Babayan, S. A. , Orton, R. J. and Streicker, D. G. (2018) Predicting reservoir hosts and arthropod vectors from evolutionary signatures in RNA virus genomes. Science, 362(6414), pp. 577-580. (doi: 10.1126/science.aap9072) (PMID:30385576) (PMCID:PMC6536379)
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Abstract
Identifying the animal origins of RNA viruses requires years of field and laboratory studies that stall responses to emerging infectious diseases. Using large genomic and ecological datasets, we demonstrate that animal reservoirs and the existence and identity of arthropod vectors can be predicted directly from viral genome sequences via machine learning. We illustrate the ability of these models to predict the epidemiology of diverse viruses across most human-infective families of single-stranded RNA viruses, including 69 viruses with previously elusive or never-investigated reservoirs or vectors. Models such as these, which capitalize on the proliferation of low-cost genomic sequencing, can narrow the time lag between virus discovery and targeted research, surveillance, and management.
Item Type: | Articles |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Orton, Dr Richard and Babayan, Dr Simon and Streicker, Professor Daniel |
Authors: | Babayan, S. A., Orton, R. J., and Streicker, D. G. |
College/School: | College of Medical Veterinary and Life Sciences > School of Infection & Immunity College of Medical Veterinary and Life Sciences > School of Infection & Immunity > Centre for Virus Research College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine |
Journal Name: | Science |
Publisher: | American Association for the Advancement of Science |
ISSN: | 0036-8075 |
ISSN (Online): | 1095-9203 |
Copyright Holders: | Copyright © 2018 The Authors |
First Published: | First published in Science 362(6414): 577-580 |
Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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