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Estimating the strength of selection for new SARS-CoV-2 variants
Controlling the SARS-CoV-2 pandemic becomes increasingly challenging as the virus adapts to human hosts through the continual emergence of more transmissible variants. Simply observing that a variant is increasing in frequency is relatively straightforward, but more sophisticated methodology is need...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8671537/ https://www.ncbi.nlm.nih.gov/pubmed/34907182 http://dx.doi.org/10.1038/s41467-021-27369-3 |
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author | Dorp, Christiaan H. van Goldberg, Emma E. Hengartner, Nick Ke, Ruian Romero-Severson, Ethan O. |
author_facet | Dorp, Christiaan H. van Goldberg, Emma E. Hengartner, Nick Ke, Ruian Romero-Severson, Ethan O. |
author_sort | Dorp, Christiaan H. van |
collection | PubMed |
description | Controlling the SARS-CoV-2 pandemic becomes increasingly challenging as the virus adapts to human hosts through the continual emergence of more transmissible variants. Simply observing that a variant is increasing in frequency is relatively straightforward, but more sophisticated methodology is needed to determine whether a new variant is a global threat and the magnitude of its selective advantage. We present two models for quantifying the strength of selection for new and emerging variants of SARS-CoV-2 relative to the background of contemporaneous variants. These methods range from a detailed model of dynamics within one country to a broad analysis across all countries, and they include alternative explanations such as migration and drift. We find evidence for strong selection favoring the D614G spike mutation and B.1.1.7 (Alpha), weaker selection favoring B.1.351 (Beta), and no advantage of R.1 after it spreads beyond Japan. Cutting back data to earlier time horizons reveals that uncertainty is large very soon after emergence, but that estimates of selection stabilize after several weeks. Our results also show substantial heterogeneity among countries, demonstrating the need for a truly global perspective on the molecular epidemiology of SARS-CoV-2. |
format | Online Article Text |
id | pubmed-8671537 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-86715372022-01-04 Estimating the strength of selection for new SARS-CoV-2 variants Dorp, Christiaan H. van Goldberg, Emma E. Hengartner, Nick Ke, Ruian Romero-Severson, Ethan O. Nat Commun Article Controlling the SARS-CoV-2 pandemic becomes increasingly challenging as the virus adapts to human hosts through the continual emergence of more transmissible variants. Simply observing that a variant is increasing in frequency is relatively straightforward, but more sophisticated methodology is needed to determine whether a new variant is a global threat and the magnitude of its selective advantage. We present two models for quantifying the strength of selection for new and emerging variants of SARS-CoV-2 relative to the background of contemporaneous variants. These methods range from a detailed model of dynamics within one country to a broad analysis across all countries, and they include alternative explanations such as migration and drift. We find evidence for strong selection favoring the D614G spike mutation and B.1.1.7 (Alpha), weaker selection favoring B.1.351 (Beta), and no advantage of R.1 after it spreads beyond Japan. Cutting back data to earlier time horizons reveals that uncertainty is large very soon after emergence, but that estimates of selection stabilize after several weeks. Our results also show substantial heterogeneity among countries, demonstrating the need for a truly global perspective on the molecular epidemiology of SARS-CoV-2. Nature Publishing Group UK 2021-12-14 /pmc/articles/PMC8671537/ /pubmed/34907182 http://dx.doi.org/10.1038/s41467-021-27369-3 Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Dorp, Christiaan H. van Goldberg, Emma E. Hengartner, Nick Ke, Ruian Romero-Severson, Ethan O. Estimating the strength of selection for new SARS-CoV-2 variants |
title | Estimating the strength of selection for new SARS-CoV-2 variants |
title_full | Estimating the strength of selection for new SARS-CoV-2 variants |
title_fullStr | Estimating the strength of selection for new SARS-CoV-2 variants |
title_full_unstemmed | Estimating the strength of selection for new SARS-CoV-2 variants |
title_short | Estimating the strength of selection for new SARS-CoV-2 variants |
title_sort | estimating the strength of selection for new sars-cov-2 variants |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8671537/ https://www.ncbi.nlm.nih.gov/pubmed/34907182 http://dx.doi.org/10.1038/s41467-021-27369-3 |
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