The Confounding Effects of Population Structure, Genetic Diversity and the Sampling Scheme on the Detection and Quantification of Population Size Changes
The Confounding Effects of Population Structure, Genetic Diversity and the Sampling Scheme on the Detection and Quantification of Population Size Changes
复制标题
DOI：
10.1534/genetics.110.118661
复制
发表时间：
2010-11-01
期刊：
影响因子：
3.3
通讯作者：
Beaumont, Mark A.
中科院分区：
文献类型：
--
作者：
Chikhi, Lounes;Sousa, Vitor C.;Beaumont, Mark A.
认为分子数据应该包含有关种群最近进化史的信息的想法已经相当陈旧了。然而，今天开展的许多工作归功于统计学家和理论家的工作，他们证明了有可能检测到偏离平衡条件的情况(例如，泛种群/突变-漂移平衡)，并根据偏离中性或平稳性来解释它们。在过去的20年中，对种群规模变化的检测通常是在假设样本来自可用Wright-Fisher模型近似的总体的情况下进行的(即，假设混杂、人口平稳性等)。然而，自然种群通常是空间网络的一部分，并通过基因流动相互联系。在这里，我们模拟了在n岛和踏脚石模型下突变和迁移-漂移平衡的遗传数据。因此，模拟的种群是固定的，不受任何种群大小的影响。我们改变了种群之间的基因流动水平和规模化的突变率。我们还使用了几种抽样方案。然后，我们使用在马尔科夫链蒙特卡罗模拟程序MSVAR中实现的贝叶斯方法来分析模拟样本，以利用微卫星数据来检测和量化假定的种群规模变化。我们的结果表明，所有三个因素(遗传分化/基因流动、遗传多样性和采样方案)都在产生虚假瓶颈信号方面发挥了作用。我们还建议了一种特别的方法来对抗这种影响。种群结构和抽样方案的混杂效应对许多保护研究具有实际意义。事实上，如果种群结构正在创造“虚假的”瓶颈信号，那么从遗传数据中解释瓶颈信号可能并不像看起来那么简单，几项研究可能高估了或错误地在濒危物种中发现了瓶颈。
The idea that molecular data should contain information on the recent evolutionary history of populations is rather old. However, much of the work carried out today owes to the work of the statisticians and theoreticians who demonstrated that it was possible to detect departures from equilibrium conditions (e. g., panmictic population/mutation-drift equilibrium) and interpret them in terms of deviations from neutrality or stationarity. During the last 20 years the detection of population size changes has usually been carried out under the assumption that samples were obtained from populations that can be approximated by a Wright-Fisher model (i.e., assuming panmixia, demographic stationarity, etc.). However, natural populations are usually part of spatial networks and are interconnected through gene flow. Here we simulated genetic data at mutation and migration-drift equilibrium under an n-island and a stepping-stone model. The simulated populations were thus stationary and not subject to any population size change. We varied the level of gene flow between populations and the scaled mutation rate. We also used several sampling schemes. We then analyzed the simulated samples using the Bayesian method implemented in MSVAR, the Markov Chain Monte Carlo simulation program, to detect and quantify putative population size changes using microsatellite data. Our results show that all three factors (genetic differentiation/gene flow, genetic diversity, and the sampling scheme) play a role in generating false bottleneck signals. We also suggest an ad hoc method to counter this effect. The confounding effect of population structure and of the sampling scheme has practical implications for many conservation studies. Indeed, if population structure is creating "spurious'' bottleneck signals, the interpretation of bottleneck signals from genetic data might be less straightforward than it would seem, and several studies may have overestimated or incorrectly detected bottlenecks in endangered species.