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

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 th...

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Detalles Bibliográficos
Autores: Garrido Martín, Diego, 1992-, Borsari, Beatrice, 1992-, Calvo, Miquel (Calvo Llorca), Reverter Comes, Ferran, Guigó Serra, Roderic
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/46710
Acceso en línea:http://hdl.handle.net/10230/46710
http://dx.doi.org/10.1038/s41467-020-20578-2
Access Level:acceso abierto
Palabra clave:Computational biology and bioinformatics
Transcriptomics
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dc.title.none.fl_str_mv Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genome
title Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genome
spellingShingle Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genome
Garrido Martín, Diego, 1992-
Computational biology and bioinformatics
Transcriptomics
title_short Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genome
title_full Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genome
title_fullStr Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genome
title_full_unstemmed Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genome
title_sort Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genome
dc.creator.none.fl_str_mv Garrido Martín, Diego, 1992-
Borsari, Beatrice, 1992-
Calvo, Miquel (Calvo Llorca)
Reverter Comes, Ferran
Guigó Serra, Roderic
author Garrido Martín, Diego, 1992-
author_facet Garrido Martín, Diego, 1992-
Borsari, Beatrice, 1992-
Calvo, Miquel (Calvo Llorca)
Reverter Comes, Ferran
Guigó Serra, Roderic
author_role author
author2 Borsari, Beatrice, 1992-
Calvo, Miquel (Calvo Llorca)
Reverter Comes, Ferran
Guigó Serra, Roderic
author2_role author
author
author
author
dc.subject.none.fl_str_mv Computational biology and bioinformatics
Transcriptomics
topic Computational biology and bioinformatics
Transcriptomics
description 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.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021
2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/46710
http://dx.doi.org/10.1038/s41467-020-20578-2
url http://hdl.handle.net/10230/46710
http://dx.doi.org/10.1038/s41467-020-20578-2
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Nat Commun. 2021; 12(1):727
info:eu-repo/grantAgreement/ES/1PE/BIO2015-70777-P
info:eu-repo/grantAgreement/ES/2PE/PGC2018-094017-B-100
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Nature Research
publisher.none.fl_str_mv Nature Research
dc.source.none.fl_str_mv reponame:Repositorio Digital de la UPF
instname:Universitat Pompeu Fabra
instname_str Universitat Pompeu Fabra
reponame_str Repositorio Digital de la UPF
collection Repositorio Digital de la UPF
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spelling Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genomeGarrido Martín, Diego, 1992-Borsari, Beatrice, 1992-Calvo, Miquel (Calvo Llorca)Reverter Comes, FerranGuigó Serra, RodericComputational biology and bioinformaticsTranscriptomicsAlternative 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.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).Nature Research202120212021info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/46710http://dx.doi.org/10.1038/s41467-020-20578-2reponame:Repositorio Digital de la UPFinstname:Universitat Pompeu FabraInglésNat Commun. 2021; 12(1):727info:eu-repo/grantAgreement/ES/1PE/BIO2015-70777-Pinfo:eu-repo/grantAgreement/ES/2PE/PGC2018-094017-B-100© 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/.http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:repositori.upf.edu:10230/467102026-06-12T07:21:37Z
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