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Detecting Selection on Segregating Gene Duplicates in a Population
Journal of Molecular Evolution ( IF 3.9 ) Pub Date : 2021-08-02 , DOI: 10.1007/s00239-021-10024-2
Tristan L Stark 1, 2 , Rebecca S Kaufman 1 , Maria A Maltepes 1 , Peter B Chi 1, 3 , David A Liberles 1
Affiliation  

Gene duplication is a fundamental process that has the potential to drive phenotypic differences between populations and species. While evolutionarily neutral changes have the potential to affect phenotypes, detecting selection acting on gene duplicates can uncover cases of adaptive diversification. Existing methods to detect selection on duplicates work mostly inter-specifically and are based upon selection on coding sequence changes, here we present a method to detect selection directly on a copy number variant segregating in a population. The method relies upon expected relationships between allele (new duplication) age and frequency in the population dependent upon the effective population size. Using both a haploid and a diploid population with a Moran Model under several population sizes, the neutral baseline for copy number variants is established. The ability of the method to reject neutrality for duplicates with known age (measured in pairwise dS value) and frequency in the population is established through mathematical analysis and through simulations. Power is particularly good in the diploid case and with larger effective population sizes, as expected. With extension of this method to larger population sizes, this is a tool to analyze selection on copy number variants in any natural or experimentally evolving population. We have made an R package available at https://github.com/peterbchi/CNVSelectR/ which implements the method introduced here.



中文翻译:

检测在群体中分离基因重复的选择

基因复制是一个基本过程,有可能推动种群和物种之间的表型差异。虽然进化中性变化有可能影响表型,但检测作用于基因重复的选择可以揭示适应性多样化的案例。现有的检测重复选择的方法主要是在特异性间工作的,并且基于对编码序列变化的选择,这里我们提出了一种直接在群体中分离的拷贝数变异上检测选择的方法。该方法依赖于取决于有效种群大小的等位基因(新重复)年龄和种群频率之间的预期关系。使用 Moran 模型在几种种群规模下同时使用单倍体和二倍体种群,建立拷贝数变异的中性基线。通过数学分析和模拟建立了该方法拒绝具有已知年龄(以成对 dS 值测量)和频率的重复项中性的能力。正如预期的那样,在二倍体情况下功效特别好,并且有效种群规模更大。通过将此方法扩展到更大的种群规模,这是一种分析任何自然或实验进化种群中拷贝数变异选择的工具。我们在 https://github.com/peterbchi/CNVSelectR/ 提供了一个 R 包,它实现了这里介绍的方法。通过数学分析和模拟建立了该方法拒绝具有已知年龄(以成对 dS 值测量)和频率的重复项中性的能力。正如预期的那样,在二倍体情况下功效特别好,并且有效种群规模更大。通过将此方法扩展到更大的种群规模,这是一种分析任何自然或实验进化种群中拷贝数变异选择的工具。我们在 https://github.com/peterbchi/CNVSelectR/ 提供了一个 R 包,它实现了这里介绍的方法。通过数学分析和模拟建立了该方法拒绝具有已知年龄(以成对 dS 值测量)和频率的重复项中性的能力。正如预期的那样,在二倍体情况下功效特别好,并且有效种群规模更大。通过将此方法扩展到更大的种群规模,这是一种分析任何自然或实验进化种群中拷贝数变异选择的工具。我们在 https://github.com/peterbchi/CNVSelectR/ 提供了一个 R 包,它实现了这里介绍的方法。这是一种分析任何自然或实验进化群体中拷贝数变异选择的工具。我们在 https://github.com/peterbchi/CNVSelectR/ 提供了一个 R 包,它实现了这里介绍的方法。这是一种分析任何自然或实验进化群体中拷贝数变异选择的工具。我们在 https://github.com/peterbchi/CNVSelectR/ 提供了一个 R 包,它实现了这里介绍的方法。

更新日期:2021-08-03
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