The divergence of mean phenotypes under persistent Gaussian selection.

IF 3.3 3区 生物学 Q2 GENETICS & HEREDITY
Genetics Pub Date : 2025-04-17 DOI:10.1093/genetics/iyaf031
Michael Lynch, Scott Menor
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引用次数: 0

Abstract

Although multigenic traits are often assumed to be under some form of stabilizing selection, numerous aspects of the population-genetic environment can cause mean phenotypes to deviate from presumed optima, often in ways that effectively transform the fitness landscape to one of directional selection. Focusing on an asexual population, we consider the ways in which such deviations scale with the relative power of selection and genetic drift, the number of linked genomic sites, the magnitude of mutation bias, and the location of optima with respect to possible genotypic space. Even in the absence of mutation bias, mutation will influence evolved mean phenotypes unless the optimum happens to coincide exactly with the mean expected under neutrality. In the case of directional mutation bias and large numbers of selected sites, effective population sizes (Ne) can be dramatically reduced by selective interference effects, leading to further mismatches between phenotypic means and optima. Situations in which the optimum is outside or near the limits of possible genotypic space (e.g. a half-Gaussian fitness function) can lead to particularly pronounced gradients of phenotypic means with respect to Ne, but such gradients can also occur when optima are well within the bounds of attainable phenotypes. These results help clarify the degree to which mean phenotypes can vary among populations experiencing identical mutation and selection pressures but differing in Ne, and yield insight into how the expected scaling relationships depend on the underlying features of the genetic system.

持续高斯选择下的平均表型分化。
虽然多基因性状通常被认为处于某种形式的稳定选择之下,但群体遗传环境的许多方面可能导致平均表型偏离假设的最佳值,通常以有效地将适应度景观转变为定向选择的方式。以无性群体为研究对象,我们考虑了这种偏差与选择和遗传漂变的相对力量、关联基因组位点的数量、突变偏差的大小以及相对于可能的基因型空间的最优位置的关系。即使在没有突变偏差的情况下,突变也会影响进化的平均表型,除非最优恰好与中性条件下的预期平均值相吻合。在定向突变偏倚和大量选择位点的情况下,有效种群大小(Ne)会因选择干扰效应而显著降低,导致表型平均值和最优值之间进一步不匹配。当最优值在可能的基因型空间的极限之外或附近时(例如,半高斯适应度函数),可能导致表型均值相对于Ne的特别明显的梯度,但当最优值在可获得的表型范围内时,也可能发生这种梯度。这些结果有助于澄清平均表型在经历相同突变和选择压力但在Ne中不同的种群之间的差异程度,并深入了解预期的缩放关系如何依赖于遗传系统的潜在特征。
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来源期刊
Genetics
Genetics GENETICS & HEREDITY-
CiteScore
6.90
自引率
6.10%
发文量
177
审稿时长
1.5 months
期刊介绍: GENETICS is published by the Genetics Society of America, a scholarly society that seeks to deepen our understanding of the living world by advancing our understanding of genetics. Since 1916, GENETICS has published high-quality, original research presenting novel findings bearing on genetics and genomics. The journal publishes empirical studies of organisms ranging from microbes to humans, as well as theoretical work. While it has an illustrious history, GENETICS has changed along with the communities it serves: it is not your mentor''s journal. The editors make decisions quickly – in around 30 days – without sacrificing the excellence and scholarship for which the journal has long been known. GENETICS is a peer reviewed, peer-edited journal, with an international reach and increasing visibility and impact. All editorial decisions are made through collaboration of at least two editors who are practicing scientists. GENETICS is constantly innovating: expanded types of content include Reviews, Commentary (current issues of interest to geneticists), Perspectives (historical), Primers (to introduce primary literature into the classroom), Toolbox Reviews, plus YeastBook, FlyBook, and WormBook (coming spring 2016). For particularly time-sensitive results, we publish Communications. As part of our mission to serve our communities, we''ve published thematic collections, including Genomic Selection, Multiparental Populations, Mouse Collaborative Cross, and the Genetics of Sex.
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