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Updated: Apr 17, 2026

Combining Analysis of DNA in a Crude Virion Extraction with the Analysis of RNA from Infected Leaves to Discover New Virus Genomes
Published on: July 27, 2018
Temporal dynamics of intrahost molecular evolution for a plant RNA virus
José M Cuevas1, Anouk Willemsen1, Julia Hillung1
1Instituto de Biología Molecular y Celular de Plantas, Consejo Superior de Investigaciones Científicas-Universidad Politécnica de Valencia, València, Spain.
Abstract:
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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