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dc.contributor.authorMirauta, Bogdan Andrei
dc.contributor.authorSeaton, Daniel D.
dc.contributor.authorBensaddek, Dalila
dc.contributor.authorBrenes, Alejandro
dc.contributor.authorBonder, Marc Jan
dc.contributor.authorKilpinen, Helena
dc.contributor.authorAgu, Chukwuma A.
dc.contributor.authorAlderton, Alex
dc.contributor.authorDanecek, Petr
dc.contributor.authorDenton, Rachel
dc.contributor.authorDurbin, Richard
dc.contributor.authorGaffney, Daniel J.
dc.contributor.authorGoncalves, Angela
dc.contributor.authorHalai, Reena
dc.contributor.authorHarper, Sarah
dc.contributor.authorKirton, Christopher M.
dc.contributor.authorKolb-Kokocinski, Anja
dc.contributor.authorLeha, Andreas
dc.contributor.authorMcCarthy, Shane A.
dc.contributor.authorMemari, Yasin
dc.contributor.authorPatel, Minal
dc.contributor.authorBirney, Ewan
dc.contributor.authorPaolo Casale, Francesco
dc.contributor.authorClarke, Laura
dc.contributor.authorHarrison, Peter W.
dc.contributor.authorStreeter, Ian
dc.contributor.authorDenovi, Davide
dc.contributor.authorMeleckyte, Ruta
dc.contributor.authorMoens, Natalie
dc.contributor.authorWatt, Fiona M.
dc.contributor.authorOuwehand, Willem H.
dc.contributor.authorBeales, Philip
dc.contributor.authorStegle, Oliver
dc.contributor.authorLamond, Angus I.
dc.date.accessioned2020-10-15T06:06:19Z
dc.date.available2020-10-15T06:06:19Z
dc.date.issued2020-08-10
dc.date.submitted2020-03-30
dc.identifier.citationMirauta, B. A., Seaton, D. D., Bensaddek, D., Brenes, A., Bonder, M. J., … Kilpinen, H. (2020). Population-scale proteome variation in human induced pluripotent stem cells. eLife, 9. doi:10.7554/elife.57390
dc.identifier.issn2050-084X
dc.identifier.doi10.7554/ELIFE.57390
dc.identifier.urihttp://hdl.handle.net/10754/665584
dc.description.abstractHuman disease phenotypes are driven primarily by alterations in protein expression and/or function. To date, relatively little is known about the variability of the human proteome in populations and how this relates to variability in mRNA expression and to disease loci. Here, we present the first comprehensive proteomic analysis of human induced pluripotent stem cells (iPSC), a key cell type for disease modelling, analysing 202 iPSC lines derived from 151 donors, with integrated transcriptome and genomic sequence data from the same lines. We characterised the major genetic and non-genetic determinants of proteome variation across iPSC lines and assessed key regulatory mechanisms affecting variation in protein abundance. We identified 654 protein quantitative trait loci (pQTLs) in iPSCs, including disease-linked variants in protein-coding sequences and variants with trans regulatory effects. These include pQTL linked to GWAS variants that cannot be detected at the mRNA level, highlighting the utility of dissecting pQTL at peptide level resolution.
dc.publishereLife Sciences Publications, Ltd
dc.relation.urlhttps://elifesciences.org/articles/57390
dc.rightsThis article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titlePopulation-scale proteome variation in human induced pluripotent stem cells
dc.typeArticle
dc.contributor.departmentProteomics and Protein Expression
dc.identifier.journaleLife
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom
dc.contributor.institutionGSK R and D, Stevenage, SG1 2NY, United Kingdom
dc.contributor.institutionCentre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dundee, United Kingdom
dc.contributor.institutionWellcome Sanger Institute, Hinxton, Cambridge, United Kingdom
dc.contributor.institutionKing’s College, London, United Kingdom
dc.contributor.institutionHelsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
dc.contributor.institutionEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
dc.contributor.institutionDivision of Computational Genomics and Systems Genetic, German Cancer Research Center, Heidelberg, Germany
dc.identifier.volume9
dc.identifier.pages1-22
kaust.personBensaddek, Dalila
dc.date.accepted2020-08-08
dc.identifier.eid2-s2.0-85092182005
refterms.dateFOA2020-10-15T06:07:35Z


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This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
Except where otherwise noted, this item's license is described as This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.