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Systematic visualisation of molecular QTLs reveals variant mechanisms at GWAS loci.
Kerimov, Nurlan; Tambets, Ralf; Hayhurst, James D; Rahu, Ida; Kolberg, Peep; Raudvere, Uku; Kuzmin, Ivan; Chowdhary, Anshika; Vija, Andreas; Teras, Hans J; Kanai, Masahiro; Ulirsch, Jacob; Ryten, Mina; Hardy, John; Guelfi, Sebastian; Trabzuni, Daniah; Kim-Hellmuth, Sarah; Rayner, Will; Finucane, Hilary; Peterson, Hedi; Mosaku, Abayomi; Parkinson, Helen; Alasoo, Kaur.
Afiliação
  • Kerimov N; Institute of Computer Science, University of Tartu, Tartu, 51009, Estonia.
  • Tambets R; Open Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
  • Hayhurst JD; Institute of Computer Science, University of Tartu, Tartu, 51009, Estonia.
  • Rahu I; Open Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
  • Kolberg P; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
  • Raudvere U; Institute of Computer Science, University of Tartu, Tartu, 51009, Estonia.
  • Kuzmin I; Institute of Computer Science, University of Tartu, Tartu, 51009, Estonia.
  • Chowdhary A; Institute of Computer Science, University of Tartu, Tartu, 51009, Estonia.
  • Vija A; Institute of Computer Science, University of Tartu, Tartu, 51009, Estonia.
  • Teras HJ; Institute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany.
  • Kanai M; Institute of Computer Science, University of Tartu, Tartu, 51009, Estonia.
  • Ulirsch J; Institute of Computer Science, University of Tartu, Tartu, 51009, Estonia.
  • Ryten M; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
  • Hardy J; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Guelfi S; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Trabzuni D; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
  • Kim-Hellmuth S; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Rayner W; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Finucane H; Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London.
  • Peterson H; Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London.
  • Mosaku A; Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London.
  • Parkinson H; Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London.
  • Alasoo K; Institute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany.
bioRxiv ; 2023 Apr 07.
Article em En | MEDLINE | ID: mdl-37066341
ABSTRACT
Splicing quantitative trait loci (QTLs) have been implicated as a common mechanism underlying complex trait associations. However, utilising splicing QTLs in target discovery and prioritisation has been challenging due to extensive data normalisation which often renders the direction of the genetic effect as well as its magnitude difficult to interpret. This is further complicated by the fact that strong expression QTLs often manifest as weak splicing QTLs and vice versa, making it difficult to uniquely identify the underlying molecular mechanism at each locus. We find that these ambiguities can be mitigated by visualising the association between the genotype and average RNA sequencing read coverage in the region. Here, we generate these QTL coverage plots for 1.7 million molecular QTL associations in the eQTL Catalogue identified with five quantification methods. We illustrate the utility of these QTL coverage plots by performing colocalisation between vitamin D levels in the UK Biobank and all molecular QTLs in the eQTL Catalogue. We find that while visually confirmed 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. All our association summary statistics and QTL coverage plots are freely available at https//www.ebi.ac.uk/eqtl/.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article