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A database for retrieving information on SARS-CoV-2 S protein mutations based on correlation network analysis

BACKGROUND: Over a million genomes and mutational analyses of SARS-CoV-2 are available in public databases, which reveal the phylogenetic tree of the virus. Although these data have enabled scientists to closely track the evolution and transmission dynamics of the virus at global and local scales, t...

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Autores principales: Ogata, Yoshiyuki, Kitayama, Ruri
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9066137/
https://www.ncbi.nlm.nih.gov/pubmed/35508965
http://dx.doi.org/10.1186/s12863-022-01052-y
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author Ogata, Yoshiyuki
Kitayama, Ruri
author_facet Ogata, Yoshiyuki
Kitayama, Ruri
author_sort Ogata, Yoshiyuki
collection PubMed
description BACKGROUND: Over a million genomes and mutational analyses of SARS-CoV-2 are available in public databases, which reveal the phylogenetic tree of the virus. Although these data have enabled scientists to closely track the evolution and transmission dynamics of the virus at global and local scales, the Mu variant, recently identified in infections in South America, shows an unusual combination of mutations, and it is difficult to visualize these atypical characteristics in public databases based on a phylogenetic tree. RESULTS: The Vcorn SARS-CoV-2 database was constructed to provide information on COVID-19 infections and mutations in the S protein of the virus based on correlation network analysis. A correlation network was constructed using the recall index of one mutation to another mutation. The network includes several network modules in which nodes represent mutations and are tightly connected to each other. Individual network modules contain mutations of single variants, such as the alpha and delta variants. In the network constructed to emphasize mutations of the Mu variant using the database, the mutations were found to be located in multiple network modules, indicating that the mutations of the variant may have originated from multiple variants or be located at a basal position with a high frequency of mutation. CONCLUSIONS: Vcorn SARS-CoV-2 provides information on COVID-19 and S protein mutations of SARS-CoV-2 via correlation network analysis. The network based on the analysis illustrates the unusual S protein mutations of the Mu variant. The database is freely available at http://www.plant.osakafu-u.ac.jp/~kagiana/vcorn/sarscov2/.
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spelling pubmed-90661372022-05-04 A database for retrieving information on SARS-CoV-2 S protein mutations based on correlation network analysis Ogata, Yoshiyuki Kitayama, Ruri BMC Genom Data Database BACKGROUND: Over a million genomes and mutational analyses of SARS-CoV-2 are available in public databases, which reveal the phylogenetic tree of the virus. Although these data have enabled scientists to closely track the evolution and transmission dynamics of the virus at global and local scales, the Mu variant, recently identified in infections in South America, shows an unusual combination of mutations, and it is difficult to visualize these atypical characteristics in public databases based on a phylogenetic tree. RESULTS: The Vcorn SARS-CoV-2 database was constructed to provide information on COVID-19 infections and mutations in the S protein of the virus based on correlation network analysis. A correlation network was constructed using the recall index of one mutation to another mutation. The network includes several network modules in which nodes represent mutations and are tightly connected to each other. Individual network modules contain mutations of single variants, such as the alpha and delta variants. In the network constructed to emphasize mutations of the Mu variant using the database, the mutations were found to be located in multiple network modules, indicating that the mutations of the variant may have originated from multiple variants or be located at a basal position with a high frequency of mutation. CONCLUSIONS: Vcorn SARS-CoV-2 provides information on COVID-19 and S protein mutations of SARS-CoV-2 via correlation network analysis. The network based on the analysis illustrates the unusual S protein mutations of the Mu variant. The database is freely available at http://www.plant.osakafu-u.ac.jp/~kagiana/vcorn/sarscov2/. BioMed Central 2022-05-04 /pmc/articles/PMC9066137/ /pubmed/35508965 http://dx.doi.org/10.1186/s12863-022-01052-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Database
Ogata, Yoshiyuki
Kitayama, Ruri
A database for retrieving information on SARS-CoV-2 S protein mutations based on correlation network analysis
title A database for retrieving information on SARS-CoV-2 S protein mutations based on correlation network analysis
title_full A database for retrieving information on SARS-CoV-2 S protein mutations based on correlation network analysis
title_fullStr A database for retrieving information on SARS-CoV-2 S protein mutations based on correlation network analysis
title_full_unstemmed A database for retrieving information on SARS-CoV-2 S protein mutations based on correlation network analysis
title_short A database for retrieving information on SARS-CoV-2 S protein mutations based on correlation network analysis
title_sort database for retrieving information on sars-cov-2 s protein mutations based on correlation network analysis
topic Database
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9066137/
https://www.ncbi.nlm.nih.gov/pubmed/35508965
http://dx.doi.org/10.1186/s12863-022-01052-y
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