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Temporal Dynamics of Intrahost Molecular Evolution for a Plant RNA Virus
Author(s) -
José M. Cuevas,
Anouk Willemsen,
Julia Hillung,
Mark P. Zwart,
Santiago F. Elena
Publication year - 2015
Publication title -
molecular biology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.637
H-Index - 218
eISSN - 1537-1719
pISSN - 0737-4038
DOI - 10.1093/molbev/msv028
Subject(s) - biology , evolutionary biology , genetic drift , host (biology) , population , viral evolution , genetics , natural selection , evolutionary dynamics , experimental evolution , nonsynonymous substitution , molecular evolution , neutral theory of molecular evolution , effective population size , selection (genetic algorithm) , genetic diversity , viral quasispecies , genetic variation , gene , phylogenetics , rna , genome , demography , artificial intelligence , sociology , computer science
Populations of plant RNA viruses are highly polymorphic in infected plants, which may allow rapid within-host evolution. To understand tobacco etch potyvirus (TEV) evolution, longitudinal samples from experimentally evolved populations in the natural host tobacco and from the alternative host pepper were phenotypically characterized and genetically analyzed. Temporal and compartmental variabilities of TEV populations were quantified using high throughput Illumina sequencing and population genetic approaches. Of the two viral phenotypic traits measured, virulence increased in the novel host but decreased in the original one, and viral load decreased in both hosts, though to a lesser extent in the novel one. Dynamics of population genetic diversity were also markedly different among hosts. Population heterozygosity increased in the ancestral host, with a dominance of synonymous mutations fixed, whereas it did not change or even decreased in the new host, with an excess of nonsynonymous mutations. All together, these observations suggest that directional selection is the dominant evolutionary force in TEV populations evolving in a novel host whereas either diversifying selection or random genetic drift may play a fundamental role in the natural host. To better understand these evolutionary dynamics, we developed a computer simulation model that incorporates the effects of mutation, selection, and drift. Upon parameterization with empirical data from previous studies, model predictions matched the observed patterns, thus reinforcing our idea that the empirical patterns of mutation accumulation represent adaptive evolution.

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