Mountain View
biomedical and healthCAre Data Discovery Index Ecosystem
help Advanced Search
Title: Dissecting the Genetics of the Human Transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding loci      
dateReleased:
06-29-2015
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.
privacy:
not applicable
aggregation:
instance of dataset
ID:
E-GEOD-65907
refinement:
raw
alternateIdentifiers:
65907
keywords:
functional genomics
dateModified:
08-19-2015
availability:
available
types:
gene expression
name:
Homo sapiens
ID:
A-GEOD-10558
name:
Illumina HumanHT-12 V4.0 expression beadchip
accessURL: https://www.ebi.ac.uk/arrayexpress/files/E-GEOD-65907/E-GEOD-65907.raw.1.zip
storedIn:
ArrayExpress
qualifier:
gzip compressed
format:
TXT
accessType:
download
authentication:
none
authorization:
none
accessURL: https://www.ebi.ac.uk/arrayexpress/files/E-GEOD-65907/E-GEOD-65907.processed.1.zip
storedIn:
ArrayExpress
qualifier:
gzip compressed
format:
TXT
accessType:
download
authentication:
none
authorization:
none
accessURL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE65907
storedIn:
Gene Expression Omnibus
qualifier:
not compressed
format:
HTML
accessType:
landing page
primary:
true
authentication:
none
authorization:
none
abbreviation:
EBI
homePage: http://www.ebi.ac.uk/
ID:
SCR:004727
name:
European Bioinformatics Institute
homePage: https://www.ebi.ac.uk/arrayexpress/
ID:
SCR:002964
name:
ArrayExpress

Feedback?

If you are having problems using our tools, or if you would just like to send us some feedback, please post your questions on GitHub.