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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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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
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author 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.
author_facet 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.
author_sort Obermeyer, Fritz
collection PubMed
description 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.
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spelling pubmed-91613722022-06-06 Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness 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. Science Reports 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. American Association for the Advancement of Science 2022-05-24 /pmc/articles/PMC9161372/ /pubmed/35608456 http://dx.doi.org/10.1126/science.abm1208 Text en Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY). https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution license (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Reports
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.
Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness
title Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness
title_full Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness
title_fullStr Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness
title_full_unstemmed Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness
title_short Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness
title_sort analysis of 6.4 million sars-cov-2 genomes identifies mutations associated with fitness
topic Reports
url 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
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