祖先品系在选择过程中的变异过程。

IF 1.2 4区 生物学 Q4 ECOLOGY
E. Baake , F. Cordero , E. Di Gaspero
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引用次数: 0

摘要

我们考虑了具有突变和选择两种类型的种群遗传学莫兰模型,并研究了从当代种群中随机抽样的个体的世系。为此,我们使用了经过修剪的祖先选择图(Lenz 等人,2015 年),该图由采样个体在任何给定时间的潜在祖先集合组成。与中性情况(即无选择)相比,我们发现有益类型普遍偏多,有益突变率增加,有害突变率降低。这对之前的分析结果有了新的启示。我们将根据系统发生学和群体遗传学交界处的一个众所周知的观察结果来讨论我们的发现,即通过系统发生学方法估计的突变率(或更准确地说,突变通量)与在血统研究中观察到的突变率之间的差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The mutation process on the ancestral line under selection

We consider the Moran model of population genetics with two types, mutation, and selection, and investigate the line of descent of a randomly-sampled individual from a contemporary population. We trace this ancestral line back into the distant past, far beyond the most recent common ancestor of the population (thus connecting population genetics to phylogeny), and analyse the mutation process along this line.

To this end, we use the pruned lookdown ancestral selection graph (Lenz et al., 2015), which consists of a set of potential ancestors of the sampled individual at any given time. Relative to the neutral case (that is, without selection), we obtain a general bias towards the beneficial type, an increase in the beneficial mutation rate, and a decrease in the deleterious mutation rate. This sheds new light on previous analytical results. We discuss our findings in the light of a well-known observation at the interface of phylogeny and population genetics, namely, the difference in the mutation rates (or, more precisely, mutation fluxes) estimated via phylogenetic methods relative to those observed in pedigree studies.

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来源期刊
Theoretical Population Biology
Theoretical Population Biology 生物-进化生物学
CiteScore
2.50
自引率
14.30%
发文量
43
审稿时长
6-12 weeks
期刊介绍: An interdisciplinary journal, Theoretical Population Biology presents articles on theoretical aspects of the biology of populations, particularly in the areas of demography, ecology, epidemiology, evolution, and genetics. Emphasis is on the development of mathematical theory and models that enhance the understanding of biological phenomena. Articles highlight the motivation and significance of the work for advancing progress in biology, relying on a substantial mathematical effort to obtain biological insight. The journal also presents empirical results and computational and statistical methods directly impinging on theoretical problems in population biology.
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