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The traveling-wave approach to asexual evolution: Muller's ratchet and speed of adaptation.

TitleThe traveling-wave approach to asexual evolution: Muller's ratchet and speed of adaptation.
Publication TypeJournal Article
Year of Publication2008
AuthorsIM Rouzine, Brunet, E, Wilke, CO
JournalTheor Popul Biol
Volume73
Issue1
Pagination24-46
Date Published2008 Feb
ISSN0040-5809
KeywordsAdaptation, Physiological, Animals, Biological Evolution, Genetics, Population, Models, Statistical, Models, Theoretical, Plants, Population Dynamics, Reproduction, Asexual, Selection, Genetic, Stochastic Processes, Viruses
Abstract

We use traveling-wave theory to derive expressions for the rate of accumulation of deleterious mutations under Muller's ratchet and the speed of adaptation under positive selection in asexual populations. Traveling-wave theory is a semi-deterministic description of an evolving population, where the bulk of the population is modeled using deterministic equations, but the class of the highest-fitness genotypes, whose evolution over time determines loss or gain of fitness in the population, is given proper stochastic treatment. We derive improved methods to model the highest-fitness class (the stochastic edge) for both Muller's ratchet and adaptive evolution, and calculate analytic correction terms that compensate for inaccuracies which arise when treating discrete fitness classes as a continuum. We show that traveling-wave theory makes excellent predictions for the rate of mutation accumulation in the case of Muller's ratchet, and makes good predictions for the speed of adaptation in a very broad parameter range. We predict the adaptation rate to grow logarithmically in the population size until the population size is extremely large.

DOI10.1016/j.tpb.2007.10.004
Alternate JournalTheor Popul Biol
PubMed ID18023832
PubMed Central IDPMC2246079
Grant ListR01 AI063926-02 / AI / NIAID NIH HHS / United States
R01 AI065960 / AI / NIAID NIH HHS / United States
R01AI065960 / AI / NIAID NIH HHS / United States
R01 AI0639236 / AI / NIAID NIH HHS / United States