Population-scale proteome variation in human induced pluripotent stem cells

TY - JOUR

T1 - Population-scale proteome variation in human induced pluripotent stem cells

AU - Mirauta, Bogdan Andrei

AU - Seaton, Daniel D.

AU - Bensaddek, Dalila

AU - Brenes Murillo, Alejandro

AU - Bonder, Marc Jan

AU - Kilpinen, Helena

AU - Stegle, Oliver

AU - Lamond, Angus I.

N1 - © 2020, Mirauta et al.

PY - 2020/8/25

Y1 - 2020/8/25

N2 - Human 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.

AB - Human 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.

UR - https://www.scopus.com/pages/publications/85092182005

U2 - 10.7554/eLife.57390

DO - 10.7554/eLife.57390

M3 - Article

C2 - 32773033

SN - 2050-084X

VL - 9

JO - eLife

JF - eLife

M1 - e57390

ER -