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Characterizing the Influence of Effective Population Size on the Rate of Adaptation: Gillespie’s Darwin Domain
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 adaptati...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3157839/ https://www.ncbi.nlm.nih.gov/pubmed/21705473 http://dx.doi.org/10.1093/gbe/evr063 |
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author | Jensen, Jeffrey D. Bachtrog, Doris |
author_facet | Jensen, Jeffrey D. Bachtrog, Doris |
author_sort | Jensen, Jeffrey D. |
collection | PubMed |
description | 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 (N(e)), 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 N(e) 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. |
format | Online Article Text |
id | pubmed-3157839 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-31578392011-08-18 Characterizing the Influence of Effective Population Size on the Rate of Adaptation: Gillespie’s Darwin Domain Jensen, Jeffrey D. Bachtrog, Doris Genome Biol Evol Research Articles 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 (N(e)), 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 N(e) 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. Oxford University Press 2011-06-24 /pmc/articles/PMC3157839/ /pubmed/21705473 http://dx.doi.org/10.1093/gbe/evr063 Text en © The Author(s) 2011. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Jensen, Jeffrey D. Bachtrog, Doris Characterizing the Influence of Effective Population Size on the Rate of Adaptation: Gillespie’s Darwin Domain |
title | Characterizing the Influence of Effective Population Size on the Rate of Adaptation: Gillespie’s Darwin Domain |
title_full | Characterizing the Influence of Effective Population Size on the Rate of Adaptation: Gillespie’s Darwin Domain |
title_fullStr | Characterizing the Influence of Effective Population Size on the Rate of Adaptation: Gillespie’s Darwin Domain |
title_full_unstemmed | Characterizing the Influence of Effective Population Size on the Rate of Adaptation: Gillespie’s Darwin Domain |
title_short | Characterizing the Influence of Effective Population Size on the Rate of Adaptation: Gillespie’s Darwin Domain |
title_sort | characterizing the influence of effective population size on the rate of adaptation: gillespie’s darwin domain |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3157839/ https://www.ncbi.nlm.nih.gov/pubmed/21705473 http://dx.doi.org/10.1093/gbe/evr063 |
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