full Text Available BACKGROUND: A central issue in the design of microarray-based analysis of global gene expression is the choice between using cells of single type and a mixture of cells. This study quantified the proportion of lipopolysaccharide (LPS induced differentially expressed monocyte genes that could be measured in peripheral blood mononuclear cells (PBMC, and determined the extent to which gene expression in the non-monocyte cell fraction diluted or obscured fold changes that could be detected in the cell mixture. METHODOLOGY/PRINCIPAL FINDINGS: Human PBMC were stimulated with LPS, and monocytes were then isolated by positive (Mono+ or negative (Mono- selection. The non-monocyte cell fraction (MonoD remaining after positive selection of monocytes was used to determine the effect of non-monocyte cells on overall expression. RNA from LPS-stimulated PBMC, Mono+, Mono- and MonoD samples was co-hybridised with unstimulated RNA for each cell type on oligonucleotide microarrays. There was a positive correlation in gene expression between PBMC and both Mono+ (0.77 and Mono- (0.61-0.67 samples. Analysis of individual genes that were differentially expressed in Mono+ and Mono- samples showed that the ability to detect expression of some genes was similar when analysing PBMC, but for others, differential expression was either not detected or changed in the opposite direction. As a result of the dilutional or obscuring effect of gene expression in non-monocyte cells, overall about half of the statistically significant LPS-induced changes in gene expression in monocytes were not detected in PBMC. However, 97% of genes with a four fold or greater change in expression in monocytes after LPS stimulation, and almost all (96-100% of the top 100 most differentially expressed monocyte genes were detected in PBMC. CONCLUSIONS/SIGNIFICANCE: The effect of non-responding cells in a mixture dilutes or obscures the detection of subtle changes in gene expression in an individual

  4. Development and application of the active surveillance of pathogens microarray to monitor bacterial gene flux

    Directory of Open Access Journals (Sweden)

    Hinds Jason

    2008-10-01

    Full Text Available Abstract Background Human and animal health is constantly under threat by emerging pathogens that have recently acquired genetic determinants that enhance their survival, transmissibility and virulence. We describe the construction and development of an Active Surveillance of Pathogens (ASP oligonucleotide microarray, designed to 'actively survey' the genome of a given bacterial pathogen for virulence-associated genes. Results The microarray consists of 4958 reporters from 151 bacterial species and include genes for the identification of individual bacterial species as well as mobile genetic elements (transposons, plasmid and phage, virulence genes and antibiotic resistance genes. The ASP microarray was validated with nineteen bacterial pathogens species, including Francisella tularensis, Clostridium difficile, Staphylococcus aureus, Enterococcus faecium and Stenotrophomonas maltophilia. The ASP microarray identified these bacteria, and provided information on potential antibiotic resistance (eg sufamethoxazole resistance and sulfonamide resistance and virulence determinants including genes likely to be acquired by horizontal gene transfer (e.g. an alpha-haemolysin. Conclusion The ASP microarray has potential in the clinic as a diagnostic tool, as a research tool for both known and emerging pathogens, and as an early warning system for pathogenic bacteria that have been recently modified either naturally or deliberately.

  5. Differentially expressed genes identified by cross-species microarray in the blind cavefish Astyanax

    OpenAIRE

    2009-01-01

    Changes in gene expression were examined by microarray analysis during development of the eyed surface dwelling (surface fish) and blind cave-dwelling (cavefish) forms of the teleost Astyanax mexicanus De Filippi, 1853. The cross-species microarray used surface and cavefish RNA hybridized to a DNA chip prepared from a closely related species, the zebrafish Danio rerio Hamilton, 1822. We identified a total of 67 differentially expressed probe sets at three days post-fertilization: six upregula...

  6. Reexploring the Possible Roles of Some Genes Associated with Nasopharyngeal Carcinoma Using Microarray-based Detection

    Institute of Scientific and Technical Information of China (English)

    Wei-Yi FANG; Xin LI; Yan-Qing DING; Kai-Tai YAO; Teng-Fei LIU; Wei-Bing XIE; Xu-Yu YANG; Shuang WANG; Cai-Ping REN; Xin DENG; Qiu-Zhen LIU; Zhong-Xi HUANG

    2005-01-01

    In gene expression profiling, nasopharyngeal carcinoma (NPC) 5-8F cells differ from 6-10B cells in terms of their high tumorigenicity and metastatic ability. Differentially expressed genes from the two cell types were analyzed by combining with MILANO (the automatic custom annotation of microarray results which is based on all the available published work in PubMed). The results showed that five genes, including CTSD, P63, CSE1L, BPAG1 and EGR1, have been studied or mentioned in published work on NPC. Subsequently, we revaluated the roles of these genes in the pathogenesis of NPC by combining the data of gene chips from NPCs versus NPs and pooled cells from 5-8F, 6-10B and CNE2 versus NPs. The results suggested that the roles of BPAG1 and EGR1 are possibly different from those reported in previous NPC studies. These five genes are likely to be involved in the proliferation, apoptosis, invasion and metastasis of NPC. A reexploration of the genes will further define their roles in the pathogenesis of NPC.

  7. Microarray analyses of SREBP-1a and SREBP-1c target genes identify new regulatory pathways in muscle.

    OpenAIRE

    Rome, Sophie; Lecomte, Virginie; Meugnier, Emmanuelle; Rieusset, Jennifer; Debard, Cyrille; Euthine, Vanessa; Vidal, Hubert; Lefai, Etienne

    2008-01-01

    International audience; In this study we have identified the target genes of sterol regulatory element binding protein (SREBP)-1a and SREBP-1c in primary cultures of human skeletal muscle cells, using adenoviral vectors expressing the mature nuclear form of human SREBP-1a or SREBP-1c combined with oligonucleotide microarrays. Overexpression of SREBP-1a led to significant changes in the expression of 1,315 genes (655 upregulated and 660 downregulated), whereas overexpression of SREBP-1c modifi...

  8. GTI: a novel algorithm for identifying outlier gene expression profiles from integrated microarray datasets.

    Directory of Open Access Journals (Sweden)

    John Patrick Mpindi

    Full Text Available BACKGROUND: Meta-analysis of gene expression microarray datasets presents significant challenges for statistical analysis. We developed and validated a new bioinformatic method for the identification of genes upregulated in subsets of samples of a given tumour type ('outlier genes', a hallmark of potential oncogenes. METHODOLOGY: A new statistical method (the gene tissue index, GTI was developed by modifying and adapting algorithms originally developed for statistical problems in economics. We compared the potential of the GTI to detect outlier genes in meta-datasets with four previously defined statistical methods, COPA, the OS statistic, the t-test and ORT, using simulated data. We demonstrated that the GTI performed equally well to existing methods in a single study simulation. Next, we evaluated the performance of the GTI in the analysis of combined Affymetrix gene expression data from several published studies covering 392 normal samples of tissue from the central nervous system, 74 astrocytomas, and 353 glioblastomas. According to the results, the GTI was better able than most of the previous methods to identify known oncogenic outlier genes. In addition, the GTI identified 29 novel outlier genes in glioblastomas, including TYMS and CDKN2A. The over-expression of these genes was validated in vivo by immunohistochemical staining data from clinical glioblastoma samples. Immunohistochemical data were available for 65% (19 of 29 of these genes, and 17 of these 19 genes (90% showed a typical outlier staining pattern. Furthermore, raltitrexed, a specific inhibitor of TYMS used in the therapy of tumour types other than glioblastoma, also effectively blocked cell proliferation in glioblastoma cell lines, thus highlighting this outlier gene candidate as a potential therapeutic target. CONCLUSIONS/SIGNIFICANCE: Taken together, these results support the GTI as a novel approach to identify potential oncogene outliers and drug targets. The algorithm is

  9. Development of a miniaturized DNA microarray for identification of 66 virulence genes of Legionella pneumophila

    Directory of Open Access Journals (Sweden)

    Mariusz Żak

    2011-12-01

    Full Text Available Introduction:For the last five years, Legionella sp. infections and legionnaire’s disease in Poland have been receiving a lot of attention, because of the new regulations concerning microbiological quality of drinking water. This was the inspiration to search for and develop a new assay to identify many virulence genes of Legionella pneumophila to better understand their distribution in environmental and clinical strains. The method might be an invaluable help in infection risk assessment and in epidemiological investigations.Material/Methods:The microarray is based on Array Tube technology. It contains 3 positive and 1 negative control. Target genes encode structural elements of T4SS, effector proteins and factors not related to T4SS. Probes were designed using OligoWiz software and data analyzed using IconoClust software. To isolate environmental and clinical strains, BAL samples and samples of hot water from different and independent hot water distribution systems of public utility buildings were collected.Results.We have developed a miniaturized DNA microarray for identification of 66 virulence genes of L. pneumophila. The assay is specific to L. pneumophila sg 1 with sensitivity sufficient to perform the assay using DNA isolated from a single L. pneumophila colony. Seven environmental strains were analyzed. Two exhibited a hybridization pattern distinct from the reference strain.Discussion:The method is time- and cost-effective. Initial studies have shown that genes encoding effector proteins may vary among environmental strains. Further studies might help to identify set of genes increasing the risk of clinical disease and to determine the pathogenic potential of environmental strains.

  10. Differential Gene Expression Analysis of Placentas with Increased Vascular Resistance and Pre-Eclampsia Using Whole-Genome Microarrays

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    M. Centlow

    2011-01-01

    Full Text Available Pre-eclampsia is a pregnancy complication characterized by hypertension and proteinuria. There are several factors associated with an increased risk of developing pre-eclampsia, one of which is increased uterine artery resistance, referred to as “notching”. However, some women do not progress into pre-eclampsia whereas others may have a higher risk of doing so. The placenta, central in pre-eclampsia pathology, may express genes associated with either protection or progression into pre-eclampsia. In order to search for genes associated with protection or progression, whole-genome profiling was performed. Placental tissue from 15 controls, 10 pre-eclamptic, 5 pre-eclampsia with notching, and 5 with notching only were analyzed using microarray and antibody microarrays to study some of the same gene product and functionally related ones. The microarray showed 148 genes to be significantly altered between the four groups. In the preeclamptic group compared to notch only, there was increased expression of genes related to chemotaxis and the NF-kappa B pathway and decreased expression of genes related to antigen processing and presentation, such as human leukocyte antigen B. Our results indicate that progression of pre-eclampsia from notching may involve the development of inflammation. Increased expression of antigen-presenting genes, as seen in the notch-only placenta, may prevent this inflammatory response and, thereby, protect the patient from developing pre-eclampsia.

  11. Microarray-based analysis for hepatocellular carcinoma: From gene expression profiling to new challenges

    Institute of Scientific and Technical Information of China (English)

    Yutaka Midorikawa; Masatoshi Makuuchi; Wei Tang; Hiroyuki Aburatani

    2007-01-01

    Accumulation of mutations and alterations in the expression of various genes result in carcinogenesis, and the development of microarray technology has enabled us to identify the comprehensive gene expression alterations in oncogenesis. Many studies have applied this technology for hepatocellular carcinoma (HCC), and identified a number of candidate genes useful as biomarkers in cancer staging, prediction of recurrence and prognosis, and treatment selection. Some of these target molecules have been used to develop new serum diagnostic markers and therapeutic targets against HCC to benefit patients. Previously, we compared gene expression profiling data with classification based on clinicopathological features, such as hepatitis viral infection or liver cancer progression. The next era of gene expression analysis will require systematic integration of expression profiles with other types of biological information, such as genomic locus, gene function, and sequence information. We have reported integration between expression profiles and locus information, which is effective in detecting structural genomic abnormalities, such as chromosomal gains and losses, in which we showed that gene expression profiles are subject to chromosomal bias. Furthermore, array-based comparative genomic hybridization analysis and allelic dosage analysis using genotyping arrays for HCC were also reviewed, with comparison of conventional methods.

  12. DNA-microarrays identification of Streptococcus mutans genes associated with biofilm thickness

    Directory of Open Access Journals (Sweden)

    Feldman Mark

    2008-12-01

    Full Text Available Abstract Background A biofilm is a complex community of microorganisms that develop on surfaces in diverse environments. The thickness of the biofilm plays a crucial role in the physiology of the immobilized bacteria. The most cariogenic bacteria, mutans streptococci, are common inhabitants of a dental biofilm community. In this study, DNA-microarray analysis was used to identify differentially expressed genes associated with the thickness of S. mutans biofilms. Results Comparative transcriptome analyses indicated that expression of 29 genes was differentially altered in 400- vs. 100-microns depth and 39 genes in 200- vs. 100-microns biofilms. Only 10 S. mutans genes showed differential expression in both 400- vs. 100-microns and 200- vs. 100-microns biofilms. All of these genes were upregulated. As sucrose is a predominant factor in oral biofilm development, its influence was evaluated on selected genes expression in the various depths of biofilms. The presence of sucrose did not noticeably change the regulation of these genes in 400- vs. 100-microns and/or 200- vs. 100-microns biofilms tested by real-time RT-PCR. Furthermore, we analyzed the expression profile of selected biofilm thickness associated genes in the luxS- mutant strain. The expression of those genes was not radically changed in the mutant strain compared to wild-type bacteria in planktonic condition. Only slight downregulation was recorded in SMU.2146c, SMU.574, SMU.609, and SMU.987 genes expression in luxS- bacteria in biofilm vs. planktonic environments. Conclusion These findings reveal genes associated with the thickness of biofilms of S. mutans. Expression of these genes is apparently not regulated directly by luxS and is not necessarily influenced by the presence of sucrose in the growth media.

  13. Inflammatory Pathways in Parkinson's Disease; A BNE Microarray Study.

    Science.gov (United States)

    Durrenberger, Pascal F; Grünblatt, Edna; Fernando, Francesca S; Monoranu, Camelia Maria; Evans, Jordan; Riederer, Peter; Reynolds, Richard; Dexter, David T

    2012-01-01

    The aetiology of Parkinson's disease (PD) is yet to be fully understood but it is becoming more and more evident that neuronal cell death may be multifactorial in essence. The main focus of PD research is to better understand substantia nigra homeostasis disruption, particularly in relation to the wide-spread deposition of the aberrant protein α-synuclein. Microarray technology contributed towards PD research with several studies to date and one gene, ALDH1A1 (Aldehyde dehydrogenase 1 family, member A1), consistently reappeared across studies including the present study, highlighting dopamine (DA) metabolism dysfunction resulting in oxidative stress and most probably leading to neuronal cell death. Neuronal cell death leads to increased inflammation through the activation of astrocytes and microglia. Using our dataset, we aimed to isolate some of these pathways so to offer potential novel neuroprotective therapeutic avenues. To that effect our study has focused on the upregulation of P2X7 (purinergic receptor P2X, ligand-gated ion channel, 7) receptor pathway (microglial activation) and on the NOS3 (nitric oxide synthase 3) pathway (angiogenesis). In summary, although the exact initiator of striatal DA neuronal cell death remains to be determined, based on our analysis, this event does not remain without consequence. Extracellular ATP and reactive astrocytes appear to be responsible for the activation of microglia which in turn release proinflammatory cytokines contributing further to the parkinsonian condition. In addition to tackling oxidative stress pathways we also suggest to reduce microglial and endothelial activation to support neuronal outgrowth.

  14. Evaluation of gene importance in microarray data based upon probability of selection

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    Fu Li M

    2005-03-01

    Full Text Available Abstract Background Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many important diseases can be traced down to the gene level, a long-standing research problem is to identify specific gene expression patterns linking to metabolic characteristics that contribute to disease development and progression. The microarray approach offers an expedited solution to this problem. However, it has posed a challenging issue to recognize disease-related genes expression patterns embedded in the microarray data. In selecting a small set of biologically significant genes for classifier design, the nature of high data dimensionality inherent in this problem creates substantial amount of uncertainty. Results Here we present a model for probability analysis of selected genes in order to determine their importance. Our contribution is that we show how to derive the P value of each selected gene in multiple gene selection trials based on different combinations of data samples and how to conduct a reliability analysis accordingly. The importance of a gene is indicated by its associated P value in that a smaller value implies higher information content from information theory. On the microarray data concerning the subtype classification of small round blue cell tumors, we demonstrate that the method is capable of finding the smallest set of genes (19 genes with optimal classification performance, compared with results reported in the literature. Conclusion In classifier design based on microarray data, the probability value derived from gene selection based on multiple combinations of data samples enables an effective mechanism for reducing the tendency of fitting local data particularities.

  15. Microarray-based analysis of differential gene expression between infective and noninfective larvae of Strongyloides stercoralis.

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    Roshan Ramanathan

    Full Text Available 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 value<0.01. Based on a functional analysis, L1 larvae have a larger number of genes putatively involved in transcription (p = 0.004, and L3i larvae have biased expression of putative heat shock proteins (such as hsp-90. Genes with products known to be immunoreactive in S. stercoralis-infected humans (such as SsIR and NIE had L3i biased expression. Abundantly expressed L3i contigs of interest included S. stercoralis orthologs of cytochrome oxidase ucr 2.1 and hsp-90, which may be potential chemotherapeutic targets. The S. stercoralis ortholog of fatty acid and retinol binding protein-1, successfully used in a vaccine against Ancylostoma ceylanicum, was identified among the 25 most highly expressed L3i genes. The sperm-containing glycoprotein domain, utilized in a vaccine against the nematode Cooperia punctata, was exclusively found in L3i biased genes and may be a valuable S. stercoralis target of interest. CONCLUSIONS: A new DNA microarray tool for the examination of S. stercoralis biology has been developed and provides new and valuable insights

  16. Bayesian meta-analysis models for microarray data: a comparative study

    Directory of Open Access Journals (Sweden)

    Song Joon J

    2007-03-01

    Full Text Available Abstract Background With the growing abundance of microarray data, statistical methods are increasingly needed to integrate results across studies. Two common approaches for meta-analysis of microarrays include either combining gene expression measures across studies or combining summaries such as p-values, probabilities or ranks. Here, we compare two Bayesian meta-analysis models that are analogous to these methods. Results Two Bayesian meta-analysis models for microarray data have recently been introduced. The first model combines standardized gene expression measures across studies into an overall mean, accounting for inter-study variability, while the second combines probabilities of differential expression without combining expression values. Both models produce the gene-specific posterior probability of differential expression, which is the basis for inference. Since the standardized expression integration model includes inter-study variability, it may improve accuracy of results versus the probability integration model. However, due to the small number of studies typical in microarray meta-analyses, the variability between studies is challenging to estimate. The probability integration model eliminates the need to model variability between studies, and thus its implementation is more straightforward. We found in simulations of two and five studies that combining probabilities outperformed combining standardized gene expression measures for three comparison values: the percent of true discovered genes in meta-analysis versus individual studies; the percent of true genes omitted in meta-analysis versus separate studies, and the number of true discovered genes for fixed levels of Bayesian false discovery. We identified similar results when pooling two independent studies of Bacillus subtilis. We assumed that each study was produced from the same microarray platform with only two conditions: a treatment and control, and that the data sets

  17. The microarray analysis for gene expression in haploids and diploids derived from twin-seedling rice

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    In this study, microarray technique was employed to analyze the gene expression at the RNA level between haploids and corresponding diploids derived from a rice twin-seedling line SARII-628. Differ- ent degrees of expression variations were observed in the plant after haploidization. The main results are as follows: (1) after haploidization, the ratio of the sensitive loci was 2.47% of the total loci designed on chip. Those loci were randomly distributed on the 12 pairs of rice chromosomes and the activated loci were more than the silenced ones. (2) Gene clusters on chromosome were observed for 33 se- quences. (3) GoPipe function classification for 575 sensitive loci revealed an involvement in the bio- logical process, cell component and molecular function. (4) RT-PCR generally validated the result from microarray with a coincidence rate of 83.78%. And for the randomly-selected activated or silenced loci in chip analysis, the coincidence rate was up to 91.86%.

  18. Differential expression of 114 oxidative stressrelated genes in peripheral blood mononuclear cells of acute cerebral infarction patients A gene microarray experiment

    Institute of Scientific and Technical Information of China (English)

    Jing Yang; Fei Zhong; Mingshan Ren; Jiangming Zhao

    2010-01-01

    Previous studies have focused on the analysis of single or several function-related genes in oxidative stress;however,little information is available regarding altered expression of oxidative stress-related genes in the process of ischemia-reperfusion injury from microarray experiments.The aim of the present study was to investigate the changes in cell oxidative stress-and toxicity-related gene expression utilizing microarray screening in patients with acute cerebral infarction during cerebral ischemia-reperfusion injury.Of the included 114 genes,expression was significantly upregulated in eight genes,including three heat shock protein-related genes,one oxidative and metabolic stress-related gene,one cell growth arrest/senescence related gene,two apoptosis signal-related genes,and one DNA damage and repair related gene.Expression was significantly downregulated in four genes,including one cell proliferation/cancer related gene,two oxidative and metabolic stress-related genes and one DNA damage and repair related gene.The results demonstrated that cerebral ischemia-reperfusion injury in patients with acute cerebral infarction was affected by many genes including oxidative stress-,heat shock-,DNA damage and repair-,and apoptosis signal-related genes.Therefore,it could be suggested that cerebral ischemia-reperfusion injury may be subjected to complex genetic regulation mechanisms.

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

    Directory of Open Access Journals (Sweden)

    Jun Yao

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

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

    Science.gov (United States)

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

    2012-01-01

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

  1. Co-expressed immune and metabolic genes in visceral and subcutaneous adipose tissue from severely obese individuals are associated with plasma HDL and glucose levels: a microarray study

    Directory of Open Access Journals (Sweden)

    Wolfs Marcel GM

    2010-08-01

    Full Text Available Abstract Background Excessive accumulation of body fat, in particular in the visceral fat depot, is a major risk factor to develop a variety of diseases such as type 2 diabetes. The mechanisms underlying the increased risk of obese individuals to develop co-morbid diseases are largely unclear. We aimed to identify genes expressed in subcutaneous adipose tissue (SAT and visceral adipose tissue (VAT that are related to blood parameters involved in obesity co-morbidity, such as plasma lipid and glucose levels, and to compare gene expression between the fat depots. Methods Whole-transcriptome SAT and VAT gene expression levels were determined in 75 individuals with a BMI >35 kg/m2. Modules of co-expressed genes likely to be functionally related were identified and correlated with BMI, plasma levels of glucose, insulin, HbA1c, triglycerides, non-esterified fatty acids, ALAT, ASAT, C-reactive protein, and LDL- and HDL cholesterol. Results Of the approximately 70 modules identified in SAT and VAT, three SAT modules were inversely associated with plasma HDL-cholesterol levels, and a fourth module was inversely associated with both plasma glucose and plasma triglyceride levels (p -5. These modules were markedly enriched in immune and metabolic genes. In VAT, one module was associated with both BMI and insulin, and another with plasma glucose (p -5. This module was also enriched in inflammatory genes and showed a marked overlap in gene content with the SAT modules related to HDL. Several genes differentially expressed in SAT and VAT were identified. Conclusions In obese subjects, groups of co-expressed genes were identified that correlated with lipid and glucose metabolism parameters; they were enriched with immune genes. A number of genes were identified of which the expression in SAT correlated with plasma HDL cholesterol, while their expression in VAT correlated with plasma glucose. This underlines both the singular importance of these genes for lipid

  2. Comparative study of discretization methods of microarray data for inferring transcriptional regulatory networks

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    Ji Wei

    2010-10-01

    Full Text Available Abstract Background Microarray data discretization is a basic preprocess for many algorithms of gene regulatory network inference. Some common discretization methods in informatics are used to discretize microarray data. Selection of the discretization method is often arbitrary and no systematic comparison of different discretization has been conducted, in the context of gene regulatory network inference from time series gene expression data. Results In this study, we propose a new discretization method "bikmeans", and compare its performance with four other widely-used discretization methods using different datasets, modeling algorithms and number of intervals. Sensitivities, specificities and total accuracies were calculated and statistical analysis was carried out. Bikmeans method always gave high total accuracies. Conclusions Our results indicate that proper discretization methods can consistently improve gene regulatory network inference independent of network modeling algorithms and datasets. Our new method, bikmeans, resulted in significant better total accuracies than other methods.

  3. Development and validation of a resistance and virulence gene microarray targeting Escherichia coli and Salmonella enterica

    Science.gov (United States)

    Davis, Margaret A.; Lim, Ji Youn; Soyer, Yesim; Harbottle, Heather; Chang, Yung-Fu; New, Daniel; Orfe, Lisa H.; Besser, Thomas E.; Call, Douglas R.

    2010-01-01

    A microarray was developed to simultaneously screen Escherichia coli and Salmonella enterica for multiple genetic traits. The final array included 203 60-mer oligonucleotide probes, including 117 for resistance genes, 16 for virulence genes, 25 for replicon markers, and 45 other markers. Validity of the array was tested by assessing interlaboratory agreement among four collaborating groups using a blinded study design. Internal validation indicated that the assay was reliable (area under the receiver-operator characteristic curve=0.97). Inter-laboratory agreement, however, was poor when estimated using the intraclass correlation coefficient, which ranged from 0.27 (95% confidence interval 0.24, 0.29) to 0.29 (0.23, 0.34). These findings suggest that extensive testing and procedure standardization will be needed before bacterial genotyping arrays can be readily shared between laboratories. PMID:20362014

  4. Microarray-based gene expression profiling of peripheral blood mononuclear cells in dairy cows with experimental hypocalcemia and milk fever

    National Research Council Canada - National Science Library

    Sasaki, K; Yamagishi, N; Kizaki, K; Sasaki, K; Devkota, B; Hashizume, K

    2014-01-01

    .... Therefore, peripheral blood mononuclear cells from dairy cows with experimentally induced hypocalcemia or spontaneous milk fever were subjected to oligo-microarray analysis to identify specific biomarker genes...

  5. Identification of differentially expressed genes associated with semigamy in Pima cotton (Gossypium barbadense L. through comparative microarray analysis

    Directory of Open Access Journals (Sweden)

    Stewart J McD

    2011-03-01

    Full Text Available Abstract Background Semigamy in cotton is a type of facultative apomixis controlled by an incompletely dominant autosomal gene (Se. During semigamy, the sperm and egg cells undergo cellular fusion, but the sperm and egg nucleus fail to fuse in the embryo sac, giving rise to diploid, haploid, or chimeric embryos composed of sectors of paternal and maternal origin. In this study we sought to identify differentially expressed genes related to the semigamy genotype by implementing a comparative microarray analysis of anthers and ovules between a non-semigametic Pima S-1 cotton and its doubled haploid natural isogenic mutant semigametic 57-4. Selected differentially expressed genes identified by the microarray results were then confirmed using quantitative reverse transcription PCR (qRT-PCR. Results The comparative analysis between isogenic 57-4 and Pima S-1 identified 284 genes in anthers and 1,864 genes in ovules as being differentially expressed in the semigametic genotype 57-4. Based on gene functions, 127 differentially expressed genes were common to both semigametic anthers and ovules, with 115 being consistently differentially expressed in both tissues. Nine of those genes were selected for qRT-PCR analysis, seven of which were confirmed. Furthermore, several well characterized metabolic pathways including glycolysis/gluconeogenesis, carbon fixation in photosynthetic organisms, sesquiterpenoid biosynthesis, and the biosynthesis of and response to plant hormones were shown to be affected by differentially expressed genes in the semigametic tissues. Conclusion As the first report using microarray analysis, several important metabolic pathways affected by differentially expressed genes in the semigametic cotton genotype have been identified and described in detail. While these genes are unlikely to be the semigamy gene itself, the effects associated with expression changes in those genes do mimic phenotypic traits observed in semigametic plants

  6. Analysis of gene expression profile induced by EMP-1 in esophageal cancer cells using cDNA Microarray

    Institute of Scientific and Technical Information of China (English)

    Hai-Tao Wang; Jian-Ping Kong; Fang Ding; Xiu-Qin Wang; Ming-Rong Wang; Lian-Xin Liu; Min Wu; Zhi-Hua Liu

    2003-01-01

    AIM: To obtain human esophageal cancer cell EC9706 stably expressed epithelial membrane protein-1 (EMP-1) with integrated eukaryotic plasmid harboring the open reading frame (ORF) of human EMP-1, and then to study the mechanism by which EMP-1 exerts its diverse cellular action on cell proliferation and altered gene profile by exploring the effect of EMP-1.METHODS: The authors first constructed pcDNA3.1/mychis expression vector harboring the ORF of EMP-1 and then transfected it into human esophageal carcinoma cell line EC9706. The positive clones were analyzed by Western blot and RT-PCR. Moreover, the cell growth curve was observed and the cell cycle was checked by FACS technique. Using cDNA microarray technology, the authors compared the gene expression pattern in positive clones with control. To confirm the gene expression profile, semi-quantitative RT-PCR was carried out for 4 of the randomly picked differentially expressed genes. For those differentially expressed genes,classification was performed according to their function and cellular component.RESULTS: Human EMP-1 gene can be stably expressed in ECg706 cell line transfected with human EMP-1. The authors found the cell growth decreased, among which S phase was arrested and G1 phase was prolonged in the transfected positive clones. By cDNA microarray analysis, 35 genes showed an over 2.0 fold change in expression level after transfection, with 28 genes being consistently up-regulated and 7 genes being down-regulated. Among the classified genes, almost half of the induced genes (13 out of 28 genes) were related to cell signaling, cell communication and particularly to adhesion.CONCLUSION: Overexpression of human EMP-1 gene can inhibit the proliferation of EC9706 cell with S phase arrested and G1 phase prolonged. The cDNA microarray analysis suggested that EMP-1 may be one of regulators involved incell signaling, cell communication and adhesion regulators.

  7. A microarray analysis of sex- and gonad-biased gene expression in the zebrafish: Evidence for masculinization of the transcriptome

    Directory of Open Access Journals (Sweden)

    Mo Qianxing

    2009-12-01

    Full Text Available Abstract Background In many taxa, males and females are very distinct phenotypically, and these differences often reflect divergent selective pressures acting on the sexes. Phenotypic sexual dimorphism almost certainly reflects differing patterns of gene expression between the sexes, and microarray studies have documented widespread sexually dimorphic gene expression. Although the evolutionary significance of sexual dimorphism in gene expression remains unresolved, these studies have led to the formulation of a hypothesis that male-driven evolution has resulted in the masculinization of animal transcriptomes. Here we use a microarray assessment of sex- and gonad-biased gene expression to test this hypothesis in zebrafish. Results By using zebrafish Affymetrix microarrays to compare gene expression patterns in male and female somatic and gonadal tissues, we identified a large number of genes (5899 demonstrating differences in transcript abundance between male and female Danio rerio. Under conservative statistical significance criteria, all sex-biases in gene expression were due to differences between testes and ovaries. Male-enriched genes were more abundant than female-enriched genes, and expression bias for male-enriched genes was greater in magnitude than that for female-enriched genes. We also identified a large number of genes demonstrating elevated transcript abundance in testes and ovaries relative to male body and female body, respectively. Conclusion Overall our results support the hypothesis that male-biased evolutionary pressures have resulted in male-biased patterns of gene expression. Interestingly, our results seem to be at odds with a handful of other microarray-based studies of sex-specific gene expression patterns in zebrafish. However, ours was the only study designed to address this specific hypothesis, and major methodological differences among studies could explain the discrepancies. Regardless, all of these studies agree

  8. GeneAnalytics: An Integrative Gene Set Analysis Tool for Next Generation Sequencing, RNAseq and Microarray Data.

    Science.gov (United States)

    Ben-Ari Fuchs, Shani; Lieder, Iris; Stelzer, Gil; Mazor, Yaron; Buzhor, Ella; Kaplan, Sergey; Bogoch, Yoel; Plaschkes, Inbar; Shitrit, Alina; Rappaport, Noa; Kohn, Asher; Edgar, Ron; Shenhav, Liraz; Safran, Marilyn; Lancet, Doron; Guan-Golan, Yaron; Warshawsky, David; Shtrichman, Ronit

    2016-03-01

    Postgenomics data are produced in large volumes by life sciences and clinical applications of novel omics diagnostics and therapeutics for precision medicine. To move from "data-to-knowledge-to-innovation," a crucial missing step in the current era is, however, our limited understanding of biological and clinical contexts associated with data. Prominent among the emerging remedies to this challenge are the gene set enrichment tools. This study reports on GeneAnalytics™ ( geneanalytics.genecards.org ), a comprehensive and easy-to-apply gene set analysis tool for rapid contextualization of expression patterns and functional signatures embedded in the postgenomics Big Data domains, such as Next Generation Sequencing (NGS), RNAseq, and microarray experiments. GeneAnalytics' differentiating features include in-depth evidence-based scoring algorithms, an intuitive user interface and proprietary unified data. GeneAnalytics employs the LifeMap Science's GeneCards suite, including the GeneCards®--the human gene database; the MalaCards-the human diseases database; and the PathCards--the biological pathways database. Expression-based analysis in GeneAnalytics relies on the LifeMap Discovery®--the embryonic development and stem cells database, which includes manually curated expression data for normal and diseased tissues, enabling advanced matching algorithm for gene-tissue association. This assists in evaluating differentiation protocols and discovering biomarkers for tissues and cells. Results are directly linked to gene, disease, or cell "cards" in the GeneCards suite. Future developments aim to enhance the GeneAnalytics algorithm as well as visualizations, employing varied graphical display items. Such attributes make GeneAnalytics a broadly applicable postgenomics data analyses and interpretation tool for translation of data to knowledge-based innovation in various Big Data fields such as precision medicine, ecogenomics, nutrigenomics, pharmacogenomics, vaccinomics

  9. Microarray analyses of glucocorticoid and vitamin D3 target genes in differentiating cultured human podocytes.

    Directory of Open Access Journals (Sweden)

    Xiwen Cheng

    Full Text Available Glomerular podocytes are highly differentiated epithelial cells that are key components of the kidney filtration units. Podocyte damage or loss is the hallmark of nephritic diseases characterized by severe proteinuria. Recent studies implicate that hormones including glucocorticoids (ligand for glucocorticoid receptor and vitamin D3 (ligand for vitamin D receptor protect or promote repair of podocytes from injury. In order to elucidate the mechanisms underlying hormone-mediated podocyte-protecting activity from injury, we carried out microarray gene expression studies to identify the target genes and corresponding pathways in response to these hormones during podocyte differentiation. We used immortalized human cultured podocytes (HPCs as a model system and carried out in vitro differentiation assays followed by dexamethasone (Dex or vitamin D3 (VD3 treatment. Upon the induction of differentiation, multiple functional categories including cell cycle, organelle dynamics, mitochondrion, apoptosis and cytoskeleton organization were among the most significantly affected. Interestingly, while Dex and VD3 are capable of protecting podocytes from injury, they only share limited target genes and affected pathways. Compared to VD3 treatment, Dex had a broader and greater impact on gene expression profiles. In-depth analyses of Dex altered genes indicate that Dex crosstalks with a broad spectrum of signaling pathways, of which inflammatory responses, cell migration, angiogenesis, NF-κB and TGFβ pathways are predominantly altered. Together, our study provides new information and identifies several new avenues for future investigation of hormone signaling in podocytes.

  10. Identification of novel tissue-specific genes by analysis of microarray databases: a human and mouse model.

    Science.gov (United States)

    Song, Yan; Ahn, Jinsoo; Suh, Yeunsu; Davis, Michael E; Lee, Kichoon

    2013-01-01

    Understanding the tissue-specific pattern of gene expression is critical in elucidating the molecular mechanisms of tissue development, gene function, and transcriptional regulations of biological processes. Although tissue-specific gene expression information is available in several databases, follow-up strategies to integrate and use these data are limited. The objective of the current study was to identify and evaluate novel tissue-specific genes in human and mouse tissues by performing comparative microarray database analysis and semi-quantitative PCR analysis. We developed a powerful approach to predict tissue-specific genes by analyzing existing microarray data from the NCBI's Gene Expression Omnibus (GEO) public repository. We investigated and confirmed tissue-specific gene expression in the human and mouse kidney, liver, lung, heart, muscle, and adipose tissue. Applying our novel comparative microarray approach, we confirmed 10 kidney, 11 liver, 11 lung, 11 heart, 8 muscle, and 8 adipose specific genes. The accuracy of this approach was further verified by employing semi-quantitative PCR reaction and by searching for gene function information in existing publications. Three novel tissue-specific genes were discovered by this approach including AMDHD1 (amidohydrolase domain containing 1) in the liver, PRUNE2 (prune homolog 2) in the heart, and ACVR1C (activin A receptor, type IC) in adipose tissue. We further confirmed the tissue-specific expression of these 3 novel genes by real-time PCR. Among them, ACVR1C is adipose tissue-specific and adipocyte-specific in adipose tissue, and can be used as an adipocyte developmental marker. From GEO profiles, we predicted the processes in which AMDHD1 and PRUNE2 may participate. Our approach provides a novel way to identify new sets of tissue-specific genes and to predict functions in which they may be involved.

  11. Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data

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    Cheung Leo

    2007-02-01

    Bayesian inferences. Simulation studies showed that, even without any knowledge of the underlying generative model, the KIGP performed very close to the theoretical Bayesian bound not only in the case with a linear Bayesian classifier but also in the case with a very non-linear Bayesian classifier. This sheds light on its broader usability to microarray data analysis problems, especially to those that linear methods work awkwardly. The KIGP was also applied to four published microarray datasets, and the results showed that the KIGP performed better than or at least as well as any of the referred state-of-the-art methods did in all of these cases. Conclusion Mathematically built on the kernel-induced feature space concept under a Bayesian framework, the KIGP method presented in this paper provides a unified machine learning approach to explore both the linear and the possibly non-linear underlying relationship between the target features of a given binary disease classification problem and the related explanatory gene expression data. More importantly, it incorporates the model parameter tuning into the framework. The model selection problem is addressed in the form of selecting a proper kernel type. The KIGP method also gives Bayesian probabilistic predictions for disease classification. These properties and features are beneficial to most real-world applications. The algorithm is naturally robust in numerical computation. The simulation studies and the published data studies demonstrated that the proposed KIGP performs satisfactorily and consistently.

  12. GeneAnalytics: An Integrative Gene Set Analysis Tool for Next Generation Sequencing, RNAseq and Microarray Data

    Science.gov (United States)

    Ben-Ari Fuchs, Shani; Lieder, Iris; Mazor, Yaron; Buzhor, Ella; Kaplan, Sergey; Bogoch, Yoel; Plaschkes, Inbar; Shitrit, Alina; Rappaport, Noa; Kohn, Asher; Edgar, Ron; Shenhav, Liraz; Safran, Marilyn; Lancet, Doron; Guan-Golan, Yaron; Warshawsky, David; Shtrichman, Ronit

    2016-01-01

    Abstract Postgenomics data are produced in large volumes by life sciences and clinical applications of novel omics diagnostics and therapeutics for precision medicine. To move from “data-to-knowledge-to-innovation,” a crucial missing step in the current era is, however, our limited understanding of biological and clinical contexts associated with data. Prominent among the emerging remedies to this challenge are the gene set enrichment tools. This study reports on GeneAnalytics™ (geneanalytics.genecards.org), a comprehensive and easy-to-apply gene set analysis tool for rapid contextualization of expression patterns and functional signatures embedded in the postgenomics Big Data domains, such as Next Generation Sequencing (NGS), RNAseq, and microarray experiments. GeneAnalytics' differentiating features include in-depth evidence-based scoring algorithms, an intuitive user interface and proprietary unified data. GeneAnalytics employs the LifeMap Science's GeneCards suite, including the GeneCards®—the human gene database; the MalaCards—the human diseases database; and the PathCards—the biological pathways database. Expression-based analysis in GeneAnalytics relies on the LifeMap Discovery®—the embryonic development and stem cells database, which includes manually curated expression data for normal and diseased tissues, enabling advanced matching algorithm for gene–tissue association. This assists in evaluating differentiation protocols and discovering biomarkers for tissues and cells. Results are directly linked to gene, disease, or cell “cards” in the GeneCards suite. Future developments aim to enhance the GeneAnalytics algorithm as well as visualizations, employing varied graphical display items. Such attributes make GeneAnalytics a broadly applicable postgenomics data analyses and interpretation tool for translation of data to knowledge-based innovation in various Big Data fields such as precision medicine, ecogenomics, nutrigenomics

  13. A process for analysis of microarray comparative genomics hybridisation studies for bacterial genomes

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    Woodward Martin J

    2008-01-01

    Full Text Available Abstract Background Microarray based comparative genomic hybridisation (CGH experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity. Results The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data. Conclusion After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.

  14. CDNA microarray analysis of gene expression patterns in blood mononuclear cells of SLA-DRB1-defined Yorkshire pigs.

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    Nino-Soto, M I; Jozani, R J; Bridle, B; Mallard, B A

    2008-01-01

    Three lines of commercialYorkshire pigs with defined SLA-DRB1 alleles were developed at the University of Guelph for xenotransplantation and immune response studies. Two of the SLA-DRB1 alleles have been previously reported (SLA-DRB1*0502 and *0701), whereas the third one is a new allele. The influence of defined SLA-DRB1 alleles on transcriptional patterns of immune-related genes in blood mononuclear cells (BMCs) of pigs was explored using cDNA microarray. Microarray analysis showed significant differential expression of inflammatory genes in association with the various SLA-DRB1 alleles. A better understanding of the association between SLA genotypes and gene activity can increase the knowledge of the function of these molecules, as well as define new strategies to control animal health and optimize animal production.

  15. Protective Effect of Gwakhyangjeonggisan Herbal Acupuncture Solution in Glioblastoma Cells: Microarray Analysis of Gene Expression

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    Hong-Seok Lee

    2005-12-01

    Full Text Available Objectives : Neurological disorders have been one of main therapeutic targets of acupuncture. The present study investigated the protective effects of Gwakhyangjeonggisan herbal acupuncture solution (GHAS. Methods : We performed 3-(4,5-dimethylthiazol-2-yl-2,5-diphenyltetrazolium bromide (MTT assay in glioblastoma cells, and did microarray analysis with cells exposed to reactive oxigen species (ROS of hydrogen peroxide by 8.0 k Human cDNA, with cut-off level of 2-fold changes in gene expression. Results : MTT assay showed protective effect of GHAS on the glioblastoma cells exposed to hydrogen peroxide. When glioblastoma cells were exposed to hydrogen peroxide, 24 genes were downregulated. When the cells were pretreated with GHAS before exposure to hydrogen peroxide, 46 genes were downregulated. Many of the genes downregulated by hydrogen peroxide stimulation were decreased in the amount of downregulation or reversed to upregulation. Conclusions : The gene expression changes observed in the present study are supposed to be related to the protective molecular mechanism of GHAS in the glioblastoma cells exposed to ROS stress.

  16. Multiclass classification of microarray data samples with a reduced number of genes

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    Ornella Leonardo

    2011-02-01

    Full Text Available Abstract Background Multiclass classification of microarray data samples with a reduced number of genes is a rich and challenging problem in Bioinformatics research. The problem gets harder as the number of classes is increased. In addition, the performance of most classifiers is tightly linked to the effectiveness of mandatory gene selection methods. Critical to gene selection is the availability of estimates about the maximum number of genes that can be handled by any classification algorithm. Lack of such estimates may lead to either computationally demanding explorations of a search space with thousands of dimensions or classification models based on gene sets of unrestricted size. In the former case, unbiased but possibly overfitted classification models may arise. In the latter case, biased classification models unable to support statistically significant findings may be obtained. Results A novel bound on the maximum number of genes that can be handled by binary classifiers in binary mediated multiclass classification algorithms of microarray data samples is presented. The bound suggests that high-dimensional binary output domains might favor the existence of accurate and sparse binary mediated multiclass classifiers for microarray data samples. Conclusions A comprehensive experimental work shows that the bound is indeed useful to induce accurate and sparse multiclass classifiers for microarray data samples.

  17. A novel parametric approach to mine gene regulatory relationship from microarray datasets

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    Zhu Yunping

    2010-12-01

    Full Text Available Abstract Background Microarray has been widely used to measure the gene expression level on the genome scale in the current decade. Many algorithms have been developed to reconstruct gene regulatory networks based on microarray data. Unfortunately, most of these models and algorithms focus on global properties of the expression of genes in regulatory networks. And few of them are able to offer intuitive parameters. We wonder whether some simple but basic characteristics of microarray datasets can be found to identify the potential gene regulatory relationship. Results Based on expression correlation, expression level variation and vectors derived from microarray expression levels, we first introduced several novel parameters to measure the characters of regulating gene pairs. Subsequently, we used the naïve Bayesian network to integrate these features as well as the functional co-annotation between transcription factors and their target genes. Then, based on the character of time-delay from the expression profile, we were able to predict the existence and direction of the regulatory relationship respectively. Conclusions Several novel parameters have been proposed and integrated to identify the regulatory relationship. This new model is proved to be of higher efficacy than that of individual features. It is believed that our parametric approach can serve as a fast approach for regulatory relationship mining.

  18. A robust measure of correlation between two genes on a microarray

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    Hicks Leanne

    2007-06-01

    Full Text Available Abstract Background The underlying goal of microarray experiments is to identify gene expression patterns across different experimental conditions. Genes that are contained in a particular pathway or that respond similarly to experimental conditions could be co-expressed and show similar patterns of expression on a microarray. Using any of a variety of clustering methods or gene network analyses we can partition genes of interest into groups, clusters, or modules based on measures of similarity. Typically, Pearson correlation is used to measure distance (or similarity before implementing a clustering algorithm. Pearson correlation is quite susceptible to outliers, however, an unfortunate characteristic when dealing with microarray data (well known to be typically quite noisy. Results We propose a resistant similarity metric based on Tukey's biweight estimate of multivariate scale and location. The resistant metric is simply the correlation obtained from a resistant covariance matrix of scale. We give results which demonstrate that our correlation metric is much more resistant than the Pearson correlation while being more efficient than other nonparametric measures of correlation (e.g., Spearman correlation. Additionally, our method gives a systematic gene flagging procedure which is useful when dealing with large amounts of noisy data. Conclusion When dealing with microarray data, which are known to be quite noisy, robust methods should be used. Specifically, robust distances, including the biweight correlation, should be used in clustering and gene network analysis.

  19. NMD Microarray Analysis for Rapid Genome-Wide Screen of Mutated Genes in Cancer

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    Maija Wolf

    2005-01-01

    Full Text Available Gene mutations play a critical role in cancer development and progression, and their identification offers possibilities for accurate diagnostics and therapeutic targeting. Finding genes undergoing mutations is challenging and slow, even in the post-genomic era. A new approach was recently developed by Noensie and Dietz to prioritize and focus the search, making use of nonsense-mediated mRNA decay (NMD inhibition and microarray analysis (NMD microarrays in the identification of transcripts containing nonsense mutations. We combined NMD microarrays with array-based CGH (comparative genomic hybridization in order to identify inactivation of tumor suppressor genes in cancer. Such a “mutatomics” screening of prostate cancer cell lines led to the identification of inactivating mutations in the EPHB2 gene. Up to 8% of metastatic uncultured prostate cancers also showed mutations of this gene whose loss of function may confer loss of tissue architecture. NMD microarray analysis could turn out to be a powerful research method to identify novel mutated genes in cancer cell lines, providing targets that could then be further investigated for their clinical relevance and therapeutic potential.

  20. Identification of potential target genes associated with the pathogenesis of osteoarthritis using microarray based analysis.

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    Li, Meng; Zhi, Liqiang; Zhang, Zhi; Bian, Weiguo; Qiu, Yusheng

    2017-09-01

    The aim of the present study was to investigate the molecular circuitry of osteoarthritis (OA) and identify more potential target genes for OA treatment. Microarray data of GSE32317 was downloaded from the National Center for Biotechnology Information Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified in samples of synovial membrane from patients with early stage of knee OA (OA_Early) and late stage of knee OA (OA_End) that were compared with healthy specimens. Bioinformatics analysis was applied to analyze the significant functions and pathways that were enriched by the common DEGs identified in OA_Early and OA_End samples. Furthermore, a protein‑protein interaction (PPI) network was constructed and significant modules were extracted. Transcription factors (TFs) that could regulate genes in the significant modules were identified. A total of 1,207 and 1,575 DEGs were identified in OA_Early and OA_End samples compared with healthy samples, respectively. A total of 740 genes were upregulated and 308 genes were downregulated across the OA_Early and OA_End samples. These common DEGs were enriched in different gene ontology terms and pathways, such as immune response. Angiotensinogen (AGT) and C‑X‑C motif chemokine ligand 12 (CXCL12) were identified to be hub proteins in the PPI network or in the selected module 1. In addition, the DEG lysine demethylase 2B (KDM2B) was identified as a TF that can regulate genes in the significant modules 2 and 3. In conclusion, the present study has identified AGT, CXCL12 and KDM2B as potentially essential genes associated with the pathogenesis of knee OA.

  1. Identification of differential gene expression for microarray data using recursive random forest

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Background The major difficulty in the research of DNA microarray data is the large number of genes compared with the relatively small number of samples as well as the complex data structure. Random forest has received much attention recently; its primary characteristic is that it can form a classification model from the data with high dimensionality. However, optimal results can not be obtained for gene selection since it is still affected by undifferentiated genes. We proposed recursive random forest analysis and applied it to gene selection. Methods Recursive random forest, which is an improvement of random forest, obtains optimal differentiated genes after step by step dropping of genes which, according to a certain algorithm, have no effects on classification. The method has the advantage of random forest and provides a gene importance scale as well. The value of the area under the curve (AUC) of the receiver operating characteristic (ROC) curve, which synthesizes the information of sensitivity and specificity, is adopted as the key standard for evaluating the performance of this method. The focus of the paper is to validate the effectiveness of gene selection using recursive random forest through the analysis of five microarray datasets; colon, prostate, leukemia, breast and skin data. Results Five microarray datasets were analyzed and better classification results have been attained using only a fewgenes after gene selection. The biological information of the selected genes from breast and skin data was confirmed according to the National Center for Biotechnology Information (NCBI). The results prove that the genes associated with diseases can be effectively retained by recursive random forest. Conclusions Recursive random forest can be effectively applied to microarray data analysis and gene selection. The retained genes in the optimal model provide important information for clinical diagnoses and research of the biological mechanism of diseases.

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

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    Latkowski, Tomasz; Osowski, Stanislaw

    2015-01-01

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

  3. cDNA Microarray Analysis Revealing Candidate Biomineralization Genes of the Pearl Oyster, Pinctada fucata martensii.

    Science.gov (United States)

    Shi, Yaohua; Zheng, Xing; Zhan, Xin; Wang, Aimin; Gu, Zhifeng

    2016-06-01

    Biomineralization is a common biological phenomenon resulting in strong tissue, such as bone, tooth, and shell. Pinctada fucata martensii is an ideal animal for the study of biomineralization. Here, microarray technique was used to identify biomineralization gene in mantle edge (ME), mantle center (MC), and both ME and MC (ME-MC) for this pearl oyster. Results revealed that 804, 306, and 1127 contigs expressed at least three times higher in ME, MC, and ME-MC as those in other tissues. Blast against non-redundant database showed that 130 contigs (16.17 %), 53 contigs (17.32 %), and 248 contigs (22.01 %) hit reference genes (E ≤ -10), among which 91 contigs, 48 contigs, and 168 contigs could be assigned to 32, 26, and 63 biomineralization genes in tissue of ME, MC, and ME-MC at a threshold of 3 times upregulated expression level. The ratios of biomineralization contigs to homologous contigs were similar at 3 times, 10 times, and 100 times of upregulated expression level in either ME, MC, or ME-MC. Moreover, the ratio of biomineralization contigs was highest in MC. Although mRNA distribution characters were similar to those in other studies for eight biomineralization genes of PFMG3, Pif, nacrein, MSI7, mantle gene 6, Pfty1, prismin, and the shematrin, most biomineralization genes presented different expression profiles from existing reports. These results provided massive fundamental information for further study of biomineralization gene function, and it may be helpful for revealing gene nets of biomineralization and the molecular mechanisms underlining formation of shell and pearl for the oyster.

  4. Integrating multiple genome annotation databases improves the interpretation of microarray gene expression data

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    Kennedy Breandan

    2010-01-01

    Full Text Available Abstract Background The Affymetrix GeneChip is a widely used gene expression profiling platform. Since the chips were originally designed, the genome databases and gene definitions have been considerably updated. Thus, more accurate interpretation of microarray data requires parallel updating of the specificity of GeneChip probes. We propose a new probe remapping protocol, using the zebrafish GeneChips as an example, by removing nonspecific probes, and grouping the probes into transcript level probe sets using an integrated zebrafish genome annotation. This genome annotation is based on combining transcript information from multiple databases. This new remapping protocol, especially the new genome annotation, is shown here to be an important factor in improving the interpretation of gene expression microarray data. Results Transcript data from the RefSeq, GenBank and Ensembl databases were downloaded from the UCSC genome browser, and integrated to generate a combined zebrafish genome annotation. Affymetrix probes were filtered and remapped according to the new annotation. The influence of transcript collection and gene definition methods was tested using two microarray data sets. Compared to remapping using a single database, this new remapping protocol results in up to 20% more probes being retained in the remapping, leading to approximately 1,000 more genes being detected. The differentially expressed gene lists are consequently increased by up to 30%. We are also able to detect up to three times more alternative splicing events. A small number of the bioinformatics predictions were confirmed using real-time PCR validation. Conclusions By combining gene definitions from multiple databases, it is possible to greatly increase the numbers of genes and splice variants that can be detected in microarray gene expression experiments.

  5. Linear fuzzy gene network models obtained from microarray data by exhaustive search

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    Quong Judy N

    2004-08-01

    Full Text Available Abstract Background Recent technological advances in high-throughput data collection allow for experimental study of increasingly complex systems on the scale of the whole cellular genome and proteome. Gene network models are needed to interpret the resulting large and complex data sets. Rationally designed perturbations (e.g., gene knock-outs can be used to iteratively refine hypothetical models, suggesting an approach for high-throughput biological system analysis. We introduce an approach to gene network modeling based on a scalable linear variant of fuzzy logic: a framework with greater resolution than Boolean logic models, but which, while still semi-quantitative, does not require the precise parameter measurement needed for chemical kinetics-based modeling. Results We demonstrated our approach with exhaustive search for fuzzy gene interaction models that best fit transcription measurements by microarray of twelve selected genes regulating the yeast cell cycle. Applying an efficient, universally applicable data normalization and fuzzification scheme, the search converged to a small number of models that individually predict experimental data within an error tolerance. Because only gene transcription levels are used to develop the models, they include both direct and indirect regulation of genes. Conclusion Biological relationships in the best-fitting fuzzy gene network models successfully recover direct and indirect interactions predicted from previous knowledge to result in transcriptional correlation. Fuzzy models fit on one yeast cell cycle data set robustly predict another experimental data set for the same system. Linear fuzzy gene networks and exhaustive rule search are the first steps towards a framework for an integrated modeling and experiment approach to high-throughput "reverse engineering" of complex biological systems.

  6. The Local Maximum Clustering Method and Its Application in Microarray Gene Expression Data Analysis

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    Chen Yidong

    2004-01-01

    Full Text Available An unsupervised data clustering method, called the local maximum clustering (LMC method, is proposed for identifying clusters in experiment data sets based on research interest. A magnitude property is defined according to research purposes, and data sets are clustered around each local maximum of the magnitude property. By properly defining a magnitude property, this method can overcome many difficulties in microarray data clustering such as reduced projection in similarities, noises, and arbitrary gene distribution. To critically evaluate the performance of this clustering method in comparison with other methods, we designed three model data sets with known cluster distributions and applied the LMC method as well as the hierarchic clustering method, the -mean clustering method, and the self-organized map method to these model data sets. The results show that the LMC method produces the most accurate clustering results. As an example of application, we applied the method to cluster the leukemia samples reported in the microarray study of Golub et al. (1999.

  7. Array2BIO: from microarray expression data to functional annotation of co-regulated genes

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    Rasley Amy

    2006-06-01

    Full Text Available Abstract Background There are several isolated tools for partial analysis of microarray expression data. To provide an integrative, easy-to-use and automated toolkit for the analysis of Affymetrix microarray expression data we have developed Array2BIO, an application that couples several analytical methods into a single web based utility. Results Array2BIO converts raw intensities into probe expression values, automatically maps those to genes, and subsequently identifies groups of co-expressed genes using two complementary approaches: (1 comparative analysis of signal versus control and (2 clustering analysis of gene expression across different conditions. The identified genes are assigned to functional categories based on Gene Ontology classification and KEGG protein interaction pathways. Array2BIO reliably handles low-expressor genes and provides a set of statistical methods for quantifying expression levels, including Benjamini-Hochberg and Bonferroni multiple testing corrections. An automated interface with the ECR Browser provides evolutionary conservation analysis for the identified gene loci while the interconnection with Crème allows prediction of gene regulatory elements that underlie observed expression patterns. Conclusion We have developed Array2BIO – a web based tool for rapid comprehensive analysis of Affymetrix microarray expression data, which also allows users to link expression data to Dcode.org comparative genomics tools and integrates a system for translating co-expression data into mechanisms of gene co-regulation. Array2BIO is publicly available at http://array2bio.dcode.org.

  8. Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB.

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    Chatziioannou, Aristotelis; Moulos, Panagiotis; Kolisis, Fragiskos N

    2009-10-27

    The microarray data analysis realm is ever growing through the development of various tools, open source and commercial. However there is absence of predefined rational algorithmic analysis workflows or batch standardized processing to incorporate all steps, from raw data import up to the derivation of significantly differentially expressed gene lists. This absence obfuscates the analytical procedure and obstructs the massive comparative processing of genomic microarray datasets. Moreover, the solutions provided, heavily depend on the programming skills of the user, whereas in the case of GUI embedded solutions, they do not provide direct support of various raw image analysis formats or a versatile and simultaneously flexible combination of signal processing methods. We describe here Gene ARMADA (Automated Robust MicroArray Data Analysis), a MATLAB implemented platform with a Graphical User Interface. This suite integrates all steps of microarray data analysis including automated data import, noise correction and filtering, normalization, statistical selection of differentially expressed genes, clustering, classification and annotation. In its current version, Gene ARMADA fully supports 2 coloured cDNA and Affymetrix oligonucleotide arrays, plus custom arrays for which experimental details are given in tabular form (Excel spreadsheet, comma separated values, tab-delimited text formats). It also supports the analysis of already processed results through its versatile import editor. Besides being fully automated, Gene ARMADA incorporates numerous functionalities of the Statistics and Bioinformatics Toolboxes of MATLAB. In addition, it provides numerous visualization and exploration tools plus customizable export data formats for seamless integration by other analysis tools or MATLAB, for further processing. Gene ARMADA requires MATLAB 7.4 (R2007a) or higher and is also distributed as a stand-alone application with MATLAB Component Runtime. Gene ARMADA provides a

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

    Science.gov (United States)

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

    2015-09-09

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

  10. Gene selection for microarray cancer classification using a new evolutionary method employing artificial intelligence concepts.

    Science.gov (United States)

    Dashtban, M; Balafar, Mohammadali

    2017-03-01

    Gene selection is a demanding task for microarray data analysis. The diverse complexity of different cancers makes this issue still challenging. In this study, a novel evolutionary method based on genetic algorithms and artificial intelligence is proposed to identify predictive genes for cancer classification. A filter method was first applied to reduce the dimensionality of feature space followed by employing an integer-coded genetic algorithm with dynamic-length genotype, intelligent parameter settings, and modified operators. The algorithmic behaviors including convergence trends, mutation and crossover rate changes, and running time were studied, conceptually discussed, and shown to be coherent with literature findings. Two well-known filter methods, Laplacian and Fisher score, were examined considering similarities, the quality of selected genes, and their influences on the evolutionary approach. Several statistical tests concerning choice of classifier, choice of dataset, and choice of filter method were performed, and they revealed some significant differences between the performance of different classifiers and filter methods over datasets. The proposed method was benchmarked upon five popular high-dimensional cancer datasets; for each, top explored genes were reported. Comparing the experimental results with several state-of-the-art methods revealed that the proposed method outperforms previous methods in DLBCL dataset. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. MGFM: a novel tool for detection of tissue and cell specific marker genes from microarray gene expression data.

    Science.gov (United States)

    El Amrani, Khadija; Stachelscheid, Harald; Lekschas, Fritz; Kurtz, Andreas; Andrade-Navarro, Miguel A

    2015-08-28

    Identification of marker genes associated with a specific tissue/cell type is a fundamental challenge in genetic and cell research. Marker genes are of great importance for determining cell identity, and for understanding tissue specific gene function and the molecular mechanisms underlying complex diseases. We have developed a new bioinformatics tool called MGFM (Marker Gene Finder in Microarray data) to predict marker genes from microarray gene expression data. Marker genes are identified through the grouping of samples of the same type with similar marker gene expression levels. We verified our approach using two microarray data sets from the NCBI's Gene Expression Omnibus public repository encompassing samples for similar sets of five human tissues (brain, heart, kidney, liver, and lung). Comparison with another tool for tissue-specific gene identification and validation with literature-derived established tissue markers established functionality, accuracy and simplicity of our tool. Furthermore, top ranked marker genes were experimentally validated by reverse transcriptase-polymerase chain reaction (RT-PCR). The sets of predicted marker genes associated with the five selected tissues comprised well-known genes of particular importance in these tissues. The tool is freely available from the Bioconductor web site, and it is also provided as an online application integrated into the CellFinder platform ( http://cellfinder.org/analysis/marker ). MGFM is a useful tool to predict tissue/cell type marker genes using microarray gene expression data. The implementation of the tool as an R-package as well as an application within CellFinder facilitates its use.

  12. Microarray analysis of gene expression in olive flounder liver infected with viral haemorrhagic septicaemia virus (VHSV).

    Science.gov (United States)

    Cho, Hyun Kook; Kim, Julan; Moon, Ji Young; Nam, Bo-Hye; Kim, Young-Ok; Kim, Woo-Jin; Park, Jung Youn; An, Cheul Min; Cheong, Jaehun; Kong, Hee Jeong

    2016-02-01

    The most fatal viral pathogen in olive flounder Paralichthys olivaceus, is viral hemorrhagic septicemia virus, which afflicts over 48 species of freshwater and marine fish. Here, we performed gene expression profiling on transcripts isolated from VHSV-infected olive flounder livers using a 13 K cDNA microarray chip. A total of 1832 and 1647 genes were upregulated and down-regulated over two-fold, respectively, after infection. A variety of immune-related genes showing significant changes in gene expression were identified in upregulated genes through gene ontology annotation. These genes were grouped into categories such as antibacterial peptide, antigen-recognition and adhesion molecules, apoptosis, cytokine-related pathway, immune system, stress response, and transcription factor and regulatory factors. To verify the cDNA microarray data, we performed quantitative real-time PCR, and the results were similar to the microarray data. In conclusion, these results may be useful for the identification of specific genes or for the diagnosis of VHSV infection in flounder.

  13. Differentially expressed genes identified by cross-species microarray in the blind cavefish Astyanax.

    Science.gov (United States)

    Strickler, Allen G; Jeffery, William R

    2009-03-01

    Changes in gene expression were examined by microarray analysis during development of the eyed surface dwelling (surface fish) and blind cave-dwelling (cavefish) forms of the teleost Astyanax mexicanus De Filippi, 1853. The cross-species microarray used surface and cavefish RNA hybridized to a DNA chip prepared from a closely related species, the zebrafish Danio rerio Hamilton, 1822. We identified a total of 67 differentially expressed probe sets at three days post-fertilization: six upregulated and 61 downregulated in cavefish relative to surface fish. Many of these genes function either in eye development and/or maintenance, or in programmed cell death. The upregulated probe set showing the highest mean fold change was similar to the human ubiquitin specific protease 53 gene. The downregulated probe sets showing some of the highest fold changes corresponded to genes with roles in eye development, including those encoding gamma crystallins, the guanine nucleotide binding proteins Gnat1 and Gant2, a BarH-like homeodomain transcription factor, and rhodopsin. Downregulation of gamma-crystallin and rhodopsin was confirmed by in situ hybridization and immunostaining with specific antibodies. Additional downregulated genes encode molecules that inhibit or activate programmed cell death. The results suggest that cross-species microarray can be used for identifying differentially expressed genes in cavefish, that many of these genes might be involved in eye degeneration via apoptotic processes, and that more genes are downregulated than upregulated in cavefish, consistent with the predominance of morphological losses over gains during regressive evolution.

  14. Studying Genes

    Science.gov (United States)

    ... NIGMS NIGMS Home > Science Education > Studying Genes Studying Genes Tagline (Optional) Middle/Main Content Area Other Fact Sheets What are genes? Genes are segments of DNA that contain instructions ...

  15. GENE EXPRESSION IN THE TESTES OF NORMOSPERMIC VERSUS TERATOSPERMIC DOMESTIC CATS USING HUMAN CDNA MICROARRAY ANALYSES

    Science.gov (United States)

    GENE EXPRESSION IN THE TESTES OF NORMOSPERMIC VERSUS TERATOSPERMIC DOMESTIC CATS USING HUMAN cDNA MICROARRAY ANALYSESB.S. Pukazhenthi1, J. C. Rockett2, M. Ouyang3, D.J. Dix2, J.G. Howard1, P. Georgopoulos4, W.J. J. Welsh3 and D. E. Wildt11Department of Reproductiv...

  16. Gene microarray data analysis using parallel point-symmetry-based clustering.

    Science.gov (United States)

    Sarkar, Anasua; Maulik, Ujjwal

    2015-01-01

    Identification of co-expressed genes is the central goal in microarray gene expression analysis. Point-symmetry-based clustering is an important unsupervised learning technique for recognising symmetrical convex- or non-convex-shaped clusters. To enable fast clustering of large microarray data, we propose a distributed time-efficient scalable approach for point-symmetry-based K-Means algorithm. A natural basis for analysing gene expression data using symmetry-based algorithm is to group together genes with similar symmetrical expression patterns. This new parallel implementation also satisfies linear speedup in timing without sacrificing the quality of clustering solution on large microarray data sets. The parallel point-symmetry-based K-Means algorithm is compared with another new parallel symmetry-based K-Means and existing parallel K-Means over eight artificial and benchmark microarray data sets, to demonstrate its superiority, in both timing and validity. The statistical analysis is also performed to establish the significance of this message-passing-interface based point-symmetry K-Means implementation. We also analysed the biological relevance of clustering solutions.

  17. Gene expression analysis of strawberry achene and receptacle maturation using DNA microarrays

    NARCIS (Netherlands)

    Aharoni, A.; O'Connell, A.P.

    2002-01-01

    Large-scale, single pass sequencing and parallel gene expression analysis using DNA microarrays were employed for the comprehensive investigation of ripening in strawberry fruit. A total of 1701 cDNA clones (comprising 1100 strawberry ESTs and 601 unsequenced cDNAs) obtained from a strawberry (Fraga

  18. Microarray and KOG analysis of Acanthamoeba healyi genes up-regulated by mouse-brain passage.

    Science.gov (United States)

    Moon, Eun-Kyung; Xuan, Ying-Hua; Kong, Hyun-Hee

    2014-08-01

    Long-term cultivation in a laboratory could reduce the virulence of Acanthamoeba. To identify virulence factors of Acanthamoeba, the authors compared the transcription profiles of long-term cultivated Acanthamoeba healyi (OLD) and three times mouse-brain passaged A. healyi (MBP) using microarray analysis and eukaryotic orthologous group (KOG) assignments. Microarray analysis revealed that 601 genes were up-regulated by mouse-brain passage. The results of real-time PCR of 8 randomly selected genes up-regulated in the MBP strain confirmed microarray analysis findings. KOG assignments showed relatively higher percentages of the MBP strain up-regulated genes in T article (signal transduction mechanism), O article (posttranslational modification, protein turnover, chaperones), C article (energy production and conversion), and J article (translation, ribosomal structure and biogenesis). In particular, the MBP strain showed higher expressions of cysteine protease and metalloprotease. A comparison of KOG assignments by microarray analysis and previous EST (expressed sequence tags) analysis showed similar populations of up-regulated genes. These results provide important information regarding the identification of virulence factors of pathogenic Acanthamoeba.

  19. Troubleshooting methods for microarray gene expression analysis in the onset of diabetic kidney disease

    NARCIS (Netherlands)

    Mazagova, Magdalena; Henning, Robert H.; Duin, Marry; van Buiten, Azuwerus; Buikema, Hendrik; Deelman, Leo E.

    2013-01-01

    Introduction: Microarrays have become the standard technique for discovering new genes involved in the development of (kidney) disease. Diabetic nephropathy is a frequent complication of diabetes and is characterized by renal fibrosis. As the pathways leading to fibrosis are initiated early in diabe

  20. A Computer-Based Microarray Experiment Design-System for Gene-Regulation Pathway Discovery

    OpenAIRE

    2003-01-01

    This paper reports the methods and evaluation of a computer-based system that recommends microarray experimental design for biologists — causal discovery in Gene Expression data using Expected Value of Experimentation (GEEVE). The GEEVE system uses causal Bayesian networks and generates a decision tree for recommendations.

  1. GENE EXPRESSION IN THE TESTES OF NORMOSPERMIC VERSUS TERATOSPERMIC DOMESTIC CATS USING HUMAN CDNA MICROARRAY ANALYSES

    Science.gov (United States)

    GENE EXPRESSION IN THE TESTES OF NORMOSPERMIC VERSUS TERATOSPERMIC DOMESTIC CATS USING HUMAN cDNA MICROARRAY ANALYSESB.S. Pukazhenthi1, J. C. Rockett2, M. Ouyang3, D.J. Dix2, J.G. Howard1, P. Georgopoulos4, W.J. J. Welsh3 and D. E. Wildt11Department of Reproductiv...

  2. Discovering gene expression patterns in time course microarray experiments by ANOVA-SCA.

    NARCIS (Netherlands)

    M.J. Nueda; A. Conessa; J.A. Westerhuis; H.C.J. Hoefsloot; A.K. Smilde; M. Talon; A. Ferrer

    2007-01-01

    In this work, we develop the application of the Analysis of variance-simultaneous component analysis (ANOVA-SCA) Smilde et al. Bioinformatics, (2005) to the analysis of multiple series time course microarray data as an example of multifactorial gene expression profiling experiments. We denoted this

  3. Identification of novel endogenous antisense transcripts by DNA microarray analysis targeting complementary strand of annotated genes

    Directory of Open Access Journals (Sweden)

    Kohama Chihiro

    2009-08-01

    Full Text Available Abstract Background Recent transcriptomic analyses in mammals have uncovered the widespread occurrence of endogenous antisense transcripts, termed natural antisense transcripts (NATs. NATs are transcribed from the opposite strand of the gene locus and are thought to control sense gene expression, but the mechanism of such regulation is as yet unknown. Although several thousand potential sense-antisense pairs have been identified in mammals, examples of functionally characterized NATs remain limited. To identify NAT candidates suitable for further functional analyses, we performed DNA microarray-based NAT screening using mouse adult normal tissues and mammary tumors to target not only the sense orientation but also the complementary strand of the annotated genes. Results First, we designed microarray probes to target the complementary strand of genes for which an antisense counterpart had been identified only in human public cDNA sources, but not in the mouse. We observed a prominent expression signal from 66.1% of 635 target genes, and 58 genes of these showed tissue-specific expression. Expression analyses of selected examples (Acaa1b and Aard confirmed their dynamic transcription in vivo. Although interspecies conservation of NAT expression was previously investigated by the presence of cDNA sources in both species, our results suggest that there are more examples of human-mouse conserved NATs that could not be identified by cDNA sources. We also designed probes to target the complementary strand of well-characterized genes, including oncogenes, and compared the expression of these genes between mammary cancerous tissues and non-pathological tissues. We found that antisense expression of 95 genes of 404 well-annotated genes was markedly altered in tumor tissue compared with that in normal tissue and that 19 of these genes also exhibited changes in sense gene expression. These results highlight the importance of NAT expression in the regulation

  4. Noninferiority tests based on concordance correlation coefficient for assessment of the agreement for gene expression data from microarray experiments.

    Science.gov (United States)

    Liao, Chen-Tuo; Lin, Chia-Ying; Liu, Jen-Pei

    2007-01-01

    Microarray is one of the breakthrough technologies in the twenty-first century. Despite of its great potential, transition and realization of microarray technology into the clinically useful commercial products have not been as rapid as the technology could promise. One of the primary reasons is lack of agreement and poor reproducibility of the intensity measurements on gene expression obtained from microarray experiments. Current practices often use the testing the hypothesis of zero Pearson correlation coefficient to assess the agreement of gene expression levels between the technical replicates from microarray experiments. However, Pearson correlation coefficient is to evaluate linear association between two variables and fail to take into account changes in accuracy and precision. Hence, it is not appropriate for evaluation of agreement of gene expression levels between technical replicates. Therefore, we propose to use the concordance correlation coefficient to assess agreement of gene expression levels between technical replicates. We also apply the Generalized Pivotal Quantities to obtain the exact confidence interval for concordance coefficient. In addition, based on the concept of noninferiority test, a one-sided (1 - alpha) lower confidence limit for concordance correlation coefficient is employed to test the hypothesis that the agreement of expression levels of the same genes between two technical replicates exceeds some minimal requirement of agreement. We conducted a simulation study, under various combinations of mean differences, variability, and sample size, to empirically compare the performance of different methods for assessment of agreement in terms of coverage probability, expected length, size, and power. Numerical data from published papers illustrate the application of the proposed methods.

  5. Three microarray platforms: an analysis of their concordance in profiling gene expression

    Directory of Open Access Journals (Sweden)

    Petersen David

    2005-05-01

    Full Text Available Abstract Background Microarrays for the analysis of gene expression are of three different types: short oligonucleotide (25–30 base, long oligonucleotide (50–80 base, and cDNA (highly variable in length. The short oligonucleotide and cDNA arrays have been the mainstay of expression analysis to date, but long oligonucleotide platforms are gaining in popularity and will probably replace cDNA arrays. As part of a validation study for the long oligonucleotide arrays, we compared and contrasted expression profiles from the three formats, testing RNA from six different cell lines against a universal reference standard. Results The three platforms had 6430 genes in common. In general, correlation of gene expression levels across the platforms was good when defined by concordance in the direction of expression difference (upregulation or downregulation, scatter plot analysis, principal component analysis, cell line correlation or quantitative RT-PCR. The overall correlations (r values between platforms were in the range 0.7 to 0.8, as determined by analysis of scatter plots. When concordance was measured for expression ratios significant at p-values of Conclusion Our results indicate that the long oligonucleotide platform is highly suitable for expression analysis and compares favorably with the cDNA and short oligonucleotide varieties. All three platforms can give similar and reproducible results if the criterion is the direction of change in gene expression and minimal emphasis is placed on the magnitude of change.

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

    Directory of Open Access Journals (Sweden)

    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

  7. Difference in gene expression of macrophage between normal spleen and portal hypertensive spleen idendified by cDNA microarray

    OpenAIRE

    2007-01-01

    AIM: To identify the difference in gene expression of microphage (Mφ) between normal spleen and portal hypertensive spleen using cDNA microarrays and find new gene functions associated with hypersplenism in portal hypertension.

  8. Effect of Thyrotropin Releasing Hormone (TRH on Gene Expressions in Rat Pancreas: Approach by Microarray Hybridization

    Directory of Open Access Journals (Sweden)

    Luo LG

    2004-07-01

    Full Text Available CONTEXT: Thyrotropin releasing hormone (TRH, originally identified as a hypothalamic hormone, expresses in the pancreas. The effects of TRH such as, inhibiting amylase secretion in rats through a direct effect on acinar cells, enhancing basal glucagon secretion from isolated perfused rat pancreas, and potentiating glucose-stimulated insulin secretion in perfused rat islets and insulin-secreting clonal beta-cell lines, suggest that TRH may play a role in pancreas. TRH also enlarged pancreas and increased pancreatic DNA content but deletion of TRH gene expression caused hyperglycemia in mice, suggesting that TRH may play a critical role in pancreatic development; however, the biological mechanisms of TRH in the adult pancreas remains unclear. OBJECTIVES: This study explored the effect of TRH on rat pancreas. SUBJECTS: Four male-Sprague-Dawley-rats (200-250 g were given 10 microg/kg BW of TRH intraperitoneally on 1st and 3rd day and sacrificed on 7th day. Four same-strain rats without TRH injection served as controls. MAIN OUTCOME MEASURES: Wet pancreatic weights were measured. Pancreatic tissues were homogenized and extracted. The insulin levels of the extracts were measured by ELISA. Total RNA from the pancreases were fluorescently labeled and hybridized to microarray with 1,081 spot genes. RESULTS: TRH increased pancreatic wet weight and insulin contents. About 75% of the 1,081 genes were detected in the pancreas. TRH regulated up 99 genes and down 76 genes. The administration of TRH induced various types of gene expressions, such as G-protein coupled receptors (GPCR and signal transduction related genes (GPCR kinase 4, transducin beta subunit 5, arrestin beta1MAPK3, MAPK5, c-Src kinase, PKCs, PI3 kinase, growth factors (PDGF-B, IGF-2, IL-18, IGF-1, IL-2, IL-6, endothelin-1 and apoptotic factors (Bcl2, BAD, Bax. CONCLUSION: Reprogramming of transcriptome may be a way for TRH-regulation of pancreatic cellular functions.

  9. Handling multiple testing while interpreting microarrays with the Gene Ontology Database

    Directory of Open Access Journals (Sweden)

    Zhao Hongyu

    2004-09-01

    Full Text Available Abstract Background The development of software tools that analyze microarray data in the context of genetic knowledgebases is being pursued by multiple research groups using different methods. A common problem for many of these tools is how to correct for multiple statistical testing since simple corrections are overly conservative and more sophisticated corrections are currently impractical. A careful study of the nature of the distribution one would expect by chance, such as by a simulation study, may be able to guide the development of an appropriate correction that is not overly time consuming computationally. Results We present the results from a preliminary study of the distribution one would expect for analyzing sets of genes extracted from Drosophila, S. cerevisiae, Wormbase, and Gramene databases using the Gene Ontology Database. Conclusions We found that the estimated distribution is not regular and is not predictable outside of a particular set of genes. Permutation-based simulations may be necessary to determine the confidence in results of such analyses.

  10. Genes transactivated by hepatitis C virus core protein, a microarray assay

    Institute of Scientific and Technical Information of China (English)

    Min Liu; Shu-Lin Zhang; Jun Cheng; Yan Liu; Lin Wang; Qing Shao; Jian Zhang; Shu-Mei Lin

    2005-01-01

    AIM: To explore the new target genes transactivated by hepatitis C virus (HCV) core protein and to elucidate the pathogenesis of HCV infection.METHODS: Reverse transcribed cDNA was subjected tomicroarray assay. The coding gene transactivated by HCV core protein was cloned and analyzed with bioinformatics methods.RESULTS: The expressive vector of pcDNA3.1(-)-core was constructed and confirmed by restriction enzyme digestion and DNA sequencing and approved correct. mRNA was purified from HepG2 and HepG2 cells transfected with pcDNA3.1(-)-core, respectively. The cDNA derived was subjected to microarray assay. A new gene namedHCTP4 was cloned with molecular biological method in combination with bioinformatics method.CONCLUSION: HCV core is a potential transactivator.Microarray is an efficient and convenient method for analysis of differentially expressed genes.

  11. Colorectal cancer driver genes identified by patient specific comparison of cytogenetic microarray

    Directory of Open Access Journals (Sweden)

    Mohammad Azhar Aziz

    2014-12-01

    Full Text Available Colorectal cancer (CRC, which has high prevalence in Saudi Arabia and worldwide, needs better understanding by exploiting the latest available cytogenetic microarrays. We used biopsy tissue from consenting colorectal cancer patients to extract DNA and carry out microarray analysis using a CytoScan HD platform from Affymetrix. Patient specific comparisons of tumor–normal pairs were carried out. To find out the high probability key players, we performed Genomic Identification of Significant Targets in Cancer analysis and found 144 genes to form the list of driver genes. Of these, 24 genes attained high GISTIC scores and suggest being significantly associated with CRC. Loss of heterozygosity and uniparental disomy were found to affect 9 genes and suggest different mechanisms associated with CRC in every patient. Here we present the details of the methods used in carrying out the above analyses. Also, we provide some additional data on biomarker analysis that would complement the findings.

  12. Development and validation of a flax (Linum usitatissimum L. gene expression oligo microarray

    Directory of Open Access Journals (Sweden)

    Gutierrez Laurent

    2010-10-01

    Full Text Available Abstract Background Flax (Linum usitatissimum L. has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars and its cellulose-rich fibres (fibre-flax cultivars used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Results Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples. A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well

  13. Identification of Differentially Expressed IGFBP5-Related Genes in Breast Cancer Tumor Tissues Using cDNA Microarray Experiments.

    Science.gov (United States)

    Akkiprik, Mustafa; Peker, İrem; Özmen, Tolga; Amuran, Gökçe Güllü; Güllüoğlu, Bahadır M; Kaya, Handan; Özer, Ayşe

    2015-11-10

    IGFBP5 is an important regulatory protein in breast cancer progression. We tried to identify differentially expressed genes (DEGs) between breast tumor tissues with IGFBP5 overexpression and their adjacent normal tissues. In this study, thirty-eight breast cancer and adjacent normal breast tissue samples were used to determine IGFBP5 expression by qPCR. cDNA microarrays were applied to the highest IGFBP5 overexpressed tumor samples compared to their adjacent normal breast tissue. Microarray analysis revealed that a total of 186 genes were differentially expressed in breast cancer compared with normal breast tissues. Of the 186 genes, 169 genes were downregulated and 17 genes were upregulated in the tumor samples. KEGG pathway analyses showed that protein digestion and absorption, focal adhesion, salivary secretion, drug metabolism-cytochrome P450, and phenylalanine metabolism pathways are involved. Among these DEGs, the prominent top two genes (MMP11 and COL1A1) which potentially correlated with IGFBP5 were selected for validation using real time RT-qPCR. Only COL1A1 expression showed a consistent upregulation with IGFBP5 expression and COL1A1 and MMP11 were significantly positively correlated. We concluded that the discovery of coordinately expressed genes related with IGFBP5 might contribute to understanding of the molecular mechanism of the function of IGFBP5 in breast cancer. Further functional studies on DEGs and association with IGFBP5 may identify novel biomarkers for clinical applications in breast cancer.

  14. Microarray gene expression profiling of neural tissues in bovine spastic paresis

    OpenAIRE

    2013-01-01

    Background Bovine Spastic Paresis (BSP) is a neuromuscular disorder which affects both male and female cattle. BSP is characterized by spastic contraction and overextension of the gastrocnemious muscle of one or both limbs and is associated with a scarce increase in body weight. This disease seems to be caused by an autosomal and recessive gene, with incomplete penetration, although no genes clearly involved with its onset have been so far identified. We employed cDNA microarrays to identify ...

  15. Application of random matrix theory to microarray data for discovering functional gene modules.

    Science.gov (United States)

    Luo, Feng; Zhong, Jianxin; Yang, Yunfeng; Zhou, Jizhong

    2006-03-01

    We show that spectral fluctuation of coexpression correlation matrices of yeast gene microarray profiles follows the description of the Gaussian orthogonal ensemble (GOE) of the random matrix theory (RMT) and removal of small values of the correlation coefficients results in a transition from the GOE statistics to the Poisson statistics of the RMT. This transition is directly related to the structural change of the gene expression network from a global network to a network of isolated modules.

  16. Application of random matrix theory to microarray data for discovering functional gene modules

    Energy Technology Data Exchange (ETDEWEB)

    Luo, F. [Xiangtan University, Xiangtan Hunan, China; Zhong, Jianxin [ORNL; Yang, Y. F. [unknown; Zhou, Jizhong [ORNL

    2006-03-01

    We show that spectral fluctuation of coexpression correlation matrices of yeast gene microarray profiles follows the description of the Gaussian orthogonal ensemble (GOE) of the random matrix theory (RMT) and removal of small values of the correlation coefficients results in a transition from the GOE statistics to the Poisson statistics of the RMT. This transition is directly related to the structural change of the gene expression network from a global network to a network of isolated modules.

  17. Interpreting the gene expression microarray results: a user-based experience.

    Science.gov (United States)

    Melissari, Erika; Di Russo, Manuela; Mariotti, Veronica; Righi, Marco; Iofrida, Caterina; Pellegrini, Silvia

    2013-06-01

    In recent years many tools have been developed to cope with the interpretation of gene expression results from microarray experiments. The effectiveness of these tools largely depends on their ease of use by biomedical researchers. Tools based on effective computational methods, indeed, cannot be fully exploited by users if they are not supported by an intuitive interface, a large set of utilities and effective outputs. In this paper, 10 tools for the interpretation of gene expression microarray results have been tested on 11 microarray datasets and evaluated according to eight assessment criteria: 1. interface design and usability, 2. easiness of input submission, 3. effectiveness of output representation and 4. of the downloaded outputs, 5. possibility to submit multiple gene IDs, 6. sources of information, 7. provision of different statistical tests and 8. of multiple test correction methods. Strengths and weaknesses of each tool are highlighted to: a. provide useful tips to users dealing with the biological interpretation of microarray results; b. draw the attention of software developers on the usability of their tools.

  18. Identification of Arabidopsis candidate genes in response to biotic and abiotic stresses using comparative microarrays.

    Directory of Open Access Journals (Sweden)

    Arjun Sham

    Full Text Available Plants have evolved with intricate mechanisms to cope with multiple environmental stresses. To adapt with biotic and abiotic stresses, plant responses involve changes at the cellular and molecular levels. The current study was designed to investigate the effects of combinations of different environmental stresses on the transcriptome level of Arabidopsis genome using public microarray databases. We investigated the role of cyclopentenones in mediating plant responses to environmental stress through TGA (TGACG motif-binding factor transcription factor, independently from jasmonic acid. Candidate genes were identified by comparing plants inoculated with Botrytis cinerea or treated with heat, salt or osmotic stress with non-inoculated or non-treated tissues. About 2.5% heat-, 19% salinity- and 41% osmotic stress-induced genes were commonly upregulated by B. cinerea-treatment; and 7.6%, 19% and 48% of genes were commonly downregulated by B. cinerea-treatment, respectively. Our results indicate that plant responses to biotic and abiotic stresses are mediated by several common regulatory genes. Comparisons between transcriptome data from Arabidopsis stressed-plants support our hypothesis that some molecular and biological processes involved in biotic and abiotic stress response are conserved. Thirteen of the common regulated genes to abiotic and biotic stresses were studied in detail to determine their role in plant resistance to B. cinerea. Moreover, a T-DNA insertion mutant of the Responsive to Dehydration gene (rd20, encoding for a member of the caleosin (lipid surface protein family, showed an enhanced sensitivity to B. cinerea infection and drought. Overall, the overlapping of plant responses to abiotic and biotic stresses, coupled with the sensitivity of the rd20 mutant, may provide new interesting programs for increased plant resistance to multiple environmental stresses, and ultimately increases its chances to survive. Future research

  19. Identification of self-consistent modulons from bacterial microarray expression data with the help of structured regulon gene sets

    KAUST Repository

    Permina, Elizaveta A.

    2013-01-01

    Identification of bacterial modulons from series of gene expression measurements on microarrays is a principal problem, especially relevant for inadequately studied but practically important species. Usage of a priori information on regulatory interactions helps to evaluate parameters for regulatory subnetwork inference. We suggest a procedure for modulon construction where a seed regulon is iteratively updated with genes having expression patterns similar to those for regulon member genes. A set of genes essential for a regulon is used to control modulon updating. Essential genes for a regulon were selected as a subset of regulon genes highly related by different measures to each other. Using Escherichia coli as a model, we studied how modulon identification depends on the data, including the microarray experiments set, the adopted relevance measure and the regulon itself. We have found that results of modulon identification are highly dependent on all parameters studied and thus the resulting modulon varies substantially depending on the identification procedure. Yet, modulons that were identified correctly displayed higher stability during iterations, which allows developing a procedure for reliable modulon identification in the case of less studied species where the known regulatory interactions are sparse. Copyright © 2013 Taylor & Francis.

  20. ZODET: software for the identification, analysis and visualisation of outlier genes in microarray expression data.

    Directory of Open Access Journals (Sweden)

    Daniel L Roden

    Full Text Available Complex human diseases can show significant heterogeneity between patients with the same phenotypic disorder. An outlier detection strategy was developed to identify variants at the level of gene transcription that are of potential biological and phenotypic importance. Here we describe a graphical software package (z-score outlier detection (ZODET that enables identification and visualisation of gross abnormalities in gene expression (outliers in individuals, using whole genome microarray data. Mean and standard deviation of expression in a healthy control cohort is used to detect both over and under-expressed probes in individual test subjects. We compared the potential of ZODET to detect outlier genes in gene expression datasets with a previously described statistical method, gene tissue index (GTI, using a simulated expression dataset and a publicly available monocyte-derived macrophage microarray dataset. Taken together, these results support ZODET as a novel approach to identify outlier genes of potential pathogenic relevance in complex human diseases. The algorithm is implemented using R packages and Java.The software is freely available from http://www.ucl.ac.uk/medicine/molecular-medicine/publications/microarray-outlier-analysis.

  1. Signal oscillation is another reason for variability in microarray-based gene expression quantification.

    Directory of Open Access Journals (Sweden)

    Raghvendra Singh

    Full Text Available Microarrays have been widely used for various biological applications, such as, gene expression profiling, determination of SNPs, and disease profiling. However, quantification and analysis of microarray data have been a challenge. Previously, by taking into account translational and rotational diffusion of the target DNA, we have shown that the rate of hybridization depends on its size. Here, by mathematical modeling of surface diffusion of transcript, we show that the dynamics of hybridization on DNA microarray surface is inherently oscillatory and the amplitude of oscillation depends on fluid velocity. We found that high fluid velocity enhances the signal without affecting the background, and reduces the oscillation, thereby reducing likelihood of inter- and intra-experiment variability. We further show that a strong probe reduces dependence of signal-to-noise ratio on probe strength, decreasing inter-microarray variability. On the other hand, weaker probes are required for SNP detection. Therefore, we recommend high fluid velocity and strong probes for all microarray applications except determination of SNPs. For SNP detection, we recommend high fluid velocity with weak probe on the spot. We also recommend a surface with high adsorption and desorption rates of transcripts.

  2. Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

    Science.gov (United States)

    2010-01-01

    Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered), missing value imputation (2), standardization of data (2), gene selection (19) or clustering method (11). The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that background correction is

  3. Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

    Directory of Open Access Journals (Sweden)

    Landfors Mattias

    2010-10-01

    Full Text Available Abstract Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered, missing value imputation (2, standardization of data (2, gene selection (19 or clustering method (11. The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that

  4. A Microarray Study of Middle Cerebral Occlusion Rat Brain with Acupuncture Intervention

    Directory of Open Access Journals (Sweden)

    Chao Zhang

    2015-01-01

    Full Text Available Microarray analysis was used to investigate the changes of gene expression of ischemic stroke and acupuncture intervention in middle cerebral artery occlusion (MCAo rat brain. Results showed that acupuncture intervention had a remarkable improvement in neural deficit score, cerebral blood flow, and cerebral infarction volume of MCAo rats. Microarray analysis showed that a total of 627 different expression genes were regulated in ischemic stroke. 417 genes were upregulated and 210 genes were downregulated. A total of 361 different expression genes were regulated after acupuncture intervention. Three genes were upregulated and 358 genes were downregulated. The expression of novel genes after acupuncture intervention, including Tph1 and Olr883, was further analyzed by Real-Time Quantitative Polymerase Chain Reaction (RT-PCR. Upregulation of Tph1 and downregulation of Olr883 indicated that the therapeutic effect of acupuncture for ischemic stroke may be closely related to the suppression of poststroke depression and regulation of olfactory transduction. In conclusion, the present study may enrich our understanding of the multiple pathological process of ischemic brain injury and indicate possible mechanisms of acupuncture on ischemic stroke.

  5. Generation of EST and cDNA Microarray Resources for the Study of Bovine Immunobiology*

    Directory of Open Access Journals (Sweden)

    Coussens PM

    2003-03-01

    Full Text Available Recent developments in expressed sequence tag (EST and cDNA microarray technology have had a dramatic impact on the ability of scientists to study the responses of thousands of genes to external stimuli, such as infection, nutrient flux, and stress. To date however, these studies have largely been limited to human and rodent systems. Despite the tremendous potential benefit of EST and cDNA microarray technology to studies of complex problems in domestic animal species, a lack of integrated resources has precluded application of these technologies to domestic species. To address this problem, the Center for Animal Functional Genomics (CAFG at Michigan State University has developed a normalized bovine total leukocyte (BOTL cDNA library, generated EST clones from this library, and printed cDNA microarrays suitable for studying bovine immunobiology. Our data revealed that the normalization procedure successfully reduced highly abundant cDNA species while enhancing the relative percentage of clones representing rare transcripts. To date, a total of 932 EST sequences have been generated from this library (BOTL and the sequence information plus BLAST results made available through a web-accessible database http://gowhite.ans.msu.edu. Cluster analysis of the data indicates that a total of 842 unique cDNAs are present in this collection, reflecting a low redundancy rate of 9.7%. For creation of first generation cDNA microarrays, inserts from 720 unique clones in this library were amplified and microarrays were produced by spotting each insert or amplicon 3 times on glass slides in a 48-patch arrangement with 64 total spots (including blanks and positive controls per patch. To test our BOTL microarray, we compared gene expression patterns of concanavalin A stimulated and unstimulated peripheral blood mononuclear cells (PBMCs. In total, hybridization signals on over 90 amplicons showed upregulation (>3× in response to Con A stimulation, relative to

  6. Multi-gene detection and identification of mosquito-borne RNA viruses using an oligonucleotide microarray.

    Directory of Open Access Journals (Sweden)

    Nathan D Grubaugh

    Full Text Available BACKGROUND: Arthropod-borne viruses are important emerging pathogens world-wide. Viruses transmitted by mosquitoes, such as dengue, yellow fever, and Japanese encephalitis viruses, infect hundreds of millions of people and animals each year. Global surveillance of these viruses in mosquito vectors using molecular based assays is critical for prevention and control of the associated diseases. Here, we report an oligonucleotide DNA microarray design, termed ArboChip5.1, for multi-gene detection and identification of mosquito-borne RNA viruses from the genera Flavivirus (family Flaviviridae, Alphavirus (Togaviridae, Orthobunyavirus (Bunyaviridae, and Phlebovirus (Bunyaviridae. METHODOLOGY/PRINCIPAL FINDINGS: The assay utilizes targeted PCR amplification of three genes from each virus genus for electrochemical detection on a portable, field-tested microarray platform. Fifty-two viruses propagated in cell-culture were used to evaluate the specificity of the PCR primer sets and the ArboChip5.1 microarray capture probes. The microarray detected all of the tested viruses and differentiated between many closely related viruses such as members of the dengue, Japanese encephalitis, and Semliki Forest virus clades. Laboratory infected mosquitoes were used to simulate field samples and to determine the limits of detection. Additionally, we identified dengue virus type 3, Japanese encephalitis virus, Tembusu virus, Culex flavivirus, and a Quang Binh-like virus from mosquitoes collected in Thailand in 2011 and 2012. CONCLUSIONS/SIGNIFICANCE: We demonstrated that the described assay can be utilized in a comprehensive field surveillance program by the broad-range amplification and specific identification of arboviruses from infected mosquitoes. Furthermore, the microarray platform can be deployed in the field and viral RNA extraction to data analysis can occur in as little as 12 h. The information derived from the ArboChip5.1 microarray can help to establish

  7. Monitoring microarray-based gene expression profile changes in hepatocellular carcinoma

    Institute of Scientific and Technical Information of China (English)

    Hong-Ju Mao; Hong-Nian Li; Xiao-Mei Zhou; Jian-Long Zhao; Da-Fang Wan

    2005-01-01

    AIM: To find out key genes responsible for hepatocarc inogenesis and to further understand the underlying molecular mechanism through investigating the differential gene expression between human normal liver tissue and hepatocellular carcinoma (HCC).METHODS: DNA microarray was prepared by spotting PCR products of 1 000 human genes including 445 novel genes, 540 known genes as well as 12 positive (housekeeping) and 3 negative controls (plant gene) onto treated glass slides. cDNA probes were prepared by labeling normal liver tissue mRNA and cancer liver tissue mRNA with Cy3-dUTP and Cy5-dUTP separately through reverse transcription. The arrays were hybridized against the cDNA probe and the fluorescent signals were scanned. The dataobtained from repeated experiments were analyzed. RESULTS: Among the 20 couple samples investigated (from cancerous liver tissue and normal liver tissue), 38 genes including 21 novel genes and 17 known genes exhibited different expressions. CONCLUSION: cDNA microarray technique is powerful to identify candidate target genes that may play important roles in human carcinogenesis. Further analysis of the obtained genes is helpful to understand the molecular changes in HCC progression and ultimately may lead to the identification of new targets for HCC diagnosis and intervention.

  8. Identification of late O{sub 3}-responsive genes in Arabidopsis thaliana by cDNA microarray analysis

    Energy Technology Data Exchange (ETDEWEB)

    D' Haese, D. [Univ. of Antwerp, Dept. of Biology, Antwerp (BE) and Univ. of Newcastle, School of Biology and Psychology, Div. of Biology, Newcastle-Upon-Tyne (United Kingdom); Horemans, N.; Coen, W. De; Guisez, Y. [Univ. of Antwerp, Dept. of Biology, Antwerp (Belgium)

    2006-09-15

    To better understand the response of a plant to 0{sub 3} stress, an integrated microarray analysis was performed on Arabidopsis plants exposed during 2 days to purified air or 150 nl l{sup -1} O{sub 3}, 8 h day-l. Agilent Arabidopsis 2 Oligo Microarrays were used of which the reliability was confirmed by quantitative real-time PCR of nine randomly selected genes. We confirmed the O{sub 3} responsiveness of heat shock proteins (HSPs), glutathione-S-tranferases and genes involved in cell wall stiffening and microbial defence. Whereas, a previous study revealed that during an early stage of the O{sub 3} stress response, gene expression was strongly dependent on jasmonic acid and ethylene, we report that at a later stage (48 h) synthesis of jasrnonic acid and ethylene was downregulated. In addition, we observed the simultaneous induction of salicylic acid synthesis and genes involved in programmed cell death and senescence. Also typically, the later stage of the response to O{sub 3} appeared to be the induction of the complete pathway leading to the biosynthesis of anthocyanin diglucosides and the induction of thioredoxin-based redox control. Surprisingly absent in the list of induced genes were genes involved in ASC-dependent antioxidation, few of which were found to be induced after 12 h of 0{sub 3} exposure in another study. We discuss these and other particular results of the microarray analysis and provide a map depicting significantly affected genes and their pathways highlighting their interrelationships and subcellular localization. (au)

  9. Identification of two genes potentially associated in iron-heme homeostasis in human carotid plaque using microarray analysis

    Indian Academy of Sciences (India)

    Hanène Ayari; Giampiero Bricca

    2013-06-01

    Classic characteristics are poor predictors of the risk of thromboembolism. Thus, better markers for the carotid atheroma plaque formation and symptom causing are needed. Our objective was to study by microarray analysis gene expression of genes involved in homeostasis of iron and heme in carotid atheroma plaque from the same patient. mRNA gene expression was measured by an Affymetrix GeneChip Human Gene 1.0 ST arrays (Affymetrix, Santa Clara, CA, USA) using RNA prepared from 68 specimens of endarteriectomy from 34 patients. Two genes involved in iron-heme homeostasis, CD163 and heme oxygenase (HO-1), were analysed in 34 plaques. CD163 (2.18, =1.45E−08) and HO-1 (fold-change 2.67, =2.07E−09) mRNAs were induced. We suggest that atheroma plaques show a more pronounced induction of CD163 and HO-1. Although further evidence is needed, our results support previous data. To our knowledge, this is the first report comparing gene expression between intact arterial tissue and carotid plaque using microarray analysis.

  10. Microarray data and gene expression statistics for Saccharomyces cerevisiae exposed to simulated asbestos mine drainage

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    Heather E. Driscoll

    2017-08-01

    Full Text Available Here we describe microarray expression data (raw and normalized, experimental metadata, and gene-level data with expression statistics from Saccharomyces cerevisiae exposed to simulated asbestos mine drainage from the Vermont Asbestos Group (VAG Mine on Belvidere Mountain in northern Vermont, USA. For nearly 100 years (between the late 1890s and 1993, chrysotile asbestos fibers were extracted from serpentinized ultramafic rock at the VAG Mine for use in construction and manufacturing industries. Studies have shown that water courses and streambeds nearby have become contaminated with asbestos mine tailings runoff, including elevated levels of magnesium, nickel, chromium, and arsenic, elevated pH, and chrysotile asbestos-laden mine tailings, due to leaching and gradual erosion of massive piles of mine waste covering approximately 9 km2. We exposed yeast to simulated VAG Mine tailings leachate to help gain insight on how eukaryotic cells exposed to VAG Mine drainage may respond in the mine environment. Affymetrix GeneChip® Yeast Genome 2.0 Arrays were utilized to assess gene expression after 24-h exposure to simulated VAG Mine tailings runoff. The chemistry of mine-tailings leachate, mine-tailings leachate plus yeast extract peptone dextrose media, and control yeast extract peptone dextrose media is also reported. To our knowledge this is the first dataset to assess global gene expression patterns in a eukaryotic model system simulating asbestos mine tailings runoff exposure. Raw and normalized gene expression data are accessible through the National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO Database Series GSE89875 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE89875.

  11. Microarray analysis of gene expression profiles in the bovine mammary gland during lactation

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Mammary glands undergo functional and metabolic changes during virgin,lactation and dry periods.A total of 122 genes were identified as differentially expressed,including 79 up-regulated and 43 down-regulated genes during lactation compared with virgin and dry periods.Gene ontology analysis showed the functional classification of the up-regulated genes in lactation,including transport,biosynthetic process,signal transduction,catalytic activity,immune system process,cell death,and positive regulation of the developmental process.Microarray data clarified molecular events in bovine mammary gland lactation.

  12. Multicriteria Gene Screening for Analysis of Differential Expression with DNA Microarrays

    Directory of Open Access Journals (Sweden)

    Alfred O. Hero

    2004-01-01

    Full Text Available This paper introduces a statistical methodology for the identification of differentially expressed genes in DNA microarray experiments based on multiple criteria. These criteria are false discovery rate (FDR, variance-normalized differential expression levels (paired t statistics, and minimum acceptable difference (MAD. The methodology also provides a set of simultaneous FDR confidence intervals on the true expression differences. The analysis can be implemented as a two-stage algorithm in which there is an initial screen that controls only FDR, which is then followed by a second screen which controls both FDR and MAD. It can also be implemented by computing and thresholding the set of FDR P values for each gene that satisfies the MAD criterion. We illustrate the procedure to identify differentially expressed genes from a wild type versus knockout comparison of microarray data.

  13. Microarray and Proteomic Analysis of Brassinosteroid- and Gibberellin-Regulated Gene and Protein Expression in Rice

    Institute of Scientific and Technical Information of China (English)

    Guangxiao Yang; Setsuko Komatsu

    2004-01-01

    Brassinosteroid (BR) and gibberellin (GA) are two groups of plant growth regulators essential for normal plant growth and development. To gain insight into the molecular mechanism by which BR and GA regulate the growth and development of plants, especially the monocot plant rice, it is necessary to identify and analyze more genes and proteins that are regulated by them. With the availability of draft sequences of two major types, japonica and indica rice, it has become possible to analyze expression changes of genes and proteins at genome scale. In this review, we summarize rice functional genomic research by using microarray and proteomic approaches and our recent research results focusing on the comparison of cDNA microarray and proteomic analyses of BR- and GA-regulated gene and protein expression in rice. We believe our findings have important implications for understanding the mechanism by which BR and GA regulate the growth and development of rice.

  14. Profiling gene expression patterns of nasopharyngeal carcinoma and normal nasopharynx tissues with cDNA microarray

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    5 μg of total RNAs from normal nasopharynx and nasopharyngeal carcinoma tissue have been labeled with α-32P-dCTP during reverse transcription. The synthesized cDNA probes have been hybridized to high-density cDNA microarray containing 5184 genes or expression sequence tags (ESTs). Then image analysis software has been applied to comparing their expression profiles. Results show that 187 ESTs were of density value above 200 in nasopharyngeal carcinoma tissue while there were 307 such ESTs in normal nasopharynx tissue; 38 ESTs were strongly expressed in nasopharynx, but weakly expressed in nasopharyngeal carcinoma; 48 ESTs were strongly expressed in nasopharyngeal carcinoma, but weakly expressed in normal nasopharynx. These results suggest that there may exist some new differentially expressed genes involved in nasopharyngeal carcinoma development. Furthermore, the results strongly indicate that high-density cDNA microarray is a powerful and efficient tool for large-scale screening differentially expressed genes.

  15. Effects of aspirin on metastasis-associated gene expression detected by cDNA microarray

    Institute of Scientific and Technical Information of China (English)

    Xue-qin GAO; Jin-xiang HAN; Hai-yan HUANG; Shi YAN; Chang-zheng SONG; Hai-nan HUANG

    2004-01-01

    AIM: To investigate the effect of aspirin on the metastasis-associated gene expression in 3AO ovarian cancer cells.METHODS: 3AO cells were treated with aspirin at the concentration of 1.2 mmol/L for 16 and 48 h, respectively.The total RNA was extracted with Trizol reagents and reverse transcribed with Superscript II and hybridized with cDNA microarray (containing oncogenes, tumor suppressor genes, signal transduction pathway molecules, adhesive molecules, growth factors and ESTs) fabricated in our lab. After normalization, the ratio of gene expression of aspirin treated to untreated 3AO cells being either 2 fold up higher or 0.5 fold down (lower) were defined as differential expression. Semi-quantitative RT-PCR was used to validate the microarray results. RESULTS: Among the 447 metastasis-associated genes, 4 genes were up-regulated and 14 genes were down-regulated in 3AO cells treated with aspirin for 16 h compared with untreated cells. While 24 genes were up-regulated and 10 genes were down-regulated in cells treated with aspirin for 48 h. Several up or down-regulated gene expression changes continued from 16 h to 48 h. CONCLUSION: Aspirin might exert its anti-metastasis effects on ovarian cancer by affecting metastasis-associated gene expression.

  16. Oligonucleotide microarray analysis of dietary-induced hyperlipidemia gene expression profiles in miniature pigs.

    Directory of Open Access Journals (Sweden)

    Junko Takahashi

    Full Text Available BACKGROUND: Hyperlipidemia animal models have been established, but complete gene expression profiles of the transition from normal lipid levels have not been obtained. Miniature pigs are useful model animals for gene expression studies on dietary-induced hyperlipidemia because they have a similar anatomy and digestive physiology to humans, and blood samples can be obtained from them repeatedly. METHODOLOGY: Two typical dietary treatments were used for dietary-induced hyperlipidemia models, by using specific pathogen-free (SPF Clawn miniature pigs. One was a high-fat and high-cholesterol diet (HFCD and the other was a high-fat, high-cholesterol, and high-sucrose diet (HFCSD. Microarray analyses were conducted from whole blood samples during the dietary period and from white blood cells at the end of the dietary period to evaluate the transition of expression profiles of the two dietary models. PRINCIPAL FINDINGS: Variations in whole blood gene expression intensity within the HFCD or the HFCSD group were in the same range as the controls provide with normal diet at all periods. This indicates uniformity of dietary-induced hyperlipidemia for our dietary protocols. Gene ontology- (GO based functional analyses revealed that characteristics of the common changes between HFCD and HFCSD were involved in inflammatory responses and reproduction. The correlation coefficient between whole blood and white blood cell expression profiles at 27 weeks with the HFCSD diet was significantly lower than that of the control and HFCD diet groups. This may be due to the effects of RNA originating from the tissues and/or organs. CONCLUSIONS: No statistically significant differences in fasting plasma lipids and glucose levels between the HFCD and HFCSD groups were observed. However, blood RNA analyses revealed different characteristics corresponding to the dietary protocols. In this study, whole blood RNA analyses proved to be a useful tool to evaluate transitions in

  17. Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and information theory

    Science.gov (United States)

    Sayyed-Ahmad, Abdallah; Tuncay, Kagan; Ortoleva, Peter J

    2007-01-01

    Background Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targeted treatments. A new approach to the construction and quantification of transcriptional regulatory networks (TRNs) is presented that integrates gene expression microarray data and cell modeling through information theory. Given a partial TRN and time series data, a probability density is constructed that is a functional of the time course of transcription factor (TF) thermodynamic activities at the site of gene control, and is a function of mRNA degradation and transcription rate coefficients, and equilibrium constants for TF/gene binding. Results Our approach yields more physicochemical information that compliments the results of network structure delineation methods, and thereby can serve as an element of a comprehensive TRN discovery/quantification system. The most probable TF time courses and values of the aforementioned parameters are obtained by maximizing the probability obtained through entropy maximization. Observed time delays between mRNA expression and activity are accounted for implicitly since the time course of the activity of a TF is coupled by probability functional maximization, and is not assumed to be proportional to expression level of the mRNA type that translates into the TF. This allows one to investigate post-translational and TF activation mechanisms of gene regulation. Accuracy and robustness of the method are evaluated. A kinetic formulation is used to facilitate the analysis of phenomena with a strongly dynamical character while a physically-motivated regularization of the TF time course is found to overcome difficulties due to omnipresent noise and data sparsity that plague other methods of gene expression data analysis. An application to Escherichia coli is presented. Conclusion Multiplex time series data can be used for the construction of the network of

  18. Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and information theory

    Directory of Open Access Journals (Sweden)

    Tuncay Kagan

    2007-01-01

    Full Text Available Abstract Background Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targeted treatments. A new approach to the construction and quantification of transcriptional regulatory networks (TRNs is presented that integrates gene expression microarray data and cell modeling through information theory. Given a partial TRN and time series data, a probability density is constructed that is a functional of the time course of transcription factor (TF thermodynamic activities at the site of gene control, and is a function of mRNA degradation and transcription rate coefficients, and equilibrium constants for TF/gene binding. Results Our approach yields more physicochemical information that compliments the results of network structure delineation methods, and thereby can serve as an element of a comprehensive TRN discovery/quantification system. The most probable TF time courses and values of the aforementioned parameters are obtained by maximizing the probability obtained through entropy maximization. Observed time delays between mRNA expression and activity are accounted for implicitly since the time course of the activity of a TF is coupled by probability functional maximization, and is not assumed to be proportional to expression level of the mRNA type that translates into the TF. This allows one to investigate post-translational and TF activation mechanisms of gene regulation. Accuracy and robustness of the method are evaluated. A kinetic formulation is used to facilitate the analysis of phenomena with a strongly dynamical character while a physically-motivated regularization of the TF time course is found to overcome difficulties due to omnipresent noise and data sparsity that plague other methods of gene expression data analysis. An application to Escherichia coli is presented. Conclusion Multiplex time series data can be used for the

  19. GeneMesh: a web-based microarray analysis tool for relating differentially expressed genes to MeSH terms

    Directory of Open Access Journals (Sweden)

    Argraves W Scott

    2010-04-01

    Full Text Available Abstract Background An important objective of DNA microarray-based gene expression experimentation is determining inter-relationships that exist between differentially expressed genes and biological processes, molecular functions, cellular components, signaling pathways, physiologic processes and diseases. Results Here we describe GeneMesh, a web-based program that facilitates analysis of DNA microarray gene expression data. GeneMesh relates genes in a query set to categories available in the Medical Subject Headings (MeSH hierarchical index. The interface enables hypothesis driven relational analysis to a specific MeSH subcategory (e.g., Cardiovascular System, Genetic Processes, Immune System Diseases etc. or unbiased relational analysis to broader MeSH categories (e.g., Anatomy, Biological Sciences, Disease etc.. Genes found associated with a given MeSH category are dynamically linked to facilitate tabular and graphical depiction of Entrez Gene information, Gene Ontology information, KEGG metabolic pathway diagrams and intermolecular interaction information. Expression intensity values of groups of genes that cluster in relation to a given MeSH category, gene ontology or pathway can be displayed as heat maps of Z score-normalized values. GeneMesh operates on gene expression data derived from a number of commercial microarray platforms including Affymetrix, Agilent and Illumina. Conclusions GeneMesh is a versatile web-based tool for testing and developing new hypotheses through relating genes in a query set (e.g., differentially expressed genes from a DNA microarray experiment to descriptors making up the hierarchical structure of the National Library of Medicine controlled vocabulary thesaurus, MeSH. The system further enhances the discovery process by providing links between sets of genes associated with a given MeSH category to a rich set of html linked tabular and graphic information including Entrez Gene summaries, gene ontologies

  20. Gene expression profile analysis of genes in rat hippocampus from antidepressant treated rats using DNA microarray

    Directory of Open Access Journals (Sweden)

    Shin Minkyu

    2010-11-01

    Full Text Available Abstract Background The molecular and biological mechanisms by which many antidepressants function are based on the monoamine depletion hypothesis. However, the entire cascade of mechanisms responsible for the therapeutic effect of antidepressants has not yet been elucidated. Results We used a genome-wide microarray system containing 30,000 clones to evaluate total RNA that had been isolated from the brains of treated rats to identify the genes involved in the therapeutic mechanisms of various antidepressants, a tricyclic antidepressant (imipramine. a selective serotonin reuptake inhibitor (fluoxetine, a monoamine oxidase inhibitor (phenelzine and psychoactive herbal extracts of Nelumbinis Semen (NS. To confirm the differential expression of the identified genes, we analyzed the amount of mRNA that was isolated from the hippocampus of rats that had been treated with antidepressants by real-time RT-PCR using primers specific for selected genes of interest. These data demonstrate that antidepressants interfere with the expression of a large array of genes involved in signaling, survival and protein metabolism, suggesting that the therapeutic effect of these antidepressants is very complex. Surprisingly, unlike other antidepressants, we found that the standardized herbal medicine, Nelumbinis Semen, is free of factors that can induce neurodegenerative diseases such as caspase 8, α-synuclein, and amyloid precursor protein. In addition, the production of the inflammatory cytokine, IFNγ, was significantly decreased in rat hippocampus in response to treatment with antidepressants, while the inhibitory cytokine, TGFβ, was significantly enhanced. Conclusions These results suggest that antidepressants function by regulating neurotransmission as well as suppressing immunoreactivity in the central nervous system.

  1. Stochastic models for inferring genetic regulation from microarray gene expression data.

    Science.gov (United States)

    Tian, Tianhai

    2010-03-01

    Microarray expression profiles are inherently noisy and many different sources of variation exist in microarray experiments. It is still a significant challenge to develop stochastic models to realize noise in microarray expression profiles, which has profound influence on the reverse engineering of genetic regulation. Using the target genes of the tumour suppressor gene p53 as the test problem, we developed stochastic differential equation models and established the relationship between the noise strength of stochastic models and parameters of an error model for describing the distribution of the microarray measurements. Numerical results indicate that the simulated variance from stochastic models with a stochastic degradation process can be represented by a monomial in terms of the hybridization intensity and the order of the monomial depends on the type of stochastic process. The developed stochastic models with multiple stochastic processes generated simulations whose variance is consistent with the prediction of the error model. This work also established a general method to develop stochastic models from experimental information.

  2. The Gene Expression Profile of D-galactose Induced Aging Model Rat Using cDNA Microarray

    Institute of Scientific and Technical Information of China (English)

    Li Min(李珉); Wang Gang; Zhang Wei; Wang Miqu; Zhang Yizheng

    2004-01-01

    In order to study the molecular mechanism of D-galactose induced aging model, cDNA microarray is used to analyze gene expression profiles of both normal and D-galactose induced aging model rats. D-galactose induced aging model rats are injected with D-galactose, while normal rats are injected with physiological saline as control. After 7 weeks, the two groups of rats are killed simultaneously. Their livers are harvested for genome-wide expression analysis. D-galactose treated rats showed changes in gene expression associated with increase or decrease in xenobiotic metabolism, protein metabolism and energy metabolism.

  3. Alternations in genes expression of pathway signaling in esophageal tissue with atresia: results of expression microarray profiling.

    Science.gov (United States)

    Smigiel, R; Lebioda, A; Blaszczyński, M; Korecka, K; Czauderna, P; Korlacki, W; Jakubiak, A; Bednarczyk, D; Maciejewski, H; Wizinska, P; Sasiadek, M M; Patkowski, D

    2015-04-01

    Esophageal atresia (EA) is a congenital defect of the esophagus involving the interruption of the esophagus with or without connection to the trachea (tracheoesophageal fistula [TEF]). EA/TEF may occur as an isolated anomaly, may be part of a complex of congenital defects (syndromic), or may develop within the context of a known syndrome or association. The molecular mechanisms underlying the development of EA are poorly understood. It is supposed that a combination of multigenic factors and epigenetic modification of genes play a role in its etiology. The aim of our work was to assess the human gene expression microarray study in esophageal tissue samples. Total RNA was extracted from 26 lower pouches of esophageal tissue collected during thoracoscopic EA repair in neonates with the isolated (IEA) and the syndromic form (SEA). We identified 787 downregulated and 841 upregulated transcripts between SEA and controls, and about 817 downregulated and 765 upregulated probes between IEA and controls. Fifty percent of these genes showed differential expression specific for either IEA or SEA. Functional pathway analysis revealed substantial enrichment for Wnt and Sonic hedgehog, as well as cytokine and chemokine signaling pathways. Moreover, we performed reverse transcription polymerase chain reaction study in a group of SHH and Wnt pathways genes with differential expression in microarray profiling to confirm the microarray expression results. We verified the altered expression in SFRP2 gene from the Wnt pathway as well as SHH, GLI1, GLI2, and GLI3 from the Sonic hedgehog pathway. The results suggest an important role of these pathways and genes for EA/TEF etiology. © 2014 International Society for Diseases of the Esophagus.

  4. Difference in gene expression of macrophage between normal spleen and portal hypertensive spleen idendified by cDNA microarray

    Institute of Scientific and Technical Information of China (English)

    Feng Yan; Xiao-Min Wang

    2007-01-01

    AIM: To identify the difference in gene expression of microphage (Mφ) between normal spleen and portal hypertensive spleen using cDNA microarrays and find new gene functions associated with hypersplenism in portal hypertension.METHODS: The Biostar-H140s chip containing 14112 spots of cDNAs were used to investigate the difference of the expression. The total RNA extracted from macrophages isolated from both normal spleen and portal hypertensive spleen was reversely transcribed to cDNA with the incorporation of fluorescent (cy3 and cy5) labeled dCTP to prepare the hybridization probes.After hybridization, the gene chip was scanned for the fluorescent intensity. The differentially expressed genes were screened. That was repeated three times,and only the genes which had differential expression in all three chips were considered to be associated with hypersplenism in portal hypertension.RESULTS: Eight hundred and ninety-six, 1330 and 898 genes were identified to be differentially expressed in three chips, respectively. One hundred and twenty-one genes (0.86%) were identified to be differentially expressed in all three chips, including 21 up-regulated genes and 73 down-regulated genes. The differentially expressed genes were related to ionic channel and transport protein, cyclin, cytoskeleton, cell receptor, cell signal conduct, metabolism, immune, and so on. These genes might be related to the hypersplenism in portal hypertension.CONCLUSION: The investigations based on cDNA microarray can screen differentially expressed genes of macrophages between normal spleen and portal hypertensive spleen, thus may provide a new idea in studying the pathogenesis of hypersplenism in portal hypertension.

  5. Multi-membership gene regulation in pathway based microarray analysis

    OpenAIRE

    2011-01-01

    This article is available through the Brunel Open Access Publishing Fund. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background: Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the inte...

  6. [DNA microarray-based gene expression profiling in diagnosis, assessing prognosis and predicting response to therapy in colorectal cancer].

    Science.gov (United States)

    Kwiatkowski, Przemysław; Wierzbicki, Piotr; Kmieć, Andrzej; Godlewski, Janusz

    2012-06-11

     Colorectal cancer is the most common cancer of the gastrointestinal tract. It is considered as a biological model of a certain type of cancerogenesis process in which progression from an early to late stage adenoma and cancer is accompanied by distinct genetic alterations. Clinical and pathological parameters commonly used in clinical practice are often insufficient to determine groups of patients suitable for personalized treatment. Moreover, reliable molecular markers with high prognostic value have not yet been determined. Molecular studies using DNA-based microarrays have identified numerous genes involved in cell proliferation and differentiation during the process of cancerogenesis. Assessment of the genetic profile of colorectal cancer using the microarray technique might be a useful tool in determining the groups of patients with different clinical outcomes who would benefit from additional personalized treatment. The main objective of this study was to present the current state of knowledge on the practical application of gene profiling techniques using microarrays for determining diagnosis, prognosis and response to treatment in colorectal cancer.

  7. Analyzing Multiple-Probe Microarray: Estimation and Application of Gene Expression Indexes

    KAUST Repository

    Maadooliat, Mehdi

    2012-07-26

    Gene expression index estimation is an essential step in analyzing multiple probe microarray data. Various modeling methods have been proposed in this area. Amidst all, a popular method proposed in Li and Wong (2001) is based on a multiplicative model, which is similar to the additive model discussed in Irizarry et al. (2003a) at the logarithm scale. Along this line, Hu et al. (2006) proposed data transformation to improve expression index estimation based on an ad hoc entropy criteria and naive grid search approach. In this work, we re-examined this problem using a new profile likelihood-based transformation estimation approach that is more statistically elegant and computationally efficient. We demonstrate the applicability of the proposed method using a benchmark Affymetrix U95A spiked-in experiment. Moreover, We introduced a new multivariate expression index and used the empirical study to shows its promise in terms of improving model fitting and power of detecting differential expression over the commonly used univariate expression index. As the other important content of the work, we discussed two generally encountered practical issues in application of gene expression index: normalization and summary statistic used for detecting differential expression. Our empirical study shows somewhat different findings from the MAQC project (MAQC, 2006).

  8. Microarray-based analysis of IncA/C plasmid-associated genes from multidrug-resistant Salmonella enterica.

    Science.gov (United States)

    Lindsey, Rebecca L; Frye, Jonathan G; Fedorka-Cray, Paula J; Meinersmann, Richard J

    2011-10-01

    In the family Enterobacteriaceae, plasmids have been classified according to 27 incompatibility (Inc) or replicon types that are based on the inability of different plasmids with the same replication mechanism to coexist in the same cell. Certain replicon types such as IncA/C are associated with multidrug resistance (MDR). We developed a microarray that contains 286 unique 70-mer oligonucleotide probes based on sequences from five IncA/C plasmids: pYR1 (Yersinia ruckeri), pPIP1202 (Yersinia pestis), pP99-018 (Photobacterium damselae), pSN254 (Salmonella enterica serovar Newport), and pP91278 (Photobacterium damselae). DNA from 59 Salmonella enterica isolates was hybridized to the microarray and analyzed for the presence or absence of genes. These isolates represented 17 serovars from 14 different animal hosts and from different geographical regions in the United States. Qualitative cluster analysis was performed using CLUSTER 3.0 to group microarray hybridization results. We found that IncA/C plasmids occurred in two lineages distinguished by a major insertion-deletion (indel) region that contains genes encoding mostly hypothetical proteins. The most variable genes were represented by transposon-associated genes as well as four antimicrobial resistance genes (aphA, merP, merA, and aadA). Sixteen mercury resistance genes were identified and highly conserved, suggesting that mercury ion-related exposure is a stronger pressure than anticipated. We used these data to construct a core IncA/C genome and an accessory genome. The results of our studies suggest that the transfer of antimicrobial resistance determinants by transfer of IncA/C plasmids is somewhat less common than exchange within the plasmids orchestrated by transposable elements, such as transposons, integrating and conjugative elements (ICEs), and insertion sequence common regions (ISCRs), and thus pose less opportunity for exchange of antimicrobial resistance.

  9. Type I interferon related genes are common genes on the early stage after vaccination by meta-analysis of microarray data.

    Science.gov (United States)

    Zhang, Junnan; Shao, Jie; Wu, Xing; Mao, Qunying; Wang, Yiping; Gao, Fan; Kong, Wei; Liang, Zhenglun

    2015-01-01

    The objective of this study was to find common immune mechanism across different kinds of vaccines. A meta-analysis of microarray datasets was performed using publicly available microarray Gene Expression Omnibus (GEO) and Array Express data sets of vaccination records. Seven studies (out of 35) were selected for this meta-analysis. A total of 447 chips (145 pre-vaccination and 302 post-vaccination) were included. Significance analysis of microarrays (SAM) program was used for screening differentially expressed genes (DEGs). Functional pathway enrichment for the DEGs was conducted in DAVID Gene Ontology (GO) database. Twenty DEGs were identified, of which 10 up-regulated genes involved immune response. Six of which were type I interferon (IFN) related genes, including LY6E, MX1, OAS3, IFI44L, IFI6 and IFITM3. Ten down-regulated genes mainly mediated negative regulation of cell proliferation and cell motion. Results of a subgroup analysis showed that although the kinds of genes varied widely between days 3 and 7 post vaccination, the pathways between them are basically the same, such as immune response and response to viruses, etc. For an independent verification of these 6 type I IFN related genes, peripheral blood mononuclear cells (PBMCs) were collected at baseline and day 3 after the vaccination from 8 Enterovirus 71(EV71) vaccinees and were assayed by RT-PCR. Results showed that the 6 DEGs were also upregulated in EV71 vaccinees. In summary, meta-analysis methods were used to explore the immune mechanism of vaccines and results indicated that the type I IFN related genes and corresponding pathways were common in early immune responses for different kinds of vaccines.

  10. MICROARRAY ANALYSIS OF DIFFERENT GENE EXPRESSION OF HUMAN CERVICAL CANCER SUBCLONE CELL LINES

    Institute of Scientific and Technical Information of China (English)

    Chen Wei; Li Xu; Wang Xiang

    2006-01-01

    Objective To examine the differentially expressed invasion-related genes in two anchorage-independent uterine cervical carcinoma cell lines derived from the same patient using a cDNA array. Methods Two human uterine cervical carcinoma subclonal cell lines CS03 and CS07 derived from a single donor line CS1213 were established by limited dilution procedure. The two cDNA samples retro-transcribed from total RNA derived from CS03 and CS07 cells were screened by a cDNA microarray carrying 234 human cell-cycle related genes and 1011 human signal transduction and membrane receptor -associated genes, scanned with a ScanArray 3000 laser scanner. Results The cDNA microarray analysis showed that 12 genes in CS03 were up-regulated compared to CS07, and 24 genes in CS07 were up-regulated. The function of a number of differentially expressed genes was consistently associated with cell-cycle, cell proliferation, migration, apoptosis, signal transduction and tumor metastasis, including p34cdc2, TSC22, plasminogen activator inhibitor I (PAI-1)and desmosome associated protein(Pinin). Conclusion Multiple genes are differentially expressed in uterine cervical carcinoma cell lines even came from the same patient. It is suggested that these genes are involved in the different phenotypic characteristics and development of cervical carcinoma.

  11. Microarray technology reveals potentially novel genes and pathways involved in non-functioning pituitary adenomas

    Science.gov (United States)

    Qiao, X; Wang, H; Wang, X; Zhao, B

    2016-01-01

    Abstract Microarray data of non-functioning pituitary adenomas (NFPAs) were analyzed to disclose novel genes and pathways involved in NFPA tumorigenesis. Raw microarray data were downloaded from Gene Expression Omnibus. Data pre-treatment and differential analysis were conducted using packages in R. Functional and pathway enrichment analyses were performed using package GOs-tats. A protein-protein interaction (PPI) network was constructed using server STRING and Cytoscape. Known genes involved in pituitary adenomas (PAs), were obtained from the Comparative Toxicogenomics Database. A total of 604 differentially expressed genes (DEGs) were identifed between NFPAs and controls, including 177 up- and 427 down-regulated genes. Jak-STAT and p53 signaling pathways were significantly enriched by DEGs. The PPI network of DEGs was constructed, containing 99 up- and 288 down-regulated known disease genes (e.g. EGFR and ESR1) as well as 16 up- and 17 down-regulated potential novel NFPAs-related genes (e.g. COL4A5, LHX3, MSN, and GHSR). Genes like COL4A5, LHX3, MSN, and GHSR and pathways such as p53 signaling and Jak-STAT signaling, might participate in NFPA development. Although further validations are required, these findings might provide guidance for future basic and therapy researches. PMID:28289583

  12. Age-Specific Gene Expression Profiles of Rhesus Monkey Ovaries Detected by Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Hengxi Wei

    2015-01-01

    Full Text Available The biological function of human ovaries declines with age. To identify the potential molecular changes in ovarian aging, we performed genome-wide gene expression analysis by microarray of ovaries from young, middle-aged, and old rhesus monkeys. Microarray data was validated by quantitative real-time PCR. Results showed that a total of 503 (60 upregulated, 443 downregulated and 84 (downregulated genes were differentially expressed in old ovaries compared to young and middle-aged groups, respectively. No difference in gene expression was found between middle-aged and young groups. Differentially expressed genes were mainly enriched in cell and organelle, cellular and physiological process, binding, and catalytic activity. These genes were primarily associated with KEGG pathways of cell cycle, DNA replication and repair, oocyte meiosis and maturation, MAPK, TGF-beta, and p53 signaling pathway. Genes upregulated were involved in aging, defense response, oxidation reduction, and negative regulation of cellular process; genes downregulated have functions in reproduction, cell cycle, DNA and RNA process, macromolecular complex assembly, and positive regulation of macromolecule metabolic process. These findings show that monkey ovary undergoes substantial change in global transcription with age. Gene expression profiles are useful in understanding the mechanisms underlying ovarian aging and age-associated infertility in primates.

  13. A genome-wide 20 K citrus microarray for gene expression analysis

    OpenAIRE

    Gadea Jose; Forment Javier; Santiago Julia; Marques M Carmen; Juarez Jose; Mauri Nuria; Martinez-Godoy M Angeles

    2008-01-01

    Abstract Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-...

  14. A genome-wide 20 K citrus microarray for gene expression analysis

    OpenAIRE

    Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose

    2008-01-01

    Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA...

  15. A genome-wide 20 K citrus microarray for gene expression analysis

    OpenAIRE

    Martínez-Godoy, M. Ángeles; Mauri, Nuria; Juárez, José; Marqués, M. Carmen; Santiago, Julia; Forment, Javier; Gadea Vacas, José

    2008-01-01

    Background: Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genomewide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results: We have designed and constructed a publicly available ...

  16. Microarray analysis of genes associated with cell surface NIS protein levels in breast cancer

    Directory of Open Access Journals (Sweden)

    Richardson Andrea L

    2011-10-01

    Full Text Available Abstract Background Na+/I- symporter (NIS-mediated iodide uptake allows radioiodine therapy for thyroid cancer. NIS is also expressed in breast tumors, raising potential for radionuclide therapy of breast cancer. However, NIS expression in most breast cancers is low and may not be sufficient for radionuclide therapy. We aimed to identify biomarkers associated with NIS expression such that mechanisms underlying NIS modulation in human breast tumors may be elucidated. Methods Published oligonucleotide microarray data within the National Center for Biotechnology Information Gene Expression Omnibus database were analyzed to identify gene expression tightly correlated with NIS mRNA level among human breast tumors. NIS immunostaining was performed in a tissue microarray composed of 28 human breast tumors which had corresponding oligonucleotide microarray data available for each tumor such that gene expression associated with cell surface NIS protein level could be identified. Results and Discussion NIS mRNA levels do not vary among breast tumors or when compared to normal breast tissues when detected by Affymetrix oligonucleotide microarray platforms. Cell surface NIS protein levels are much more variable than their corresponding NIS mRNA levels. Despite a limited number of breast tumors examined, our analysis identified cysteinyl-tRNA synthetase as a biomarker that is highly associated with cell surface NIS protein levels in the ER-positive breast cancer subtype. Conclusions Further investigation on genes associated with cell surface NIS protein levels within each breast cancer molecular subtype may lead to novel targets for selectively increasing NIS expression/function in a subset of breast cancers patients.

  17. Gene expression profiling in human peripheral blood mononuclear cells using high-density filter-based cDNA microarrays.

    Science.gov (United States)

    Walker, J; Rigley, K

    2000-05-26

    Microarray technology has provided the ability to analyse the expression profiles for thousands of genes in parallel. The need for highly specialised equipment to use certain types of microarrays has restricted the application of this technology to a small number of dedicated laboratories. High-density filter-based cDNA microarrays provide a low-cost option for performing high-throughput gene expression analysis. We have used a model system in which filter-based cDNA microarrays representing over 4000 known human genes were used to monitor the kinetics of gene expression in human peripheral blood mononuclear cells (PBMCs) stimulated with phytohaemagluttinin (PHA). Using software-based cluster analysis, we identified 104 genes that altered in expression levels in response to PHA stimulation of PBMCs and showed that there was a considerable overlap between genes with similar temporal expression profiles and similar functional roles. Comparison of microarray quantitation with quantitative PCR showed almost identical expression profiles for a number of genes. Coupled with the fact that our findings are in agreement with a large number of independent observations, we conclude that the use of filter-based cDNA microarrays is a valid and accurate method for high-throughput gene expression profiling.

  18. Discovery of possible gene relationships through the application of self-organizing maps to DNA microarray databases.

    Directory of Open Access Journals (Sweden)

    Rocio Chavez-Alvarez

    Full Text Available DNA microarrays and cell cycle synchronization experiments have made possible the study of the mechanisms of cell cycle regulation of Saccharomyces cerevisiae by simultaneously monitoring the expression levels of thousands of genes at specific time points. On the other hand, pattern recognition techniques can contribute to the analysis of such massive measurements, providing a model of gene expression level evolution through the cell cycle process. In this paper, we propose the use of one of such techniques--an unsupervised artificial neural network called a Self-Organizing Map (SOM-which has been successfully applied to processes involving very noisy signals, classifying and organizing them, and assisting in the discovery of behavior patterns without requiring prior knowledge about the process under analysis. As a test bed for the use of SOMs in finding possible relationships among genes and their possible contribution in some biological processes, we selected 282 S. cerevisiae genes that have been shown through biological experiments to have an activity during the cell cycle. The expression level of these genes was analyzed in five of the most cited time series DNA microarray databases used in the study of the cell cycle of this organism. With the use of SOM, it was possible to find clusters of genes with similar behavior in the five databases along two cell cycles. This result suggested that some of these genes might be biologically related or might have a regulatory relationship, as was corroborated by comparing some of the clusters obtained with SOMs against a previously reported regulatory network that was generated using biological knowledge, such as protein-protein interactions, gene expression levels, metabolism dynamics, promoter binding, and modification, regulation and transport of proteins. The methodology described in this paper could be applied to the study of gene relationships of other biological processes in different organisms.

  19. Gametogenesis in the Pacific Oyster Crassostrea gigas: A Microarrays-Based Analysis Identifies Sex and Stage Specific Genes

    Science.gov (United States)

    Dheilly, Nolwenn M.; Lelong, Christophe; Huvet, Arnaud; Kellner, Kristell; Dubos, Marie-Pierre; Riviere, Guillaume; Boudry, Pierre; Favrel, Pascal

    2012-01-01

    Background The Pacific oyster Crassostrea gigas (Mollusca, Lophotrochozoa) is an alternative and irregular protandrous hermaphrodite: most individuals mature first as males and then change sex several times. Little is known about genetic and phenotypic basis of sex differentiation in oysters, and little more about the molecular pathways regulating reproduction. We have recently developed and validated a microarray containing 31,918 oligomers (Dheilly et al., 2011) representing the oyster transcriptome. The application of this microarray to the study of mollusk gametogenesis should provide a better understanding of the key factors involved in sex differentiation and the regulation of oyster reproduction. Methodology/Principal Findings Gene expression was studied in gonads of oysters cultured over a yearly reproductive cycle. Principal component analysis and hierarchical clustering showed a significant divergence in gene expression patterns of males and females coinciding with the start of gonial mitosis. ANOVA analysis of the data revealed 2,482 genes differentially expressed during the course of males and/or females gametogenesis. The expression of 434 genes could be localized in either germ cells or somatic cells of the gonad by comparing the transcriptome of female gonads to the transcriptome of stripped oocytes and somatic tissues. Analysis of the annotated genes revealed conserved molecular mechanisms between mollusks and mammals: genes involved in chromatin condensation, DNA replication and repair, mitosis and meiosis regulation, transcription, translation and apoptosis were expressed in both male and female gonads. Most interestingly, early expressed male-specific genes included bindin and a dpy-30 homolog and female-specific genes included foxL2, nanos homolog 3, a pancreatic lipase related protein, cd63 and vitellogenin. Further functional analyses are now required in order to investigate their role in sex differentiation in oysters. Conclusions

  20. Microarray analysis after RNA amplification can detect pronounced differences in gene expression using limma

    Directory of Open Access Journals (Sweden)

    Orengo Christine

    2006-10-01

    Full Text Available Abstract Background RNA amplification is necessary for profiling gene expression from small tissue samples. Previous studies have shown that the T7 based amplification techniques are reproducible but may distort the true abundance of targets. However, the consequences of such distortions on the ability to detect biological variation in expression have not been explored sufficiently to define the true extent of usability and limitations of such amplification techniques. Results We show that expression ratios are occasionally distorted by amplification using the Affymetrix small sample protocol version 2 due to a disproportional shift in intensity across biological samples. This occurs when a shift in one sample cannot be reflected in the other sample because the intensity would lie outside the dynamic range of the scanner. Interestingly, such distortions most commonly result in smaller ratios with the consequence of reducing the statistical significance of the ratios. This becomes more critical for less pronounced ratios where the evidence for differential expression is not strong. Indeed, statistical analysis by limma suggests that up to 87% of the genes with the largest and therefore most significant ratios (p -20 in the unamplified group have a p-value below 10e-20 in the amplified group. On the other hand, only 69% of the more moderate ratios (10e-20 -10 in the unamplified group have a p-value below 10e-10 in the amplified group. Our analysis also suggests that, overall, limma shows better overlap of genes found to be significant in the amplified and unamplified groups than the Z-scores statistics. Conclusion We conclude that microarray analysis of amplified samples performs best at detecting differences in gene expression, when these are large and when limma statistics are used.

  1. Suppression subtractive hybridization coupled with microarray analysis to examine differential expression of genes in virus infected cells

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    Munir Shirin

    2004-01-01

    Full Text Available High throughput detection of differential expression of genes is an efficient means of identifying genes and pathways that may play a role in biological systems under certain experimental conditions. There exist a variety of approaches that could be used to identify groups of genes that change in expression in response to a particular stimulus or environment. We here describe the application of suppression subtractive hybridization (SSH coupled with cDNA microarray analysis for isolation and identification of chicken transcripts that change in expression on infection of host cells with a paramyxovirus. SSH was used for initial isolation of differentially expressed transcripts, a large-scale validation of which was accomplished by microarray analysis. The data reveals a large group of regulated genes constituting many biochemical pathways that could serve as targets for future investigations to explore their role in paramyxovirus pathogenesis. The detailed methods described herein could be useful and adaptable to any biological system for studying changes in gene expression.

  2. Finding differentially expressed genes in two-channel DNA microarray datasets: how to increase reliability of data preprocessing.

    Science.gov (United States)

    Rotter, Ana; Hren, Matjaz; Baebler, Spela; Blejec, Andrej; Gruden, Kristina

    2008-09-01

    Due to the great variety of preprocessing tools in two-channel expression microarray data analysis it is difficult to choose the most appropriate one for a given experimental setup. In our study, two independent two-channel inhouse microarray experiments as well as a publicly available dataset were used to investigate the influence of the selection of preprocessing methods (background correction, normalization, and duplicate spots correlation calculation) on the discovery of differentially expressed genes. Here we are showing that both the list of differentially expressed genes and the expression values of selected genes depend significantly on the preprocessing approach applied. The choice of normalization method to be used had the highest impact on the results. We propose a simple but efficient approach to increase the reliability of obtained results, where two normalization methods which are theoretically distinct from one another are used on the same dataset. Then the intersection of results, that is, the lists of differentially expressed genes, is used in order to get a more accurate estimation of the genes that were de facto differentially expressed.

  3. Microarray analysis of differentially expressed genes regulating lipid metabolism during melanoma progression.

    Science.gov (United States)

    Sumantran, Venil N; Mishra, Pratik; Sudhakar, N

    2015-04-01

    A new hallmark of cancer involves acquisition of a lipogenic phenotype which promotes tumorigenesis. Little is known about lipid metabolism in melanomas. Therefore, we used BRB (Biometrics Research Branch) class comparison tool with multivariate analysis to identify differentially expressed genes in human cutaneous melanomas, compared with benign nevi and normal skin derived from the microarray dataset (GDS1375). The methods were validated by identifying known melanoma biomarkers (CITED1, FGFR2, PTPRF, LICAM, SPP1 and PHACTR1) in our results. Eighteen genes regulating metabolism of fatty acids, lipid second messengers and gangliosides were 2-9 fold upregulated in melanomas of GDS-1375. Out of the 18 genes, 13 were confirmed by KEGG pathway analysis and 10 were also significantly upregulated in human melanoma cell lines of NCI-60 Cell Miner database. Results showed that melanomas upregulated PPARGC1A transcription factor and its target genes regulating synthesis of fatty acids (SCD) and complex lipids (FABP3 and ACSL3). Melanoma also upregulated genes which prevented lipotoxicity (CPT2 and ACOT7) and regulated lipid second messengers, such as phosphatidic acid (AGPAT-4, PLD3) and inositol triphosphate (ITPKB, ITPR3). Genes for synthesis of pro-tumorigenic GM3 and GD3 gangliosides (UGCG, HEXA, ST3GAL5 and ST8SIA1) were also upregulated in melanoma. Overall, the microarray analysis of GDS-1375 dataset indicated that melanomas can become lipogenic by upregulating genes, leading to increase in fatty acid metabolism, metabolism of specific lipid second messengers, and ganglioside synthesis.

  4. Analysis of factorial time-course microarrays with application to a clinical study of burn injury.

    Science.gov (United States)

    Zhou, Baiyu; Xu, Weihong; Herndon, David; Tompkins, Ronald; Davis, Ronald; Xiao, Wenzhong; Wong, Wing Hung; Toner, Mehmet; Warren, H Shaw; Schoenfeld, David A; Rahme, Laurence; McDonald-Smith, Grace P; Hayden, Douglas; Mason, Philip; Fagan, Shawn; Yu, Yong-Ming; Cobb, J Perren; Remick, Daniel G; Mannick, John A; Lederer, James A; Gamelli, Richard L; Silver, Geoffrey M; West, Michael A; Shapiro, Michael B; Smith, Richard; Camp, David G; Qian, Weijun; Storey, John; Mindrinos, Michael; Tibshirani, Rob; Lowry, Stephen; Calvano, Steven; Chaudry, Irshad; West, Michael A; Cohen, Mitchell; Moore, Ernest E; Johnson, Jeffrey; Moldawer, Lyle L; Baker, Henry V; Efron, Philip A; Balis, Ulysses G J; Billiar, Timothy R; Ochoa, Juan B; Sperry, Jason L; Miller-Graziano, Carol L; De, Asit K; Bankey, Paul E; Finnerty, Celeste C; Jeschke, Marc G; Minei, Joseph P; Arnoldo, Brett D; Hunt, John L; Horton, Jureta; Cobb, J Perren; Brownstein, Bernard; Freeman, Bradley; Maier, Ronald V; Nathens, Avery B; Cuschieri, Joseph; Gibran, Nicole; Klein, Matthew; O'Keefe, Grant

    2010-06-01

    Time-course microarray experiments are capable of capturing dynamic gene expression profiles. It is important to study how these dynamic profiles depend on the multiple factors that characterize the experimental condition under which the time course is observed. Analytic methods are needed to simultaneously handle the time course and factorial structure in the data. We developed a method to evaluate factor effects by pooling information across the time course while accounting for multiple testing and nonnormality of the microarray data. The method effectively extracts gene-specific response features and models their dependency on the experimental factors. Both longitudinal and cross-sectional time-course data can be handled by our approach. The method was used to analyze the impact of age on the temporal gene response to burn injury in a large-scale clinical study. Our analysis reveals that 21% of the genes responsive to burn are age-specific, among which expressions of mitochondria and immunoglobulin genes are differentially perturbed in pediatric and adult patients by burn injury. These new findings in the body's response to burn injury between children and adults support further investigations of therapeutic options targeting specific age groups. The methodology proposed here has been implemented in R package "TANOVA" and submitted to the Comprehensive R Archive Network at http://www.r-project.org/. It is also available for download at http://gluegrant1.stanford.edu/TANOVA/.

  5. Investigating the effect of paralogs on microarray gene-set analysis

    LENUS (Irish Health Repository)

    Faure, Andre J

    2011-01-24

    Abstract Background In order to interpret the results obtained from a microarray experiment, researchers often shift focus from analysis of individual differentially expressed genes to analyses of sets of genes. These gene-set analysis (GSA) methods use previously accumulated biological knowledge to group genes into sets and then aim to rank these gene sets in a way that reflects their relative importance in the experimental situation in question. We suspect that the presence of paralogs affects the ability of GSA methods to accurately identify the most important sets of genes for subsequent research. Results We show that paralogs, which typically have high sequence identity and similar molecular functions, also exhibit high correlation in their expression patterns. We investigate this correlation as a potential confounding factor common to current GSA methods using Indygene http:\\/\\/www.cbio.uct.ac.za\\/indygene, a web tool that reduces a supplied list of genes so that it includes no pairwise paralogy relationships above a specified sequence similarity threshold. We use the tool to reanalyse previously published microarray datasets and determine the potential utility of accounting for the presence of paralogs. Conclusions The Indygene tool efficiently removes paralogy relationships from a given dataset and we found that such a reduction, performed prior to GSA, has the ability to generate significantly different results that often represent novel and plausible biological hypotheses. This was demonstrated for three different GSA approaches when applied to the reanalysis of previously published microarray datasets and suggests that the redundancy and non-independence of paralogs is an important consideration when dealing with GSA methodologies.

  6. A study of inter-lab and inter-platform agreement of DNA microarray data

    Directory of Open Access Journals (Sweden)

    Wilson Carole

    2005-05-01

    Full Text Available Abstract As gene expression profile data from DNA microarrays accumulate rapidly, there is a natural need to compare data across labs and platforms. Comparisons of microarray data can be quite challenging due to data complexity and variability. Different labs may adopt different technology platforms. One may ask about the degree of agreement we can expect from different labs and different platforms. To address this question, we conducted a study of inter-lab and inter-platform agreement of microarray data across three platforms and three labs. The statistical measures of consistency and agreement used in this paper are the Pearson correlation, intraclass correlation, kappa coefficients, and a measure of intra-transcript correlation. The three platforms used in the present paper were Affymetrix GeneChip, custom cDNA arrays, and custom oligo arrays. Using the within-platform variability as a benchmark, we found that these technology platforms exhibited an acceptable level of agreement, but the agreement between two technologies within the same lab was greater than that between two labs using the same technology. The consistency of replicates in each experiment varies from lab to lab. When there is high consistency among replicates, different technologies show good agreement within and across labs using the same RNA samples. On the other hand, the lab effect, especially when confounded with the RNA sample effect, plays a bigger role than the platform effect on data agreement.

  7. Identification of human prolactinoma related genes by DNA microarray

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    Lin Zhao

    2014-01-01

    Conclusion: Several DEGs between prolactinoma and normal samples were identified in our study and candidate agents such as LHB and FSHB may provide the groundwork for a targeted therapy approach for prolactinomas.

  8. Transcriptome-Wide High-Density Microarray Analysis Reveals Differential Gene Transcription in Periprosthetic Tissue From Hips With Chronic Periprosthetic Joint Infection vs Aseptic Loosening.

    Science.gov (United States)

    Omar, Mohamed; Klawonn, Frank; Brand, Stephan; Stiesch, Meike; Krettek, Christian; Eberhard, Jörg

    2017-01-01

    Differentiating between periprosthetic hip infection and aseptic hip prosthesis loosening can be challenging, especially in patients with chronic infections. This study used whole-genome microarray analysis to investigate the transcriptomes of periprosthetic hip tissues to identify genes that are differentially transcripted between chronic periprosthetic hip infection and aseptic hip prosthesis loosening. In this pilot study, a total of 24 patients with either chronic periprosthetic hip infection (n = 12) or aseptic hip prosthesis loosening (n = 12) were analyzed. Periprosthetic hip infection was diagnosed based on modified criteria of the Musculoskeletal Infection Society. To evaluate differences in gene transcription, whole-genome microarray analysis was performed on the mRNA of periprosthetic tissue. Microarray analysis revealed differential gene transcription in periprosthetic hip tissue affected by chronic hip infection vs aseptic hip prosthesis loosening. A total of 39 genes had area under the curve values greater than 0.9 for diagnosing chronic periprosthetic hip infection; 5 genes had annotations relevant to infection and metabolism. The 39 genes also included 7 genes that were differentially transcribed but that have no apparent connection to immune response processes plus 27 genes with unknown function. Differences in gene transcription profiles might represent novel diagnostic targets that can be used to differentiate between chronic periprosthetic hip infections and aseptic hip prosthesis loosening. Secondary metabolites of differentially transcripted genes might serve as easily accessible markers for detecting chronic periprosthetic joint infection in future. Copyright © 2016 Elsevier Inc. All rights reserved.

  9. Microarray profiling of mononuclear peripheral blood cells identifies novel candidate genes related to chemoradiation response in rectal cancer.

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    Pablo Palma

    Full Text Available Preoperative chemoradiation significantly improves oncological outcome in locally advanced rectal cancer. However there is no effective method of predicting tumor response to chemoradiation in these patients. Peripheral blood mononuclear cells have emerged recently as pathology markers of cancer and other diseases, making possible their use as therapy predictors. Furthermore, the importance of the immune response in radiosensivity of solid organs led us to hypothesized that microarray gene expression profiling of peripheral blood mononuclear cells could identify patients with response to chemoradiation in rectal cancer. Thirty five 35 patients with locally advanced rectal cancer were recruited initially to perform the study. Peripheral blood samples were obtained before neaodjuvant treatment. RNA was extracted and purified to obtain cDNA and cRNA for hybridization of microarrays included in Human WG CodeLink bioarrays. Quantitative real time PCR was used to validate microarray experiment data. Results were correlated with pathological response, according to Mandard´s criteria and final UICC Stage (patients with tumor regression grade 1-2 and downstaging being defined as responders and patients with grade 3-5 and no downstaging as non-responders. Twenty seven out of 35 patients were finally included in the study. We performed a multiple t-test using Significance Analysis of Microarrays, to find those genes differing significantly in expression, between responders (n = 11 and non-responders (n = 16 to CRT. The differently expressed genes were: BC 035656.1, CIR, PRDM2, CAPG, FALZ, HLA-DPB2, NUPL2, and ZFP36. The measurement of FALZ (p = 0.029 gene expression level determined by qRT-PCR, showed statistically significant differences between the two groups. Gene expression profiling reveals novel genes in peripheral blood samples of mononuclear cells that could predict responders and non-responders to chemoradiation in patients with

  10. Statistical Analysis of Microarray Data with Replicated Spots: A Case Study with Synechococcus WH8102

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    E. V. Thomas

    2009-01-01

    Full Text Available Until recently microarray experiments often involved relatively few arrays with only a single representation of each gene on each array. A complete genome microarray with multiple spots per gene (spread out spatially across the array was developed in order to compare the gene expression of a marine cyanobacterium and a knockout mutant strain in a defined artificial seawater medium. Statistical methods were developed for analysis in the special situation of this case study where there is gene replication within an array and where relatively few arrays are used, which can be the case with current array technology. Due in part to the replication within an array, it was possible to detect very small changes in the levels of expression between the wild type and mutant strains. One interesting biological outcome of this experiment is the indication of the extent to which the phosphorus regulatory system of this cyanobacterium affects the expression of multiple genes beyond those strictly involved in phosphorus acquisition.

  11. Analysis of differentially expressed genes in placental tissues of preeclampsia patients using microarray combined with the Connectivity Map database.

    Science.gov (United States)

    Song, Y; Liu, J; Huang, S; Zhang, L

    2013-12-01

    Preeclampsia (PE), which affects 2-7% of human pregnancies, causes significant maternal and neonatal morbidity and mortality. To better understand the pathophysiology of PE, the gene expression profiles of placental tissue from 5 controls and 5 PE patients were assessed using microarray. A total of 224 transcripts were significantly differentially expressed (>2-fold change and q value <0.05, SAM software). Gene Ontology (GO) enrichment analysis indicated that genes involved in hypoxia and oxidative and reductive processes were significantly changed. Three differentially expressed genes (DEGs) involved in these biological processes were further verified by quantitative real-time PCR. Finally, the potential therapeutic agents for PE were explored via the Connectivity Map database. In conclusion, the data obtained in this study might provide clues to better understand the pathophysiology of PE and to identify potential therapeutic agents for PE patients. Copyright © 2013 Elsevier Ltd. All rights reserved.

  12. Microarray analysis of genes differentially expressed in placentas of pregnancy-induced hypertension patients

    Institute of Scientific and Technical Information of China (English)

    李东红; 黄飞; 郑维国; 姜锋; 高平

    2003-01-01

    Objective: To uncover new clue for the research of the etiology of pregnancy-induced hypertension (PIH) by testing the gene expression difference between preeclamptic placentas and normal ones. Methods: mRNA level of 4 PIH placentas were examined using 4000 feature cDNA microarray in comparison with the pooled control consisting of total RNA from 4 cases of PIH placentas after the control cDNA and experimental cDNA were labeled by cy3 and cy5 respectively. Results: Fifty-eight to 131 genes were found down or up-regulated in 4 runs of hybridization. Among the differentially expressed genes, 22 genes, including genes encoding secreted protein ADRP, CYR61, EPI and HIF2, had the concordance in at least 2 cases were up-regulated or down-regulated. Conclusion: cDNA microarray is a high throughput and time-saving method to monitor the altered gene expression and the result could provide interesting clue and strategy for the etiological research of PIH.

  13. Gene expression profiling of gastric cancer by microarray combined with laser capture microdissection

    Institute of Scientific and Technical Information of China (English)

    Ming-Shiang Wu; Yi-Shing Lin; Yu-Ting Chang; Chia-Tung Shun; Ming-Tsan Lin; Jaw-Town Lin

    2005-01-01

    AIM: To examine the gene expression profile of gastric cancer (GC) by combination of laser capture microdissection (LCM) and microarray and to correlate the profiling with histological subtypes. METHODS: Using LCM, pure cancer cells were procured from 45 cancerous tissues. After procurement of about 5 000 cells, total RNA was extracted and the quality of RNA was determined before further amplification and hybridization. One microgram of amplified RNA was converted to cDNA and hybridized to cDNA microarray. RESULTS: Among 45 cases, only 21 were qualified for their RNAs. A total of 62 arrays were performed. These included 42 arrays for cancer (21 cases with dyeswab duplication) and 20 arrays for non-tumorous cells (10 cases with dye-swab duplication) with universal reference. Analyzed data showed 504 genes were differentially expressed and could distinguish cancerous and non-cancerous groups with more than 99% accuracy. Of the 504 genes, trefoil factors 1, 2, and 3 were in the list and their expression patterns were consistent with previous reports. Immunohistochemical staining of trefoil factor 1 was also consistent with the array data. Analyses of the tumor group with these 504 genes showed that there were 3 subgroups of GC that did not correspond to any current classification system, including Lauren's classification. CONCLUSION: By using LCM, linear amplification of RNA, and cDNA microarray, we have identified a panel of genes that have the power to discriminate between GC and non-cancer groups. The new molecular classification and the identified novel genes in gastric carcinogenesis deserve further investigations to elucidate their dinicopathological significance.

  14. Cluster stability scores for microarray data in cancer studies

    Directory of Open Access Journals (Sweden)

    Ghosh Debashis

    2003-09-01

    Full Text Available Abstract Background A potential benefit of profiling of tissue samples using microarrays is the generation of molecular fingerprints that will define subtypes of disease. Hierarchical clustering has been the primary analytical tool used to define disease subtypes from microarray experiments in cancer settings. Assessing cluster reliability poses a major complication in analyzing output from clustering procedures. While most work has focused on estimating the number of clusters in a dataset, the question of stability of individual-level clusters has not been addressed. Results We address this problem by developing cluster stability scores using subsampling techniques. These scores exploit the redundancy in biologically discriminatory information on the chip. Our approach is generic and can be used with any clustering method. We propose procedures for calculating cluster stability scores for situations involving both known and unknown numbers of clusters. We also develop cluster-size adjusted stability scores. The method is illustrated by application to data three cancer studies; one involving childhood cancers, the second involving B-cell lymphoma, and the final is from a malignant melanoma study. Availability Code implementing the proposed analytic method can be obtained at the second author's website.

  15. Rapid Detection of rpoB Gene Mutations in Rif-resistant M.tuberculosis Isolates by Obligonucleotide Microarray

    Institute of Scientific and Technical Information of China (English)

    AI-HUA SUN; XING-LI FAN; LI-WEI LI; LI-FANG WANG; WEN-YING AN; JIE YAN

    2009-01-01

    Objective To detect the specific mutations in rpoB gene of Mycobacterium tuberculosis by oligonucleotide microarray.Methods Four wild-type and 8 mutant probes were used to detect rifampin resistant strains.Target DNA of M.tuberculosis was amplified by PCR,hybridized and scanned.Direct sequencing was performed to verify the results of oligonuclcotide microarray.Results of the 102 rifampin-resistant strains 98 (96.1%) had mutations in the rpoB genes. Conclusion Oligonucleotide microarray with mutation-specific probes is a reliable and useful tool for the rapid and accurate diagnosis of rifampin resistance in M.tuberculosis isolates.

  16. Intertwining threshold settings, biological data and database knowledge to optimize the selection of differentially expressed genes from microarray

    OpenAIRE

    Paul Chuchana; Philippe Holzmuller; Frederic Vezilier; David Berthier; Isabelle Chantal; Dany Severac; Jean Loup Lemesre; Gerard Cuny; Philippe Nirdé; Bruno Bucheton

    2010-01-01

    International audience; BACKGROUND: Many tools used to analyze microarrays in different conditions have been described. However, the integration of deregulated genes within coherent metabolic pathways is lacking. Currently no objective selection criterion based on biological functions exists to determine a threshold demonstrating that a gene is indeed differentially expressed. METHODOLOGY/PRINCIPAL FINDINGS: To improve transcriptomic analysis of microarrays, we propose a new statistical appro...

  17. Study of gene mutation in 21 deaf patients with DNA microarray%基因芯片法检测21例耳聋患者基因突变的研究

    Institute of Scientific and Technical Information of China (English)

    韩崇旭; 任传利; 李贵玲; 汪骅; 张素华; 孙艳; 关兵

    2012-01-01

    Objective To investigate the application of DNA microarray to the screening of deafness gene mutations. Methods Twenty one deaf patients aged from 8 to 18 years were extracted for peripheral blood. DNA microarray was applied to detecting mutations of 9 hot-spots in four most common pathologic genes, namely GJB2 (35delG, 176dell6, 235delC, 299delAT), GJB3 (C538T), SLC26A4 (IVS7-2A>G, A2168G) and mitochondrial 12S rRNA (A1SS5G, C1494T). Results SLC26A4 gene mutations were detected in 8 cases (38% ), including IVS7-2A > G heterozygous mutation in 7 and IVS7-2A >G and 2168A>G heterozygous mutation in one. Four cases (19% ) carried GJB2 gene mutations, including 176 del 16 heterozygous mutation (n = 1 ) , 299 delAT heterozygous mutation ( n = 1 ) , 176 del 16 and 235 del C heterozygous mutation ( n = 1 ) , and 235 del C homozygous mutation ( n = 1 ). Conclusion DNA microarray is a sensitive and specific method for screening sequence variation in deafness gene.%目的 探讨基因芯片在耳聋基因筛查中的应用价值.方法 对扬州市聋哑学校21例8~18岁的耳聋患者中4个耳聋相关基因上的9个热点突变进行检测,包括GJB2( 35 delG、176de116、235 delC及299 delAT)、GJB3 (C538T)、SLC26A4( IVS7-2A>G、A2168G)以及线粒体12S rRNA(A1555G、C1494T).结果 SLC26 A4突变阳性率为38% (8/21),其中IVS7-2A>G杂合突变7例,IVS7-2 A>G与A2168G杂合突变1例;GJB2突变阳性率为19% (4/21),其中176de116杂合突变1例,299 delAT杂合突变1例,176 del 16与235 del C杂合突变1例,235 del C纯合突变1例.结论 基因芯片是一种筛查耳聋基因的高效、经济、简便、灵敏及特异性方法.

  18. Microarray analysis of bone marrow lesions in osteoarthritis demonstrates upregulation of genes implicated in osteochondral turnover, neurogenesis and inflammation.

    Science.gov (United States)

    Kuttapitiya, Anasuya; Assi, Lena; Laing, Ken; Hing, Caroline; Mitchell, Philip; Whitley, Guy; Harrison, Abiola; Howe, Franklyn A; Ejindu, Vivian; Heron, Christine; Sofat, Nidhi

    2017-10-01

    Bone marrow lesions (BMLs) are well described in osteoarthritis (OA) using MRI and are associated with pain, but little is known about their pathological characteristics and gene expression. We evaluated BMLs using novel tissue analysis tools to gain a deeper understanding of their cellular and molecular expression. We recruited 98 participants, 72 with advanced OA requiring total knee replacement (TKR), 12 with mild OA and 14 non-OA controls. Participants were assessed for pain (using Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC)) and with a knee MRI (using MOAKS). Tissue was then harvested at TKR for BML analysis using histology and tissue microarray. The mean (SD) WOMAC pain scores were significantly increased in advanced OA 59.4 (21.3) and mild OA 30.9 (20.3) compared with controls 0.5 (1.28) (plesions, bone marrow volume was starkly reduced being replaced by dense fibrous connective tissue, new blood vessels, hyaline cartilage and fibrocartilage. Microarray comparing OA BML and normal bone found a significant difference in expression of 218 genes (p<0.05). The most upregulated genes included stathmin 2, thrombospondin 4, matrix metalloproteinase 13 and Wnt/Notch/catenin/chemokine signalling molecules that are known to constitute neuronal, osteogenic and chondrogenic pathways. Our study is the first to employ detailed histological analysis and microarray techniques to investigate knee OA BMLs. BMLs demonstrated areas of high metabolic activity expressing pain sensitisation, neuronal, extracellular matrix and proinflammatory signalling genes that may explain their strong association with pain. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  19. Growth hormone regulation of rat liver gene expression assessed by SSH and microarray.

    Science.gov (United States)

    Gardmo, Cissi; Swerdlow, Harold; Mode, Agneta

    2002-04-25

    The sexually dimorphic secretion of growth hormone (GH) that prevails in the rat leads to a sex-differentiated expression of GH target genes, particularly in the liver. We have used subtractive suppressive hybridization (SSH) to search for new target genes induced by the female-characteristic, near continuous, pattern of GH secretion. Microarrays and dot-blot hybridizations were used in an attempt to confirm differential ratios of expression of obtained SSH clones. Out of 173 unique SSH clones, 41 could be verified as differentially expressed. Among these, we identified 17 known genes not previously recognized as differentially regulated by the sex-specific GH pattern. Additional SSH clones may also represent genes subjected to sex-specific GH regulation since only transcripts abundantly expressed could be verified. Optimized analyses, specific for each gene, are required to fully characterize the degree of differential expression.

  20. Gene expression microarray data from human microvascular endothelial cells supplemented with a low concentration of niacin

    Directory of Open Access Journals (Sweden)

    Jennifer M. Hughes-Large

    2016-03-01

    Full Text Available The systemic lipid modifying drug, niacin, can directly improve human microvascular endothelial cell angiogenic function under lipotoxic conditions, possibly through activation of niacin receptors “Niacin receptor activation improves human microvascular endothelial cell angiogenic function during lipotoxicity” (Hughes-Large et al. 2014. Here we provide accompanying data collected using Affymetrix GeneChip microarrays to identify changes in gene expression in human microvascular endothelial cells treated with 10 μM niacin. Statistical analyses of robust multi-array average (RMA values revealed that only 16 genes exhibited greater than 1.3-fold differential expression. Of these 16, only 5 were identified protein coding genes, while 3 of the remaining 11 genes appeared to be small nuclear/nucleolar RNAs. Altered expression of EFCAB4B, NAP1L2, and OR13C8 was confirmed by real time quantitative PCR.

  1. Spatial and temporal gene expression differences in core and periinfarct areas in experimental stroke: a microarray analysis.

    Directory of Open Access Journals (Sweden)

    Jaime Ramos-Cejudo

    Full Text Available BACKGROUND: A large number of genes are regulated to promote brain repair following stroke. The thorough analysis of this process can help identify new markers and develop therapeutic strategies. This study analyzes gene expression following experimental stroke. METHODOLOGY/PRINCIPAL FINDINGS: A microarray study of gene expression in the core, periinfarct and contralateral cortex was performed in adult Sprague-Dawley rats (n = 60 after 24 hours (acute phase or 3 days (delayed stage of permanent middle cerebral artery (MCA occlusion. Independent qRT-PCR validation (n = 12 was performed for 22 of the genes. Functional data were evaluated by Ingenuity Pathway Analysis. The number of genes differentially expressed was 2,612 (24 h and 5,717 (3 d in the core; and 3,505 (24 h and 1,686 (3 d in the periinfarct area (logFC>|1|; adjP<0.05. Expression of many neurovascular unit development genes was altered at 24 h and 3 d including HES2, OLIG2, LINGO1 and NOGO-A; chemokines like CXCL1 and CXCL12, stress-response genes like HIF-1A, and trophic factors like BDNF or BMP4. Nearly half of the detected genes (43% had not been associated with stroke previously. CONCLUSIONS: This comprehensive study of gene regulation in the core and periinfarct areas at different times following permanent MCA occlusion provides new data that can be helpful in translational research.

  2. Analysis of gene expression patterns with cDNA micro-array during late stage of spermatogenesis in mice

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The differentiation process of round spermatids to spermatozoa during the late stage of spermatogenesis is called spermiogenesis. To explore spermiogenesis-related genes, cDNA microarray was used to study expression patterns of 1176 genes in pachytene spermatocytes, round spermatids and elongating spermatids of Balb/c mice. The results showed that 208 genes were detected in all the three cell types. Most of them were down-regulated from pachytene spermatocytes to round spermatids and elongating spermatids. However, up-regulation of 7 genes expression in round spermatids and 3 genes in elongating spermatids were found. Expression of 7 differentially expressed genes in cDNA arrays was further confirmed by semi-quantitative RT-PCR study. The RT-PCR results indicated that the expression of 6 genes was consistent with that in cDNA arrays, only one gene did not show differential expression by RT-PCR. These results may provide important clues for studying of expression, regulation, and function of spermiogenesis-related genes.

  3. Microarray analysis of E-box binding-related gene expression in young and replicatively senescent human fibroblasts.

    Science.gov (United States)

    Semov, Alexandre; Marcotte, Richard; Semova, Natalie; Ye, Xiangyun; Wang, Eugenia

    2002-03-01

    An E-box (CACGTG) designer microarray was developed to monitor a group of genes whose expressions share a particular regulatory mode. Sensitivity and specificity of microarray hybridization, as well as variability of microarray data, were evaluated. This designer microarray was used to generate expression profiles of E-box binding-related genes in WI-38 fibroblast cultures at three different growth states: low-passage replicating, low-passage contact-inhibited quiescent, and replicatively senescent. Microarray gene screening reveals that quiescent and senescent cells, in comparison with replicating ones, are characterized by downregulation of Pam, a protein associated with c-Myc, and upregulation of Mad family genes, Max dimerization proteins. Moreover, quiescence and senescence can be distinguished by increased expression of Irlb, c-Myc transcription factor, and Miz-1, c-Myc-interacting Zn finger protein 1, only in the former state. Senescence is characterized by downregulation of Id4, inhibitor of DNA binding 4, and Mitf, microphthalmia-associated transcription factor, in comparison with young replicating and quiescent states. Differential expression of genes detected by microarray hybridization was independently confirmed by reverse transcription polymerase chain reaction technique. Alterations in the expression of E-box-binding transcription factors and c-Myc-binding proteins demonstrate the importance of these genes in establishing the contact-inhibited quiescent or senescent phenotypes.

  4. Maize microarray annotation database

    Directory of Open Access Journals (Sweden)

    Berger Dave K

    2011-10-01

    Full Text Available Abstract Background Microarray technology has matured over the past fifteen years into a cost-effective solution with established data analysis protocols for global gene expression profiling. The Agilent-016047 maize 44 K microarray was custom-designed from EST sequences, but only reporter sequences with EST accession numbers are publicly available. The following information is lacking: (a reporter - gene model match, (b number of reporters per gene model, (c potential for cross hybridization, (d sense/antisense orientation of reporters, (e position of reporter on B73 genome sequence (for eQTL studies, and (f functional annotations of genes represented by reporters. To address this, we developed a strategy to annotate the Agilent-016047 maize microarray, and built a publicly accessible annotation database. Description Genomic annotation of the 42,034 reporters on the Agilent-016047 maize microarray was based on BLASTN results of the 60-mer reporter sequences and their corresponding ESTs against the maize B73 RefGen v2 "Working Gene Set" (WGS predicted transcripts and the genome sequence. The agreement between the EST, WGS transcript and gDNA BLASTN results were used to assign the reporters into six genomic annotation groups. These annotation groups were: (i "annotation by sense gene model" (23,668 reporters, (ii "annotation by antisense gene model" (4,330; (iii "annotation by gDNA" without a WGS transcript hit (1,549; (iv "annotation by EST", in which case the EST from which the reporter was designed, but not the reporter itself, has a WGS transcript hit (3,390; (v "ambiguous annotation" (2,608; and (vi "inconclusive annotation" (6,489. Functional annotations of reporters were obtained by BLASTX and Blast2GO analysis of corresponding WGS transcripts against GenBank. The annotations are available in the Maize Microarray Annotation Database http://MaizeArrayAnnot.bi.up.ac.za/, as well as through a GBrowse annotation file that can be uploaded to

  5. Microarray analysis of extracellular matrix genes expression in myocardium of mouse with Coxsackie virus B3 myocarditis

    Institute of Scientific and Technical Information of China (English)

    张召才; 李双杰; 杨英珍; 陈瑞珍; 葛均波; 陈灏珠

    2004-01-01

    Background Extracellular matrix (ECM) orchestrates cell behaviour including growth, death, apoptosis, adhesion, migration, and invasion by activating several signalling pathways. Certain components of ECM, such as integrins, may act as receptors or co-receptors of enterovirus. ECM-activated gene expressions in myocardium of viral heart disease including myocarditis and partial cardiomyopathy remain elusive. This study was to investigate the expression of ECM-activated genes in myocardium of mouse with viral myocarditis. Methods BALB/c mice were infected with Coxsackie virus B3 (CVB3) to establish an animal model of myocarditis. Uninfected mice were also prepared and served as controls. Specific mRNA expression pattern in myocarditic mouse heart was analysed by an in-house cDNA microarray containing 8192 genes. Overexpressed ECM genes were selected and subsequently confirmed by Northern blot analysis. Results Nine ECM genes were isolated, from the array of 8192 genes, as overexpressed genes in hearts of myocarditic mice in comparison with controls. Subsequent Northern blot analysis confirmed that four of the nine genes were highly expressed. Expression of these four genes, Fin15, Ilk, Lamr1 and ADAMTS-1, has not been reported previously to be induced by Coxsackie virus. Conclusion CVB3-induced myocarditis is associated with gene expression profiles of certain ECM components.

  6. Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

    Science.gov (United States)

    Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A

    2015-06-01

    Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification.

  7. An ensemble method for gene discovery based on DNA microarray data

    Institute of Scientific and Technical Information of China (English)

    2004-01-01

    The advent of DNA microarray technology has offered the promise of casting new insights onto deciphering secrets of life by monitoring activities of thousands of genes simultaneously.Current analyses of microarray data focus on precise classification of biological types,for example,tumor versus normal tissues.A further scientific challenging task is to extract disease-relevant genes from the bewildering amounts of raw data,which is one of the most critical themes in the post-genomic era,but it is generally ignored due to lack of an efficient approach.In this paper,we present a novel ensemble method for gene extraction that can be tailored to fulfill multiple biological tasks including(i)precise classification of biological types;(ii)disease gene mining; and(iii)target-driven gene networking.We also give a numerical application for(i)and(ii)using a public microarrary data set and set aside a separate paper to address(iii).

  8. SoFoCles: feature filtering for microarray classification based on gene ontology.

    Science.gov (United States)

    Papachristoudis, Georgios; Diplaris, Sotiris; Mitkas, Pericles A

    2010-02-01

    Marker gene selection has been an important research topic in the classification analysis of gene expression data. Current methods try to reduce the "curse of dimensionality" by using statistical intra-feature set calculations, or classifiers that are based on the given dataset. In this paper, we present SoFoCles, an interactive tool that enables semantic feature filtering in microarray classification problems with the use of external, well-defined knowledge retrieved from the Gene Ontology. The notion of semantic similarity is used to derive genes that are involved in the same biological path during the microarray experiment, by enriching a feature set that has been initially produced with legacy methods. Among its other functionalities, SoFoCles offers a large repository of semantic similarity methods that are used in order to derive feature sets and marker genes. The structure and functionality of the tool are discussed in detail, as well as its ability to improve classification accuracy. Through experimental evaluation, SoFoCles is shown to outperform other classification schemes in terms of classification accuracy in two real datasets using different semantic similarity computation approaches.

  9. Hepatic gene expression changes in pigs experimentally infected with the lung pathogen Actinobacillus pleuropneumoniae as analysed with an innate immunity focused microarray

    DEFF Research Database (Denmark)

    Skovgaard, Kerstin; Mortensen, Shila; Boye, Mette

    2010-01-01

    Knowledge on gene expression in the liver during respiratory infections is limited although it is well-established that this organ is an important site of synthesis of several systemic innate immune components as response to infections. In the present study, the early transcriptional hepatic...... response of genes associated with innate immune responses was studied in pigs 14–18 h after intranasal inoculation with Actinobacillus pleuropneumoniae, using innate immune focused microarrays and quantitative real-time PCR (qPCR). The microarray analysis of liver tissue established that 51 genes were......, transferrin and albumin which were down-regulated. Additional genes associated with innate immune responses were investigated using qPCR; genes encoding interleukin (IL)1, IL6, IL8, lipopolysaccharide binding protein, lactotransferrin, and PigMAP were up-regulated and interferon 1a, a1-acid glycoprotein...

  10. Microarray analysis of gender- and parasite-specific gene transcription in Strongyloides ratti

    NARCIS (Netherlands)

    Evans, Helen; Mello, Luciane V.; Fang, Yongxiang; Wit, Ernst; Thompson, Fiona J.; Viney, Mark E.; Paterson, Steve

    2008-01-01

    The molecular mechanisms by which parasitic nematodes reproduce and have adapted to life within a host are unclear. In the present study, microarray analysis was used to explore differential transcription among the different stages and sexes of Strongyloides ratti, a parasitic nematode of brown rats

  11. ANALYSIS OF GENES ASSOCIATED WITH LYMPHATIC METASTASIS IN PANCREATIC CARCINOMA USING cDNA MICROARRAY

    Institute of Scientific and Technical Information of China (English)

    谭志军; 胡先贵; 曹贵松; 唐岩

    2003-01-01

    Objective: To identify new markers for prediction of lymph node metastasis. Methods: cDNA probes were prepared by labeling mRNA from samples of four pancreatic carcinoma tissues with Cy5-dUTP and mRNA from adjacent normal tissues with Cy3-dUTP respectively through reverse transcription. The mixed probes of each sample were then hybridized with 4,096 cDNA arrays (4,000 unique human cDNA sequences), and the fluorescent signals were scanned by ScanArray 3000 scanner (General Scanning, Inc.). The values of Cy5-dUTP and Cy3-dUTP on each spot were analyzed and calculated by ImaGene 3.0 software (BioDiscovery, Inc.). Genes that differentially expresses in each cancerous tissue were sought out according to the standard that the absolute value of natural logarithm of the ratio of Cy5 to Cy3 is greater than 0.69, i. e., more than 2 times change of gene expression, and the signal value of either Cy3 and Cy5 need to be greater than 600. Then, the genes differently expressed in cancer with and without lymphatic metastasis were screened out for further analysis. Results: Among 2 samples with lymphatic metastasis and 2 samples without metastasis, 56 genes, which accounted for 1.40% of genes on the microarray slides, exhibited differentially expression in cancerous tissues with lymphatic metastasis. There were 32 over-expressed genes including 11 having been registered in Genebank, and 24 under-expressed genes including 3 in Genebank. Conclusion: Microarray analysis may provide invaluable information to identify specific gene expression profile of lymphatic metastasis in pancreatic cancer.

  12. Maize Gene Atlas Developed by RNA Sequencing and Comparative Evaluation of Transcriptomes Based on RNA Sequencing and Microarrays

    Science.gov (United States)

    Sekhon, Rajandeep S.; Briskine, Roman; Hirsch, Candice N.; Myers, Chad L.; Springer, Nathan M.; Buell, C. Robin; de Leon, Natalia; Kaeppler, Shawn M.

    2013-01-01

    Transcriptome analysis is a valuable tool for identification and characterization of genes and pathways underlying plant growth and development. We previously published a microarray-based maize gene atlas from the analysis of 60 unique spatially and temporally separated tissues from 11 maize organs [1]. To enhance the coverage and resolution of the maize gene atlas, we have analyzed 18 selected tissues representing five organs using RNA sequencing (RNA-Seq). For a direct comparison of the two methodologies, the same RNA samples originally used for our microarray-based atlas were evaluated using RNA-Seq. Both technologies produced similar transcriptome profiles as evident from high Pearson's correlation statistics ranging from 0.70 to 0.83, and from nearly identical clustering of the tissues. RNA-Seq provided enhanced coverage of the transcriptome, with 82.1% of the filtered maize genes detected as expressed in at least one tissue by RNA-Seq compared to only 56.5% detected by microarrays. Further, from the set of 465 maize genes that have been historically well characterized by mutant analysis, 427 show significant expression in at least one tissue by RNA-Seq compared to 390 by microarray analysis. RNA-Seq provided higher resolution for identifying tissue-specific expression as well as for distinguishing the expression profiles of closely related paralogs as compared to microarray-derived profiles. Co-expression analysis derived from the microarray and RNA-Seq data revealed that broadly similar networks result from both platforms, and that co-expression estimates are stable even when constructed from mixed data including both RNA-Seq and microarray expression data. The RNA-Seq information provides a useful complement to the microarray-based maize gene atlas and helps to further understand the dynamics of transcription during maize development. PMID:23637782

  13. Optimization of candidate-gene SNP-genotyping by flexible oligonucleotide microarrays; analyzing variations in immune regulator genes of hay-fever samples

    Directory of Open Access Journals (Sweden)

    Beier Markus

    2007-08-01

    Full Text Available Abstract Background Genetic variants in immune regulator genes have been associated with numerous diseases, including allergies and cancer. Increasing evidence suggests a substantially elevated disease risk in individuals who carry a combination of disease-relevant single nucleotide polymorphisms (SNPs. For the genotyping of immune regulator genes, such as cytokines, chemokines and transcription factors, an oligonucleotide microarray for the analysis of 99 relevant SNPs was established. Since the microarray design was based on a platform that permits flexible in situ oligonucleotide synthesis, a set of optimally performing probes could be defined by a selection approach that combined computational and experimental aspects. Results While the in silico process eliminated 9% of the initial probe set, which had been picked purely on the basis of potential association with disease, the subsequent experimental validation excluded more than twice as many. The performance of the optimized microarray was demonstrated in a pilot study. The genotypes of 19 hay-fever patients (aged 40–44 with high IgE levels against inhalant antigens were compared to the results obtained with 19 age- and sex-matched controls. For several variants, allele-frequency differences of more than 10% were identified. Conclusion Based on the ability to improve empirically a chip design, the application of candidate-SNP typing represents a viable approach in the context of molecular epidemiological studies.

  14. DNA microarray revealed and RNAi plants confirmed key genes conferring low Cd accumulation in barley grains

    DEFF Research Database (Denmark)

    Sun, Hongyan; Chen, Zhong-Hua; Chen, Fei

    2015-01-01

    accumulation and tolerance between the two contrasting barley genotypes: W6nk2 (a low-grain-Cd-accumulating and Cd-sensitive genotype) and Zhenong8 (a high-grain-Cd-accumulating and tolerant genotype). A DNA microarray analysis detected large-scale changes of gene expression in response to Cd stress...... with a substantial difference between the two genotypes. Cd stress led to higher expression of genes involved in transport, carbohydrate metabolism and signal transduction in the low-grain-Cd-accumulating genotype. Novel transporter genes such as zinc transporter genes were identified as being associated with low Cd......Background Understanding the mechanism of low Cd accumulation in crops is crucial for sustainable safe food production in Cd-contaminated soils. Results Confocal microscopy, atomic absorption spectrometry, gas exchange and chlorophyll fluorescence analyses revealed a distinct difference in Cd...

  15. Microarray Analysis on Gene Regulation by Estrogen, Progesterone and Tamoxifen in Human Endometrial Stromal Cells

    Directory of Open Access Journals (Sweden)

    Chun-E Ren

    2015-03-01

    Full Text Available Epithelial stromal cells represent a major cellular component of human uterine endometrium that is subject to tight hormonal regulation. Through cell-cell contacts and/or paracrine mechanisms, stromal cells play a significant role in the malignant transformation of epithelial cells. We isolated stromal cells from normal human endometrium and investigated the morphological and transcriptional changes induced by estrogen, progesterone and tamoxifen. We demonstrated that stromal cells express appreciable levels of estrogen and progesterone receptors and undergo different morphological changes upon hormonal stimulation. Microarray analysis indicated that both estrogen and progesterone induced dramatic alterations in a variety of genes associated with cell structure, transcription, cell cycle, and signaling. However, divergent patterns of changes, and in some genes opposite effects, were observed for the two hormones. A large number of genes are identified as novel targets for hormonal regulation. These hormone-responsive genes may be involved in normal uterine function and the development of endometrial malignancies.

  16. Microarray Analysis on Gene Regulation by Estrogen, Progesterone and Tamoxifen in Human Endometrial Stromal Cells

    Science.gov (United States)

    Ren, Chun-E; Zhu, Xueqiong; Li, Jinping; Lyle, Christian; Dowdy, Sean; Podratz, Karl C.; Byck, David; Chen, Hai-Bin; Jiang, Shi-Wen

    2015-01-01

    Epithelial stromal cells represent a major cellular component of human uterine endometrium that is subject to tight hormonal regulation. Through cell-cell contacts and/or paracrine mechanisms, stromal cells play a significant role in the malignant transformation of epithelial cells. We isolated stromal cells from normal human endometrium and investigated the morphological and transcriptional changes induced by estrogen, progesterone and tamoxifen. We demonstrated that stromal cells express appreciable levels of estrogen and progesterone receptors and undergo different morphological changes upon hormonal stimulation. Microarray analysis indicated that both estrogen and progesterone induced dramatic alterations in a variety of genes associated with cell structure, transcription, cell cycle, and signaling. However, divergent patterns of changes, and in some genes opposite effects, were observed for the two hormones. A large number of genes are identified as novel targets for hormonal regulation. These hormone-responsive genes may be involved in normal uterine function and the development of endometrial malignancies. PMID:25782154

  17. OpWise: Operons aid the identification of differentially expressed genes in bacterial microarray experiments

    Directory of Open Access Journals (Sweden)

    Arkin Adam P

    2006-01-01

    Full Text Available Abstract Background Differentially expressed genes are typically identified by analyzing the variation between replicate measurements. These procedures implicitly assume that there are no systematic errors in the data even though several sources of systematic error are known. Results OpWise estimates the amount of systematic error in bacterial microarray data by assuming that genes in the same operon have matching expression patterns. OpWise then performs a Bayesian analysis of a linear model to estimate significance. In simulations, OpWise corrects for systematic error and is robust to deviations from its assumptions. In several bacterial data sets, significant amounts of systematic error are present, and replicate-based approaches overstate the confidence of the changers dramatically, while OpWise does not. Finally, OpWise can identify additional changers by assigning genes higher confidence if they are consistent with other genes in the same operon. Conclusion Although microarray data can contain large amounts of systematic error, operons provide an external standard and allow for reasonable estimates of significance. OpWise is available at http://microbesonline.org/OpWise.

  18. cDNA microarray reveals the alterations of cytoskeleton-related genes in osteoblast under high magneto-gravitational environment

    Institute of Scientific and Technical Information of China (English)

    Airong Qian; Shengmeng Di; Xiang Gao; Wei Zhang; Zongcheng Tian; Jingbao Li; Lifang Hu; Pengfei Yang; Dachuan Yin; Peng Shang

    2009-01-01

    The diamagnetic levitation as a novel ground-based model for simulating a reduced gravity environment has been widely applied in many fields.In this study,a special designed superconducting magnet,which can produce three apparent gravity levels (0,1,and 2 g),namely high magneto-gravitational environment (HMGE),was used to simulate space gravity environment.The effects of HMGE on osteoblast gene expression profile were investigated by microarray.Genes sensitive to diamagnetic levitation environment (0 g),gravity changes,and high magnetic field changes were sorted on the basis of typical cell func-tions.Cytoskeleton,as an intracellular load-bearing struc-ture,plays an important role in gravity perception.Therefore,13 cytoskeleton-related genes were chosen according to the results of microarray analysis,and the expressions of these genes were found to be altered under HMGE by real-time PCR.Based on the PCR results,the expressions of WASF2 (WAS protein family,member 2),WIPFI (WAS/WASL interacting protein family,member 1),paxillin:and talin 1 were further identified by western blot assay.Results indicated that WASF2 and WIPF1 were more sensitive to altered gravity levels,and talin 1 and paxillin were sensitive to both magnetic field and gravity changes.Our findings demonstrated that HMGE can affect osteoblast gene expression profile and cytoskele-ton-related genes expression.The identification of mechanosensitive genes may enhance our understandings to the mechanism of bone loss induced by microgravity and may provide some potential targets for preventing and treating bone loss or osteoporosis.

  19. Determination of the differentially expressed genes in microarray experiments using local FDR

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    Daudin J-J

    2004-09-01

    Full Text Available Abstract Background Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expected proportion of false positive genes in a set of genes, called the False Discovery Rate (FDR, has been proposed to measure the statistical significance of this set. Various procedures exist for controlling the FDR. However the threshold (generally 5% is arbitrary and a specific measure associated with each gene would be worthwhile. Results Using process intensity estimation methods, we define and give estimates of the local FDR, which may be considered as the probability for a gene to be a false positive. After a global assessment rule controlling the false positive error, the local FDR is a valuable guideline for deciding wether a gene is differentially expressed. The interest of the method is illustrated on three well known data sets. A R routine for computing local FDR estimates from p-values is available at http://www.inapg.fr/ens_rech/mathinfo/recherche/mathematique/outil.html. Conclusions The local FDR associated with each gene measures the probability that it is a false positive. It gives the opportunity to compute the FDR of any given group of clones (of the same gene or genes pertaining to the same regulation network or the same chromosomic region.

  20. Improving signal intensities for genes with low-expression on oligonucleotide microarrays

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    Hu Limei

    2004-06-01

    Full Text Available Abstract Background DNA microarrays using long oligonucleotide probes are widely used to evaluate gene expression in biological samples. These oligonucleotides are pre-synthesized and sequence-optimized to represent specific genes with minimal cross-hybridization to homologous genes. Probe length and concentration are critical factors for signal sensitivity, particularly when genes with various expression levels are being tested. We evaluated the effects of oligonucleotide probe length and concentration on signal intensity measurements of the expression levels of genes in a target sample. Results Selected genes of various expression levels in a single cell line were hybridized to oligonucleotide arrays of four lengths and four concentrations of probes to determine how these critical parameters affected the intensity of the signal representing their expression. We found that oligonucleotides of longer length significantly increased the signals of genes with low-expression in the target. High-expressing gene signals were also boosted but to a lesser degree. Increasing the probe concentration, however, did not linearly increase the signal intensity for either low- or high-expressing genes. Conclusions We conclude that the longer the oligonuclotide probe the better the signal intensities of low expressing genes on oligonucleotide arrays.

  1. Design of a combinatorial dna microarray for protein-dnainteraction studies

    Energy Technology Data Exchange (ETDEWEB)

    Mintseris, Julian; Eisen, Michael B.

    2006-07-07

    Background: Discovery of precise specificity oftranscription factors is an important step on the way to understandingthe complex mechanisms of gene regulation in eukaryotes. Recently,doublestranded protein-binding microarrays were developed as apotentially scalable approach to tackle transcription factor binding siteidentification. Results: Here we present an algorithmic approach toexperimental design of a microarray that allows for testing fullspecificity of a transcription factor binding to all possible DNA bindingsites of a given length, with optimally efficient use of the array. Thisdesign is universal, works for any factor that binds a sequence motif andis not species-specific. Furthermore, simulation results show that dataproduced with the designed arrays is easier to analyze and would resultin more precise identification of binding sites. Conclusion: In thisstudy, we present a design of a double stranded DNA microarray forprotein-DNA interaction studies and show that our algorithm allowsoptimally efficient use of the arrays for this purpose. We believe such adesign will prove useful for transcription factor binding siteidentification and other biological problems.

  2. Global gene expression of a murein (Braun) lipoprotein mutant of Salmonella enterica serovar Typhimurium by microarray analysis.

    Science.gov (United States)

    Fadl, A A; Galindo, C L; Sha, J; Klimpel, G R; Popov, V L; Chopra, A K

    2006-06-01

    Braun/murein lipoprotein (Lpp) is one of the major outer membrane components of gram-negative enteric bacteria involved in inflammatory responses and septic shock. In previous studies, we reported that two copies of the lipoprotein (lpp) gene (designated as lppA and lppB) existed on the chromosome of Salmonella enterica serovar Typhimurium. Deletion of both lppA and lppB genes rendered Salmonella defective in invasion, motility, induction of cytotoxicity, and production of inflammatory cytokines/chemokines. The lppAB double-knockout (DKO) mutant was attenuated in mice, and animals immunized with this mutant were protected against subsequent challenge with lethal doses of wild-type (wt) S. Typhimurium. To better understand how deletion of the lpp gene might affect Salmonella virulence, we performed global transcriptional profiling of the genes in the wt and the lppAB DKO mutant of S. Typhimurium using microarrays. Our data revealed alterations in the expression of flagellar genes, invasion-associated type III secretion system genes, and transcriptional virulence gene regulators in the lppAB DKO mutant compared to wt S. Typhimurium. These data correlated with the lppAB DKO mutant phenotype and provided possible mechanism(s) of Lpp-associated attenuation in S. Typhimurium. Although these studies were performed in in vitro grown bacteria, our future research will be targeted at global transcriptional profiling of the genes in in vivo grown wt S. Typhimurium and its Lpp mutant.

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

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    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. Comparative genomic profiling of Dutch clinical Bordetella pertussis isolates using DNA microarrays: Identification of genes absent from epidemic strains

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    van Gent Marjolein

    2008-06-01

    Full Text Available Abstract Background Whooping cough caused by Bordetella pertussis in humans, is re-emerging in many countries despite vaccination. Several studies have shown that significant shifts have occurred in the B. pertussis population resulting in antigenic divergence between vaccine strains and circulating strains and suggesting pathogen adaptation. In the Netherlands, the resurgence of pertussis is associated with the rise of B. pertussis strains with an altered promoter region for pertussis toxin (ptxP3. Results We used Multi-Locus Sequence Typing (MLST, Multiple-Locus Variable Number of Tandem Repeat Analysis (MLVA and microarray-based comparative genomic hybridization (CGH to characterize the ptxP3 strains associated with the Dutch epidemic. For CGH analysis, we developed an oligonucleotide (70-mers microarray consisting of 3,581 oligonucleotides representing 94% of the gene repertoire of the B. pertussis strain Tohama I. Nine different MLST profiles and 38 different MLVA types were found in the period 1993 to 2004. Forty-three Dutch clinical isolates were analyzed with CGH, 98 genes were found to be absent in at least one of the B. pertussis strains tested, these genes were clustered in 8 distinct regions of difference. Conclusion The presented MLST, MLVA and CGH-analysis identified distinctive characteristics of ptxP3 B. pertussis strains -the most prominent of which was a genomic deletion removing about 23,000 bp. We propose a model for the emergence of ptxP3 strains.

  5. 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.

  6. Microarray profile of gene expression during osteoclast differentiation in modelled microgravity.

    Science.gov (United States)

    Sambandam, Yuvaraj; Blanchard, Jeremy J; Daughtridge, Giffin; Kolb, Robert J; Shanmugarajan, Srinivasan; Pandruvada, Subramanya N M; Bateman, Ted A; Reddy, Sakamuri V

    2010-12-01

    Microgravity (µXg) leads to a 10-15% loss of bone mass in astronauts during space flight. Osteoclast (OCL) is the multinucleated bone-resorbing cell. In this study, we used the NASA developed ground-based rotating wall vessel bioreactor (RWV), rotary cell culture system (RCCS) to simulate µXg conditions and demonstrated a significant increase (2-fold) in osteoclastogenesis compared to normal gravity control (Xg). Gene expression profiling of RAW 264.7 OCL progenitor cells in modelled µXg by Agilent microarray analysis revealed significantly increased expression of critical molecules such as cytokines/growth factors, proteases and signalling proteins, which play an important role in enhanced OCL differentiation/function. Transcription factors such as c-Jun, MITF and CREB implicated in OCL differentiation are upregulated; however no significant change in the levels of NFATc1 expression in preosteoclast cells subjected to modelled µXg. We also identified high-level expression of calcium-binding protein, S100A8 (calcium-binding protein molecule A8/calgranulin A) in preosteoclast cells under µXg. Furthermore, modelled µXg stimulated RAW 264.7 cells showed elevated cytosolic calcium (Ca(2+)) levels/oscillations compared to Xg cells. siRNA knock-down of S100A8 expression in RAW 264.7 cells resulted in a significant decrease in modelled µXg stimulated OCL differentiation. We also identified elevated levels of phospho-CREB in preosteoclast cells subjected to modelled µXg compared to Xg. Thus, modelled µXg regulated gene expression profiling in preosteoclast cells provide new insights into molecular mechanisms and therapeutic targets of enhanced OCL differentiation/activation to prevent bone loss and fracture risk in astronauts during space flight missions.

  7. The Sterolgene v0 cDNA microarray: a systemic approach to studies of cholesterol homeostasis and drug metabolism

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    Aggerbeck Lawrence P

    2008-02-01

    Full Text Available Abstract Background Cholesterol homeostasis and xenobiotic metabolism are complex biological processes, which are difficult to study with traditional methods. Deciphering complex regulation and response of these two processes to different factors is crucial also for understanding of disease development. Systems biology tools as are microarrays can importantly contribute to this knowledge and can also discover novel interactions between the two processes. Results We have developed a low density Sterolgene v0 cDNA microarray dedicated to studies of cholesterol homeostasis and drug metabolism in the mouse. To illustrate its performance, we have analyzed mouse liver samples from studies focused on regulation of cholesterol homeostasis and drug metabolism by diet, drugs and inflammation. We observed down-regulation of cholesterol biosynthesis during fasting and high-cholesterol diet and subsequent up-regulation by inflammation. Drug metabolism was down-regulated by fasting and inflammation, but up-regulated by phenobarbital treatment and high-cholesterol diet. Additionally, the performance of the Sterolgene v0 was compared to the two commercial high density microarray platforms: the Agilent cDNA (G4104A and the Affymetrix MOE430A GeneChip. We hybridized identical RNA samples to the commercial microarrays and showed that the performance of Sterolgene is comparable to commercial arrays in terms of detection of changes in cholesterol homeostasis and drug metabolism. Conclusion Using the Sterolgene v0 microarray we were able to detect important changes in cholesterol homeostasis and drug metabolism caused by diet, drugs and inflammation. Together with its next generations the Sterolgene microarrays represent original and dedicated tools enabling focused and cost effective studies of cholesterol homeostasis and drug metabolism. These microarrays have the potential of being further developed into screening or diagnostic tools.

  8. Microarray-based method for detecting methylation changes of p16Ink4a gene 5'-CpG islands in gastric carcinomas

    Institute of Scientific and Technical Information of China (English)

    Peng Hou; Jia-Yao Shen; Mei-Ju Ji; Nong-Yue He; Zu-Hong Lu

    2004-01-01

    AIM: Aberrant DNA methylation of CpG site is among the earliest and most frequent alterations in cancer. Several studies suggest that aberrant methylation of the CpG sites of the tumor suppressor gene is closely associated with carcinogenesis. However, large-scale analysis of candidate genes has so far been hampered by the lack of highthroughput approach for analyzing DNA methylation. The aim of this study was to describe a microarray-based method for detecting changes of DNA methylation in cancer.METHODS: This method used bisulfite-modified DNA as a template for PCR amplification, resulting in conversion of unmethylated cytosine, but not methylated cytosine, into thymine within CpG islands of interest. Therefore, the amplified product might contain a pool of DNA fragments with altered nucleotide sequences due to differential methylation status.Nine sets of oligonucleotide probes were designed to fabricate a DNA microarray to detect the methylation changes of p16 gene CpG islands in gastric carcinomas. The results were further validated by methylation-specific PCR (MSP).RESULTS: The experimental results showed that the microarray assay could successfully detect methylation changes of p16 gene in 18 gastric tumor samples. Moreover,it could also potentially increase the frequency of detecting p16 methylation from tumor samples than MSP.CONCLUSION: Microarray assay could be applied as a useful tool for mapping methylation changes in multiple CpG loci and for generating epigenetic profiles in cancer.

  9. Phylogenetic modeling of heterogeneous gene-expression microarray data from cancerous specimens.

    Science.gov (United States)

    Abu-Asab, Mones S; Chaouchi, Mohamed; Amri, Hakima

    2008-09-01

    The qualitative dimension of gene expression data and its heterogeneous nature in cancerous specimens can be accounted for by phylogenetic modeling that incorporates the directionality of altered gene expressions, complex patterns of expressions among a group of specimens, and data-based rather than specimen-based gene linkage. Our phylogenetic modeling approach is a double algorithmic technique that includes polarity assessment that brings out the qualitative value of the data, followed by maximum parsimony analysis that is most suitable for the data heterogeneity of cancer gene expression. We demonstrate that polarity assessment of expression values into derived and ancestral states, via outgroup comparison, reduces experimental noise; reveals dichotomously expressed asynchronous genes; and allows data pooling as well as comparability of intra- and interplatforms. Parsimony phylogenetic analysis of the polarized values produces a multidimensional classification of specimens into clades that reveal shared derived gene expressions (the synapomorphies); provides better assessment of ontogenic pathways and phyletic relatedness of specimens; efficiently utilizes dichotomously expressed genes; produces highly predictive class recognition; illustrates gene linkage and multiple developmental pathways; provides higher concordance between gene lists; and projects the direction of change among specimens. Further implication of this phylogenetic approach is that it may transform microarray into diagnostic, prognostic, and predictive tool.

  10. Analysis of gene expression profile of pancreatic carcinoma using CDNA microarray

    Institute of Scientific and Technical Information of China (English)

    ZhiJun Tan; Xian-Gui Hu; Gui-Song Cao; Yan Tang

    2003-01-01

    AIM: To identify new diagnostic markers and drug targets,the gene expression profiles of pancreatic cancer were compared with that of adjacent normal tissues utilizing cDNA microarray analysis.METHODS: cDNA probes were prepared by labeling mRNA from samples of six pancreatic carcinoma tissues with Cy5dUTP and mRNA from adjacent normal tissues with Cy3dUTP respectively through reverse transcription. The mixed probes of each sample were then hybridized with 12 800cDNA arrays (12 648 unique human cDNA sequences), and the fluorescent signals were scanned by ScanArray 3 000scanner (General Scanning, Inc.). The values of CyS-dUTP and Cy3-dUTP on each spot were analyzed and calculated by ImaGene 3.0 software (BioDiscovery, Inc.). Differentially expressed genes were screened according to the criterion that the absolute value of natural logarithm of the ratio of Cy5-dUTP to Cy3-dUTP was greater-than 0.69.RESETS: Among 6 samples investigated, 301 genes, which accounted for 2.38% of genes on the microarry slides,exhibited differentially expression at least in 5. There were 166 over-expressed genes including 136 having been registered in Genebank, and 135 under-expressed genes including 79 in Genebank in cancerous tissues.CONCLUSION: Microarray analysis may provide invaluable information on disease pathology, progression, resistance to treatment, and response to cellular microenvironments of pancreatic carcinoma and ultimately may lead to improving early diagnosis and discovering innovative therapeutic approaches for cancer.

  11. Using microarrays to study the microenvironment in tumor biology: The crucial role of statistics

    OpenAIRE

    2008-01-01

    Microarrays represent a potentially powerful tool for better understanding the role of the microenvironment on tumor biology. To make the best use of microarray data and avoid incorrect or unsubstantiated conclusions, care must be taken in the statistical analysis. To illustrate the statistical issues involved we discuss three microarray studies related to the microenvironment and tumor biology involving: (i) prostatic stroma cells in cancer and non-cancer tissues; (ii) breast stroma and epit...

  12. Classification of Non-Small Cell Lung Cancer Using Significance Analysis of Microarray-Gene Set Reduction Algorithm

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    Lei Zhang

    2016-01-01

    Full Text Available Among non-small cell lung cancer (NSCLC, adenocarcinoma (AC, and squamous cell carcinoma (SCC are two major histology subtypes, accounting for roughly 40% and 30% of all lung cancer cases, respectively. Since AC and SCC differ in their cell of origin, location within the lung, and growth pattern, they are considered as distinct diseases. Gene expression signatures have been demonstrated to be an effective tool for distinguishing AC and SCC. Gene set analysis is regarded as irrelevant to the identification of gene expression signatures. Nevertheless, we found that one specific gene set analysis method, significance analysis of microarray-gene set reduction (SAMGSR, can be adopted directly to select relevant features and to construct gene expression signatures. In this study, we applied SAMGSR to a NSCLC gene expression dataset. When compared with several novel feature selection algorithms, for example, LASSO, SAMGSR has equivalent or better performance in terms of predictive ability and model parsimony. Therefore, SAMGSR is a feature selection algorithm, indeed. Additionally, we applied SAMGSR to AC and SCC subtypes separately to discriminate their respective stages, that is, stage II versus stage I. Few overlaps between these two resulting gene signatures illustrate that AC and SCC are technically distinct diseases. Therefore, stratified analyses on subtypes are recommended when diagnostic or prognostic signatures of these two NSCLC subtypes are constructed.

  13. Classification of Non-Small Cell Lung Cancer Using Significance Analysis of Microarray-Gene Set Reduction Algorithm.

    Science.gov (United States)

    Zhang, Lei; Wang, Linlin; Du, Bochuan; Wang, Tianjiao; Tian, Pu; Tian, Suyan

    2016-01-01

    Among non-small cell lung cancer (NSCLC), adenocarcinoma (AC), and squamous cell carcinoma (SCC) are two major histology subtypes, accounting for roughly 40% and 30% of all lung cancer cases, respectively. Since AC and SCC differ in their cell of origin, location within the lung, and growth pattern, they are considered as distinct diseases. Gene expression signatures have been demonstrated to be an effective tool for distinguishing AC and SCC. Gene set analysis is regarded as irrelevant to the identification of gene expression signatures. Nevertheless, we found that one specific gene set analysis method, significance analysis of microarray-gene set reduction (SAMGSR), can be adopted directly to select relevant features and to construct gene expression signatures. In this study, we applied SAMGSR to a NSCLC gene expression dataset. When compared with several novel feature selection algorithms, for example, LASSO, SAMGSR has equivalent or better performance in terms of predictive ability and model parsimony. Therefore, SAMGSR is a feature selection algorithm, indeed. Additionally, we applied SAMGSR to AC and SCC subtypes separately to discriminate their respective stages, that is, stage II versus stage I. Few overlaps between these two resulting gene signatures illustrate that AC and SCC are technically distinct diseases. Therefore, stratified analyses on subtypes are recommended when diagnostic or prognostic signatures of these two NSCLC subtypes are constructed.

  14. Altered metabolism of growth hormone receptor mutant mice: a combined NMR metabonomics and microarray study.

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    Horst Joachim Schirra

    Full Text Available BACKGROUND: Growth hormone is an important regulator of post-natal growth and metabolism. We have investigated the metabolic consequences of altered growth hormone signalling in mutant mice that have truncations at position 569 and 391 of the intracellular domain of the growth hormone receptor, and thus exhibit either low (around 30% maximum or no growth hormone-dependent STAT5 signalling respectively. These mutations result in altered liver metabolism, obesity and insulin resistance. METHODOLOGY/PRINCIPAL FINDINGS: The analysis of metabolic changes was performed using microarray analysis of liver tissue and NMR metabonomics of urine and liver tissue. Data were analyzed using multivariate statistics and Gene Ontology tools. The metabolic profiles characteristic for each of the two mutant groups and wild-type mice were identified with NMR metabonomics. We found decreased urinary levels of taurine, citrate and 2-oxoglutarate, and increased levels of trimethylamine, creatine and creatinine when compared to wild-type mice. These results indicate significant changes in lipid and choline metabolism, and were coupled with increased fat deposition, leading to obesity. The microarray analysis identified changes in expression of metabolic enzymes correlating with alterations in metabolite concentration both in urine and liver. Similarity of mutant 569 to the wild-type was seen in young mice, but the pattern of metabolites shifted to that of the 391 mutant as the 569 mice became obese after six months age. CONCLUSIONS/SIGNIFICANCE: The metabonomic observations were consistent with the parallel analysis of gene expression and pathway mapping using microarray data, identifying metabolites and gene transcripts involved in hepatic metabolism, especially for taurine, choline and creatinine metabolism. The systems biology approach applied in this study provides a coherent picture of metabolic changes resulting from impaired STAT5 signalling by the growth hormone

  15. Optimality criteria for the design of 2-color microarray studies.

    Science.gov (United States)

    Kerr, Kathleen F

    2012-01-13

    We discuss the definition and application of design criteria for evaluating the efficiency of 2-color microarray designs. First, we point out that design optimality criteria are defined differently for the regression and block design settings. This has caused some confusion in the literature and warrants clarification. Linear models for microarray data analysis have equivalent formulations as ANOVA or regression models. However, this equivalence does not extend to design criteria. We discuss optimality criterion, and argue against applying regression-style D-optimality to the microarray design problem. We further disfavor E- and D-optimality (as defined in block design) because they are not attuned to scientific questions of interest.

  16. High-Resolution Analysis of Gene Copy Number Alterations in Human Prostate Cancer Using CGH on cDNA Microarrays: Impact of Copy Number on Gene Expression

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    Maija Wolf

    2004-05-01

    Full Text Available Identification of target genes for genetic rearrangements in prostate cancer and the impact of copy number changes on gene expression are currently not well understood. Here, we applied high-resolution comparative genomic hybridization (CGH on cDNA microarrays for analysis of prostate cancer cell lines. CGH microarrays identified most of the alterations detected by classical chromosomal CGH, as well as a number of previously unreported alterations. Specific recurrent regions of gain (28 and loss (18 were found, their boundaries defined with sub-megabasepair accuracy. The most common changes included copy number decreases at 13% and gains at iq and 5p. Refined mapping identified several sites, such as at 13q (33-44, 49-51, 74-76 Mbp from the p-telomere, which matched with minimal regions of loss seen in extensive loss of heterozygosity mapping studies of large numbers of tumors. Previously unreported recurrent changes were found at 2p, 2q, 3p, 17q (losses, at 3q, 5p, 6p (gains. Integration of genomic and transcriptomic data revealed the role of individual candidate target genes for genomic alterations as well as a highly significant (P < .0001 overall association between copy number levels and the percentage of differentially expressed genes. Across the genome, the overall impact of copy number on gene expression levels was, to a large extent, attributable to low-level gains and losses of copy number, corresponding to common deletions and gains of often large chromosomal regions.

  17. Functional Characterization of Gibberellin-Regulated Genes in Rice Using Microarray System

    Institute of Scientific and Technical Information of China (English)

    Asad Jan; Setsuko Komatsu

    2006-01-01

    Gibberellin (GA) is collectively referred to a group of diterpenoid acids, some of which act as plant hormones and are essential for normal plant growth and development. DNA microarray technology has become the standard tool for the parallel quantification of large numbers of messenger RNA transcripts. The power of this approach has been demonstrated in dissecting plant physiology and development, and in unraveling the underlying cellular signaling pathways. To understand the molecular mechanism by which GA regulates the growth and development of plants, with reference to the monocot model plant-rice, it is essential to identify and analyze more genes and their products at the transcription and translation levels that are regulated by GA. With the availability of draft sequences of two major rice types, indica and japonica rice, it has become possible to analyze global expression profiles of genes on a genome scale. In this review, the progress made in finding new genes in rice leaf sheath using microarray system and their characterization is discussed. It is believed that the findings made in this regard have important implications for understanding the mechanism by which GA regulates the growth and development of rice.

  18. Microarray evidence of glutaminyl cyclase gene expression in melanoma: implications for tumor antigen specific immunotherapy

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    Gillis John

    2006-07-01

    Full Text Available Abstract Background In recent years encouraging progress has been made in developing vaccine treatments for cancer, particularly with melanoma. However, the overall rate of clinically significant results has remained low. The present research used microarray datasets from previous investigations to examine gene expression patterns in cancer cell lines with the goal of better understanding the tumor microenvironment. Methods Principal Components Analyses with Promax rotational transformations were carried out with 90 cancer cell lines from 3 microarray datasets, which had been made available on the internet as supplementary information from prior publications. Results In each of the analyses a well defined melanoma component was identified that contained a gene coding for the enzyme, glutaminyl cyclase, which was as highly expressed as genes from a variety of well established biomarkers for melanoma, such as MAGE-3 and MART-1, which have frequently been used in clinical trials of melanoma vaccines. Conclusion Since glutaminyl cyclase converts glutamine and glutamic acid into a pyroglutamic form, it may interfere with the tumor destructive process of vaccines using peptides having glutamine or glutamic acid at their N-terminals. Finding ways of inhibiting the activity of glutaminyl cyclase in the tumor microenvironment may help to increase the effectiveness of some melanoma vaccines.

  19. Microarray-Based Gene Expression Analysis for Veterinary Pathologists: A Review.

    Science.gov (United States)

    Raddatz, Barbara B; Spitzbarth, Ingo; Matheis, Katja A; Kalkuhl, Arno; Deschl, Ulrich; Baumgärtner, Wolfgang; Ulrich, Reiner

    2017-09-01

    High-throughput, genome-wide transcriptome analysis is now commonly used in all fields of life science research and is on the cusp of medical and veterinary diagnostic application. Transcriptomic methods such as microarrays and next-generation sequencing generate enormous amounts of data. The pathogenetic expertise acquired from understanding of general pathology provides veterinary pathologists with a profound background, which is essential in translating transcriptomic data into meaningful biological knowledge, thereby leading to a better understanding of underlying disease mechanisms. The scientific literature concerning high-throughput data-mining techniques usually addresses mathematicians or computer scientists as the target audience. In contrast, the present review provides the reader with a clear and systematic basis from a veterinary pathologist's perspective. Therefore, the aims are (1) to introduce the reader to the necessary methodological background; (2) to introduce the sequential steps commonly performed in a microarray analysis including quality control, annotation, normalization, selection of differentially expressed genes, clustering, gene ontology and pathway analysis, analysis of manually selected genes, and biomarker discovery; and (3) to provide references to publically available and user-friendly software suites. In summary, the data analysis methods presented within this review will enable veterinary pathologists to analyze high-throughput transcriptome data obtained from their own experiments, supplemental data that accompany scientific publications, or public repositories in order to obtain a more in-depth insight into underlying disease mechanisms.

  20. Detection and isolation of selected genes of interest from metagenomic libraries by a DNA microarray approach.

    Science.gov (United States)

    Pathak, Gopal P; Gärtner, Wolfgang

    2010-01-01

    A DNA microarray-based approach is described for screening metagenomic libraries for the presence of selected genes. The protocol is exemplified for the identification of flavin-binding, blue-light-sensitive biological photoreceptors (BL), based on a homology search in already sequenced, annotated genomes. The microarray carried 149 different 54-mer oligonucleotides, derived from consensus sequences of BL photoreceptors. The array could readily identify targets carrying 4% sequence mismatch, and allowed unambiguous identification of a positive cosmid clone of as little as 10 ng against a background of 25 μg of cosmid DNA. The protocol allows screening up to 1,200 library clones in concentrations as low as ca. 20 ng, each with a ca. 40 kb insert size readily in a single batch. Calibration and control conditions are outlined. This protocol, when applied to the thermophilic fraction of a soil sample, yielded the identification and functional characterization of a novel, BL-encoding gene that showed a 58% similarity to a known, BL-encoding gene from Kineococcus radiotolerans SRS30216 (similarity values refer to the respective LOV domains).

  1. Not proper ROC curves as new tool for the analysis of differentially expressed genes in microarray experiments

    Directory of Open Access Journals (Sweden)

    Pistoia Vito

    2008-10-01

    Full Text Available Abstract Background Most microarray experiments are carried out with the purpose of identifying genes whose expression varies in relation with specific conditions or in response to environmental stimuli. In such studies, genes showing similar mean expression values between two or more groups are considered as not differentially expressed, even if hidden subclasses with different expression values may exist. In this paper we propose a new method for identifying differentially expressed genes, based on the area between the ROC curve and the rising diagonal (ABCR. ABCR represents a more general approach than the standard area under the ROC curve (AUC, because it can identify both proper (i.e., concave and not proper ROC curves (NPRC. In particular, NPRC may correspond to those genes that tend to escape standard selection methods. Results We assessed the performance of our method using data from a publicly available database of 4026 genes, including 14 normal B cell samples (NBC and 20 heterogeneous lymphomas (namely: 9 follicular lymphomas and 11 chronic lymphocytic leukemias. Moreover, NBC also included two sub-classes, i.e., 6 heavily stimulated and 8 slightly or not stimulated samples. We identified 1607 differentially expressed genes with an estimated False Discovery Rate of 15%. Among them, 16 corresponded to NPRC and all escaped standard selection procedures based on AUC and t statistics. Moreover, a simple inspection to the shape of such plots allowed to identify the two subclasses in either one class in 13 cases (81%. Conclusion NPRC represent a new useful tool for the analysis of microarray data.

  2. A survey on filter techniques for feature selection in gene expression microarray analysis.

    Science.gov (United States)

    Lazar, Cosmin; Taminau, Jonatan; Meganck, Stijn; Steenhoff, David; Coletta, Alain; Molter, Colin; de Schaetzen, Virginie; Duque, Robin; Bersini, Hugues; Nowé, Ann

    2012-01-01

    A plenitude of feature selection (FS) methods is available in the literature, most of them rising as a need to analyze data of very high dimension, usually hundreds or thousands of variables. Such data sets are now available in various application areas like combinatorial chemistry, text mining, multivariate imaging, or bioinformatics. As a general accepted rule, these methods are grouped in filters, wrappers, and embedded methods. More recently, a new group of methods has been added in the general framework of FS: ensemble techniques. The focus in this survey is on filter feature selection methods for informative feature discovery in gene expression microarray (GEM) analysis, which is also known as differentially expressed genes (DEGs) discovery, gene prioritization, or biomarker discovery. We present them in a unified framework, using standardized notations in order to reveal their technical details and to highlight their common characteristics as well as their particularities.

  3. Study of generational risk in deafness inflicted couples using deafness gene microarray technique%应用耳聋基因芯片探讨聋哑夫妇的生育风险

    Institute of Scientific and Technical Information of China (English)

    王苹; 赵佳; 于姝媛; 金鹏; 祝威; 杜波

    2011-01-01

    目的 通过耳聋基因芯片诊断技术,探讨耳聋易感基因筛选在聋哑人家庭优生优育中的意义.方法 52对聋人夫妻来自长春市某聋哑社区,平均((x)±s)年龄(58.3±6.7)岁.在受检者知情同意情况下采集外周静脉血3 ml,分离基因组DNA,利用遗传性耳聋基因检测芯片对GJB2、SLC26A4、GJB3和线粒体DNA等常见耳聋基因中的9个突变位点进行检测.通过直接测序法验证基因芯片结果.以50名年龄相仿的健康人为对照.结果 所有聋人夫妻纯音测听检查均为双耳非综合征型感音神经性聋.104例患者中,有32例出现GJB2基因突变,占耳聋总人数的30.7%(32/104),包括35delG、176del16、235delC、299delAT;其中18例存在235delC突变,占所有GJB2等位基因突变的59.1%(18/32).SLC26A4基因纯合突变4例,杂合突变3例,均为IVS7-2 A>G突变.问卷调查和基因检测分析发现,52对聋人夫妻,有4个家庭后代出现耳聋成员,占聋人家庭总数的7.6%(4/52).夫妻双方均携带相同基因突变,其子女均发生耳聋,耳聋发生风险为100%.基因芯片的结果与测序方法的结果完全一致.结论 聋哑家庭再生育聋人的风险较高,通过基因芯片技术进行耳聋易感基因检测,可避免明确病因的耳聋家庭出现新的耳聋病例.%Objective To explored the significance of screening the gene mutations of deafness related in deaf-mute ( deaf & dumb) family using DNA microarray. Methods Total of 52 couples of deafmute were recruited from Changchun deaf-mute community. With an averageage of (58. 3 ±6. 7) years old ((x) ± s) . Blood samples were obtained with informed consent. Their genomic DNA was extracted from peripheral blood and PCR was performed. Nine of hot spot mutations in four most common deafness pathologic gene were examined with the DNA microarray, including GJB2, GJB3,PDS and mtDNA 12SrRNA genes. At the same time, the results were verified with the traditional methods of sequencing. Fifty

  4. Comparison and Validation of Putative Pathogenicity-Related Genes Identified by T-DNA Insertional Mutagenesis and Microarray Expression Profiling in Magnaporthe oryzae

    Science.gov (United States)

    Wáng, Ying; Tan, Qi; Gao, Ying Nv; Li, Yan

    2017-01-01

    High-throughput technologies of functional genomics such as T-DNA insertional mutagenesis and microarray expression profiling have been employed to identify genes related to pathogenicity in Magnaporthe oryzae. However, validation of the functions of individual genes identified by these high-throughput approaches is laborious. In this study, we compared two published lists of genes putatively related to pathogenicity in M. oryzae identified by T-DNA insertional mutagenesis (comprising 1024 genes) and microarray expression profiling (comprising 236 genes), respectively, and then validated the functions of some overlapped genes between the two lists by knocking them out using the method of target gene replacement. Surprisingly, only 13 genes were overlapped between the two lists, and none of the four genes selected from the overlapped genes exhibited visible phenotypic changes on vegetative growth, asexual reproduction, and infection ability in their knockout mutants. Our results suggest that both of the lists might contain large proportions of unrelated genes to pathogenicity and therefore comparing the two gene lists is hardly helpful for the identification of genes that are more likely to be involved in pathogenicity as we initially expected.

  5. Cluster stability scores for microarray data in cancer studies

    OpenAIRE

    Ghosh Debashis; Smolkin Mark

    2003-01-01

    Abstract Background A potential benefit of profiling of tissue samples using microarrays is the generation of molecular fingerprints that will define subtypes of disease. Hierarchical clustering has been the primary analytical tool used to define disease subtypes from microarray experiments in cancer settings. Assessing cluster reliability poses a major complication in analyzing output from clustering procedures. While most work has focused on estimating the number of clusters in a dataset, t...

  6. Construction of the Seed-Coat cDNA Microarray and Screening of Differentially Expressed Genes in Barley

    Institute of Scientific and Technical Information of China (English)

    Jin-Song PANG; Meng-Yuan HE; Bao LIU

    2004-01-01

    Some barley mutants can synthesize neither anthocyanins nor proanthocyanidins in the seed coat, which is related to several genes in locus Ant13, but the exact model of action remains unknown. We used the cDNA microarray technology with barley transcription-deficient mutant (ant13-152) that does not synthesize proanthocyanidins as the tester, and its wild type genotype (Triumph) as the driver, to study this question. Six-thousand and forty-eight clones from the wild type Morex testa+pericarp cDNA library were amplified using PCR, and the DNA fragments were spotted on commercial amino-modified glass slide as microarray. The mRNAs from the developing seed coat (8-15 days) of both the mutant and the wild-type barley plants were isolated, and labeled respectively with Cy3-dUTP and Cy5-dUTP when reversely transcribed to cDNAs. The labeled cDNAs were used as probes, mixed at the same molar concentration, and hybridized with the DNA fragments on the slide. Seventy clones exhibiting marked differential expression (ratio>4) were identified from the microarray. All the 25 cDNA clones that showed an over-expression in wild type in comparison to the mutant ant13-152 were sequenced. It was found that most of these overexpressing clones were transcription/translation and hordein-associated genes. These results have laid a solid material basis for further elucidation of the metabolic pathway in proanthocyanidin synthesis in barley and likely other plants.

  7. A model system for assessing and comparing the ability of exon microarray and tag sequencing to detect genes specific for malignant B-cells

    Directory of Open Access Journals (Sweden)

    Kloster Maria

    2012-11-01

    Full Text Available Abstract Background Malignant cells in tumours of B-cell origin account for 0.1% to 98% of the total cell content, depending on disease entity. Recently, gene expression profiles (GEPs of B-cell lymphomas based on microarray technologies have contributed significantly to improved sub-classification and diagnostics. However, the varying degrees of malignant B-cell frequencies in analysed samples influence the interpretation of the GEPs. Based on emerging next-generation sequencing technologies (NGS like tag sequencing (tag-seq for GEP, it is expected that the detection of mRNA transcripts from malignant B-cells can be supplemented. This study provides a quantitative assessment and comparison of the ability of microarrays and tag-seq to detect mRNA transcripts from malignant B-cells. A model system was established by eight serial dilutions of the malignant B-cell lymphoma cell line, OCI-Ly8, into the embryonic kidney cell line, HEK293, prior to parallel analysis by exon microarrays and tag-seq. Results We identified 123 and 117 differentially expressed genes between pure OCI-Ly8 and HEK293 cells by exon microarray and tag-seq, respectively. There were thirty genes in common, and of those, most were B-cell specific. Hierarchical clustering from all dilutions based on the differentially expressed genes showed that neither technology could distinguish between samples with less than 1% malignant B-cells from non-B-cells. A novel statistical concept was developed to assess the ability to detect single genes for both technologies, and used to demonstrate an inverse proportional relationship with the sample purity. Of the 30 common genes, the detection capability of a representative set of three B-cell specific genes - CD74, HLA-DRA, and BCL6 - was analysed. It was noticed that at least 5%, 13% and 22% sample purity respectively was required for detection of the three genes by exon microarray whereas at least 2%, 4% and 51% percent sample purity of

  8. An Improved Fuzzy Based Missing Value Estimation in DNA Microarray Validated by Gene Ranking

    Directory of Open Access Journals (Sweden)

    Sujay Saha

    2016-01-01

    Full Text Available Most of the gene expression data analysis algorithms require the entire gene expression matrix without any missing values. Hence, it is necessary to devise methods which would impute missing data values accurately. There exist a number of imputation algorithms to estimate those missing values. This work starts with a microarray dataset containing multiple missing values. We first apply the modified version of the fuzzy theory based existing method LRFDVImpute to impute multiple missing values of time series gene expression data and then validate the result of imputation by genetic algorithm (GA based gene ranking methodology along with some regular statistical validation techniques, like RMSE method. Gene ranking, as far as our knowledge, has not been used yet to validate the result of missing value estimation. Firstly, the proposed method has been tested on the very popular Spellman dataset and results show that error margins have been drastically reduced compared to some previous works, which indirectly validates the statistical significance of the proposed method. Then it has been applied on four other 2-class benchmark datasets, like Colorectal Cancer tumours dataset (GDS4382, Breast Cancer dataset (GSE349-350, Prostate Cancer dataset, and DLBCL-FL (Leukaemia for both missing value estimation and ranking the genes, and the results show that the proposed method can reach 100% classification accuracy with very few dominant genes, which indirectly validates the biological significance of the proposed method.

  9. Identification and Optimization of Classifier Genes from Multi-Class Earthworm Microarray Dataset

    Science.gov (United States)

    2010-10-28

    This work was supported by the U.S. Army Environmental Quality Technology Research Program. The funders had no role in study design, data collection... bioindicators for adverse effects caused by environmental contaminants. Previously, we developed an earthworm (Eisenia fetida) cDNA microarray to...Zhang1, Ping Gong3* 1 School of Computing, University of Southern Mississippi, Hattiesburg, Mississippi, United States of America, 2 Environmental

  10. Microarray-based characterization of differential gene expression during vocal fold wound healing in rats.

    Science.gov (United States)

    Welham, Nathan V; Ling, Changying; Dawson, John A; Kendziorski, Christina; Thibeault, Susan L; Yamashita, Masaru

    2015-03-01

    The vocal fold (VF) mucosa confers elegant biomechanical function for voice production but is susceptible to scar formation following injury. Current understanding of VF wound healing is hindered by a paucity of data and is therefore often generalized from research conducted in skin and other mucosal systems. Here, using a previously validated rat injury model, expression microarray technology and an empirical Bayes analysis approach, we generated a VF-specific transcriptome dataset to better capture the system-level complexity of wound healing in this specialized tissue. We measured differential gene expression at 3, 14 and 60 days post-injury compared to experimentally naïve controls, pursued functional enrichment analyses to refine and add greater biological definition to the previously proposed temporal phases of VF wound healing, and validated the expression and localization of a subset of previously unidentified repair- and regeneration-related genes at the protein level. Our microarray dataset is a resource for the wider research community and has the potential to stimulate new hypotheses and avenues of investigation, improve biological and mechanistic insight, and accelerate the identification of novel therapeutic targets.

  11. Microarray-based characterization of differential gene expression during vocal fold wound healing in rats

    Directory of Open Access Journals (Sweden)

    Nathan V. Welham

    2015-03-01

    Full Text Available The vocal fold (VF mucosa confers elegant biomechanical function for voice production but is susceptible to scar formation following injury. Current understanding of VF wound healing is hindered by a paucity of data and is therefore often generalized from research conducted in skin and other mucosal systems. Here, using a previously validated rat injury model, expression microarray technology and an empirical Bayes analysis approach, we generated a VF-specific transcriptome dataset to better capture the system-level complexity of wound healing in this specialized tissue. We measured differential gene expression at 3, 14 and 60 days post-injury compared to experimentally naïve controls, pursued functional enrichment analyses to refine and add greater biological definition to the previously proposed temporal phases of VF wound healing, and validated the expression and localization of a subset of previously unidentified repair- and regeneration-related genes at the protein level. Our microarray dataset is a resource for the wider research community and has the potential to stimulate new hypotheses and avenues of investigation, improve biological and mechanistic insight, and accelerate the identification of novel therapeutic targets.

  12. Tissue-based microarray expression of genes predictive of metastasis in uveal melanoma and differentially expressed in metastatic uveal melanoma.

    Science.gov (United States)

    Demirci, Hakan; Reed, David; Elner, Victor M

    2013-10-01

    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. 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. 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. 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.

  13. 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.

  14. The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.

    Science.gov (United States)

    Shi, Leming; Campbell, Gregory; Jones, Wendell D; Campagne, Fabien; Wen, Zhining; Walker, Stephen J; Su, Zhenqiang; Chu, Tzu-Ming; Goodsaid, Federico M; Pusztai, Lajos; Shaughnessy, John D; Oberthuer, André; Thomas, Russell S; Paules, Richard S; Fielden, Mark; Barlogie, Bart; Chen, Weijie; Du, Pan; Fischer, Matthias; Furlanello, Cesare; Gallas, Brandon D; Ge, Xijin; Megherbi, Dalila B; Symmans, W Fraser; Wang, May D; Zhang, John; Bitter, Hans; Brors, Benedikt; Bushel, Pierre R; Bylesjo, Max; Chen, Minjun; Cheng, Jie; Cheng, Jing; Chou, Jeff; Davison, Timothy S; Delorenzi, Mauro; Deng, Youping; Devanarayan, Viswanath; Dix, David J; Dopazo, Joaquin; Dorff, Kevin C; Elloumi, Fathi; Fan, Jianqing; Fan, Shicai; Fan, Xiaohui; Fang, Hong; Gonzaludo, Nina; Hess, Kenneth R; Hong, Huixiao; Huan, Jun; Irizarry, Rafael A; Judson, Richard; Juraeva, Dilafruz; Lababidi, Samir; Lambert, Christophe G; Li, Li; Li, Yanen; Li, Zhen; Lin, Simon M; Liu, Guozhen; Lobenhofer, Edward K; Luo, Jun; Luo, Wen; McCall, Matthew N; Nikolsky, Yuri; Pennello, Gene A; Perkins, Roger G; Philip, Reena; Popovici, Vlad; Price, Nathan D; Qian, Feng; Scherer, Andreas; Shi, Tieliu; Shi, Weiwei; Sung, Jaeyun; Thierry-Mieg, Danielle; Thierry-Mieg, Jean; Thodima, Venkata; Trygg, Johan; Vishnuvajjala, Lakshmi; Wang, Sue Jane; Wu, Jianping; Wu, Yichao; Xie, Qian; Yousef, Waleed A; Zhang, Liang; Zhang, Xuegong; Zhong, Sheng; Zhou, Yiming; Zhu, Sheng; Arasappan, Dhivya; Bao, Wenjun; Lucas, Anne Bergstrom; Berthold, Frank; Brennan, Richard J; Buness, Andreas; Catalano, Jennifer G; Chang, Chang; Chen, Rong; Cheng, Yiyu; Cui, Jian; Czika, Wendy; Demichelis, Francesca; Deng, Xutao; Dosymbekov, Damir; Eils, Roland; Feng, Yang; Fostel, Jennifer; Fulmer-Smentek, Stephanie; Fuscoe, James C; Gatto, Laurent; Ge, Weigong; Goldstein, Darlene R; Guo, Li; Halbert, Donald N; Han, Jing; Harris, Stephen C; Hatzis, Christos; Herman, Damir; Huang, Jianping; Jensen, Roderick V; Jiang, Rui; Johnson, Charles D; Jurman, Giuseppe; Kahlert, Yvonne; Khuder, Sadik A; Kohl, Matthias; Li, Jianying; Li, Li; Li, Menglong; Li, Quan-Zhen; Li, Shao; Li, Zhiguang; Liu, Jie; Liu, Ying; Liu, Zhichao; Meng, Lu; Madera, Manuel; Martinez-Murillo, Francisco; Medina, Ignacio; Meehan, Joseph; Miclaus, Kelci; Moffitt, Richard A; Montaner, David; Mukherjee, Piali; Mulligan, George J; Neville, Padraic; Nikolskaya, Tatiana; Ning, Baitang; Page, Grier P; Parker, Joel; Parry, R Mitchell; Peng, Xuejun; Peterson, Ron L; Phan, John H; Quanz, Brian; Ren, Yi; Riccadonna, Samantha; Roter, Alan H; Samuelson, Frank W; Schumacher, Martin M; Shambaugh, Joseph D; Shi, Qiang; Shippy, Richard; Si, Shengzhu; Smalter, Aaron; Sotiriou, Christos; Soukup, Mat; Staedtler, Frank; Steiner, Guido; Stokes, Todd H; Sun, Qinglan; Tan, Pei-Yi; Tang, Rong; Tezak, Zivana; Thorn, Brett; Tsyganova, Marina; Turpaz, Yaron; Vega, Silvia C; Visintainer, Roberto; von Frese, Juergen; Wang, Charles; Wang, Eric; Wang, Junwei; Wang, Wei; Westermann, Frank; Willey, James C; Woods, Matthew; Wu, Shujian; Xiao, Nianqing; Xu, Joshua; Xu, Lei; Yang, Lun; Zeng, Xiao; Zhang, Jialu; Zhang, Li; Zhang, Min; Zhao, Chen; Puri, Raj K; Scherf, Uwe; Tong, Weida; Wolfinger, Russell D

    2010-08-01

    Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

  15. Microarray profiling reveals suppressed interferon stimulated gene program in fibroblasts from scleroderma-associated interstitial lung disease

    Science.gov (United States)

    2013-01-01

    Background Interstitial lung disease is a major cause of morbidity and mortality in systemic sclerosis (SSc), with insufficiently effective treatment options. Progression of pulmonary fibrosis involves expanding populations of fibroblasts, and the accumulation of extracellular matrix proteins. Characterisation of SSc lung fibroblast gene expression profiles underlying the fibrotic cell phenotype could enable a better understanding of the processes leading to the progressive build-up of scar tissue in the lungs. In this study we evaluate the transcriptomes of fibroblasts isolated from SSc lung biopsies at the time of diagnosis, compared with those from control lungs. Methods We used Affymetrix oligonucleotide microarrays to compare the gene expression profile of pulmonary fibroblasts cultured from 8 patients with pulmonary fibrosis associated with SSc (SSc-ILD), with those from control lung tissue peripheral to resected cancer (n=10). Fibroblast cultures from 3 patients with idiopathic pulmonary fibrosis (IPF) were included as a further comparison. Genes differentially expressed were identified using two separate analysis programs following a set of pre-determined criteria: only genes significant in both analyses were considered. Microarray expression data was verified by qRT-PCR and/or western blot analysis. Results A total of 843 genes were identified as differentially expressed in pulmonary fibroblasts from SSc-ILD and/or IPF compared to control lung, with a large overlap in the expression profiles of both diseases. We observed increased expression of a TGF-β response signature including fibrosis associated genes and myofibroblast markers, with marked heterogeneity across samples. Strongly suppressed expression of interferon stimulated genes, including antiviral, chemokine, and MHC class 1 genes, was uniformly observed in fibrotic fibroblasts. This expression profile includes key regulators and mediators of the interferon response, such as STAT1, and CXCL10, and

  16. Identification of target genes conferring ethanol stress tolerance to Saccharomyces cerevisiae based on DNA microarray data analysis.

    Science.gov (United States)

    Hirasawa, Takashi; Yoshikawa, Katsunori; Nakakura, Yuki; Nagahisa, Keisuke; Furusawa, Chikara; Katakura, Yoshio; Shimizu, Hiroshi; Shioya, Suteaki

    2007-08-01

    During industrial production process using yeast, cells are exposed to the stress due to the accumulation of ethanol, which affects the cell growth activity and productivity of target products, thus, the ethanol stress-tolerant yeast strains are highly desired. To identify the target gene(s) for constructing ethanol stress tolerant yeast strains, we obtained the gene expression profiles of two strains of Saccharomyces cerevisiae, namely, a laboratory strain and a strain used for brewing Japanese rice wine (sake), in the presence of 5% (v/v) ethanol, using DNA microarray. For the selection of target genes for breeding ethanol stress tolerant strains, clustering of DNA microarray data was performed. For further selection, the ethanol sensitivity of the knockout mutants in each of which the gene selected by DNA microarray analysis is deleted, was also investigated. The integration of the DNA microarray data and the ethanol sensitivity data of knockout strains suggests that the enhancement of expression of genes related to tryptophan biosynthesis might confer the ethanol stress tolerance to yeast cells. Indeed, the strains overexpressing tryptophan biosynthesis genes showed a stress tolerance to 5% ethanol. Moreover, the addition of tryptophan to the culture medium and overexpression of tryptophan permease gene conferred ethanol stress tolerance to yeast cells. These results indicate that overexpression of the genes for trypophan biosynthesis increases the ethanol stress tolerance. Tryptophan supplementation to culture and overexpression of the tryptophan permease gene are also effective for the increase in ethanol stress tolerance. Our methodology for the selection of target genes for constructing ethanol stress tolerant strains, based on the data of DNA microarray analysis and phenotypes of knockout mutants, was validated.

  17. Comprehensive gene expression microarray analysis of Ets-1 blockade in PC3 prostate cancer cells and correlations with prostate cancer tissues: Insights into genes involved in the metastatic cascade.

    Science.gov (United States)

    Shaikhibrahim, Zaki; Lindstrot, Andreas; Langer, Berit; Buettner, Reinhard; Wernert, Nicolas

    2011-06-01

    Ets-1 is the prototype of the ETS family of transcription factors and is suggested to play an important role in the malignant progression of prostatic carcinomas. Therefore, in this study we investigated the effect of blocking Ets-1 in PC3 prostate cancer cells on genes involved in the metastatic cascade, and correlated these findings with prostate cancer tissues. Two stable PC3 cell cultures were established by transfection with either an Ets-1 inverse antisense expression vector or a mock control vector. The effect of blocking Ets-1 on genes involved in the metastatic cascade was assessed by a comprehensive gene expression microarray analysis of Ets-1 inverse and mock control cells. Correlating the sets of genes found in the PC3 microarray data with prostate cancer tissues was performed by verifying the genes in a comprehensive gene expression microarray analysis of RNA extracted from laser microdissected normal prostate glands and from carcinoma glands taken from prostate cancer patients. Western blot analysis confirmed the presence of Ets-1 in mock cells and its absence in Ets-1 inverse cells. In the Ets-1 blockade microarray, many differentially expressed genes were found; however, only genes with a greater than 10-fold up- or down-regulation between the Ets-1 blockade and mock control were considered significant. The genes were placed into four groups that play a role in the so-called metastatic cascade based on their known functions in proliferation, apoptosis, migration and angiogenesis. The genes found in the Ets-1 blockade microarray analysis were verified for their presence in the microarray analysis of prostate cancer tissues. Genes found in the microarray analysis of prostate cancer tissues with an >2-fold change and a p-value tissues, we identified 16 genes that are up- or down-regulated in healthy compared to tumor prostate glands. Further investigation revealed that 4 out of the 16 genes have been reported to be regulated by members of the ETS

  18. cDNA microarray analysis of human keratinocytes cells of patients submitted to chemoradiotherapy and oral photobiomodulation therapy: pilot study.

    Science.gov (United States)

    Antunes, Heliton S; Wajnberg, Gabriel; Pinho, Marcos B; Jorge, Natasha Andressa Nogueira; de Moraes, Joyce Luana Melo; Stefanoff, Claudio Gustavo; Herchenhorn, Daniel; Araújo, Carlos M M; Viégas, Celia Maria Pais; Rampini, Mariana P; Dias, Fernando L; de Araujo-Souza, Patricia Savio; Passetti, Fabio; Ferreira, Carlos G

    2017-08-24

    Oral mucositis is an acute toxicity that occurs in patients submitted to chemoradiotherapy to treat head and neck squamous cell carcinoma. In this study, we evaluated differences in gene expression in the keratinocytes of the oral mucosa of patients treated with photobiomodulation therapy and tried to associate the molecular mechanisms with clinical findings. From June 2009 to December 2010, 27 patients were included in a randomized double-blind pilot study. Buccal smears from 13 patients were obtained at days 1 and 10 of chemoradiotherapy, and overall gene expression of samples from both dates were analyzed by complementary DNA (cDNA) microarray. In addition, samples from other 14 patients were also collected at D1 and D10 of chemoradiotherapy for subsequent validation of cDNA microarray findings by qPCR. The expression array analysis identified 105 upregulated and 60 downregulated genes in our post-treatment samples when compared with controls. Among the upregulated genes with the highest fold change, it was interesting to observe the presence of genes related to keratinocyte differentiation. Among downregulated genes were observed genes related to cytotoxicity and immune response. The results indicate that genes known to be induced during differentiation of human epidermal keratinocytes were upregulated while genes associated with cytotoxicity and immune response were downregulated in the laser group. These results support previous clinical findings indicating that the lower incidence of oral mucositis associated with photobiomodulation therapy might be correlated to the activation of genes involved in keratinocyte differentiation.

  19. Bayesian Hierarchical Model for Estimating Gene Expression Intensity Using Multiple Scanned Microarrays

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    Auvinen Petri

    2008-01-01

    Full Text Available We propose a method for improving the quality of signal from DNA microarrays by using several scans at varying scanner sen-sitivities. A Bayesian latent intensity model is introduced for the analysis of such data. The method improves the accuracy at which expressions can be measured in all ranges and extends the dynamic range of measured gene expression at the high end. Our method is generic and can be applied to data from any organism, for imaging with any scanner that allows varying the laser power, and for extraction with any image analysis software. Results from a self-self hybridization data set illustrate an improved precision in the estimation of the expression of genes compared to what can be achieved by applying standard methods and using only a single scan.

  20. Understanding Autoimmune Mechanisms in Multiple Sclerosis Using Gene Expression Microarrays: Treatment Effect and Cytokine-related Pathways

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    A. Achiron

    2004-01-01

    Full Text Available Multiple sclerosis (MS is a central nervous system disease in which activated autoreactive T-cells invade the blood brain barrier and initiate an inflammatory response that leads to myelin destruction and axonal loss. The etiology of MS, as well as the mechanisms associated with its unexpected onset, the unpredictable clinical course spanning decades, and the different rates of progression leading to disability over time, remains an enigma. We have applied gene expression microarrays technology in peripheral blood mononuclear cells (PBMC to better understand MS pathogenesis and better target treatment approaches. A signature of 535 genes were found to distinguish immunomodulatory treatment effects between 13 treated and 13 untreated MS patients. In addition, the expression pattern of 1109 gene transcripts that were previously reported to significantly differentiate between MS patients and healthy subjects were further analyzed to study the effect of cytokine-related pathways on disease pathogenesis. When relative gene expression for 26 MS patients was compared to 18 healthy controls, 30 genes related to various cytokine-associated pathways were identified. These genes belong to a variety of families such as interleukins, small inducible cytokine subfamily and tumor necrosis factor ligand and receptor. Further analysis disclosed seven cytokine-associated genes within the immunomodulatory treatment signature, and two cytokine-associated genes SCYA4 (small inducible cytokine A4 and FCAR (Fc fragment of IgA, CD89 that were common to both the MS gene expression signature and the immunomodulatory treatment gene expression signature. Our results indicate that cytokine-associated genes are involved in various pathogenic pathways in MS and also related to immunomodulatory treatment effects.

  1. Mapping of heterologous expressed sequence tags as an alternative to microarrays for study of defense responses in plants

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    Postnikova Olga A

    2009-06-01

    Full Text Available Abstract Background Microarray technology helped to accumulate an immense pool of data on gene expression changes in response to different environmental factors. Yet, computer- generated gene profiling using expressed sequence tags (EST represents a valuable alternative to microarrays, which allows efficient discovery of homologous sequences in evolutionarily different species and comparison of gene sets on the whole genome scale. In this study, we used publicly available EST database derived from different plant species infected with a variety of pathogens, to generate an expression profile of homologous genes involved in defense response of a model organism, Arabidopsis thaliana. Results EST-driven prediction identified 4,935 genes (16% of the total Arabidopsis genome which, according to the origin of EST sets, were associated with defense responses in the reference genome. Profiles of defense-related genes, obtained by mapping of heterologous EST, represent putative Arabidopsis homologs of the corresponding species. Comparison of these profiles in pairs and locating common genes allowed estimating similarity between defense-related gene sets of different plant species. To experimentally support computer data, we arbitrarily selected a number of transcription factor genes (TF detected by EST mapping. Their expression levels were examined by real-time polymerase chain reaction during infection with yellow strain of Cucumber mosaic virus, a compatible virus systemically infecting Arabidopsis. We observed that 65% of the designated TF were upregulated in accordance with the EST-generated profile. Conclusion We demonstrated that heterologous EST mapping may be efficiently used to reveal genes involved in host defense responses to pathogens. Upregulated genes identified in this study substantially overlap with those previously obtained by microarrays.

  2. Gametogenesis in the Pacific oyster Crassostrea gigas: a microarrays-based analysis identifies sex and stage specific genes.

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    Nolwenn M Dheilly

    Full Text Available BACKGROUND: The Pacific oyster Crassostrea gigas (Mollusca, Lophotrochozoa is an alternative and irregular protandrous hermaphrodite: most individuals mature first as males and then change sex several times. Little is known about genetic and phenotypic basis of sex differentiation in oysters, and little more about the molecular pathways regulating reproduction. We have recently developed and validated a microarray containing 31,918 oligomers (Dheilly et al., 2011 representing the oyster transcriptome. The application of this microarray to the study of mollusk gametogenesis should provide a better understanding of the key factors involved in sex differentiation and the regulation of oyster reproduction. METHODOLOGY/PRINCIPAL FINDINGS: Gene expression was studied in gonads of oysters cultured over a yearly reproductive cycle. Principal component analysis and hierarchical clustering showed a significant divergence in gene expression patterns of males and females coinciding with the start of gonial mitosis. ANOVA analysis of the data revealed 2,482 genes differentially expressed during the course of males and/or females gametogenesis. The expression of 434 genes could be localized in either germ cells or somatic cells of the gonad by comparing the transcriptome of female gonads to the transcriptome of stripped oocytes and somatic tissues. Analysis of the annotated genes revealed conserved molecular mechanisms between mollusks and mammals: genes involved in chromatin condensation, DNA replication and repair, mitosis and meiosis regulation, transcription, translation and apoptosis were expressed in both male and female gonads. Most interestingly, early expressed male-specific genes included bindin and a dpy-30 homolog and female-specific genes included foxL2, nanos homolog 3, a pancreatic lipase related protein, cd63 and vitellogenin. Further functional analyses are now required in order to investigate their role in sex differentiation in oysters

  3. Sex-related gene expression profiles in the adrenal cortex in the mature rat: microarray analysis with emphasis on genes involved in steroidogenesis.

    Science.gov (United States)

    Trejter, Marcin; Hochol, Anna; Tyczewska, Marianna; Ziolkowska, Agnieszka; Jopek, Karol; Szyszka, Marta; Malendowicz, Ludwik K; Rucinski, Marcin

    2015-03-01

    Notable sex-related differences exist in mammalian adrenal cortex structure and function. In adult rats, the adrenal weight and the average volume of zona fasciculata cells of females are larger and secrete greater amounts of corticosterone than those of males. The molecular bases of these sex-related differences are poorly understood. In this study, to explore the molecular background of these differences, we defined zone- and sex-specific transcripts in adult male and female (estrous cycle phase) rats. Twelve-week-old rats of both genders were used and samples were taken from the zona glomerulosa (ZG) and zona fasciculata/reticularis (ZF/R) zones. Transcriptome identification was carried out using the Affymetrix(®) Rat Gene 1.1 ST Array. The microarray data were compared by fold change with significance according to moderated t-statistics. Subsequently, we performed functional annotation clustering using the Gene Ontology (GO) and Database for Annotation, Visualization and Integrated Discovery (DAVID). In the first step, we explored differentially expressed transcripts in the adrenal ZG and ZF/R. The number of differentially expressed transcripts was notably higher in the female than in the male rats (702 vs. 571). The differentially expressed genes which were significantly enriched included genes involved in steroid hormone metabolism, and their expression levels in the ZF/R of adult female rats were significantly higher compared with those in the male rats. In the female ZF/R, when compared with that of the males, prevailing numbers of genes linked to cell fraction, oxidation/reduction processes, response to nutrients and to extracellular stimuli or steroid hormone stimuli were downregulated. The microarray data for key genes involved directly in steroidogenesis were confirmed by qPCR. Thus, when compared with that of the males, in the female ZF/R, higher expression levels of genes involved directly in steroid hormone synthesis were accompanied by lower

  4. Genome Array on Differentially Expressed Genes of Skin Tissue in Cashmere Goat at Early Anagen of Cashmere Growth Cycle Using DNA Microarray

    Institute of Scientific and Technical Information of China (English)

    DI Jiang; Marzeya Yasen; XU Xin-ming; Lazate Ainiwaer; ZHANG Yan-hua; TIAN Ke-chuan; YU Li-juan; WU Wei-wei; Hanikezi Tulafu; FU Xue-feng

    2014-01-01

    In order to study the molecular mechanism involved in cashmere regeneration, this study investigated the gene expression proifle of skin tissue at various stages of the cashmere growth cycle and screen differentially expressed genes at proangen in 10 cashmere goats at 2 years of age using agilent sheep oligo microarray. Signiifcance analysis of microarray (SAM) methods was used to identify the differentially expressed genes, Hierarchical clustering was performed to clarify these genes in association with different cashmere growth stages, and GO (Gene ontology) and the pathway analyses were con-ducted by a free web-based Molecular Annotation System3.0 (MAS 3.0). Approximately 10 200 probe sets were detected in skin tissue of 2-yr-old cashmere goat. After SAM analysis of the microarray data, totally 417 genes were shown to be differentially expressed at different cashmere growth stages, and 24 genes are signiifcantly up-regulated (21) or down-regulated (3) at proangen concurrently compared to angen and telogen. Hierarchical clustering analysis clearly distinguished the differentially expressed genes of each stage. GO analysis indicated that these altered genes at proangen were predominantly involved in collagen ifbril organization, integrin-mediated signaling pathway, cell-matrix adhesion, cell adhesion, transforming growth factor-β (TGF-β) receptor signaling pathway, regulation of cell growth. Kyoto encyclopedia of genes and genomes (KEGG) analysis showed that the signiifcant pathways involved mainly included focal adhesion and extracellular matrixc (ECM)-receptor interaction. Some important genes involved in these biological processes, such as COL1A1, COL1A2, COL3A1, SPARC, CYR61 and CTGF, were related to tissue remolding and repairing and detected by more than one probe with similar expression trends at different stages of cashmere growth cycle. The different expression of these genes may contribute to understanding the molecular mechanism of cashmere

  5. A regression-based differential expression detection algorithm for microarray studies with ultra-low sample size.

    Science.gov (United States)

    Vasiliu, Daniel; Clamons, Samuel; McDonough, Molly; Rabe, Brian; Saha, Margaret

    2015-01-01

    Global gene expression analysis using microarrays and, more recently, RNA-seq, has allowed investigators to understand biological processes at a system level. However, the identification of differentially expressed genes in experiments with small sample size, high dimensionality, and high variance remains challenging, limiting the usability of these tens of thousands of publicly available, and possibly many more unpublished, gene expression datasets. We propose a novel variable selection algorithm for ultra-low-n microarray studies using generalized linear model-based variable selection with a penalized binomial regression algorithm called penalized Euclidean distance (PED). Our method uses PED to build a classifier on the experimental data to rank genes by importance. In place of cross-validation, which is required by most similar methods but not reliable for experiments with small sample size, we use a simulation-based approach to additively build a list of differentially expressed genes from the rank-ordered list. Our simulation-based approach maintains a low false discovery rate while maximizing the number of differentially expressed genes identified, a feature critical for downstream pathway analysis. We apply our method to microarray data from an experiment perturbing the Notch signaling pathway in Xenopus laevis embryos. This dataset was chosen because it showed very little differential expression according to limma, a powerful and widely-used method for microarray analysis. Our method was able to detect a significant number of differentially expressed genes in this dataset and suggest future directions for investigation. Our method is easily adaptable for analysis of data from RNA-seq and other global expression experiments with low sample size and high dimensionality.

  6. A regression-based differential expression detection algorithm for microarray studies with ultra-low sample size.

    Directory of Open Access Journals (Sweden)

    Daniel Vasiliu

    Full Text Available Global gene expression analysis using microarrays and, more recently, RNA-seq, has allowed investigators to understand biological processes at a system level. However, the identification of differentially expressed genes in experiments with small sample size, high dimensionality, and high variance remains challenging, limiting the usability of these tens of thousands of publicly available, and possibly many more unpublished, gene expression datasets. We propose a novel variable selection algorithm for ultra-low-n microarray studies using generalized linear model-based variable selection with a penalized binomial regression algorithm called penalized Euclidean distance (PED. Our method uses PED to build a classifier on the experimental data to rank genes by importance. In place of cross-validation, which is required by most similar methods but not reliable for experiments with small sample size, we use a simulation-based approach to additively build a list of differentially expressed genes from the rank-ordered list. Our simulation-based approach maintains a low false discovery rate while maximizing the number of differentially expressed genes identified, a feature critical for downstream pathway analysis. We apply our method to microarray data from an experiment perturbing the Notch signaling pathway in Xenopus laevis embryos. This dataset was chosen because it showed very little differential expression according to limma, a powerful and widely-used method for microarray analysis. Our method was able to detect a significant number of differentially expressed genes in this dataset and suggest future directions for investigation. Our method is easily adaptable for analysis of data from RNA-seq and other global expression experiments with low sample size and high dimensionality.

  7. Microarray analysis of inflammatory response-related gene expression in the uteri of dogs with pyometra.

    Science.gov (United States)

    Bukowska, D; Kempisty, B; Zawierucha, P; Jopek, K; Piotrowska, H; Antosik, P; Ciesiółka, S; Woźna, M; Brüssow, K P; Jaśkowski, J M

    2014-01-01

    Pyometra, which is accompanied by bacterial contamination of the uterus, is defined as a complex disease associated with the activation of several systems, including the immune system. The objective of the study was to evaluate the gene expression profile in dogs with pyometra compared with those that were clinically normal. The study included uteri from 43 mongrel bitches (23 with pyometra, 20 clinically healthy). RNA used for the microarray study was pooled to four separated vials for control and pyometra. A total of 17,138 different transcripts were analyzed on the uteri of female dogs with pyometra and of healthy controls. From 264 inflammatory response-related transcripts, we found 23 transcripts that revealed a 10- to 77-fold increased expression. Thereby, the expression of interleukin 8 (IL8), interleukin-1-beta (IL1B), interleukin 18 receptor (IL18RAP), interleukin 1-alpha (IL1A), interleukin receptor antagonist (IL1RN) and interleukin 6 (IL6) increased 77-, 20-, 17-, 13-, 13- and 11-fold, respectively. Furthermore, the expression of the calcium binding proteins S100A8 was 44-fold higher, and that of S100A12 and S100A9 37-fold, respectively, in the uteri of canines with pyometra compared with that of the controls. Moreover, the expression of the transcripts of toll-like receptors (TLR8 and TLR2), integrin beta 2 (ITGB2), chemokine ligand 3 (CCL3), semaphorin 7A (SEMA7A), CD14 and prostaglandin-endoperoxide synthase 2 (PTGS2) was increased between 10- and 18-fold. Furthermore, after using RT-qPCR we found an increased expression of AOAH, IL1A, IL8, CCL3, IL1RN and SERPINE 1 mRNAs which can be served also as markers of the occurrence of pyometra in domestic bitches. In summary, it is concluded that up-regulation of interleukins may be used as a marker of the inflammatory response in dogs with pyometra. Moreover, all of the 23 up-regulated transcripts may be novel molecular markers of the pathogenesis of canine pyometra. Several proteins--–products of these

  8. The Current Status of DNA Microarrays

    Science.gov (United States)

    Shi, Leming; Perkins, Roger G.; Tong, Weida

    DNA microarray technology that allows simultaneous assay of thousands of genes in a single experiment has steadily advanced to become a mainstream method used in research, and has reached a stage that envisions its use in medical applications and personalized medicine. Many different strategies have been developed for manufacturing DNA microarrays. In this chapter, we discuss the manufacturing characteristics of seven microarray platforms that were used in a recently completed large study by the MicroArray Quality Control (MAQC) consortium, which evaluated the concordance of results across these platforms. The platforms can be grouped into three categories: (1) in situ synthesis of oligonucleotide probes on microarrays (Affymetrix GeneChip® arrays based on photolithography synthesis and Agilent's arrays based on inkjet synthesis); (2) spotting of presynthesized oligonucleotide probes on microarrays (GE Healthcare's CodeLink system, Applied Biosystems' Genome Survey Microarrays, and the custom microarrays printed with Operon's oligonucleotide set); and (3) deposition of presynthesized oligonucleotide probes on bead-based microarrays (Illumina's BeadChip microarrays). We conclude this chapter with our views on the challenges and opportunities toward acceptance of DNA microarray data in clinical and regulatory settings.

  9. Early changes in gene expression profiles of hepatic GVHD uncovered by oligonucleotide microarrays.

    Science.gov (United States)

    Ichiba, Tamotsu; Teshima, Takanori; Kuick, Rork; Misek, David E; Liu, Chen; Takada, Yuichiro; Maeda, Yoshinobu; Reddy, Pavan; Williams, Debra L; Hanash, Samir M; Ferrara, James L M

    2003-07-15

    The liver, skin, and gastrointestinal tract are major target organs of acute graft-versus-host disease (GVHD), the major complication of allogeneic bone marrow transplantation (BMT). In order to gain a better understanding of acute GVHD in the liver, we compared the gene expression profiles of livers after experimental allogeneic and syngeneic BMT using oligonucleotide microarray. At 35 days after allogeneic BMT when hepatic GVHD was histologically evident, genes related to cellular effectors and acute-phase proteins were up-regulated, whereas genes largely related to metabolism and endocrine function were down-regulated. At day 7 after BMT before the development of histologic changes in the liver, interferon gamma (IFN-gamma)-inducible genes, major histocompatibility (MHC) class II molecules, and genes related to leukocyte trafficking had been up-regulated. Immunohistochemistry demonstrated that expression of IFN-gamma protein itself was increased in the spleen but not in hepatic tissue. These results suggest that the increased expression of genes associated with the attraction and activation of donor T cells induced by IFN-gamma early after BMT is important in the initiation of hepatic GVHD in this model and provide new potential molecular targets for early detection and intervention of acute GVHD.

  10. 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.

  11. Missing value imputation for microarray gene expression data using histone acetylation information

    Directory of Open Access Journals (Sweden)

    Feng Jihua

    2008-05-01

    Full Text Available Abstract Background It is an important pre-processing step to accurately estimate missing values in microarray data, because complete datasets are required in numerous expression profile analysis in bioinformatics. Although several methods have been suggested, their performances are not satisfactory for datasets with high missing percentages. Results The paper explores the feasibility of doing missing value imputation with the help of gene regulatory mechanism. An imputation framework called histone acetylation information aided imputation method (HAIimpute method is presented. It incorporates the histone acetylation information into the conventional KNN(k-nearest neighbor and LLS(local least square imputation algorithms for final prediction of the missing values. The experimental results indicated that the use of acetylation information can provide significant improvements in microarray imputation accuracy. The HAIimpute methods consistently improve the widely used methods such as KNN and LLS in terms of normalized root mean squared error (NRMSE. Meanwhile, the genes imputed by HAIimpute methods are more correlated with the original complete genes in terms of Pearson correlation coefficients. Furthermore, the proposed methods also outperform GOimpute, which is one of the existing related methods that use the functional similarity as the external information. Conclusion We demonstrated that the using of histone acetylation information could greatly improve the performance of the imputation especially at high missing percentages. This idea can be generalized to various imputation methods to facilitate the performance. Moreover, with more knowledge accumulated on gene regulatory mechanism in addition to histone acetylation, the performance of our approach can be further improved and verified.

  12. Gene expression profiling in gill tissues of White spot syndrome virus infected black tiger shrimp Penaeus monodon by DNA microarray.

    Science.gov (United States)

    Shekhar, M S; Gomathi, A; Gopikrishna, G; Ponniah, A G

    2015-06-01

    White spot syndrome virus (WSSV) continues to be the most devastating viral pathogen infecting penaeid shrimp the world over. The genome of WSSV has been deciphered and characterized from three geographical isolates and significant progress has been made in developing various molecular diagnostic methods to detect the virus. However, the information on host immune gene response to WSSV pathogenesis is limited. Microarray analysis was carried out as an approach to analyse the gene expression in black tiger shrimp Penaeus monodon in response to WSSV infection. Gill tissues collected from the WSSV infected shrimp at 6, 24, 48 h and moribund stage were analysed for differential gene expression. Shrimp cDNAs of 40,059 unique sequences were considered for designing the microarray chip. The Cy3-labeled cRNA derived from healthy and WSSV-infected shrimp was subjected to hybridization with all the DNA spots in the microarray which revealed 8,633 and 11,147 as up- and down-regulated genes respectively at different time intervals post infection. The altered expression of these numerous genes represented diverse functions such as immune response, osmoregulation, apoptosis, nucleic acid binding, energy and metabolism, signal transduction, stress response and molting. The changes in gene expression profiles observed by microarray analysis provides molecular insights and framework of genes which are up- and down-regulated at different time intervals during WSSV infection in shrimp. The microarray data was validated by Real Time analysis of four differentially expressed genes involved in apoptosis (translationally controlled tumor protein, inhibitor of apoptosis protein, ubiquitin conjugated enzyme E2 and caspase) for gene expression levels. The role of apoptosis related genes in WSSV infected shrimp is discussed herein.

  13. Combining metabolomic analysis and microarray gene expression analysis in the characterization of the medicinal plant Chelidonium majus L.

    Science.gov (United States)

    Orland, A; Knapp, K; König, G M; Ulrich-Merzenich, G; Knöß, W

    2014-10-15

    Even though herbal medicines have played an important role in disease management and health for many centuries, their present frequent use is challenged by the necessity to determine their complex composition and their multitarget mode of action. In the present study, modern methods were investigated towards their potential in the characterization of herbal substances. As a model the herbal substance Chelidonii herba was used, for which several reports on liver toxicities exist. Extracts of Chelidonii herba with different solvents were characterized phytochemically and functionally by experiments with HepG2 liver cells. Chelidonii herba was extracted with four solvents of different polarity (dichloromethane, water, ethanol, and ethanol 50% (V/V); four replicates each). The different extracts were characterized metabolomically by (1)H-NMR fingerprinting analysis and principal component analysis (PCA). The content of alkaloids was additionally determined by RP-HPLC. Functional characterization was achieved by the determination of cell proliferation and by transcriptomics techniques (Whole Genome Gene Expression Microarrays v2, Agilent Technologies) in HepG2 cells after exposure to the different extracts (four experimental replicates each). Based on data from (1)H-NMR fingerprints and RP-HPLC analyses the different extracts showed a divergent composition of constituents depending on the solvent used. HepG2 liver cells responded differentially to the four extracts. Microarray analysis revealed a significant regulation of genes and signal cascades related to biotransformation. Also liver-toxic signal cascades were activated. Neither the activated genes nor the proliferation response could be clearly related to the differing alkaloid content of the extracts. Different manufacturing processes lead to different herbal preparations. A systems biology approach combining a metabolomic plant analysis with a functional characterization by gene expression profiling in HepG2

  14. Development of a cDNA microarray for the measurement of gene expression in the sheep scab mite Psoroptes ovis

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    Burgess Stewart TG

    2012-02-01

    Full Text Available Abstract Background Sheep scab is caused by the ectoparasitic mite Psoroptes ovis which initiates a profound cutaneous inflammatory response, leading to the development of the skin lesions which are characteristic of the disease. Existing control strategies rely upon injectable endectocides and acaricidal dips but concerns over residues, eco-toxicity and the development of acaricide resistance limit the sustainability of this approach. In order to identify alternative means of disease control, a deeper understanding of both the parasite and its interaction with the host are required. Methods Herein we describe the development and utilisation of an annotated P. ovis cDNA microarray containing 3,456 elements for the measurement of gene expression in this economically important ectoparasite. The array consists of 981 P. ovis EST sequences printed in triplicate along with 513 control elements. Array performance was validated through the analysis of gene expression differences between fed and starved P. ovis mites. Results Sequences represented on the array include homologues of major house dust mite allergens and tick salivary proteins, along with factors potentially involved in mite reproduction and xenobiotic metabolism. In order to validate the performance of this unique resource under biological conditions we used the array to analyse gene expression differences between fed and starved P. ovis mites. These analyses identified a number of house dust mite allergen homologues up-regulated in fed mites and P. ovis transcripts involved in stress responses, autophagy and chemosensory perception up-regulated in starved mites. Conclusion The P. ovis cDNA microarray described here has been shown to be both robust and reproducible and will enable future studies to analyse gene expression in this important ectoparasite.

  15. Prediction of optimal gene functions for osteosarcoma using network-based- guilt by association method based on gene oncology and microarray profile.

    Science.gov (United States)

    Chen, Xinrang

    2017-06-01

    In the current study, we planned to predict the optimal gene functions for osteosarcoma (OS) by integrating network-based method with guilt by association (GBA) principle (called as network-based gene function inference approach) based on gene oncology (GO) data and gene expression profile. To begin with, differentially expressed genes (DEGs) were extracted using linear models for microarray data (LIMMA) package. Then, construction of differential co-expression network (DCN) relying on DEGs was implemented, and sub-DCN was identified using Spearman correlation coefficient (SCC). Subsequently, GO annotations for OS were collected according to known confirmed database and DEGs. Ultimately, gene functions were predicted by means of GBA principle based on the area under the curve (AUC) for GO terms, and we determined GO terms with AUC >0.7 as the optimal gene functions for OS. Totally, 123 DEGs and 137 GO terms were obtained for further analysis. A DCN was constructed, which included 123 DEGs and 7503 interactions. A total of 105 GO terms were identified when the threshold was set as AUC >0.5, which had a good classification performance. Among these 105 GO terms, 2 functions had the AUC >0.7 and were determined as the optimal gene functions including angiogenesis (AUC =0.767) and regulation of immune system process (AUC =0.710). These gene functions appear to have potential for early detection and clinical treatment of OS in the future.

  16. Uncovering potential key genes associated with the pathogenesis of asthma: A microarray analysis of asthma-relevant tissues.

    Science.gov (United States)

    Guan, Y; Jin, X; Liu, X; Huang, Y; Wang, M; Li, X

    The present study aimed to discover more potential genes associated with the pathogenesis of asthma. The microarray data of GSE67940 was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified in bronchial alveolar lavage cells from patients with mild-moderate asthma (notSA) and severe asthma (SA) compared with normal controls (NC), respectively. Functional and pathway enrichment analysis, protein-protein interaction (PPI) network analysis were performed upon the identified up- and down-regulated DEGs. Besides, the gene association network based on the common up-regulated and down-regulated genes was generated and transcriptional regulatory pairs of overlapping DEGs in the PPI network were identified. A total of 104 DEGs (30 up- and 74 down-regulated genes) were identified in notSA vs. NC. Additionally, 2796 DEGs were screened out in SA vs. NC group, including 320 up-regulated DEGs, and 135 down-regulated DEGs. Specially, 41 overlapping DEGs were screened out in notSA vs. NC and SA vs. NC, including 16 common up-regulated genes and 25 common down-regulated genes. No pathways were enriched by the DEGs in notSA vs. NC. DEGs in SA vs. NC were associated with cytokine-cytokine receptor interaction. VEGFA was a hub protein in both the PPI networks of DEGs in notSA vs. NC and SA vs. NC. Gene association network showed that signalling pathways and cytokine-cytokine receptor interaction were involved in. The overlapping VEGFA, and IFRD1, and ZNF331 were regulated by more TFs. Genes such as VEGFA, and IFRD1, and ZNF331 may be associated with pathogenesis of asthma. Copyright © 2016 SEICAP. Published by Elsevier España, S.L.U. All rights reserved.

  17. Development of a Pacific oyster (Crassostrea gigas) 31,918-feature microarray: identification of reference genes and tissue-enriched expression patterns

    Science.gov (United States)

    2011-01-01

    Background Research using the Pacific oyster Crassostrea gigas as a model organism has experienced rapid growth in recent years due to the development of high-throughput molecular technologies. As many as 56,268 EST sequences have been sequenced to date, representing a genome-wide resource that can be used for transcriptomic investigations. Results In this paper, we developed a Pacific oyster microarray containing oligonucleotides representing 31,918 transcribed sequences selected from the publicly accessible GigasDatabase. This newly designed microarray was used to study the transcriptome of male and female gonads, mantle, gills, posterior adductor muscle, visceral ganglia, hemocytes, labial palps and digestive gland. Statistical analyses identified genes differentially expressed among tissues and clusters of tissue-enriched genes. These genes reflect major tissue-specific functions at the molecular level, such as tissue formation in the mantle, filtering in the gills and labial palps, and reproduction in the gonads. Hierarchical clustering predicted the involvement of unannotated genes in specific functional pathways such as the insulin/NPY pathway, an important pathway under study in our model species. Microarray data also accurately identified reference genes whose mRNA level appeared stable across all the analyzed tissues. Adp-ribosylation factor 1 (arf1) appeared to be the most robust reference for normalizing gene expression data across different tissues and is therefore proposed as a relevant reference gene for further gene expression analysis in the Pacific oyster. Conclusions This study provides a new transcriptomic tool for studies of oyster biology, which will help in the annotation of its genome and which identifies candidate reference genes for gene expression analysis. PMID:21951653

  18. Literature-aided meta-analysis of microarray data: a compendium study on muscle development and disease

    Directory of Open Access Journals (Sweden)

    van Ommen Gert-Jan B

    2008-06-01

    Full Text Available Abstract Background Comparative analysis of expression microarray studies is difficult due to the large influence of technical factors on experimental outcome. Still, the identified differentially expressed genes may hint at the same biological processes. However, manually curated assignment of genes to biological processes, such as pursued by the Gene Ontology (GO consortium, is incomplete and limited. We hypothesised that automatic association of genes with biological processes through thesaurus-controlled mining of Medline abstracts would be more effective. Therefore, we developed a novel algorithm (LAMA: Literature-Aided Meta-Analysis to quantify the similarity between transcriptomics studies. We evaluated our algorithm on a large compendium of 102 microarray studies published in the field of muscle development and disease, and compared it to similarity measures based on gene overlap and over-representation of biological processes assigned by GO. Results While the overlap in both genes and overrepresented GO-terms was poor, LAMA retrieved many more biologically meaningful links between studies, with substantially lower influence of technical factors. LAMA correctly grouped muscular dystrophy, regeneration and myositis studies, and linked patient and corresponding mouse model studies. LAMA also retrieves the connecting biological concepts. Among other new discoveries, we associated cullin proteins, a class of ubiquitinylation proteins, with genes down-regulated during muscle regeneration, whereas ubiquitinylation was previously reported to be activated during the inverse process: muscle atrophy. Conclusion Our literature-based association analysis is capable of finding hidden common biological denominators in microarray studies, and circumvents the need for raw data analysis or curated gene annotation databases.

  19. A meta-analysis of public microarray data identifies gene regulatory pathways deregulated in peripheral blood mononuclear cells from individuals with Systemic Lupus Erythematosus compared to those without.

    Science.gov (United States)

    Kröger, Wendy; Mapiye, Darlington; Entfellner, Jean-Baka Domelevo; Tiffin, Nicki

    2016-11-15

    Systemic Lupus Erythematosus (SLE) is a complex, multi-systemic, autoimmune disease for which the underlying aetiological mechanisms are poorly understood. The genetic and molecular processes underlying lupus have been extensively investigated using a variety of -omics approaches, including genome-wide association studies, candidate gene studies and microarray experiments of differential gene expression in lupus samples compared to controls. This study analyses a combination of existing microarray data sets to identify differentially regulated genetic pathways that are dysregulated in human peripheral blood mononuclear cells from SLE patients compared to unaffected controls. Two statistical approaches, quantile discretisation and scaling, are used to combine publicly available expression microarray datasets and perform a meta-analysis of differentially expressed genes. Differentially expressed genes implicated in interferon signaling were identified by the meta-analysis, in agreement with the findings of the individual studies that generated the datasets used. In contrast to the individual studies, however, the meta-analysis and subsequent pathway analysis additionally highlighted TLR signaling, oxidative phosphorylation and diapedesis and adhesion regulatory networks as being differentially regulated in peripheral blood mononuclear cells (PBMCs) from SLE patients compared to controls. Our analysis demonstrates that it is possible to derive additional information from publicly available expression data using meta-analysis techniques, which is particularly relevant to research into rare diseases where sample numbers can be limiting.

  20. Microarray analysis of genes differentially expressed in HepG2 cells cultured in simulated microgravity: preliminary report

    Science.gov (United States)

    Khaoustov, V. I.; Risin, D.; Pellis, N. R.; Yoffe, B.; McIntire, L. V. (Principal Investigator)

    2001-01-01

    Developed at NASA, the rotary cell culture system (RCCS) allows the creation of unique microgravity environment of low shear force, high-mass transfer, and enables three-dimensional (3D) cell culture of dissimilar cell types. Recently we demonstrated that a simulated microgravity is conducive for maintaining long-term cultures of functional hepatocytes and promote 3D cell assembly. Using deoxyribonucleic acid (DNA) microarray technology, it is now possible to measure the levels of thousands of different messenger ribonucleic acids (mRNAs) in a single hybridization step. This technique is particularly powerful for comparing gene expression in the same tissue under different environmental conditions. The aim of this research was to analyze gene expression of hepatoblastoma cell line (HepG2) during early stage of 3D-cell assembly in simulated microgravity. For this, mRNA from HepG2 cultured in the RCCS was analyzed by deoxyribonucleic acid microarray. Analyses of HepG2 mRNA by using 6K glass DNA microarray revealed changes in expression of 95 genes (overexpression of 85 genes and downregulation of 10 genes). Our preliminary results indicated that simulated microgravity modifies the expression of several genes and that microarray technology may provide new understanding of the fundamental biological questions of how gravity affects the development and function of individual cells.

  1. Time-course microarray analysis for identifying candidate genes involved in obesity-associated pathological changes in the mouse colon.

    Science.gov (United States)

    Bae, Yun Jung; Kim, Sung-Eun; Hong, Seong Yeon; Park, Taesun; Lee, Sang Gyu; Choi, Myung-Sook; Sung, Mi-Kyung

    2016-01-01

    Obesity is known to increase the risk of colorectal cancer. However, mechanisms underlying the pathogenesis of obesity-induced colorectal cancer are not completely understood. The purposes of this study were to identify differentially expressed genes in the colon of mice with diet-induced obesity and to select candidate genes as early markers of obesity-associated abnormal cell growth in the colon. C57BL/6N mice were fed normal diet (11% fat energy) or high-fat diet (40% fat energy) and were euthanized at different time points. Genome-wide expression profiles of the colon were determined at 2, 4, 8, and 12 weeks. Cluster analysis was performed using expression data of genes showing log2 fold change of ≥1 or ≤-1 (twofold change), based on time-dependent expression patterns, followed by virtual network analysis. High-fat diet-fed mice showed significant increase in body weight and total visceral fat weight over 12 weeks. Time-course microarray analysis showed that 50, 47, 36, and 411 genes were differentially expressed at 2, 4, 8, and 12 weeks, respectively. Ten cluster profiles representing distinguishable patterns of genes differentially expressed over time were determined. Cluster 4, which consisted of genes showing the most significant alterations in expression in response to high-fat diet over 12 weeks, included Apoa4 (apolipoprotein A-IV), Ppap2b (phosphatidic acid phosphatase type 2B), Cel (carboxyl ester lipase), and Clps (colipase, pancreatic), which interacted strongly with surrounding genes associated with colorectal cancer or obesity. Our data indicate that Apoa4, Ppap2b, Cel, and Clps are candidate early marker genes associated with obesity-related pathological changes in the colon. Genome-wide analyses performed in the present study provide new insights on selecting novel genes that may be associated with the development of diseases of the colon.

  2. Microarray Expression Data Identify DCC as a Candidate Gene for Early Meningioma Progression.

    Science.gov (United States)

    Schulten, Hans-Juergen; Hussein, Deema; Al-Adwani, Fatima; Karim, Sajjad; Al-Maghrabi, Jaudah; Al-Sharif, Mona; Jamal, Awatif; Al-Ghamdi, Fahad; Baeesa, Saleh S; Bangash, Mohammed; Chaudhary, Adeel; Al-Qahtani, Mohammed

    2016-01-01

    Meningiomas are the most common primary brain tumors bearing in a minority of cases an aggressive phenotype. Although meningiomas are stratified according to their histology and clinical behavior, the underlying molecular genetics predicting aggressiveness are not thoroughly understood. We performed whole transcript expression profiling in 10 grade I and four grade II meningiomas, three of which invaded the brain. Microarray expression analysis identified deleted in colorectal cancer (DCC) as a differentially expressed gene (DEG) enabling us to cluster meningiomas into DCC low expression (3 grade I and 3 grade II tumors), DCC medium expression (2 grade I and 1 grade II tumors), and DCC high expression (5 grade I tumors) groups. Comparison between the DCC low expression and DCC high expression groups resulted in 416 DEGs (p-value2). The most significantly downregulated genes in the DCC low expression group comprised DCC, phosphodiesterase 1C (PDE1C), calmodulin-dependent 70kDa olfactomedin 2 (OLFM2), glutathione S-transferase mu 5 (GSTM5), phosphotyrosine interaction domain containing 1 (PID1), sema domain, transmembrane domain (TM) and cytoplasmic domain, (semaphorin) 6D (SEMA6D), and indolethylamine N-methyltransferase (INMT). The most significantly upregulated genes comprised chromosome 5 open reading frame 63 (C5orf63), homeodomain interacting protein kinase 2 (HIPK2), and basic helix-loop-helix family, member e40 (BHLHE40). Biofunctional analysis identified as predicted top upstream regulators beta-estradiol, TGFB1, Tgf beta complex, LY294002, and dexamethasone and as predicted top regulator effectors NFkB, PIK3R1, and CREBBP. The microarray expression data served also for a comparison between meningiomas from female and male patients and for a comparison between brain invasive and non-invasive meningiomas resulting in a number of significant DEGs and related biofunctions. In conclusion, based on its expression levels, DCC may constitute a valid biomarker to

  3. Genetic targets of hydrogen sulfide in ventilator-induced lung injury--a microarray study.

    Directory of Open Access Journals (Sweden)

    Sashko Spassov

    Full Text Available Recently, we have shown that inhalation of hydrogen sulfide (H2S protects against ventilator-induced lung injury (VILI. In the present study, we aimed to determine the underlying molecular mechanisms of H2S-dependent lung protection by analyzing gene expression profiles in mice. C57BL/6 mice were subjected to spontaneous breathing or mechanical ventilation in the absence or presence of H2S (80 parts per million. Gene expression profiles were determined by microarray, sqRT-PCR and Western Blot analyses. The association of Atf3 in protection against VILI was confirmed with a Vivo-Morpholino knockout model. Mechanical ventilation caused a significant lung inflammation and damage that was prevented in the presence of H2S. Mechanical ventilation favoured the expression of genes involved in inflammation, leukocyte activation and chemotaxis. In contrast, ventilation with H2S activated genes involved in extracellular matrix remodelling, angiogenesis, inhibition of apoptosis, and inflammation. Amongst others, H2S administration induced Atf3, an anti-inflammatory and anti-apoptotic regulator. Morpholino mediated reduction of Atf3 resulted in elevated lung injury despite the presence of H2S. In conclusion, lung protection by H2S during mechanical ventilation is associated with down-regulation of genes related to oxidative stress and inflammation and up-regulation of anti-apoptotic and anti-inflammatory genes. Here we show that Atf3 is clearly involved in H2S mediated protection.

  4. Microarray screening for target genes of the proto-oncogene PLAG1.

    Science.gov (United States)

    Voz, Marianne L; Mathys, Janick; Hensen, Karen; Pendeville, Hélène; Van Valckenborgh, Isabelle; Van Huffel, Christophe; Chavez, Marcela; Van Damme, Boudewijn; De Moor, Bart; Moreau, Yves; Van de Ven, Wim J M

    2004-01-08

    PLAG1 is a proto-oncogene whose ectopic expression can trigger the development of pleomorphic adenomas of the salivary glands and of lipoblastomas. As PLAG1 is a transcription factor, able to activate transcription through the binding to the consensus sequence GRGGC(N)(6-8)GGG, its ectopic expression presumably results in the deregulation of target genes, leading to uncontrolled cell proliferation. The identification of PLAG1 target genes is therefore a crucial step in understanding the molecular mechanisms involved in PLAG1-induced tumorigenesis. To this end, we analysed the changes in gene expression caused by the conditional induction of PLAG1 expression in fetal kidney 293 cell lines. Using oligonucleotide microarray analyses of about 12 000 genes, we consistently identified 47 genes induced and 12 genes repressed by PLAG1. One of the largest classes identified as upregulated PLAG1 targets consists of growth factors such as the insulin-like growth factor II and the cytokine-like factor 1. The in silico search for PLAG1 consensus sequences in the promoter of the upregulated genes reveals that a large proportion of them harbor several copies of the PLAG1-binding motif, suggesting that they represent direct PLAG1 targets. Our approach was complemented by the comparison of the expression profiles of pleomorphic adenomas induced by PLAG1 versus normal salivary glands. Concordance between these two sets of experiments pinpointed 12 genes that were significantly and consistently upregulated in pleomorphic adenomas and in PLAG1-expressing cells, identifying them as putative PLAG1 targets in these tumors.

  5. Identification of new reference genes for the normalisation of canine osteoarthritic joint tissue transcripts from microarray data

    Directory of Open Access Journals (Sweden)

    Clements Dylan N

    2007-07-01

    Full Text Available Abstract Background Real-time reverse transcriptase quantitative polymerase chain reaction (real-time RT-qPCR is the most accurate measure of gene expression in biological systems. The comparison of different samples requires the transformation of data through a process called normalisation. Reference or housekeeping genes are candidate genes which are selected on the basis of constitutive expression across samples, and allow the quantification of changes in gene expression. At present, no reference gene has been identified for any organism which is universally optimal for use across different tissue types or disease situations. We used microarray data to identify new reference genes generated from total RNA isolated from normal and osteoarthritic canine articular tissues (bone, ligament, cartilage, synovium and fat. RT-qPCR assays were designed and applied to each different articular tissue. Reference gene expression stability and ranking was compared using three different mathematical algorithms. Results Twelve new potential reference genes were identified from microarray data. One gene (mitochondrial ribosomal protein S7 [MRPS7] was stably expressed in all five of the articular tissues evaluated. One gene HIRA interacting protein 5 isoform 2 [HIRP5] was stably expressed in four of the tissues evaluated. A commonly used reference gene glyceraldehyde-3-phosphate dehydrogenase (GAPDH was not stably expressed in any of the tissues evaluated. Most consistent agreement between rank ordering of reference genes was observed between Bestkeeper© and geNorm, although each method tended to agree on the identity of the most stably expressed genes and the least stably expressed genes for each tissue. New reference genes identified using microarray data normalised in a conventional manner were more stable than those identified by microarray data normalised by using a real-time RT-qPCR methodology. Conclusion Microarray data normalised by a conventional

  6. RNA expression microarrays (REMs), a high-throughput method to measure differences in gene expression in diverse biological samples

    OpenAIRE

    2004-01-01

    We have developed RNA expression microarrays (REMs), in which each spot on a glass support is composed of a population of cDNAs synthesized from a cell or tissue sample. We used simultaneous hybridization with test and reference (housekeeping) genes to calculate an expression ratio based on normalization with the endogenous reference gene. A test REM containing artificial mixtures of liver cDNA and dilutions of the bacterial LysA gene cDNA demonstrated the feasibility of detecting transcripts...

  7. Microarrays, Integrated Analytical Systems

    Science.gov (United States)

    Combinatorial chemistry is used to find materials that form sensor