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COVID-19 CG enables SARS-CoV-2 mutation and lineage tracking by locations and dates of interest
COVID-19 CG (covidcg.org) is an open resource for tracking SARS-CoV-2 single-nucleotide variations (SNVs), lineages, and clades using the virus genomes on the GISAID database while filtering by location, date, gene, and mutation of interest. COVID-19 CG provides significant time, labor, and cost-sav...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7901870/ https://www.ncbi.nlm.nih.gov/pubmed/33620031 http://dx.doi.org/10.7554/eLife.63409 |
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author | Chen, Albert Tian Altschuler, Kevin Zhan, Shing Hei Chan, Yujia Alina Deverman, Benjamin E |
author_facet | Chen, Albert Tian Altschuler, Kevin Zhan, Shing Hei Chan, Yujia Alina Deverman, Benjamin E |
author_sort | Chen, Albert Tian |
collection | PubMed |
description | COVID-19 CG (covidcg.org) is an open resource for tracking SARS-CoV-2 single-nucleotide variations (SNVs), lineages, and clades using the virus genomes on the GISAID database while filtering by location, date, gene, and mutation of interest. COVID-19 CG provides significant time, labor, and cost-saving utility to projects on SARS-CoV-2 transmission, evolution, diagnostics, therapeutics, vaccines, and intervention tracking. Here, we describe case studies in which users can interrogate (1) SNVs in the SARS-CoV-2 spike receptor binding domain (RBD) across different geographical regions to inform the design and testing of therapeutics, (2) SNVs that may impact the sensitivity of commonly used diagnostic primers, and (3) the emergence of a dominant lineage harboring an S477N RBD mutation in Australia in 2020. To accelerate COVID-19 efforts, COVID-19 CG will be upgraded with new features for users to rapidly pinpoint mutations as the virus evolves throughout the pandemic and in response to therapeutic and public health interventions. |
format | Online Article Text |
id | pubmed-7901870 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-79018702021-02-24 COVID-19 CG enables SARS-CoV-2 mutation and lineage tracking by locations and dates of interest Chen, Albert Tian Altschuler, Kevin Zhan, Shing Hei Chan, Yujia Alina Deverman, Benjamin E eLife Epidemiology and Global Health COVID-19 CG (covidcg.org) is an open resource for tracking SARS-CoV-2 single-nucleotide variations (SNVs), lineages, and clades using the virus genomes on the GISAID database while filtering by location, date, gene, and mutation of interest. COVID-19 CG provides significant time, labor, and cost-saving utility to projects on SARS-CoV-2 transmission, evolution, diagnostics, therapeutics, vaccines, and intervention tracking. Here, we describe case studies in which users can interrogate (1) SNVs in the SARS-CoV-2 spike receptor binding domain (RBD) across different geographical regions to inform the design and testing of therapeutics, (2) SNVs that may impact the sensitivity of commonly used diagnostic primers, and (3) the emergence of a dominant lineage harboring an S477N RBD mutation in Australia in 2020. To accelerate COVID-19 efforts, COVID-19 CG will be upgraded with new features for users to rapidly pinpoint mutations as the virus evolves throughout the pandemic and in response to therapeutic and public health interventions. eLife Sciences Publications, Ltd 2021-02-23 /pmc/articles/PMC7901870/ /pubmed/33620031 http://dx.doi.org/10.7554/eLife.63409 Text en © 2021, Chen et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Epidemiology and Global Health Chen, Albert Tian Altschuler, Kevin Zhan, Shing Hei Chan, Yujia Alina Deverman, Benjamin E COVID-19 CG enables SARS-CoV-2 mutation and lineage tracking by locations and dates of interest |
title | COVID-19 CG enables SARS-CoV-2 mutation and lineage tracking by locations and dates of interest |
title_full | COVID-19 CG enables SARS-CoV-2 mutation and lineage tracking by locations and dates of interest |
title_fullStr | COVID-19 CG enables SARS-CoV-2 mutation and lineage tracking by locations and dates of interest |
title_full_unstemmed | COVID-19 CG enables SARS-CoV-2 mutation and lineage tracking by locations and dates of interest |
title_short | COVID-19 CG enables SARS-CoV-2 mutation and lineage tracking by locations and dates of interest |
title_sort | covid-19 cg enables sars-cov-2 mutation and lineage tracking by locations and dates of interest |
topic | Epidemiology and Global Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7901870/ https://www.ncbi.nlm.nih.gov/pubmed/33620031 http://dx.doi.org/10.7554/eLife.63409 |
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