Genetic analysis of isoform usage in the human anti-viral response
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE92904 | GEO | 2018/10/04
REPOSITORIES: GEO
Similar Datasets
Project description:Genetic variants that impact gene regulation are important contributors to human phenotypic variation. For this reason, considerable efforts have been made to identify genetic associations with differences in mRNA levels of nearby genes, namely, cis expression quantitative trait loci (eQTLs). The phenotypic consequences of eQTLs are presumably due, in most cases, to their ultimate effects on protein expression levels. Yet, only few studies have quantified the impact of genetic variation on proteins levels directly. It remains unclear how faithfully eQTLs are reflected at the protein level, and whether there is a significant layer of cis regulatory variation acting primarily on translation or steady state protein levels. To address these questions, we measured ribosome occupancy by high-throughput sequencing, and relative protein levels by high-resolution quantitative mass spectrometry, in a panel of lymphoblastoid cell lines (LCLs) in which we had previously measured transcript expression using RNA sequencing. We then mapped genetic variants that are associated with changes in transcript expression (eQTLs), ribosome occupancy (rQTLs), or protein abundance (pQTLs). Most of the QTLs we detected are associated with transcript expression levels, with consequent effects on ribosome and protein levels. However, we found that eQTLs tend to have significantly reduced effect sizes on protein levels, suggesting that their potential impact on downstream phenotypes is often attenuated or buffered. Additionally, we confirmed the presence of a class of cis QTLs that specifically affect protein abundance with little or no effect on mRNA levels; most of these QTLs have little effect on ribosome occupancy, and hence may arise from differences in post-translational regulation.
2014-12-19 | PXD001406 | Pride
Project description:Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2,112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters, and enrichment of co-localised functional elements. We found eQTLs for about 85% of analysed genes, 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 MB to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might often be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels, and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. We show for strongly heritable transcripts that a considerable gap still exists between total heritability resulting from all trans-chromosomes and explained variance of all identified trans-eSNPs. In contrast, the vast majority of most cis-heritability of these genes is already explained. Dissection of co-localised functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene-expression, pathways and disease related processes. Gene expression from human blood mononuclear cells from individuals of the Leipzig LIFE Heart Study was analyzed applying Illumina HT-12 v4 Expression BeadChips. After preprocessing, 28,295 expression probes for 2,112 individuals remained for analysis. In a population-based analysis, we identified associations between DNA variants and RNA expression levels and characterized these findings.
2015-06-29 | E-GEOD-65907 | biostudies-arrayexpress
Project description:A proportion of the genetic variants underlying complex phenotypes do so through their effects on gene expression, so an important challenge in complex trait analysis is to discover the genetic basis for the variation in transcript abundance. So far, the potential of mapping both quantitative trait loci (QTLs) and expression quantitative trait loci (eQTLs) in rodents has been limited by the low mapping resolution inherent in crosses between inbred strains. We provide a megabase resolution map of thousands of eQTLs in hippocampus, lung, and liver samples from heterogeneous stock (HS) mice in which 843 QTLs have also been mapped at megabase resolution. We exploit dense mouse SNP data to show that artifacts due to allele-specific hybridization occur in _30% of the cis-acting eQTLs and, by comparison with exon expression data, we show that alternative splicing of the 3_ end of the genes accounts for <1% of cis-acting eQTLs. Approximately one third of cis-acting eQTLs and one half of trans-acting eQTLs are tissue specific. We have created an important systems biology resource for the genetic analysis of complex traits in a key model organism.
2009-10-22 | E-MTAB-88 | biostudies-arrayexpress
Project description:Genetic variants that impact gene regulation are important contributors to human phenotypic variation. For this reason, considerable efforts have been made to identify genetic associations with differences in mRNA levels of nearby genes, namely, cis expression quantitative trait loci (eQTLs). The phenotypic consequences of eQTLs are presumably due, in most cases, to their ultimate effects on protein expression levels. Yet, only few studies have quantified the impact of genetic variation on proteins levels directly. It remains unclear how faithfully eQTLs are reflected at the protein level, and whether there is a significant layer of cis regulatory variation acting primarily on translation or steady state protein levels. To address these questions, we measured ribosome occupancy by high-throughput sequencing, and relative protein levels by high-resolution quantitative mass spectrometry, in a panel of lymphoblastoid cell lines (LCLs) in which we had previously measured transcript expression using RNA sequencing. We then mapped genetic variants that are associated with changes in transcript expression (eQTLs), ribosome occupancy (rQTLs), or protein abundance (pQTLs). Most of the QTLs we detected are associated with transcript expression levels, with consequent effects on ribosome and protein levels. However, we found that eQTLs tend to have significantly reduced effect sizes on protein levels, suggesting that their potential impact on downstream phenotypes is often attenuated or buffered. Additionally, we confirmed the presence of a class of cis QTLs that specifically affect protein abundance with little or no effect on mRNA levels; most of these QTLs have little effect on ribosome occupancy, and hence may arise from differences in post-translational regulation. We measured level of translation transcriptome-wide in lymphoblastoid cell lines derived from 72 HapMap Yoruba individuals using ribosome profiling assay, for which we have transcript level, protein level (62 out of 72) and genotype information collected.
2014-12-19 | E-GEOD-61742 | biostudies-arrayexpress
Project description:African Americans (AAs) are disproportionately affected by metabolic diseases and adverse drug events, with limited publicly available genomic and transcriptomic data to advance the knowledge of the molecular underpinnings or genetic associations to these diseases or drug response phenotypes. To fill this gap, we obtained 60 primary hepatocyte cultures from AA liver donors for genome-wide mapping of expression quantitative trait loci (eQTL) using LAMatrix. We identified 277 eGenes and 19,770 eQTLs, of which 67 eGenes and 7,415 eQTLs are not observed in the Genotype-Tissue Expression Project (GTEx) liver eQTL analysis. Of the eGenes found in GTEx only 25 share the same lead eQTL. These AA-specific eQTLs are less correlated to GTEx eQTL in effect sizes and have larger Fst values compared to eQTLs found in both cohorts (overlapping eQTLs). We assessed the overlap between GWAS variants and their tagging variants with AA hepatocyte eQTLs and demonstrated that AA hepatocyte eQTLs can decrease the number of potential causal variants at GWAS loci. Additionally, we identified 75,002 exon QTLs of which 48.8% are not eQTLs in AA hepatocytes. Our analysis provides the first comprehensive characterization of AA hepatocyte eQTLs and highlights the unique discoveries that are made possible due to the increased genetic diversity within the African ancestry genome.
2020-03-27 | GSE147628 | GEO
Project description:Genetic variants that impact gene regulation are important contributors to human phenotypic variation. For this reason, considerable efforts have been made to identify genetic associations with differences in mRNA levels of nearby genes, namely, cis expression quantitative trait loci (eQTLs). The phenotypic consequences of eQTLs are presumably due, in most cases, to their ultimate effects on protein expression levels. Yet, only few studies have quantified the impact of genetic variation on proteins levels directly. It remains unclear how faithfully eQTLs are reflected at the protein level, and whether there is a significant layer of cis regulatory variation acting primarily on translation or steady state protein levels. To address these questions, we measured ribosome occupancy by high-throughput sequencing, and relative protein levels by high-resolution quantitative mass spectrometry, in a panel of lymphoblastoid cell lines (LCLs) in which we had previously measured transcript expression using RNA sequencing. We then mapped genetic variants that are associated with changes in transcript expression (eQTLs), ribosome occupancy (rQTLs), or protein abundance (pQTLs). Most of the QTLs we detected are associated with transcript expression levels, with consequent effects on ribosome and protein levels. However, we found that eQTLs tend to have significantly reduced effect sizes on protein levels, suggesting that their potential impact on downstream phenotypes is often attenuated or buffered. Additionally, we confirmed the presence of a class of cis QTLs that specifically affect protein abundance with little or no effect on mRNA levels; most of these QTLs have little effect on ribosome occupancy, and hence may arise from differences in post-translational regulation.
2014-12-19 | GSE61742 | GEO
Project description:Understanding the genetic mechanisms underlying natural variation in gene expression is a central goal of both medical and evolutionary genetics, and studies of expression quantitative trait loci (eQTLs) have become an important tool for achieving this goal. While all eQTL studies to date have assayed mRNA levels using expression microarrays, recent advances in RNA sequencing enable the analysis of transcript variation at unprecedented resolution. We sequenced RNA from 69 lymphoblastoid cell lines (LCLs) derived from unrelated Nigerian individuals that have been extensively genotyped by the International HapMap Project. Pooling data from all individuals, we generated a map of the transcriptional landscape of these cells, identifying extensive use of unannotated polyadenylation sites and over 100 novel putative protein-coding exons. Using the genotypes from the HapMap project, we identified over a thousand genes at which genetic variation influences overall expression levels or splicing. We demonstrate that eQTLs near genes generally act via a mechanism involving allele-specific expression, and that variation that influences the inclusion of an exon is enriched within or near the consensus splice sites. Our results illustrate the power of high-throughput sequencing for the joint analysis of variation in transcription, splicing, and allele-specific expression across individuals. RNA-Seq in 69 lymphoblastoid cell lines from multiple Yoruban HapMap individuals in at least two replicate lanes per individual
2010-02-28 | E-GEOD-19480 | biostudies-arrayexpress
Project description:We designed a massively parallel reporter assay (MPRA) in an Epstein-Barr virus transformed B cell line to directly characterize the potential for histone post-translational modifications, i.e., histone quantitative trait loci (hQTLs), expression QTLs (eQTLs), and variants on SLE and autoimmune (AI) disease risk haplotypes to modulate regulatory activity in an allele dependent manner. Our study demonstrates that hQTLs, as a group, are more likely to modulate regulatory activity in an MPRA compared to other variant classes tested, including a set of eQTLs previously shown to interact with hQTLs and tested AI risk variants. In addition, we nominate 17 variants (including 11 previously unreported) as putative causal variants for SLE and another 14 for various other AI diseases, prioritizing these variants for future functional studies primary and immortalized B cells. Thus, we uncover important insights into the mechanistic relationships between genotype, epigenetics, and gene expression in SLE and AI disease phenotypes.
2024-03-10 | GSE254502 | GEO
Project description:Genome-wide association studies have identified thousands of non-coding variants that are statistically associated with human traits and diseases. However, functional interpretation of these variants remains a major challenge. Here, we describe the first atlas of human 3’-UTR alternative polyadenylation (APA) Quantitative Trait Loci (3′aQTLs), i.e. ~0.4 million genetic variants associated with APA of target genes across 46 Genotype-Tissue Expression (GTEx) tissues from 467 individuals. APA occurs in approximately 70% of human genes and substantively impacts cellular proliferation, differentiation and tumorigenesis. Mechanistically, 3′aQTLs could alter polyA motifs and RNA-binding protein binding sites, leading to thousands of APA changes. Importantly, 3′aQTLs can be used to interpret ~16.1% of trait-associated variants and are largely distinct from other QTLs such as eQTLs. These 3′aQTLs thus represent the genetic basis of APA as a novel molecular phenotype to explain a large fraction of non-coding variants and to provide new insights into complex traits and disease etiologies.
2020-05-02 | GSE139548 | GEO
Project description:Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2,112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters, and enrichment of co-localised functional elements. We found eQTLs for about 85% of analysed genes, 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 MB to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might often be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels, and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. We show for strongly heritable transcripts that a considerable gap still exists between total heritability resulting from all trans-chromosomes and explained variance of all identified trans-eSNPs. In contrast, the vast majority of most cis-heritability of these genes is already explained. Dissection of co-localised functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene-expression, pathways and disease related processes.
2015-06-29 | GSE65907 | GEO