Bridging Wright–Fisher and Moran models

The Wright-Fisher model and the Moran model are both widely used in population genetics. They describe the time evolution of the frequency of an allele in a well-mixed population with fixed size. We propose a simple and tractable model which bridges the Wright-Fisher and the Moran descriptions. We assume that a fixed fraction of the population is updated at each discrete time step. In this model, we determine the fixation probability of a mutant and its average fixation and extinction times, under the diffusion approximation. We further study the associated coalescent process, which converges to Kingman's coalescent, and we calculate effective population sizes. We generalize our model, first by taking into account fluctuating updated fractions or individual lifetimes, and then by incorporating selection on the lifetime as well as on the reproductive fitness.

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Publication Details

Journal
Journal of Theoretical Biology
Published
2024-12-19
DOI
https://doi.org/10.1016/j.jtbi.2024.112030
Citations
5
Primary Topic
Evolutionary Game Theory and Cooperation
Type
article
Field-Weighted Citation Impact
5.66

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Bridging Wright–Fisher and Moran models

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Journal of Theoretical Biology
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Bridging Wright–Fisher and Moran models

Anne‐Florence Bitbol, Alia Abbara, Arthur Alexandre, Claude Loverdo, Cecilia Fruet
article en
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Abstract

The Wright-Fisher model and the Moran model are both widely used in population genetics. They describe the time evolution of the frequency of an allele in a well-mixed population with fixed size. We propose a simple and tractable model which bridges the Wright-Fisher and the Moran descriptions. We assume that a fixed fraction of the population is updated at each discrete time step. In this model, we determine the fixation probability of a mutant and its average fixation and extinction times, under the diffusion approximation. We further study the associated coalescent process, which converges to Kingman's coalescent, and we calculate effective population sizes. We generalize our model, first by taking into account fluctuating updated fractions or individual lifetimes, and then by incorporating selection on the lifetime as well as on the reproductive fitness.

Journal of Theoretical BiologyVol. 599
SIB Swiss Institute of Bioinformatics (CH), Centre National de la Recherche Scientifique (FR), Sorbonne Université (FR), Laboratoire Jean Perrin (FR), Institut de Biologie Paris-Seine (FR), École Polytechnique Fédérale de Lausanne (CH)
Chan Zuckerberg Initiative, Agence Nationale de la Recherche, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Horizon 2020 Framework Programme, European Research Council, Horizon 2020, H2020 European Research Council
Openalex Percentile: Top 4%
Evolutionary Game Theory and Cooperation
5.66
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