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Proceedings of the Royal Society B Biological Sciences
Article . 2007 . Peer-reviewed
License: Royal Society Data Sharing and Accessibility
Data sources: Crossref
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Quasi-species evolution in subdivided populations favours maximally deleterious mutations

Authors: Brendan D, O'Fallon; Frederick R, Adler; Stephen R, Proulx;

Quasi-species evolution in subdivided populations favours maximally deleterious mutations

Abstract

Most models of quasi-species evolution predict that populations will evolve to occupy areas of sequence space with the greatest concentration of neutral sequences, thus minimizing the deleterious mutation rate and creating mutationally ‘robust’ genomes. In contrast, empirical studies of the principal model of quasi-species evolution, RNA viruses, suggest that the effects of deleterious mutations are more severe than in similar DNA-based microbes. We demonstrate that populations divided into discrete patches connected by dispersal may favour genotypes where the deleterious effect of non-neutral mutations is maximized. This effect is especially strong in the absence of back mutation and when the amount of time spent in hosts prior to dispersal is intermediate. Our results indicate that RNA viruses that produce acute infections initiated by a small number of virions are expected to evolve fragile genetic architectures when compared with other RNA viruses.

Related Organizations
Keywords

Genotype, Mutation, RNA Viruses, Computer Simulation, Selection, Genetic, Biological Evolution, Models, Biological

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Average
Average
Average
bronze