ArticleProceedings of the National Academy of Sciences of the United States of America2020
Global analysis of more than 50,000 SARS-CoV-2 genomes reveals epistasis between eight viral genes.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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34 citing papers in PubMed, 75 citations in OpenAlex.
- Classification of SARS-CoV-2 Variants Through the Epistatic Circos Plots with Convolutional Neural Networks.Journal of molecular evolution · 2026Article
- Evolution of BA.2.86 to JN.1 reveals that functional changes in non-structural viral proteins are required for fitness of SARS-CoV-2.Journal of virology · 2025Article
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- The importance of epistasis in the evolution of viral pathogens.Virus evolution · 2025Review
- Real-time identification of epistatic interactions in SARS-CoV-2 from large genome collections.Genome biology · 2024Article
- Functional effects of mutations in proteins can be predicted and interpreted by guided selection of sequence covariation information.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Article
- Early detection of emerging viral variants through analysis of community structure of coordinated substitution networks.Nature communications · 2024Article
- In vivo functional phenotypes from a computational epistatic model of evolution.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Evolutionary trajectory of diverse SARS-CoV-2 variants at the beginning of COVID-19 outbreak.Virus evolution · 2024Article
- Intra- vs. Interhost Evolution of SARS-CoV-2 Driven by Uncorrelated Selection-The Evolution Thwarted.Molecular biology and evolution · 2023Article
- Computational Analysis Predicts Correlations among Amino Acids in SARS-CoV-2 Proteomes.Biomedicines · 2023Article
- Article
- Structural patterns of SARS-CoV-2 variants of concern (alpha, beta, gamma, delta) spike protein are influenced by variant-specific amino acid mutations: A computational study with implications on viral evolution.Journal of theoretical biology · 2023Article
- Identification of potential pathogenic targets and survival strategies ofFrontiers in cellular and infection microbiology · 2023Article
- Serum Proteomic Analysis for New Types of Long-Term Persistent COVID-19 Patients in Wuhan.Microbiology spectrum · 2022Article
- The effect of mutations on binding interactions between the SARS-CoV-2 receptor binding domain and neutralizing antibodies B38 and CB6.Scientific reports · 2022Article
- Subtyping of major SARS-CoV-2 variants reveals different transmission dynamics based on 10 million genomes.PNAS nexus · 2022Article
- VGsim: Scalable viral genealogy simulator for global pandemic.PLoS computational biology · 2022Article
- Article
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Authors and funding
5 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
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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