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Population-scale proteome variation in human induced pluripotent stem cells

Bogdan A Mirauta, Daniel D Seaton, Dalila Bensaddek, Alejandro Brenes, Marc J Bonder, Helena Kilpinen, HipSci Consortium, Oliver Stegle, Angus I Lamond
doi: https://doi.org/10.1101/439216
Bogdan A Mirauta
1European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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Daniel D Seaton
1European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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Dalila Bensaddek
2Centre for Gene Regulation & Expression, School of Life Sciences, University of Dundee, Dundee, DD1 5EH, UK
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Alejandro Brenes
2Centre for Gene Regulation & Expression, School of Life Sciences, University of Dundee, Dundee, DD1 5EH, UK
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Marc J Bonder
1European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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Helena Kilpinen
1European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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Oliver Stegle
1European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
3European Molecular Biology Laboratory, Genome Biology Unit, 69117 Heidelberg, Germany
4Division of Computational Genomics and Systems Genetics, German Cancer Research Center, 69120 Heidelberg, Germany
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Angus I Lamond
2Centre for Gene Regulation & Expression, School of Life Sciences, University of Dundee, Dundee, DD1 5EH, UK
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Abstract

Realising the potential of human induced pluripotent stem cell (iPSC) technology for drug discovery, disease modelling and cell therapy requires an understanding of variability across iPSC lines. While previous studies have characterized iPS cell lines genetically and transcriptionally, little is known about the variability of the iPSC proteome. Here, we present the first comprehensive proteomic iPSC dataset, analysing 202 iPSC lines derived from 151 donors. We characterise the major genetic determinants affecting proteome and transcriptome variation across iPSC lines and identify key regulatory mechanisms affecting variation in protein abundance. Our data identified >700 human iPSC protein quantitative trait loci (pQTLs). We mapped trans regulatory effects, identifying an important role for protein-protein interactions. We discovered that pQTLs show increased enrichment in disease-linked GWAS variants, compared with RNA-based eQTLs.

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Posted October 11, 2018.
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Population-scale proteome variation in human induced pluripotent stem cells
Bogdan A Mirauta, Daniel D Seaton, Dalila Bensaddek, Alejandro Brenes, Marc J Bonder, Helena Kilpinen, HipSci Consortium, Oliver Stegle, Angus I Lamond
bioRxiv 439216; doi: https://doi.org/10.1101/439216
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Population-scale proteome variation in human induced pluripotent stem cells
Bogdan A Mirauta, Daniel D Seaton, Dalila Bensaddek, Alejandro Brenes, Marc J Bonder, Helena Kilpinen, HipSci Consortium, Oliver Stegle, Angus I Lamond
bioRxiv 439216; doi: https://doi.org/10.1101/439216

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