Global analysis of more than 50,000 SARS-CoV-2 genomes reveals epistasis between eight viral genes

Proceedings of the National Academy of Sciences of the United States of America
Hong-Li ZengErik Aurell

Abstract

Genome-wide epistasis analysis is a powerful tool to infer gene interactions, which can guide drug and vaccine development and lead to deeper understanding of microbial pathogenesis. We have considered all complete severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes deposited in the Global Initiative on Sharing All Influenza Data (GISAID) repository until four different cutoff dates, and used direct coupling analysis together with an assumption of quasi-linkage equilibrium to infer epistatic contributions to fitness from polymorphic loci. We find eight interactions, of which three are between pairs where one locus lies in gene ORF3a, both loci holding nonsynonymous mutations. We also find interactions between two loci in gene nsp13, both holding nonsynonymous mutations, and four interactions involving one locus holding a synonymous mutation. Altogether, we infer interactions between loci in viral genes ORF3a and nsp2, nsp12, and nsp6, between ORF8 and nsp4, and between loci in genes nsp2, nsp13, and nsp14. The paper opens the prospect to use prominent epistatically linked pairs as a starting point to search for combinatorial weaknesses of recombinant viral pathogens.

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Citations

Mar 27, 2021·Environmental Microbiology·Ruibang LuoAntoine Danchin
Apr 14, 2021·Nucleic Acids Research·Christian M GallardoBruce E Torbett
May 25, 2021·PLoS Computational Biology·Edwin Rodriguez Horta, Martin Weigt
Jul 6, 2021·Briefings in Bioinformatics·Shokouh RezaeiVuk Uskoković
Aug 16, 2021·Mathematical Biosciences·Evan Cresswell-Clay, Vipul Periwal
Aug 27, 2021·The Science of the Total Environment·Candice L SwiftR Sean Norman
Oct 26, 2021·Genomics, Proteomics & Bioinformatics·Shuhui SongYiming Bao

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Methods Mentioned

BETA
GISAID

Software Mentioned

Phylogeny
GISAID
PLM
circos
DCA

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