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Kerimov, N.* ; Tambets, R.* ; Hayhurst, J.D.* ; Rahu, I.* ; Kolberg, P.* ; Raudvere, U.* ; Kuzmin, I.* ; Chowdhary A. ; Vija, A.* ; Teras, H.J.* ; Kanai, M.* ; Ulirsch, J.* ; Ryten, M.* ; Hardy, J.* ; Guelfi, S.* ; Trabzuni, D.* ; Kim-Hellmuth, S. ; Rayner, N.W. ; Finucane, H.* ; Peterson, H.* ; Mosaku, A.* ; Parkinson, H.* ; Alasoo, K.*

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

PLoS Genet. 19:e1010932 (2023)
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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.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Genetic-variation; Functional Variation; Expression; Quantification; Annotation; Conversion; Thousands; Alignment; Reveals
Language english
Publication Year 2023
HGF-reported in Year 2023
ISSN (print) / ISBN 1553-7390
e-ISSN 1553-7404
Journal PLoS Genetics
Quellenangaben Volume: 19, Issue: 9, Pages: , Article Number: e1010932 Supplement: ,
Publisher Public Library of Science (PLoS)
Publishing Place 1160 Battery Street, Ste 100, San Francisco, Ca 94111 Usa
Reviewing status Peer reviewed
Institute(s) Institute of Translational Genomics (ITG)
POF-Topic(s) 30205 - Bioengineering and Digital Health
Research field(s) Genetics and Epidemiology
PSP Element(s) G-506700-001
Grants The RNA-seq quantification and QTL analyses were performed at the High Performance Computing Center, University of Tartu. We thank O.E. Oopkaup, S. Kuusemets and the rest of the team of the High Performance Computing Center for their professional and time
DOI 10.1371/journal.pgen.1010932
WOS ID 001070246500004
Scopus ID 85171833589
PubMed ID 37721944
Erfassungsdatum 2023-10-18
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