Homo sapiens
Ontology highlight
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PROVIDER: PRJNA173725 | ENA |
REPOSITORIES: ENA
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Project description:Motivation: Identification of eQTL, the genetic loci that contribute to heritable variation in gene expression, can be obstructed by factors that produce variation in expression profiles if these factors are unmeasured or hidden from direct analysis. Methods: We have developed a method for Hidden Expression Factor analysis (HEFT) that identifies individual and pleiotropic effects of eQTL in the presence of hidden factors. The HEFT model simultaneously accounts for the effects of genotypes while learning hidden factors, where we make use of the complete likelihood of a unified multivariate regression and factor analysis model to derive a ridge estimator for combined factor learning and detection of eQTL. HEFT requires no pre-estimation of hidden factor effects, no iterative model selection, it provides p-values, and is extremely fast, requiring just a few hours to complete an eQTL analysis of thousands of expression variables when analyzing hundreds of thousands of SNPs on a standard 8 core 2.6G desktop. Results: By analyzing simulated data, we demonstrate that HEFT can correct for an unknown number of hidden factors and outperforms related hidden factor methods for eQTL analysis, where the improved performance is particularly evident in the detection of eQTL with multivariate effects. To demonstrate a real-world application, we applied HEFT to identify eQTL affecting gene expression in human lung tissue for a study that included presumptive hidden factors. The analysis identified a number of eQTL with direct relevance to lung disease that could not be found without a hidden factor analysis, including cis-eQTL for GTF2H1 and MTRR, genes that have been independently associated with lung cancer. We have developed HEFT, a fast multivariate method that detect eQTLs by analyzing thousands of traits simultaneously in the presence of hidden factors. HEFT employs a combined regression factor analysis approach to analyze the gene expression and genotype data sets, looking for univariate or multivariate eQTLs that regulate gene expression, while simultaneously controlling for both orthogonal or non-orthogonal hidden factors. We show by extensive simulation that HEFT outperforms competing methods, and by applying HEFT to a study that included presumptive hidden factors, we identified a number of eQTL with direct relevance to lung disease that could not be found without a hidden factor analysis. HEFT analysis results file (includes all results, not just top hits) linked below as supplementary file.
2014-01-07 | E-GEOD-40364 | biostudies-arrayexpress
Project description:Motivation: Identification of eQTL, the genetic loci that contribute to heritable variation in gene expression, can be obstructed by factors that produce variation in expression profiles if these factors are unmeasured or hidden from direct analysis. Methods: We have developed a method for Hidden Expression Factor analysis (HEFT) that identifies individual and pleiotropic effects of eQTL in the presence of hidden factors. The HEFT model simultaneously accounts for the effects of genotypes while learning hidden factors, where we make use of the complete likelihood of a unified multivariate regression and factor analysis model to derive a ridge estimator for combined factor learning and detection of eQTL. HEFT requires no pre-estimation of hidden factor effects, no iterative model selection, it provides p-values, and is extremely fast, requiring just a few hours to complete an eQTL analysis of thousands of expression variables when analyzing hundreds of thousands of SNPs on a standard 8 core 2.6G desktop. Results: By analyzing simulated data, we demonstrate that HEFT can correct for an unknown number of hidden factors and outperforms related hidden factor methods for eQTL analysis, where the improved performance is particularly evident in the detection of eQTL with multivariate effects. To demonstrate a real-world application, we applied HEFT to identify eQTL affecting gene expression in human lung tissue for a study that included presumptive hidden factors. The analysis identified a number of eQTL with direct relevance to lung disease that could not be found without a hidden factor analysis, including cis-eQTL for GTF2H1 and MTRR, genes that have been independently associated with lung cancer.
2014-01-07 | GSE40364 | GEO
Project description:We performed expression quantitative trait locus (eQTL) mapping between two strains of Tetranychus urticae (the two-spotted spider mite), a generalist herbivore known for its rapid evolution of acaricide resistance. For parents, we used the inbred strain MR-VPi that is highly resistant to multiple acaricides in different classes, and the inbred strain ROS-ITi that is comparatively susceptible to many acaricides. The eQTL mapping experiment was performed with F3 samples, and thousands of trans and cis eQTL were identified, including for genes in families known (or suspected) to be involved in the metabolism of xenobiotics (plant produced secondary compounds and acaricides). One trans eQTL hotspot was identified that strongly impacted the expression of many detoxification genes in different gene families. Follow up studies using derived near isogenic lines validated the trans eQTL hotspot, and RNA interference (RNAi) knockdown of tandemly duplicated genes encoding products with homology to the ligand binding domains of nuclear hormone receptor 96 genes impacted many of the same detoxification genes controlled by the hotspot.
2023-07-14 | GSE221677 | GEO
Project description:<p>Schizophrenia is a common and severe psychotic disorder. While some common SNPs and rare copy number variants have been identified as being significantly associated with disease risk, the biological mechanisms remain undefined. To identify gene expression abnormalities in schizophrenia, we generated whole-genome gene expression profiles using microarrays on lymphoblastoid cell lines from a total of 413 cases and 446 controls. Regression analysis identified 95 transcripts differentially expressed by affection status at a genome-wide false discovery rate of 0.05, while simultaneously controlling for confounding effects. These transcripts represented 89 genes with functions such as neurotransmission, gene regulation, cell cycle progression, differentiation, apoptosis, and immunity. The observed differential expression of extended major histocompatibility complex region genes converges with the genetic evidence from schizophrenia genome-wide association studies, which find the same region to be the most significant schizophrenia susceptibility locus. Our analysis also provides novel candidate genes for further study to assess their potential contribution to schizophrenia.</p>
| phs000775 | dbGaP
Project description:Background: Expression QTL analyses have shed light on transcriptional regulation in numerous species of plants, animals, and yeasts. These microarray-based analyses identify regulators of gene expression as either cis-acting factors that regulate proximal genes, or trans-acting factors that function through a variety of mechanisms to affect transcript abundance of unlinked genes. Results: A hydroponics-based genetical genomics study in roots of a Zea mays IBM2 Syn10 double haploid population identified tens of thousands of cis-acting and trans-acting eQTL. Cases of false-positive eQTL, which results from the lack of complete genomic sequences from both parental genomes, were described. A candidate gene for a trans-acting regulatory factor was identified through positional cloning. The unexpected regulatory function of a class I glutamine amidotransferase controls the expression of an ABA 8’-hydroxylase pseudogene.
2011-06-22 | GSE29964 | GEO
Project description:Analyses of QTLs for expression levels (eQTLs) of the genes reveal genetic relationship between expression variation and the regulator, thus unlocking the information for identifying the regulatory network. Oligo-nucleotide expression microarrays hybridized with RNA can simultaneously provide data for molecular markers and transcript abundance. In this study, we used Affymetrix GeneChip Rice Genome Array to analyze eQTLs in rice shoots at 72 h after germination from 110 recombinant inbred lines (RILs) derived from a cross between Zhenshan 97 and Minghui 63. Totally 1,632 single feature polymorphisms (SFPs) plus 23 PCR markers were identified and placed into 601 recombinant bins, spanning 1,459 cM in length, which were used as markers to genotype the RILs. We obtained 16,372 expression traits (e-traits) each with at least one eQTL, resulting in 26,051 eQTLs in total, including both cis- and trans-eQTLs. We also identified 171 eQTL hotspots among rice genome, each of which controls transcript variations of many e-traits. Gene Ontology analysis revealed enrichment of certain functional categories of genes in some of the eQTL hotspots. In particular, eQTLs for e-traits involving DNA metabolic process was significantly enriched in several eQTL hotspots on chromosomes 3, 5 and 10. Several transcription factors colocalizing with cis-eQTLs showed significant correlations with hundreds of e-traits, indicating possible co-regulation. We also detected correlations between the QTLs for shoot dry weight and eQTLs, revealing possible candidate genes for the trait. These results provided the clues for identification and characterization of regulatory network in the whole genome at the transcriptional level.
2011-06-24 | GSE22564 | GEO
Project description:<p>Follicular lymphoma (FL) is a generally incurable B-cell malignancy which has the potential to transform into highly aggressive lymphomas. Genomic studies indicate it is often a small subpopulation rather than the dominant population in the FL that gives rise to the more aggressive subtype. To resolve the underlying transcriptional networks of follicular B-cell lymphomas at single molecule and cell resolution, we leveraged droplet-based barcoding technology for highly parallel single cell RNA-Seq. We analyzed the transcriptomes from tens of thousands of cells derived from five primary FL tumors. Simultaneously, we conducted multi-dimensional flow cell sorting to validate our characterizing of cellular lineages and critical expressed proteins. For each tumor, we identified multiple cellular subpopulations, matching known hematopoietic lineages. Comparison of gene expression by matched malignant and normal B cells from the same patient revealed tumor-specific features. Malignant B cells exhibited restricted immunoglobulin light chain expression (either Ig Kappa or Ig Lambda), as well the expected upregulation of the BCL2 gene, but also down-regulation of the FCER2, CD52 and MHC class II genes. By leveraging the single-cell resolution on large numbers of cells per patient, we were able to examine tumor-resident T cells. We identified pairs of immune checkpoint molecules that were co-expressed, providing a potentially useful strategy for selection of patient-tailored combination immunotherapies. In summary, massively parallel measurement of single-cell expression in thousands of tumor cells and tumor-resident lymphocytes can be used to obtain a systems-level view of the tumor microenvironment and identify new avenues for therapeutic development.</p>
| phs001378 | dbGaP
Project description:Analyses of QTLs for expression levels (eQTLs) of the genes reveal genetic relationship between expression variation and the regulator, thus unlocking the information for identifying the regulatory network. Oligo-nucleotide expression microarrays hybridized with RNA can simultaneously provide data for molecular markers and transcript abundance. In this study, we used Affymetrix GeneChip Rice Genome Array to analyze eQTLs in rice shoots at 72 h after germination from 110 recombinant inbred lines (RILs) derived from a cross between Zhenshan 97 and Minghui 63. Totally 1,632 single feature polymorphisms (SFPs) plus 23 PCR markers were identified and placed into 601 recombinant bins, spanning 1,459 cM in length, which were used as markers to genotype the RILs. We obtained 16,372 expression traits (e-traits) each with at least one eQTL, resulting in 26,051 eQTLs in total, including both cis- and trans-eQTLs. We also identified 171 eQTL hotspots among rice genome, each of which controls transcript variations of many e-traits. Gene Ontology analysis revealed enrichment of certain functional categories of genes in some of the eQTL hotspots. In particular, eQTLs for e-traits involving DNA metabolic process was significantly enriched in several eQTL hotspots on chromosomes 3, 5 and 10. Several transcription factors colocalizing with cis-eQTLs showed significant correlations with hundreds of e-traits, indicating possible co-regulation. We also detected correlations between the QTLs for shoot dry weight and eQTLs, revealing possible candidate genes for the trait. These results provided the clues for identification and characterization of regulatory network in the whole genome at the transcriptional level. To dissect the genetic variation between the two rice indica varieties Minghui 63 and Zhenshan 97, a total of 110 RILs from Minghui 63 and Zhenshan 97 and parents were sampled. And the Affymetrix Genechip rice Genome Array was used to investigate their dynamic transcript levels. Two independent biological replicates were sampled from each RIL, and three replicates for each parent.resulting in a dataset of 226 microarrays.
2011-06-24 | E-GEOD-22564 | biostudies-arrayexpress
Project description:Heterosis (hybrid vigor) refers to the superior performance of hybrid progeny relative to their parents. Although widely exploited in agriculture, the mechanisms responsible for heterosis are not well understood. As a monoecious organism, a given maize plant can be used as both male and female parents of crosses. Regardless of the cross direction, the maize inbred lines B73 and Mo17 produce hybrids that substantially out-perform their parents. These reciprocal hybrids differ phenotypically from each other despite having identical nuclear genomes. Consistent with these phenotypic observations, 30-50% of genes were differentially expressed between these reciprocal hybrids. An eQTL experiment conducted to better understand the regulation of gene expression in inbred and hybrid lines detected ~4,000 eQTL associations. The majority of these eQTL act in trans to regulate expression of genes on other chromosomes. Surprisingly, many of the trans-eQTL, when heterozygous, differentially regulated transcript accumulation in a manner consistent with gene expression in the hybrid being regulated exclusively by the paternally transmitted allele. The design of the eQTL experiment controlled for cytoplasmic and maternal effects, suggesting that widespread paternal genomic imprinting contributes to the regulation of gene expression in maize hybrids. Keywords: eQTL, parent-of-origin
2009-11-20 | GSE16136 | GEO
Project description:Microarray technologies,which can measure the expression of thousands of genes simultaneously are useful in understanding global gene networks and identifying novel genes and functional gene classes.The adipose depots may have various adipogenic state-specific genes and regulations of adipose accretion patterns in beef cattle.Therefore,the purpose of this study was to examine the molecular mechanisms of longissimus dorsi muscle,subcutaneous and abdominal adipose tissue depots in a native Chinese yellow breed by identifying differentially expressed genes using Bovine Genome Array.The GO and pathway analysis further validated differentially expressed genes identified in array analysis.
2016-08-18 | GSE49992 | GEO