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Rapid adaptive amplification of preexisting variation in an RNA virus.

TitleRapid adaptive amplification of preexisting variation in an RNA virus.
Publication TypeJournal Article
Year of Publication2008
AuthorsDutta, RN, IM Rouzine, Smith, SD, Wilke, CO, Novella, IS
JournalJ Virol
Date Published2008 May
KeywordsAdaptation, Physiological, Genetic Variation, Genetics, Population, Genome, Viral, Models, Genetic, RNA Viruses, Selection, Genetic, Vesicular Stomatitis, Virus Replication

The amount and nature of preexisting variation in a population of RNA viruses is an important determinant of the virus's ability to adapt rapidly to a changed environment. However, direct quantification of this preexisting variation may be cumbersome, because potentially beneficial alleles are typically rare, and isolation of a large number of subclones is required. Here, we propose a simpler method. We infer the initial population structure of vesicular stomatitis virus (VSV) by fitting a mathematical model of asexual evolution to an extensive set of measurements of VSV fitness dynamics under various conditions, including new and previously published data. The inferred variation of fitness in the initial population agrees very well with the results of direct experiments with subclone fitness quantification. From the same procedure, we also estimate the mean fitness effect of beneficial mutations (selection coefficient s), the percentage of sites in the genome that are under moderate positive or negative selection, and the percentage of sites where beneficial mutations may potentially occur. For VSV strain MARM U evolving in BHK-21 cells, the three parameters have values of 0.39, 9%, and 0.06%, respectively. The method can be generalized and applied easily to other rapidly evolving microbes, including both asexual microorganisms and those with recombination.

Alternate JournalJ. Virol.
PubMed ID18287227
PubMed Central IDPMC2293023
Grant ListR01 AI065960 / AI / NIAID NIH HHS / United States
R01AI0639236 / AI / NIAID NIH HHS / United States
R01AI065960 / AI / NIAID NIH HHS / United States

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