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从群体基因组数据中检测平衡选择的时间挑战。

Temporal challenges in detecting balancing selection from population genomic data.

机构信息

School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ 85281, USA.

出版信息

G3 (Bethesda). 2024 Jun 5;14(6). doi: 10.1093/g3journal/jkae069.

Abstract

The role of balancing selection in maintaining genetic variation remains an open question in population genetics. Recent years have seen numerous studies identifying candidate loci potentially experiencing balancing selection, most predominantly in human populations. There are however numerous alternative evolutionary processes that may leave similar patterns of variation, thereby potentially confounding inference, and the expected signatures of balancing selection additionally change in a temporal fashion. Here we use forward-in-time simulations to quantify expected statistical power to detect balancing selection using both site frequency spectrum- and linkage disequilibrium-based methods under a variety of evolutionarily realistic null models. We find that whilst site frequency spectrum-based methods have little power immediately after a balanced mutation begins segregating, power increases with time since the introduction of the balanced allele. Conversely, linkage disequilibrium-based methods have considerable power whilst the allele is young, and power dissipates rapidly as the time since introduction increases. Taken together, this suggests that site frequency spectrum-based methods are most effective at detecting long-term balancing selection (>25N generations since the introduction of the balanced allele) whilst linkage disequilibrium-based methods are effective over much shorter timescales (<1N generations), thereby leaving a large time frame over which current methods have little power to detect the action of balancing selection. Finally, we investigate the extent to which alternative evolutionary processes may mimic these patterns, and demonstrate the need for caution in attempting to distinguish the signatures of balancing selection from those of both neutral processes (e.g. population structure and admixture) as well as of alternative selective processes (e.g. partial selective sweeps).

摘要

平衡选择在维持遗传变异中的作用仍然是群体遗传学中的一个悬而未决的问题。近年来,已有许多研究确定了可能经历平衡选择的候选基因座,其中大多数是在人类群体中。然而,还有许多其他的进化过程可能会留下类似的变异模式,从而可能会干扰推断,并且平衡选择的预期特征也会随着时间的推移而发生变化。在这里,我们使用正向时间模拟来量化在各种进化现实的零模型下,使用基于位点频率谱和连锁不平衡的方法来检测平衡选择的预期统计能力。我们发现,虽然基于位点频率谱的方法在平衡突变开始分离后立即几乎没有能力,但随着平衡等位基因引入后的时间增加,能力会增加。相反,基于连锁不平衡的方法在等位基因年轻的时候具有相当大的能力,而随着引入时间的增加,能力会迅速消散。总的来说,这表明基于位点频率谱的方法最有效地检测长期的平衡选择(自引入平衡等位基因以来>25N 代),而基于连锁不平衡的方法在较短的时间范围内有效(<1N 代),从而导致当前方法在检测平衡选择作用方面的能力在很大的时间范围内都很小。最后,我们调查了替代进化过程在多大程度上可能模拟这些模式,并证明在试图区分平衡选择的特征与中性过程(例如种群结构和混合)以及替代选择过程(例如部分选择清扫)的特征时需要谨慎。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bef/11152078/cb0d4e5d3701/jkae069f1.jpg

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