Viral priorities from genomic signatures

Access through your institution Buy or subscribe Mollentze, N. et al. _PLoS Biol_. https://doi.org/10.1371/journal.pbio.3001390 (2021) It is likely that more than a million different viruses

infect animals, and high-throughput sequencing is allowing genomic descriptions of hundreds of them. Yet only a small proportion of these will ever move from their animal reservoirs to

infect humans. Writing in _PLoS Biology_, Mollentze et al. used genome sequences of 861 RNA and DNA viruses to develop machine-learning models that predict zoonotic potential. Models trained

on the basis of genomic signatures of known human-infecting viruses were better at identifying candidates for zoonosis than models trained on viral phylogenetic relatedness to known

human-infecting viruses; the authors suggest this indicates the existence of generalizable genomic features that pre-adapt viruses to human infectivity. When the authors tested their model

on 645 other animal-associated viruses, they identified 41 very high-risk candidates for zoonosis; viruses associated with non-human primates were particularly represented in the high-risk

category, consistent with expectations from known virus movement between phylogenetically close hosts. The method may aid in the prioritization of animal viruses for further investigation or

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Ecology & Evolution https://www.nature.com/natecolevol Marian Turner Authors * Marian Turner View author publications You can also search for this author inPubMed Google Scholar

CORRESPONDING AUTHOR Correspondence to Marian Turner. RIGHTS AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Turner, M. Viral priorities from genomic

signatures. _Nat Ecol Evol_ 5, 1570 (2021). https://doi.org/10.1038/s41559-021-01599-6 Download citation * Published: 08 November 2021 * Issue Date: December 2021 * DOI:

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