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在持续高斯选择下平均表型的差异。

The divergence of mean phenotypes under persistent Gaussian selection.

作者信息

Lynch Michael, Menor Scott

机构信息

Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ 85287, USA.

出版信息

Genetics. 2025 Apr 17;229(4). doi: 10.1093/genetics/iyaf031.

DOI:10.1093/genetics/iyaf031
PMID:39999028
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12005259/
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.

摘要

尽管多基因性状通常被认为受到某种形式的稳定选择,但群体遗传环境的许多方面会导致平均表型偏离假定的最优值,而且往往是以有效地将适应度景观转变为定向选择景观的方式。以无性繁殖群体为研究对象,我们考虑了这些偏离如何随着选择和遗传漂变的相对强度、连锁基因组位点的数量、突变偏向的程度以及最优值相对于可能的基因型空间的位置而变化。即使没有突变偏向,突变也会影响进化的平均表型,除非最优值恰好与中性条件下预期的平均值完全一致。在存在定向突变偏向和大量被选择位点的情况下,有效种群大小(Ne)会因选择干扰效应而大幅降低,导致表型均值与最优值之间出现进一步的不匹配。最优值位于可能的基因型空间之外或接近其边界的情况(例如半高斯适应度函数)会导致相对于Ne的表型均值出现特别明显的梯度变化,但当最优值完全处于可达到的表型范围内时,这种梯度变化也可能出现。这些结果有助于阐明在经历相同突变和选择压力但Ne不同的群体中,平均表型能够变化的程度,并深入了解预期的尺度关系如何依赖于遗传系统的潜在特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb94/12005259/a6a425565827/iyaf031f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb94/12005259/2343e388d5f0/iyaf031f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb94/12005259/09aade420ef1/iyaf031f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb94/12005259/1f60a3b3334c/iyaf031f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb94/12005259/19c1dc44314f/iyaf031f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb94/12005259/a6a425565827/iyaf031f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb94/12005259/2343e388d5f0/iyaf031f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb94/12005259/09aade420ef1/iyaf031f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb94/12005259/1f60a3b3334c/iyaf031f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb94/12005259/19c1dc44314f/iyaf031f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb94/12005259/a6a425565827/iyaf031f5.jpg

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本文引用的文献

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The effects of weak selection on neutral diversity at linked sites.连锁位点中性多样性的弱选择效应。
Genetics. 2022 May 5;221(1). doi: 10.1093/genetics/iyac027.
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How Long Does It Take to Fix a Favorable Mutation, and Why Should We Care?有利突变的修复需要多长时间,我们为什么要关心?
Am Nat. 2020 May;195(5):753-771. doi: 10.1086/708187. Epub 2020 Mar 30.
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Evolution. 2018 Sep;72(9):1740-1758. doi: 10.1111/evo.13547. Epub 2018 Jul 26.
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