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Non-Poissonian Bursts in the Arrival of Phenotypic Variation Can Strongly Affect the Dynamics of Adaptation

Abstract:
Modeling the rate at which adaptive phenotypes appear in a population is a key to predicting evolutionary processes. Given random mutations, should this rate be modeled by a simple Poisson process, or is a more complex dynamics needed? Here we use analytic calculations and simulations of evolving populations on explicit genotype–phenotype maps to show that the introduction of novel phenotypes can be “bursty” or overdispersed. In other words, a novel phenotype either appears multiple times in quick succession or not at all for many generations. These bursts are fundamentally caused by statistical fluctuations and other structure in the map from genotypes to phenotypes. Their strength depends on population parameters, being highest for “monomorphic” populations with low mutation rates. They can also be enhanced by additional inhomogeneities in the mapping from genotypes to phenotypes. We mainly investigate the effect of bursts using the well-studied genotype–phenotype map for RNA secondary structure, but find similar behavior in a lattice protein model and in Richard Dawkins’s biomorphs model of morphological development. Bursts can profoundly affect adaptive dynamics. Most notably, they imply that fitness differences play a smaller role in determining which phenotype fixes than would be the case for a Poisson process without bursts.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1093/molbev/msae085

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Institution:
University of Oxford
Role:
Author
ORCID:
0000-0003-4026-0985
More by this author
Institution:
University of Oxford
Role:
Author
More by this author
Institution:
University of Oxford
Role:
Author
More by this author
Institution:
University of Oxford
Role:
Author



Publisher:
Oxford University Press
Journal:
Molecular Biology and Evolution More from this journal
Volume:
41
Issue:
6
Article number:
msae085
Publication date:
2024-05-02
Acceptance date:
2024-04-17
DOI:
EISSN:
1537-1719
ISSN:
0737-4038


Language:
English
Keywords:
Source identifiers:
2023940
Deposit date:
2024-06-06

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