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推断混合人群中的多位点选择。

Inferring multi-locus selection in admixed populations.

机构信息

Genomics Institute, University of California, Santa Cruz; Santa Cruz, California, United States of America.

Department of Biomolecular Engineering, University of California, Santa Cruz; Santa Cruz, California, United States of America.

出版信息

PLoS Genet. 2023 Nov 28;19(11):e1011062. doi: 10.1371/journal.pgen.1011062. eCollection 2023 Nov.

Abstract

Admixture, the exchange of genetic information between distinct source populations, is thought to be a major source of adaptive genetic variation. Unlike mutation events, which periodically generate single alleles, admixture can introduce many selected alleles simultaneously. As such, the effects of linkage between selected alleles may be especially pronounced in admixed populations. However, existing tools for identifying selected mutations within admixed populations only account for selection at a single site, overlooking phenomena such as linkage among proximal selected alleles. Here, we develop and extensively validate a method for identifying and quantifying the individual effects of multiple linked selected sites on a chromosome in admixed populations. Our approach numerically calculates the expected local ancestry landscape in an admixed population for a given multi-locus selection model, and then maximizes the likelihood of the model. After applying this method to admixed populations of Drosophila melanogaster and Passer italiae, we found that the impacts between linked sites may be an important contributor to natural selection in admixed populations. Furthermore, for the situations we considered, the selection coefficients and number of selected sites are overestimated in analyses that do not consider the effects of linkage among selected sites. Our results imply that linkage among selected sites may be an important evolutionary force in admixed populations. This tool provides a powerful generalized method to investigate these crucial phenomena in diverse populations.

摘要

混合,即不同来源群体之间遗传信息的交换,被认为是适应性遗传变异的主要来源。与偶尔产生单个等位基因的突变事件不同,混合可以同时引入许多被选择的等位基因。因此,在混合群体中,选择等位基因之间的连锁效应可能尤为明显。然而,现有的在混合群体中识别被选择突变的工具仅考虑了单个位点的选择,而忽略了近端被选择等位基因之间的连锁等现象。在这里,我们开发并广泛验证了一种方法,用于识别和量化在混合群体中染色体上多个连锁被选择位点对个体的影响。我们的方法通过数值计算给定多基因选择模型在混合群体中的局部亲缘关系景观,然后最大化模型的似然性。将该方法应用于黑腹果蝇和麻雀的混合群体后,我们发现连锁位点之间的影响可能是混合群体中自然选择的一个重要因素。此外,对于我们考虑的情况,如果不考虑被选择的位点之间的连锁效应,分析中被选择的位点的选择系数和数量会被高估。我们的结果表明,连锁的被选择的位点可能是混合群体中一个重要的进化力量。该工具为在不同群体中研究这些关键现象提供了一种强大的通用方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d018/10707604/036d1a896b50/pgen.1011062.g001.jpg

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