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Global analysis of more than 50,000 SARS-CoV-2 genomes reveals epistasis between eight viral genes.
Proc Natl Acad Sci U S A. 2020 12 08; 117(49):31519-31526.PN

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.

Authors+Show Affiliations

New Energy Technology Engineering Laboratory of Jiangsu Province, School of Science, Nanjing University of Posts and Telecommunications, Nanjing, 210023, China. Nordic Institute for Theoretical Physics, Royal Institute of Technology and Stockholm University, 10691 Stockholm, Sweden.Nordic Institute for Theoretical Physics, Royal Institute of Technology and Stockholm University, 10691 Stockholm, Sweden. Department of Physics, University of Trieste, 34151 Trieste, Italy. Department of Computational Science and Technology, AlbaNova University Center, 10691 Stockholm, Sweden.Group of Complex Systems and Statistical Physics, Department of Theoretical Physics, Physics Faculty, University of Havana, 10400 Havana, Cuba.Department of Infectious Diseases, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, 40530 Gothenburg, Sweden. Center for Translational Microbiome Research, Department of Microbiology, Cell and Tumor Biology, Karolinska Institutet, 17177 Stockholm, Sweden.Department of Computational Science and Technology, AlbaNova University Center, 10691 Stockholm, Sweden; eaurell@kth.se.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

33203681

Citation

Zeng, Hong-Li, et al. "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, vol. 117, no. 49, 2020, pp. 31519-31526.
Zeng HL, Dichio V, Rodríguez Horta E, et al. Global analysis of more than 50,000 SARS-CoV-2 genomes reveals epistasis between eight viral genes. Proc Natl Acad Sci U S A. 2020;117(49):31519-31526.
Zeng, H. L., Dichio, V., Rodríguez Horta, E., Thorell, K., & Aurell, E. (2020). 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, 117(49), 31519-31526. https://doi.org/10.1073/pnas.2012331117
Zeng HL, et al. Global Analysis of More Than 50,000 SARS-CoV-2 Genomes Reveals Epistasis Between Eight Viral Genes. Proc Natl Acad Sci U S A. 2020 12 8;117(49):31519-31526. PubMed PMID: 33203681.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Global analysis of more than 50,000 SARS-CoV-2 genomes reveals epistasis between eight viral genes. AU - Zeng,Hong-Li, AU - Dichio,Vito, AU - Rodríguez Horta,Edwin, AU - Thorell,Kaisa, AU - Aurell,Erik, Y1 - 2020/11/17/ PY - 2020/11/19/pubmed PY - 2020/11/19/medline PY - 2020/11/18/entrez KW - SARS-CoV-2 KW - direct coupling analysis KW - epistasis KW - recombination SP - 31519 EP - 31526 JF - Proceedings of the National Academy of Sciences of the United States of America JO - Proc Natl Acad Sci U S A VL - 117 IS - 49 N2 - 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. SN - 1091-6490 UR - https://www.unboundmedicine.com/medline/citation/33203681/Global_analysis_of_more_than_50000_SARS_CoV_2_genomes_reveals_epistasis_between_eight_viral_genes_ L2 - http://www.pnas.org/cgi/pmidlookup?view=long&pmid=33203681 DB - PRIME DP - Unbound Medicine ER -