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Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness

Repeated emergence of SARS-CoV-2 variants with increased fitness underscores the value of rapid detection and characterization of new lineages. We have developed PyR(0), a hierarchical Bayesian multinomial logistic regression model that infers relative prevalence of all viral lineages across geograp...

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Detalles Bibliográficos
Autores principales: Obermeyer, Fritz, Jankowiak, Martin, Barkas, Nikolaos, Schaffner, Stephen F., Pyle, Jesse D., Yurkovetskiy, Leonid, Bosso, Matteo, Park, Daniel J., Babadi, Mehrtash, MacInnis, Bronwyn L., Luban, Jeremy, Sabeti, Pardis C., Lemieux, Jacob E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9161372/
https://www.ncbi.nlm.nih.gov/pubmed/35608456
http://dx.doi.org/10.1126/science.abm1208
Descripción
Sumario:Repeated emergence of SARS-CoV-2 variants with increased fitness underscores the value of rapid detection and characterization of new lineages. We have developed PyR(0), a hierarchical Bayesian multinomial logistic regression model that infers relative prevalence of all viral lineages across geographic regions, detects lineages increasing in prevalence, and identifies mutations relevant to fitness. Applying PyR(0) to all publicly available SARS-CoV-2 genomes, we identify numerous substitutions that increase fitness, including previously identified spike mutations and many non-spike mutations within the nucleocapsid and nonstructural proteins. PyR(0) forecasts growth of new lineages from their mutational profile, ranks the fitness of lineages as new sequences become available, and prioritizes mutations of biological and public health concern for functional characterization.