Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 117, Issue 49, Pages 31519-31526Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.2012331117
Keywords
SARS-CoV-2; epistasis; recombination; direct coupling analysis
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Funding
- National Natural Science Foundation of China [11705097]
- Natural Science Foundation of Jiangsu Province [BK20170895]
- Jiangsu Government Scholarship for Overseas Studies of 2018
- Scientific Research Foundation of Nanjing University of Posts and Telecommunications [NY217013]
- Extra-Erasmus Scholarship (University of Trieste)
- Collegio Universitario Luciano Fonda
- EU H2020 research and innovation program MSCARISE-2016 [734439 INFERNET]
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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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