Journal Article

Characterizing the Influence of Effective Population Size on the Rate of Adaptation: Gillespie’s Darwin Domain

Jeffrey D. Jensen and Doris Bachtrog

in Genome Biology and Evolution

Published on behalf of Society for Molecular Biology and Evolution

Volume 3, issue , pages 687-701
Published in print January 2011 |
Published online June 2011 | e-ISSN: 1759-6653 | DOI: http://dx.doi.org/10.1093/gbe/evr063

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Characterizing the role of effective population size in dictating the rate of adaptive evolution remains a major challenge in evolutionary biology. Depending on the underlying distribution of fitness effects of new mutations, populations of different sizes may differ vastly in their rate of adaptation. Here, we collect polymorphism data at over 100 loci for two closely related Drosophila species with different current effective population sizes (Ne), Drosophila miranda and D. pseudoobscura, to evaluate the prevalence of adaptive evolution versus genetic drift in molecular evolution. Utilizing these large and consistently sampled data sets, we obtain greatly improved estimates of the demographic histories of both species. Specifically, although current Ne differs between these species, their ancestral sizes were much more similar. We find that statistical approaches capturing recent adaptive evolution (using patterns of polymorphisms) detect higher rates of adaptive evolution in the larger D. pseudoobscura population. In contrast, methods aimed at detecting selection over longer time periods (i.e., those relying on divergence data) estimate more similar rates of adaptation between the two species. Thus, our results suggest an important role of effective population size in dictating rates of adaptation and highlight how complicated population histories—as is probably the case for most species—can effect rates of adaptation. Additionally, we also show how different methodologies to detect positive selection can reveal information about different timescales of adaptive evolution.

Keywords: selective sweeps; demography; natural selection

Journal Article.  10577 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology ; Evolutionary Biology ; Genetics and Genomics

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