State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, 1 Beichen West Road, Chaoyang District, Beijing 100101.
Mol Ecol. 2011 Jun;20(12):2494-509. doi: 10.1111/j.1365-294X.2011.05108.x. Epub 2011 May 9.
The genetic differentiation of populations is a key parameter in population genetic investigations. Wright's F(ST) (and its relatives such as G(ST) ) has been a standard measure of differentiation. However, the deficiencies of these indexes have been increasingly realized in recent years, leading to some new measures being proposed, such as Jost's D (Molecular Ecology, 2008; 17, 4015). The existence of these new metrics has stimulated considerable debate and induced some confusion on which statistics should be used for estimating population differentiation. Here, we report a simulation study with neutral microsatellite DNA loci under a finite island model to compare the performance of G(ST) and D, particularly under nonequilibrium conditions. Our results suggest that there exist fundamental differences between the two statistics, and neither G(ST) nor D operates satisfactorily in all situations for quantifying differentiation. D is very sensitive to mutation models but G(ST) noticeably less so, which limits D's utility in population parameter estimation and comparisons across genetic markers. Also, the initial heterozygosity of the starting populations has some important effects on both the individual behaviours of G(ST) and D and their relative behaviours in early differentiation, and this effect is much greater for D than G(ST) . In the early stages of differentiation, when initial heterozygosity is relatively low (<0.5, if the number of subpopulations is large), G(ST) increases faster than D; the opposite is true when initial heterozygosity is high. Therefore, the state of the ancestral population appears to have some lasting impacts on population differentiation. In general, G(ST) can measure differentiation fairly well when heterozygosity is low whatever the causes; however, when heterozygosity is high (e.g. as a result of either high mutation rate or high initial heterozygosity) and gene flow is moderate to strong, G(ST) fails to measure differentiation. Interestingly, when population size is not very small (e.g. N ≥ 1000), G(ST) measures differentiation quite linearly with time over a long duration when gene flow is absent or very weak even if mutation rate is not low (e.g. μ = 0.001). In contrast, D, as a differentiation measure, performs rather robustly in all these situations. In practice, both indexes should be calculated and the relative levels of heterozygosities (especially H(S) ) and gene flow taken into account. We suggest that a comparison of the two indexes can generate useful insights into the evolutionary processes that influence population differentiation.
群体遗传分化是群体遗传学研究的一个关键参数。Wright 的 F(ST)（及其类似指标，如 G(ST)）一直是分化的标准衡量指标。然而，近年来这些指标的缺陷越来越明显，导致一些新的指标被提出，例如 Jost 的 D（Molecular Ecology，2008；17，4015）。这些新指标的出现引发了相当多的争论，并导致一些混淆，即应该使用哪种统计数据来估计群体分化。在这里，我们报告了一项使用中性微卫星 DNA 位点在有限岛屿模型下的模拟研究，以比较 G(ST)和 D 的性能，特别是在非平衡条件下。我们的结果表明，这两个统计数据之间存在根本差异，并且在所有情况下，G(ST)和 D 都不能令人满意地用于量化分化。D 对突变模型非常敏感，但 G(ST)则不那么敏感，这限制了 D 在种群参数估计和跨遗传标记比较中的应用。此外，起始种群的初始杂合度对 G(ST)和 D 的个体行为及其在早期分化中的相对行为都有一些重要影响，而且这种影响对于 D 比对 G(ST)更大。在分化的早期阶段，当初始杂合度相对较低（<0.5，如果亚种群数量较大）时，G(ST)的增长速度快于 D；当初始杂合度较高时则相反。因此，祖先种群的状态似乎对种群分化有一些持久的影响。一般来说，当杂合度较低时，无论原因如何，G(ST)都可以很好地衡量分化；然而，当杂合度较高（例如由于突变率较高或初始杂合度较高）且基因流中等至较强时，G(ST)无法衡量分化。有趣的是，当种群数量不是非常小时（例如 N≥1000），即使突变率不低（例如μ=0.001），在没有或非常弱的基因流的情况下，G(ST)在很长一段时间内都可以与时间呈相当线性的关系来衡量分化。相比之下，D 作为一种分化指标，在所有这些情况下表现都相当稳健。在实践中，应该计算这两个指标，并考虑异质性水平（尤其是 H(S)）和基因流的相对水平。我们建议，对这两个指标进行比较可以为影响种群分化的进化过程提供有用的见解。
