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One Is Enough: In Vivo Effective Population Size Is Dose- Dependent for a Plant RNA Virus

AuthorsZwart, Mark P. ; Daròs Arnau, José Antonio ; Elena, Santiago F.
Issue DateMay-2011
PublisherPublic Library of Science
CitationPLoS Pathogens 7/7: e1002122 (2011)
AbstractEffective population size (Ne) determines the strength of genetic drift and the frequency of co-infection by multiple genotypes, making it a key factor in viral evolution. Experimental estimates of Ne for different plant viruses have, however, rendered diverging results. The independent action hypothesis (IAH) states that each virion has a probability of infection, and that virions act independent of one another during the infection process. A corollary of IAH is that Ne must be dose dependent. A test of IAH for a plant virus has not been reported yet. Here we perform a test of an IAH infection model using a plant RNA virus, Tobacco etch virus (TEV) variants carrying GFP or mCherry fluorescent markers, in Nicotiana tabacum and Capsicum annuum plants. The number of primary infection foci increased linearly with dose, and was similar to a Poisson distribution. At high doses, primary infection foci containing both genotypes were found at a low frequency (,2%). The probability that a genotype that infected the inoculated leaf would systemically infect that plant was near 1, although in a few rare cases genotypes could be trapped in the inoculated leaf by being physically surrounded by the other genotype. The frequency of mixed-genotype infection could be predicted from the mean number of primary infection foci using the independent-action model. Independent action appears to hold for TEV, and Ne is therefore dose-dependent for this plant RNA virus. The mean number of virions causing systemic infection can be very small, and approaches 1 at low doses. Dosedependency in TEV suggests that comparison of Ne estimates for different viruses are not very meaningful unless dose effects are taken into consideration.
Publisher version (URL). doi:10.1371/journal.ppat.1002122
Appears in Collections:(IBMCP) Artículos
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