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A comprehensive dataset of animal-associated sarbecoviruses
Zoonotic spillover of sarbecoviruses (SarbeCoVs) from non-human animals to humans under natural conditions has led to two large-scale pandemics, the severe acute respiratory syndrome (SARS) pandemic in 2003 and the ongoing COVID-19 pandemic. Knowledge of the genetic diversity, geographical distribut...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10560225/ https://www.ncbi.nlm.nih.gov/pubmed/37805633 http://dx.doi.org/10.1038/s41597-023-02558-5 |
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author | Liu, Bo Zhao, Peng Xu, Panpan Han, Yelin Wang, Yuyang Chen, Lihong Wu, Zhiqiang Yang, Jian |
author_facet | Liu, Bo Zhao, Peng Xu, Panpan Han, Yelin Wang, Yuyang Chen, Lihong Wu, Zhiqiang Yang, Jian |
author_sort | Liu, Bo |
collection | PubMed |
description | Zoonotic spillover of sarbecoviruses (SarbeCoVs) from non-human animals to humans under natural conditions has led to two large-scale pandemics, the severe acute respiratory syndrome (SARS) pandemic in 2003 and the ongoing COVID-19 pandemic. Knowledge of the genetic diversity, geographical distribution, and host specificity of SarbeCoVs is therefore of interest for pandemic surveillance and origin tracing of SARS-CoV and SARS-CoV-2. This study presents a comprehensive repository of publicly available animal-associated SarbeCoVs, covering 1,535 viruses identified from 63 animal species distributed in 43 countries worldwide (as of February 14,2023). Relevant meta-information, such as host species, sampling time and location, was manually curated and included in the dataset to facilitate further research on the potential patterns of viral diversity and ecological characteristics. In addition, the dataset also provides well-annotated sequence sets of receptor-binding domains (RBDs) and receptor-binding motifs (RBMs) for the scientific community to highlight the potential determinants of successful cross-species transmission that could be aid in risk estimation and strategic design for future emerging infectious disease control and prevention. |
format | Online Article Text |
id | pubmed-10560225 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105602252023-10-09 A comprehensive dataset of animal-associated sarbecoviruses Liu, Bo Zhao, Peng Xu, Panpan Han, Yelin Wang, Yuyang Chen, Lihong Wu, Zhiqiang Yang, Jian Sci Data Data Descriptor Zoonotic spillover of sarbecoviruses (SarbeCoVs) from non-human animals to humans under natural conditions has led to two large-scale pandemics, the severe acute respiratory syndrome (SARS) pandemic in 2003 and the ongoing COVID-19 pandemic. Knowledge of the genetic diversity, geographical distribution, and host specificity of SarbeCoVs is therefore of interest for pandemic surveillance and origin tracing of SARS-CoV and SARS-CoV-2. This study presents a comprehensive repository of publicly available animal-associated SarbeCoVs, covering 1,535 viruses identified from 63 animal species distributed in 43 countries worldwide (as of February 14,2023). Relevant meta-information, such as host species, sampling time and location, was manually curated and included in the dataset to facilitate further research on the potential patterns of viral diversity and ecological characteristics. In addition, the dataset also provides well-annotated sequence sets of receptor-binding domains (RBDs) and receptor-binding motifs (RBMs) for the scientific community to highlight the potential determinants of successful cross-species transmission that could be aid in risk estimation and strategic design for future emerging infectious disease control and prevention. Nature Publishing Group UK 2023-10-07 /pmc/articles/PMC10560225/ /pubmed/37805633 http://dx.doi.org/10.1038/s41597-023-02558-5 Text en © The Author(s) 2023 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 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/) . |
spellingShingle | Data Descriptor Liu, Bo Zhao, Peng Xu, Panpan Han, Yelin Wang, Yuyang Chen, Lihong Wu, Zhiqiang Yang, Jian A comprehensive dataset of animal-associated sarbecoviruses |
title | A comprehensive dataset of animal-associated sarbecoviruses |
title_full | A comprehensive dataset of animal-associated sarbecoviruses |
title_fullStr | A comprehensive dataset of animal-associated sarbecoviruses |
title_full_unstemmed | A comprehensive dataset of animal-associated sarbecoviruses |
title_short | A comprehensive dataset of animal-associated sarbecoviruses |
title_sort | comprehensive dataset of animal-associated sarbecoviruses |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10560225/ https://www.ncbi.nlm.nih.gov/pubmed/37805633 http://dx.doi.org/10.1038/s41597-023-02558-5 |
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