Identifying the genetic basis of viral spillover using Lassa virus as a test case.

Autor:	Whitlock AOB; Department of Biological Sciences, University of Idaho, Moscow, ID, USA., Bird BH; One Health Institute, School of Veterinary Medicine, University of California, Davis, Davis, CA, USA., Ghersi B; One Health Institute, School of Veterinary Medicine, University of California, Davis, Davis, CA, USA., Davison AJ; MRC-University of Glasgow Centre for Virus Research, Glasgow, UK., Hughes J; MRC-University of Glasgow Centre for Virus Research, Glasgow, UK., Nichols J; MRC-University of Glasgow Centre for Virus Research, Glasgow, UK., Vučak M; MRC-University of Glasgow Centre for Virus Research, Glasgow, UK., Amara E; University of Makeni and University of California, Davis One Health Program, Makeni, Sierra Leone., Bangura J; University of Makeni and University of California, Davis One Health Program, Makeni, Sierra Leone., Lavalie EG; University of Makeni and University of California, Davis One Health Program, Makeni, Sierra Leone., Kanu MC; University of Makeni and University of California, Davis One Health Program, Makeni, Sierra Leone., Kanu OT; University of Makeni and University of California, Davis One Health Program, Makeni, Sierra Leone., Sjodin A; Department of Biological Sciences, University of Idaho, Moscow, ID, USA., Remien CH; Department of Mathematics and Statistical Science, University of Idaho, Moscow, ID, USA., Nuismer SL; Department of Biological Sciences, University of Idaho, Moscow, ID, USA.
Jazyk:	angličtina
Zdroj:	Royal Society open science [R Soc Open Sci] 2023 Mar 22; Vol. 10 (3), pp. 221503. Date of Electronic Publication: 2023 Mar 22 (Print Publication: 2023).
DOI:	10.1098/rsos.221503
Abstrakt:	The rate at which zoonotic viruses spill over into the human population varies significantly over space and time. Remarkably, we do not yet know how much of this variation is attributable to genetic variation within viral populations. This gap in understanding arises because we lack methods of genetic analysis that can be easily applied to zoonotic viruses, where the number of available viral sequences is often limited, and opportunistic sampling introduces significant population stratification. Here, we explore the feasibility of using patterns of shared ancestry to correct for population stratification, enabling genome-wide association methods to identify genetic substitutions associated with spillover into the human population. Using a combination of phylogenetically structured simulations and Lassa virus sequences collected from humans and rodents in Sierra Leone, we demonstrate that existing methods do not fully correct for stratification, leading to elevated error rates. We also demonstrate, however, that the Type I error rate can be substantially reduced by confining the analysis to a less-stratified region of the phylogeny, even in an already-small dataset. Using this method, we detect two candidate single-nucleotide polymorphisms associated with spillover in the Lassa virus polymerase gene and provide generalized recommendations for the collection and analysis of zoonotic viruses. Competing Interests: We declare we have no competing interests. (© 2023 The Authors.)
Databáze:	MEDLINE
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