Many gene expression quantitative trait locus (eQTL) studies have published their summary statistics, which can be used to gain insight into complex human traits by downstream analyses, such as fine mapping and co-localization. However, technical differences between these datasets are a barrier to their widespread use. Consequently, target genes for most genome-wide association study (GWAS) signals have still not been identified.
Researchers from the University of Tartu have created the eQTL Catalogue, a resource of quality-controlled, uniformly re-computed gene expression and splicing QTLs from 21 studies. The researchers find that, for matching cell types and tissues, the eQTL effect sizes are highly reproducible between studies. Although most QTLs were shared between most bulk tissues, they identified a greater diversity of cell-type-specific QTLs from purified cell types, a subset of which also manifested as new disease co-localizations. The summary statistics are freely available to enable the systematic interpretation of human GWAS associations across many cell types and tissues.
Overview of the eQTL Catalogue database
a, A high-level representation of the uniform data harmonization and eQTL mapping process. b, The eQTL Catalogue summary results for the RBMS1 gene in BLUEPRINT CD4+ T cells, viewed via the Ensembl Genome Browser.
Availability – https://www.ebi.ac.uk/eqtl