4.7 Article

Evolutionary rate and genetic load in an emblematic Mediterranean tree following an ancient and prolonged population collapse

期刊

MOLECULAR ECOLOGY
卷 29, 期 24, 页码 4797-4811

出版社

WILEY
DOI: 10.1111/mec.15684

关键词

bottleneck; distribution of fitness effects; genetic pauperization; nucleotide diversity; purifying selection efficiency; stone pine

资金

  1. DGAPA-UNAM
  2. EVOLTREE
  3. Horizon 2020 Framework Programme [773383]

向作者/读者索取更多资源

Severe bottlenecks significantly diminish the amount of genetic diversity and the speed at which it accumulates (i.e., evolutionary rate). They further compromise the efficiency of natural selection to eliminate deleterious variants, which may reach fixation in the surviving populations. Consequently, expanding and adapting to new environments may pose a significant challenge when strong bottlenecks result in genetic pauperization. Herein, we surveyed the patterns of nucleotide diversity, molecular adaptation and genetic load across 177 gene-loci in a circum-Mediterranean conifer (Pinus pinea L.) that represents one of the most extreme cases of genetic pauperization in widespread outbreeding taxa. We found very little genetic variation in both hypervariable nuclear microsatellites (SSRs) and gene-loci, which translated into genetic diversity estimates one order of magnitude lower than those previously reported for pines. Such values were consistent with a strong population decline that began some similar to 1 Ma. Comparisons with the related and parapatric maritime pine (Pinus pinaster Ait.) revealed reduced rates of adaptive evolution (alpha and omega(a)) and a significant accumulation of genetic load. It is unlikely that these are the result from differences in mutation rate or linkage disequilibrium between the two species; instead they are the presumable outcome of contrasting demographic histories affecting both the speed at which these taxa accumulate genetic diversity, and the global efficacy of selection. Future studies, and programs for conservation and management, should thus start testing for the effects of genetic load on fitness, and integrating such effects into predictive models.

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