Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genome

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  • dc.contributor.author Garrido Martín, Diego, 1992-
  • dc.contributor.author Borsari, Beatrice, 1992-
  • dc.contributor.author Calvo, Miquel (Calvo Llorca)
  • dc.contributor.author Reverter, Ferran
  • dc.contributor.author Guigó Serra, Roderic
  • dc.date.accessioned 2021-03-10T06:52:49Z
  • dc.date.available 2021-03-10T06:52:49Z
  • dc.date.issued 2021
  • dc.description.abstract Alternative splicing (AS) is a fundamental step in eukaryotic mRNA biogenesis. Here, we develop an efficient and reproducible pipeline for the discovery of genetic variants that affect AS (splicing QTLs, sQTLs). We use it to analyze the GTEx dataset, generating a comprehensive catalog of sQTLs in the human genome. Downstream analysis of this catalog provides insight into the mechanisms underlying splicing regulation. We report that a core set of sQTLs is shared across multiple tissues. sQTLs often target the global splicing pattern of genes, rather than individual splicing events. Many also affect the expression of the same or other genes, uncovering regulatory loci that act through different mechanisms. sQTLs tend to be located in post-transcriptionally spliced introns, which would function as hotspots for splicing regulation. While many variants affect splicing patterns by altering the sequence of splice sites, many more modify the binding sites of RNA-binding proteins. Genetic variants affecting splicing can have a stronger phenotypic impact than those affecting gene expression.
  • dc.description.sponsorship This project was supported by the National Human Genome Research Institute of the National Institutes of Health under grants R01MH101814 and 5U24HG009446, as well as by the BIO2015-70777-P grant from the Spanish Ministry of Economy, Industry and Competitiveness (MEIC), and the PGC2018-094017-B-100 grant from the Agencia Estatal de Investigación/European Regional Development Fund (ERDF). It has been also possible in part thanks to the grant CZF2019-002436 from the Chan Zuckerberg Initiative. The Genotype-Tissue Expression (GTEx) project was supported by the Common Fund of the Office of the Director of the National Institutes of Health (http://commonfund.nih.gov/GTEx). D.G.-M. is supported by a ‘la Caixa’-Severo Ochoa pre-doctoral fellowship (LCF/BQ/SO15/52260001). B.B. is supported by the fellowship 2017FI_B 00722 from the Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement (Generalitat de Catalunya) and the European Social Fund (ESF). We thank the ENCODE Consortium and, in particular, Thomas Gingeras’, Gene Yeo’s and Bradley Bernstein’s laboratories for data production. We also acknowledge support of the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) to the EMBL partnership, ‘Centro de Excelencia Severo Ochoa’, the CERCA Programme/Generalitat de Catalunya and the European Regional Development Fund (ERDF).
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Garrido-Martín D, Borsari B, Calvo M, Reverter F, Guigó R. Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genome. Nat Commun. 2021; 12(1):727. DOI: 10.1038/s41467-020-20578-2
  • dc.identifier.doi http://dx.doi.org/10.1038/s41467-020-20578-2
  • dc.identifier.issn 2041-1723
  • dc.identifier.uri http://hdl.handle.net/10230/46710
  • dc.language.iso eng
  • dc.publisher Nature Research
  • dc.relation.ispartof Nat Commun. 2021; 12(1):727
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/BIO2015-70777-P
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PGC2018-094017-B-100
  • dc.rights © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri http://creativecommons.org/licenses/by/4.0/
  • dc.subject.keyword Computational biology and bioinformatics
  • dc.subject.keyword Transcriptomics
  • dc.title Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genome
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/publishedVersion

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