The Prognostic Role of Androgen Receptor in Patients with Early-Stage Breast Cancer: A Meta-analysis of Clinical and Gene Expression Data.

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Bozovic-Spasojevic, Ivana; Zardavas, Dimitrios; Brohée, Sylvain; Ameye, Lieveke; Fumagalli, Debora; Ades, Felipe; de Azambuja, Evandro; Bareche, Yacine; Piccart, Martine; Paesmans, Marianne; Sotiriou, Christos

2017-06-01

Purpose: Androgen receptor (AR) expression has been observed in about 70% of patients with breast cancer, but its prognostic role remains uncertain. Experimental Design: To assess the prognostic role of AR expression in early-stage breast cancer, we performed a meta-analysis of studies that evaluated the impact of AR at the protein and gene expression level on disease-free survival (DFS) and/or overall survival (OS). Eligible studies were identified by systematic review of electronic databases using the MeSH-terms "breast neoplasm" and "androgen receptor" and were selected after a qualitative assessment based on the REMARK criteria. A pooled gene expression analysis of 35 publicly available microarray data sets was also performed from patients with early-stage breast cancer with available gene expression and clinical outcome data. Results: Twenty-two of 33 eligible studies for the clinical meta-analysis, including 10,004 patients, were considered as evaluable for the current study after the qualitative assessment. AR positivity defined by IHC was associated with improved DFS in all patients with breast cancer [multivariate (M) analysis, HR 0.46; 95% confidence interval (CI) 0.37-0.58, P expression analysis. High AR mRNA levels were found to confer positive prognosis overall in terms of DFS (HR 0.82; 95% CI 0.72-0.92; P = 0.0007) and OS (HR 0.84; 95% CI, 0.75-0.94; P = 0.02) only in univariate analysis. Conclusions: Our analysis, conducted among more than 17,000 women with early-stage breast cancer included in clinical and gene expression analysis, demonstrates that AR positivity is associated with favorable clinical outcome. Clin Cancer Res; 23(11); 2702-12. ©2016 AACR . ©2016 American Association for Cancer Research.

Cross-study analysis of gene expression data for intermediate neuroblastoma identifies two biological subtypes

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Warnat, Patrick; Oberthuer, André; Fischer, Matthias; Westermann, Frank; Eils, Roland; Brors, Benedikt

2007-01-01

Neuroblastoma patients show heterogeneous clinical courses ranging from life-threatening progression to spontaneous regression. Recently, gene expression profiles of neuroblastoma tumours were associated with clinically different phenotypes. However, such data is still rare for important patient subgroups, such as patients with MYCN non-amplified advanced stage disease. Prediction of the individual course of disease and optimal therapy selection in this cohort is challenging. Additional research effort is needed to describe the patterns of gene expression in this cohort and to identify reliable prognostic markers for this subset of patients. We combined gene expression data from two studies in a meta-analysis in order to investigate differences in gene expression of advanced stage (3 or 4) tumours without MYCN amplification that show contrasting outcomes (alive or dead) at five years after initial diagnosis. In addition, a predictive model for outcome was generated. Gene expression profiles from 66 patients were included from two studies using different microarray platforms. In the combined data set, 72 genes were identified as differentially expressed by meta-analysis at a false discovery rate (FDR) of 8.33%. Meta-analysis detected 34 differentially expressed genes that were not found as significant in either single study. Outcome prediction based on data of both studies resulted in a predictive accuracy of 77%. Moreover, the genes that were differentially expressed in subgroups of advanced stage patients without MYCN amplification accurately separated MYCN amplified tumours from low stage tumours without MYCN amplification. Our findings support the hypothesis that neuroblastoma consists of two biologically distinct subgroups that differ by characteristic gene expression patterns, which are associated with divergent clinical outcome

Identification of cytokinin-responsive genes using microarray meta-analysis and RNA-Seq in Arabidopsis.

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Bhargava, Apurva; Clabaugh, Ivory; To, Jenn P; Maxwell, Bridey B; Chiang, Yi-Hsuan; Schaller, G Eric; Loraine, Ann; Kieber, Joseph J

2013-05-01

Cytokinins are N(6)-substituted adenine derivatives that play diverse roles in plant growth and development. We sought to define a robust set of genes regulated by cytokinin as well as to query the response of genes not represented on microarrays. To this end, we performed a meta-analysis of microarray data from a variety of cytokinin-treated samples and used RNA-seq to examine cytokinin-regulated gene expression in Arabidopsis (Arabidopsis thaliana). Microarray meta-analysis using 13 microarray experiments combined with empirically defined filtering criteria identified a set of 226 genes differentially regulated by cytokinin, a subset of which has previously been validated by other methods. RNA-seq validated about 73% of the up-regulated genes identified by this meta-analysis. In silico promoter analysis indicated an overrepresentation of type-B Arabidopsis response regulator binding elements, consistent with the role of type-B Arabidopsis response regulators as primary mediators of cytokinin-responsive gene expression. RNA-seq analysis identified 73 cytokinin-regulated genes that were not represented on the ATH1 microarray. Representative genes were verified using quantitative reverse transcription-polymerase chain reaction and NanoString analysis. Analysis of the genes identified reveals a substantial effect of cytokinin on genes encoding proteins involved in secondary metabolism, particularly those acting in flavonoid and phenylpropanoid biosynthesis, as well as in the regulation of redox state of the cell, particularly a set of glutaredoxin genes. Novel splicing events were found in members of some gene families that are known to play a role in cytokinin signaling or metabolism. The genes identified in this analysis represent a robust set of cytokinin-responsive genes that are useful in the analysis of cytokinin function in plants.

Gene Expression Meta-Analysis identifies Cytokine Pathways and 5q Aberrations involved in Metastasis of ERBB2 Amplified and Basal Breast Cancer

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Thomassen, Mads; Tan, Qihua; Burton, Mark

2013-01-01

Background: Breast tumors have been described by molecular subtypes characterized by pervasively different gene expression profiles. The subtypes are associated with different clinical parameters and origin of precursor cells. However, the biological pathways and chromosomal aberrations that differ...... the subgroups impact metastasis. Results: We have scrutinized publicly available gene expression datasets and identified molecular subtypes in 1,394 breast tumors with outcome data. By analysis of chromosomal regions and pathways using “Gene set enrichment analysis” followed by a meta-analysis, we identified...... between the subgroups are less well characterized. The molecular subtypes are associated with different risk of metastatic recurrence of the disease. Nevertheless, the performance of these overall patterns to predict outcome is far from optimal, suggesting that biological mechanisms that extend beyond...

Meta-analysis of Drosophila circadian microarray studies identifies a novel set of rhythmically expressed genes.

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Kevin P Keegan

2007-11-01

Full Text Available Five independent groups have reported microarray studies that identify dozens of rhythmically expressed genes in the fruit fly Drosophila melanogaster. Limited overlap among the lists of discovered genes makes it difficult to determine which, if any, exhibit truly rhythmic patterns of expression. We reanalyzed data from all five reports and found two sources for the observed discrepancies, the use of different expression pattern detection algorithms and underlying variation among the datasets. To improve upon the methods originally employed, we developed a new analysis that involves compilation of all existing data, application of identical transformation and standardization procedures followed by ANOVA-based statistical prescreening, and three separate classes of post hoc analysis: cross-correlation to various cycling waveforms, autocorrelation, and a previously described fast Fourier transform-based technique. Permutation-based statistical tests were used to derive significance measures for all post hoc tests. We find application of our method, most significantly the ANOVA prescreening procedure, significantly reduces the false discovery rate relative to that observed among the results of the original five reports while maintaining desirable statistical power. We identify a set of 81 cycling transcripts previously found in one or more of the original reports as well as a novel set of 133 transcripts not found in any of the original studies. We introduce a novel analysis method that compensates for variability observed among the original five Drosophila circadian array reports. Based on the statistical fidelity of our meta-analysis results, and the results of our initial validation experiments (quantitative RT-PCR, we predict many of our newly found genes to be bona fide cyclers, and suggest that they may lead to new insights into the pathways through which clock mechanisms regulate behavioral rhythms.

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

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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

Identification of conserved drought-adaptive genes using a cross-species meta-analysis approach.

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Shaar-Moshe, Lidor; Hübner, Sariel; Peleg, Zvi

2015-05-03

Drought is the major environmental stress threatening crop-plant productivity worldwide. Identification of new genes and metabolic pathways involved in plant adaptation to progressive drought stress at the reproductive stage is of great interest for agricultural research. We developed a novel Cross-Species meta-Analysis of progressive Drought stress at the reproductive stage (CSA:Drought) to identify key drought adaptive genes and mechanisms and to test their evolutionary conservation. Empirically defined filtering criteria were used to facilitate a robust integration of 17 deposited microarray experiments (148 arrays) of Arabidopsis, rice, wheat and barley. By prioritizing consistency over intensity, our approach was able to identify 225 differentially expressed genes shared across studies and taxa. Gene ontology enrichment and pathway analyses classified the shared genes into functional categories involved predominantly in metabolic processes (e.g. amino acid and carbohydrate metabolism), regulatory function (e.g. protein degradation and transcription) and response to stimulus. We further investigated drought related cis-acting elements in the shared gene promoters, and the evolutionary conservation of shared genes. The universal nature of the identified drought-adaptive genes was further validated in a fifth species, Brachypodium distachyon that was not included in the meta-analysis. qPCR analysis of 27, randomly selected, shared orthologs showed similar expression pattern as was found by the CSA:Drought.In accordance, morpho-physiological characterization of progressive drought stress, in B. distachyon, highlighted the key role of osmotic adjustment as evolutionary conserved drought-adaptive mechanism. Our CSA:Drought strategy highlights major drought-adaptive genes and metabolic pathways that were only partially, if at all, reported in the original studies included in the meta-analysis. These genes include a group of unclassified genes that could be involved

A novel joint analysis framework improves identification of differentially expressed genes in cross disease transcriptomic analysis

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Wenyi Qin

2018-02-01

Full Text Available Abstract Motivation Detecting differentially expressed (DE genes between disease and normal control group is one of the most common analyses in genome-wide transcriptomic data. Since most studies don’t have a lot of samples, researchers have used meta-analysis to group different datasets for the same disease. Even then, in many cases the statistical power is still not enough. Taking into account the fact that many diseases share the same disease genes, it is desirable to design a statistical framework that can identify diseases’ common and specific DE genes simultaneously to improve the identification power. Results We developed a novel empirical Bayes based mixture model to identify DE genes in specific study by leveraging the shared information across multiple different disease expression data sets. The effectiveness of joint analysis was demonstrated through comprehensive simulation studies and two real data applications. The simulation results showed that our method consistently outperformed single data set analysis and two other meta-analysis methods in identification power. In real data analysis, overall our method demonstrated better identification power in detecting DE genes and prioritized more disease related genes and disease related pathways than single data set analysis. Over 150% more disease related genes are identified by our method in application to Huntington’s disease. We expect that our method would provide researchers a new way of utilizing available data sets from different diseases when sample size of the focused disease is limited.

A meta-analysis of adiponectin gene rs22411766 T>G polymorphism and ischemic stroke susceptibility

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Xiuju Chen

2016-01-01

Full Text Available Several studies have investigated the correlation between adiponectin gene rs22411766 T>G polymorphism and ischemic stroke risk. However, the results were not conclusive with each other. Therefore, to overcome this obstacle, we performed this meta-analysis to further explicate the adiponectin gene rs22411766 T>G polymorphism and ischemic stroke susceptibility. Case-control or cohort studies focused on adiponectin gene rs22411766 T>G polymorphism and ischemic stroke risk were electronic searched in the databases of Medline, Pubmed, Cochrane library, Excerpta Medica database(EMBASE and China National Knowledge Infrastructure (CNKI. All the potentially relevant studies were included in this meta-analysis. The association between adiponectin gene rs22411766 T>G polymorphism and ischemic stroke was expressed by odds ratio with its confidence interval. Publication bias has been assessed by begg’s funnel plot. All the analyses have been performed by Revman 5.1 statistical software. Finally, a total of six studies with 1,345 cases and 1,421 controls were included in this meta-analysis. Our results demonstrated that there was a significant association between adiponectin gene rs22411766 T>G polymorphism and ischemic stroke risk (p<0.05. People with G single nucleotide of adiponectin gene have the increased risk of developing ischemic stroke compared to T single nucleotide.

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

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Jun Seita

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

A Meta-Analysis of Multiple Matched Copy Number and Transcriptomics Data Sets for Inferring Gene Regulatory Relationships

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Newton, Richard; Wernisch, Lorenz

2014-01-01

Inferring gene regulatory relationships from observational data is challenging. Manipulation and intervention is often required to unravel causal relationships unambiguously. However, gene copy number changes, as they frequently occur in cancer cells, might be considered natural manipulation experiments on gene expression. An increasing number of data sets on matched array comparative genomic hybridisation and transcriptomics experiments from a variety of cancer pathologies are becoming publicly available. Here we explore the potential of a meta-analysis of thirty such data sets. The aim of our analysis was to assess the potential of in silico inference of trans-acting gene regulatory relationships from this type of data. We found sufficient correlation signal in the data to infer gene regulatory relationships, with interesting similarities between data sets. A number of genes had highly correlated copy number and expression changes in many of the data sets and we present predicted potential trans-acted regulatory relationships for each of these genes. The study also investigates to what extent heterogeneity between cell types and between pathologies determines the number of statistically significant predictions available from a meta-analysis of experiments. PMID:25148247

Transcriptomic Analysis and Meta-Analysis of Human Granulosa and Cumulus Cells.

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Tanja Burnik Papler

Full Text Available Specific gene expression in oocytes and its surrounding cumulus (CC and granulosa (GC cells is needed for successful folliculogenesis and oocyte maturation. The aim of the present study was to compare genome-wide gene expression and biological functions of human GC and CC. Individual GC and CC were derived from 37 women undergoing IVF procedures. Gene expression analysis was performed using microarrays, followed by a meta-analysis. Results were validated using quantitative real-time PCR. There were 6029 differentially expressed genes (q < 10-4; of which 650 genes had a log2 FC ≥ 2. After the meta-analysis there were 3156 genes differentially expressed. Among these there were genes that have previously not been reported in human somatic follicular cells, like prokineticin 2 (PROK2, higher expressed in GC, and pregnancy up-regulated nonubiquitous CaM kinase (PNCK, higher expressed in CC. Pathways like inflammatory response and angiogenesis were enriched in GC, whereas in CC, cell differentiation and multicellular organismal development were among enriched pathways. In conclusion, transcriptomes of GC and CC as well as biological functions, are distinctive for each cell subpopulation. By describing novel genes like PROK2 and PNCK, expressed in GC and CC, we upgraded the existing data on human follicular biology.

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

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

2017-08-01

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

Analysis of baseline gene expression levels from ...

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The use of gene expression profiling to predict chemical mode of action would be enhanced by better characterization of variance due to individual, environmental, and technical factors. Meta-analysis of microarray data from untreated or vehicle-treated animals within the control arm of toxicogenomics studies has yielded useful information on baseline fluctuations in gene expression. A dataset of control animal microarray expression data was assembled by a working group of the Health and Environmental Sciences Institute's Technical Committee on the Application of Genomics in Mechanism Based Risk Assessment in order to provide a public resource for assessments of variability in baseline gene expression. Data from over 500 Affymetrix microarrays from control rat liver and kidney were collected from 16 different institutions. Thirty-five biological and technical factors were obtained for each animal, describing a wide range of study characteristics, and a subset were evaluated in detail for their contribution to total variability using multivariate statistical and graphical techniques. The study factors that emerged as key sources of variability included gender, organ section, strain, and fasting state. These and other study factors were identified as key descriptors that should be included in the minimal information about a toxicogenomics study needed for interpretation of results by an independent source. Genes that are the most and least variable, gender-selectiv

Temporal profiling of cytokine-induced genes in pancreatic β-cells by meta-analysis and network inference

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Lopes, Miguel; Kutlu, Burak; Miani, Michela

2014-01-01

Type 1 Diabetes (T1D) is an autoimmune disease where local release of cytokines such as IL-1β and IFN-γ contributes to β-cell apoptosis. To identify relevant genes regulating this process we performed a meta-analysis of 8 datasets of β-cell gene expression after exposure to IL-1β and IFN-γ. Two...

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

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Manijak, Mieszko P.; Nielsen, Henrik Bjørn

2011-01-01

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

Gene expression meta-analysis identifies chromosomal regions involved in ovarian cancer survival

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Thomassen, Mads; Jochumsen, Kirsten M; Mogensen, Ole

2009-01-01

the relation of gene expression and chromosomal position to identify chromosomal regions of importance for early recurrence of ovarian cancer. By use of *Gene Set Enrichment Analysis*, we have ranked chromosomal regions according to their association to survival. Over-representation analysis including 1...... using death (P = 0.015) and recurrence (P = 0.002) as outcome. The combined mutation score is strongly associated to upregulation of several growth factor pathways....

Association of mRNA expression of TP53 and the TP53 codon 72 Arg/Pro gene polymorphism with colorectal cancer risk in Asian population: a bioinformatics analysis and meta-analysis.

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Dong, Zhiyong; Zheng, Longzhi; Liu, Weimin; Wang, Cunchuan

2018-01-01

The relationship between TP53 codon 72 Pro/Arg gene polymorphism and colorectal cancer risk in Asians is still controversial, and this bioinformatics analysis and meta-analysis was performed to assess the associations. The association studies were identified from PubMed, and eligible reports were included. RevMan 5.3.1 software, Oncolnc, cBioPortal, and Oncomine online tools were used for statistical analysis. A random/fixed effects model was used in meta-analysis. The data were reported as risk ratios or mean differences with corresponding 95% CI. We confirmed that TP53 was associated with colorectal cancer, the alteration frequency of TP53 was 53% mutation and 7% deep deletion, and TP53 mRNA expression was different in different types of colorectal cancer based on The Cancer Genome Atlas database. Then, 18 studies were included that examine the association of TP53 codon 72 gene polymorphism with colorectal cancer risk in Asians. The meta-analysis indicated that TP53 Pro allele and Pro/Pro genotype were associated with colorectal cancer risk in Asian population, but Arg/Arg genotype was not (Pro allele: odds ratios [OR]=1.20, 95% CI: 1.06 to 1.35, P =0.003; Pro/Pro genotype: OR=1.39, 95% CI: 1.15 to 1.69, P =0.0007; Arg/Arg genotype: OR=0.86, 95% CI: 0.74 to 1.00, P =0.05). Interestingly, in the meta-analysis of the controls from the population-based studies, we found that TP53 codon 72 Pro/Arg gene polymorphism was associated with colorectal cancer risk (Pro allele: OR=1.33, 95% CI: 1.15 to 1.55, P =0.0002; Pro/Pro genotype: OR=1.61, 95% CI: 1.28 to 2.02, P colorectal cancer, but the different value levels of mRNA expression were not associated with survival rate of colon and rectal cancer. TP53 Pro allele and Pro/Pro genotype were associated with colorectal cancer risk in Asians.

Meta-analysis methods for combining multiple expression profiles: comparisons, statistical characterization and an application guideline.

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Chang, Lun-Ching; Lin, Hui-Min; Sibille, Etienne; Tseng, George C

2013-12-21

As high-throughput genomic technologies become accurate and affordable, an increasing number of data sets have been accumulated in the public domain and genomic information integration and meta-analysis have become routine in biomedical research. In this paper, we focus on microarray meta-analysis, where multiple microarray studies with relevant biological hypotheses are combined in order to improve candidate marker detection. Many methods have been developed and applied in the literature, but their performance and properties have only been minimally investigated. There is currently no clear conclusion or guideline as to the proper choice of a meta-analysis method given an application; the decision essentially requires both statistical and biological considerations. We performed 12 microarray meta-analysis methods for combining multiple simulated expression profiles, and such methods can be categorized for different hypothesis setting purposes: (1) HS(A): DE genes with non-zero effect sizes in all studies, (2) HS(B): DE genes with non-zero effect sizes in one or more studies and (3) HS(r): DE gene with non-zero effect in "majority" of studies. We then performed a comprehensive comparative analysis through six large-scale real applications using four quantitative statistical evaluation criteria: detection capability, biological association, stability and robustness. We elucidated hypothesis settings behind the methods and further apply multi-dimensional scaling (MDS) and an entropy measure to characterize the meta-analysis methods and data structure, respectively. The aggregated results from the simulation study categorized the 12 methods into three hypothesis settings (HS(A), HS(B), and HS(r)). Evaluation in real data and results from MDS and entropy analyses provided an insightful and practical guideline to the choice of the most suitable method in a given application. All source files for simulation and real data are available on the author's publication website.

Integrative sparse principal component analysis of gene expression data.

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Liu, Mengque; Fan, Xinyan; Fang, Kuangnan; Zhang, Qingzhao; Ma, Shuangge

2017-12-01

In the analysis of gene expression data, dimension reduction techniques have been extensively adopted. The most popular one is perhaps the PCA (principal component analysis). To generate more reliable and more interpretable results, the SPCA (sparse PCA) technique has been developed. With the "small sample size, high dimensionality" characteristic of gene expression data, the analysis results generated from a single dataset are often unsatisfactory. Under contexts other than dimension reduction, integrative analysis techniques, which jointly analyze the raw data of multiple independent datasets, have been developed and shown to outperform "classic" meta-analysis and other multidatasets techniques and single-dataset analysis. In this study, we conduct integrative analysis by developing the iSPCA (integrative SPCA) method. iSPCA achieves the selection and estimation of sparse loadings using a group penalty. To take advantage of the similarity across datasets and generate more accurate results, we further impose contrasted penalties. Different penalties are proposed to accommodate different data conditions. Extensive simulations show that iSPCA outperforms the alternatives under a wide spectrum of settings. The analysis of breast cancer and pancreatic cancer data further shows iSPCA's satisfactory performance. © 2017 WILEY PERIODICALS, INC.

Exercise-associated DNA methylation change in skeletal muscle and the importance of imprinted genes: a bioinformatics meta-analysis.

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Brown, William M

2015-12-01

Epigenetics is the study of processes--beyond DNA sequence alteration--producing heritable characteristics. For example, DNA methylation modifies gene expression without altering the nucleotide sequence. A well-studied DNA methylation-based phenomenon is genomic imprinting (ie, genotype-independent parent-of-origin effects). We aimed to elucidate: (1) the effect of exercise on DNA methylation and (2) the role of imprinted genes in skeletal muscle gene networks (ie, gene group functional profiling analyses). Gene ontology (ie, gene product elucidation)/meta-analysis. 26 skeletal muscle and 86 imprinted genes were subjected to g:Profiler ontology analysis. Meta-analysis assessed exercise-associated DNA methylation change. g:Profiler found four muscle gene networks with imprinted loci. Meta-analysis identified 16 articles (387 genes/1580 individuals) associated with exercise. Age, method, sample size, sex and tissue variation could elevate effect size bias. Only skeletal muscle gene networks including imprinted genes were reported. Exercise-associated effect sizes were calculated by gene. Age, method, sample size, sex and tissue variation were moderators. Six imprinted loci (RB1, MEG3, UBE3A, PLAGL1, SGCE, INS) were important for muscle gene networks, while meta-analysis uncovered five exercise-associated imprinted loci (KCNQ1, MEG3, GRB10, L3MBTL1, PLAGL1). DNA methylation decreased with exercise (60% of loci). Exercise-associated DNA methylation change was stronger among older people (ie, age accounted for 30% of the variation). Among older people, genes exhibiting DNA methylation decreases were part of a microRNA-regulated gene network functioning to suppress cancer. Imprinted genes were identified in skeletal muscle gene networks and exercise-associated DNA methylation change. Exercise-associated DNA methylation modification could rewind the 'epigenetic clock' as we age. CRD42014009800. Published by the BMJ Publishing Group Limited. For permission to use (where

C-reactive protein gene polymorphisms and myocardial infarction risk: a meta-analysis and meta-regression.

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Zhu, Yanbin; Liu, Tongku; He, Haitao; Sun, Yuqing; Zhuo, Fengling

2013-12-01

C-reactive protein (CRP), the classic acute-phase protein, plays an important role in the etiology of myocardial infarction (MI). Emerging evidence has shown that the common polymorphisms in the CRP gene may influence an individual's susceptibility to MI; but individually published studies showed inconclusive results. This meta-analysis aimed to derive a more precise estimation of the associations between CRP gene polymorphisms and MI risk. A literature search of PubMed, Embase, Web of Science, and China BioMedicine (CBM) databases was conducted on articles published before June 1st, 2013. Crude odds ratio (OR) with 95% confidence interval (CI) were calculated. Nine case-control studies were included with a total of 2992 MI patients and 4711 healthy controls. The meta-analysis results indicated that CRP rs3093059 (T>C) polymorphism was associated with decreased risk of MI, especially among Asian populations. However, similar associations were not observed in CRP rs1800947 (G>C) and rs2794521 (G>A) polymorphisms (all p>0.05) among both Asian and Caucasian populations. Univariate and multivariate meta-regression analyses showed that ethnicity may be a major source of heterogeneity. No publication bias was detected in this meta-analysis. In conclusion, the current meta-analysis indicates that CRP rs3093059 (T>C) polymorphism may be associated with decreased risk of MI, especially among Asian populations.

Meta-analysis of expression and function of neprilysin in Alzheimer's disease.

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Zhang, Huifeng; Liu, Dan; Wang, Yixing; Huang, Huanhuan; Zhao, Yujia; Zhou, Hui

2017-09-14

Neprilysin (NEP) is one of the most important Aβ-degrading enzymes, and its expression and activity in Alzheimer's brain have been widely reported, but the results remain debatable. Thus, the meta-analysis was performed to elucidate the role of NEP in Alzheimer's disease (AD). The relevant case-control or cohort studies were retrieved according to our inclusion/exclusion criteria. Six studies with 123 controls and 141 AD cases, seven studies with 102 controls and 90 AD cases, and four studies with 93 controls and 132 AD cases were included in meta-analysis of NEP's protein, mRNA, and enzyme activity respectively. We conducted Meta regression to detect the sources of heterogeneity and further performed cumulative meta-analysis or subgroup analysis. Our meta-analysis revealed a significantly lower level of NEP mRNA (SMD=-0.44, 95%CI: -0.87, -0.00, p=0.049) in AD cases than in non-AD cases, and such pattern was not altered over time in the cumulative meta-analysis. However, the decrease of NEP protein (SMD=-0.18, 95%CI: -0.62, 0.25) and enzyme activity (SMD=-0.35, 95%CI: -1.03, 0.32) in AD cases did not pass the significance check, while the cumulative meta-analysis by average age showed the pooled effect became insignificant as adding the studies with younger subjects, which indicates that the protein expression and enzyme activity of NEP in the cortex are affected by age. Therefore, the present meta-analysis suggests the need of further investigation of roles of NEP in AD pathogenesis and treatment. Copyright © 2017 Elsevier B.V. All rights reserved.

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

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Tsoi, Lam C; Qin, Tingting; Slate, Elizabeth H; Zheng, W Jim

2011-11-11

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. 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. 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 insensitivity to data variation commonly associated with microarray

Integrative analysis of genome-wide gene copy number changes and gene expression in non-small cell lung cancer.

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Verena Jabs

Full Text Available Non-small cell lung cancer (NSCLC represents a genomically unstable cancer type with extensive copy number aberrations. The relationship of gene copy number alterations and subsequent mRNA levels has only fragmentarily been described. The aim of this study was to conduct a genome-wide analysis of gene copy number gains and corresponding gene expression levels in a clinically well annotated NSCLC patient cohort (n = 190 and their association with survival. While more than half of all analyzed gene copy number-gene expression pairs showed statistically significant correlations (10,296 of 18,756 genes, high correlations, with a correlation coefficient >0.7, were obtained only in a subset of 301 genes (1.6%, including KRAS, EGFR and MDM2. Higher correlation coefficients were associated with higher copy number and expression levels. Strong correlations were frequently based on few tumors with high copy number gains and correspondingly increased mRNA expression. Among the highly correlating genes, GO groups associated with posttranslational protein modifications were particularly frequent, including ubiquitination and neddylation. In a meta-analysis including 1,779 patients we found that survival associated genes were overrepresented among highly correlating genes (61 of the 301 highly correlating genes, FDR adjusted p<0.05. Among them are the chaperone CCT2, the core complex protein NUP107 and the ubiquitination and neddylation associated protein CAND1. In conclusion, in a comprehensive analysis we described a distinct set of highly correlating genes. These genes were found to be overrepresented among survival-associated genes based on gene expression in a large collection of publicly available datasets.

The interaction between cannabis use and the Val158Met polymorphism of the COMT gene in psychosis: A transdiagnostic meta - analysis

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Vaessen, Thomas Stephanus Johannes; de Jong, Lea; Schäfer, Annika Theresia; Damen, Thomas; Uittenboogaard, Aniek; Krolinski, Pauline; Nwosu, Chinyere Vicky; Pinckaers, Florentina Maria Egidius; Rotee, Iris Leah Marije; Smeets, Antonius Petrus Wilhelmus; Ermiş, Ayşegül; Kennedy, James L.; Nieman, Dorien H.; Tiwari, Arun; van Os, Jim; Drukker, Marjan

2018-01-01

Neither environmental nor genetic factors are sufficient to predict the transdiagnostic expression of psychosis. Therefore, analysis of gene-environment interactions may be productive. A meta-analysis was performed using papers investigating the interaction between cannabis use and catechol-O-methyl

Improved score statistics for meta-analysis in single-variant and gene-level association studies.

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Yang, Jingjing; Chen, Sai; Abecasis, Gonçalo

2018-06-01

Meta-analysis is now an essential tool for genetic association studies, allowing them to combine large studies and greatly accelerating the pace of genetic discovery. Although the standard meta-analysis methods perform equivalently as the more cumbersome joint analysis under ideal settings, they result in substantial power loss under unbalanced settings with various case-control ratios. Here, we investigate the power loss problem by the standard meta-analysis methods for unbalanced studies, and further propose novel meta-analysis methods performing equivalently to the joint analysis under both balanced and unbalanced settings. We derive improved meta-score-statistics that can accurately approximate the joint-score-statistics with combined individual-level data, for both linear and logistic regression models, with and without covariates. In addition, we propose a novel approach to adjust for population stratification by correcting for known population structures through minor allele frequencies. In the simulated gene-level association studies under unbalanced settings, our method recovered up to 85% power loss caused by the standard methods. We further showed the power gain of our methods in gene-level tests with 26 unbalanced studies of age-related macular degeneration . In addition, we took the meta-analysis of three unbalanced studies of type 2 diabetes as an example to discuss the challenges of meta-analyzing multi-ethnic samples. In summary, our improved meta-score-statistics with corrections for population stratification can be used to construct both single-variant and gene-level association studies, providing a useful framework for ensuring well-powered, convenient, cross-study analyses. © 2018 WILEY PERIODICALS, INC.

Global meta-analysis of transcriptomics studies.

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José Caldas

Full Text Available Transcriptomics meta-analysis aims at re-using existing data to derive novel biological hypotheses, and is motivated by the public availability of a large number of independent studies. Current methods are based on breaking down studies into multiple comparisons between phenotypes (e.g. disease vs. healthy, based on the studies' experimental designs, followed by computing the overlap between the resulting differential expression signatures. While useful, in this methodology each study yields multiple independent phenotype comparisons, and connections are established not between studies, but rather between subsets of the studies corresponding to phenotype comparisons. We propose a rank-based statistical meta-analysis framework that establishes global connections between transcriptomics studies without breaking down studies into sets of phenotype comparisons. By using a rank product method, our framework extracts global features from each study, corresponding to genes that are consistently among the most expressed or differentially expressed genes in that study. Those features are then statistically modelled via a term-frequency inverse-document frequency (TF-IDF model, which is then used for connecting studies. Our framework is fast and parameter-free; when applied to large collections of Homo sapiens and Streptococcus pneumoniae transcriptomics studies, it performs better than similarity-based approaches in retrieving related studies, using a Medical Subject Headings gold standard. Finally, we highlight via case studies how the framework can be used to derive novel biological hypotheses regarding related studies and the genes that drive those connections. Our proposed statistical framework shows that it is possible to perform a meta-analysis of transcriptomics studies with arbitrary experimental designs by deriving global expression features rather than decomposing studies into multiple phenotype comparisons.

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

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

2015-01-27

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

Gene expression meta-analysis identifies metastatic pathways and transcription factors in breast cancer

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Thomassen, Mads; Tan, Qihua; Kruse, Torben

2008-01-01

ABSTRACT: BACKGROUND: Metastasis is believed to progress in several steps including different pathways but the determination and understanding of these mechanisms is still fragmentary. Microarray analysis of gene expression patterns in breast tumors has been used to predict outcome in recent stud...

Identifying novel glioma associated pathways based on systems biology level meta-analysis.

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Hu, Yangfan; Li, Jinquan; Yan, Wenying; Chen, Jiajia; Li, Yin; Hu, Guang; Shen, Bairong

2013-01-01

With recent advances in microarray technology, including genomics, proteomics, and metabolomics, it brings a great challenge for integrating this "-omics" data to analysis complex disease. Glioma is an extremely aggressive and lethal form of brain tumor, and thus the study of the molecule mechanism underlying glioma remains very important. To date, most studies focus on detecting the differentially expressed genes in glioma. However, the meta-analysis for pathway analysis based on multiple microarray datasets has not been systematically pursued. In this study, we therefore developed a systems biology based approach by integrating three types of omics data to identify common pathways in glioma. Firstly, the meta-analysis has been performed to study the overlapping of signatures at different levels based on the microarray gene expression data of glioma. Among these gene expression datasets, 12 pathways were found in GeneGO database that shared by four stages. Then, microRNA expression profiles and ChIP-seq data were integrated for the further pathway enrichment analysis. As a result, we suggest 5 of these pathways could be served as putative pathways in glioma. Among them, the pathway of TGF-beta-dependent induction of EMT via SMAD is of particular importance. Our results demonstrate that the meta-analysis based on systems biology level provide a more useful approach to study the molecule mechanism of complex disease. The integration of different types of omics data, including gene expression microarrays, microRNA and ChIP-seq data, suggest some common pathways correlated with glioma. These findings will offer useful potential candidates for targeted therapeutic intervention of glioma.

Microarray Meta-Analysis Identifies Acute Lung Injury Biomarkers in Donor Lungs That Predict Development of Primary Graft Failure in Recipients

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Haitsma, Jack J.; Furmli, Suleiman; Masoom, Hussain; Liu, Mingyao; Imai, Yumiko; Slutsky, Arthur S.; Beyene, Joseph; Greenwood, Celia M. T.; dos Santos, Claudia

2012-01-01

Objectives To perform a meta-analysis of gene expression microarray data from animal studies of lung injury, and to identify an injury-specific gene expression signature capable of predicting the development of lung injury in humans. Methods We performed a microarray meta-analysis using 77 microarray chips across six platforms, two species and different animal lung injury models exposed to lung injury with or/and without mechanical ventilation. Individual gene chips were classified and grouped based on the strategy used to induce lung injury. Effect size (change in gene expression) was calculated between non-injurious and injurious conditions comparing two main strategies to pool chips: (1) one-hit and (2) two-hit lung injury models. A random effects model was used to integrate individual effect sizes calculated from each experiment. Classification models were built using the gene expression signatures generated by the meta-analysis to predict the development of lung injury in human lung transplant recipients. Results Two injury-specific lists of differentially expressed genes generated from our meta-analysis of lung injury models were validated using external data sets and prospective data from animal models of ventilator-induced lung injury (VILI). Pathway analysis of gene sets revealed that both new and previously implicated VILI-related pathways are enriched with differentially regulated genes. Classification model based on gene expression signatures identified in animal models of lung injury predicted development of primary graft failure (PGF) in lung transplant recipients with larger than 80% accuracy based upon injury profiles from transplant donors. We also found that better classifier performance can be achieved by using meta-analysis to identify differentially-expressed genes than using single study-based differential analysis. Conclusion Taken together, our data suggests that microarray analysis of gene expression data allows for the detection of �

DNA repair gene polymorphisms and risk of cutaneous melanoma: a systematic review and meta-analysis.

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Mocellin, Simone; Verdi, Daunia; Nitti, Donato

2009-10-01

Polymorphisms of DNA repair-related genes might modulate cancer predisposition. We performed a systematic review and meta-analysis of the available evidence regarding the relationship between these polymorphisms and the risk of developing cutaneous melanoma. Relevant studies were searched using PubMed, Medline, Embase, Cancerlit, Cochrane and ISI Web of Knowledge databases. Data were gathered according to the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) guidelines. The model-free approach was adopted to perform the meta-analysis of the retrieved data. We identified 20 original reports that describe the relationship between melanoma risk and the single-nucleotide polymorphisms (SNPs) of 16 genes (cases = 4195). For seven SNPs considered in at least two studies, the findings were heterogeneous. Data were suitable for meta-analysis only in the case of the XPD/ERCC2 SNP rs13181 (cases = 2308, controls = 3698) and demonstrated that the variant C allele is associated with increased melanoma risk (odds ratio = 1.12, 95% confidence interval = 1.03-1.21, P = 0.01; population attributable risk = 9.6%). This is the first meta-analysis suggesting that XPD/ERCC2 might represent a low-penetrance melanoma susceptibility gene. Much work is still to be done before definitive conclusions can be drawn on the role of DNA repair alterations in melanomagenesis since for the other genes involved in this highly complex process, the available information is scarce or null.

Hematopoietically-expressed homeobox gene three widely-evaluated polymorphisms and risk for diabetes: a meta-analysis.

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Xiaobo Li

Full Text Available BACKGROUND: The hematopoietically-expressed homeobox (HHEX gene is identified as a promising candidate for type 2 diabetes by genome-wide association studies, triggering plenty of subsequent replications; however, the results are conflicting. We therefore conducted a meta-analysis of three widely-evaluated polymorphisms in HHEX gene and diabetes risk. METHODOLOGY/PRINCIPAL FINDINGS: A random-effects model was adopted irrespective of heterogeneity. Data and study quality were assessed in duplicate. There were 49 studies (cases/controls: 57931/74658 for rs1111875, 18 studies (18227/30366 for rs5015480 and 26 studies (25725/30579 for rs7923837, respectively. Overall analyses indicated that rs1111875-C allele (odds ratio [OR] = 1.16; 95% confidence interval [CI]: 1.13-1.2; P<0.0005, rs5015480-C allele (OR = 1.16; 95% CI: 1.06-1.26; P = 0.001 and rs7923837-G allele (OR = 1.18; 95% CI: 1.12-1.24; P<0.0005 conferred significantly increased risk for type 2 diabetes, yet accompanying moderate to strong evidence of heterogeneity. Despite vast divergence in allele distributions, subgroup analyses by ethnicity showed comparable risk estimates between Asians and Caucasians for three examined polymorphisms. Moreover, results of studies with hospital-based controls deviated greatly from that of all qualified studies, especially for rs7923837-G allele carrying a doubled risk (OR = 1.37 versus 1.18. Furthermore, when only large studies (≥ 500 case-patients were considered, risk effects were identical to the overall estimates for three examined polymorphisms. The Begg's funnel plot and Egger's test indicated low probability of publication bias. CONCLUSIONS: Our results provide clarification to the significant association of rs1111875, rs5015480 and rs7923837 in HHEX gene with type 2 diabetes.

Prognostic value of Notch-1 expression in hepatocellular carcinoma: a meta-analysis

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Wu T

2015-10-01

Full Text Available Tao Wu,1 Min Jiao,1 Li Jing,1 Min-Cong Wang,1 Hai-Feng Sun,2 Qing Li,1 Yi-Yang Bai,1 Yong-Chang Wei,1 Ke-Jun Nan,1 Hui Guo1 1Department of Medical Oncology, The First Affiliated Hospital of Xi’an Jiaotong University, 2Department of Oncology, Shaanxi Cancer Hospital, Xi’an, People’s Republic of China Abstract: Association of Notch-1 expression with prognosis of patients with hepatocellular carcinoma (HCC remains controversial. We conducted a meta-analysis to reevaluate the association of Notch-1 expression with clinicopathological characteristics and prognosis of HCC. PubMed, Embase, Web of Science, and China National Knowledge Infrastructure were searched to look for relevant studies. The association between Notch-1 expression and clinicopathological parameters and overall survival (OS was then reassessed using the meta-analysis for odds ratio (OR or hazard ratio (HR and 95% confidence interval (CI. A total of seven studies, including 810 HCC patients, were eligible for the meta-analysis. Our data showed that high Notch-1 expression was able to predict poor OS (HR 1.50, 95% CI 1.17–1.83, P=0.0001. The pooled OR showed that high Notch-1 expression was significantly associated with tumor metastasis (OR 0.37, 95% CI 0.16–0.86, P=0.02 and tumor size >5 cm (OR 0.48, 95% CI 0.26–0.88, P=0.02. In contrast, there was no association between high Notch-1 expression and tumor differentiation, late TNM stage, tumor number, and portal vein invasion of HCC. In conclusion, Notch-1 overexpression might predict poorer survival and more aggressive behavior in patients with HCC. Keywords: hepatocellular carcinoma, Notch-1, prognosis, clinicopathological features, meta-analysis

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

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Boris P Hejblum

2015-06-01

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

The Relationship between FHIT Gene Promoter Methylation and Lung Cancer Risk: 
a Meta-analysis

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Yichang SUN

2014-03-01

Full Text Available Background and objective Tumor-suppressor gene promoter DNA methylation in tumor cells is associated with its reduced expression. FHIT (fragile histindine triad was one of the important tumor suppressor genes which was found hypermethylated in the promoter region in most of tumors. The aim of this study is to evaluate the relationship between FIHT gene promother methylation and lung cancer risk by meta-analysis. Methods By searching Pubmed, CNKI and Wanfang, the open published articles related to FHIT gene promoter methylation and lung carcinoma risk were collected. The odds ratio (OR and range of FHIT gene of cancer tissue of lung cancer patients compared with normal lung tissue, plasma and the bronchial lavage fluid were pooled by statistical software Stata 11.0. Results Eleven studies were finally included in this meta-analysis. The median methylation rate were Pmedian=40.0% (0-68.3%, Pmedian=8.7% (0-35.0%, Pmedian=33.3% (17.1%-38.3% and Pmedian=35.9% (31.1%-50.8% in cancer tissue, NLT, BALF and plasm respectively. The pooled results showed the methylation rate in tumor tissue was much higer than that of NLT OR=5.82 (95%CI: 3.74-9.06, P0.05 and plasma OR=1.41 (95%CI: 0.90-2.20, P>0.05. Conclusion Hypermethylation of FHIT gene promoter region was found more frequent in cancer tissue than that of NLT which may demonstrated association between lung cancer risk and FHIT gene promoter methylation.

The Brassicaceae family displays divergent, shoot-skewed NLR resistance gene expression

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Munch, David; Gupta, Vikas; Bachmann, Asger

2018-01-01

Nucleotide-binding site leucine-rich repeat resistance genes (NLRs) allow plants to detect microbial effectors. We hypothesized that NLR expression patterns could reflect organ-specific differences in effector challenge and tested this by carrying out a meta-analysis of expression data for 1,235 ...

Meta-Analysis of Placental Transcriptome Data Identifies a Novel Molecular Pathway Related to Preeclampsia.

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van Uitert, Miranda; Moerland, Perry D; Enquobahrie, Daniel A; Laivuori, Hannele; van der Post, Joris A M; Ris-Stalpers, Carrie; Afink, Gijs B

2015-01-01

Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia gene expression signature, we performed a meta-analysis on the original data of 11 placenta RNA microarray experiments, representing 139 normotensive and 116 preeclamptic pregnancies. Microarray data were pre-processed and analyzed using standardized bioinformatics and statistical procedures and the effect sizes were combined using an inverse-variance random-effects model. Interactions between genes in the resulting gene expression signature were identified by pathway analysis (Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, Graphite) and protein-protein associations (STRING). This approach has resulted in a comprehensive list of differentially expressed genes that led to a 388-gene meta-signature of preeclamptic placenta. Pathway analysis highlights the involvement of the previously identified hypoxia/HIF1A pathway in the establishment of the preeclamptic gene expression profile, while analysis of protein interaction networks indicates CREBBP/EP300 as a novel element central to the preeclamptic placental transcriptome. In addition, there is an apparent high incidence of preeclampsia in women carrying a child with a mutation in CREBBP/EP300 (Rubinstein-Taybi Syndrome). The 388-gene preeclampsia meta-signature offers a vital starting point for further studies into the relevance of these genes (in particular CREBBP/EP300) and their concomitant pathways as biomarkers or functional molecules in preeclampsia. This will result in a better understanding of the molecular basis of this disease and opens up the opportunity to develop rational therapies targeting the placental dysfunction causal to preeclampsia.

Screening Key Genes Associated with the Development and Progression of Non-small Cell Lung Cancer Based on Gene-enrichment Analysis and Meta-analysis

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Wenwu HE

2012-07-01

Full Text Available Background and objective Non-small cell lung cancer (NSCLC is one of the most common malignant tumors; however, its causes are still not completely understood. This study was designed to screen the key genes and pathways related to NSCLC occurrence and development and to establish the scientific foundation for the genetic mechanisms and targeted therapy of NSCLC. Methods Both gene set-enrichment analysis (GSEA and meta-analysis (meta were used to screen the critical pathways and genes that might be corretacted with the development and progression of lung cancer at the transcription level. Results Using the GSEA and meta methods, focal adhesion and regulation of actin cytoskeleton were determined to be the more prominent overlapping significant pathways. In the focal adhesion pathway, 31 genes were statistically significant (P<0.05, whereas in the regulation of actin cytoskeleton pathway, 32 genes were statistically significant (P<0.05. Conclusion The focal adhesion and the regulation of actin cytoskeleton pathways might play important roles in the occurrence and development of NSCLC. Further studies are needed to determine the biological function for the positiue genes.

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

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

2012-12-01

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

Meta-analysis of Cancer Gene Profiling Data.

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Roy, Janine; Winter, Christof; Schroeder, Michael

2016-01-01

The simultaneous measurement of thousands of genes gives the opportunity to personalize and improve cancer therapy. In addition, the integration of meta-data such as protein-protein interaction (PPI) information into the analyses helps in the identification and prioritization of genes from these screens. Here, we describe a computational approach that identifies genes prognostic for outcome by combining gene profiling data from any source with a network of known relationships between genes.

Multiscale Embedded Gene Co-expression Network Analysis.

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Won-Min Song

2015-11-01

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

Multiscale Embedded Gene Co-expression Network Analysis.

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Song, Won-Min; Zhang, Bin

2015-11-01

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

Meta-analysis of inter-species liver co-expression networks elucidates traits associated with common human diseases.

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Kai Wang

2009-12-01

Full Text Available Co-expression networks are routinely used to study human diseases like obesity and diabetes. Systematic comparison of these networks between species has the potential to elucidate common mechanisms that are conserved between human and rodent species, as well as those that are species-specific characterizing evolutionary plasticity. We developed a semi-parametric meta-analysis approach for combining gene-gene co-expression relationships across expression profile datasets from multiple species. The simulation results showed that the semi-parametric method is robust against noise. When applied to human, mouse, and rat liver co-expression networks, our method out-performed existing methods in identifying gene pairs with coherent biological functions. We identified a network conserved across species that highlighted cell-cell signaling, cell-adhesion and sterol biosynthesis as main biological processes represented in genome-wide association study candidate gene sets for blood lipid levels. We further developed a heterogeneity statistic to test for network differences among multiple datasets, and demonstrated that genes with species-specific interactions tend to be under positive selection throughout evolution. Finally, we identified a human-specific sub-network regulated by RXRG, which has been validated to play a different role in hyperlipidemia and Type 2 diabetes between human and mouse. Taken together, our approach represents a novel step forward in integrating gene co-expression networks from multiple large scale datasets to leverage not only common information but also differences that are dataset-specific.

Serial Expression Analysis: a web tool for the analysis of serial gene expression data

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Nueda, Maria José; Carbonell, José; Medina, Ignacio; Dopazo, Joaquín; Conesa, Ana

2010-01-01

Serial transcriptomics experiments investigate the dynamics of gene expression changes associated with a quantitative variable such as time or dosage. The statistical analysis of these data implies the study of global and gene-specific expression trends, the identification of significant serial changes, the comparison of expression profiles and the assessment of transcriptional changes in terms of cellular processes. We have created the SEA (Serial Expression Analysis) suite to provide a complete web-based resource for the analysis of serial transcriptomics data. SEA offers five different algorithms based on univariate, multivariate and functional profiling strategies framed within a user-friendly interface and a project-oriented architecture to facilitate the analysis of serial gene expression data sets from different perspectives. SEA is available at sea.bioinfo.cipf.es. PMID:20525784

Serial analysis of gene expression (SAGE)

NARCIS (Netherlands)

van Ruissen, Fred; Baas, Frank

2007-01-01

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

Meta-Analysis of Placental Transcriptome Data Identifies a Novel Molecular Pathway Related to Preeclampsia.

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Miranda van Uitert

Full Text Available Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia gene expression signature, we performed a meta-analysis on the original data of 11 placenta RNA microarray experiments, representing 139 normotensive and 116 preeclamptic pregnancies. Microarray data were pre-processed and analyzed using standardized bioinformatics and statistical procedures and the effect sizes were combined using an inverse-variance random-effects model. Interactions between genes in the resulting gene expression signature were identified by pathway analysis (Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, Graphite and protein-protein associations (STRING. This approach has resulted in a comprehensive list of differentially expressed genes that led to a 388-gene meta-signature of preeclamptic placenta. Pathway analysis highlights the involvement of the previously identified hypoxia/HIF1A pathway in the establishment of the preeclamptic gene expression profile, while analysis of protein interaction networks indicates CREBBP/EP300 as a novel element central to the preeclamptic placental transcriptome. In addition, there is an apparent high incidence of preeclampsia in women carrying a child with a mutation in CREBBP/EP300 (Rubinstein-Taybi Syndrome. The 388-gene preeclampsia meta-signature offers a vital starting point for further studies into the relevance of these genes (in particular CREBBP/EP300 and their concomitant pathways as biomarkers or functional molecules in preeclampsia. This will result in a better understanding of the molecular basis of this disease and opens up the opportunity to develop rational therapies targeting the placental dysfunction causal to preeclampsia.

Inferring gene expression dynamics via functional regression analysis

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Leng Xiaoyan

2008-01-01

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

Meta-analysis and candidate gene mining of low-phosphorus tolerance in maize.

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Zhang, Hongwei; Uddin, Mohammed Shalim; Zou, Cheng; Xie, Chuanxiao; Xu, Yunbi; Li, Wen-Xue

2014-03-01

Plants with tolerance to low-phosphorus (P) can grow better under low-P conditions, and understanding of genetic mechanisms of low-P tolerance can not only facilitate identifying relevant genes but also help to develop low-P tolerant cultivars. QTL meta-analysis was conducted after a comprehensive review of the reports on QTL mapping for low-P tolerance-related traits in maize. Meta-analysis produced 23 consensus QTL (cQTL), 17 of which located in similar chromosome regions to those previously reported to influence root traits. Meanwhile, candidate gene mining yielded 215 genes, 22 of which located in the cQTL regions. These 22 genes are homologous to 14 functionally characterized genes that were found to participate in plant low-P tolerance, including genes encoding miR399s, Pi transporters and purple acid phosphatases. Four cQTL loci (cQTL2-1, cQTL5-3, cQTL6-2, and cQTL10-2) may play important roles for low-P tolerance because each contains more original QTL and has better consistency across previous reports. © 2014 Institute of Botany, Chinese Academy of Sciences.

Dynamic association rules for gene expression data analysis.

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

2015-10-14

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

Integrated Analyses of Gene Expression Profiles Digs out Common Markers for Rheumatic Diseases

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Wang, Lan; Wu, Long-Fei; Lu, Xin; Mo, Xing-Bo; Tang, Zai-Xiang; Lei, Shu-Feng; Deng, Fei-Yan

2015-01-01

Objective Rheumatic diseases have some common symptoms. Extensive gene expression studies, accumulated thus far, have successfully identified signature molecules for each rheumatic disease, individually. However, whether there exist shared factors across rheumatic diseases has yet to be tested. Methods We collected and utilized 6 public microarray datasets covering 4 types of representative rheumatic diseases including rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis, and osteoarthritis. Then we detected overlaps of differentially expressed genes across datasets and performed a meta-analysis aiming at identifying common differentially expressed genes that discriminate between pathological cases and normal controls. To further gain insights into the functions of the identified common differentially expressed genes, we conducted gene ontology enrichment analysis and protein-protein interaction analysis. Results We identified a total of eight differentially expressed genes (TNFSF10, CX3CR1, LY96, TLR5, TXN, TIA1, PRKCH, PRF1), each associated with at least 3 of the 4 studied rheumatic diseases. Meta-analysis warranted the significance of the eight genes and highlighted the general significance of four genes (CX3CR1, LY96, TLR5, and PRF1). Protein-protein interaction and gene ontology enrichment analyses indicated that the eight genes interact with each other to exert functions related to immune response and immune regulation. Conclusion The findings support that there exist common factors underlying rheumatic diseases. For rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis and osteoarthritis diseases, those common factors include TNFSF10, CX3CR1, LY96, TLR5, TXN, TIA1, PRKCH, and PRF1. In-depth studies on these common factors may provide keys to understanding the pathogenesis and developing intervention strategies for rheumatic diseases. PMID:26352601

Meta-analysis of expression of l(3)mbt tumor-associated germline genes supports the model that a soma-to-germline transition is a hallmark of human cancers.

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Feichtinger, Julia; Larcombe, Lee; McFarlane, Ramsay J

2014-05-15

Evidence is starting to emerge indicating that tumorigenesis in metazoans involves a soma-to-germline transition, which may contribute to the acquisition of neoplastic characteristics. Here, we have meta-analyzed gene expression profiles of the human orthologs of Drosophila melanogaster germline genes that are ectopically expressed in l(3)mbt brain tumors using gene expression datasets derived from a large cohort of human tumors. We find these germline genes, some of which drive oncogenesis in D. melanogaster, are similarly ectopically activated in a wide range of human cancers. Some of these genes normally have expression restricted to the germline, making them of particular clinical interest. Importantly, these analyses provide additional support to the emerging model that proposes a soma-to-germline transition is a general hallmark of a wide range of human tumors. This has implications for our understanding of human oncogenesis and the development of new therapeutic and biomarker targets with clinical potential. © 2013 The Authors. Published by Wiley Periodicals, Inc. on behalf of UICC.

Clinical Significance of Resistin Expression in Osteoarthritis: A Meta-Analysis

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Xiao-Chuan Li

2014-01-01

Full Text Available Background. The objective of this study was to conduct a systematic review of literature evaluating human resistin expression as a diagnostic factor in osteoarthritis development and to quantify the overall diagnostic effect. Method. Relevant studies were identified and evaluated for quality through multiple search strategies. Studies analyzing resistin expression in the development of OA were eligible for inclusion. Data from eligible studies were extracted and included into the meta-analysis using a random-effects model. Results. Four case-control studies consisting of a total of 375 OA patients and 214 controls as well as three sex-stratified analyses composed of 53 males and 104 females were incorporated into our meta-analysis. Our results revealed that resistin levels were significantly higher in male OA subjects and OA patients overall. Country-stratified analysis yielded significantly different estimates in resistin levels between male OA subjects and female OA subjects in the Canadian subgroup but not among the French and USA subgroups. Based on the resistin levels in OA cases and controls, resistin levels were heightened in OA patients in the Dutch population. Conclusion. These results support the hypothesis that high expression of resistin represents a significant and reproducible marker of poor progression in OA patients, especially in males.

Identification of Differentially Expressed Genes through Integrated Study of Alzheimer's Disease Affected Brain Regions.

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Nisha Puthiyedth

Full Text Available Alzheimer's disease (AD is the most common form of dementia in older adults that damages the brain and results in impaired memory, thinking and behaviour. The identification of differentially expressed genes and related pathways among affected brain regions can provide more information on the mechanisms of AD. In the past decade, several studies have reported many genes that are associated with AD. This wealth of information has become difficult to follow and interpret as most of the results are conflicting. In that case, it is worth doing an integrated study of multiple datasets that helps to increase the total number of samples and the statistical power in detecting biomarkers. In this study, we present an integrated analysis of five different brain region datasets and introduce new genes that warrant further investigation.The aim of our study is to apply a novel combinatorial optimisation based meta-analysis approach to identify differentially expressed genes that are associated to AD across brain regions. In this study, microarray gene expression data from 161 samples (74 non-demented controls, 87 AD from the Entorhinal Cortex (EC, Hippocampus (HIP, Middle temporal gyrus (MTG, Posterior cingulate cortex (PC, Superior frontal gyrus (SFG and visual cortex (VCX brain regions were integrated and analysed using our method. The results are then compared to two popular meta-analysis methods, RankProd and GeneMeta, and to what can be obtained by analysing the individual datasets.We find genes related with AD that are consistent with existing studies, and new candidate genes not previously related with AD. Our study confirms the up-regualtion of INFAR2 and PTMA along with the down regulation of GPHN, RAB2A, PSMD14 and FGF. Novel genes PSMB2, WNK1, RPL15, SEMA4C, RWDD2A and LARGE are found to be differentially expressed across all brain regions. Further investigation on these genes may provide new insights into the development of AD. In addition, we

Gene expression profiles in Parkinson disease prefrontal cortex implicate FOXO1 and genes under its transcriptional regulation.

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Alexandra Dumitriu

2012-06-01

Full Text Available Parkinson disease (PD is a complex neurodegenerative disorder with largely unknown genetic mechanisms. While the degeneration of dopaminergic neurons in PD mainly takes place in the substantia nigra pars compacta (SN region, other brain areas, including the prefrontal cortex, develop Lewy bodies, the neuropathological hallmark of PD. We generated and analyzed expression data from the prefrontal cortex Brodmann Area 9 (BA9 of 27 PD and 26 control samples using the 44K One-Color Agilent 60-mer Whole Human Genome Microarray. All samples were male, without significant Alzheimer disease pathology and with extensive pathological annotation available. 507 of the 39,122 analyzed expression probes were different between PD and control samples at false discovery rate (FDR of 5%. One of the genes with significantly increased expression in PD was the forkhead box O1 (FOXO1 transcription factor. Notably, genes carrying the FoxO1 binding site were significantly enriched in the FDR-significant group of genes (177 genes covered by 189 probes, suggesting a role for FoxO1 upstream of the observed expression changes. Single-nucleotide polymorphisms (SNPs selected from a recent meta-analysis of PD genome-wide association studies (GWAS were successfully genotyped in 50 out of the 53 microarray brains, allowing a targeted expression-SNP (eSNP analysis for 52 SNPs associated with PD affection at genome-wide significance and the 189 probes from FoxO1 regulated genes. A significant association was observed between a SNP in the cyclin G associated kinase (GAK gene and a probe in the spermine oxidase (SMOX gene. Further examination of the FOXO1 region in a meta-analysis of six available GWAS showed two SNPs significantly associated with age at onset of PD. These results implicate FOXO1 as a PD-relevant gene and warrant further functional analyses of its transcriptional regulatory mechanisms.

SIGNATURE: A workbench for gene expression signature analysis

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Chang Jeffrey T

2011-11-01

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

A meta-analysis of human embryonic stem cells transcriptome integrated into a web-based expression atlas.

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Assou, Said; Le Carrour, Tanguy; Tondeur, Sylvie; Ström, Susanne; Gabelle, Audrey; Marty, Sophie; Nadal, Laure; Pantesco, Véronique; Réme, Thierry; Hugnot, Jean-Philippe; Gasca, Stéphan; Hovatta, Outi; Hamamah, Samir; Klein, Bernard; De Vos, John

2007-04-01

Microarray technology provides a unique opportunity to examine gene expression patterns in human embryonic stem cells (hESCs). We performed a meta-analysis of 38 original studies reporting on the transcriptome of hESCs. We determined that 1,076 genes were found to be overexpressed in hESCs by at least three studies when compared to differentiated cell types, thus composing a "consensus hESC gene list." Only one gene was reported by all studies: the homeodomain transcription factor POU5F1/OCT3/4. The list comprised other genes critical for pluripotency such as the transcription factors NANOG and SOX2, and the growth factors TDGF1/CRIPTO and Galanin. We show that CD24 and SEMA6A, two cell surface protein-coding genes from the top of the consensus hESC gene list, display a strong and specific membrane protein expression on hESCs. Moreover, CD24 labeling permits the purification by flow cytometry of hESCs cocultured on human fibroblasts. The consensus hESC gene list also included the FZD7 WNT receptor, the G protein-coupled receptor GPR19, and the HELLS helicase, which could play an important role in hESCs biology. Conversely, we identified 783 genes downregulated in hESCs and reported in at least three studies. This "consensus differentiation gene list" included the IL6ST/GP130 LIF receptor. We created an online hESC expression atlas, http://amazonia.montp.inserm.fr, to provide an easy access to this public transcriptome dataset. Expression histograms comparing hESCs to a broad collection of fetal and adult tissues can be retrieved with this web tool for more than 15,000 genes.

State-related alterations of gene expression in bipolar disorder

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Munkholm, Klaus; Vinberg, Maj; Berk, Michael

2012-01-01

Munkholm K, Vinberg M, Berk M, Kessing LV. State-related alterations of gene expression in bipolar disorder: a systematic review. Bipolar Disord 2012: 14: 684-696. © 2012 The Authors. Journal compilation © 2012 John Wiley & Sons A/S. Objective:  Alterations in gene expression in bipolar disorder...... have been found in numerous studies. It is unclear whether such alterations are related to specific mood states. As a biphasic disorder, mood state-related alterations in gene expression have the potential to point to markers of disease activity, and trait-related alterations might indicate...... vulnerability pathways. This review therefore evaluated the evidence for whether gene expression in bipolar disorder is state or trait related. Methods:  A systematic review, using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guideline for reporting systematic reviews, based...

LncRNA expression and implication in osteosarcoma: a systematic review and meta-analysis

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Wang Y

2017-11-01

Full Text Available Ying Wang,1,2,* Yuelong Huang,2,* Peng Xiang,3 Wei Tian2 1Department of Molecular Orthopaedics, Beijing Institute of Traumatology and Orthopaedics, 2Department of Spinal Surgery, Beijing Jishuitan Hospital, The Fourth Clinical Medical College of Peking University, 3Department of Urology, Peking University First Hospital, Beijing, People’s Republic of China *These authors contributed equally to this work Purpose: Osteosarcoma is the most prevalent primary bone tumor in children, adolescents, and older adults, typically presenting with poor survival outcomes. In recent years, ample evidence has shown that many long noncoding RNAs (lncRNAs have been aberrantly expressed in osteosarcoma, demonstrating their potential to serve as prognostic markers. In this study, we performed a meta-analysis on four lncRNAs (TUG1, UCA1, BCAR4, and HULC to systematically evaluate their prognostic value in osteosarcoma.Materials and methods: The eligible articles were systematically searched in PubMed, Web of Science, Embase, and Elsevier ScienceDirect (up to September 22, 2017, and one meta-analysis concerning the association between lncRNA expression and the overall survival (OS of osteosarcoma patients was performed. Survival outcomes were analyzed by OS. Subgroup analyses were performed.Results: A total of 1,361 patients with osteosarcoma and 12 lncRNAs from 16 articles were included in the study. Of the listed lncRNAs, the high expression of 10 lncRNAs indicated worse survival outcomes, while only two lncRNAs were shown to positively affect patients’ OS.Conclusion: This meta-analysis indicated that the abnormally expressed lncRNAs might significantly affect the survival of osteosarcoma patients. Combined use of these lncRNAs may serve as potential novel biomarkers for the indication of clinical outcomes of osteosarcoma patients as well as the selection of adjuvant chemotherapy strategies for clinical treatment of this disease. Keywords: lncRNAs, osteosarcoma

HFE gene C282Y variant is associated with colorectal cancer in Caucasians: a meta-analysis.

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Chen, Weidong; Zhao, Hua; Li, Tiegang; Yao, Hongliang

2013-08-01

The HFE gene has been suggested to play an important role in the pathogenesis of colorectal cancer. However, the results have been conflicting. In this study, we performed a meta-analysis to clarify the association of HFE gene C282Y variant with colorectal cancer. PubMed and Embase were retrieved to identify the potential literature. Pooled odds ratio (OR) with 95 % confidence interval (CI) was calculated using fixed- or random-effects model. A total of eight papers including nine studies (7,588 colorectal cancer cases and 81,571 controls) for HFE gene C282Y variant were included in the meta-analysis. The result indicated that HFE gene C282Y variant was significantly associated with colorectal cancer under recessive model (OR = 2.00, 95 % CI = 1.32-3.04), with no evidence of between-study heterogeneity (I (2) = 0.2 %, p = 0.432). Further subgroup analysis by number of cases suggested the effect was significant in studies with more than 500 cases (OR = 2.51, 95 % CI = 1.58-3.98, I (2) = 0.0 %, p = 0.921), but not in studies with less than 500 cases (OR = 0.75, 95 % CI = 0.28-1.97, I (2) = 0.0 %, p = 0.622). The current meta-analysis supported the positive association of HFE gene C282Y variant with colorectal cancer. Further large-scale studies with the consideration for gene-gene/gene-environment interactions should be conducted to investigate the association.

Prognostic value of stromal decorin expression in patients with breast cancer: a meta-analysis.

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Li, Shuang-Jiang; Chen, Da-Li; Zhang, Wen-Biao; Shen, Cheng; Che, Guo-Wei

2015-11-01

Numbers of studies have investigated the biological functions of decorin (DCN) in oncogenesis, tumor progression, angiogenesis and metastasis. Although many of them aim to highlight the prognostic value of stromal DCN expression in breast cancer, some controversial results still exist and a consensus has not been reached until now. Therefore, our meta-analysis aims to determine the prognostic significance of stromal DCN expression in breast cancer patients. PubMed, EMBASE, the Web of Science and China National Knowledge Infrastructure (CNKI) databases were searched for full-text literatures met out inclusion criteria. We applied the hazard ratio (HR) with 95% confidence interval (CI) as the appropriate summarized statistics. Q-test and I(2) statistic were employed to estimate the level of heterogeneity across the included studies. Sensitivity analysis was conducted to further identify the possible origins of heterogeneity. The publication bias was detected by Begg's test and Egger's test. There were three English literatures (involving 6 studies) included into our meta-analysis. On the one hand, both the summarized outcomes based on univariate analysis (HR: 0.513; 95% CI: 0.406-0.648; Panalysis (HR: 0.544; 95% CI: 0.388-0.763; Panalysis (HR: 0.504; 95% CI: 0.389-0.651; Panalysis (HR: 0.568; 95% CI: 0.400-0.806; P=0.002) also indicated that stromal DCN expression was positively associated with high disease-free survival (DFS) of breast cancer patients. No significant heterogeneity or publication bias was observed within this meta-analysis. The present evidences indicate that high stromal DCN expression can significantly predict the good prognosis in patients with breast cancer. The discoveries from our meta-analysis have better be confirmed in the updated review pooling more relevant investigations in the future.

Prognostic and clinical significance of histone deacetylase 1 expression in breast cancer: A meta-analysis.

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Qiao, Weiqiang; Liu, Heyang; Liu, Ruidong; Liu, Qipeng; Zhang, Ting; Guo, Wanying; Li, Peng; Deng, Miao

2018-05-05

There are conflicting reports about the role of histone deacetylase 1 (HDAC1) in breast cancer prognosis. Here, we conducted a meta-analysis to investigate the prognostic significance of HDAC1 in breast cancer. We searched different databases to identify studies evaluating the association between HDAC1 expression and its prognostic value in breast cancer. The pooled hazard ratios (HRs) and odds radios (ORs) with 95% confidence intervals (95% CIs) were calculated from these studies to assess specific correlation. Our meta-analysis of four databases identified 7 eligible studies with 1429 total patients. We found that HDAC1 over-expression did not correlate with disease-free survival (DFS) and overall survival (OS) in breast cancer. Subgroup analysis indicated an association between up-regulated HDAC1 expression and better OS (HR = 0.47, 95% CI: 0.23-0.97; P = 0.04) in Asian breast cancer patients. However, false-positive report probability (FPRP) analysis and trial sequential analysis (TSA) indicated that the results need further validation. Furthermore, HDAC1 over-expression was associated with positive estrogen receptor (ER) expression (OR, 3.30; 95% CI, 1.11-9.83; P = 0.03) and negative human epidermal growth factor receptor 2 (HER2) expression (OR, 1.79; 95% CI, 1.22-2.61; P = 0.003), but there were no significant differences between patients based on age, tumor size, lymph node metastasis, nuclear grade, or progesterone receptor (PR) expression. Overall, our meta-analysis demonstrated an association between increased HDAC1 expression and better OS in Asian breast cancer patients. In addition, HDAC1 over-expression correlated with positive ER and negative HER2 expression in breast cancer. However, researches in large patients' randomised controlled trials (RCTs) are needed to confirm the results. Copyright © 2018 Elsevier B.V. All rights reserved.

An expression meta-analysis of predicted microRNA targets identifies a diagnostic signature for lung cancer

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Liang Yu

2008-12-01

Full Text Available Abstract Background Patients diagnosed with lung adenocarcinoma (AD and squamous cell carcinoma (SCC, two major histologic subtypes of lung cancer, currently receive similar standard treatments, but resistance to adjuvant chemotherapy is prevalent. Identification of differentially expressed genes marking AD and SCC may prove to be of diagnostic value and help unravel molecular basis of their histogenesis and biologies, and deliver more effective and specific systemic therapy. Methods MiRNA target genes were predicted by union of miRanda, TargetScan, and PicTar, followed by screening for matched gene symbols in NCBI human sequences and Gene Ontology (GO terms using the PANTHER database that was also used for analyzing the significance of biological processes and pathways within each ontology term. Microarray data were extracted from Gene Expression Omnibus repository, and tumor subtype prediction by gene expression used Prediction Analysis of Microarrays. Results Computationally predicted target genes of three microRNAs, miR-34b/34c/449, that were detected in human lung, testis, and fallopian tubes but not in other normal tissues, were filtered by representation of GO terms and their ability to classify lung cancer subtypes, followed by a meta-analysis of microarray data to classify AD and SCC. Expression of a minimal set of 17 predicted miR-34b/34c/449 target genes derived from the developmental process GO category was identified from a training set to classify 41 AD and 17 SCC, and correctly predicted in average 87% of 354 AD and 82% of 282 SCC specimens from total 9 independent published datasets. The accuracy of prediction still remains comparable when classifying 103 AD and 79 SCC samples from another 4 published datasets that have only 14 to 16 of the 17 genes available for prediction (84% and 85% for AD and SCC, respectively. Expression of this signature in two published datasets of epithelial cells obtained at bronchoscopy from cigarette

Developmental and environmental regulation of Aquaporin gene expression across Populus species: divergence or redundancy?

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Cohen, David; Bogeat-Triboulot, Marie-Béatrice; Vialet-Chabrand, Silvère; Merret, Rémy; Courty, Pierre-Emmanuel; Moretti, Sébastien; Bizet, François; Guilliot, Agnès; Hummel, Irène

2013-01-01

Aquaporins (AQPs) are membrane channels belonging to the major intrinsic proteins family and are known for their ability to facilitate water movement. While in Populus trichocarpa, AQP proteins form a large family encompassing fifty-five genes, most of the experimental work focused on a few genes or subfamilies. The current work was undertaken to develop a comprehensive picture of the whole AQP gene family in Populus species by delineating gene expression domain and distinguishing responsiveness to developmental and environmental cues. Since duplication events amplified the poplar AQP family, we addressed the question of expression redundancy between gene duplicates. On these purposes, we carried a meta-analysis of all publicly available Affymetrix experiments. Our in-silico strategy controlled for previously identified biases in cross-species transcriptomics, a necessary step for any comparative transcriptomics based on multispecies design chips. Three poplar AQPs were not supported by any expression data, even in a large collection of situations (abiotic and biotic constraints, temporal oscillations and mutants). The expression of 11 AQPs was never or poorly regulated whatever the wideness of their expression domain and their expression level. Our work highlighted that PtTIP1;4 was the most responsive gene of the AQP family. A high functional divergence between gene duplicates was detected across species and in response to tested cues, except for the root-expressed PtTIP2;3/PtTIP2;4 pair exhibiting 80% convergent responses. Our meta-analysis assessed key features of aquaporin expression which had remained hidden in single experiments, such as expression wideness, response specificity and genotype and environment interactions. By consolidating expression profiles using independent experimental series, we showed that the large expansion of AQP family in poplar was accompanied with a strong divergence of gene expression, even if some cases of functional redundancy

Developmental and environmental regulation of Aquaporin gene expression across Populus species: divergence or redundancy?

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David Cohen

Full Text Available Aquaporins (AQPs are membrane channels belonging to the major intrinsic proteins family and are known for their ability to facilitate water movement. While in Populus trichocarpa, AQP proteins form a large family encompassing fifty-five genes, most of the experimental work focused on a few genes or subfamilies. The current work was undertaken to develop a comprehensive picture of the whole AQP gene family in Populus species by delineating gene expression domain and distinguishing responsiveness to developmental and environmental cues. Since duplication events amplified the poplar AQP family, we addressed the question of expression redundancy between gene duplicates. On these purposes, we carried a meta-analysis of all publicly available Affymetrix experiments. Our in-silico strategy controlled for previously identified biases in cross-species transcriptomics, a necessary step for any comparative transcriptomics based on multispecies design chips. Three poplar AQPs were not supported by any expression data, even in a large collection of situations (abiotic and biotic constraints, temporal oscillations and mutants. The expression of 11 AQPs was never or poorly regulated whatever the wideness of their expression domain and their expression level. Our work highlighted that PtTIP1;4 was the most responsive gene of the AQP family. A high functional divergence between gene duplicates was detected across species and in response to tested cues, except for the root-expressed PtTIP2;3/PtTIP2;4 pair exhibiting 80% convergent responses. Our meta-analysis assessed key features of aquaporin expression which had remained hidden in single experiments, such as expression wideness, response specificity and genotype and environment interactions. By consolidating expression profiles using independent experimental series, we showed that the large expansion of AQP family in poplar was accompanied with a strong divergence of gene expression, even if some cases of

Gene expression profiling of resting and activated vascular smooth muscle cells by serial analysis of gene expression and clustering analysis

NARCIS (Netherlands)

Beauchamp, Nicholas J.; van Achterberg, Tanja A. E.; Engelse, Marten A.; Pannekoek, Hans; de Vries, Carlie J. M.

2003-01-01

Migration and proliferation of vascular smooth muscle cells (SMCs) are key events in atherosclerosis. However, little is known about alterations in gene expression upon transition of the quiescent, contractile SMC to the proliferative SMC. We performed serial analysis of gene expression (SAGE) of

A comparative study of three different gene expression analysis methods.

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Choe, Jae Young; Han, Hyung Soo; Lee, Seon Duk; Lee, Hanna; Lee, Dong Eun; Ahn, Jae Yun; Ryoo, Hyun Wook; Seo, Kang Suk; Kim, Jong Kun

2017-12-04

TNF-α regulates immune cells and acts as an endogenous pyrogen. Reverse transcription polymerase chain reaction (RT-PCR) is one of the most commonly used methods for gene expression analysis. Among the alternatives to PCR, loop-mediated isothermal amplification (LAMP) shows good potential in terms of specificity and sensitivity. However, few studies have compared RT-PCR and LAMP for human gene expression analysis. Therefore, in the present study, we compared one-step RT-PCR, two-step RT-LAMP and one-step RT-LAMP for human gene expression analysis. We compared three gene expression analysis methods using the human TNF-α gene as a biomarker from peripheral blood cells. Total RNA from the three selected febrile patients were subjected to the three different methods of gene expression analysis. In the comparison of three gene expression analysis methods, the detection limit of both one-step RT-PCR and one-step RT-LAMP were the same, while that of two-step RT-LAMP was inferior. One-step RT-LAMP takes less time, and the experimental result is easy to determine. One-step RT-LAMP is a potentially useful and complementary tool that is fast and reasonably sensitive. In addition, one-step RT-LAMP could be useful in environments lacking specialized equipment or expertise.

Comprehensive analysis of gene expression patterns of hedgehog-related genes

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Baillie David

2006-10-01

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

Meta-analytic framework for liquid association.

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Wang, Lin; Liu, Silvia; Ding, Ying; Yuan, Shin-Sheng; Ho, Yen-Yi; Tseng, George C

2017-07-15

Although coexpression analysis via pair-wise expression correlation is popularly used to elucidate gene-gene interactions at the whole-genome scale, many complicated multi-gene regulations require more advanced detection methods. Liquid association (LA) is a powerful tool to detect the dynamic correlation of two gene variables depending on the expression level of a third variable (LA scouting gene). LA detection from single transcriptomic study, however, is often unstable and not generalizable due to cohort bias, biological variation and limited sample size. With the rapid development of microarray and NGS technology, LA analysis combining multiple gene expression studies can provide more accurate and stable results. In this article, we proposed two meta-analytic approaches for LA analysis (MetaLA and MetaMLA) to combine multiple transcriptomic studies. To compensate demanding computing, we also proposed a two-step fast screening algorithm for more efficient genome-wide screening: bootstrap filtering and sign filtering. We applied the methods to five Saccharomyces cerevisiae datasets related to environmental changes. The fast screening algorithm reduced 98% of running time. When compared with single study analysis, MetaLA and MetaMLA provided stronger detection signal and more consistent and stable results. The top triplets are highly enriched in fundamental biological processes related to environmental changes. Our method can help biologists understand underlying regulatory mechanisms under different environmental exposure or disease states. A MetaLA R package, data and code for this article are available at http://tsenglab.biostat.pitt.edu/software.htm. ctseng@pitt.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Gene expression analysis of flax seed development

Science.gov (United States)

2011-01-01

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

Gene expression analysis of flax seed development

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Sharpe Andrew

2011-04-01

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

Gene-based meta-analysis of genome-wide association studies implicates new loci involved in obesity

DEFF Research Database (Denmark)

Hägg, Sara; Ganna, Andrea; Van Der Laan, Sander W

2015-01-01

) approach to assign variants to genes and to calculate gene-based P-values based on simulations. The VEGAS method was applied to each cohort separately before a gene-based meta-analysis was performed. In Stage 1, two known (FTO and TMEM18) and six novel (PEX2, MTFR2, SSFA2, IARS2, CEP295 and TXNDC12) loci...

RETINOBASE: a web database, data mining and analysis platform for gene expression data on retina

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Léveillard Thierry

2008-05-01

Full Text Available Abstract Background The retina is a multi-layered sensory tissue that lines the back of the eye and acts at the interface of input light and visual perception. Its main function is to capture photons and convert them into electrical impulses that travel along the optic nerve to the brain where they are turned into images. It consists of neurons, nourishing blood vessels and different cell types, of which neural cells predominate. Defects in any of these cells can lead to a variety of retinal diseases, including age-related macular degeneration, retinitis pigmentosa, Leber congenital amaurosis and glaucoma. Recent progress in genomics and microarray technology provides extensive opportunities to examine alterations in retinal gene expression profiles during development and diseases. However, there is no specific database that deals with retinal gene expression profiling. In this context we have built RETINOBASE, a dedicated microarray database for retina. Description RETINOBASE is a microarray relational database, analysis and visualization system that allows simple yet powerful queries to retrieve information about gene expression in retina. It provides access to gene expression meta-data and offers significant insights into gene networks in retina, resulting in better hypothesis framing for biological problems that can subsequently be tested in the laboratory. Public and proprietary data are automatically analyzed with 3 distinct methods, RMA, dChip and MAS5, then clustered using 2 different K-means and 1 mixture models method. Thus, RETINOBASE provides a framework to compare these methods and to optimize the retinal data analysis. RETINOBASE has three different modules, "Gene Information", "Raw Data System Analysis" and "Fold change system Analysis" that are interconnected in a relational schema, allowing efficient retrieval and cross comparison of data. Currently, RETINOBASE contains datasets from 28 different microarray experiments performed

Systematic enrichment analysis of gene expression profiling studies identifies consensus pathways implicated in colorectal cancer development

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Jesús Lascorz

2011-01-01

Full Text Available Background: A large number of gene expression profiling (GEP studies on colorectal carcinogenesis have been performed but no reliable gene signature has been identified so far due to the lack of reproducibility in the reported genes. There is growing evidence that functionally related genes, rather than individual genes, contribute to the etiology of complex traits. We used, as a novel approach, pathway enrichment tools to define functionally related genes that are consistently up- or down-regulated in colorectal carcinogenesis. Materials and Methods: We started the analysis with 242 unique annotated genes that had been reported by any of three recent meta-analyses covering GEP studies on genes differentially expressed in carcinoma vs normal mucosa. Most of these genes (218, 91.9% had been reported in at least three GEP studies. These 242 genes were submitted to bioinformatic analysis using a total of nine tools to detect enrichment of Gene Ontology (GO categories or Kyoto Encyclopedia of Genes and Genomes (KEGG pathways. As a final consistency criterion the pathway categories had to be enriched by several tools to be taken into consideration. Results: Our pathway-based enrichment analysis identified the categories of ribosomal protein constituents, extracellular matrix receptor interaction, carbonic anhydrase isozymes, and a general category related to inflammation and cellular response as significantly and consistently overrepresented entities. Conclusions: We triaged the genes covered by the published GEP literature on colorectal carcinogenesis and subjected them to multiple enrichment tools in order to identify the consistently enriched gene categories. These turned out to have known functional relationships to cancer development and thus deserve further investigation.

Brain Responses to Dynamic Facial Expressions: A Normative Meta-Analysis

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Oksana Zinchenko

2018-06-01

Full Text Available Identifying facial expressions is crucial for social interactions. Functional neuroimaging studies show that a set of brain areas, such as the fusiform gyrus and amygdala, become active when viewing emotional facial expressions. The majority of functional magnetic resonance imaging (fMRI studies investigating face perception typically employ static images of faces. However, studies that use dynamic facial expressions (e.g., videos are accumulating and suggest that a dynamic presentation may be more sensitive and ecologically valid for investigating faces. By using quantitative fMRI meta-analysis the present study examined concordance of brain regions associated with viewing dynamic facial expressions. We analyzed data from 216 participants that participated in 14 studies, which reported coordinates for 28 experiments. Our analysis revealed bilateral fusiform and middle temporal gyri, left amygdala, left declive of the cerebellum and the right inferior frontal gyrus. These regions are discussed in terms of their relation to models of face processing.

Brain Responses to Dynamic Facial Expressions: A Normative Meta-Analysis.

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Zinchenko, Oksana; Yaple, Zachary A; Arsalidou, Marie

2018-01-01

Identifying facial expressions is crucial for social interactions. Functional neuroimaging studies show that a set of brain areas, such as the fusiform gyrus and amygdala, become active when viewing emotional facial expressions. The majority of functional magnetic resonance imaging (fMRI) studies investigating face perception typically employ static images of faces. However, studies that use dynamic facial expressions (e.g., videos) are accumulating and suggest that a dynamic presentation may be more sensitive and ecologically valid for investigating faces. By using quantitative fMRI meta-analysis the present study examined concordance of brain regions associated with viewing dynamic facial expressions. We analyzed data from 216 participants that participated in 14 studies, which reported coordinates for 28 experiments. Our analysis revealed bilateral fusiform and middle temporal gyri, left amygdala, left declive of the cerebellum and the right inferior frontal gyrus. These regions are discussed in terms of their relation to models of face processing.

Comparative analysis of gene expression in normal and cancer human prostate cell lines

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E. E. Rosenberg

2014-04-01

Full Text Available Prostate cancer is one of the main causes of mortality in men with malignant tumors. The urgent problem was a search for biomarkers of prostate cancer, which would allow distinguishing between aggressive metastatic and latent tumors. The aim of this work was to search for differentially expressed genes in normal epithelial cells PNT2 and prostate cancer cell lines LNCaP, DU145 and PC3, produced from tumors with different aggressiveness and metas­tatic ability. Such genes might be used to create a panel of prognostic markers for aggressiveness and metastasis. Relative gene expression of 65 cancer-related genes was determined by the quantitative polymerase chain reaction (Q-PCR. Expression of 29 genes was changed in LNCaP cells, 20 genes in DU145 and 16 genes in PC3 cell lines, compared with normal line PNT2. The obtained data make it possible to conclude that the epithelial-mesenchymal cell transition took place, which involved the loss of epithelial markers, reduced cell adhesion and increased migration. We have also found few differentially expressed genes among 3 prostate cancer cell lines. We have found that genes, involved in cell adhesion (CDH1, invasiveness and metastasis (IL8, CXCL2 and cell cycle control (P16, CCNE1 underwent most changes. These genes might be used for diagnosis and prognosis of invasive metastatic prostate tumors.

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

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Tintle Nathan L

2012-08-01

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

Prognostic significance of p53 expression in patients with esophageal cancer: a meta-analysis

International Nuclear Information System (INIS)

Wang, Lianghai; Yu, Xiaodan; Li, Jing; Zhang, Zhiyu; Hou, Jun; Li, Feng

2016-01-01

The prognostic value of p53 protein expression in esophageal cancer has been evaluated, but the results remain inconclusive and no consensus has yet been achieved. This meta-analysis was conducted to quantitatively assess the prognostic significance of p53 expression in esophageal cancer. Publications that assessed the clinical or prognostic significance of p53 expression in esophageal cancer and were published before July 1, 2015 were identified by searching the PubMed and EMBASE databases. A meta-analysis was performed to clarify the association between p53 expression and the clinical outcomes. A total of 36 publications met the criteria and included 4577 cases. Analysis of these data showed that p53 expression in esophageal cancer was significantly associated with poorer 5-year survival (RR = 1.30, 95 % CI: 1.11–1.51, P = 0.0008). Subgroup analyses according to histological type, continent of the patients, and cut-off value revealed the similar results. The results also indicated that p53 expression was highly associated with advanced TNM stages (I/II vs. III/IV, OR = 0.74, 95 % CI: 0.55–0.99, P = 0.04), lymph node metastasis (OR = 0.77, 95 % CI: 0.66–0.90, P = 0.001), and distant metastasis (OR = 0.46, 95 % CI: 0.26–0.80, P = 0.006). However, p53 expression in the included studies was not significantly associated with tumor size (≤ 5 cm vs. > 5 cm, OR = 1.13, 95 % CI: 0.92–1.40, P = 0.24), tumor location (upper + middle vs. lower, OR = 0.91, 95 % CI: 0.70–1.17, P = 0.45), grade of differentiation (well + moderate vs. poor, OR = 1.10, 95 % CI: 0.90–1.34, P = 0.35), and the depth of invasion (T1/T2 vs. T3/T4, OR = 0.86, 95 % CI: 0.71–1.03, P = 0.09). This meta-analysis showed that p53 expression may be a useful biomarker for predicting poorer prognosis in patients with esophageal cancer

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

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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

Meta-analysis of crowdsourced data compendia suggests pan-disease transcriptional signatures of autoimmunity [version 1; referees: 2 approved

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William W. Lau

2016-12-01

Full Text Available Background: The proliferation of publicly accessible large-scale biological data together with increasing availability of bioinformatics tools have the potential to transform biomedical research. Here we report a crowdsourcing Jamboree that explored whether a team of volunteer biologists without formal bioinformatics training could use OMiCC, a crowdsourcing web platform that facilitates the reuse and (meta- analysis of public gene expression data, to compile and annotate gene expression data, and design comparisons between disease and control sample groups. Methods: The Jamboree focused on several common human autoimmune diseases, including systemic lupus erythematosus (SLE, multiple sclerosis (MS, type I diabetes (DM1, and rheumatoid arthritis (RA, and the corresponding mouse models. Meta-analyses were performed in OMiCC using comparisons constructed by the participants to identify 1 gene expression signatures for each disease (disease versus healthy controls at the gene expression and biological pathway levels, 2 conserved signatures across all diseases within each species (pan-disease signatures, and 3 conserved signatures between species for each disease and across all diseases (cross-species signatures. Results: A large number of differentially expressed genes were identified for each disease based on meta-analysis, with observed overlap among diseases both within and across species. Gene set/pathway enrichment of upregulated genes suggested conserved signatures (e.g., interferon across all human and mouse conditions. Conclusions: Our Jamboree exercise provides evidence that when enabled by appropriate tools, a "crowd" of biologists can work together to accelerate the pace by which the increasingly large amounts of public data can be reused and meta-analyzed for generating and testing hypotheses. Our encouraging experience suggests that a similar crowdsourcing approach can be used to explore other biological questions.

A meta-analysis of the association between cytokine gene polymorphisms and systemic sclerosis.

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Peng, Wen-jia; Pan, Hai-feng; Tao, Jin-hui; Wang, Bing-xiang; Lu, Man-man; Wang, Song; He, Qian; Wang, Jing

2012-09-01

We conducted a comprehensive meta-analysis to quantitatively evaluate the association of cytokine gene polymorphisms with systemic sclerosis (SSc) susceptibility. Electronic databases were used to identify published studies before July 2011. In total, 23 case-control studies including 3524 SSc cases and 6086 healthy controls were included in the meta-analysis. We examined the relationship between five gene polymorphisms [cytotoxic T lymphocyte associated antigen 4 (CTLA-4) -1722T/C, CTLA-4 -318C/T, CTLA-4 +49A/G, angiotensin-converting enzyme I/D, STAT-4 rs7574865] and susceptibility to SSc. The combined odds ratio (OR) with 95% confidence interval (95% CI) was calculated to estimate the strength of the association in a fixed or random effect model. Heterogeneity and publication bias were also assessed. We found a significant association between SSc and STAT rs7574865 (TT vs. GG: OR 0.44, 95% CI 0.36-0.54; TT vs. TG + GG: OR 0.48, 95% CI 0.39-0.59; TT + TG vs. GG: OR 0.74, 95% CI 0.66-0.83; T vs. G: OR 0.72, 95% CI 0.66-0.79), but there were no other statistically significant associations with other gene polymorphisms. Our study suggested that SSc is associated with STAT gene rs7574865 polymorphism.

Meta-analysis of Arabidopsis KANADI1 direct target genes identifies basic growth-promoting module acting upstream of hormonal signaling pathways

DEFF Research Database (Denmark)

Xie, Yakun; Straub, Daniel; Eguen, Teinai Ebimienere

2015-01-01

An intricate network of antagonistically acting transcription factors mediates formation of a flat leaf lamina of Arabidopsis thaliana plants. In this context, members of the class III homeodomain leucine zipper (HD-ZIPIII) transcription factor family specify the adaxial domain (future upper side......) of the leaf, while antagonistically acting KANADI transcription factors determine the abaxial domain (future lower side). Here we used an mRNA-seq approach to identify genes regulated by KANADI1 (KAN1) and subsequently performed a meta-analysis approach combining our datasets with published genome......-wide datasets. Our analysis revealed that KAN1 acts upstream of several genes encoding auxin biosynthetic enzymes. When exposed to shade, we find three YUCCA genes, YUC2, YUC5 and YUC8 to be transcriptionally upregulated, which correlates with an increase in the levels of free auxin. When ectopically expressed...

Association between FOXO3A gene polymorphisms and human longevity: a meta-analysis

OpenAIRE

Bao, Ji-Ming; Song, Xian-Lu; Hong, Ying-Qia; Zhu, Hai-Li; Li, Cui; Zhang, Tao; Chen, Wei; Zhao, Shan-Chao; Chen, Qing

2014-01-01

Numerous studies have shown associations between the FOXO3A gene, encoding the forkhead box O3 transcription factor, and human or specifically male longevity. However, the associations of specific FOXO3A polymorphisms with longevity remain inconclusive. We performed a meta-analysis of existing studies to clarify these potential associations. A comprehensive search was conducted to identify studies of FOXO3A gene polymorphisms and longevity. Pooled odds ratios (ORs) and 95% confidence interval...

Suppression and expression of emotion in social and interpersonal outcomes: A meta-analysis.

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Chervonsky, Elizabeth; Hunt, Caroline

2017-06-01

Emotion expression is critical for the communication of important social information, such as emotional states and behavioral intentions. However, people tend to vary in their level of emotional expression. This meta-analysis investigated the relationships between levels of emotion expression and suppression, and social and interpersonal outcomes. PsycINFO databases, as well as reference lists were searched. Forty-three papers from a total of 3,200 papers met inclusion criteria, allowing for 105 effect sizes to be calculated. Meta-analyses revealed that greater suppression of emotion was significantly associated with poorer social wellbeing, including more negative first impressions, lower social support, lower social satisfaction and quality, and poorer romantic relationship quality. Furthermore, the expression of positive and general/nonspecific emotion was related to better social outcomes, while the expression of anger was associated with poorer social wellbeing. Expression of negative emotion generally was also associated with poorer social outcomes, although this effect size was very small and consisted of mixed results. These findings highlight the importance of considering the role that regulation of emotional expression can play in the development of social dysfunction and interpersonal problems. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Global Transcriptome Analysis of Combined Abiotic Stress Signaling Genes Unravels Key Players in Oryza sativa L.: An In silico Approach

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Pandiyan Muthuramalingam

2017-05-01

Full Text Available Combined abiotic stress (CAbS affects the field grown plants simultaneously. The multigenic and quantitative nature of uncontrollable abiotic stresses complicates the process of understanding the stress response by plants. Considering this, we analyzed the CAbS response of C3 model plant, Oryza sativa by meta-analysis. The datasets of commonly expressed genes by drought, salinity, submergence, metal, natural expression, biotic, and abiotic stresses were data mined through publically accessible transcriptomic abiotic stress (AbS responsive datasets. Of which 1,175, 12,821, and 42,877 genes were commonly expressed in meta differential, individual differential, and unchanged expressions respectively. Highly regulated 100 differentially expressed AbS genes were derived through integrative meta-analysis of expression data (INMEX. Of this 30 genes were identified from AbS gene families through expression atlas that were computationally analyzed for their physicochemical properties. All AbS genes were physically mapped against O. sativa genome. Comparative mapping of these genes demonstrated the orthologous relationship with related C4 panicoid genome. In silico expression analysis of these genes showed differential expression patterns in different developmental tissues. Protein–protein interaction of these genes, represented the complexity of AbS. Computational expression profiling of candidate genes in response to multiple stresses suggested the putative involvement of OS05G0350900, OS02G0612700, OS05G0104200, OS03G0596200, OS12G0225900, OS07G0152000, OS08G0119500, OS06G0594700, and Os01g0393100 in CAbS. These potential candidate genes need to be studied further to decipher their functional roles in AbS dynamics.

Dissociation between recognition and detection advantage for facial expressions: a meta-analysis.

Science.gov (United States)

Nummenmaa, Lauri; Calvo, Manuel G

2015-04-01

Happy facial expressions are recognized faster and more accurately than other expressions in categorization tasks, whereas detection in visual search tasks is widely believed to be faster for angry than happy faces. We used meta-analytic techniques for resolving this categorization versus detection advantage discrepancy for positive versus negative facial expressions. Effect sizes were computed on the basis of the r statistic for a total of 34 recognition studies with 3,561 participants and 37 visual search studies with 2,455 participants, yielding a total of 41 effect sizes for recognition accuracy, 25 for recognition speed, and 125 for visual search speed. Random effects meta-analysis was conducted to estimate effect sizes at population level. For recognition tasks, an advantage in recognition accuracy and speed for happy expressions was found for all stimulus types. In contrast, for visual search tasks, moderator analysis revealed that a happy face detection advantage was restricted to photographic faces, whereas a clear angry face advantage was found for schematic and "smiley" faces. Robust detection advantage for nonhappy faces was observed even when stimulus emotionality was distorted by inversion or rearrangement of the facial features, suggesting that visual features primarily drive the search. We conclude that the recognition advantage for happy faces is a genuine phenomenon related to processing of facial expression category and affective valence. In contrast, detection advantages toward either happy (photographic stimuli) or nonhappy (schematic) faces is contingent on visual stimulus features rather than facial expression, and may not involve categorical or affective processing. (c) 2015 APA, all rights reserved).

Expression microarray meta-analysis identifies genes associated with Ras/MAPK and related pathways in progression of muscle-invasive bladder transition cell carcinoma.

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Jonathan A Ewald

Full Text Available The effective detection and management of muscle-invasive bladder Transition Cell Carcinoma (TCC continues to be an urgent clinical challenge. While some differences of gene expression and function in papillary (Ta, superficial (T1 and muscle-invasive (≥T2 bladder cancers have been investigated, the understanding of mechanisms involved in the progression of bladder tumors remains incomplete. Statistical methods of pathway-enrichment, cluster analysis and text-mining can extract and help interpret functional information about gene expression patterns in large sets of genomic data. The public availability of patient-derived expression microarray data allows open access and analysis of large amounts of clinical data. Using these resources, we investigated gene expression differences associated with tumor progression and muscle-invasive TCC. Gene expression was calculated relative to Ta tumors to assess progression-associated differences, revealing a network of genes related to Ras/MAPK and PI3K signaling pathways with increased expression. Further, we identified genes within this network that are similarly expressed in superficial Ta and T1 stages but altered in muscle-invasive T2 tumors, finding 7 genes (COL3A1, COL5A1, COL11A1, FN1, ErbB3, MAPK10 and CDC25C whose expression patterns in muscle-invasive tumors are consistent in 5 to 7 independent outside microarray studies. Further, we found increased expression of the fibrillar collagen proteins COL3A1 and COL5A1 in muscle-invasive tumor samples and metastatic T24 cells. Our results suggest that increased expression of genes involved in mitogenic signaling may support the progression of muscle-invasive bladder tumors that generally lack activating mutations in these pathways, while expression changes of fibrillar collagens, fibronectin and specific signaling proteins are associated with muscle-invasive disease. These results identify potential biomarkers and targets for TCC treatments, and

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

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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

The identification of functional motifs in temporal gene expression analysis

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Michael G. Surette

2005-01-01

Full Text Available The identification of transcription factor binding sites is essential to the understanding of the regulation of gene expression and the reconstruction of genetic regulatory networks. The in silico identification of cis-regulatory motifs is challenging due to sequence variability and lack of sufficient data to generate consensus motifs that are of quantitative or even qualitative predictive value. To determine functional motifs in gene expression, we propose a strategy to adopt false discovery rate (FDR and estimate motif effects to evaluate combinatorial analysis of motif candidates and temporal gene expression data. The method decreases the number of predicted motifs, which can then be confirmed by genetic analysis. To assess the method we used simulated motif/expression data to evaluate parameters. We applied this approach to experimental data for a group of iron responsive genes in Salmonella typhimurium 14028S. The method identified known and potentially new ferric-uptake regulator (Fur binding sites. In addition, we identified uncharacterized functional motif candidates that correlated with specific patterns of expression. A SAS code for the simulation and analysis gene expression data is available from the first author upon request.

Asthma susceptible genes in Chinese population: A meta-analysis

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He Chao

2010-09-01

Full Text Available Abstract Background Published data regarding the associations between genetic variants and asthma risk in Chinese population were inconclusive. The aim of this study was to investigate asthma susceptible genes in Chinese population. Methods The authors conducted 18 meta-analyzes for 18 polymorphisms in 13 genes from eighty-two publications. Results Seven polymorphisms were found being associated with risk of asthma, namely: A Disintegrin and Metalloprotease 33 (ADAM33 T1-C/T (odds ratio [OR] = 6.07, 95% confidence interval [CI]: 2.69-13.73, Angiotensin-Converting Enzyme (ACE D/I (OR = 3.85, 95%CI: 2.49-5.94, High-affinity IgE receptor β chain (FcεRIβ -6843G/A (OR = 1.49, 95%CI: 1.01-2.22, Interleukin 13(IL-13 -1923C/T (OR = 2.99, 95%CI: 2.12-4.24, IL-13 -2044A/G (OR = 1.49, 95%CI: 1.07-2.08, Regulated upon Activation, Normal T cell Expressed and Secreted (RANTES -28C/G (OR = 1.64, 95%CI: 1.09-2.46, Tumor Necrosis Factor-α (TNF-α -308G/A(OR = 1.42, 95%CI: 1.09, 1.85. After subgroup analysis by age, the ACE D/I, β2-Adrenergic Receptor (β2-AR -79G/C, TNF-α -308G/A, Interleukin 4 receptor(IL-4R -1902G/A and IL-13 -1923C/T polymorphisms were found significantly associated with asthma risk in Chinese children. In addition, the ACE D/I, FcεRIβ -6843G/A, TNF-α -308G/A, IL-13 -1923C/T and IL-13 -2044A/G polymorphisms were associated with asthma risk in Chinese adults. Conclusion ADAM33, FcεRIβ, RANTES, TNF-α, ACE, β2-AR, IL-4R and IL-13 genes could be proposed as asthma susceptible genes in Chinese population. Given the limited number of studies, more data are required to validate these associations.

Polymorphisms in interleukins 17A and 17F genes and periodontitis: results from a meta-analysis.

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da Silva, Felipe Rodolfo Pereira; Pessoa, Larissa Dos Santos; Vasconcelos, Any Carolina Cardoso Guimarães; de Aquino Lima, Weberson; Alves, Even Herlany Pereira; Vasconcelos, Daniel Fernando Pereira

2017-12-01

Polymorphisms in inflammatory genes such as interleukins 17A and 17F are associated with the risk of development of periodontitis, although the results remain contradictory. Hence, the aim of this study was perform a meta-analysis focusing on two polymorphisms (rs2275913 and rs763780) in interleukins 17A and 17F genes, respectively, in both chronic (CP) and aggressive periodontitis (AgP). A review in literature was performed in several databases for studies published before 25, September 2016. The meta-analysis was obtained through the review manager statistical software (version 5.2) with odds ratio (OR) calculation and funnel plot (P < 0.05) for heterogeneity, as well as the comprehensive meta-analysis software (version 3.3.070) for the assessment of publication bias. Seven articles with 1540 participants composed the results in which the mutant allele in the rs2275913 polymorphism did not present significant association with the risk of CP or AgP (OR 1.56, 95% CI 0.77, 3.15, P = 0.21; OR 1.12, 95% CI 0.05, 23.44, P = 0.94, respectively) nor was the mutant allele in rs763780 associated with the risk of CP (OR 1.19, 95% CI 0.80, 1.76, P = 0.39) or AgP (OR 1.07, 95% CI 0.63, 1.84, P = 0.79). No bias of publication was observed by Egger's and Begg's tests in any allelic evaluation. This meta-analysis showed a non-significant association between the polymorphisms rs2275913 and rs763780 in interleukins 17A and 17F genes and chronic and aggressive periodontitis in the allelic evaluation.

Associations of CTLA4 Gene Polymorphisms with Graves’ Ophthalmopathy: A Meta-Analysis

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Pengfei Du

2014-01-01

Full Text Available Many studies have established that T-lymphocyte antigen-4 (CTLA4 is a susceptible gene for Graves’ disease (GD. Also many studies showed the association between the CTLA4 exon-1 49A/G polymorphism and the risk of developing Graves’ ophthalmopathy (GO in GD patients. But those results were inconsistent. In recent years many new studies were published which helped to shed light on the relationship of CTLA4 SNP49 with GO. So we performed the meta-analysis to explore the association between the SNP49 and GO susceptibility in GD patients. Studies up to February 29, 2012, were searched by using PubMed. The odds ratio was used to evaluate the strength of the association. Altogether 12 case-control studies involving 2,505 participants were included in the meta-analysis. Results showed that the G allele was related to the increased risk of GO compared with the A allele under allelic genetic model (OR = 1.14, 95% CI: 1.14–1.72, P=0.001 in European subgroup. No publication bias was detected. Our results showed that the SNP49 polymorphism of CTLA4 gene was related to increased risk of GO.

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

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

2013-01-01

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

Microarray analysis of the gene expression profile in triethylene ...

African Journals Online (AJOL)

Microarray analysis of the gene expression profile in triethylene glycol dimethacrylate-treated human dental pulp cells. ... Conclusions: Our results suggest that TEGDMA can change the many functions of hDPCs through large changes in gene expression levels and complex interactions with different signaling pathways.

Analysis of multiplex gene expression maps obtained by voxelation

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Smith Desmond J

2009-04-01

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

Analysis of multiplex gene expression maps obtained by voxelation.

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

2009-04-29

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

Quantitative Trait Locus (QTL meta-analysis and comparative genomics for candidate gene prediction in perennial ryegrass (Lolium perenne L.

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Shinozuka Hiroshi

2012-11-01

Full Text Available Abstract Background In crop species, QTL analysis is commonly used for identification of factors contributing to variation of agronomically important traits. As an important pasture species, a large number of QTLs have been reported for perennial ryegrass based on analysis of biparental mapping populations. Further characterisation of those QTLs is, however, essential for utilisation in varietal improvement programs. Results A bibliographic survey of perennial ryegrass trait-dissection studies identified a total of 560 QTLs from previously published papers, of which 189, 270 and 101 were classified as morphology-, physiology- and resistance/tolerance-related loci, respectively. The collected dataset permitted a subsequent meta-QTL study and implementation of a cross-species candidate gene identification approach. A meta-QTL analysis based on use of the BioMercator software was performed to identify two consensus regions for pathogen resistance traits. Genes that are candidates for causal polymorphism underpinning perennial ryegrass QTLs were identified through in silico comparative mapping using rice databases, and 7 genes were assigned to the p150/112 reference map. Markers linked to the LpDGL1, LpPh1 and LpPIPK1 genes were located close to plant size, leaf extension time and heading date-related QTLs, respectively, suggesting that these genes may be functionally associated with important agronomic traits in perennial ryegrass. Conclusions Functional markers are valuable for QTL meta-analysis and comparative genomics. Enrichment of such genetic markers may permit further detailed characterisation of QTLs. The outcomes of QTL meta-analysis and comparative genomics studies may be useful for accelerated development of novel perennial ryegrass cultivars with desirable traits.

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

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Meizhen eWang

2016-01-01

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

Note of the methodological flaws in the paper entitled "Polymorphisms in IL-4/IL-13 pathway genes and glioma risk: an updated meta-analysis".

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Wang, Ting-Ting; Li, Jin-Mei; Zhou, Dong

2016-01-01

With great interest, we read the paper "Polymorphisms in IL-4/IL-13 pathway genes and glioma risk: an updated meta-analysis" (by Chen PQ et al.) [1], which has reached important conclusions about the relationship between polymorphisms in interleukin (IL)-4/IL-13 pathway genes and glioma risk. Through quantitative analysis, the meta-analysis found no association between IL-4/IL-13 pathway genetic polymorphisms and glioma risk (Chen et al. in Tumor Biol 36:121-127, 2015). The meta-analysis is the most comprehensive study of polymorphisms in the IL-4/IL-13 pathway and glioma risk. Nevertheless, some deficiencies still exist in this meta-analysis that we would like to raise.

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

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Ellis Stephen G

2011-03-01

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

E-selectin gene polymorphisms and essential hypertension in Asian population: an updated meta-analysis.

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Gaojun Cai

Full Text Available Epidemiological studies have shown that E-selectin gene polymorphisms (A561C and C1839T may be associated with essential hypertension (EH, but the results are conflicting in different ethnic populations. Thus, we performed this meta-analysis to investigate a more authentic association between E-selectin gene polymorphisms and the risk of EH.We searched the relevant studies for the present meta-analysis from the following electronic databases: PubMed, Embase, Cochrane Library, Google Scholar, Web of Science, Wanfang Data, and China National Knowledge Infrastructure (CNKI. Odds ratios (OR with 95% confidence interval (CI were used to evaluate the strength of the association between E-selectin gene polymorphisms and EH susceptibility. The pooled ORs were performed for dominant model, allelic model and recessive model. The publication bias was examined by Begg's funnel plots and Egger's test.A total of eleven studies met the inclusion criteria. All studies came from Asians. Ten studies (12 cohorts evaluated the A561C polymorphism and EH risk, including 2,813 cases and 2,817 controls. The pooled OR was 2.280 (95%CI: 1.893-2.748, P<0.001 in dominant model, 5.284 (95%CI: 2.679-10.420, P<0.001 in recessive model and 2.359 (95%CI: 1.981-2.808, P = 0.001 in allelic model. Four studies (six cohorts evaluated C1839T polymorphism and EH risk, including 1,700 cases and 1,681 controls. The pooled OR was 0.785 (95%CI: 0.627-0.983, P = 0.035 in dominant model, 1.250 (95%CI: 0.336-4.652, P = 0.739 in recessive model and 0.805 (95%CI: 0.649-0.999, P = 0.049 in allelic model.The current meta-analysis concludes that the C allele of E-selectin A561C gene polymorphism might increase the EH risk in Asian population, whereas the T allele of E-selectin C1839T gene polymorphism might decrease the EH risk.

Meta-STEPP: subpopulation treatment effect pattern plot for individual patient data meta-analysis.

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Wang, Xin Victoria; Cole, Bernard; Bonetti, Marco; Gelber, Richard D

2016-09-20

We have developed a method, called Meta-STEPP (subpopulation treatment effect pattern plot for meta-analysis), to explore treatment effect heterogeneity across covariate values in the meta-analysis setting for time-to-event data when the covariate of interest is continuous. Meta-STEPP forms overlapping subpopulations from individual patient data containing similar numbers of events with increasing covariate values, estimates subpopulation treatment effects using standard fixed-effects meta-analysis methodology, displays the estimated subpopulation treatment effect as a function of the covariate values, and provides a statistical test to detect possibly complex treatment-covariate interactions. Simulation studies show that this test has adequate type-I error rate recovery as well as power when reasonable window sizes are chosen. When applied to eight breast cancer trials, Meta-STEPP suggests that chemotherapy is less effective for tumors with high estrogen receptor expression compared with those with low expression. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Prognostic and predictive value of VHL gene alteration in renal cell carcinoma: a meta-analysis and review.

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Kim, Bum Jun; Kim, Jung Han; Kim, Hyeong Su; Zang, Dae Young

2017-02-21

The von Hippel-Lindau (VHL) gene is often inactivated in sporadic renal cell carcinoma (RCC) by mutation or promoter hypermethylation. The prognostic or predictive value of VHL gene alteration is not well established. We conducted this meta-analysis to evaluate the association between the VHL alteration and clinical outcomes in patients with RCC. We searched PUBMED, MEDLINE and EMBASE for articles including following terms in their titles, abstracts, or keywords: 'kidney or renal', 'carcinoma or cancer or neoplasm or malignancy', 'von Hippel-Lindau or VHL', 'alteration or mutation or methylation', and 'prognostic or predictive'. There were six studies fulfilling inclusion criteria and a total of 633 patients with clear cell RCC were included in the study: 244 patients who received anti-vascular endothelial growth factor (VEGF) therapy in the predictive value analysis and 419 in the prognostic value analysis. Out of 663 patients, 410 (61.8%) had VHL alteration. The meta-analysis showed no association between the VHL gene alteration and overall response rate (relative risk = 1.47 [95% CI, 0.81-2.67], P = 0.20) or progression free survival (hazard ratio = 1.02 [95% CI, 0.72-1.44], P = 0.91) in patients with RCC who received VEGF-targeted therapy. There was also no correlation between the VHL alteration and overall survival (HR = 0.80 [95% CI, 0.56-1.14], P = 0.21). In conclusion, this meta-analysis indicates that VHL gene alteration has no prognostic or predictive value in patients with clear cell RCC.

Capturing heterogeneity in gene expression studies by surrogate variable analysis.

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Jeffrey T Leek

2007-09-01

Full Text Available It has unambiguously been shown that genetic, environmental, demographic, and technical factors may have substantial effects on gene expression levels. In addition to the measured variable(s of interest, there will tend to be sources of signal due to factors that are unknown, unmeasured, or too complicated to capture through simple models. We show that failing to incorporate these sources of heterogeneity into an analysis can have widespread and detrimental effects on the study. Not only can this reduce power or induce unwanted dependence across genes, but it can also introduce sources of spurious signal to many genes. This phenomenon is true even for well-designed, randomized studies. We introduce "surrogate variable analysis" (SVA to overcome the problems caused by heterogeneity in expression studies. SVA can be applied in conjunction with standard analysis techniques to accurately capture the relationship between expression and any modeled variables of interest. We apply SVA to disease class, time course, and genetics of gene expression studies. We show that SVA increases the biological accuracy and reproducibility of analyses in genome-wide expression studies.

Characterization of the global profile of genes expressed in cervical epithelium by Serial Analysis of Gene Expression (SAGE

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Piña-Sanchez Patricia

2005-09-01

Full Text Available Abstract Background Serial Analysis of Gene Expression (SAGE is a new technique that allows a detailed and profound quantitative and qualitative knowledge of gene expression profile, without previous knowledge of sequence of analyzed genes. We carried out a modification of SAGE methodology (microSAGE, useful for the analysis of limited quantities of tissue samples, on normal human cervical tissue obtained from a donor without histopathological lesions. Cervical epithelium is constituted mainly by cervical keratinocytes which are the targets of human papilloma virus (HPV, where persistent HPV infection of cervical epithelium is associated with an increase risk for developing cervical carcinomas (CC. Results We report here a transcriptome analysis of cervical tissue by SAGE, derived from 30,418 sequenced tags that provide a wealth of information about the gene products involved in normal cervical epithelium physiology, as well as genes not previously found in uterine cervix tissue involved in the process of epidermal differentiation. Conclusion This first comprehensive and profound analysis of uterine cervix transcriptome, should be useful for the identification of genes involved in normal cervix uterine function, and candidate genes associated with cervical carcinoma.

Association between FOXO3A gene polymorphisms and human longevity: a meta-analysis

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Ji-Ming Bao

2014-06-01

Full Text Available Numerous studies have shown associations between the FOXO3A gene, encoding the forkhead box O3 transcription factor, and human or specifically male longevity. However, the associations of specific FOXO3A polymorphisms with longevity remain inconclusive. We performed a meta-analysis of existing studies to clarify these potential associations. A comprehensive search was conducted to identify studies of FOXO3A gene polymorphisms and longevity. Pooled odds ratios (ORs and 95% confidence intervals (CIs were calculated by comparing the minor and major alleles. A total of seven articles reporting associations of FOXO3A polymorphisms with longevity were identified and included in this meta-analysis. These comprised 11 independent studies with 5241 cases and 5724 controls from different ethnic groups. rs2802292, rs2764264, rs13217795, rs1935949 and rs2802288 polymorphisms were associated with human longevity (OR = 1.36, 95% CI = 1.10-1.69, P= 0.005; OR = 1.20, 95% CI = 1.04-1.37, P= 0.01; OR = 1.27, 95% CI = 1.10-1.46, P= 0.001; OR = 1.14, 95% CI = 1.01-1.27 and OR = 1.24, 95% CI = 1.07-1.43, P= 0.003, respectively. Analysis stratified by gender indicated significant associations between rs2802292, rs2764264 and rs13217795 and male longevity (OR = 1.54, 95% CI = 1.33-1.79, P < 0.001; OR = 1.38, 95% CI = 1.15-1.66, P= 0.001; and OR = 1.39, 95% CI = 1.15-1.67, P= 0.001, but rs2802292, rs2764264 and rs1935949 were not linked to female longevity. Moreover, our study showed no association between rs2153960, rs7762395 or rs13220810 polymorphisms and longevity. In conclusion, this meta-analysis indicates a significant association of five FOXO3A gene polymorphisms with longevity, with the effects of rs2802292 and rs2764264 being male-specific. Further investigations are required to confirm these findings.

Association between FOXO3A gene polymorphisms and human longevity: a meta-analysis.

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Bao, Ji-Ming; Song, Xian-Lu; Hong, Ying-Qia; Zhu, Hai-Li; Li, Cui; Zhang, Tao; Chen, Wei; Zhao, Shan-Chao; Chen, Qing

2014-01-01

Numerous studies have shown associations between the FOXO3A gene, encoding the forkhead box O3 transcription factor, and human or specifically male longevity. However, the associations of specific FOXO3A polymorphisms with longevity remain inconclusive. We performed a meta-analysis of existing studies to clarify these potential associations. A comprehensive search was conducted to identify studies of FOXO3A gene polymorphisms and longevity. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated by comparing the minor and major alleles. A total of seven articles reporting associations of FOXO3A polymorphisms with longevity were identified and included in this meta-analysis. These comprised 11 independent studies with 5241 cases and 5724 controls from different ethnic groups. rs2802292, rs2764264, rs13217795, rs1935949 and rs2802288 polymorphisms were associated with human longevity (OR = 1.36, 95% CI = 1.10-1.69, P= 0.005; OR = 1.20, 95% CI = 1.04-1.37, P= 0.01; OR = 1.27, 95% CI = 1.10-1.46, P= 0.001; OR = 1.14, 95% CI = 1.01-1.27 and OR = 1.24, 95% CI = 1.07-1.43, P= 0.003, respectively). Analysis stratified by gender indicated significant associations between rs2802292, rs2764264 and rs13217795 and male longevity (OR = 1.54, 95% CI = 1.33-1.79, P < 0.001; OR = 1.38, 95% CI = 1.15-1.66, P= 0.001; and OR = 1.39, 95% CI = 1.15-1.67, P= 0.001), but rs2802292, rs2764264 and rs1935949 were not linked to female longevity. Moreover, our study showed no association between rs2153960, rs7762395 or rs13220810 polymorphisms and longevity. In conclusion, this meta-analysis indicates a significant association of five FOXO3A gene polymorphisms with longevity, with the effects of rs2802292 and rs2764264 being male-specific. Further investigations are required to confirm these findings.

DAG expression: high-throughput gene expression analysis of real-time PCR data using standard curves for relative quantification.

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María Ballester

Full Text Available BACKGROUND: Real-time quantitative PCR (qPCR is still the gold-standard technique for gene-expression quantification. Recent technological advances of this method allow for the high-throughput gene-expression analysis, without the limitations of sample space and reagent used. However, non-commercial and user-friendly software for the management and analysis of these data is not available. RESULTS: The recently developed commercial microarrays allow for the drawing of standard curves of multiple assays using the same n-fold diluted samples. Data Analysis Gene (DAG Expression software has been developed to perform high-throughput gene-expression data analysis using standard curves for relative quantification and one or multiple reference genes for sample normalization. We discuss the application of DAG Expression in the analysis of data from an experiment performed with Fluidigm technology, in which 48 genes and 115 samples were measured. Furthermore, the quality of our analysis was tested and compared with other available methods. CONCLUSIONS: DAG Expression is a freely available software that permits the automated analysis and visualization of high-throughput qPCR. A detailed manual and a demo-experiment are provided within the DAG Expression software at http://www.dagexpression.com/dage.zip.

MetaSeq: privacy preserving meta-analysis of sequencing-based association studies.

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Singh, Angad Pal; Zafer, Samreen; Pe'er, Itsik

2013-01-01

Human genetics recently transitioned from GWAS to studies based on NGS data. For GWAS, small effects dictated large sample sizes, typically made possible through meta-analysis by exchanging summary statistics across consortia. NGS studies groupwise-test for association of multiple potentially-causal alleles along each gene. They are subject to similar power constraints and therefore likely to resort to meta-analysis as well. The problem arises when considering privacy of the genetic information during the data-exchange process. Many scoring schemes for NGS association rely on the frequency of each variant thus requiring the exchange of identity of the sequenced variant. As such variants are often rare, potentially revealing the identity of their carriers and jeopardizing privacy. We have thus developed MetaSeq, a protocol for meta-analysis of genome-wide sequencing data by multiple collaborating parties, scoring association for rare variants pooled per gene across all parties. We tackle the challenge of tallying frequency counts of rare, sequenced alleles, for metaanalysis of sequencing data without disclosing the allele identity and counts, thereby protecting sample identity. This apparent paradoxical exchange of information is achieved through cryptographic means. The key idea is that parties encrypt identity of genes and variants. When they transfer information about frequency counts in cases and controls, the exchanged data does not convey the identity of a mutation and therefore does not expose carrier identity. The exchange relies on a 3rd party, trusted to follow the protocol although not trusted to learn about the raw data. We show applicability of this method to publicly available exome-sequencing data from multiple studies, simulating phenotypic information for powerful meta-analysis. The MetaSeq software is publicly available as open source.

Xylella fastidiosa gene expression analysis by DNA microarrays

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Regiane F. Travensolo

2009-01-01

Full Text Available Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM2 and liquid BCYE. All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others. The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants.

Multivariate Methods for Meta-Analysis of Genetic Association Studies.

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Dimou, Niki L; Pantavou, Katerina G; Braliou, Georgia G; Bagos, Pantelis G

2018-01-01

Multivariate meta-analysis of genetic association studies and genome-wide association studies has received a remarkable attention as it improves the precision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in brief univariate methods for meta-analysis and we then scrutinize multivariate methodologies. Multivariate models of meta-analysis for a single gene-disease association studies, including models for haplotype association studies, multiple linked polymorphisms and multiple outcomes are discussed. The popular Mendelian randomization approach and special cases of meta-analysis addressing issues such as the assumption of the mode of inheritance, deviation from Hardy-Weinberg Equilibrium and gene-environment interactions are also presented. All available methods are enriched with practical applications and methodologies that could be developed in the future are discussed. Links for all available software implementing multivariate meta-analysis methods are also provided.

Life cycle analysis of kidney gene expression in male F344 rats.

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Joshua C Kwekel

Full Text Available Age is a predisposing condition for susceptibility to chronic kidney disease and progression as well as acute kidney injury that may arise due to the adverse effects of some drugs. Age-related differences in kidney biology, therefore, are a key concern in understanding drug safety and disease progression. We hypothesize that the underlying suite of genes expressed in the kidney at various life cycle stages will impact susceptibility to adverse drug reactions. Therefore, establishing changes in baseline expression data between these life stages is the first and necessary step in evaluating this hypothesis. Untreated male F344 rats were sacrificed at 2, 5, 6, 8, 15, 21, 78, and 104 weeks of age. Kidneys were collected for histology and gene expression analysis. Agilent whole-genome rat microarrays were used to query global expression profiles. An ANOVA (p1.5 in relative mRNA expression, was used to identify 3,724 unique differentially expressed genes (DEGs. Principal component analyses of these DEGs revealed three major divisions in life-cycle renal gene expression. K-means cluster analysis identified several groups of genes that shared age-specific patterns of expression. Pathway analysis of these gene groups revealed age-specific gene networks and functions related to renal function and aging, including extracellular matrix turnover, immune cell response, and renal tubular injury. Large age-related changes in expression were also demonstrated for the genes that code for qualified renal injury biomarkers KIM-1, Clu, and Tff3. These results suggest specific groups of genes that may underlie age-specific susceptibilities to adverse drug reactions and disease. This analysis of the basal gene expression patterns of renal genes throughout the life cycle of the rat will improve the use of current and future renal biomarkers and inform our assessments of kidney injury and disease.

Prioritizing genes associated with prostate cancer development

International Nuclear Information System (INIS)

Gorlov, Ivan P; Logothetis, Christopher J; Sircar, Kanishka; Zhao, Hongya; Maity, Sankar N; Navone, Nora M; Gorlova, Olga Y; Troncoso, Patricia; Pettaway, Curtis A; Byun, Jin Young

2010-01-01

The genetic control of prostate cancer development is poorly understood. Large numbers of gene-expression datasets on different aspects of prostate tumorigenesis are available. We used these data to identify and prioritize candidate genes associated with the development of prostate cancer and bone metastases. Our working hypothesis was that combining meta-analyses on different but overlapping steps of prostate tumorigenesis will improve identification of genes associated with prostate cancer development. A Z score-based meta-analysis of gene-expression data was used to identify candidate genes associated with prostate cancer development. To put together different datasets, we conducted a meta-analysis on 3 levels that follow the natural history of prostate cancer development. For experimental verification of candidates, we used in silico validation as well as in-house gene-expression data. Genes with experimental evidence of an association with prostate cancer development were overrepresented among our top candidates. The meta-analysis also identified a considerable number of novel candidate genes with no published evidence of a role in prostate cancer development. Functional annotation identified cytoskeleton, cell adhesion, extracellular matrix, and cell motility as the top functions associated with prostate cancer development. We identified 10 genes--CDC2, CCNA2, IGF1, EGR1, SRF, CTGF, CCL2, CAV1, SMAD4, and AURKA--that form hubs of the interaction network and therefore are likely to be primary drivers of prostate cancer development. By using this large 3-level meta-analysis of the gene-expression data to identify candidate genes associated with prostate cancer development, we have generated a list of candidate genes that may be a useful resource for researchers studying the molecular mechanisms underlying prostate cancer development

Association between MASP-2 gene polymorphism and risk of infection diseases: A meta-analysis.

Science.gov (United States)

Fu, Jie; Wang, Jingqiu; Luo, Yanping; Zhang, Lifeng; Zhang, Yuan; Dong, Xinfang; Yu, Hongjuan; Cao, Mingqiang; Ma, Xingming

2016-11-01

The role of MASP-2 is vital in the process of complement activation by the lectin pathway. It is generally considered that the functional activation of MASP-2 contribute to the infection disease development process. To analyze the association between MASP-2 functional gene (rs72550870) polymorphism and the infection disease risk by a meta-analysis. Relevant case-control studies were identified by searching Cochrane Library, PubMed, Emabase, DOAJ, CAB Abstracts, CSA, CINAHL, EBSCO, Scopus, Global Health, Index Copernicus, CA, China National Knowledge Infrastructure (CNKI) databases up to 10th January 2016. The data were extracted and the methodological quality of studies were evaluated. The STATA 12.0 software was used to perform statistical analysis. 9 studies were included. There was no significant association between masp-2 gene (p.D120G, rs72550870) polymorphism and the risk of infection disease under the allele model (G vs. A: OR = 0.89, 95%CI = 0.66-1.21)(P = 0.445>0.05) and the recessive model (AG + GG vs.AA: OR = 0.88, 95%CI = 0.65-1.20) (P = 0.428>0.05). This is the first comprehensive meta-analysis indicates that the MASP-2 functional gene (rs72550870) polymorphism is not associated with the infection diseases, and the key functional gene polymorphism of rs72550870 did not increase susceptibility to the infection diseases. Similarly, there were no obvious difference in subgroup analysis based on geographical areas and pathogenic microorganisms. Copyright © 2016 Elsevier Ltd. All rights reserved.

A whole-blood transcriptome meta-analysis identifies gene expression signatures of cigarette smoking

NARCIS (Netherlands)

Huan, T. (Tianxiao); R. Joehanes (Roby); C. Schurmann (Claudia); K. Schramm (Katharina); L.C. Pilling (Luke); M.J. Peters (Marjolein); R. Mägi (Reedik); D.L. Demeo (Dawn L.); G.T. O'Connor (George); L. Ferrucci (Luigi); A. Teumer (Alexander); G. Homuth (Georg); R. Biffar (Reiner); U. Völker (Uwe); C. Herder (Christian); M. Waldenberger (Melanie); A. Peters (Annette); S. Zeilinger (Sonja); A. Metspalu (Andres); A. Hofman (Albert); A.G. Uitterlinden (André); D.G. Hernandez (Dena); A. Singleton (Andrew); S. Bandinelli (Stefania); P.J. Munson (Peter); H. Lin (Honghuang); E.J. Benjamin (Emelia); T. Esko (Tõnu); H.J. Grabe (Hans Jörgen); H. Prokisch (Holger); J.B.J. van Meurs (Joyce); D. Melzer (David); D. Levy (Daniel)

2016-01-01

textabstractCigarette smoking is a leading modifiable cause of death worldwide. We hypothesized that cigarette smoking induces extensive transcriptomic changes that lead to target-organ damage and smoking-related diseases. We performed a metaanalysis of transcriptome-wide gene expression using whole

Associations between interleukin-1 gene polymorphisms and coronary heart disease risk: a meta-analysis.

Directory of Open Access Journals (Sweden)

Liang Zhou

Full Text Available OBJECTIVE: A great number of studies regarding the associations between IL-1B-511, IL-1B+3954 and IL-1RN VNTR polymorphisms within the IL-1gene cluster and coronary heart disease (CHD have been published. However, results have been inconsistent. In this study, a meta-analysis was performed to investigate the associations. METHODS: Published literature from PubMed and Embase databases were searched for eligible publications. Pooled odds ratios (ORs with 95% confidence intervals (CIs were calculated using random- or fixed- effect model. RESULTS: Thirteen studies (3,219 cases/2,445 controls for IL-1B-511 polymorphism, nine studies (1,828 cases/1,818 controls for IL-1B+3954 polymorphism and twelve studies (2,987 cases/ 2,208 controls for IL-1RN VNTR polymorphism were included in this meta analysis. The results indicated that both IL-1B-511 and IL-1B+3954 polymorphisms were not associated with CHD risk (IL-1B-511 T vs. C: OR = 0.98, 95%CI 0.87-1.09; IL-1B+3954 T vs. C: OR = 1.06, 95%CI 0.95-1.19. Similarly, there was no association between IL-1RN VNTR polymorphism and CHD risk (*2 vs. L: OR = 1.00, 95%CI 0.85-1.17. CONCLUSIONS: This meta-analysis suggested that there were no associations between IL-1 gene cluster polymorphisms and CHD.

Global gene expression analysis for evaluation and design of biomaterials

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Nobutaka Hanagata, Taro Takemura and Takashi Minowa

2010-01-01

Full Text Available Comprehensive gene expression analysis using DNA microarrays has become a widespread technique in molecular biological research. In the biomaterials field, it is used to evaluate the biocompatibility or cellular toxicity of metals, polymers and ceramics. Studies in this field have extracted differentially expressed genes in the context of differences in cellular responses among multiple materials. Based on these genes, the effects of materials on cells at the molecular level have been examined. Expression data ranging from several to tens of thousands of genes can be obtained from DNA microarrays. For this reason, several tens or hundreds of differentially expressed genes are often present in different materials. In this review, we outline the principles of DNA microarrays, and provide an introduction to methods of extracting information which is useful for evaluating and designing biomaterials from comprehensive gene expression data.

Global gene expression analysis for evaluation and design of biomaterials

International Nuclear Information System (INIS)

Hanagata, Nobutaka; Takemura, Taro; Minowa, Takashi

2010-01-01

Comprehensive gene expression analysis using DNA microarrays has become a widespread technique in molecular biological research. In the biomaterials field, it is used to evaluate the biocompatibility or cellular toxicity of metals, polymers and ceramics. Studies in this field have extracted differentially expressed genes in the context of differences in cellular responses among multiple materials. Based on these genes, the effects of materials on cells at the molecular level have been examined. Expression data ranging from several to tens of thousands of genes can be obtained from DNA microarrays. For this reason, several tens or hundreds of differentially expressed genes are often present in different materials. In this review, we outline the principles of DNA microarrays, and provide an introduction to methods of extracting information which is useful for evaluating and designing biomaterials from comprehensive gene expression data. (topical review)

Functional annotation of rheumatoid arthritis and osteoarthritis associated genes by integrative genome-wide gene expression profiling analysis.

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Zhan-Chun Li

Full Text Available BACKGROUND: Rheumatoid arthritis (RA and osteoarthritis (OA are two major types of joint diseases that share multiple common symptoms. However, their pathological mechanism remains largely unknown. The aim of our study is to identify RA and OA related-genes and gain an insight into the underlying genetic basis of these diseases. METHODS: We collected 11 whole genome-wide expression profiling datasets from RA and OA cohorts and performed a meta-analysis to comprehensively investigate their expression signatures. This method can avoid some pitfalls of single dataset analyses. RESULTS AND CONCLUSION: We found that several biological pathways (i.e., the immunity, inflammation and apoptosis related pathways are commonly involved in the development of both RA and OA. Whereas several other pathways (i.e., vasopressin-related pathway, regulation of autophagy, endocytosis, calcium transport and endoplasmic reticulum stress related pathways present significant difference between RA and OA. This study provides novel insights into the molecular mechanisms underlying this disease, thereby aiding the diagnosis and treatment of the disease.

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

DEFF Research Database (Denmark)

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

2006-01-01

be examined using the novel clique finder tool to determine the sets of genes most likely to be regulated in a similar manner. In combination, these tools offer three levels of analysis: creation of correlation lists of co-expressed genes, refinement of these lists using two-dimensional scatter plots......We present a new WWW-based tool for plant gene analysis, the Arabidopsis Co-Expression Tool (act) , based on a large Arabidopsis thaliana microarray data set obtained from the Nottingham Arabidopsis Stock Centre. The co-expression analysis tool allows users to identify genes whose expression...

MicroRNA meta-signature of oral cancer: evidence from a meta-analysis.

Science.gov (United States)

Zeljic, Katarina; Jovanovic, Ivan; Jovanovic, Jasmina; Magic, Zvonko; Stankovic, Aleksandra; Supic, Gordana

2018-03-01

It was the aim of the study to identify commonly deregulated miRNAs in oral cancer patients by performing a meta-analysis of previously published miRNA expression profiles in cancer and matched normal non-cancerous tissue in such patients. Meta-analysis included seven independent studies analyzed by a vote-counting method followed by bioinformatic enrichment analysis. Amongst seven independent studies included in the meta-analysis, 20 miRNAs were found to be deregulated in oral cancer when compared with non-cancerous tissue. Eleven miRNAs were consistently up-regulated in three or more studies (miR-21-5p, miR-31-5p, miR-135b-5p, miR-31-3p, miR-93-5p, miR-34b-5p, miR-424-5p, miR-18a-5p, miR-455-3p, miR-450a-5p, miR-21-3p), and nine were down-regulated (miR-139-5p, miR-30a-3p, miR-376c-3p, miR-885-5p, miR-375, miR-486-5p, miR-411-5p, miR-133a-3p, miR-30a-5p). The meta-signature of identified miRNAs was functionally characterized by KEGG enrichment analysis. Twenty-four KEGG pathways were significantly enriched, and TGF-beta signaling was the most enriched signaling pathway. The highest number of meta-signature miRNAs was involved in the sphingolipid signaling pathway. Natural killer cell-mediated cytotoxicity was the pathway with most genes regulated by identified miRNAs. The rest of the enriched pathways in our miRNA list describe different malignancies and signaling. The identified miRNA meta-signature might be considered as a potential battery of biomarkers when distinguishing oral cancer tissue from normal, non-cancerous tissue. Further mechanistic studies are warranted in order to confirm and fully elucidate the role of deregulated miRNAs in oral cancer.

GECKO: a complete large-scale gene expression analysis platform

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Heuer Michael

2004-12-01

Full Text Available Abstract Background Gecko (Gene Expression: Computation and Knowledge Organization is a complete, high-capacity centralized gene expression analysis system, developed in response to the needs of a distributed user community. Results Based on a client-server architecture, with a centralized repository of typically many tens of thousands of Affymetrix scans, Gecko includes automatic processing pipelines for uploading data from remote sites, a data base, a computational engine implementing ~ 50 different analysis tools, and a client application. Among available analysis tools are clustering methods, principal component analysis, supervised classification including feature selection and cross-validation, multi-factorial ANOVA, statistical contrast calculations, and various post-processing tools for extracting data at given error rates or significance levels. On account of its open architecture, Gecko also allows for the integration of new algorithms. The Gecko framework is very general: non-Affymetrix and non-gene expression data can be analyzed as well. A unique feature of the Gecko architecture is the concept of the Analysis Tree (actually, a directed acyclic graph, in which all successive results in ongoing analyses are saved. This approach has proven invaluable in allowing a large (~ 100 users and distributed community to share results, and to repeatedly return over a span of years to older and potentially very complex analyses of gene expression data. Conclusions The Gecko system is being made publicly available as free software http://sourceforge.net/projects/geckoe. In totality or in parts, the Gecko framework should prove useful to users and system developers with a broad range of analysis needs.

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

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

2017-11-13

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

Digital Gene Expression Profiling Analysis of Aged Mice under Moxibustion Treatment

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Nan Liu

2018-01-01

Full Text Available Aging is closely connected with death, progressive physiological decline, and increased risk of diseases, such as cancer, arteriosclerosis, heart disease, hypertension, and neurodegenerative diseases. It is reported that moxibustion can treat more than 300 kinds of diseases including aging related problems and can improve immune function and physiological functions. The digital gene expression profiling of aged mice with or without moxibustion treatment was investigated and the mechanisms of moxibustion in aged mice were speculated by gene ontology and pathway analysis in the study. Almost 145 million raw reads were obtained by digital gene expression analysis and about 140 million (96.55% were clean reads. Five differentially expressed genes with an adjusted P value 1 were identified between the control and moxibustion groups. They were Gm6563, Gm8116, Rps26-ps1, Nat8f4, and Igkv3-12. Gene ontology analysis was carried out by the GOseq R package and functional annotations of the differentially expressed genes related to translation, mRNA export from nucleus, mRNA transport, nuclear body, acetyltransferase activity, and so on. Kyoto Encyclopedia of Genes and Genomes database was used for pathway analysis and ribosome was the most significantly enriched pathway term.

Transcriptome analysis reveals key differentially expressed genes involved in wheat grain development

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Yonglong Yu

2016-04-01

Full Text Available Wheat seed development is an important physiological process of seed maturation and directly affects wheat yield and quality. In this study, we performed dynamic transcriptome microarray analysis of an elite Chinese bread wheat cultivar (Jimai 20 during grain development using the GeneChip Wheat Genome Array. Grain morphology and scanning electron microscope observations showed that the period of 11–15 days post-anthesis (DPA was a key stage for the synthesis and accumulation of seed starch. Genome-wide transcriptional profiling and significance analysis of microarrays revealed that the period from 11 to 15 DPA was more important than the 15–20 DPA stage for the synthesis and accumulation of nutritive reserves. Series test of cluster analysis of differential genes revealed five statistically significant gene expression profiles. Gene ontology annotation and enrichment analysis gave further information about differentially expressed genes, and MapMan analysis revealed expression changes within functional groups during seed development. Metabolic pathway network analysis showed that major and minor metabolic pathways regulate one another to ensure regular seed development and nutritive reserve accumulation. We performed gene co-expression network analysis to identify genes that play vital roles in seed development and identified several key genes involved in important metabolic pathways. The transcriptional expression of eight key genes involved in starch and protein synthesis and stress defense was further validated by qRT-PCR. Our results provide new insight into the molecular mechanisms of wheat seed development and the determinants of yield and quality.

The role of CD147 expression in prostate cancer: a systematic review and meta-analysis.

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Ye, Yun; Li, Su-Liang; Wang, Yao; Yao, Yang; Wang, Juan; Ma, Yue-Yun; Hao, Xiao-Ke

2016-01-01

There are a number of studies which show that expression of CD147 is increased significantly in prostate cancer (PCa). However, conflicting conclusions have also been reported by other researchers lately. In order to arrive at a clear conclusion, a meta-analysis of eligible studies was conducted. We searched PubMed, MEDLINE, Cochrane Library, and the China National Knowledge Infrastructure databases to identify all the published case-control studies on the relationship between the expression of CD147 and PCa until February 2016. In the end, a total of 930 patients in eight studies were included in the meta-analysis. CD147 expression in the PCa patients increased significantly (odds ratio [OR], 4.65; 95% confidence interval [CI], 3.52-6.14; Z=10.79; PCD147 was associated with PCa among the Asian population (OR, 21.01; 95% CI, 12.88-34.28; Z=12.19; PCD147 was related to PCa, significant heterogeneity was not found between Asian studies, and the result became more significant. The positive expression of CD147 was significantly related to the clinicopathological characteristics of PCa. This suggests that CD147 plays an essential role in poor prognosis and recurrence prediction.

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.

Meta-analysis of breast cancer microarray studies in conjunction with conserved cis-elements suggest patterns for coordinate regulation

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Lundberg Cathryn

2008-01-01

Full Text Available Abstract Background Gene expression measurements from breast cancer (BrCa tumors are established clinical predictive tools to identify tumor subtypes, identify patients showing poor/good prognosis, and identify patients likely to have disease recurrence. However, diverse breast cancer datasets in conjunction with diagnostic clinical arrays show little overlap in the sets of genes identified. One approach to identify a set of consistently dysregulated candidate genes in these tumors is to employ meta-analysis of multiple independent microarray datasets. This allows one to compare expression data from a diverse collection of breast tumor array datasets generated on either cDNA or oligonucleotide arrays. Results We gathered expression data from 9 published microarray studies examining estrogen receptor positive (ER+ and estrogen receptor negative (ER- BrCa tumor cases from the Oncomine database. We performed a meta-analysis and identified genes that were universally up or down regulated with respect to ER+ versus ER- tumor status. We surveyed both the proximal promoter and 3' untranslated regions (3'UTR of our top-ranking genes in each expression group to test whether common sequence elements may contribute to the observed expression patterns. Utilizing a combination of known transcription factor binding sites (TFBS, evolutionarily conserved mammalian promoter and 3'UTR motifs, and microRNA (miRNA seed sequences, we identified numerous motifs that were disproportionately represented between the two gene classes suggesting a common regulatory network for the observed gene expression patterns. Conclusion Some of the genes we identified distinguish key transcripts previously seen in array studies, while others are newly defined. Many of the genes identified as overexpressed in ER- tumors were previously identified as expression markers for neoplastic transformation in multiple human cancers. Moreover, our motif analysis identified a collection of

Meta-Analysis of Transcriptome Data Related to Hippocampus Biopsies and iPSC-Derived Neuronal Cells from Alzheimer's Disease Patients Reveals an Association with FOXA1 and FOXA2 Gene Regulatory Networks.

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Wruck, Wasco; Schröter, Friederike; Adjaye, James

2016-01-01

Although the incidence of Alzheimer's disease (AD) is continuously increasing in the aging population worldwide, effective therapies are not available. The interplay between causative genetic and environmental factors is partially understood. Meta-analyses have been performed on aspects such as polymorphisms, cytokines, and cognitive training. Here, we propose a meta-analysis approach based on hierarchical clustering analysis of a reliable training set of hippocampus biopsies, which is condensed to a gene expression signature. This gene expression signature was applied to various test sets of brain biopsies and iPSC-derived neuronal cell models to demonstrate its ability to distinguish AD samples from control. Thus, our identified AD-gene signature may form the basis for determination of biomarkers that are urgently needed to overcome current diagnostic shortfalls. Intriguingly, the well-described AD-related genes APP and APOE are not within the signature because their gene expression profiles show a lower correlation to the disease phenotype than genes from the signature. This is in line with the differing characteristics of the disease as early-/late-onset or with/without genetic predisposition. To investigate the gene signature's systemic role(s), signaling pathways, gene ontologies, and transcription factors were analyzed which revealed over-representation of response to stress, regulation of cellular metabolic processes, and reactive oxygen species. Additionally, our results clearly point to an important role of FOXA1 and FOXA2 gene regulatory networks in the etiology of AD. This finding is in corroboration with the recently reported major role of the dopaminergic system in the development of AD and its regulation by FOXA1 and FOXA2.

AB126. Association between FOX03A gene polymorphisms and human longevity: a meta-analysis

OpenAIRE

Zhao, Shanchao; Bao, Jiming; Song, Xianlu

2016-01-01

Objective Numerous studies have shown associations between the FOX03A gene, encoding the forkhead box 03 transcription factor, and human or specifically male longevity. However, the associations of specific FOX03A polymorphisms with longevity remain inconclusive. We performed a meta-analysis of existing studies to clarify these potential associations. Methods A comprehensive search was conducted to identify studies of FOX03A gene polymorphisms and longevity. Pooled odds ratios (ORs) and 95% c...

Association between polymorphism in STAT4 gene and risk of rheumatoid arthritis: a meta-analysis.

Science.gov (United States)

Tong, Guanghui; Zhang, Xiaochen; Tong, Weiwei; Liu, Yong

2013-05-01

Rheumatoid arthritis (RA) is a common chronic inflammatory autoimmune disease, affecting 1% of the population worldwide. Single nucleotide polymorphisms (SNPs) of signal transducer and activator of transcription 4 (STAT4) gene are suspected to have some relationship with the risk of RA. This meta-analysis aimed to evaluate the relationship between the polymorphism rs7574865 in STAT4 gene with RA and also examine whether the associations that have been reported in these studies differ between ethnic groups. We retrieved the relevant articles from PubMed, EMBASE and the China National Knowledge Infrastructure (CNKI) databases. The odds ratios (ORs) and their 95% confidence intervals (95% CIs) associated with the minor T allele of STAT4 rs7574865 SNP were extracted from the published studies and included in the analysis. Meta-analyses were performed on the total data set and separately for the major ethnic groups and RF and anti-CCP status. All analyses were performed using the Stata software. Twenty-three articles were included in the present analysis. Meta-analysis showed an association between the STAT4 polymorphism and RA in all subjects (OR=1.299, 95%CI=1.230-1.371, Prs7574865 T allele was significantly associated with RA in both Caucasians and Asians, in both positive and negative RF patients versus controls, also significantly in the presence of anti-CCP, both positive and negative. As for genotypes of rs7574865 polymorphism, all the results were significant, no matter in total subjects or stratified analyses by ethnic groups or by RF and anti-CCP status. Genetic polymorphism rs7574865 in STAT4 gene might be associated with RA susceptibility in total subjects, major ethnic groups and different status of anti-CCP or RF. Copyright © 2012 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

Association between CD14 gene polymorphisms and cancer risk: a meta-analysis.

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Jun Wang

Full Text Available BACKGROUND: Two polymorphisms, -260C/T and -651C/T, in the CD14 gene have been implicated in susceptibility to cancer. However, the results remain inconclusive. This meta-analysis aimed to investigate the association between the two polymorphisms and risk of cancer. METHODS: All eligible case-control studies published up to March 2014 were identified by searching PubMed, Web of Science, CNKI and WanFang database. Pooled odds ratio (OR with 95% confidence interval (CI were used to access the strength of this association in fixed- or random-effects model. RESULTS: 17 case-control studies from fourteen articles were included. Of those, there were 17 studies (4198 cases and 4194 controls for -260C/T polymorphism and three studies (832 cases and 1190 controls for -651C/T polymorphism. Overall, no significant associations between the two polymorphisms of CD14 gene and cancer risk were found. When stratified by ethnicity, cancer type and source of control, similar results were observed among them. In addition, in further subgroups analysis by Helicobacter pylori (H. pylori infection status and tumor location in gastric cancer subgroup, we found that the CD14 -260C/T polymorphism may increase the risk of gastric cancer in H. pylori-infected individuals. CONCLUSIONS: This meta-analysis suggests that the CD14 -260C/T polymorphism may increase the risk of gastric cancer in H. pylori-infected individuals. However, large and well-designed studies are warranted to validate our findings.

Reference genes for gene expression analysis by real-time reverse transcription polymerase chain reaction of renal cell carcinoma.

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Bjerregaard, Henriette; Pedersen, Shona; Kristensen, Søren Risom; Marcussen, Niels

2011-12-01

Differentiation between malignant renal cell carcinoma and benign oncocytoma is of great importance to choose the optimal treatment. Accurate preoperative diagnosis of renal tumor is therefore crucial; however, existing imaging techniques and histologic examinations are incapable of providing an optimal differentiation profile. Analysis of gene expression of molecular markers is a new possibility but relies on appropriate standardization to compare different samples. The aim of this study was to identify stably expressed reference genes suitable for the normalization of results extracted from gene expression analysis of renal tumors. Expression levels of 8 potential reference genes (ATP5J, HMBS, HPRT1, PPIA, TBP, 18S, GAPDH, and POLR2A) were examined by real-time reverse transcription polymerase chain reaction in tumor and normal tissue from removed kidneys from 13 patients with renal cell carcinoma and 5 patients with oncocytoma. The expression levels of genes were compared by gene stability value M, average gene stability M, pairwise variation V, and coefficient of variation CV. More candidates were not suitable for the purpose, but a combination of HMBS, PPIA, ATP5J, and TBP was found to be the best combination with an average gene stability value M of 0.9 and a CV of 0.4 in the 18 tumors and normal tissues. A combination of 4 genes, HMBS, PPIA, ATP5J, and TBP, is a possible reference in renal tumor gene expression analysis by reverse transcription polymerase chain reaction. A combination of four genes, HMBS, PPIA, ATP5J and TBP, being stably expressed in tissues from RCC is possible reference genes for gene expression analysis.

ADAGE signature analysis: differential expression analysis with data-defined gene sets.

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Tan, Jie; Huyck, Matthew; Hu, Dongbo; Zelaya, René A; Hogan, Deborah A; Greene, Casey S

2017-11-22

Gene set enrichment analysis and overrepresentation analyses are commonly used methods to determine the biological processes affected by a differential expression experiment. This approach requires biologically relevant gene sets, which are currently curated manually, limiting their availability and accuracy in many organisms without extensively curated resources. New feature learning approaches can now be paired with existing data collections to directly extract functional gene sets from big data. Here we introduce a method to identify perturbed processes. In contrast with methods that use curated gene sets, this approach uses signatures extracted from public expression data. We first extract expression signatures from public data using ADAGE, a neural network-based feature extraction approach. We next identify signatures that are differentially active under a given treatment. Our results demonstrate that these signatures represent biological processes that are perturbed by the experiment. Because these signatures are directly learned from data without supervision, they can identify uncurated or novel biological processes. We implemented ADAGE signature analysis for the bacterial pathogen Pseudomonas aeruginosa. For the convenience of different user groups, we implemented both an R package (ADAGEpath) and a web server ( http://adage.greenelab.com ) to run these analyses. Both are open-source to allow easy expansion to other organisms or signature generation methods. We applied ADAGE signature analysis to an example dataset in which wild-type and ∆anr mutant cells were grown as biofilms on the Cystic Fibrosis genotype bronchial epithelial cells. We mapped active signatures in the dataset to KEGG pathways and compared with pathways identified using GSEA. The two approaches generally return consistent results; however, ADAGE signature analysis also identified a signature that revealed the molecularly supported link between the MexT regulon and Anr. We designed

Stochastic biological response to radiation. Comprehensive analysis of gene expression

International Nuclear Information System (INIS)

Inoue, Tohru; Hirabayashi, Yoko

2012-01-01

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

MUC2 Expression Is Correlated with Tumor Differentiation and Inhibits Tumor Invasion in Gastric Carcinomas: A Systematic Review and Meta-analysis

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Jung-Soo Pyo

2015-05-01

Full Text Available Background: While MUC2 is expressed in intestinal metaplasia and malignant lesions, the clinicopathological significance of MUC2 expression is not fully elucidated in gastric carcinoma (GC. Methods: The present study investigated the correlation between MUC2 expression and clinicopathological parameters in 167 human GCs. In addition, to confirm the clinicopathological significance of MUC2 expression, we performed a systematic review and meta-analysis in 1,832 GCs. Results: MUC2 expression was found in 58 of 167 GCs (34.7%. MUC2-expressing GC showed lower primary tumor (T, regional lymph node (N, and tumor node metastasis (TNM stages compared with GCs without MUC2 expression (p=.001, p=.001, and p=.011, respectively. However, MUC2 expression was not correlated with Lauren’s classification and tumor differentiation. In meta-analysis, MUC2 expression was significantly correlated with differentiation and lower tumor stage (odds ratio [OR], 1.303; 95% confidence interval [CI], 1.020 to 1.664; p = .034 and OR, 1.352; 95% CI, 1.055 to 1.734; p = .017, respectively but not with Lauren’s classification, pN stage, or pTNM stage. Conclusions: MUC2 expression was correlated with a lower tumor depth and lower lymph node metastasis in our study; the meta-analysis showed a correlation of MUC2 expression with tumor differentiation and lower tumor depth.

Integration of machine learning and meta-analysis identifies the transcriptomic bio-signature of mastitis disease in cattle.

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Sharifi, Somayeh; Pakdel, Abbas; Ebrahimi, Mansour; Reecy, James M; Fazeli Farsani, Samaneh; Ebrahimie, Esmaeil

2018-01-01

Gram-negative bacteria such as Escherichia coli (E. coli) are assumed to be among the main agents that cause severe mastitis disease with clinical signs in dairy cattle. Rapid detection of this disease is so important in order to prevent transmission to other cows and helps to reduce inappropriate use of antibiotics. With the rapid progress in high-throughput technologies, and accumulation of various kinds of '-omics' data in public repositories, there is an opportunity to retrieve, integrate, and reanalyze these resources to improve the diagnosis and treatment of different diseases and to provide mechanistic insights into host resistance in an efficient way. Meta-analysis is a relatively inexpensive option with good potential to increase the statistical power and generalizability of single-study analysis. In the current meta-analysis research, six microarray-based studies that investigate the transcriptome profile of mammary gland tissue after induced mastitis by E. coli infection were used. This meta-analysis not only reinforced the findings in individual studies, but also several novel terms including responses to hypoxia, response to drug, anti-apoptosis and positive regulation of transcription from RNA polymerase II promoter enriched by up-regulated genes. Finally, in order to identify the small sets of genes that are sufficiently informative in E. coli mastitis, the differentially expressed gene introduced by meta-analysis were prioritized by using ten different attribute weighting algorithms. Twelve meta-genes were detected by the majority of attribute weighting algorithms (with weight above 0.7) as most informative genes including CXCL8 (IL8), NFKBIZ, HP, ZC3H12A, PDE4B, CASP4, CXCL2, CCL20, GRO1(CXCL1), CFB, S100A9, and S100A8. Interestingly, the results have been demonstrated that all of these genes are the key genes in the immune response, inflammation or mastitis. The Decision tree models efficiently discovered the best combination of the meta-genes as

Disease gene characterization through large-scale co-expression analysis.

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Allen Day

2009-12-01

Full Text Available In the post genome era, a major goal of biology is the identification of specific roles for individual genes. We report a new genomic tool for gene characterization, the UCLA Gene Expression Tool (UGET.Celsius, the largest co-normalized microarray dataset of Affymetrix based gene expression, was used to calculate the correlation between all possible gene pairs on all platforms, and generate stored indexes in a web searchable format. The size of Celsius makes UGET a powerful gene characterization tool. Using a small seed list of known cartilage-selective genes, UGET extended the list of known genes by identifying 32 new highly cartilage-selective genes. Of these, 7 of 10 tested were validated by qPCR including the novel cartilage-specific genes SDK2 and FLJ41170. In addition, we retrospectively tested UGET and other gene expression based prioritization tools to identify disease-causing genes within known linkage intervals. We first demonstrated this utility with UGET using genetically heterogeneous disorders such as Joubert syndrome, microcephaly, neuropsychiatric disorders and type 2 limb girdle muscular dystrophy (LGMD2 and then compared UGET to other gene expression based prioritization programs which use small but discrete and well annotated datasets. Finally, we observed a significantly higher gene correlation shared between genes in disease networks associated with similar complex or Mendelian disorders.UGET is an invaluable resource for a geneticist that permits the rapid inclusion of expression criteria from one to hundreds of genes in genomic intervals linked to disease. By using thousands of arrays UGET annotates and prioritizes genes better than other tools especially with rare tissue disorders or complex multi-tissue biological processes. This information can be critical in prioritization of candidate genes for sequence analysis.

Meta-Analysis of Microarray Data of Rainbow Trout Fry Gonad Differentiation Modulated by Ethynylestradiol.

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Sophie Depiereux

Full Text Available Sex differentiation in fish is a highly labile process easily reversed by the use of exogenous hormonal treatment and has led to environmental concerns since low doses of estrogenic molecules can adversely impact fish reproduction. The goal of this study was to identify pathways altered by treatment with ethynylestradiol (EE2 in developing fish and to find new target genes to be tested further for their possible role in male-to-female sex transdifferentiation. To this end, we have successfully adapted a previously developed bioinformatics workflow to a meta-analysis of two datasets studying sex reversal following exposure to EE2 in juvenile rainbow trout. The meta-analysis consisted of retrieving the intersection of the top gene lists generated for both datasets, performed at different levels of stringency. The intersecting gene lists, enriched in true positive differentially expressed genes (DEGs, were subjected to over-representation analysis (ORA which allowed identifying several statistically significant enriched pathways altered by EE2 treatment and several new candidate pathways, such as progesterone-mediated oocyte maturation and PPAR signalling. Moreover, several relevant key genes potentially implicated in the early transdifferentiation process were selected. Altogether, the results show that EE2 has a great effect on gene expression in juvenile rainbow trout. The feminization process seems to result from the altered transcription of genes implicated in normal female gonad differentiation, resulting in expression similar to that observed in normal females (i.e. the repression of key testicular markers cyp17a1, cyp11b, tbx1, as well as from other genes (including transcription factors that respond specifically to the EE2 treatment. The results also showed that the bioinformatics workflow can be applied to different types of microarray platforms and could be generalized to (ecotoxicogenomics studies for environmental risk assessment

Spectral map-analysis: a method to analyze gene expression data

OpenAIRE

Bijnens, Luc J.M.; Lewi, Paul J.; Göhlmann, Hinrich W.; Molenberghs, Geert; Wouters, Luc

2004-01-01

bioinformatics; biplot; correspondence factor analysis; data mining; data visualization; gene expression data; microarray data; multivariate exploratory data analysis; principal component analysis; Spectral map analysis

Effects of in ovo electroporation on endogenous gene expression: genome-wide analysis

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Chambers David

2011-04-01

Full Text Available Abstract Background In ovo electroporation is a widely used technique to study gene function in developmental biology. Despite the widespread acceptance of this technique, no genome-wide analysis of the effects of in ovo electroporation, principally the current applied across the tissue and exogenous vector DNA introduced, on endogenous gene expression has been undertaken. Here, the effects of electric current and expression of a GFP-containing construct, via electroporation into the midbrain of Hamburger-Hamilton stage 10 chicken embryos, are analysed by microarray. Results Both current alone and in combination with exogenous DNA expression have a small but reproducible effect on endogenous gene expression, changing the expression of the genes represented on the array by less than 0.1% (current and less than 0.5% (current + DNA, respectively. The subset of genes regulated by electric current and exogenous DNA span a disparate set of cellular functions. However, no genes involved in the regional identity were affected. In sharp contrast to this, electroporation of a known transcription factor, Dmrt5, caused a much greater change in gene expression. Conclusions These findings represent the first systematic genome-wide analysis of the effects of in ovo electroporation on gene expression during embryonic development. The analysis reveals that this process has minimal impact on the genetic basis of cell fate specification. Thus, the study demonstrates the validity of the in ovo electroporation technique to study gene function and expression during development. Furthermore, the data presented here can be used as a resource to refine the set of transcriptional responders in future in ovo electroporation studies of specific gene function.

Genetic variation of clock genes and cancer risk: a field synopsis and meta-analysis.

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Benna, Clara; Helfrich-Förster, Charlotte; Rajendran, Senthilkumar; Monticelli, Halenya; Pilati, Pierluigi; Nitti, Donato; Mocellin, Simone

2017-04-04

The number of studies on the association between clock genes' polymorphisms and cancer susceptibility has increased over the last years but the results are often conflicting and no comprehensive overview and quantitative summary of the evidence in this field is available. Literature search identified 27 eligible studies comprising 96756 subjects (cases: 38231) and investigating 687 polymorphisms involving 14 clock genes. Overall, 1025 primary and subgroup meta-analyses on 366 gene variants were performed. Study distribution by tumor was as follows: breast cancer (n=15), prostate cancer (n=3), pancreatic cancer (n=2), non-Hodgkin's lymphoma (n=2), glioma (n=1), chronic lymphocytic leukemia (n=1), colorectal cancer (n=1), non-small cell lung cancer (n=1) and ovarian cancer (n=1).We identified 10 single nucleotide polymorphisms (SNPs) significantly associated with cancer risk: NPAS2 rs10165970 (mixed and breast cancer shiftworkers), rs895520 (mixed), rs17024869 (breast) and rs7581886 (breast); CLOCK rs3749474 (breast) and rs11943456 (breast); RORA rs7164773 (breast and breast cancer postmenopausal), rs10519097 (breast); RORB rs7867494 (breast cancer postmenopausal), PER3 rs1012477 (breast cancer subgroups) and assessed the level of quality evidence to be intermediate. We also identified polymorphisms with lower quality statistically significant associations (n=30). Our work supports the hypothesis that genetic variation of clock genes might affect cancer risk. These findings also highlight the need for more efforts in this research field in order to fully establish the contribution of clock gene variants to the risk of developing cancer. We conducted a systematic review and meta-analysis of the evidence on the association between clock genes' germline variants and the risk of developing cancer. To assess result credibility, summary evidence was graded according to the Venice criteria and false positive report probability (FPRP) was calculated to further validate

Semi-supervised consensus clustering for gene expression data analysis

OpenAIRE

Wang, Yunli; Pan, Youlian

2014-01-01

Background Simple clustering methods such as hierarchical clustering and k-means are widely used for gene expression data analysis; but they are unable to deal with noise and high dimensionality associated with the microarray gene expression data. Consensus clustering appears to improve the robustness and quality of clustering results. Incorporating prior knowledge in clustering process (semi-supervised clustering) has been shown to improve the consistency between the data partitioning and do...

Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

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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.

Microarray gene expression profiling and analysis in renal cell carcinoma

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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

Gastric Cancer Associated Genes Identified by an Integrative Analysis of Gene Expression Data

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Bing Jiang

2017-01-01

Full Text Available Gastric cancer is one of the most severe complex diseases with high morbidity and mortality in the world. The molecular mechanisms and risk factors for this disease are still not clear since the cancer heterogeneity caused by different genetic and environmental factors. With more and more expression data accumulated nowadays, we can perform integrative analysis for these data to understand the complexity of gastric cancer and to identify consensus players for the heterogeneous cancer. In the present work, we screened the published gene expression data and analyzed them with integrative tool, combined with pathway and gene ontology enrichment investigation. We identified several consensus differentially expressed genes and these genes were further confirmed with literature mining; at last, two genes, that is, immunoglobulin J chain and C-X-C motif chemokine ligand 17, were screened as novel gastric cancer associated genes. Experimental validation is proposed to further confirm this finding.

Comparative modular analysis of gene expression in vertebrate organs

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Piasecka Barbara

2012-03-01

Full Text Available Abstract Background The degree of conservation of gene expression between homologous organs largely remains an open question. Several recent studies reported some evidence in favor of such conservation. Most studies compute organs' similarity across all orthologous genes, whereas the expression level of many genes are not informative about organ specificity. Results Here, we use a modularization algorithm to overcome this limitation through the identification of inter-species co-modules of organs and genes. We identify such co-modules using mouse and human microarray expression data. They are functionally coherent both in terms of genes and of organs from both organisms. We show that a large proportion of genes belonging to the same co-module are orthologous between mouse and human. Moreover, their zebrafish orthologs also tend to be expressed in the corresponding homologous organs. Notable exceptions to the general pattern of conservation are the testis and the olfactory bulb. Interestingly, some co-modules consist of single organs, while others combine several functionally related organs. For instance, amygdala, cerebral cortex, hypothalamus and spinal cord form a clearly discernible unit of expression, both in mouse and human. Conclusions Our study provides a new framework for comparative analysis which will be applicable also to other sets of large-scale phenotypic data collected across different species.

Comparative modular analysis of gene expression in vertebrate organs.

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Piasecka, Barbara; Kutalik, Zoltán; Roux, Julien; Bergmann, Sven; Robinson-Rechavi, Marc

2012-03-29

The degree of conservation of gene expression between homologous organs largely remains an open question. Several recent studies reported some evidence in favor of such conservation. Most studies compute organs' similarity across all orthologous genes, whereas the expression level of many genes are not informative about organ specificity. Here, we use a modularization algorithm to overcome this limitation through the identification of inter-species co-modules of organs and genes. We identify such co-modules using mouse and human microarray expression data. They are functionally coherent both in terms of genes and of organs from both organisms. We show that a large proportion of genes belonging to the same co-module are orthologous between mouse and human. Moreover, their zebrafish orthologs also tend to be expressed in the corresponding homologous organs. Notable exceptions to the general pattern of conservation are the testis and the olfactory bulb. Interestingly, some co-modules consist of single organs, while others combine several functionally related organs. For instance, amygdala, cerebral cortex, hypothalamus and spinal cord form a clearly discernible unit of expression, both in mouse and human. Our study provides a new framework for comparative analysis which will be applicable also to other sets of large-scale phenotypic data collected across different species.

Identification of pathogenic genes related to rheumatoid arthritis through integrated analysis of DNA methylation and gene expression profiling.

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Zhang, Lei; Ma, Shiyun; Wang, Huailiang; Su, Hang; Su, Ke; Li, Longjie

2017-11-15

The purpose of our study was to identify new pathogenic genes used for exploring the pathogenesis of rheumatoid arthritis (RA). To screen pathogenic genes of RA, an integrated analysis was performed by using the microarray datasets in RA derived from the Gene Expression Omnibus (GEO) database. The functional annotation and potential pathways of differentially expressed genes (DEGs) were further discovered by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Afterwards, the integrated analysis of DNA methylation and gene expression profiling was used to screen crucial genes. In addition, we used RT-PCR and MSP to verify the expression levels and methylation status of these crucial genes in 20 synovial biopsy samples obtained from 10 RA model mice and 10 normal mice. BCL11B, CCDC88C, FCRLA and APOL6 were both up-regulated and hypomethylated in RA according to integrated analysis, RT-PCR and MSP verification. Four crucial genes (BCL11B, CCDC88C, FCRLA and APOL6) identified and analyzed in this study might be closely connected with the pathogenesis of RA. Copyright © 2017. Published by Elsevier B.V.

A Serial Analysis of Gene Expression (SAGE) database analysis of chemosensitivity

DEFF Research Database (Denmark)

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

2004-01-01

are their corresponding solid tumors. We used the Serial Analysis of Gene Expression (SAGE) database to identify differences between solid tumors and cell lines, hoping to detect genes that could potentially explain differences in drug sensitivity. SAGE libraries were available for both solid tumors and cell lines from...

Systematic review and meta-analysis: the relationship between the Helicobacter pylori dupA gene and clinical outcomes

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Shiota Seiji

2010-10-01

Full Text Available Abstract Background In 2005, the first disease-specific Helicobacter pylori virulence factor that induced duodenal ulcer and had a suppressive action on gastric cancer has been identified, and was named duodenal ulcer promoting gene (dupA. However, the importance of the dupA gene on clinical outcomes is conflicting in subsequent studies. The aim of this study was to estimate the magnitude of the risk for clinical outcomes associated with dupA gene. Methods A meta-analysis of case-control studies which provided raw data on the infection rates with the dupA-positive H. pylori detected by polymerase chain reaction was performed. Results Seventeen studies with a total of 2,466 patients were identified in the search. Infection with the dupA-positive H. pylori increased the risk for duodenal ulcer by 1.41-fold (95% confidence interval [CI], 1.12-1.76 overall. Subgroup analysis showed that the summary odds ratio (OR was 1.57 (95% CI, 1.19-2.06 in Asian countries and 1.09 (95% CI, 0.73-1.62 in Western countries. There was no association between the presence of the dupA gene and gastric cancer and gastric ulcer. Publication bias did not exist. Conclusion Our meta-analysis confirmed the importance of the presence of the dupA gene for duodenal ulcer, especially in Asian countries.

Systematic review and meta-analysis: the relationship between the Helicobacter pylori dupA gene and clinical outcomes.

Science.gov (United States)

Shiota, Seiji; Matsunari, Osamu; Watada, Masahide; Hanada, Katsuhiro; Yamaoka, Yoshio

2010-10-31

In 2005, the first disease-specific Helicobacter pylori virulence factor that induced duodenal ulcer and had a suppressive action on gastric cancer has been identified, and was named duodenal ulcer promoting gene (dupA). However, the importance of the dupA gene on clinical outcomes is conflicting in subsequent studies. The aim of this study was to estimate the magnitude of the risk for clinical outcomes associated with dupA gene. A meta-analysis of case-control studies which provided raw data on the infection rates with the dupA-positive H. pylori detected by polymerase chain reaction was performed. Seventeen studies with a total of 2,466 patients were identified in the search. Infection with the dupA-positive H. pylori increased the risk for duodenal ulcer by 1.41-fold (95% confidence interval [CI], 1.12-1.76) overall. Subgroup analysis showed that the summary odds ratio (OR) was 1.57 (95% CI, 1.19-2.06) in Asian countries and 1.09 (95% CI, 0.73-1.62) in Western countries. There was no association between the presence of the dupA gene and gastric cancer and gastric ulcer. Publication bias did not exist. Our meta-analysis confirmed the importance of the presence of the dupA gene for duodenal ulcer, especially in Asian countries.

Expression analysis of dihydroflavonol 4-reductase genes in Petunia hybrida.

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Chu, Y X; Chen, H R; Wu, A Z; Cai, R; Pan, J S

2015-05-12

Dihydroflavonol 4-reductase (DFR) genes from Rosa chinensis (Asn type) and Calibrachoa hybrida (Asp type), driven by a CaMV 35S promoter, were integrated into the petunia (Petunia hybrida) cultivar 9702. Exogenous DFR gene expression characteristics were similar to flower-color changes, and effects on anthocyanin concentration were observed in both types of DFR gene transformants. Expression analysis showed that exogenous DFR genes were expressed in all of the tissues, but the expression levels were significantly different. However, both of them exhibited a high expression level in petals that were starting to open. The introgression of DFR genes may significantly change DFR enzyme activity. Anthocyanin ultra-performance liquid chromatography results showed that anthocyanin concentrations changed according to DFR enzyme activity. Therefore, the change in flower color was probably the result of a DFR enzyme change. Pelargonidin 3-O-glucoside was found in two different transgenic petunias, indicating that both CaDFR and RoDFR could catalyze dihydrokaempferol. Our results also suggest that transgenic petunias with DFR gene of Asp type could biosynthesize pelargonidin 3-O-glucoside.

Survivin protein expression is involved in the progression of non-small cell lung cancer in Asians: a meta-analysis

International Nuclear Information System (INIS)

Duan, Liang; Hu, Xuefei; Jin, Yuxing; Liu, Ruijun; You, Qingjun

2016-01-01

Surviving expression might serve as a prognostic biomarker predicting the clinical outcome of non-small cell lung cancer (NSCLC). The study was conducted to explore the potential correlation of survivin protein expression with NSCLC and its clinicopathologic characteristics. PubMed, Medline, Cochrane Library, CNKI and Wanfang database were searched through January 2016 with a set of inclusion and exclusion criteria. Data was extracted from these articles and all statistical analysis was conducted by using Stata 12.0. A total of 28 literatures (14 studies in Chinese and 14 studies in English) were enrolled in this meta-analysis, including 3206 NSCLC patients and 816 normal controls. The result of meta-analysis demonstrated a significant difference of survivin positive expression between NSCLC patients and normal controls (RR = 7.16, 95 % CI = 4.63-11.07, P < 0.001). To investigate the relationship of survivin expression and clinicopathologic characteristics, we performed a meta-analysis in NSCLC patients. Our results indicates survivin expression was associated with histological differentiation, tumor-node-metastasis (TNM) stage and lymph node metastasis (LNM) (RR = 0.80, 95 % CI = 0.73-0.87, P < 0.001; RR = 0.75, 95 % CI = 0.67-0.84, P < 0.001; RR = 1.14, 95 % CI = 1.01-1.29, P = 0.035, respectively), but not pathological type and tumor size. (RR = 1.00, 95 % CI = 0.93-1.07, P = 0.983; RR = 0.95, 95 % CI = 0.86-1.05, P = 0.336, respectively). Higher expression of survivin in NSCLC patients was found when compared to normal controls. Survivin expression was associated with the clinicopathologic characteristics of NSCLC and may serves as an important biomarker for NSCLC progression

Quick and sensitive determination of gene expression of fatty acid ...

African Journals Online (AJOL)

User

2011-05-16

May 16, 2011 ... from fatty acid synthase (FAS) with a different glucose level in ... By using the following formula, this study was able to quantify the mRNA expression of ... hypertension, heart disease and diabetes. ... regulation of gene expression has emerged in recent ... stages of adipocyte meta-bolism are relatively well.

Time-Course Analysis of Gene Expression During the Saccharomyces cerevisiae Hypoxic Response

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Nasrine Bendjilali

2017-01-01

Full Text Available Many cells experience hypoxia, or low oxygen, and respond by dramatically altering gene expression. In the yeast Saccharomyces cerevisiae, genes that respond are required for many oxygen-dependent cellular processes, such as respiration, biosynthesis, and redox regulation. To more fully characterize the global response to hypoxia, we exposed yeast to hypoxic conditions, extracted RNA at different times, and performed RNA sequencing (RNA-seq analysis. Time-course statistical analysis revealed hundreds of genes that changed expression by up to 550-fold. The genes responded with varying kinetics suggesting that multiple regulatory pathways are involved. We identified most known oxygen-regulated genes and also uncovered new regulated genes. Reverse transcription-quantitative PCR (RT-qPCR analysis confirmed that the lysine methyltransferase EFM6 and the recombinase DMC1, both conserved in humans, are indeed oxygen-responsive. Looking more broadly, oxygen-regulated genes participate in expected processes like respiration and lipid metabolism, but also in unexpected processes like amino acid and vitamin metabolism. Using principle component analysis, we discovered that the hypoxic response largely occurs during the first 2 hr and then a new steady-state expression state is achieved. Moreover, we show that the oxygen-dependent genes are not part of the previously described environmental stress response (ESR consisting of genes that respond to diverse types of stress. While hypoxia appears to cause a transient stress, the hypoxic response is mostly characterized by a transition to a new state of gene expression. In summary, our results reveal that hypoxia causes widespread and complex changes in gene expression to prepare the cell to function with little or no oxygen.

Time-Course Analysis of Gene Expression During the Saccharomyces cerevisiae Hypoxic Response.

Science.gov (United States)

Bendjilali, Nasrine; MacLeon, Samuel; Kalra, Gurmannat; Willis, Stephen D; Hossian, A K M Nawshad; Avery, Erica; Wojtowicz, Olivia; Hickman, Mark J

2017-01-05

Many cells experience hypoxia, or low oxygen, and respond by dramatically altering gene expression. In the yeast Saccharomyces cerevisiae, genes that respond are required for many oxygen-dependent cellular processes, such as respiration, biosynthesis, and redox regulation. To more fully characterize the global response to hypoxia, we exposed yeast to hypoxic conditions, extracted RNA at different times, and performed RNA sequencing (RNA-seq) analysis. Time-course statistical analysis revealed hundreds of genes that changed expression by up to 550-fold. The genes responded with varying kinetics suggesting that multiple regulatory pathways are involved. We identified most known oxygen-regulated genes and also uncovered new regulated genes. Reverse transcription-quantitative PCR (RT-qPCR) analysis confirmed that the lysine methyltransferase EFM6 and the recombinase DMC1, both conserved in humans, are indeed oxygen-responsive. Looking more broadly, oxygen-regulated genes participate in expected processes like respiration and lipid metabolism, but also in unexpected processes like amino acid and vitamin metabolism. Using principle component analysis, we discovered that the hypoxic response largely occurs during the first 2 hr and then a new steady-state expression state is achieved. Moreover, we show that the oxygen-dependent genes are not part of the previously described environmental stress response (ESR) consisting of genes that respond to diverse types of stress. While hypoxia appears to cause a transient stress, the hypoxic response is mostly characterized by a transition to a new state of gene expression. In summary, our results reveal that hypoxia causes widespread and complex changes in gene expression to prepare the cell to function with little or no oxygen. Copyright © 2017 Bendjilali et al.

The role of the Cys23Ser (rs6318) polymorphism of the HTR2C gene in suicidal behavior: systematic review and meta-analysis.

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González-Castro, Thelma B; Hernandez-Diaz, Yazmín; Juárez-Rojop, Isela E; López-Narváez, Lilia; Tovilla-Zárate, Carlos A; Rodriguez-Perez, José M; Sánchez-de la Cruz, Juan P

2017-12-01

The polymorphisms of the serotonin receptor 2C (HTR2C) gene have been proposed to influence suicidal behavior. The aim of our study was to explore the role of the HTR2C gene variant Cys23Ser (rs6318) in the pathogenesis of suicidal behavior through a systematic review and meta-analysis. The search was performed using EBSCO and PubMed databases. To be included in the analysis, the studies had to evaluate suicidal behavior (attempted, ideation, or completed suicide). The results of the meta-analysis were expressed as odds ratios (ORs). Because HTR2C lies on chromosome X, pooled ORs were calculated, respectively, for each of the models used, namely: allelic, homozygous, dominant, and recessive for the female group and allelic for the male group. The meta-analysis comprised 3867 individuals, including 1668 cases and 2199 controls. The HTR2C Cys23Ser (rs6318) polymorphism did not show a significant association with suicidal behavior either in women (OR: 0.75; 95% confidence interval: 0.55-1.00) or in men (OR: 0.89; 95% confidence interval: 0.64-1.23). Similarly, nonsignificant associations were observed for all of the genetic models used in any of the populations/subgroups studied. Our findings suggest that the rs6318 (Cys23Ser) polymorphism is not associated with suicidal behavior. However, because of the study limitations, we suggest more researches should be performed, increasing the sample sizes and statistical power, to determine the association between the rs6318 variant and suicidal behavior.

Association between fat mass- and obesity-associated (FTO gene polymorphism and polycystic ovary syndrome: a meta-analysis.

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Xianli Cai

Full Text Available Many studies have investigated the relationship between FTO gene polymorphism and polycystic ovary syndrome (PCOS susceptibility but revealed mixed results. In this study, we aimed to perform a meta-analysis to clarify this association.Published literature from PubMed, Embase and CNKI was retrieved. Meta-analysis was performed to calculate pooled odds ratio (OR with 95% confidence interval (CI using the random- or fix- effects model.A total of 5 studies (4778 cases and 4272 controls were included in our meta-analysis. The results suggested that FTO rs9939609 polymorphism (or its proxy was marginally associated with PCOS risk after adjustment for body mass index (BMI (OR = 1.26; 95%CI: 1.02-1.55. However, the marginal association was not stable after sensitivity analysis. In the subgroup analysis by ethnicity, the association was significant in East Asians (OR = 1.43, 95%CI = 1.30-1.59 but not in Caucasians (OR = 1.04, 95%CI = 0.85-1.29.Our present meta-analysis indicated that FTO rs9939609 polymorphism (or its proxy might not be associated with risk of PCOS in overall population. However, in East Asians, there might be a direct association between FTO variant and PCOS risk, which is independent of BMI (adiposity.

Serial analysis of gene expression (SAGE) in rat liver regeneration

International Nuclear Information System (INIS)

Cimica, Velasco; Batusic, Danko; Haralanova-Ilieva, Borislava; Chen, Yonglong; Hollemann, Thomas; Pieler, Tomas; Ramadori, Giuliano

2007-01-01

We have applied serial analysis of gene expression for studying the molecular mechanism of the rat liver regeneration in the model of 70% partial hepatectomy. We generated three SAGE libraries from a normal control liver (NL library: 52,343 tags), from a sham control operated liver (Sham library: 51,028 tags), and from a regenerating liver (PH library: 53,061 tags). By SAGE bioinformatics analysis we identified 40 induced genes and 20 repressed genes during the liver regeneration. We verified temporal expression of such genes by real time PCR during the regeneration process and we characterized 13 induced genes and 3 repressed genes. We found connective tissue growth factor transcript and protein induced very early at 4 h after PH operation before hepatocytes proliferation is triggered. Our study suggests CTGF as a growth factor signaling mediator that could be involved directly in the mechanism of liver regeneration induction

Global Gene Expression Analysis of Yeast Cells during Sake Brewing▿ †

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Wu, Hong; Zheng, Xiaohong; Araki, Yoshio; Sahara, Hiroshi; Takagi, Hiroshi; Shimoi, Hitoshi

2006-01-01

During the brewing of Japanese sake, Saccharomyces cerevisiae cells produce a high concentration of ethanol compared with other ethanol fermentation methods. We analyzed the gene expression profiles of yeast cells during sake brewing using DNA microarray analysis. This analysis revealed some characteristics of yeast gene expression during sake brewing and provided a scaffold for a molecular level understanding of the sake brewing process. PMID:16997994

Discs Large Homolog 5 (DLG5 Gene Polymorphism and Crohn’s Disease: A Meta-Analysis of the Published Studies

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Arezoo Shafieyoun

2016-05-01

Full Text Available The real pathophysiology of Crohn’s disease is unknown. The higher prevalence of Crohn’s disease in Caucasian and Jewish ethnicities, as well as its familial aggregation and higher concordance among monozygotic twins, suggest some roles for genes in its development, clinical progression, and outcome. Recent original studies have indicated DLG5113G/A gene polymorphism as a risk factor for Crohn’s disease. Meanwhile, the results of these studies are not consistent. We performed the current meta-analysis to understand whether there is any association between DLG5 gene polymorphism and the risk of Crohn’s disease. PubMed was searched to find the case-control studies on DLG5 gene polymorphisms and Crohn’s disease. This search compiled 65 articles and based on our criteria. 11 articles were included in this meta-analysis. The association between the DLG5 113G/A polymorphism and the risk of disease was assessed using odds ratio (OR and 95% confidence interval (95% CI. Heterogeneity was evaluated based on I2 values.  Random and fixed-effect models were used when I2>50% and I2≤50%, respectively. Eleven studies with a total of 4648 cases and 5677 controls were pooled. Based on our meta-analysis, DLG5113G/A gene polymorphism both at genotypic and allelic levels were not associated with the risk of Crohn’s disease. Pooled data indicated no significant association between DLG5113G/A gene polymorphism and the development of Crohn’s disease. In order to achieve a superior conclusion, multicenter studies on larger number of patients are recommended.

A Systematic Review and Meta-Analysis of Predictors of Expressive-Language Outcomes among Late Talkers

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Fisher, Evelyn L.

2017-01-01

Purpose: The purpose of this study was to explore the literature on predictors of outcomes among late talkers using systematic review and meta-analysis methods. We sought to answer the question: What factors predict preschool-age expressive-language outcomes among late-talking toddlers? Method: We entered carefully selected search terms into the…

Global gene expression analysis of the zoonotic parasite Trichinella spiralis revealed novel genes in host parasite interaction.

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Xiaolei Liu

Full Text Available BACKGROUND: Trichinellosis is a typical food-borne zoonotic disease which is epidemic worldwide and the nematode Trichinella spiralis is the main pathogen. The life cycle of T. spiralis contains three developmental stages, i.e. adult worms, new borne larva (new borne L1 larva and muscular larva (infective L1 larva. Stage-specific gene expression in the parasites has been investigated with various immunological and cDNA cloning approaches, whereas the genome-wide transcriptome and expression features of the parasite have been largely unknown. The availability of the genome sequence information of T. spiralis has made it possible to deeply dissect parasite biology in association with global gene expression and pathogenesis. METHODOLOGY AND PRINCIPAL FINDINGS: In this study, we analyzed the global gene expression patterns in the three developmental stages of T. spiralis using digital gene expression (DGE analysis. Almost 15 million sequence tags were generated with the Illumina RNA-seq technology, producing expression data for more than 9,000 genes, covering 65% of the genome. The transcriptome analysis revealed thousands of differentially expressed genes within the genome, and importantly, a panel of genes encoding functional proteins associated with parasite invasion and immuno-modulation were identified. More than 45% of the genes were found to be transcribed from both strands, indicating the importance of RNA-mediated gene regulation in the development of the parasite. Further, based on gene ontological analysis, over 3000 genes were functionally categorized and biological pathways in the three life cycle stage were elucidated. CONCLUSIONS AND SIGNIFICANCE: The global transcriptome of T. spiralis in three developmental stages has been profiled, and most gene activity in the genome was found to be developmentally regulated. Many metabolic and biological pathways have been revealed. The findings of the differential expression of several protein

Serial Analysis of Gene Expression: Applications in Human Studies

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Tuteja Renu

2004-01-01

Full Text Available Serial analysis of gene expression (SAGE is a powerful tool, which provides quantitative and comprehensive expression profile of genes in a given cell population. It works by isolating short fragments of genetic information from the expressed genes that are present in the cell being studied. These short sequences, called SAGE tags, are linked together for efficient sequencing. The frequency of each SAGE tag in the cloned multimers directly reflects the transcript abundance. Therefore, SAGE results in an accurate picture of gene expression at both the qualitative and the quantitative levels. It does not require a hybridization probe for each transcript and allows new genes to be discovered. This technique has been applied widely in human studies and various SAGE tags/SAGE libraries have been generated from different cells/tissues such as dendritic cells, lung fibroblast cells, oocytes, thyroid tissue, B-cell lymphoma, cultured keratinocytes, muscles, brain tissues, sciatic nerve, cultured Schwann cells, cord blood-derived mast cells, retina, macula, retinal pigment epithelial cells, skin cells, and so forth. In this review we present the updated information on the applications of SAGE technology mainly to human studies.

Associations between dopamine D2 receptor gene polymorphisms and schizophrenia risk: a PRISMA compliant meta-analysis

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He HR

2016-12-01

Full Text Available Hairong He,1 Huanhuan Wu,1,2 Lihong Yang,1 Fan Gao,1 Yajuan Fan,3 Junqin Feng,3 Xiancang Ma1,3 1Clinical Research Center, The First Affiliated Hospital of Xi’an Jiaotong University, 2College of Pharmacy, Xi’an Medical University, 3Department of Psychiatry, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China Objective: To determine the relationships between dopamine D2 receptor gene polymorphisms and the risk of schizophrenia using meta-analysis.Method: The PubMed, Embase, and China National Knowledge Infrastructure databases were searched to identify relevant literature published up to February 2016. The allele contrast model was used. STATA software was used for statistical analysis, with odds ratios (ORs and 95% confidence intervals (CIs calculated to evaluate the associations between dopamine D2 receptor gene polymorphisms and the risk of schizophrenia. Meta-regression and publication bias, trim-and-fill, subgroup, sensitivity, cumulative, and fail-safe number analyses were also performed.Results: This meta-analysis included 81 studies. The rs1801028 and rs1799732 were associated with schizophrenia risk among Asians (P=0.04, OR =1.25, 95% CI =1.01–1.55; P<0.01, OR =0.76, 95% CI =0.63–0.92, respectively, while the rs6277 was associated with schizophrenia risk in Caucasians (P<0.01, OR=0.72, 95% CI =0.66–0.79. The rs1800497 was also associated with schizophrenia risk in population-based controls (P<0.01, OR =0.84, 95% CI =0.72–0.97. The rs6275, rs1079597, and rs1800498 were not associated with schizophrenia risk. In addition, meta-regression indicated that the controls may be sources of heterogeneity for the rs1801028 single-nucleotide polymorphism (SNP, while ethnicity may be sources of heterogeneity for the rs6277 SNP. Publication bias was significant for the rs1801028 SNP, and this result changed after the publication bias was adjusted using the trim-and-fill method

AB126. Association between FOX03A gene polymorphisms and human longevity: a meta-analysis

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Zhao, Shanchao; Bao, Jiming; Song, Xianlu

2016-01-01

Objective Numerous studies have shown associations between the FOX03A gene, encoding the forkhead box 03 transcription factor, and human or specifically male longevity. However, the associations of specific FOX03A polymorphisms with longevity remain inconclusive. We performed a meta-analysis of existing studies to clarify these potential associations. Methods A comprehensive search was conducted to identify studies of FOX03A gene polymorphisms and longevity. Pooled odds ratios (ORs) and 95% confidence intervals (Cls) were calculated by comparing the minor and major alleles. Results A total of seven articles reporting associations of FOX03A polymorphisms with longevity were identified and included in this meta-analysis. These comprised 11 independent studies with 5241 cases and 5724 controls from different ethnic groups. rs2802292, rs2764264, rsI3217795, rs1935949 and rs2802288 polymorphisms were associated with human longevity (OR =1.36, 95% CI, 1. 10–1.69, P=0.005; OR =1.20, 95% CI, 1.04–1.37, P=0.01; OR =1.27, 95% CI, 1.10–1.46, P=0.001; OR =1.14, 95% CI, 1.01–1.27 and OR =1.24, 95% CI, 1.07–1.43, P=0.003, respectively). Analysis is stratified by gender indicated significant associations between rs2802292, rs2764264 and rs13217795 and male longevity (OR =1.54, 95% CI, 1.33–1.79, P<0.001; OR =1.38, 95% CI, 1.15–1.66, P=0.001; and OR =1.39, 95% CI, 1.15–1.67, P=0.001), but rs2802292, rs2764264 and rs1935949 were not linked to female longevity. Moreover, our study showed no association between rs2153960, rs7762395 or rs13220810 polymorphisms and longevity. Conclusions In conclusion, this meta-analysis indicates a significant association of five FOX03A gene polymorphisms with longevity, with the effects of rs2802292 and rs2764264 being male-specific. Further investigations are required to confirm these findings.

Analysis of gene expression profile microarray data in complex regional pain syndrome.

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Tan, Wulin; Song, Yiyan; Mo, Chengqiang; Jiang, Shuangjian; Wang, Zhongxing

2017-09-01

The aim of the present study was to predict key genes and proteins associated with complex regional pain syndrome (CRPS) using bioinformatics analysis. The gene expression profiling microarray data, GSE47603, which included peripheral blood samples from 4 patients with CRPS and 5 healthy controls, was obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in CRPS patients compared with healthy controls were identified using the GEO2R online tool. Functional enrichment analysis was then performed using The Database for Annotation Visualization and Integrated Discovery online tool. Protein‑protein interaction (PPI) network analysis was subsequently performed using Search Tool for the Retrieval of Interaction Genes database and analyzed with Cytoscape software. A total of 257 DEGs were identified, including 243 upregulated genes and 14 downregulated ones. Genes in the human leukocyte antigen (HLA) family were most significantly differentially expressed. Enrichment analysis demonstrated that signaling pathways, including immune response, cell motion, adhesion and angiogenesis were associated with CRPS. PPI network analysis revealed that key genes, including early region 1A binding protein p300 (EP300), CREB‑binding protein (CREBBP), signal transducer and activator of transcription (STAT)3, STAT5A and integrin α M were associated with CRPS. The results suggest that the immune response may therefore serve an important role in CRPS development. In addition, genes in the HLA family, such as HLA‑DQB1 and HLA‑DRB1, may present potential biomarkers for the diagnosis of CRPS. Furthermore, EP300, its paralog CREBBP, and the STAT family genes, STAT3 and STAT5 may be important in the development of CRPS.

Identification of Important Physiological Traits and Moderators That Are Associated with Improved Salt Tolerance in CBL and CIPK Overexpressors through a Meta-Analysis

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Yuanchun Ma

2017-05-01

Full Text Available The CBL-CIPK pathway is a plant-specific Ca2+ sensor relaying pathway that has been shown to be involved in plant response to salt stress. Over-expression of CBL-CIPK network genes has been reported to increase salt tolerance in many studies. The studies on the overexpression of CBL-CIPK network genes, however, have used various indices to evaluate the effect of these genes on salt tolerance and have indicated a variety of roles for the major CBL-CIPK pathway genes. Therefore, it is of great interest to analyze the various effects resulting from the overexpression CBL-CIPK pathway genes and their relation to salt tolerance. The meta-analysis conducted in the present study investigated how over-expression of CBLs or CIPKs in transgenic plants affects the response to salt stress and identified the increase or decrease that occurs in these experimental variables when foreign CIPK or CBL genes are overexpressed in transgenic plants. The data from the collective studies on over-expression of CIPKs indicated that 6 of the 11 examined parameters (main effects increased by 22% or more, while two of the six examined parameters increased by at least 78% in transgenic plants overexpressing CBL genes. In addition to analyzing the impact of overexpression on the main effects, eight different modifying parameters were also analyzed. Results indicated that several moderators impact the extent to which overexpression of CBLs and CIPKs affect the main parameters. The majority of CBLs have been obtained from dicotyledonous plants and most of the CBLs and CIPKs have been expressed in dicotyledonous plants. In comparison to homologous expression, the meta-analysis indicated that heterogeneous expression of CBLs resulted in greater increases in seed germination. The results of the meta-analysis provide information that could be useful in designing research to examine the mechanisms by which CBL-CIPK pathway genes increase salt tolerance in plants.

The Gly482Ser genotype at the PPARGC1A gene and elevated blood pressure: a meta-analysis involving 13,949 individuals

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Vimaleswaran, Karani Santhanakrishnan; Luan, Jian'an; Andersen, Gitte

2008-01-01

The protein encoded by the PPARGC1A gene is expressed at high levels in metabolically active tissues and is involved in the control of oxidative stress via reactive oxygen species detoxification. Several recent reports suggest that the PPARGC1A Gly482Ser (rs8192678) missense polymorphism may relate...... inversely with blood pressure. We used conventional meta-analysis methods to assess the association between Gly482Ser and systolic (SBP) or diastolic blood pressures (DBP) or hypertension in 13,949 individuals from 17 studies, of which 6,042 were previously unpublished observations. The studies comprised...

Semantic integration of gene expression analysis tools and data sources using software connectors

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2013-01-01

Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools

The role of CD147 expression in prostate cancer: a systematic review and meta-analysis

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Ye Y

2016-08-01

Full Text Available Yun Ye,1,2,* Su-Liang Li,2,* Yao Wang,2 Yang Yao,2 Juan Wang,1 Yue-Yun Ma,1 Xiao-Ke Hao1 1Department of Laboratory Medicine, Xijing Hospital, Fourth Military Medical University, 2Department of Clinical Laboratory, The First Affiliated Hospital of Xi’an Medical University, Xi’an, Shaanxi, People’s Republic of China *These authors contributed equally to this work Background: There are a number of studies which show that expression of CD147 is increased significantly in prostate cancer (PCa. However, conflicting conclusions have also been reported by other researchers lately. In order to arrive at a clear conclusion, a meta-analysis of eligible studies was conducted.Materials and methods: We searched PubMed, MEDLINE, Cochrane Library, and the China National Knowledge Infrastructure databases to identify all the published case–control studies on the relationship between the expression of CD147 and PCa until February 2016. In the end, a total of 930 patients in eight studies were included in the meta-analysis.Results: CD147 expression in the PCa patients increased significantly (odds ratio [OR], 4.65; 95% confidence interval [CI], 3.52–6.14; Z=10.79; P<0.05, but there was obvious heterogeneity between studies (I2=92.9%, P<0.05. Subgroup analysis showed that positive expression of CD147 was associated with PCa among the Asian population (OR, 21.01; 95% CI, 12.88–34.28; Z=12.19; P<0.05. Furthermore, it was significantly related to TNM stage (OR, 0.24; 95% CI, 0.17–0.35; Z=7.74; P<0.05, Gleason score (OR, 0.41; 95% CI, 0.31–0.56; Z=5.62; P<0.05, differentiation grade (OR, 0.27; 95% CI, 0.13–0.56; Z=3.47; P<0.05, and pretreatment serum prostate-specific antigen level (OR, 0.07; 95% CI, 0.03–0.16; Z=6.47; P<0.05.Conclusion: Positive expression of CD147 was related to PCa, significant heterogeneity was not found between Asian studies, and the result became more significant. The positive expression of CD147 was significantly related to

Meta-Analysis of Maternal and Fetal Transcriptomic Data Elucidates the Role of Adaptive and Innate Immunity in Preterm Birth

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Vora, Bianca; Wang, Aolin; Kosti, Idit; Huang, Hongtai; Paranjpe, Ishan; Woodruff, Tracey J.; MacKenzie, Tippi; Sirota, Marina

2018-01-01

Preterm birth (PTB) is the leading cause of newborn deaths around the world. Spontaneous preterm birth (sPTB) accounts for two-thirds of all PTBs; however, there remains an unmet need of detecting and preventing sPTB. Although the dysregulation of the immune system has been implicated in various studies, small sizes and irreproducibility of results have limited identification of its role. Here, we present a cross-study meta-analysis to evaluate genome-wide differential gene expression signals in sPTB. A comprehensive search of the NIH genomic database for studies related to sPTB with maternal whole blood samples resulted in data from three separate studies consisting of 339 samples. After aggregating and normalizing these transcriptomic datasets and performing a meta-analysis, we identified 210 genes that were differentially expressed in sPTB relative to term birth. These genes were enriched in immune-related pathways, showing upregulation of innate immunity and downregulation of adaptive immunity in women who delivered preterm. An additional analysis found several of these differentially expressed at mid-gestation, suggesting their potential to be clinically relevant biomarkers. Furthermore, a complementary analysis identified 473 genes differentially expressed in preterm cord blood samples. However, these genes demonstrated downregulation of the innate immune system, a stark contrast to findings using maternal blood samples. These immune-related findings were further confirmed by cell deconvolution as well as upstream transcription and cytokine regulation analyses. Overall, this study identified a strong immune signature related to sPTB as well as several potential biomarkers that could be translated to clinical use.

Meta-Analysis of Maternal and Fetal Transcriptomic Data Elucidates the Role of Adaptive and Innate Immunity in Preterm Birth

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Bianca Vora

2018-05-01

Full Text Available Preterm birth (PTB is the leading cause of newborn deaths around the world. Spontaneous preterm birth (sPTB accounts for two-thirds of all PTBs; however, there remains an unmet need of detecting and preventing sPTB. Although the dysregulation of the immune system has been implicated in various studies, small sizes and irreproducibility of results have limited identification of its role. Here, we present a cross-study meta-analysis to evaluate genome-wide differential gene expression signals in sPTB. A comprehensive search of the NIH genomic database for studies related to sPTB with maternal whole blood samples resulted in data from three separate studies consisting of 339 samples. After aggregating and normalizing these transcriptomic datasets and performing a meta-analysis, we identified 210 genes that were differentially expressed in sPTB relative to term birth. These genes were enriched in immune-related pathways, showing upregulation of innate immunity and downregulation of adaptive immunity in women who delivered preterm. An additional analysis found several of these differentially expressed at mid-gestation, suggesting their potential to be clinically relevant biomarkers. Furthermore, a complementary analysis identified 473 genes differentially expressed in preterm cord blood samples. However, these genes demonstrated downregulation of the innate immune system, a stark contrast to findings using maternal blood samples. These immune-related findings were further confirmed by cell deconvolution as well as upstream transcription and cytokine regulation analyses. Overall, this study identified a strong immune signature related to sPTB as well as several potential biomarkers that could be translated to clinical use.

Teaching meta-analysis using MetaLight

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Thomas James

2012-10-01

Full Text Available Abstract Background Meta-analysis is a statistical method for combining the results of primary studies. It is often used in systematic reviews and is increasingly a method and topic that appears in student dissertations. MetaLight is a freely available software application that runs simple meta-analyses and contains specific functionality to facilitate the teaching and learning of meta-analysis. While there are many courses and resources for meta-analysis available and numerous software applications to run meta-analyses, there are few pieces of software which are aimed specifically at helping those teaching and learning meta-analysis. Valuable teaching time can be spent learning the mechanics of a new software application, rather than on the principles and practices of meta-analysis. Findings We discuss ways in which the MetaLight tool can be used to present some of the main issues involved in undertaking and interpreting a meta-analysis. Conclusions While there are many software tools available for conducting meta-analysis, in the context of a teaching programme such software can require expenditure both in terms of money and in terms of the time it takes to learn how to use it. MetaLight was developed specifically as a tool to facilitate the teaching and learning of meta-analysis and we have presented here some of the ways it might be used in a training situation.

GSMA: Gene Set Matrix Analysis, An Automated Method for Rapid Hypothesis Testing of Gene Expression Data

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Chris Cheadle

2007-01-01

Full Text Available Background: Microarray technology has become highly valuable for identifying complex global changes in gene expression patterns. The assignment of functional information to these complex patterns remains a challenging task in effectively interpreting data and correlating results from across experiments, projects and laboratories. Methods which allow the rapid and robust evaluation of multiple functional hypotheses increase the power of individual researchers to data mine gene expression data more efficiently.Results: We have developed (gene set matrix analysis GSMA as a useful method for the rapid testing of group-wise up- or downregulation of gene expression simultaneously for multiple lists of genes (gene sets against entire distributions of gene expression changes (datasets for single or multiple experiments. The utility of GSMA lies in its flexibility to rapidly poll gene sets related by known biological function or as designated solely by the end-user against large numbers of datasets simultaneously.Conclusions: GSMA provides a simple and straightforward method for hypothesis testing in which genes are tested by groups across multiple datasets for patterns of expression enrichment.

Association between interleukin 1 receptor antagonist gene 86-bp VNTR polymorphism and sepsis: a meta-analysis.

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Fang, Fang; Pan, Jian; Li, Yiping; Xu, Lixiao; Su, Guanghao; Li, Gang; Wang, Jian

2015-01-01

Many studies have focused on the relationship between interleukin 1 receptor antagonist (IL1RN) gene 86-bp VNTR polymorphism and sepsis, but the results remain inconsistent. Thus, a meta-analysis was carried out to derive a more precise estimation of the association between IL1RN 86-bp VNTR polymorphism and risk of sepsis and sepsis-related mortality. Relevant publications were searched in several widely used databases and six eligible studies were included in the meta-analysis. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to evaluate the strength of the association between IL1RN 86-bp VNTR polymorphism and risk of sepsis and sepsis-related mortality. Significant associations between IL1RN 86-bp VNTR polymorphism and sepsis risk were observed in both overall meta-analysis for L2 versus 22 (OR=0.75, 95% CI=0.59-0.94) and severe sepsis subgroup for LL+L2 versus 22 (OR=0.67, 95% CI=0.47-0.93). L stands for long alleles containing three to six repeats; 2 stands for short allele containing two repeats. However, no significant sepsis mortality variation was detected for all genetic models. According to the results of our meta-analysis, the IL1RN 86-bp VNTR polymorphism probably associates with sepsis risk but not with sepsis-related mortality. Copyright © 2014. Published by Elsevier Inc.

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis

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Akira Ishikawa

2017-11-01

Full Text Available Large numbers of quantitative trait loci (QTL affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis.

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Ishikawa, Akira

2017-11-27

Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

Serial analysis of gene expression in the silkworm, Bombyx mori.

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Huang, Jianhua; Miao, Xuexia; Jin, Weirong; Couble, Pierre; Mita, Kasuei; Zhang, Yong; Liu, Wenbin; Zhuang, Leijun; Shen, Yan; Keime, Celine; Gandrillon, Olivier; Brouilly, Patrick; Briolay, Jerome; Zhao, Guoping; Huang, Yongping

2005-08-01

The silkworm Bombyx mori is one of the most economically important insects and serves as a model for Lepidoptera insects. We used serial analysis of gene expression (SAGE) to derive profiles of expressed genes during the developmental life cycle of the silkworm and to create a reference for understanding silkworm metamorphosis. We generated four SAGE libraries, one from each of the four developmental stages of the silkworm. In total we obtained 257,964 SAGE tags, of which 39,485 were unique tags. Sorted by copy number, 14.1% of the unique tags were detected at a median to high level (five or more copies), 24.2% at lower levels (two to four copies), and 61.7% as single copies. Using a basic local alignment search tool on the EST database, 35% of the tags matched known silkworm expressed sequence tags. SAGE demonstrated that a number of the genes were up- or down-regulated during the four developmental phases of the egg, larva, pupa, and adult. Furthermore, we found that the generation of longer cDNA fragments from SAGE tags constituted the most efficient method of gene identification, which facilitated the analysis of a large number of unknown genes.

Gene dosage, expression, and ontology analysis identifies driver genes in the carcinogenesis and chemoradioresistance of cervical cancer.

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Malin Lando

2009-11-01

Full Text Available Integrative analysis of gene dosage, expression, and ontology (GO data was performed to discover driver genes in the carcinogenesis and chemoradioresistance of cervical cancers. Gene dosage and expression profiles of 102 locally advanced cervical cancers were generated by microarray techniques. Fifty-two of these patients were also analyzed with the Illumina expression method to confirm the gene expression results. An independent cohort of 41 patients was used for validation of gene expressions associated with clinical outcome. Statistical analysis identified 29 recurrent gains and losses and 3 losses (on 3p, 13q, 21q associated with poor outcome after chemoradiotherapy. The intratumor heterogeneity, assessed from the gene dosage profiles, was low for these alterations, showing that they had emerged prior to many other alterations and probably were early events in carcinogenesis. Integration of the alterations with gene expression and GO data identified genes that were regulated by the alterations and revealed five biological processes that were significantly overrepresented among the affected genes: apoptosis, metabolism, macromolecule localization, translation, and transcription. Four genes on 3p (RYBP, GBE1 and 13q (FAM48A, MED4 correlated with outcome at both the gene dosage and expression level and were satisfactorily validated in the independent cohort. These integrated analyses yielded 57 candidate drivers of 24 genetic events, including novel loci responsible for chemoradioresistance. Further mapping of the connections among genetic events, drivers, and biological processes suggested that each individual event stimulates specific processes in carcinogenesis through the coordinated control of multiple genes. The present results may provide novel therapeutic opportunities of both early and advanced stage cervical cancers.

Identification of a set of genes showing regionally enriched expression in the mouse brain

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Marra Marco A

2008-07-01

Full Text Available Abstract Background The Pleiades Promoter Project aims to improve gene therapy by designing human mini-promoters ( Results We have utilized LongSAGE to identify regionally enriched transcripts in the adult mouse brain. As supplemental strategies, we also performed a meta-analysis of published literature and inspected the Allen Brain Atlas in situ hybridization data. From a set of approximately 30,000 mouse genes, 237 were identified as showing specific or enriched expression in 30 target regions of the mouse brain. GO term over-representation among these genes revealed co-involvement in various aspects of central nervous system development and physiology. Conclusion Using a multi-faceted expression validation approach, we have identified mouse genes whose human orthologs are good candidates for design of mini-promoters. These mouse genes represent molecular markers in several discrete brain regions/cell-types, which could potentially provide a mechanistic explanation of unique functions performed by each region. This set of markers may also serve as a resource for further studies of gene regulatory elements influencing brain expression.

EXP-PAC: providing comparative analysis and storage of next generation gene expression data.

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Church, Philip C; Goscinski, Andrzej; Lefèvre, Christophe

2012-07-01

Microarrays and more recently RNA sequencing has led to an increase in available gene expression data. How to manage and store this data is becoming a key issue. In response we have developed EXP-PAC, a web based software package for storage, management and analysis of gene expression and sequence data. Unique to this package is SQL based querying of gene expression data sets, distributed normalization of raw gene expression data and analysis of gene expression data across experiments and species. This package has been populated with lactation data in the international milk genomic consortium web portal (http://milkgenomics.org/). Source code is also available which can be hosted on a Windows, Linux or Mac APACHE server connected to a private or public network (http://mamsap.it.deakin.edu.au/~pcc/Release/EXP_PAC.html). Copyright © 2012 Elsevier Inc. All rights reserved.

Gene expression analysis of FABP4 in gastric cancer

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Abdulkarim Yasin Karim

2016-06-01

Full Text Available Purpose: Gastric cancer has high incidence and mortality rate in several countries and is still one of the most frequent and lethal disease. In this study, we aimed to determine diagnostic markers in gastric cancer by molecular techniques; include mRNA expression analysis of FABP4 gene. Fatty acid binding protein 4 (FABP4 gene encodes the fatty acid binding protein found in adipocytes. The protein encoded by FABP4 are a family of small, highly conserved, cytoplasmic proteins that bind long-chain fatty acids and other hydrophobic ligands. It is thought that FABPs roles include fatty acid uptake, transport, and metabolism. Material and Methods: Total RNA were extracted from paired tumor and normal tissues of 47 gastric cancer. The mRNA expression level of FABP4 was measured employing semi- quantitative reverse transcription- polymerase chain reaction (RT- PCR. Results: The mRNA expression level of FABP4 was significantly decreased (down- regulated. Conclusion: Down-regulation of FABP4 gene seems to occur at the initial steps of gastric cancer development. In order to confirm the relationship between the gastric tumor and FABP4 gene, further analysis like immunohistochemistry and epigenetc techniques are necessary. [Cukurova Med J 2016; 41(2.000: 248-252

MetaComp: comprehensive analysis software for comparative meta-omics including comparative metagenomics.

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Zhai, Peng; Yang, Longshu; Guo, Xiao; Wang, Zhe; Guo, Jiangtao; Wang, Xiaoqi; Zhu, Huaiqiu

2017-10-02

During the past decade, the development of high throughput nucleic sequencing and mass spectrometry analysis techniques have enabled the characterization of microbial communities through metagenomics, metatranscriptomics, metaproteomics and metabolomics data. To reveal the diversity of microbial communities and interactions between living conditions and microbes, it is necessary to introduce comparative analysis based upon integration of all four types of data mentioned above. Comparative meta-omics, especially comparative metageomics, has been established as a routine process to highlight the significant differences in taxon composition and functional gene abundance among microbiota samples. Meanwhile, biologists are increasingly concerning about the correlations between meta-omics features and environmental factors, which may further decipher the adaptation strategy of a microbial community. We developed a graphical comprehensive analysis software named MetaComp comprising a series of statistical analysis approaches with visualized results for metagenomics and other meta-omics data comparison. This software is capable to read files generated by a variety of upstream programs. After data loading, analyses such as multivariate statistics, hypothesis testing of two-sample, multi-sample as well as two-group sample and a novel function-regression analysis of environmental factors are offered. Here, regression analysis regards meta-omic features as independent variable and environmental factors as dependent variables. Moreover, MetaComp is capable to automatically choose an appropriate two-group sample test based upon the traits of input abundance profiles. We further evaluate the performance of its choice, and exhibit applications for metagenomics, metaproteomics and metabolomics samples. MetaComp, an integrative software capable for applying to all meta-omics data, originally distills the influence of living environment on microbial community by regression analysis

Cartilage-selective genes identified in genome-scale analysis of non-cartilage and cartilage gene expression

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Cohn Zachary A

2007-06-01

Full Text Available Abstract Background Cartilage plays a fundamental role in the development of the human skeleton. Early in embryogenesis, mesenchymal cells condense and differentiate into chondrocytes to shape the early skeleton. Subsequently, the cartilage anlagen differentiate to form the growth plates, which are responsible for linear bone growth, and the articular chondrocytes, which facilitate joint function. However, despite the multiplicity of roles of cartilage during human fetal life, surprisingly little is known about its transcriptome. To address this, a whole genome microarray expression profile was generated using RNA isolated from 18–22 week human distal femur fetal cartilage and compared with a database of control normal human tissues aggregated at UCLA, termed Celsius. Results 161 cartilage-selective genes were identified, defined as genes significantly expressed in cartilage with low expression and little variation across a panel of 34 non-cartilage tissues. Among these 161 genes were cartilage-specific genes such as cartilage collagen genes and 25 genes which have been associated with skeletal phenotypes in humans and/or mice. Many of the other cartilage-selective genes do not have established roles in cartilage or are novel, unannotated genes. Quantitative RT-PCR confirmed the unique pattern of gene expression observed by microarray analysis. Conclusion Defining the gene expression pattern for cartilage has identified new genes that may contribute to human skeletogenesis as well as provided further candidate genes for skeletal dysplasias. The data suggest that fetal cartilage is a complex and transcriptionally active tissue and demonstrate that the set of genes selectively expressed in the tissue has been greatly underestimated.

Comparative analysis of clustering methods for gene expression time course data

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Ivan G. Costa

2004-01-01

Full Text Available This work performs a data driven comparative study of clustering methods used in the analysis of gene expression time courses (or time series. Five clustering methods found in the literature of gene expression analysis are compared: agglomerative hierarchical clustering, CLICK, dynamical clustering, k-means and self-organizing maps. In order to evaluate the methods, a k-fold cross-validation procedure adapted to unsupervised methods is applied. The accuracy of the results is assessed by the comparison of the partitions obtained in these experiments with gene annotation, such as protein function and series classification.

Association between vitamin D receptor gene polymorphisms and breast cancer risk: a meta-analysis of 39 studies.

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Kai Zhang

Full Text Available BACKGROUND: The associations between vitamin D receptor (VDR gene polymorphisms and breast cancer risk were comprehensively investigated to clarify issues that remain controversial. METHODOLOGY/PRINCIPAL FINDINGS: An electronic search was conducted of several databases, including PubMed, the Cochrane library, Web of Science, EMBASE, CBM and CNKI, for papers that describe the association between Fok1, poly-A repeat, Bsm1, Taq1 or Apa1 polymorphisms of the VDR gene and breast cancer risk. Summary odds ratios and 95% confidence intervals (CI were estimated based on a fixed-effect model (FEM or random-effect model (REM, depending on the absence or presence of significant heterogeneity. A total of 39 studies met the inclusion criteria. A meta-analysis of high-quality studies showed that the Fok1 polymorphism of the VDR gene was associated with an increased risk of breast cancer (ff vs. Ff+FF, OR: 1.09, 95%CI: 1.02 to 1.16, p = 0.007. No significant associations were observed between the other polymorphisms and breast cancer risk. No positive results were detected by pooling the results of all relevant studies. CONCLUSION: A meta-analysis of high-quality studies demonstrated that the Fok1 polymorphism of the VDR gene was closely associated with breast cancer risk.

Glutathione S-transferase P1, gene-gene interaction, and lung cancer susceptibility in the Chinese population: An updated meta-analysis and review

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Xue-Ming Li

2015-01-01

Full Text Available Aim of Study: To assess the impact of glutathione S-transferase P1 (GSTP1 Ile105Val polymorphism on the risk of lung cancer in the Chinese population, an updated meta-analysis and review was performed. Materials and Methods: Relevant studies were identified from PubMed, Springer Link, Ovid, Chinese Wanfang Data Knowledge Service Platform, Chinese National Knowledge Infrastructure, and Chinese Biology Medicine published through January 22, 2015. The odds ratios (ORs and 95% confidence intervals (CIs were calculated to estimate the strength of the associations. Results: A total of 13 case-control studies, including 2026 lung cancer cases and 2451 controls, were included in this meta-analysis. Overall, significantly increased lung cancer risk was associated with the variant genotypes of GSTP1 polymorphism in the Chinese population (GG vs. AA: OR = 1.36, 95% CI = 1.01-1.84. In subgroup analyses stratified by geographic area and source of controls, the significant results were found in population-based studies (GG vs. AA: OR = 1.62, 95% CI: 1.13-2.31; GG vs. AG: OR = 1.49, 95% CI: 1.03-2.16; GG vs. AA + AG: OR = 1.55, 95% CI: 1.12-2.26. A gene-gene interaction analysis showed that there was an interaction for individuals with combination of GSTM1 (or GSTT1 null genotype and GSTP1 (AG + GG mutant genotype for lung cancer risk in Chinese. Conclusion: This meta-analysis suggests that GSTP1 Ile105Val polymorphism may increase the risk of lung cancer in the Chinese population.

Digital gene expression analysis of Microsporum canis exposed to berberine chloride.

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Chen-Wen Xiao

Full Text Available Berberine, a natural isoquinoline alkaloid of many medicinal herbs, has an active function against a variety of microbial infections including Microsporum canis (M. canis. However, the underlying mechanisms are poorly understood. To study the effect of berberine chloride on M. canis infection, a Digital Gene Expression (DGE tag profiling was constructed and a transcriptome analysis of the M. canis cellular responses upon berberine treatment was performed. Illumina/Hisseq sequencing technique was used to generate the data of gene expression profile, and the following enrichment analysis of Gene Ontology (GO and Pathway function were conducted based on the data of transcriptome. The results of DGE showed that there were 8476945, 14256722, 7708575, 5669955, 6565513 and 9303468 tags respectively, which was obtained from M. canis incubated with berberine or control DMSO. 8,783 genes were totally mapped, and 1,890 genes have shown significant changes between the two groups. 1,030 genes were up-regulated and 860 genes were down-regulated (P<0.05 in berberine treated group compared to the control group. Besides, twenty-three GO terms were identified by Gene Ontology functional enrichment analysis, such as calcium-transporting ATPase activity, 2-oxoglutarate metabolic process, valine catabolic process, peroxisome and unfolded protein binding. Pathway significant enrichment analysis indicated 6 signaling pathways that are significant, including steroid biosynthesis, steroid hormone biosynthesis, Parkinson's disease, 2,4-Dichlorobenzoate degradation, and tropane, piperidine and Isoquinoline alkaloid biosynthesis. Among these, eleven selected genes were further verified by qRT-PCR. Our findings provide a comprehensive view on the gene expression profile of M. canis upon berberine treatment, and shed light on its complicated effects on M. canis.

Association of vitamin D receptor BsmI gene polymorphism with risk of tuberculosis: a meta-analysis of 15 studies.

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Yu-Jiao Wu

Full Text Available BACKGROUND: Genetic variations in vitamin D receptor (VDR may contribute to tuberculosis (TB risk. Many studies have investigated the association between VDR BsmI gene polymorphism and TB risk, but yielded inconclusive results. METHODOLOGY/PRINCIPAL FINDINGS: We performed a comprehensive meta-analysis of 15 publications with a total of 2309 cases and 3568 controls. We assessed the strength of the association between VDR BsmI gene polymorphism and TB risk and performed sub-group analyses by ethnicity, sample size and Hardy-Weinberg equilibrium (HWE. We found a statistically significant correlation between VDR BsmI gene polymorphism and decreased TB risk in four comparison models: allele model (b vs. B: OR = 0.78, 95% CI = 0.67, 0.89; Pheterogeneity = 0.004, homozygote model (bb vs. BB: OR = 0.61, 95% CI = 0.43, 0.87; Pheterogeneity = 0.001, recessive model (bb vs. Bb+BB: OR = 0.70, 95% CI = 0.56, 0.88; Pheterogeneity = 0.005 and dominant model (bb+Bb vs. BB: OR = 0.77, 95% CI = 0.61, 0.97; Pheterogeneity = 0.010, especially in studies based on Asian population. Sub-group analyses also revealed that there was a statistically decreased TB risk in "small" studies (0.5. Meta-regression and stratification analysis both showed that the ethnicity and sample size contributed to heterogeneity. CONCLUSIONS: This meta-analysis suggests that VDR BsmI gene polymorphism is associated with a significant decreased TB risk, especially in Asian population.

Serial analysis of gene expression (SAGE) in normal human trabecular meshwork.

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Liu, Yutao; Munro, Drew; Layfield, David; Dellinger, Andrew; Walter, Jeffrey; Peterson, Katherine; Rickman, Catherine Bowes; Allingham, R Rand; Hauser, Michael A

2011-04-08

To identify the genes expressed in normal human trabecular meshwork tissue, a tissue critical to the pathogenesis of glaucoma. Total RNA was extracted from human trabecular meshwork (HTM) harvested from 3 different donors. Extracted RNA was used to synthesize individual SAGE (serial analysis of gene expression) libraries using the I-SAGE Long kit from Invitrogen. Libraries were analyzed using SAGE 2000 software to extract the 17 base pair sequence tags. The extracted sequence tags were mapped to the genome using SAGE Genie map. A total of 298,834 SAGE tags were identified from all HTM libraries (96,842, 88,126, and 113,866 tags, respectively). Collectively, there were 107,325 unique tags. There were 10,329 unique tags with a minimum of 2 counts from a single library. These tags were mapped to known unique Unigene clusters. Approximately 29% of the tags (orphan tags) did not map to a known Unigene cluster. Thirteen percent of the tags mapped to at least 2 Unigene clusters. Sequence tags from many glaucoma-related genes, including myocilin, optineurin, and WD repeat domain 36, were identified. This is the first time SAGE analysis has been used to characterize the gene expression profile in normal HTM. SAGE analysis provides an unbiased sampling of gene expression of the target tissue. These data will provide new and valuable information to improve understanding of the biology of human aqueous outflow.

Selection of reference genes for expression analysis in the entomophthoralean fungus Pandora neoaphidis.

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Chen, Chun; Xie, Tingna; Ye, Sudan; Jensen, Annette Bruun; Eilenberg, Jørgen

2016-01-01

The selection of suitable reference genes is crucial for accurate quantification of gene expression and can add to our understanding of host-pathogen interactions. To identify suitable reference genes in Pandora neoaphidis, an obligate aphid pathogenic fungus, the expression of three traditional candidate genes including 18S rRNA(18S), 28S rRNA(28S) and elongation factor 1 alpha-like protein (EF1), were measured by quantitative polymerase chain reaction at different developmental stages (conidia, conidia with germ tubes, short hyphae and elongated hyphae), and under different nutritional conditions. We calculated the expression stability of candidate reference genes using four algorithms including geNorm, NormFinder, BestKeeper and Delta Ct. The analysis results revealed that the comprehensive ranking of candidate reference genes from the most stable to the least stable was 18S (1.189), 28S (1.414) and EF1 (3). The 18S was, therefore, the most suitable reference gene for real-time RT-PCR analysis of gene expression under all conditions. These results will support further studies on gene expression in P. neoaphidis. Copyright © 2015 Sociedade Brasileira de Microbiologia. Published by Elsevier Editora Ltda. All rights reserved.

Selection of reference genes for expression analysis in the entomophthoralean fungus Pandora neoaphidis

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Chun Chen

2016-03-01

Full Text Available Abstract The selection of suitable reference genes is crucial for accurate quantification of gene expression and can add to our understanding of host–pathogen interactions. To identify suitable reference genes in Pandora neoaphidis, an obligate aphid pathogenic fungus, the expression of three traditional candidate genes including 18S rRNA(18S, 28S rRNA(28S and elongation factor 1 alpha-like protein (EF1, were measured by quantitative polymerase chain reaction at different developmental stages (conidia, conidia with germ tubes, short hyphae and elongated hyphae, and under different nutritional conditions. We calculated the expression stability of candidate reference genes using four algorithms including geNorm, NormFinder, BestKeeper and Delta Ct. The analysis results revealed that the comprehensive ranking of candidate reference genes from the most stable to the least stable was 18S (1.189, 28S (1.414 and EF1 (3. The 18S was, therefore, the most suitable reference gene for real-time RT-PCR analysis of gene expression under all conditions. These results will support further studies on gene expression in P. neoaphidis.

Global Analysis of miRNA Gene Clusters and Gene Families Reveals Dynamic and Coordinated Expression

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Li Guo

2014-01-01

Full Text Available To further understand the potential expression relationships of miRNAs in miRNA gene clusters and gene families, a global analysis was performed in 4 paired tumor (breast cancer and adjacent normal tissue samples using deep sequencing datasets. The compositions of miRNA gene clusters and families are not random, and clustered and homologous miRNAs may have close relationships with overlapped miRNA species. Members in the miRNA group always had various expression levels, and even some showed larger expression divergence. Despite the dynamic expression as well as individual difference, these miRNAs always indicated consistent or similar deregulation patterns. The consistent deregulation expression may contribute to dynamic and coordinated interaction between different miRNAs in regulatory network. Further, we found that those clustered or homologous miRNAs that were also identified as sense and antisense miRNAs showed larger expression divergence. miRNA gene clusters and families indicated important biological roles, and the specific distribution and expression further enrich and ensure the flexible and robust regulatory network.

Interaction between early-life stress and FKBP5 gene variants in major depressive disorder and post-traumatic stress disorder: A systematic review and meta-analysis.

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Wang, Qingzhong; Shelton, Richard C; Dwivedi, Yogesh

2018-01-01

Gene-environment interaction contributes to the risks of psychiatric disorders. Interactions between FKBP5 gene variants and early-life stress may enhance the risk not only for mood disorder, but also for a number of other behavioral phenotypes. The aim of the present study was to review and conduct a meta-analysis on the results from published studies examining interaction between FKBP5 gene variants and early-life stress and their associations with stress-related disorders such as major depression and PTSD. A literature search was conducted using PsychINFO and PubMed databases until May 2017. A total of 14 studies with a pooled total of 15109 participants met the inclusion criteria, the results of which were combined and a meta-analysis was performed using the differences in correlations as the effect measure. Based on literature, rs1360780, rs3800373, and rs9470080 SNPs were selected within the FKBP5 gene and systematic review was conducted. Based on the Comprehensive Meta-Analysis software, no publication bias was detected. Sensitivity analysis and credibility of meta-analysis results also indicated that the analyses were stable. The meta-analysis showed that individuals who carry T allele of rs1360780, C-allele of rs3800373 or T-allele of rs9470080 exposed to early-life trauma had higher risks for depression or PTSD. The effects of ethnicity, age, sex, and different stress measures were not examined due to limited sample size. These results provide strong evidence of interactions between FKBP5 genotypes and early-life stress, which could pose a significant risk factor for stress-associated disorders such as major depression and PTSD. Copyright © 2017 Elsevier B.V. All rights reserved.

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

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Kouji Satoh

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

Identification and expression analysis of genes associated with bovine blastocyst formation

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Van Zeveren Alex

2007-06-01

Full Text Available Abstract Background Normal preimplantation embryo development encompasses a series of events including first cleavage division, activation of the embryonic genome, compaction and blastocyst formation. First lineage differentiation starts at the blastocyst stage with the formation of the trophectoderm and the inner cell mass. The main objective of this study was the detection, identification and expression analysis of genes associated with blastocyst formation in order to help us better understand this process. This information could lead to improvements of in vitro embryo production procedures. Results A subtractive cDNA library was constructed enriched for transcripts preferentially expressed at the blastocyst stage compared to the 2-cell and 8-cell stage. Sequence information was obtained for 65 randomly selected clones. The RNA expression levels of 12 candidate genes were determined throughout 3 stages of preimplantation embryo development (2-cell, 8-cell and blastocyst and compared with the RNA expression levels of in vivo "golden standard" embryos using real-time PCR. The RNA expression profiles of 9 (75% transcripts (KRT18, FN1, MYL6, ATP1B3, FTH1, HINT1, SLC25A5, ATP6V0B, RPL10 were in agreement with the subtractive cDNA cloning approach, whereas for the remaining 3 (25% (ACTN1, COPE, EEF1A1 the RNA expression level was equal or even higher at the earlier developmental stages compared to the blastocyst stage. Moreover, significant differences in RNA expression levels were observed between in vitro and in vivo produced embryos. By immunofluorescent labelling, the protein expression of KRT18, FN1 and MYL6 was determined throughout bovine preimplantation embryo development and showed the same pattern as the RNA expression analyses. Conclusion By subtractive cDNA cloning, candidate genes involved in blastocyst formation were identified. For several candidate genes, important differences in gene expression were observed between in vivo and in

Suitable Reference Genes for Accurate Gene Expression Analysis in Parsley (Petroselinum crispum) for Abiotic Stresses and Hormone Stimuli.

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Li, Meng-Yao; Song, Xiong; Wang, Feng; Xiong, Ai-Sheng

2016-01-01

Parsley, one of the most important vegetables in the Apiaceae family, is widely used in the food, medicinal, and cosmetic industries. Recent studies on parsley mainly focus on its chemical composition, and further research involving the analysis of the plant's gene functions and expressions is required. qPCR is a powerful method for detecting very low quantities of target transcript levels and is widely used to study gene expression. To ensure the accuracy of results, a suitable reference gene is necessary for expression normalization. In this study, four software, namely geNorm, NormFinder, BestKeeper, and RefFinder were used to evaluate the expression stabilities of eight candidate reference genes of parsley ( GAPDH, ACTIN, eIF-4 α, SAND, UBC, TIP41, EF-1 α, and TUB ) under various conditions, including abiotic stresses (heat, cold, salt, and drought) and hormone stimuli treatments (GA, SA, MeJA, and ABA). Results showed that EF-1 α and TUB were the most stable genes for abiotic stresses, whereas EF-1 α, GAPDH , and TUB were the top three choices for hormone stimuli treatments. Moreover, EF-1 α and TUB were the most stable reference genes among all tested samples, and UBC was the least stable one. Expression analysis of PcDREB1 and PcDREB2 further verified that the selected stable reference genes were suitable for gene expression normalization. This study can guide the selection of suitable reference genes in gene expression in parsley.

Suitable reference genes for accurate gene expression analysis in parsley (Petroselinum crispum for abiotic stresses and hormone stimuli

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Meng-Yao Li

2016-09-01

Full Text Available Parsley is one of the most important vegetable in Apiaceae family and widely used in food industry, medicinal and cosmetic. The recent studies in parsley are mainly focus on chemical composition, further research involving the analysis of the gene functions and expressions will be required. qPCR is a powerful method for detecting very low quantities of target transcript levels and widely used for gene expression studies. To ensure the accuracy of results, a suitable reference gene is necessary for expression normalization. In this study, three software geNorm, NormFinder, and BestKeeper were used to evaluate the expression stabilities of eight candidate reference genes (GAPDH, ACTIN, eIF-4α, SAND, UBC, TIP41, EF-1α, and TUB under various conditions including abiotic stresses (heat, cold, salt, and drought and hormone stimuli treatments (GA, SA, MeJA, and ABA. The results showed that EF-1α and TUB were identified as the most stable genes for abiotic stresses, while EF-1α, GAPDH, and TUB were the top three choices for hormone stimuli treatments. Moreover, EF-1α and TUB were the most stable reference genes across all the tested samples, while UBC was the least stable one. The expression analysis of PcDREB1 and PcDREB2 further verified that the selected stable reference genes were suitable for gene expression normalization. This study provides a guideline for selection the suitable reference genes in gene expression in parsley.

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

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Elvezia Maria Paraboschi

2015-09-01

Full Text Available 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.

The utility of optical detection system (qPCR) and bioinformatics methods in reference gene expression analysis

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Skarzyńska, Agnieszka; Pawełkowicz, Magdalena; PlÄ der, Wojciech; Przybecki, Zbigniew

2016-09-01

Real-time quantitative polymerase chain reaction is consider as the most reliable method for gene expression studies. However, the expression of target gene could be misinterpreted due to improper normalization. Therefore, the crucial step for analysing of qPCR data is selection of suitable reference genes, which should be validated experimentally. In order to choice the gene with stable expression in the designed experiment, we performed reference gene expression analysis. In this study genes described in the literature and novel genes predicted as control genes, based on the in silico analysis of transcriptome data were used. Analysis with geNorm and NormFinder algorithms allow to create the ranking of candidate genes and indicate the best reference for flower morphogenesis study. According to the results, genes CACS and CYCL were characterised the most stable expression, but the least suitable genes were TUA and EF.

Complex nature of SNP genotype effects on gene expression in primary human leucocytes

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Dinesen Lotte C

2009-01-01

Full Text Available Abstract Background Genome wide association studies have been hugely successful in identifying disease risk variants, yet most variants do not lead to coding changes and how variants influence biological function is usually unknown. Methods We correlated gene expression and genetic variation in untouched primary leucocytes (n = 110 from individuals with celiac disease – a common condition with multiple risk variants identified. We compared our observations with an EBV-transformed HapMap B cell line dataset (n = 90, and performed a meta-analysis to increase power to detect non-tissue specific effects. Results In celiac peripheral blood, 2,315 SNP variants influenced gene expression at 765 different transcripts (cis expression quantitative trait loci, eQTLs. 135 of the detected SNP-probe effects (reflecting 51 unique probes were also detected in a HapMap B cell line published dataset, all with effects in the same allelic direction. Overall gene expression differences within the two datasets predominantly explain the limited overlap in observed cis-eQTLs. Celiac associated risk variants from two regions, containing genes IL18RAP and CCR3, showed significant cis genotype-expression correlations in the peripheral blood but not in the B cell line datasets. We identified 14 genes where a SNP affected the expression of different probes within the same gene, but in opposite allelic directions. By incorporating genetic variation in co-expression analyses, functional relationships between genes can be more significantly detected. Conclusion In conclusion, the complex nature of genotypic effects in human populations makes the use of a relevant tissue, large datasets, and analysis of different exons essential to enable the identification of the function for many genetic risk variants in common diseases.

Clinical Omics Analysis of Colorectal Cancer Incorporating Copy Number Aberrations and Gene Expression Data

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Tsuyoshi Yoshida

2010-07-01

Full Text Available Background: Colorectal cancer (CRC is one of the most frequently occurring cancers in Japan, and thus a wide range of methods have been deployed to study the molecular mechanisms of CRC. In this study, we performed a comprehensive analysis of CRC, incorporating copy number aberration (CRC and gene expression data. For the last four years, we have been collecting data from CRC cases and organizing the information as an “omics” study by integrating many kinds of analysis into a single comprehensive investigation. In our previous studies, we had experienced difficulty in finding genes related to CRC, as we observed higher noise levels in the expression data than in the data for other cancers. Because chromosomal aberrations are often observed in CRC, here, we have performed a combination of CNA analysis and expression analysis in order to identify some new genes responsible for CRC. This study was performed as part of the Clinical Omics Database Project at Tokyo Medical and Dental University. The purpose of this study was to investigate the mechanism of genetic instability in CRC by this combination of expression analysis and CNA, and to establish a new method for the diagnosis and treatment of CRC. Materials and methods: Comprehensive gene expression analysis was performed on 79 CRC cases using an Affymetrix Gene Chip, and comprehensive CNA analysis was performed using an Affymetrix DNA Sty array. To avoid the contamination of cancer tissue with normal cells, laser micro-dissection was performed before DNA/RNA extraction. Data analysis was performed using original software written in the R language. Result: We observed a high percentage of CNA in colorectal cancer, including copy number gains at 7, 8q, 13 and 20q, and copy number losses at 8p, 17p and 18. Gene expression analysis provided many candidates for CRC-related genes, but their association with CRC did not reach the level of statistical significance. The combination of CNA and gene

Allen Brain Atlas-Driven Visualizations: a web-based gene expression energy visualization tool.

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Zaldivar, Andrew; Krichmar, Jeffrey L

2014-01-01

The Allen Brain Atlas-Driven Visualizations (ABADV) is a publicly accessible web-based tool created to retrieve and visualize expression energy data from the Allen Brain Atlas (ABA) across multiple genes and brain structures. Though the ABA offers their own search engine and software for researchers to view their growing collection of online public data sets, including extensive gene expression and neuroanatomical data from human and mouse brain, many of their tools limit the amount of genes and brain structures researchers can view at once. To complement their work, ABADV generates multiple pie charts, bar charts and heat maps of expression energy values for any given set of genes and brain structures. Such a suite of free and easy-to-understand visualizations allows for easy comparison of gene expression across multiple brain areas. In addition, each visualization links back to the ABA so researchers may view a summary of the experimental detail. ABADV is currently supported on modern web browsers and is compatible with expression energy data from the Allen Mouse Brain Atlas in situ hybridization data. By creating this web application, researchers can immediately obtain and survey numerous amounts of expression energy data from the ABA, which they can then use to supplement their work or perform meta-analysis. In the future, we hope to enable ABADV across multiple data resources.

Allen Brain Atlas-Driven Visualizations: A Web-Based Gene Expression Energy Visualization Tool

Directory of Open Access Journals (Sweden)

Andrew eZaldivar

2014-05-01

Full Text Available The Allen Brain Atlas-Driven Visualizations (ABADV is a publicly accessible web-based tool created to retrieve and visualize expression energy data from the Allen Brain Atlas (ABA across multiple genes and brain structures. Though the ABA offers their own search engine and software for researchers to view their growing collection of online public data sets, including extensive gene expression and neuroanatomical data from human and mouse brain, many of their tools limit the amount of genes and brain structures researchers can view at once. To complement their work, ABADV generates multiple pie charts, bar charts and heat maps of expression energy values for any given set of genes and brain structures. Such a suite of free and easy-to-understand visualizations allows for easy comparison of gene expression across multiple brain areas. In addition, each visualization links back to the ABA so researchers may view a summary of the experimental detail. ABADV is currently supported on modern web browsers and is compatible with expression energy data from the Allen Mouse Brain Atlas in situ hybridization data. By creating this web application, researchers can immediately obtain and survey numerous amounts of expression energy data from the ABA, which they can then use to supplement their work or perform meta-analysis. In the future, we hope to enable ABADV across multiple data resources.

Pattern Recognition of Gene Expression with Singular Spectrum Analysis

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Hossein Hassani

2014-07-01

Full Text Available Drosophila segmentation as a model organism is one of the most highly studied. Among many maternal segmentation coordinate genes, bicoid protein pattern plays a significant role during Drosophila embryogenesis, since this gradient determines most aspects of head and thorax development. Despite the fact that several models have been proposed to describe the bicoid gradient, due to its association with considerable error, each can only partially explain bicoid characteristics. In this paper, a modified version of singular spectrum analysis is examined for filtering and extracting the bicoid gene expression signal. The results with strong evidence indicate that the proposed technique is able to remove noise more effectively and can be considered as a promising method for filtering gene expression measurements for other applications.

Molecular Characterization and Expression Analysis of Equine ( Gene in Horse (

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Ki-Duk Song

2014-05-01

Full Text Available The objective of this study was to determine the molecular characteristics of the horse vascular endothelial growth factor alpha gene (VEGFα by constructing a phylogenetic tree, and to investigate gene expression profiles in tissues and blood leukocytes after exercise for development of suitable biomarkers. Using published amino acid sequences of other vertebrate species (human, chimpanzee, mouse, rat, cow, pig, chicken and dog, we constructed a phylogenetic tree which showed that equine VEGFα belonged to the same clade of the pig VEGFα. Analysis for synonymous (Ks and non-synonymous substitution ratios (Ka revealed that the horse VEGFα underwent positive selection. RNA was extracted from blood samples before and after exercise and different tissue samples of three horses. Expression analyses using reverse transcription-polymerase chain reaction (RT-PCR and quantitative-polymerase chain reaction (qPCR showed ubiquitous expression of VEGFα mRNA in skeletal muscle, kidney, thyroid, lung, appendix, colon, spinal cord, and heart tissues. Analysis of differential expression of VEGFα gene in blood leukocytes after exercise indicated a unimodal pattern. These results will be useful in developing biomarkers that can predict the recovery capacity of racing horses.

Analysis of Gene Expression Variance in Schizophrenia Using Structural Equation Modeling

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Anna A. Igolkina

2018-06-01

Full Text Available Schizophrenia (SCZ is a psychiatric disorder of unknown etiology. There is evidence suggesting that aberrations in neurodevelopment are a significant attribute of schizophrenia pathogenesis and progression. To identify biologically relevant molecular abnormalities affecting neurodevelopment in SCZ we used cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells. Here, we tested the hypothesis that variance in gene expression differs between individuals from SCZ and control groups. In CNON cells, variance in gene expression was significantly higher in SCZ samples in comparison with control samples. Variance in gene expression was enriched in five molecular pathways: serine biosynthesis, PI3K-Akt, MAPK, neurotrophin and focal adhesion. More than 14% of variance in disease status was explained within the logistic regression model (C-value = 0.70 by predictors accounting for gene expression in 69 genes from these five pathways. Structural equation modeling (SEM was applied to explore how the structure of these five pathways was altered between SCZ patients and controls. Four out of five pathways showed differences in the estimated relationships among genes: between KRAS and NF1, and KRAS and SOS1 in the MAPK pathway; between PSPH and SHMT2 in serine biosynthesis; between AKT3 and TSC2 in the PI3K-Akt signaling pathway; and between CRK and RAPGEF1 in the focal adhesion pathway. Our analysis provides evidence that variance in gene expression is an important characteristic of SCZ, and SEM is a promising method for uncovering altered relationships between specific genes thus suggesting affected gene regulation associated with the disease. We identified altered gene-gene interactions in pathways enriched for genes with increased variance in expression in SCZ. These pathways and loci were previously implicated in SCZ, providing further support for the hypothesis that gene expression variance plays important role in the etiology

dictyExpress: a Dictyostelium discoideum gene expression database with an explorative data analysis web-based interface

Science.gov (United States)

Rot, Gregor; Parikh, Anup; Curk, Tomaz; Kuspa, Adam; Shaulsky, Gad; Zupan, Blaz

2009-01-01

Background Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability. Results We have developed dictyExpress, a web application that features a graphical, highly interactive explorative interface to our database that consists of more than 1000 Dictyostelium discoideum gene expression experiments. In dictyExpress, the user can select experiments and genes, perform gene clustering, view gene expression profiles across time, view gene co-expression networks, perform analyses of Gene Ontology term enrichment, and simultaneously display expression profiles for a selected gene in various experiments. Most importantly, these tasks are achieved through web applications whose components are seamlessly interlinked and immediately respond to events triggered by the user, thus providing a powerful explorative data analysis environment. Conclusion dictyExpress is a precursor for a new generation of web-based bioinformatics applications with simple but powerful interactive interfaces that resemble that of the modern desktop. While dictyExpress serves mainly the Dictyostelium research community, it is relatively easy to adapt it to other datasets. We propose that the design ideas behind dictyExpress will influence the development of similar applications for other model organisms. PMID:19706156

Prognostic value of FGFR gene amplification in patients with different types of cancer: a systematic review and meta-analysis.

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Jinjia Chang

Full Text Available BACKGROUND: Fibroblast growth factor receptor (FGFR gene amplification has been reported in different types of cancer. We performed an up-to-date meta-analysis to further characterize the prognostic value of FGFR gene amplification in patients with cancer. METHODS: A search of several databases, including MEDLINE (PubMed, EMBASE, Web of Science, and China National Knowledge Infrastructure, was conducted to identify studies examining the association between FGFR gene amplification and cancer. A total of 24 studies met the inclusion criteria, and overall incidence rates, hazard risk (HR, overall survival, disease-free survival, and 95% confidence intervals (CIs were calculated employing fixed- or random-effects models depending on the heterogeneity of the included studies. RESULTS: In the meta-analysis of 24 studies, the prevalence of FGFR gene amplification was FGFR1: 0.11 (95% CI: 0.08-0.13 and FGFR2: 0.04 (95% CI: 0.02-0.06. Overall survival was significantly worse among patients with FGFR gene amplification: FGFR1 [HR 1.57 (95% CI: 1.23-1.99; p = 0.0002] and FGFR2 [HR 2.27 (95% CI: 1.73-3.00; p<0.00001]. CONCLUSIONS: Current evidence supports the conclusion that the outcomes of patients with FGFR gene amplified cancers is worse than for those with non-FGFR gene amplified cancers.

Molecular characterization, sequence analysis and tissue expression of a porcine gene – MOSPD2

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Yang Jie

2017-01-01

Full Text Available The full-length cDNA sequence of a porcine gene, MOSPD2, was amplified using the rapid amplification of cDNA ends method based on a pig expressed sequence tag sequence which was highly homologous to the coding sequence of the human MOSPD2 gene. Sequence prediction analysis revealed that the open reading frame of this gene encodes a protein of 491 amino acids that has high homology with the motile sperm domain-containing protein 2 (MOSPD2 of five species: horse (89%, human (90%, chimpanzee (89%, rhesus monkey (89% and mouse (85%; thus, it could be defined as a porcine MOSPD2 gene. This novel porcine gene was assigned GeneID: 100153601. This gene is structured in 15 exons and 14 introns as revealed by computer-assisted analysis. The phylogenetic analysis revealed that the porcine MOSPD2 gene has a closer genetic relationship with the MOSPD2 gene of horse. Tissue expression analysis indicated that the porcine MOSPD2 gene is generally and differentially expressed in the spleen, muscle, skin, kidney, lung, liver, fat and heart. Our experiment is the first to establish the primary foundation for further research on the porcine MOSPD2 gene.

MetaGOmics: A Web-Based Tool for Peptide-Centric Functional and Taxonomic Analysis of Metaproteomics Data.

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Riffle, Michael; May, Damon H; Timmins-Schiffman, Emma; Mikan, Molly P; Jaschob, Daniel; Noble, William Stafford; Nunn, Brook L

2017-12-27

Metaproteomics is the characterization of all proteins being expressed by a community of organisms in a complex biological sample at a single point in time. Applications of metaproteomics range from the comparative analysis of environmental samples (such as ocean water and soil) to microbiome data from multicellular organisms (such as the human gut). Metaproteomics research is often focused on the quantitative functional makeup of the metaproteome and which organisms are making those proteins. That is: What are the functions of the currently expressed proteins? How much of the metaproteome is associated with those functions? And, which microorganisms are expressing the proteins that perform those functions? However, traditional protein-centric functional analysis is greatly complicated by the large size, redundancy, and lack of biological annotations for the protein sequences in the database used to search the data. To help address these issues, we have developed an algorithm and web application (dubbed "MetaGOmics") that automates the quantitative functional (using Gene Ontology) and taxonomic analysis of metaproteomics data and subsequent visualization of the results. MetaGOmics is designed to overcome the shortcomings of traditional proteomics analysis when used with metaproteomics data. It is easy to use, requires minimal input, and fully automates most steps of the analysis-including comparing the functional makeup between samples. MetaGOmics is freely available at https://www.yeastrc.org/metagomics/.

Identification of a gene expression core signature for Duchenne Muscular Dystrophy (DMD) via integrative analysis reveals novel potential compounds for treatment

KAUST Repository

Ichim-Moreno, Norú

2010-05-01

Duchenne muscular dystrophy (DMD) is a recessive X-linked form of muscular dystrophy and one of the most prevalent genetic disorders of childhood. DMD is characterized by rapid progression of muscle degeneration, and ultimately death. Currently, glucocorticoids are the only available treatment for DMD, but they have been shown to result in serious side effects. The purpose of this research was to define a core signature of gene expression related to DMD via integrative analysis of mouse and human datasets. This core signature was subsequently used to screen for novel potential compounds that antagonistically affect the expression of signature genes. With this approach we were able to identify compounds that are 1) already used to treat DMD, 2) currently under investigation for treatment, and 3) so far unknown but promising candidates. Our study highlights the potential of meta-analyses through the combination of datasets to unravel previously unrecognized associations and reveal new relationships. © IEEE.

A Methodology for the Development of RESTful Semantic Web Services for Gene Expression Analysis.

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Gabriela D A Guardia

Full Text Available Gene expression studies are generally performed through multi-step analysis processes, which require the integrated use of a number of analysis tools. In order to facilitate tool/data integration, an increasing number of analysis tools have been developed as or adapted to semantic web services. In recent years, some approaches have been defined for the development and semantic annotation of web services created from legacy software tools, but these approaches still present many limitations. In addition, to the best of our knowledge, no suitable approach has been defined for the functional genomics domain. Therefore, this paper aims at defining an integrated methodology for the implementation of RESTful semantic web services created from gene expression analysis tools and the semantic annotation of such services. We have applied our methodology to the development of a number of services to support the analysis of different types of gene expression data, including microarray and RNASeq. All developed services are publicly available in the Gene Expression Analysis Services (GEAS Repository at http://dcm.ffclrp.usp.br/lssb/geas. Additionally, we have used a number of the developed services to create different integrated analysis scenarios to reproduce parts of two gene expression studies documented in the literature. The first study involves the analysis of one-color microarray data obtained from multiple sclerosis patients and healthy donors. The second study comprises the analysis of RNA-Seq data obtained from melanoma cells to investigate the role of the remodeller BRG1 in the proliferation and morphology of these cells. Our methodology provides concrete guidelines and technical details in order to facilitate the systematic development of semantic web services. Moreover, it encourages the development and reuse of these services for the creation of semantically integrated solutions for gene expression analysis.

A Methodology for the Development of RESTful Semantic Web Services for Gene Expression Analysis.

Science.gov (United States)

Guardia, Gabriela D A; Pires, Luís Ferreira; Vêncio, Ricardo Z N; Malmegrim, Kelen C R; de Farias, Cléver R G

2015-01-01

Gene expression studies are generally performed through multi-step analysis processes, which require the integrated use of a number of analysis tools. In order to facilitate tool/data integration, an increasing number of analysis tools have been developed as or adapted to semantic web services. In recent years, some approaches have been defined for the development and semantic annotation of web services created from legacy software tools, but these approaches still present many limitations. In addition, to the best of our knowledge, no suitable approach has been defined for the functional genomics domain. Therefore, this paper aims at defining an integrated methodology for the implementation of RESTful semantic web services created from gene expression analysis tools and the semantic annotation of such services. We have applied our methodology to the development of a number of services to support the analysis of different types of gene expression data, including microarray and RNASeq. All developed services are publicly available in the Gene Expression Analysis Services (GEAS) Repository at http://dcm.ffclrp.usp.br/lssb/geas. Additionally, we have used a number of the developed services to create different integrated analysis scenarios to reproduce parts of two gene expression studies documented in the literature. The first study involves the analysis of one-color microarray data obtained from multiple sclerosis patients and healthy donors. The second study comprises the analysis of RNA-Seq data obtained from melanoma cells to investigate the role of the remodeller BRG1 in the proliferation and morphology of these cells. Our methodology provides concrete guidelines and technical details in order to facilitate the systematic development of semantic web services. Moreover, it encourages the development and reuse of these services for the creation of semantically integrated solutions for gene expression analysis.

In Vitro Global Gene Expression Analyses Support the Ethnopharmacological Use of Achyranthes aspera

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Pochi R. Subbarayan

2013-01-01

Full Text Available Achyranthes aspera (family Amaranthaceae is known for its anticancer properties. We have systematically validated the in vitro and in vivo anticancer properties of this plant. However, we do not know its mode of action. Global gene expression analyses may help decipher its mode of action. In the absence of identified active molecules, we believe this is the best approach to discover the mode of action of natural products with known medicinal properties. We exposed human pancreatic cancer cell line MiaPaCa-2 (CRL-1420 to 34 μg/mL of LE for 24, 48, and 72 hours. Gene expression analyses were performed using whole human genome microarrays (Agilent Technologies, USA. In our analyses, 82 (54/28 genes passed the quality control parameter, set at FDR ≤ 0.01 and FC of ≥±2. LE predominantly affected pathways of immune response, metabolism, development, gene expression regulation, cell adhesion, cystic fibrosis transmembrane conductance regulation (CFTR, and chemotaxis (MetaCore tool (Thomson Reuters, NY. Disease biomarker enrichment analysis identified LE regulated genes involved in Vasculitis—inflammation of blood vessels. Arthritis and pancreatitis are two of many etiologies for vasculitis. The outcome of disease network analysis supports the medicinal use of A. aspera, viz, to stop bleeding, as a cure for pancreatic cancer, as an antiarthritic medication, and so forth.

Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

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Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia

2015-06-01

To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.

Genetic Polymorphism of Angiotensin-Converting Enzyme and Chronic Obstructive Pulmonary Disease Risk: An Updated Meta-Analysis

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Sang Wook Kang

2016-01-01

Full Text Available The relationship between polymorphism of the angiotensin I converting enzyme (ACE gene and chronic obstructive pulmonary disease (COPD has been examined in many previous studies. However, their results were controversial. Therefore, we performed a meta-analysis to evaluate the relationship between the ACE gene and the risk of COPD. Fourteen case-control studies were included in this meta-analysis. The pooled p value, odds ratio (OR, and 95% confidence interval (95% CI were used to investigate the strength of the association. The meta-analysis was performed using comprehensive meta-analysis software. Our meta-analysis results revealed that ACE polymorphisms were not related to the risk of COPD (p>0.05 in each model. In further analyses based on ethnicity, we observed an association between insertion/deletion polymorphism of the ACE gene and risk of COPD in the Asian population (codominant 2, OR = 3.126, 95% CI = 1.919–5.093, p0.05 in each model. In conclusion, the present meta-analysis indicated that the insertion/deletion polymorphism of the ACE gene may be associated with susceptibility to COPD in the Asian population but not in the Caucasian population. However, the results of the present meta-analysis need to be confirmed in a larger sample.

Gene expression in triple-negative breast cancer in relation to survival.

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Wang, Shuyang; Beeghly-Fadiel, Alicia; Cai, Qiuyin; Cai, Hui; Guo, Xingyi; Shi, Liang; Wu, Jie; Ye, Fei; Qiu, Qingchao; Zheng, Ying; Zheng, Wei; Bao, Ping-Ping; Shu, Xiao-Ou

2018-05-10

The identification of biomarkers related to the prognosis of triple-negative breast cancer (TNBC) is critically important for improved understanding of the biology that drives TNBC progression. We evaluated gene expression in total RNA isolated from formalin-fixed paraffin-embedded tumor samples using the NanoString nCounter assay for 469 TNBC cases from the Shanghai Breast Cancer Survival Study. We used Cox regression to quantify Hazard Ratios (HR) and corresponding confidence intervals (CI) for overall survival (OS) and disease-free survival (DFS) in models that included adjustment for breast cancer intrinsic subtype. Of 302 genes in our discovery analysis, 22 were further evaluated in relation to OS among 134 TNBC cases from the Nashville Breast Health Study and the Southern Community Cohort Study; 16 genes were further evaluated in relation to DFS in 335 TNBC cases from four gene expression omnibus datasets. Fixed-effect meta-analysis was used to combine results across data sources. Twofold higher expression of EOMES (HR 0.90, 95% CI 0.83-0.97), RASGRP1 (HR 0.89, 95% CI 0.82-0.97), and SOD2 (HR 0.80, 95% CI 0.66-0.96) was associated with better OS. Twofold higher expression of EOMES (HR 0.89, 95% CI 0.81-0.97) and RASGRP1 (HR 0.87, 95% CI 0.81-0.95) was also associated with better DFS. On the contrary, a doubling of FA2H (HR 1.14, 95% CI 1.06-1.22) and GSPT1 (HR 1.33, 95% CI 1.14-1.55) expression was associated with shorter DFS. We identified five genes (EOMES, FA2H, GSPT1, RASGRP1, and SOD2) that may serve as potential prognostic biomarkers and/or therapeutic targets for TNBC.

Molecular responses and expression analysis of genes in a ...

African Journals Online (AJOL)

STORAGESEVER

2009-06-17

Jun 17, 2009 ... Molecular responses and expression analysis of genes in a xerophytic desert shrub Haloxylon ammodendron .... physiological determination and cDNA-AFLP analysis, three groups of seeds were sowed in pots with sand and .... HaDR27. U. 234. PDR-like ABC transporter. AT1G59870. HaDR28. U. 135.

Partial Least Squares Based Gene Expression Analysis in EBV- Positive and EBV-Negative Posttransplant Lymphoproliferative Disorders.

Science.gov (United States)

Wu, Sa; Zhang, Xin; Li, Zhi-Ming; Shi, Yan-Xia; Huang, Jia-Jia; Xia, Yi; Yang, Hang; Jiang, Wen-Qi

2013-01-01

Post-transplant lymphoproliferative disorder (PTLD) is a common complication of therapeutic immunosuppression after organ transplantation. Gene expression profile facilitates the identification of biological difference between Epstein-Barr virus (EBV) positive and negative PTLDs. Previous studies mainly implemented variance/regression analysis without considering unaccounted array specific factors. The aim of this study is to investigate the gene expression difference between EBV positive and negative PTLDs through partial least squares (PLS) based analysis. With a microarray data set from the Gene Expression Omnibus database, we performed PLS based analysis. We acquired 1188 differentially expressed genes. Pathway and Gene Ontology enrichment analysis identified significantly over-representation of dysregulated genes in immune response and cancer related biological processes. Network analysis identified three hub genes with degrees higher than 15, including CREBBP, ATXN1, and PML. Proteins encoded by CREBBP and PML have been reported to be interact with EBV before. Our findings shed light on expression distinction of EBV positive and negative PTLDs with the hope to offer theoretical support for future therapeutic study.

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

NARCIS (Netherlands)

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

2008-01-01

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

Bone Metastasis in Advanced Breast Cancer: Analysis of Gene Expression Microarray.

Science.gov (United States)

Cosphiadi, Irawan; Atmakusumah, Tubagus D; Siregar, Nurjati C; Muthalib, Abdul; Harahap, Alida; Mansyur, Muchtarruddin

2018-03-08

Approximately 30% to 40% of breast cancer recurrences involve bone metastasis (BM). Certain genes have been linked to BM; however, none have been able to predict bone involvement. In this study, we analyzed gene expression profiles in advanced breast cancer patients to elucidate genes that can be used to predict BM. A total of 92 advanced breast cancer patients, including 46 patients with BM and 46 patients without BM, were identified for this study. Immunohistochemistry and gene expression analysis was performed on 81 formalin-fixed paraffin-embedded samples. Data were collected through medical records, and gene expression of 200 selected genes compiled from 6 previous studies was performed using NanoString nCounter. Genetic expression profiles showed that 22 genes were significantly differentially expressed between breast cancer patients with metastasis in bone and other organs (BM+) and non-BM, whereas subjects with only BM showed 17 significantly differentially expressed genes. The following genes were associated with an increasing incidence of BM in the BM+ group: estrogen receptor 1 (ESR1), GATA binding protein 3 (GATA3), and melanophilin with an area under the curve (AUC) of 0.804. In the BM group, the following genes were associated with an increasing incidence of BM: ESR1, progesterone receptor, B-cell lymphoma 2, Rab escort protein, N-acetyltransferase 1, GATA3, annexin A9, and chromosome 9 open reading frame 116. ESR1 and GATA3 showed an increased strength of association with an AUC of 0.928. A combination of the identified 3 genes in BM+ and 8 genes in BM showed better prediction than did each individual gene, and this combination can be used as a training set. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Association of CDX2 Expression With Survival in Early Colorectal Cancer: A Systematic Review and Meta-analysis.

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Tomasello, Gianluca; Barni, Sandro; Turati, Luca; Ghidini, Michele; Pezzica, Ezio; Passalacqua, Rodolfo; Petrelli, Fausto

2018-02-15

CDX2 is a homeobox gene encoding transcriptional factors for intestinal organogenesis and represents a specific marker of colorectal adenocarcinoma (CRC) differentiation. We have evaluated if CDX2 expression is associated with better overall and disease-free survival (OS and DFS) in patients with CRC. PubMed, SCOPUS, EMBASE, The Cochrane Library, and Web of Science (from inception to July 2017) were systematically reviewed for relevant studies on adult patients with CRC where OS and DFS were calculated according to CDX2 expression in uni- or multivariate analysis were included. Hazard ratio (HR) for mortality and/or disease progression was calculated. The search produced 16 studies suitable for inclusion (6291 individual patients). The meta-analysis showed a reduced risk of death for patients with CDX2-positive CRC in 14 studies (HR, 0.5; 95% confidence interval [CI], 0.38-0.66; P < .001 according to random effect model). In 6 studies where only DFS data was available, CDX2 expression led to a 52% lower risk of relapse or death (HR, 0.48; 95% CI, 0.39-0.59; P < .001 according to random effect model). The results did not change as a function of ethnicity, type of study, CDX2 detection modality, or stage. Interestingly, in stages II to III, CDX2 expression was associated with a 70% lower risk of death (HR, 0.3; 95% CI, 0.12-0.77; P = .01). CDX2 expression confirms to be a strong prognostic factor in stage II and III CRC. In this setting, along with other clinical and pathologic factors, the lack of expression of CDX2 may be considered an important variable when deciding for adjuvant chemotherapy. Copyright © 2018 Elsevier Inc. All rights reserved.

In silico analysis and verification of S100 gene expression in gastric cancer

International Nuclear Information System (INIS)

Liu, Ji; Li, Xue; Dong, Guang-Long; Zhang, Hong-Wei; Chen, Dong-Li; Du, Jian-Jun; Zheng, Jian-Yong; Li, Ji-Peng; Wang, Wei-Zhong

2008-01-01

The S100 protein family comprises 22 members whose protein sequences encompass at least one EF-hand Ca 2+ binding motif. They were involved in the regulation of a number of cellular processes such as cell cycle progression and differentiation. However, the expression status of S100 family members in gastric cancer was not known yet. Combined with analysis of series analysis of gene expression, virtual Northern blot and microarray data, the expression levels of S100 family members in normal and malignant stomach tissues were systematically investigated. The expression of S100A3 was further evaluated by quantitative RT-PCR. At least 5 S100 genes were found to be upregulated in gastric cance by in silico analysis. Among them, four genes, including S100A2, S100A4, S100A7 and S100A10, were reported to overexpressed in gastric cancer previously. The expression of S100A3 in eighty patients of gastric cancer was further examined. The results showed that the mean expression levels of S100A3 in gastric cancer tissues were 2.5 times as high as in adjacent non-tumorous tissues. S100A3 expression was correlated with tumor differentiation and TNM (Tumor-Node-Metastasis) stage of gastric cancer, which was relatively highly expressed in poorly differentiated and advanced gastric cancer tissues (P < 0.05). To our knowledge this is the first report of systematic evaluation of S100 gene expressions in gastric cancers by multiple in silico analysis. The results indicated that overexpression of S100 gene family members were characteristics of gastric cancers and S100A3 might play important roles in differentiation and progression of gastric cancer

Identification of distinct genes associated with seawater aspiration-induced acute lung injury by gene expression profile analysis

Science.gov (United States)

Liu, Wei; Pan, Lei; Zhang, Minlong; Bo, Liyan; Li, Congcong; Liu, Qingqing; Wang, Li; Jin, Faguang

2016-01-01

Seawater aspiration-induced acute lung injury (ALI) is a syndrome associated with a high mortality rate, which is characterized by severe hypoxemia, pulmonary edema and inflammation. The present study is the first, to the best of our knowledge, to analyze gene expression profiles from a rat model of seawater aspiration-induced ALI. Adult male Sprague-Dawley rats were instilled with seawater (4 ml/kg) in the seawater aspiration-induced ALI group (S group) or with distilled water (4 ml/kg) in the distilled water negative control group (D group). In the blank control group (C group) the rats' tracheae were exposed without instillation. Subsequently, lung samples were examined by histopathology; total protein concentration was detected in bronchoalveolar lavage fluid (BALF); lung wet/dry weight ratios were determined; and transcript expression was detected by gene sequencing analysis. The results demonstrated that histopathological alterations, pulmonary edema and total protein concentrations in BALF were increased in the S group compared with in the D group. Analysis of differential gene expression identified up and downregulated genes in the S group compared with in the D and C groups. A gene ontology analysis of the differential gene expression revealed enrichment of genes in the functional pathways associated with neutrophil chemotaxis, immune and defense responses, and cytokine activity. Kyoto Encyclopedia of Genes and Genomes analysis revealed that the cytokine-cytokine receptor interaction pathway was one of the most important pathways involved in seawater aspiration-induced ALI. In conclusion, activation of the cytokine-cytokine receptor interaction pathway may have an essential role in the progression of seawater aspiration-induced ALI, and the downregulation of tumor necrosis factor superfamily member 10 may enhance inflammation. Furthermore, IL-6 may be considered a biomarker in seawater aspiration-induced ALI. PMID:27509884

Gene Co-expression Analysis to Characterize Genes Related to Marbling Trait in Hanwoo (Korean) Cattle.

Science.gov (United States)

Lim, Dajeong; Lee, Seung-Hwan; Kim, Nam-Kuk; Cho, Yong-Min; Chai, Han-Ha; Seong, Hwan-Hoo; Kim, Heebal

2013-01-01

Marbling (intramuscular fat) is an important trait that affects meat quality and is a casual factor determining the price of beef in the Korean beef market. It is a complex trait and has many biological pathways related to muscle and fat. There is a need to identify functional modules or genes related to marbling traits and investigate their relationships through a weighted gene co-expression network analysis based on the system level. Therefore, we investigated the co-expression relationships of genes related to the 'marbling score' trait and systemically analyzed the network topology in Hanwoo (Korean cattle). As a result, we determined 3 modules (gene groups) that showed statistically significant results for marbling score. In particular, one module (denoted as red) has a statistically significant result for marbling score (p = 0.008) and intramuscular fat (p = 0.02) and water capacity (p = 0.006). From functional enrichment and relationship analysis of the red module, the pathway hub genes (IL6, CHRNE, RB1, INHBA and NPPA) have a direct interaction relationship and share the biological functions related to fat or muscle, such as adipogenesis or muscle growth. This is the first gene network study with m.logissimus in Hanwoo to observe co-expression patterns in divergent marbling phenotypes. It may provide insights into the functional mechanisms of the marbling trait.

Gene Co-expression Analysis to Characterize Genes Related to Marbling Trait in Hanwoo (Korean Cattle

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Dajeong Lim

2013-01-01

Full Text Available Marbling (intramuscular fat is an important trait that affects meat quality and is a casual factor determining the price of beef in the Korean beef market. It is a complex trait and has many biological pathways related to muscle and fat. There is a need to identify functional modules or genes related to marbling traits and investigate their relationships through a weighted gene co-expression network analysis based on the system level. Therefore, we investigated the co-expression relationships of genes related to the ‘marbling score’ trait and systemically analyzed the network topology in Hanwoo (Korean cattle. As a result, we determined 3 modules (gene groups that showed statistically significant results for marbling score. In particular, one module (denoted as red has a statistically significant result for marbling score (p = 0.008 and intramuscular fat (p = 0.02 and water capacity (p = 0.006. From functional enrichment and relationship analysis of the red module, the pathway hub genes (IL6, CHRNE, RB1, INHBA and NPPA have a direct interaction relationship and share the biological functions related to fat or muscle, such as adipogenesis or muscle growth. This is the first gene network study with m.logissimus in Hanwoo to observe co-expression patterns in divergent marbling phenotypes. It may provide insights into the functional mechanisms of the marbling trait.

MetaGOmics: A Web-Based Tool for Peptide-Centric Functional and Taxonomic Analysis of Metaproteomics Data

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Michael Riffle

2017-12-01

Full Text Available Metaproteomics is the characterization of all proteins being expressed by a community of organisms in a complex biological sample at a single point in time. Applications of metaproteomics range from the comparative analysis of environmental samples (such as ocean water and soil to microbiome data from multicellular organisms (such as the human gut. Metaproteomics research is often focused on the quantitative functional makeup of the metaproteome and which organisms are making those proteins. That is: What are the functions of the currently expressed proteins? How much of the metaproteome is associated with those functions? And, which microorganisms are expressing the proteins that perform those functions? However, traditional protein-centric functional analysis is greatly complicated by the large size, redundancy, and lack of biological annotations for the protein sequences in the database used to search the data. To help address these issues, we have developed an algorithm and web application (dubbed “MetaGOmics” that automates the quantitative functional (using Gene Ontology and taxonomic analysis of metaproteomics data and subsequent visualization of the results. MetaGOmics is designed to overcome the shortcomings of traditional proteomics analysis when used with metaproteomics data. It is easy to use, requires minimal input, and fully automates most steps of the analysis—including comparing the functional makeup between samples. MetaGOmics is freely available at https://www.yeastrc.org/metagomics/.

Systematic analysis of gene expression patterns associated with postmortem interval in human tissues.

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Zhu, Yizhang; Wang, Likun; Yin, Yuxin; Yang, Ence

2017-07-14

Postmortem mRNA degradation is considered to be the major concern in gene expression research utilizing human postmortem tissues. A key factor in this process is the postmortem interval (PMI), which is defined as the interval between death and sample collection. However, global patterns of postmortem mRNA degradation at individual gene levels across diverse human tissues remain largely unknown. In this study, we performed a systematic analysis of alteration of gene expression associated with PMI in human tissues. From the Genotype-Tissue Expression (GTEx) database, we evaluated gene expression levels of 2,016 high-quality postmortem samples from 316 donors of European descent, with PMI ranging from 1 to 27 hours. We found that PMI-related mRNA degradation is tissue-specific, gene-specific, and even genotype-dependent, thus drawing a more comprehensive picture of PMI-associated gene expression across diverse human tissues. Additionally, we also identified 266 differentially variable (DV) genes, such as DEFB4B and IFNG, whose expression is significantly dispersed between short PMI (S-PMI) and long PMI (L-PMI) groups. In summary, our analyses provide a comprehensive profile of PMI-associated gene expression, which will help interpret gene expression patterns in the evaluation of postmortem tissues.

Microarray analysis of gene expression profiles in ripening pineapple fruits.

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Koia, Jonni H; Moyle, Richard L; Botella, Jose R

2012-12-18

Pineapple (Ananas comosus) is a tropical fruit crop of significant commercial importance. Although the physiological changes that occur during pineapple fruit development have been well characterized, little is known about the molecular events that occur during the fruit ripening process. Understanding the molecular basis of pineapple fruit ripening will aid the development of new varieties via molecular breeding or genetic modification. In this study we developed a 9277 element pineapple microarray and used it to profile gene expression changes that occur during pineapple fruit ripening. Microarray analyses identified 271 unique cDNAs differentially expressed at least 1.5-fold between the mature green and mature yellow stages of pineapple fruit ripening. Among these 271 sequences, 184 share significant homology with genes encoding proteins of known function, 53 share homology with genes encoding proteins of unknown function and 34 share no significant homology with any database accession. Of the 237 pineapple sequences with homologs, 160 were up-regulated and 77 were down-regulated during pineapple fruit ripening. DAVID Functional Annotation Cluster (FAC) analysis of all 237 sequences with homologs revealed confident enrichment scores for redox activity, organic acid metabolism, metalloenzyme activity, glycolysis, vitamin C biosynthesis, antioxidant activity and cysteine peptidase activity, indicating the functional significance and importance of these processes and pathways during pineapple fruit development. Quantitative real-time PCR analysis validated the microarray expression results for nine out of ten genes tested. This is the first report of a microarray based gene expression study undertaken in pineapple. Our bioinformatic analyses of the transcript profiles have identified a number of genes, processes and pathways with putative involvement in the pineapple fruit ripening process. This study extends our knowledge of the molecular basis of pineapple fruit

Prognostic and clinicopathological significance of serum interleukin-6 expression in colorectal cancer: a systematic review and meta-analysis

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Wang Z

2015-12-01

Full Text Available Zhen Wang,1 Pin Wu,1,2 Dang Wu,1 Zhigang Zhang,3 Guoming Hu,1 Shuai Zhao,1 Yucheng Lai,1 Jian Huang1,41Cancer Institute, Key Laboratory of Cancer Prevention and Intervention, Key Laboratory of Molecular Biology in Medical Sciences, China National Ministry of Education, 2Department of Thoracic Surgery, 3Department of Gynecology, 4Department of Surgical Oncology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, People’s Republic of ChinaPurpose: Interleukin-6 (IL-6 plays an important role in human colorectal cancer (CRC development. However, the exact clinical and prognostic significance of IL-6 in CRC is still unclear. Here, we conducted this meta-analysis to explore this issue in detail.Methods: A meta-analysis was performed to clarify the association between serum IL-6 expression and clinical outcomes in articles published up to June 2015. Weighted mean difference (WMD and its corresponding 95% confidence interval (CI were used to assess the association between serum IL-6 expression and the clinicopathological characteristics of CRC. Hazard ratio (HR with 95% CI was used to quantify the predictive value of IL-6 on CRC prognosis.Results: Fourteen studies comprising 1,245 patients were included. Analysis of these data showed that serum IL-6 expression was highly correlated with poor 5-year overall survival (OS rate (HR =0.43, 95% CI: 0.31–0.59, P=0.755. Simultaneously, we also found that serum IL-6 expression was associated with certain clinical parameters of CRC, such as tumor invasion (T category: T0–T2, T3–T4 (WMD =3.15, 95% CI: 1.92–4.39, P=0.816, distant metastasis (M category: M0, M1 (WMD =4.69, 95% CI: 3.33–6.06, P=0.377, and tumor stage (I–II, III–IV (WMD =2.65, 95% CI: 1.09–4.21, P=0.066.Conclusion: A high serum IL-6 expression is associated with adverse OS in CRC. The IL-6 expression can be an important supplement in establishing prognostic score

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

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Paules Richard S

2007-11-01

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

Analysis of gene expression of myo1c and inpp5k genes involved in endometrial adenocarcinoma

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Koul, A.M.; Nadeem, A.; Baryalai, P.

2012-01-01

Abstract: Inpp5k gene encodes a protein which plays a very vital role in a number of metabolic pathways. It is very significant in the glucose metabolism where it regulates the signalling of the insulin pathway. But the full molecular details of the pathways regulated by Inpp5k encoded protein are not known. It is speculated that Inpp5k gene expression is altered in case of endometrial adenocarcinoma. Myolc gene encodes for a protein called Myosin-lc which acts an actin-based molecular motor in the cells. II has been studied that this gene down-regulates during endometrial adenocarcinoma and colorectal cancers. In this study the expression analysis of these two was carried out using multiplex PCR. An endogenous control was used for this PCR. ACTS gene served as the endogenous control because of it being a house keeping gene. It thus shows a universal expression in all cells. Thus in this study the gene expression of Inpp5k and Myulc genes was comparatively analysed with ACTS gene. The results that came out of this study showed an over-expression of Inpp5k gene and down-regulation of myolc gene with respect to ACTS gene in cancer cell lines as was indicated by the previous studies with these genes. Expression of both genes i.e. Inpp5k and Myolc was statistically compared between normal and cancerous cell lines and was found statistically significant at a value of P< O.O I in most of the cases. (author)

Systematic analysis of gene expression pattern in has-miR-197 over-expressed human uterine leiomyoma cells.

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Ling, Jing; Wu, Xiaoli; Fu, Ziyi; Tan, Jie; Xu, Qing

2015-10-01

Our previous study showed that the expression of miR-197 in leiomyoma was down-regulated compared with myometrium. Further, miR-197 has been identified to affect uterine leiomyoma cell proliferation, apoptosis, and metastasis ability, though the responsible molecular mechanism has not been well elucidated. In this study, we sought to determine the expression patterns of miR-197 targeted genes and to explore their potential functions, participating Pathways and the networks that are involved in the biological behavior of human uterine leiomyoma. After transfection of human uterine leiomyoma cells with miR-197, we confirmed the expression level of miR-197 using quantitative real-time PCR (qRT-PCR), and we detected the gene expression profiles after miR-197 over-expression through DNA microarray analysis. Further, we performed GO and Pathway analysis. The dominantly dys-regulated genes, which were up- or down-regulated by more than 10-fold, compared with parental cells, were confirmed using qRT-PCR technology. Compared with the control group, miR-197 was up-regulated by 30-fold after miR-197 lentiviral transfection. The microarray data showed that 872 genes were dys-regulated by more than 2-fold in human uterine leiomyoma cells after miR-197 overexpression, including 537 up-regulated and 335 down-regulated genes. The GO analysis indicated that the dys-regulated genes were primarily involved in response to stimuli, multicellular organ processes, and the signaling of biological progression. Further, Pathway analysis data showed that these genes participated in regulating several signaling Pathways, including the JAK/STAT signaling Pathway, the Toll-like receptor signaling Pathway, and cytokine-cytokine receptor interaction. The qRT-PCR results confirmed that 17 of the 66 selected genes, which were up- or down-regulated more than 10-fold by miR-197, were consistent with the microarray results, including tumorigenesis-related genes, such as DRT7, SLC549, SFMBT2, FLJ37956

Evaluation of reference genes for gene expression analysis using quantitative RT-PCR in Azospirillum brasilense.

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McMillan, Mary; Pereg, Lily

2014-01-01

Azospirillum brasilense is a nitrogen fixing bacterium that has been shown to have various beneficial effects on plant growth and yield. Under normal conditions A. brasilense exists in a motile flagellated form, which, under starvation or stress conditions, can undergo differentiation into an encapsulated, cyst-like form. Quantitative RT-PCR can be used to analyse changes in gene expression during this differentiation process. The accuracy of quantification of mRNA levels by qRT-PCR relies on the normalisation of data against stably expressed reference genes. No suitable set of reference genes has yet been described for A. brasilense. Here we evaluated the expression of ten candidate reference genes (16S rRNA, gapB, glyA, gyrA, proC, pykA, recA, recF, rpoD, and tpiA) in wild-type and mutant A. brasilense strains under different culture conditions, including conditions that induce differentiation. Analysis with the software programs BestKeeper, NormFinder and GeNorm indicated that gyrA, glyA and recA are the most stably expressed reference genes in A. brasilense. The results also suggested that the use of two reference genes (gyrA and glyA) is sufficient for effective normalisation of qRT-PCR data.

Evaluation of reference genes for gene expression analysis using quantitative RT-PCR in Azospirillum brasilense.

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Mary McMillan

Full Text Available Azospirillum brasilense is a nitrogen fixing bacterium that has been shown to have various beneficial effects on plant growth and yield. Under normal conditions A. brasilense exists in a motile flagellated form, which, under starvation or stress conditions, can undergo differentiation into an encapsulated, cyst-like form. Quantitative RT-PCR can be used to analyse changes in gene expression during this differentiation process. The accuracy of quantification of mRNA levels by qRT-PCR relies on the normalisation of data against stably expressed reference genes. No suitable set of reference genes has yet been described for A. brasilense. Here we evaluated the expression of ten candidate reference genes (16S rRNA, gapB, glyA, gyrA, proC, pykA, recA, recF, rpoD, and tpiA in wild-type and mutant A. brasilense strains under different culture conditions, including conditions that induce differentiation. Analysis with the software programs BestKeeper, NormFinder and GeNorm indicated that gyrA, glyA and recA are the most stably expressed reference genes in A. brasilense. The results also suggested that the use of two reference genes (gyrA and glyA is sufficient for effective normalisation of qRT-PCR data.

Association between TNF-α-238G/A gene polymorphism and OCD susceptibility: A meta-analysis.

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Jiang, Caixiao; Ma, Xinyan; Qi, Shunxiang; Han, Guangyue; Li, Yan; Liu, Yanfang; Liu, Lanfen

2018-02-01

Tumor necrosis factor-alpha (TNF-α) is an important cytokine and has been reported to be associated with the pathogenesis of many autoimmune and inflammatory diseases. TNF-α gene is located on a region that has been found to be associated with obsessive-compulsive disorder (OCD). We performed this meta-analysis to assess the relationship between susceptibility to OCD and the TNF-α-238G/A gene polymorphism. An extensive search of the available literature on the association between the susceptibility to OCD and the TNF gene polymorphism was conducted by searching PubMed, Web of Knowledge, Embase, Chinese Web of Knowledge, Wanfang, and Chongqing VIP database. The database was searched up to December 2016 and includes language of English and/or Chinese with the keywords of "obsessive-compulsive disorder" or "OCD," polymorphism or variant or mutation, "tumor necrosis factor" or "TNF" or "cytokine." The association between TNF-α-238G/A gene polymorphism and the susceptibility of OCD was anticipated by odds ratio (OR) with the corresponding 95% confidence interval (95% CI). Four studies including 435 cases and 1073 controls were incorporated in our meta-analysis. In general, TNF-α-238G/A gene polymorphism might lead to a decreased risk of OCD susceptibility (G vs A genotype model: OR = 1.01, 95% CI = 0.37-2.77, P = .981; GG vs AA+AG model: OR = 0.93, 95% CI = 0.37-2.36, P = .879; GG+AG vs AA model: OR = 0.22, 95% CI = 0.06-0.73, P = .014; GG vs AA model: OR = 0.21, 95% CI = 0.06-0.71, P = .012; AG vs AA model: OR = 0.29, 95% CI = 0.07-1.16, P = .081; GG+AA vs AG model: OR = 1.17, 95% CI = 0.55-2.51, P = .683). TNF-α-238G/A gene polymorphism might lead to a decreased risk of OCD susceptibility.

MDM2 SNP309, gene-gene interaction, and tumor susceptibility: an updated meta-analysis

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Wu Wei

2011-05-01

Full Text Available Abstract Background The tumor suppressor gene p53 is involved in multiple cellular pathways including apoptosis, transcriptional control, and cell cycle regulation. In the last decade it has been demonstrated that the single nucleotide polymorphism (SNP at codon 72 of the p53 gene is associated with the risk for development of various neoplasms. MDM2 SNP309 is a single nucleotide T to G polymorphism located in the MDM2 gene promoter. From the time that this well-characterized functional polymorphism was identified, a variety of case-control studies have been published that investigate the possible association between MDM2 SNP309 and cancer risk. However, the results of the published studies, as well as the subsequent meta-analyses, remain contradictory. Methods To investigate whether currently published epidemiological studies can clarify the potential interaction between MDM2 SNP309 and the functional genetic variant in p53 codon72 (Arg72Pro and p53 mutation status, we performed a meta-analysis of the risk estimate on 27,813 cases with various tumor types and 30,295 controls. Results The data we reviewed indicated that variant homozygote 309GG and heterozygote 309TG were associated with a significant increased risk of all tumor types (homozygote comparison: odds ratio (OR = 1.25, 95% confidence interval (CI = 1.13-1.37; heterozygote comparison: OR = 1.10, 95% CI = 1.03-1.17. We also found that the combination of GG and Pro/Pro, TG and Pro/Pro, GG and Arg/Arg significantly increased the risk of cancer (OR = 3.38, 95% CI = 1.77-6.47; OR = 1.88, 95% CI = 1.26-2.81; OR = 1.96, 95% CI = 1.01-3.78, respectively. In a stratified analysis by tumor location, we also found a significant increased risk in brain, liver, stomach and uterus cancer (OR = 1.47, 95% CI = 1.06-2.03; OR = 2.24, 95%CI = 1.57-3.18; OR = 1.54, 95%CI = 1.04-2.29; OR = 1.34, 95%CI = 1.07-1.29, respectively. However, no association was seen between MDM2 SNP309 and tumor susceptibility

Global gene expression analysis of apple fruit development from the floral bud to ripe fruit

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McArtney Steve

2008-02-01

Full Text Available Abstract Background Apple fruit develop over a period of 150 days from anthesis to fully ripe. An array representing approximately 13000 genes (15726 oligonucleotides of 45–55 bases designed from apple ESTs has been used to study gene expression over eight time points during fruit development. This analysis of gene expression lays the groundwork for a molecular understanding of fruit growth and development in apple. Results Using ANOVA analysis of the microarray data, 1955 genes showed significant changes in expression over this time course. Expression of genes is coordinated with four major patterns of expression observed: high in floral buds; high during cell division; high when starch levels and cell expansion rates peak; and high during ripening. Functional analysis associated cell cycle genes with early fruit development and three core cell cycle genes are significantly up-regulated in the early stages of fruit development. Starch metabolic genes were associated with changes in starch levels during fruit development. Comparison with microarrays of ethylene-treated apple fruit identified a group of ethylene induced genes also induced in normal fruit ripening. Comparison with fruit development microarrays in tomato has been used to identify 16 genes for which expression patterns are similar in apple and tomato and these genes may play fundamental roles in fruit development. The early phase of cell division and tissue specification that occurs in the first 35 days after pollination has been associated with up-regulation of a cluster of genes that includes core cell cycle genes. Conclusion Gene expression in apple fruit is coordinated with specific developmental stages. The array results are reproducible and comparisons with experiments in other species has been used to identify genes that may play a fundamental role in fruit development.

Mucin Expression in Colorectal Cancer (CRC): Systematic Review and Meta-Analysis.

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Niv, Yaron; Rokkas, Theodore

2018-05-18

A body of evidence has suggested that mucins play an important role in adhesion, invasion, and cancer metastasis. However, this evidence is scarce and sometimes confusing. We performed a systematic review and meta-analysis of available studies to better define the role of mucins in the behavior of colorectal cancer (CRC). Medical literature was searched through November 30, 2017, using suitable keywords. Pooled estimates, that is, odd ratios (ORs), were obtained using fixed or random-effects models, as appropriate. Heterogeneity between studies was evaluated with the Cochran Q test and I values, whereas the likelihood of publication bias was assessed by constructing funnel plots. Their symmetry was estimated by the Begg and Mazumdar adjusted rank correlation test and by the Egger regression test. A total of 2234 CRC patients were included in 12 studies, eligible for meta-analysis. There was a significant difference concerning total mucin expression between CRC patients and controls [pooled ORs (95% confidence interval)=8.156 (2.624-25.354), test for overall effect Z=3.627, PCRC, that is advanced stage versus localized disease [ORs (95% confidence interval)=2.724 (1.211-6.127), Z= 2.423, P=0.015], as opposed to MUC2 and MUC4. MUC1 is overexpressed in CRC tissue comparing with healthy mucosa, and may have a role in the neoplastic transformation and metastatic process. MUC2 has probably no role in carcinogenesis.

Biclustering methods: biological relevance and application in gene expression analysis.

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Ali Oghabian

Full Text Available DNA microarray technologies are used extensively to profile the expression levels of thousands of genes under various conditions, yielding extremely large data-matrices. Thus, analyzing this information and extracting biologically relevant knowledge becomes a considerable challenge. A classical approach for tackling this challenge is to use clustering (also known as one-way clustering methods where genes (or respectively samples are grouped together based on the similarity of their expression profiles across the set of all samples (or respectively genes. An alternative approach is to develop biclustering methods to identify local patterns in the data. These methods extract subgroups of genes that are co-expressed across only a subset of samples and may feature important biological or medical implications. In this study we evaluate 13 biclustering and 2 clustering (k-means and hierarchical methods. We use several approaches to compare their performance on two real gene expression data sets. For this purpose we apply four evaluation measures in our analysis: (1 we examine how well the considered (biclustering methods differentiate various sample types; (2 we evaluate how well the groups of genes discovered by the (biclustering methods are annotated with similar Gene Ontology categories; (3 we evaluate the capability of the methods to differentiate genes that are known to be specific to the particular sample types we study and (4 we compare the running time of the algorithms. In the end, we conclude that as long as the samples are well defined and annotated, the contamination of the samples is limited, and the samples are well replicated, biclustering methods such as Plaid and SAMBA are useful for discovering relevant subsets of genes and samples.

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

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Yunxie eWei

2016-02-01

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

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

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

2016-01-01

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

Selection and validation of a set of reliable reference genes for quantitative sod gene expression analysis in C. elegans

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Vandesompele Jo

2008-01-01

Full Text Available Abstract Background In the nematode Caenorhabditis elegans the conserved Ins/IGF-1 signaling pathway regulates many biological processes including life span, stress response, dauer diapause and metabolism. Detection of differentially expressed genes may contribute to a better understanding of the mechanism by which the Ins/IGF-1 signaling pathway regulates these processes. Appropriate normalization is an essential prerequisite for obtaining accurate and reproducible quantification of gene expression levels. The aim of this study was to establish a reliable set of reference genes for gene expression analysis in C. elegans. Results Real-time quantitative PCR was used to evaluate the expression stability of 12 candidate reference genes (act-1, ama-1, cdc-42, csq-1, eif-3.C, mdh-1, gpd-2, pmp-3, tba-1, Y45F10D.4, rgs-6 and unc-16 in wild-type, three Ins/IGF-1 pathway mutants, dauers and L3 stage larvae. After geNorm analysis, cdc-42, pmp-3 and Y45F10D.4 showed the most stable expression pattern and were used to normalize 5 sod expression levels. Significant differences in mRNA levels were observed for sod-1 and sod-3 in daf-2 relative to wild-type animals, whereas in dauers sod-1, sod-3, sod-4 and sod-5 are differentially expressed relative to third stage larvae. Conclusion Our findings emphasize the importance of accurate normalization using stably expressed reference genes. The methodology used in this study is generally applicable to reliably quantify gene expression levels in the nematode C. elegans using quantitative PCR.

Weighted gene co-expression network analysis reveals potential genes involved in early metamorphosis process in sea cucumber Apostichopus japonicus.

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Li, Yongxin; Kikuchi, Mani; Li, Xueyan; Gao, Qionghua; Xiong, Zijun; Ren, Yandong; Zhao, Ruoping; Mao, Bingyu; Kondo, Mariko; Irie, Naoki; Wang, Wen

2018-01-01

Sea cucumbers, one main class of Echinoderms, have a very fast and drastic metamorphosis process during their development. However, the molecular basis under this process remains largely unknown. Here we systematically examined the gene expression profiles of Japanese common sea cucumber (Apostichopus japonicus) for the first time by RNA sequencing across 16 developmental time points from fertilized egg to juvenile stage. Based on the weighted gene co-expression network analysis (WGCNA), we identified 21 modules. Among them, MEdarkmagenta was highly expressed and correlated with the early metamorphosis process from late auricularia to doliolaria larva. Furthermore, gene enrichment and differentially expressed gene analysis identified several genes in the module that may play key roles in the metamorphosis process. Our results not only provide a molecular basis for experimentally studying the development and morphological complexity of sea cucumber, but also lay a foundation for improving its emergence rate. Copyright © 2017 Elsevier Inc. All rights reserved.

Preferential Allele Expression Analysis Identifies Shared Germline and Somatic Driver Genes in Advanced Ovarian Cancer

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Halabi, Najeeb M.; Martinez, Alejandra; Al-Farsi, Halema; Mery, Eliane; Puydenus, Laurence; Pujol, Pascal; Khalak, Hanif G.; McLurcan, Cameron; Ferron, Gwenael; Querleu, Denis; Al-Azwani, Iman; Al-Dous, Eman; Mohamoud, Yasmin A.; Malek, Joel A.; Rafii, Arash

2016-01-01

Identifying genes where a variant allele is preferentially expressed in tumors could lead to a better understanding of cancer biology and optimization of targeted therapy. However, tumor sample heterogeneity complicates standard approaches for detecting preferential allele expression. We therefore developed a novel approach combining genome and transcriptome sequencing data from the same sample that corrects for sample heterogeneity and identifies significant preferentially expressed alleles. We applied this analysis to epithelial ovarian cancer samples consisting of matched primary ovary and peritoneum and lymph node metastasis. We find that preferentially expressed variant alleles include germline and somatic variants, are shared at a relatively high frequency between patients, and are in gene networks known to be involved in cancer processes. Analysis at a patient level identifies patient-specific preferentially expressed alleles in genes that are targets for known drugs. Analysis at a site level identifies patterns of site specific preferential allele expression with similar pathways being impacted in the primary and metastasis sites. We conclude that genes with preferentially expressed variant alleles can act as cancer drivers and that targeting those genes could lead to new therapeutic strategies. PMID:26735499

Integrating genome-wide association study and expression quantitative trait loci data identifies multiple genes and gene set associated with neuroticism.

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Fan, Qianrui; Wang, Wenyu; Hao, Jingcan; He, Awen; Wen, Yan; Guo, Xiong; Wu, Cuiyan; Ning, Yujie; Wang, Xi; Wang, Sen; Zhang, Feng

2017-08-01

Neuroticism is a fundamental personality trait with significant genetic determinant. To identify novel susceptibility genes for neuroticism, we conducted an integrative analysis of genomic and transcriptomic data of genome wide association study (GWAS) and expression quantitative trait locus (eQTL) study. GWAS summary data was driven from published studies of neuroticism, totally involving 170,906 subjects. eQTL dataset containing 927,753 eQTLs were obtained from an eQTL meta-analysis of 5311 samples. Integrative analysis of GWAS and eQTL data was conducted by summary data-based Mendelian randomization (SMR) analysis software. To identify neuroticism associated gene sets, the SMR analysis results were further subjected to gene set enrichment analysis (GSEA). The gene set annotation dataset (containing 13,311 annotated gene sets) of GSEA Molecular Signatures Database was used. SMR single gene analysis identified 6 significant genes for neuroticism, including MSRA (p value=2.27×10 -10 ), MGC57346 (p value=6.92×10 -7 ), BLK (p value=1.01×10 -6 ), XKR6 (p value=1.11×10 -6 ), C17ORF69 (p value=1.12×10 -6 ) and KIAA1267 (p value=4.00×10 -6 ). Gene set enrichment analysis observed significant association for Chr8p23 gene set (false discovery rate=0.033). Our results provide novel clues for the genetic mechanism studies of neuroticism. Copyright © 2017. Published by Elsevier Inc.

Profile of the genes expressed in the human peripheral retina, macula, and retinal pigment epithelium determined through serial analysis of gene expression (SAGE)

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Sharon, Dror; Blackshaw, Seth; Cepko, Constance L.; Dryja, Thaddeus P.

2002-01-01

We used the serial analysis of gene expression (SAGE) technique to catalogue and measure the relative levels of expression of the genes expressed in the human peripheral retina, macula, and retinal pigment epithelium (RPE) from one or both of two humans, aged 88 and 44 years. The cone photoreceptor contribution to all transcription in the retina was found to be similar in the macula versus the retinal periphery, whereas the rod contribution was greater in the periphery versus the macula. Genes encoding structural proteins for axons were found to be expressed at higher levels in the macula versus the retinal periphery, probably reflecting the large proportion of ganglion cells in the central retina. In comparison with the younger eye, the peripheral retina of the older eye had a substantially higher proportion of mRNAs from genes encoding proteins involved in iron metabolism or protection against oxidative damage and a substantially lower proportion of mRNAs from genes encoding proteins involved in rod phototransduction. These differences may reflect the difference in age between the two donors or merely interindividual variation. The RPE library had numerous previously unencountered tags, suggesting that this cell type has a large, idiosyncratic repertoire of expressed genes. Comparison of these libraries with 100 reported nonocular SAGE libraries revealed 89 retina-specific or enriched genes expressed at substantial levels, of which 14 are known to cause a retinal disease and 53 are RPE-specific genes. We expect that these libraries will serve as a resource for understanding the relative expression levels of genes in the retina and the RPE and for identifying additional disease genes. PMID:11756676

Use of meta-analysis to combine candidate gene association studies: application to study the relationship between the ESR PvuII polymorphism and sow litter size

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Alfonso Leopoldo

2005-07-01

Full Text Available Abstract This article investigates the application of meta-analysis on livestock candidate gene effects. The PvuII polymorphism of the ESR gene is used as an example. The association among ESR PvuII alleles with the number of piglets born alive and total born in the first (NBA1, TNB1 and later parities (NBA, TNB is reviewed by conducting a meta-analysis of 15 published studies including 9329 sows. Under a fixed effects model, litter size values were significantly lower in the "AA" genotype groups when compared with "AB" and "BB" homozygotes. Under the random effects model, the results were similar although differences between "AA" and "AB" genotype groups were not clearly significant for NBA and TNB. Nevertheless, the most noticeable result was the high and significant heterogeneity estimated among studies. This heterogeneity could be assigned to error sampling, genotype by environment interaction, linkage or epistasis, as referred to in the literature, but also to the hypothesis of population admixture/stratification. It is concluded that meta-analysis can be considered as a helpful analytical tool to synthesise and discuss livestock candidate gene effects. The main difficulty found was the insufficient information on the standard errors of the estimated genotype effects in several publications. Consequently, the convenience of publishing the standard errors or the concrete P-values instead of the test significance level should be recommended to guarantee the quality of candidate gene effect meta-analyses.

Mercury-induced hepatotoxicity in zebrafish: in vivo mechanistic insights from transcriptome analysis, phenotype anchoring and targeted gene expression validation

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Mathavan Sinnakaruppan

2010-03-01

Full Text Available Abstract Background Mercury is a prominent environmental contaminant that causes detrimental effects to human health. Although the liver has been known to be a main target organ, there is limited information on in vivo molecular mechanism of mercury-induced toxicity in the liver. By using transcriptome analysis, phenotypic anchoring and validation of targeted gene expression in zebrafish, mercury-induced hepatotoxicity was investigated and a number of perturbed cellular processes were identified and compared with those captured in the in vitro human cell line studies. Results Hepato-transcriptome analysis of mercury-exposed zebrafish revealed that the earliest deregulated genes were associated with electron transport chain, mitochondrial fatty acid beta-oxidation, nuclear receptor signaling and apoptotic pathway, followed by complement system and proteasome pathway, and thereafter DNA damage, hypoxia, Wnt signaling, fatty acid synthesis, gluconeogenesis, cell cycle and motility. Comparative meta-analysis of microarray data between zebrafish liver and human HepG2 cells exposed to mercury identified some common toxicological effects of mercury-induced hepatotoxicity in both models. Histological analyses of liver from mercury-exposed fish revealed morphological changes of liver parenchyma, decreased nucleated cell count, increased lipid vesicles, glycogen and apoptotic bodies, thus providing phenotypic evidence for anchoring of the transcriptome analysis. Validation of targeted gene expression confirmed deregulated gene-pathways from enrichment analysis. Some of these genes responding to low concentrations of mercury may serve as toxicogenomic-based markers for detection and health risk assessment of environmental mercury contaminations. Conclusion Mercury-induced hepatotoxicity was triggered by oxidative stresses, intrinsic apoptotic pathway, deregulation of nuclear receptor and kinase activities including Gsk3 that deregulates Wnt signaling

Gene expression analysis of matched ovarian primary tumors and peritoneal metastasis

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Malek Joel A

2012-06-01

Full Text Available Abstract Background Ovarian cancer is the most deadly gynecological cancer due to late diagnosis at advanced stage with major peritoneal involvement. To date most research has focused on primary tumor. However the prognosis is directly related to residual disease at the end of the treatment. Therefore it is mandatory to focus and study the biology of meatastatic disease that is most frequently localized to the peritoneal caivty in ovarian cancer. Methods We used high-density gene expression arrays to investigate gene expression changes between matched primary and metastatic (peritoneal lesions. Results Here we show that gene expression profiles in peritoneal metastasis are significantly different than their matched primary tumor and these changes are affected by underlying copy number variation differences among other causes. We show that differentially expressed genes are enriched in specific pathways including JAK/STAT pathway, cytokine signaling and other immune related pathways. We show that underlying copy number variations significantly affect gene expression. Indeed patients with important differences in copy number variation displayed greater gene expression differences between their primary and matched metastatic lesions. Conclusions Our analysis shows a very specific targeting at both the genomic and transcriptomic level to upregulate certain pathways in the peritoneal metastasis of ovarian cancer. Moreover, while primary tumors use certain pathways we identify distinct differences with metastatic lesions. The variation between primary and metastatic lesions should be considered in personalized treatment of ovarian cancer.

Meta-analysis of archived DNA microarrays identifies genes regulated by hypoxia and involved in a metastatic phenotype in cancer cells

International Nuclear Information System (INIS)

Pierre, Michael; DeHertogh, Benoît; Gaigneaux, Anthoula; DeMeulder, Bertrand; Berger, Fabrice; Bareke, Eric; Michiels, Carine; Depiereux, Eric

2010-01-01

Metastasis is a major cancer-related cause of death. Recent studies have described metastasis pathways. However, the exact contribution of each pathway remains unclear. Another key feature of a tumor is the presence of hypoxic areas caused by a lack of oxygen at the center of the tumor. Hypoxia leads to the expression of pro-metastatic genes as well as the repression of anti-metastatic genes. As many Affymetrix datasets about metastasis and hypoxia are publicly available and not fully exploited, this study proposes to re-analyze these datasets to extract new information about the metastatic phenotype induced by hypoxia in different cancer cell lines. Affymetrix datasets about metastasis and/or hypoxia were downloaded from GEO and ArrayExpress. AffyProbeMiner and GCRMA packages were used for pre-processing and the Window Welch t test was used for processing. Three approaches of meta-analysis were eventually used for the selection of genes of interest. Three complementary approaches were used, that eventually selected 183 genes of interest. Out of these 183 genes, 99, among which the well known JUNB, FOS and TP63, have already been described in the literature to be involved in cancer. Moreover, 39 genes of those, such as SERPINE1 and MMP7, are known to regulate metastasis. Twenty-one genes including VEGFA and ID2 have also been described to be involved in the response to hypoxia. Lastly, DAVID classified those 183 genes in 24 different pathways, among which 8 are directly related to cancer while 5 others are related to proliferation and cell motility. A negative control composed of 183 random genes failed to provide such results. Interestingly, 6 pathways retrieved by DAVID with the 183 genes of interest concern pathogen recognition and phagocytosis. The proposed methodology was able to find genes actually known to be involved in cancer, metastasis and hypoxia and, thus, we propose that the other genes selected based on the same methodology are of prime interest in

A meta-analysis of xeroderma pigmentosum gene D Ls751Gln polymorphism and susceptibility to hepatocellular carcinoma.

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Wang, Yu; Zhao, Yingren; Zhang, Aiyun; Ma, Juan; Wang, Zhenzhen; Zhang, Xu

2015-01-01

Hepatocellular carcinoma (HCC) is one of most common malignant tumors worldwide, but with unclear mechanisms. Xeroderma pigmentosum gene D (XPD) is one important DNA damage repair gene and can be involved in protein mutation. Currently little has been known about XPD polymorphism and HCC susceptibility in Chinese people. This study used a meta-analysis approach to comprehensively investigate the correlation between XPD polymorphism and HCC susceptibility in Chinese population, based on previously published literatures. A computer retrieval system was used to collect all case-control studies about XPD Lys751Gln polymorphism and HCC susceptibility. Data in literatures were extracted for meta-analysis. After the primary screening, four independent studies, which were published in 3 English articles and one Chinese article, were recruited in this study. There were 1,717 samples included in all studies. Using Gln/Gln + Lys/Gln, Lys/Lys + Lys/Gln and Lys allels as the reference, HCC disease alleles including Lys/Lys, Gln/Gln and Gln had OR values (95% CI, I(2)) of 1.007 (0.657~4.672, 91%), 3.516 (0.220~20.661, 48%) and 3.225 (0.278~12.326, 84%), respectively. The polymorphism of XPD751 loci is closely correlated with primary HCC. Lys751Gln polymorphism of XPD gene can be used as one susceptibility factor for HCC.

MALDI-TOF mass spectrometry for quantitative gene expression analysis of acid responses in Staphylococcus aureus.

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Rode, Tone Mari; Berget, Ingunn; Langsrud, Solveig; Møretrø, Trond; Holck, Askild

2009-07-01

Microorganisms are constantly exposed to new and altered growth conditions, and respond by changing gene expression patterns. Several methods for studying gene expression exist. During the last decade, the analysis of microarrays has been one of the most common approaches applied for large scale gene expression studies. A relatively new method for gene expression analysis is MassARRAY, which combines real competitive-PCR and MALDI-TOF (matrix-assisted laser desorption/ionization time-of-flight) mass spectrometry. In contrast to microarray methods, MassARRAY technology is suitable for analysing a larger number of samples, though for a smaller set of genes. In this study we compare the results from MassARRAY with microarrays on gene expression responses of Staphylococcus aureus exposed to acid stress at pH 4.5. RNA isolated from the same stress experiments was analysed using both the MassARRAY and the microarray methods. The MassARRAY and microarray methods showed good correlation. Both MassARRAY and microarray estimated somewhat lower fold changes compared with quantitative real-time PCR (qRT-PCR). The results confirmed the up-regulation of the urease genes in acidic environments, and also indicated the importance of metal ion regulation. This study shows that the MassARRAY technology is suitable for gene expression analysis in prokaryotes, and has advantages when a set of genes is being analysed for an organism exposed to many different environmental conditions.

Association between variations in the disrupted in schizophrenia 1 gene and schizophrenia: A meta-analysis.

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Xu, Yiliang; Ren, Jun; Ye, Haihong

2018-04-20

Schizophrenia is a severe psychiatric disorder. Genetic and functional studies have strongly implicated the disrupted in schizophrenia 1 gene (DISC1) as a candidate susceptibility gene for schizophrenia. Moreover, recent association studies have indicated that several DISC1 single nucleotide polymorphisms (SNPs) are associated with schizophrenia. However, the association is hardly replicate in different ethnic group. Here, we performed a meta-analysis of the association between DISC1 SNPs and schizophrenia in which the samples were divided into subgroups according to ethnicity. Both rs3738401 and rs821616 showed not significantly association with schizophrenia in the Caucasian, Asian, Japanese or Han Chinese populations. Copyright © 2018 Elsevier B.V. All rights reserved.

Genes and co-expression modules common to drought and bacterial stress responses in Arabidopsis and rice.

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Rafi Shaik

Full Text Available Plants are simultaneously exposed to multiple stresses resulting in enormous changes in the molecular landscape within the cell. Identification and characterization of the synergistic and antagonistic components of stress response mechanisms contributing to the cross talk between stresses is of high priority to explore and enhance multiple stress responses. To this end, we performed meta-analysis of drought (abiotic, bacterial (biotic stress response in rice and Arabidopsis by analyzing a total of 386 microarray samples belonging to 20 microarray studies and identified approximately 3100 and 900 DEGs in rice and Arabidopsis, respectively. About 38.5% (1214 and 28.7% (272 DEGs were common to drought and bacterial stresses in rice and Arabidopsis, respectively. A majority of these common DEGs showed conserved expression status in both stresses. Gene ontology enrichment analysis clearly demarcated the response and regulation of various plant hormones and related biological processes. Fatty acid metabolism and biosynthesis of alkaloids were upregulated and, nitrogen metabolism and photosynthesis was downregulated in both stress conditions. WRKY transcription family genes were highly enriched in all upregulated gene sets while 'CO-like' TF family showed inverse relationship of expression between drought and bacterial stresses. Weighted gene co-expression network analysis divided DEG sets into multiple modules that show high co-expression and identified stress specific hub genes with high connectivity. Detection of consensus modules based on DEGs common to drought and bacterial stress revealed 9 and 4 modules in rice and Arabidopsis, respectively, with conserved and reversed co-expression patterns.

rpb2 is a reliable reference gene for quantitative gene expression analysis in the dermatophyte Trichophyton rubrum.

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Jacob, Tiago R; Peres, Nalu T A; Persinoti, Gabriela F; Silva, Larissa G; Mazucato, Mendelson; Rossi, Antonio; Martinez-Rossi, Nilce M

2012-05-01

The selection of reference genes used for data normalization to quantify gene expression by real-time PCR amplifications (qRT-PCR) is crucial for the accuracy of this technique. In spite of this, little information regarding such genes for qRT-PCR is available for gene expression analyses in pathogenic fungi. Thus, we investigated the suitability of eight candidate reference genes in isolates of the human dermatophyte Trichophyton rubrum subjected to several environmental challenges, such as drug exposure, interaction with human nail and skin, and heat stress. The stability of these genes was determined by geNorm, NormFinder and Best-Keeper programs. The gene with the most stable expression in the majority of the conditions tested was rpb2 (DNA-dependent RNA polymerase II), which was validated in three T. rubrum strains. Moreover, the combination of rpb2 and chs1 (chitin synthase) genes provided for the most reliable qRT-PCR data normalization in T. rubrum under a broad range of biological conditions. To the best of our knowledge this is the first report on the selection of reference genes for qRT-PCR data normalization in dermatophytes and the results of these studies should permit further analysis of gene expression under several experimental conditions, with improved accuracy and reliability.

Partial least squares based gene expression analysis in estrogen receptor positive and negative breast tumors.

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Ma, W; Zhang, T-F; Lu, P; Lu, S H

2014-01-01

Breast cancer is categorized into two broad groups: estrogen receptor positive (ER+) and ER negative (ER-) groups. Previous study proposed that under trastuzumab-based neoadjuvant chemotherapy, tumor initiating cell (TIC) featured ER- tumors response better than ER+ tumors. Exploration of the molecular difference of these two groups may help developing new therapeutic strategies, especially for ER- patients. With gene expression profile from the Gene Expression Omnibus (GEO) database, we performed partial least squares (PLS) based analysis, which is more sensitive than common variance/regression analysis. We acquired 512 differentially expressed genes. Four pathways were found to be enriched with differentially expressed genes, involving immune system, metabolism and genetic information processing process. Network analysis identified five hub genes with degrees higher than 10, including APP, ESR1, SMAD3, HDAC2, and PRKAA1. Our findings provide new understanding for the molecular difference between TIC featured ER- and ER+ breast tumors with the hope offer supports for therapeutic studies.

Meta-analysis with R

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Schwarzer, Guido; Rücker, Gerta

2015-01-01

This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with R. As such, the book introduces the key concepts and models used in meta-analysis. It also includes chapters on the following advanced topics: publication bias and small study effects; missing data; multivariate meta-analysis, network meta-analysis; and meta-analysis of diagnostic studies.  .

Comparative transcriptome analysis reveals differentially expressed genes associated with sex expression in garden asparagus (Asparagus officinalis).

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Li, Shu-Fen; Zhang, Guo-Jun; Zhang, Xue-Jin; Yuan, Jin-Hong; Deng, Chuan-Liang; Gao, Wu-Jun

2017-08-22

Garden asparagus (Asparagus officinalis) is a highly valuable vegetable crop of commercial and nutritional interest. It is also commonly used to investigate the mechanisms of sex determination and differentiation in plants. However, the sex expression mechanisms in asparagus remain poorly understood. De novo transcriptome sequencing via Illumina paired-end sequencing revealed more than 26 billion bases of high-quality sequence data from male and female asparagus flower buds. A total of 72,626 unigenes with an average length of 979 bp were assembled. In comparative transcriptome analysis, 4876 differentially expressed genes (DEGs) were identified in the possible sex-determining stage of female and male/supermale flower buds. Of these DEGs, 433, including 285 male/supermale-biased and 149 female-biased genes, were annotated as flower related. Of the male/supermale-biased flower-related genes, 102 were probably involved in anther development. In addition, 43 DEGs implicated in hormone response and biosynthesis putatively associated with sex expression and reproduction were discovered. Moreover, 128 transcription factor (TF)-related genes belonging to various families were found to be differentially expressed, and this finding implied the essential roles of TF in sex determination or differentiation in asparagus. Correlation analysis indicated that miRNA-DEG pairs were also implicated in asparagus sexual development. Our study identified a large number of DEGs involved in the sex expression and reproduction of asparagus, including known genes participating in plant reproduction, plant hormone signaling, TF encoding, and genes with unclear functions. We also found that miRNAs might be involved in the sex differentiation process. Our study could provide a valuable basis for further investigations on the regulatory networks of sex determination and differentiation in asparagus and facilitate further genetic and genomic studies on this dioecious species.

Assessing a new gene expression analysis technique for radiation biodosimetry applications

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Manning, Grainne; Kabacik, Sylwia; Finnon, Paul; Paillier, Francois; Bouffler, Simon [Cancer Genetics and Cytogenetics, Biological Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Health Protection Agency, Chilton, Didcot, Oxfordshire OX11 ORQ (United Kingdom); Badie, Christophe, E-mail: christophe.badie@hpa.org.uk [Cancer Genetics and Cytogenetics, Biological Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Health Protection Agency, Chilton, Didcot, Oxfordshire OX11 ORQ (United Kingdom)

2011-09-15

The response to any radiation accident or incident involving actual or potential ionising radiation exposure requires accurate and rapid assessment of the doses received by individuals. The techniques available today for biodosimetry purposes are not fully adapted to rapid high-throughput measurements of exposures in large numbers of individuals. A recently emerging technique is based on gene expression analysis, as there are a number of genes which are radiation responsive in a dose-dependent manner. The present work aimed to assess a new technique which allows the detection of the level of expression of up to 800 genes without need of enzymatic reactions. In order to do so, human peripheral blood was exposed ex vivo to a range of x-ray doses from 5 mGy to 4 Gy of x-rays and the transcriptional expression of five radiation-responsive genes PHPT1, PUMA, CCNG1, DDB2 and MDM2 was studied by both the nCounter Digital Analyzer and Multiplex Quantitative Real-Time Polymerase Chain Reaction (MQRT-PCR) as the benchmark technology. Results from both techniques showed good correlation for all genes with R{sup 2} values ranging between 0.8160 and 0.9754. The reproducibility of the nCounter Digital Analyzer was also assessed in independent biological replicates and proved to be good. Although the slopes of the correlation of results obtained by the techniques suggest that MQRT-PCR is more sensitive than the nCounter Digital Analyzer, the nCounter Digital Analyzer provides sensitive and reliable data on modifications in gene expression in human blood exposed to radiation without enzymatic amplification of RNA prior to analysis.

Interleukin 1 beta gene and risk of schizophrenia: detailed case-control and family-based studies and an updated meta-analysis.

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Shibuya, Masako; Watanabe, Yuichiro; Nunokawa, Ayako; Egawa, Jun; Kaneko, Naoshi; Igeta, Hirofumi; Someya, Toshiyuki

2014-01-01

Interleukin-1 beta (IL-1β) has been implicated in the pathophysiology of schizophrenia. To assess whether the IL1B gene confers increased susceptibility to schizophrenia, we conducted case-control and family-based studies and an updated meta-analysis. We tested the association between IL1B and schizophrenia in 1229 case-control and 112 trio samples using 12 markers, including common tagging single nucleotide variations (SNVs) and a rare non-synonymous variation detected by resequencing the coding regions. We also performed a meta-analysis of rs16944 using a total of 8724 case-control and 201 trio samples from 16 independent populations. We found no significant associations between any of the 12 SNVs examined and schizophrenia in either case-control or trio samples. Moreover, our meta-analysis results showed no significant association between the common SNV, rs16944, and schizophrenia. The present study does not support a role for IL1B in schizophrenia susceptibility.

Bayesian Modeling of MPSS Data: Gene Expression Analysis of Bovine Salmonella Infection

KAUST Repository

Dhavala, Soma S.

2010-09-01

Massively Parallel Signature Sequencing (MPSS) is a high-throughput, counting-based technology available for gene expression profiling. It produces output that is similar to Serial Analysis of Gene Expression and is ideal for building complex relational databases for gene expression. Our goal is to compare the in vivo global gene expression profiles of tissues infected with different strains of Salmonella obtained using the MPSS technology. In this article, we develop an exact ANOVA type model for this count data using a zero-inflatedPoisson distribution, different from existing methods that assume continuous densities. We adopt two Bayesian hierarchical models-one parametric and the other semiparametric with a Dirichlet process prior that has the ability to "borrow strength" across related signatures, where a signature is a specific arrangement of the nucleotides, usually 16-21 base pairs long. We utilize the discreteness of Dirichlet process prior to cluster signatures that exhibit similar differential expression profiles. Tests for differential expression are carried out using nonparametric approaches, while controlling the false discovery rate. We identify several differentially expressed genes that have important biological significance and conclude with a summary of the biological discoveries. This article has supplementary materials online. © 2010 American Statistical Association.

Bayesian Modeling of MPSS Data: Gene Expression Analysis of Bovine Salmonella Infection

KAUST Repository

Dhavala, Soma S.; Datta, Sujay; Mallick, Bani K.; Carroll, Raymond J.; Khare, Sangeeta; Lawhon, Sara D.; Adams, L. Garry

2010-01-01

Massively Parallel Signature Sequencing (MPSS) is a high-throughput, counting-based technology available for gene expression profiling. It produces output that is similar to Serial Analysis of Gene Expression and is ideal for building complex relational databases for gene expression. Our goal is to compare the in vivo global gene expression profiles of tissues infected with different strains of Salmonella obtained using the MPSS technology. In this article, we develop an exact ANOVA type model for this count data using a zero-inflatedPoisson distribution, different from existing methods that assume continuous densities. We adopt two Bayesian hierarchical models-one parametric and the other semiparametric with a Dirichlet process prior that has the ability to "borrow strength" across related signatures, where a signature is a specific arrangement of the nucleotides, usually 16-21 base pairs long. We utilize the discreteness of Dirichlet process prior to cluster signatures that exhibit similar differential expression profiles. Tests for differential expression are carried out using nonparametric approaches, while controlling the false discovery rate. We identify several differentially expressed genes that have important biological significance and conclude with a summary of the biological discoveries. This article has supplementary materials online. © 2010 American Statistical Association.

Expression analysis of the Theileria parva subtelomere-encoded variable secreted protein gene family.

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Jacqueline Schmuckli-Maurer

Full Text Available The intracellular protozoan parasite Theileria parva transforms bovine lymphocytes inducing uncontrolled proliferation. Proteins released from the parasite are assumed to contribute to phenotypic changes of the host cell and parasite persistence. With 85 members, genes encoding subtelomeric variable secreted proteins (SVSPs form the largest gene family in T. parva. The majority of SVSPs contain predicted signal peptides, suggesting secretion into the host cell cytoplasm.We analysed SVSP expression in T. parva-transformed cell lines established in vitro by infection of T or B lymphocytes with cloned T. parva parasites. Microarray and quantitative real-time PCR analysis revealed mRNA expression for a wide range of SVSP genes. The pattern of mRNA expression was largely defined by the parasite genotype and not by host background or cell type, and found to be relatively stable in vitro over a period of two months. Interestingly, immunofluorescence analysis carried out on cell lines established from a cloned parasite showed that expression of a single SVSP encoded by TP03_0882 is limited to only a small percentage of parasites. Epitope-tagged TP03_0882 expressed in mammalian cells was found to translocate into the nucleus, a process that could be attributed to two different nuclear localisation signals.Our analysis reveals a complex pattern of Theileria SVSP mRNA expression, which depends on the parasite genotype. Whereas in cell lines established from a cloned parasite transcripts can be found corresponding to a wide range of SVSP genes, only a minority of parasites appear to express a particular SVSP protein. The fact that a number of SVSPs contain functional nuclear localisation signals suggests that proteins released from the parasite could contribute to phenotypic changes of the host cell. This initial characterisation will facilitate future studies on the regulation of SVSP gene expression and the potential biological role of these enigmatic

16S Ribosomal Ribonucleic Acid Gene Polymerase Chain Reaction in the Diagnosis of Bloodstream Infections: A Systematic Review and Meta-Analysis.

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Su, Guoming; Fu, Zhuqing; Hu, Liren; Wang, Yueying; Zhao, Zuguo; Yang, Weiqing

2015-01-01

We aim to evaluate the accuracy of the 16S ribosomal ribonucleic acid (rRNA) gene polymerase chain reaction (PCR) test in the diagnosis of bloodstream infections through a systematic review and meta-analysis. A computerized literature search was conducted to identify studies that assessed the diagnostic value of 16S rRNA gene PCR test for bloodstream infections. Study quality was assessed using the revised Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. We calculated the sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR) and their 95% confidence intervals (95% CI) for each study. Summary receiver operating characteristic (SROC) curve was used to summarize overall test performance. Statistical analysis was performed in Meta-DiSc 1.4 and Stata/SE 12.0 software. Twenty-eight studies were included in our meta-analysis. Using random-effect model analysis, the pooled sensitivity, specificity, PLR, NLR, and DOR were 0.87 (95% CI, 0.85-0.89), 0.94 (95% CI, 0.93-0.95), 12.65 (95% CI, 8.04-19.90), 0.14 (95% CI, 0.08-0.24), and 116.76 (95% CI, 52.02-262.05), respectively. The SROC curve indicated that the area under the curve (AUC) was 0.9690 and the maximum joint sensitivity and specificity (Q*) was 0.9183. In addition, heterogeneity was statistically significant but was not caused by the threshold effect. Existing data suggest that 16S rRNA gene PCR test is a practical tool for the rapid screening of sepsis. Further prospective studies are needed to assess the diagnostic value of PCR amplification and DNA microarray hybridization of 16S rRNA gene in the future.

Gene expression analysis reveals new possible mechanisms of vancomycin-induced nephrotoxicity and identifies gene markers candidates.

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Dieterich, Christine; Puey, Angela; Lin, Sylvia; Lyn, Sylvia; Swezey, Robert; Furimsky, Anna; Fairchild, David; Mirsalis, Jon C; Ng, Hanna H

2009-01-01

Vancomycin, one of few effective treatments against methicillin-resistant Staphylococcus aureus, is nephrotoxic. The goals of this study were to (1) gain insights into molecular mechanisms of nephrotoxicity at the genomic level, (2) evaluate gene markers of vancomycin-induced kidney injury, and (3) compare gene expression responses after iv and ip administration. Groups of six female BALB/c mice were treated with seven daily iv or ip doses of vancomycin (50, 200, and 400 mg/kg) or saline, and sacrificed on day 8. Clinical chemistry and histopathology demonstrated kidney injury at 400 mg/kg only. Hierarchical clustering analysis revealed that kidney gene expression profiles of all mice treated at 400 mg/kg clustered with those of mice administered 200 mg/kg iv. Transcriptional profiling might thus be more sensitive than current clinical markers for detecting kidney damage, though the profiles can differ with the route of administration. Analysis of transcripts whose expression was changed by at least twofold compared with vehicle saline after high iv and ip doses of vancomycin suggested the possibility of oxidative stress and mitochondrial damage in vancomycin-induced toxicity. In addition, our data showed changes in expression of several transcripts from the complement and inflammatory pathways. Such expression changes were confirmed by relative real-time reverse transcription-polymerase chain reaction. Finally, our results further substantiate the use of gene markers of kidney toxicity such as KIM-1/Havcr1, as indicators of renal injury.

Validation of reference genes for gene expression analysis in olive (Olea europaea) mesocarp tissue by quantitative real-time RT-PCR

Science.gov (United States)

2014-01-01

Background Gene expression analysis using quantitative reverse transcription PCR (qRT-PCR) is a robust method wherein the expression levels of target genes are normalised using internal control genes, known as reference genes, to derive changes in gene expression levels. Although reference genes have recently been suggested for olive tissues, combined/independent analysis on different cultivars has not yet been tested. Therefore, an assessment of reference genes was required to validate the recent findings and select stably expressed genes across different olive cultivars. Results A total of eight candidate reference genes [glyceraldehyde 3-phosphate dehydrogenase (GAPDH), serine/threonine-protein phosphatase catalytic subunit (PP2A), elongation factor 1 alpha (EF1-alpha), polyubiquitin (OUB2), aquaporin tonoplast intrinsic protein (TIP2), tubulin alpha (TUBA), 60S ribosomal protein L18-3 (60S RBP L18-3) and polypyrimidine tract-binding protein homolog 3 (PTB)] were chosen based on their stability in olive tissues as well as in other plants. Expression stability was examined by qRT-PCR across 12 biological samples, representing mesocarp tissues at various developmental stages in three different olive cultivars, Barnea, Frantoio and Picual, independently and together during the 2009 season with two software programs, GeNorm and BestKeeper. Both software packages identified GAPDH, EF1-alpha and PP2A as the three most stable reference genes across the three cultivars and in the cultivar, Barnea. GAPDH, EF1-alpha and 60S RBP L18-3 were found to be most stable reference genes in the cultivar Frantoio while 60S RBP L18-3, OUB2 and PP2A were found to be most stable reference genes in the cultivar Picual. Conclusions The analyses of expression stability of reference genes using qRT-PCR revealed that GAPDH, EF1-alpha, PP2A, 60S RBP L18-3 and OUB2 are suitable reference genes for expression analysis in developing Olea europaea mesocarp tissues, displaying the highest level

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

Directory of Open Access Journals (Sweden)

Xing Ding

2018-05-01

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

Long SAGE analysis of genes differentially expressed in the midgut ...

African Journals Online (AJOL)

Long SAGE analysis of genes differentially expressed in the midgut and silk gland between the sexes of the silkwormBombyx mori. Liping Gan, Ying Wang, Jian Xi, Yanshan Niu, Hongyou Qin, Yanghu Sima, Shiqing Xu ...

Gene expression profiling of low-grade endometrial stromal sarcoma indicates fusion protein-mediated activation of the Wnt signaling pathway.

Science.gov (United States)

Przybyl, Joanna; Kidzinski, Lukasz; Hastie, Trevor; Debiec-Rychter, Maria; Nusse, Roel; van de Rijn, Matt

2018-05-01

Low-grade endometrial stromal sarcomas (LGESS) harbor chromosomal translocations that affect proteins associated with chromatin remodeling Polycomb Repressive Complex 2 (PRC2), including SUZ12, PHF1 and EPC1. Roughly half of LGESS also demonstrate nuclear accumulation of β-catenin, which is a hallmark of Wnt signaling activation. However, the targets affected by the fusion proteins and the role of Wnt signaling in the pathogenesis of these tumors remain largely unknown. Here we report the results of a meta-analysis of three independent gene expression profiling studies on LGESS and immunohistochemical evaluation of nuclear expression of β-catenin and Lef1 in 112 uterine sarcoma specimens obtained from 20 LGESS and 89 LMS patients. Our results demonstrate that 143 out of 310 genes overexpressed in LGESS are known to be directly regulated by SUZ12. In addition, our gene expression meta-analysis shows activation of multiple genes implicated in Wnt signaling. We further emphasize the role of the Wnt signaling pathway by demonstrating concordant nuclear expression of β-catenin and Lef1 in 7/16 LGESS. Based on our findings, we suggest that LGESS-specific fusion proteins disrupt the repressive function of the PRC2 complex similar to the mechanism seen in synovial sarcoma, where the SS18-SSX fusion proteins disrupt the mSWI/SNF (BAF) chromatin remodeling complex. We propose that these fusion proteins in LGESS contribute to overexpression of Wnt ligands with subsequent activation of Wnt signaling pathway and formation of an active β-catenin/Lef1 transcriptional complex. These observations could lead to novel therapeutic approaches that focus on the Wnt pathway in LGESS. Copyright © 2018 Elsevier Inc. All rights reserved.

In-silico gene co-expression network analysis in Paracoccidioides brasiliensis with reference to haloacid dehalogenase superfamily hydrolase gene