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The competition between simple and complex evolutionary trajectories in asexual populations
BACKGROUND: On rugged fitness landscapes where sign epistasis is common, adaptation can often involve either individually beneficial “uphill” mutations or more complex mutational trajectories involving fitness valleys or plateaus. The dynamics of the evolutionary process determine the probability th...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4391547/ https://www.ncbi.nlm.nih.gov/pubmed/25881244 http://dx.doi.org/10.1186/s12862-015-0334-0 |
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author | Ochs, Ian E Desai, Michael M |
author_facet | Ochs, Ian E Desai, Michael M |
author_sort | Ochs, Ian E |
collection | PubMed |
description | BACKGROUND: On rugged fitness landscapes where sign epistasis is common, adaptation can often involve either individually beneficial “uphill” mutations or more complex mutational trajectories involving fitness valleys or plateaus. The dynamics of the evolutionary process determine the probability that evolution will take any specific path among a variety of competing possible trajectories. Understanding this evolutionary choice is essential if we are to understand the outcomes and predictability of adaptation on rugged landscapes. RESULTS: We present a simple model to analyze the probability that evolution will eschew immediately uphill paths in favor of crossing fitness valleys or plateaus that lead to higher fitness but less accessible genotypes. We calculate how this probability depends on the population size, mutation rates, and relevant selection pressures, and compare our analytical results to Wright-Fisher simulations. CONCLUSION: We find that the probability of valley crossing depends nonmonotonically on population size: intermediate size populations are most likely to follow a “greedy” strategy of acquiring immediately beneficial mutations even if they lead to evolutionary dead ends, while larger and smaller populations are more likely to cross fitness valleys to reach distant advantageous genotypes. We explicitly identify the boundaries between these different regimes in terms of the relevant evolutionary parameters. Above a certain threshold population size, we show that the probability that the population finds the more distant peak depends only on a single simple combination of the relevant parameters. |
format | Online Article Text |
id | pubmed-4391547 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43915472015-04-10 The competition between simple and complex evolutionary trajectories in asexual populations Ochs, Ian E Desai, Michael M BMC Evol Biol Research Article BACKGROUND: On rugged fitness landscapes where sign epistasis is common, adaptation can often involve either individually beneficial “uphill” mutations or more complex mutational trajectories involving fitness valleys or plateaus. The dynamics of the evolutionary process determine the probability that evolution will take any specific path among a variety of competing possible trajectories. Understanding this evolutionary choice is essential if we are to understand the outcomes and predictability of adaptation on rugged landscapes. RESULTS: We present a simple model to analyze the probability that evolution will eschew immediately uphill paths in favor of crossing fitness valleys or plateaus that lead to higher fitness but less accessible genotypes. We calculate how this probability depends on the population size, mutation rates, and relevant selection pressures, and compare our analytical results to Wright-Fisher simulations. CONCLUSION: We find that the probability of valley crossing depends nonmonotonically on population size: intermediate size populations are most likely to follow a “greedy” strategy of acquiring immediately beneficial mutations even if they lead to evolutionary dead ends, while larger and smaller populations are more likely to cross fitness valleys to reach distant advantageous genotypes. We explicitly identify the boundaries between these different regimes in terms of the relevant evolutionary parameters. Above a certain threshold population size, we show that the probability that the population finds the more distant peak depends only on a single simple combination of the relevant parameters. BioMed Central 2015-03-26 /pmc/articles/PMC4391547/ /pubmed/25881244 http://dx.doi.org/10.1186/s12862-015-0334-0 Text en © Ochs and Desai; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Ochs, Ian E Desai, Michael M The competition between simple and complex evolutionary trajectories in asexual populations |
title | The competition between simple and complex evolutionary trajectories in asexual populations |
title_full | The competition between simple and complex evolutionary trajectories in asexual populations |
title_fullStr | The competition between simple and complex evolutionary trajectories in asexual populations |
title_full_unstemmed | The competition between simple and complex evolutionary trajectories in asexual populations |
title_short | The competition between simple and complex evolutionary trajectories in asexual populations |
title_sort | competition between simple and complex evolutionary trajectories in asexual populations |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4391547/ https://www.ncbi.nlm.nih.gov/pubmed/25881244 http://dx.doi.org/10.1186/s12862-015-0334-0 |
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