The aim of the eQTLGen consortium is to investigate the genetic architecture of blood gene expression and to understand the genetic underpinnings of complex traits. The bulk eQTLGen project is currently in its second phase, which is focused on a large-scale genome-wide meta-analysis in blood. The cookbook for this second phase analysis can be found here. We are also working on a single-cell version of this consortium, called Single-Cell eQTLGen.
The eQTLGen Consortium has been set up to investigate the genetic architecture of blood gene expression and to understand the genetic underpinnings of complex traits. Currently, we are initiating the second phase of eQTLGen analyses: highly-powered genome-wide eQTL meta-analysis in blood. This project dramatically expands our previous work where we tested, in addition to cis-eQTLs, trans-eQTLs for a limited subset of ~10,000 trait-associated SNPs. We plan to conduct such genome-wide meta-analysis on as many blood-based cohorts as possible.
Resulting genome-wide association profiles on gene expression would enable to address many relevant scientific questions. Most simple example: with such data, you can interpret your GWAS locus by finding potentially relevant genes from all over the genome, not only in the near vicinity of trait-associated locus.
If you know any blood-based eQTL cohort not yet joined our consortium, please drop us a line with the reference and/or contact.
The aims of our consortium are:
Previously we have conducted cis-eQTL, targeted trans-eQTL and eQTS analysis in up to 31,684 blood and PBMC samples from 37 individual cohorts from eQTLGen Consortium (eQTLGen phase I). In this project, we tested the subset of ~10,000 trait-related variants for the associations with the expression of distal genes (trans).
Võsa & Claringbould et. al. (2021). Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression. Nature Genetics, 53(9), 1300–1310. https://doi.org/10.1038/s41588-021-00913-z
Full summary statistics from eQTLGen phase I are available on the dedicated web site.
Results from this project have been used in collaboration projects before and after publication. According to Google Scholar, the published paper and preprint have been cited 733 times (by 21.04.2023).
Links to all available summary statistics from our publications and preprints are under Resources
eQTLGen Consortium is jointly coordinated by: