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pubmed:abstractText |
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.
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