溯祖理论
群体遗传学
进化生物学
生物
适应(眼睛)
遗传漂变
遗传多样性
人口
人类进化遗传学
选择(遗传算法)
推论
有效人口规模
人口规模
中性分子进化理论
遗传变异
遗传学
计算机科学
基因
基因组
人工智能
系统发育学
人口学
社会学
神经科学
标识
DOI:10.1146/annurev-ecolsys-110512-135920
摘要
To learn about the past from a sample of genomic sequences, one needs to understand how evolutionary processes shape genetic diversity. Most population genetics inferences are based on frameworks assuming that adaptive evolution is rare. But if positive selection operates on many loci simultaneously, as has recently been suggested for many species, including animals such as flies, then a different approach is necessary. In this review, I discuss recent progress in characterizing and understanding evolution in rapidly adapting populations, in which random associations of mutations with genetic backgrounds of different fitness, i.e., genetic draft, dominate over genetic drift. As a result, neutral genetic diversity depends weakly on population size but strongly on the rate of adaptation or more generally the variance in fitness. Coalescent processes with multiple mergers, rather than Kingman's coalescent, are appropriate genealogical models for rapidly adapting populations, with important implications for population genetics inference.
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