eQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs

PLoS Genet. 2023 Sep 18;19(9):e1010932. doi: 10.1371/journal.pgen.1010932. eCollection 2023 Sep.


The eQTL Catalogue is an open database of uniformly processed human molecular quantitative trait loci (QTLs). We are continuously updating the resource to further increase its utility for interpreting genetic associations with complex traits. Over the past two years, we have increased the number of uniformly processed studies from 21 to 31 and added X chromosome QTLs for 19 compatible studies. We have also implemented Leafcutter to directly identify splice-junction usage QTLs in all RNA sequencing datasets. Finally, to improve the interpretability of transcript-level QTLs, we have developed static QTL coverage plots that visualise the association between the genotype and average RNA sequencing read coverage in the region for all 1.7 million fine mapped associations. To illustrate the utility of these updates to the eQTL Catalogue, we performed colocalisation analysis between vitamin D levels in the UK Biobank and all molecular QTLs in the eQTL Catalogue. Although most GWAS loci colocalised both with eQTLs and transcript-level QTLs, we found that visual inspection could sometimes be used to distinguish primary splicing QTLs from those that appear to be secondary consequences of large-effect gene expression QTLs. While these visually confirmed primary splicing QTLs explain just 6/53 of the colocalising signals, they are significantly less pleiotropic than eQTLs and identify a prioritised causal gene in 4/6 cases.

MeSH terms

  • Base Sequence
  • Genome-Wide Association Study
  • Genotype
  • Humans
  • Multifactorial Inheritance*
  • Polymorphism, Single Nucleotide
  • Quantitative Trait Loci* / genetics

Grants and funding

N.K., J.D.H., P.K. and H.J.T. were supported by a grant from Open Targets (grant no. OTAR2077). H. P., A.M. and J.H. were supported by the European Molecular Biology Laboratory. K.A., A.C., W.R. and N.K. also received funding from the European Union’s Horizon 2020 research and innovation program (grant no. 825775). K.A., N.K, R.T., A.V., P.K. and I.R. were supported by the Estonian Research Council (grant no. PSG415). K.A. was supported by the Estonian Research Council (grant no. IUT34-4). K.A. and N.K. were also supported by the Estonian Centre of Excellence in ICT Research (EXCITE), funded by the European Regional Development Fund. I.K., U.R. and H. P. were supported by the Distributed Infrastructure for Life-Science Information ELIXIR, European Regional Development Fund project (2014-2020.4.01.16-0271). S.K.-H. was supported by the Emmy Noether Programme KI 2091/2-1 (459153572), SFB/TRR237-B29 (369799452) and SFB/TRR359-B06 (491676693) of the Deutsche Forschungsgemeinschaft (DFG). Funding information for individual studies included in the eQTL Catalogue is presented in S1 Text. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.