Population-scale proteome variation in human induced pluripotent stem cells

Bogdan Andrei Mirauta; Daniel D. Seaton; Dalila Bensaddek; Alejandro Brenes; Marc Jan Bonder; Helena Kilpinen; Chukwuma A. Agu; Alex Alderton; Petr Danecek; Rachel Denton; Richard Durbin; Daniel J. Gaffney; Angela Goncalves; Reena Halai; Sarah Harper; Christopher M. Kirton; Anja Kolb-Kokocinski; Andreas Leha; Shane A. McCarthy; Yasin Memari; Minal Patel; Ewan Birney; Francesco Paolo Casale; Laura Clarke; Peter W. Harrison; Ian Streeter; Davide Denovi; Ruta Meleckyte; Natalie Moens; Fiona M. Watt; Willem H. Ouwehand; Philip Beales; Oliver Stegle; Angus I. Lamond

doi:10.7554/ELIFE.57390

Population-scale proteome variation in human induced pluripotent stem cells

Bogdan Andrei Mirauta, Daniel D. Seaton, Dalila Bensaddek, Alejandro Brenes, Marc Jan Bonder, Helena Kilpinen, Chukwuma A. Agu, Alex Alderton, Petr Danecek, Rachel Denton, Richard Durbin, Daniel J. Gaffney, Angela Goncalves, Reena Halai, Sarah Harper, Christopher M. Kirton, Anja Kolb-Kokocinski, Andreas Leha, Shane A. McCarthy, Yasin MemariMinal Patel, Ewan Birney, Francesco Paolo Casale, Laura Clarke, Peter W. Harrison, Ian Streeter, Davide Denovi, Ruta Meleckyte, Natalie Moens, Fiona M. Watt, Willem H. Ouwehand, Philip Beales, Oliver Stegle, Angus I. Lamond

Research output: Contribution to journal › Article › peer-review

35 Scopus citations

Abstract

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.

Original language	English (US)
Pages (from-to)	1-22
Number of pages	22
Journal	eLife
Volume	9
DOIs	https://doi.org/10.7554/ELIFE.57390
State	Published - Aug 10 2020

Bibliographical note

KAUST Repository Item: Exported on 2020-10-16

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https://repository.kaust.edu.sa/bitstream/10754/665584/1/elife-57390-v3.pdf

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Mirauta, B. A., Seaton, D. D., Bensaddek, D., Brenes, A., Bonder, M. J., Kilpinen, H., Agu, C. A., Alderton, A., Danecek, P., Denton, R., Durbin, R., Gaffney, D. J., Goncalves, A., Halai, R., Harper, S., Kirton, C. M., Kolb-Kokocinski, A., Leha, A., McCarthy, S. A., ... Lamond, A. I. (2020). Population-scale proteome variation in human induced pluripotent stem cells. eLife, 9, 1-22. https://doi.org/10.7554/ELIFE.57390

@article{c3e4705671554875b04c1a107a8ebab5,

title = "Population-scale proteome variation in human induced pluripotent stem cells",

abstract = "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.",

author = "Mirauta, {Bogdan Andrei} and Seaton, {Daniel D.} and Dalila Bensaddek and Alejandro Brenes and Bonder, {Marc Jan} and Helena Kilpinen and Agu, {Chukwuma A.} and Alex Alderton and Petr Danecek and Rachel Denton and Richard Durbin and Gaffney, {Daniel J.} and Angela Goncalves and Reena Halai and Sarah Harper and Kirton, {Christopher M.} and Anja Kolb-Kokocinski and Andreas Leha and McCarthy, {Shane A.} and Yasin Memari and Minal Patel and Ewan Birney and {Paolo Casale}, Francesco and Laura Clarke and Harrison, {Peter W.} and Ian Streeter and Davide Denovi and Ruta Meleckyte and Natalie Moens and Watt, {Fiona M.} and Ouwehand, {Willem H.} and Philip Beales and Oliver Stegle and Lamond, {Angus I.}",

note = "KAUST Repository Item: Exported on 2020-10-16",

year = "2020",

month = aug,

day = "10",

doi = "10.7554/ELIFE.57390",

language = "English (US)",

volume = "9",

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journal = "eLife",

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Mirauta, BA, Seaton, DD, Bensaddek, D, Brenes, A, Bonder, MJ, Kilpinen, H, Agu, CA, Alderton, A, Danecek, P, Denton, R, Durbin, R, Gaffney, DJ, Goncalves, A, Halai, R, Harper, S, Kirton, CM, Kolb-Kokocinski, A, Leha, A, McCarthy, SA, Memari, Y, Patel, M, Birney, E, Paolo Casale, F, Clarke, L, Harrison, PW, Streeter, I, Denovi, D, Meleckyte, R, Moens, N, Watt, FM, Ouwehand, WH, Beales, P, Stegle, O & Lamond, AI 2020, 'Population-scale proteome variation in human induced pluripotent stem cells', eLife, vol. 9, pp. 1-22. https://doi.org/10.7554/ELIFE.57390

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, Alejandro

AU - Bonder, Marc Jan

AU - Kilpinen, Helena

AU - Agu, Chukwuma A.

AU - Alderton, Alex

AU - Danecek, Petr

AU - Denton, Rachel

AU - Durbin, Richard

AU - Gaffney, Daniel J.

AU - Goncalves, Angela

AU - Halai, Reena

AU - Harper, Sarah

AU - Kirton, Christopher M.

AU - Kolb-Kokocinski, Anja

AU - Leha, Andreas

AU - McCarthy, Shane A.

AU - Memari, Yasin

AU - Patel, Minal

AU - Birney, Ewan

AU - Paolo Casale, Francesco

AU - Clarke, Laura

AU - Harrison, Peter W.

AU - Streeter, Ian

AU - Denovi, Davide

AU - Meleckyte, Ruta

AU - Moens, Natalie

AU - Watt, Fiona M.

AU - Ouwehand, Willem H.

AU - Beales, Philip

AU - Stegle, Oliver

AU - Lamond, Angus I.

N1 - KAUST Repository Item: Exported on 2020-10-16

PY - 2020/8/10

Y1 - 2020/8/10

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 - http://hdl.handle.net/10754/665584

UR - https://elifesciences.org/articles/57390

UR - http://www.scopus.com/inward/record.url?scp=85092182005&partnerID=8YFLogxK

U2 - 10.7554/ELIFE.57390

DO - 10.7554/ELIFE.57390

M3 - Article

SN - 2050-084X

VL - 9

SP - 1

EP - 22

JO - eLife

JF - eLife

ER -

Population-scale proteome variation in human induced pluripotent stem cells

Abstract

Bibliographical note

UN SDGs

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