1. Genetics and Genomics

Population-scale proteome variation in human induced pluripotent stem cells

  1. Bogdan Andrei Mirauta
  2. Daniel D Seaton
  3. Dalila Bensaddek
  4. Alejandro Brenes
  5. Marc Jan Bonder
  6. Helena Kilpinen
  7. HipSci Consortium
  8. Oliver Stegle  Is a corresponding author
  9. Angus I Lamond  Is a corresponding author
  1. European Bioinformatics Institute, United Kingdom
  2. University of Dundee, United Kingdom
  3. University College London, United Kingdom
  4. European Molecular Biology Laboratory, European Bioinformatics Institute, United Kingdom
https://doi.org/10.7554/eLife.57390
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Cite this article
  1. Bogdan Andrei Mirauta
  2. Daniel D Seaton
  3. Dalila Bensaddek
  4. Alejandro Brenes
  5. Marc Jan Bonder
  6. Helena Kilpinen
  7. HipSci Consortium
  8. Oliver Stegle
  9. Angus I Lamond
(2020)
Population-scale proteome variation in human induced pluripotent stem cells
eLife 9:e57390.
https://doi.org/10.7554/eLife.57390
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Abstract

Human disease phenotypes are ultimately 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.

Data availability

RNA-Seq data for 331 samples are available on the European Nucleotide Archive (ENA): study PRJEB7388; accession ERP007111. Proteomics quantifications (protein group and peptide resolution; MaxQuant output), and run parameters are available on the PRIDE Archive PRIDE (PXD010557). Analysed data is included in the supplementary external files.

The following data sets were generated

Article and author information

Author details

  1. Bogdan Andrei Mirauta

    Statistical genomics, European Bioinformatics Institute, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.

  2. Daniel D Seaton

    Statistical genomics, European Bioinformatics Institute, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.

  3. Dalila Bensaddek

    Centre for Gene Regulation & Expression, School of Life Sciences, University of Dundee, Dundee, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.

  4. Alejandro Brenes

    Centre for Gene Regulation & Expression, School of Life Sciences, University of Dundee, Dundee, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.

  5. Marc Jan Bonder

    Statistical genomics, European Bioinformatics Institute, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8431-3180

  6. Helena Kilpinen

    Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6692-6154

  7. HipSci Consortium

  8. Oliver Stegle

    Wellcome Trust Genome Campus, European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, United Kingdom
    For correspondence
    oliver.stegle@ebi.ac.uk
    Competing interests
    The authors declare that no competing interests exist.

  9. Angus I Lamond

    Centre for Gene Regulation and Expression, University of Dundee, Dundee, United Kingdom
    For correspondence
    a.i.lamond@dundee.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6204-6045

Funding

Wellcome Trust Strategic Award and UK Medical Research Council (WT098503)

  • Bogdan Andrei Mirauta
  • Daniel D Seaton
  • Dalila Bensaddek

Wellcome Trust Strategic Award (105024/Z/14/Z)

  • Bogdan Andrei Mirauta

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Stephen CJ Parker, University of Michigan, United States

Version history

  1. Received: March 30, 2020
  2. Accepted: August 8, 2020
  3. Accepted Manuscript published: August 10, 2020 (version 1)
  4. Accepted Manuscript updated: August 12, 2020 (version 2)
  5. Version of Record published: August 25, 2020 (version 3)

Copyright

© 2020, Mirauta et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Bogdan Andrei Mirauta
  2. Daniel D Seaton
  3. Dalila Bensaddek
  4. Alejandro Brenes
  5. Marc Jan Bonder
  6. Helena Kilpinen
  7. HipSci Consortium
  8. Oliver Stegle
  9. Angus I Lamond
(2020)
Population-scale proteome variation in human induced pluripotent stem cells
eLife 9:e57390.
https://doi.org/10.7554/eLife.57390

Share this article

https://doi.org/10.7554/eLife.57390

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