Nature Communications (Sep 2019)
Extensive disruption of protein interactions by genetic variants across the allele frequency spectrum in human populations
- 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. Stenson,
- David N. Cooper,
- Xiaomu Wei,
- Alon Keinan,
- John C. Schimenti,
- Andrew G. Clark,
- Haiyuan Yu
Affiliations
- Robert Fragoza
- Department of Computational Biology, Cornell University
- Jishnu Das
- Ragon Institute of MGH, MIT and Harvard
- Shayne D. Wierbowski
- Department of Computational Biology, Cornell University
- Jin Liang
- Department of Computational Biology, Cornell University
- Tina N. Tran
- Department of Biomedical Science, Cornell University
- Siqi Liang
- Department of Computational Biology, Cornell University
- Juan F. Beltran
- Department of Computational Biology, Cornell University
- Christen A. Rivera-Erick
- Department of Computational Biology, Cornell University
- Kaixiong Ye
- Department of Computational Biology, Cornell University
- Ting-Yi Wang
- Department of Computational Biology, Cornell University
- Li Yao
- Department of Computational Biology, Cornell University
- Matthew Mort
- Institute of Medical Genetics, Cardiff University, Heath Park
- Peter D. Stenson
- Institute of Medical Genetics, Cardiff University, Heath Park
- David N. Cooper
- Institute of Medical Genetics, Cardiff University, Heath Park
- Xiaomu Wei
- Department of Computational Biology, Cornell University
- Alon Keinan
- Department of Computational Biology, Cornell University
- John C. Schimenti
- Department of Biomedical Science, Cornell University
- Andrew G. Clark
- Department of Computational Biology, Cornell University
- Haiyuan Yu
- Department of Computational Biology, Cornell University
- DOI
- https://doi.org/10.1038/s41467-019-11959-3
- Journal volume & issue
-
Vol. 10,
no. 1
pp. 1 – 15
Abstract
Low frequency coding single-nucleotide variants (SNVs) are predicted to disproportionately affect protein function. Here, the authors evaluate 2,009 missense SNVs across 2,185 protein-protein interactions using yeast two-hybrid and protein complementation assays and find that disruptive SNVs often occur in disease-associated genes.
