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

Robert Fragoza,Jishnu Das,Christen A Rivera-Erick,Ting-Yi Wang,John C Schimenti,Peter D Stenson,Jin Liang,Siqi Liang,Juan F Beltran,David N Cooper,Shayne D Wierbowski,Kaixiong Ye,Li Yao,Andrew G Clark,Matthew Mort,Tina N Tran,Xiaomu Wei,Haiyuan Yu,Alon Keinan

doi:10.1038/s41467-019-11959-3

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.

Highlights

IntroductionThe extent to which this variation is functional and the mechanisms by which they exert their influence remains largely unexplored
Each human genome carries tens of thousands of coding variants
We characterize a rare variant on the enzyme PSPH that significantly reduces its catalytic activity, as well as a rare variant on SEPT12 that results in male subfertility in CRISPR-edited mice, demonstrating the functional relevance of the interactiondisruptive single nucleotide variants (SNVs) reported here

Summary

Introduction

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 SNVinteraction pairs, of which 421 SNVs segregate at > 1% allele frequency in human populations. We show how candidate disease-associated mutations can be identified through matching interaction perturbation profiles with known disease-causing mutations In this manner, we characterize a rare variant on the enzyme PSPH that significantly reduces its catalytic activity, as well as a rare variant on SEPT12 that results in male subfertility in CRISPR-edited mice, demonstrating the functional relevance of the interactiondisruptive SNVs reported here

Methods

Results

Conclusion