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Extensive disruption of protein interactions by genetic variants across the allele frequency spectrum in human populations

Author

Listed:
  • Robert Fragoza

    (Cornell University
    Cornell University)

  • Jishnu Das

    (Ragon Institute of MGH, MIT and Harvard
    Massachusetts Institute of Technology)

  • Shayne D. Wierbowski

    (Cornell University
    Cornell University)

  • Jin Liang

    (Cornell University
    Cornell University)

  • Tina N. Tran

    (Cornell University
    Cornell University)

  • Siqi Liang

    (Cornell University
    Cornell University)

  • Juan F. Beltran

    (Cornell University
    Cornell University)

  • Christen A. Rivera-Erick

    (Cornell University
    Cornell University)

  • Kaixiong Ye

    (Cornell University)

  • Ting-Yi Wang

    (Cornell University
    Cornell University)

  • Li Yao

    (Cornell University
    Cornell University)

  • Matthew Mort

    (Cardiff University, Heath Park)

  • Peter D. Stenson

    (Cardiff University, Heath Park)

  • David N. Cooper

    (Cardiff University, Heath Park)

  • Xiaomu Wei

    (Cornell University)

  • Alon Keinan

    (Cornell University)

  • John C. Schimenti

    (Cornell University)

  • Andrew G. Clark

    (Cornell University
    Cornell University)

  • Haiyuan Yu

    (Cornell University
    Cornell University)

Abstract

Each human genome carries tens of thousands of coding variants. The extent to which this variation is functional and the mechanisms by which they exert their influence remains largely unexplored. To address this gap, we leverage the ExAC database of 60,706 human exomes to investigate experimentally the impact of 2009 missense single nucleotide variants (SNVs) across 2185 protein-protein interactions, generating interaction profiles for 4797 SNV-interaction pairs, of which 421 SNVs segregate at > 1% allele frequency in human populations. We find that interaction-disruptive SNVs are prevalent at both rare and common allele frequencies. Furthermore, these results suggest that 10.5% of missense variants carried per individual are disruptive, a higher proportion than previously reported; this indicates that each individual’s genetic makeup may be significantly more complex than expected. Finally, we demonstrate that candidate disease-associated mutations can be identified through shared interaction perturbations between variants of interest and known disease mutations.

Suggested Citation

  • Robert Fragoza & Jishnu Das & Shayne D. Wierbowski & Jin Liang & Tina N. Tran & Siqi Liang & Juan F. Beltran & Christen A. Rivera-Erick & Kaixiong Ye & Ting-Yi Wang & Li Yao & Matthew Mort & Peter D. , 2019. "Extensive disruption of protein interactions by genetic variants across the allele frequency spectrum in human populations," Nature Communications, Nature, vol. 10(1), pages 1-15, December.
  • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-11959-3
    DOI: 10.1038/s41467-019-11959-3
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