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Predicting the global mammalian viral sharing network using phylogeography
Understanding interspecific viral transmission is key to understanding viral ecology and evolution, disease spillover into humans, and the consequences of global change. Prior studies have uncovered macroecological drivers of viral sharing, but analyses have never attempted to predict viral sharing...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7210981/ https://www.ncbi.nlm.nih.gov/pubmed/32385239 http://dx.doi.org/10.1038/s41467-020-16153-4 |
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author | Albery, Gregory F. Eskew, Evan A. Ross, Noam Olival, Kevin J. |
author_facet | Albery, Gregory F. Eskew, Evan A. Ross, Noam Olival, Kevin J. |
author_sort | Albery, Gregory F. |
collection | PubMed |
description | Understanding interspecific viral transmission is key to understanding viral ecology and evolution, disease spillover into humans, and the consequences of global change. Prior studies have uncovered macroecological drivers of viral sharing, but analyses have never attempted to predict viral sharing in a pan-mammalian context. Using a conservative modelling framework, we confirm that host phylogenetic similarity and geographic range overlap are strong, nonlinear predictors of viral sharing among species across the entire mammal class. Using these traits, we predict global viral sharing patterns of 4196 mammal species and show that our simulated network successfully predicts viral sharing and reservoir host status using internal validation and an external dataset. We predict high rates of mammalian viral sharing in the tropics, particularly among rodents and bats, and within- and between-order sharing differed geographically and taxonomically. Our results emphasize the importance of ecological and phylogenetic factors in shaping mammalian viral communities, and provide a robust, general model to predict viral host range and guide pathogen surveillance and conservation efforts. |
format | Online Article Text |
id | pubmed-7210981 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-72109812020-05-13 Predicting the global mammalian viral sharing network using phylogeography Albery, Gregory F. Eskew, Evan A. Ross, Noam Olival, Kevin J. Nat Commun Article Understanding interspecific viral transmission is key to understanding viral ecology and evolution, disease spillover into humans, and the consequences of global change. Prior studies have uncovered macroecological drivers of viral sharing, but analyses have never attempted to predict viral sharing in a pan-mammalian context. Using a conservative modelling framework, we confirm that host phylogenetic similarity and geographic range overlap are strong, nonlinear predictors of viral sharing among species across the entire mammal class. Using these traits, we predict global viral sharing patterns of 4196 mammal species and show that our simulated network successfully predicts viral sharing and reservoir host status using internal validation and an external dataset. We predict high rates of mammalian viral sharing in the tropics, particularly among rodents and bats, and within- and between-order sharing differed geographically and taxonomically. Our results emphasize the importance of ecological and phylogenetic factors in shaping mammalian viral communities, and provide a robust, general model to predict viral host range and guide pathogen surveillance and conservation efforts. Nature Publishing Group UK 2020-05-08 /pmc/articles/PMC7210981/ /pubmed/32385239 http://dx.doi.org/10.1038/s41467-020-16153-4 Text en © The Author(s) 2020 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/. |
spellingShingle | Article Albery, Gregory F. Eskew, Evan A. Ross, Noam Olival, Kevin J. Predicting the global mammalian viral sharing network using phylogeography |
title | Predicting the global mammalian viral sharing network using phylogeography |
title_full | Predicting the global mammalian viral sharing network using phylogeography |
title_fullStr | Predicting the global mammalian viral sharing network using phylogeography |
title_full_unstemmed | Predicting the global mammalian viral sharing network using phylogeography |
title_short | Predicting the global mammalian viral sharing network using phylogeography |
title_sort | predicting the global mammalian viral sharing network using phylogeography |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7210981/ https://www.ncbi.nlm.nih.gov/pubmed/32385239 http://dx.doi.org/10.1038/s41467-020-16153-4 |
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