bioRxivEvolutionary Biology
Genetic drift shapes the evolution of a highly dynamic metapopulation
Abstract
The dynamics of extinction and (re)colonization in habitat patches are common features of metapopulations, causing them to evolve differently than large, stable populations. The propagule model, which assumes genetic bottlenecks during colonization, posits that newly founded subpopulations have low genetic diversity and are genetically highly differentiated from each other. Immigration may then increase diversity and decrease differentiation between subpopulations. Thus, older and/or less isolated subpopulations are expected to have higher genetic diversity and less genetic differentiation. We tested this theory using whole-genome pool-sequencing to characterize nucleotide diversity and differentiation in 60 subpopulations of a natural metapopulation of the cyclical parthenogen Daphnia magna. For comparison, we characterized diversity in a single, large, stable D. magna population. We found reduced (synonymous) genomic diversity, a proxy for effective population size, weak purifying selection, and low rates of adaptive evolution in the metapopulation compared to the large, stable population. These differences suggest that genetic bottlenecks during colonization reduce effective population sizes, which leads to strong genetic drift and reduced selection efficacy in the metapopulation. Consistent with the propagule model, we found lower diversity and increased differentiation in more isolated, younger subpopulations. Our study sheds light on the genomic consequences of extinction-(re)colonization dynamics to an unprecedented degree, giving strong support for the propagule model. We demonstrate that the metapopulation evolves differently from a large, stable population and that the evolutionary process is largely driven by genetic drift.
- organism: Drosophila
- assay: whole-genome sequencing
- research focus: chromatin & epigenetic regulation
- research focus: genome assembly
- research focus: variant calling
- research focus: variant effect prediction
- approach: experimental assay
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