Estimation of past demographic parameters from the distribution of pairwise differences when the mutation rates vary among sites: application to human mitochondrial DNA.
Estimation of past demographic parameters from the distribution of pairwise differences when the mutation rates vary among sites: application to human mitochondrial DNA.
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DOI：
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发表时间：
1999-07
期刊：
影响因子：
3.3
通讯作者：
S. Schneider;L. Excoffier
中科院分区：
文献类型：
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作者：
S. Schneider;L. Excoffier
成对差异的分布通常被称为“失配分布”，已被广泛用于估计过去人口扩张的人口统计参数。然而，这些估计依赖于这样的假设，即发生在一对基因的祖先中的所有突变都会导致可观察到的差异（无限位点模型）。这种突变模型可能不太现实，尤其是在线粒体DNA控制区的情况下，这种方法主要应用于该区域。在这篇文章中，我们展示了如何推断过去的人口统计参数，明确考虑到突变率的异质性有限站点模型。我们还提出了另一种方法来获得周围的估计参数的置信区间，基于自举方法。通过模拟检查这些置信区间的有效性，我们发现，只有那些与扩张的时间近似正确估计，而周围的人口规模过大。我们还提出了一个测试的有效性估计的人口膨胀的情况下，其适当的行为是通过模拟验证。我们用人类线粒体DNA说明了我们的方法，当考虑到突变率的异质性时，扩展时间的估计比无限位点模型大10-20%。
Distributions of pairwise differences often called "mismatch distributions" have been extensively used to estimate the demographic parameters of past population expansions. However, these estimations relied on the assumption that all mutations occurring in the ancestry of a pair of genes lead to observable differences (the infinite-sites model). This mutation model may not be very realistic, especially in the case of the control region of mitochondrial DNA, where this methodology has been mostly applied. In this article, we show how to infer past demographic parameters by explicitly taking into account a finite-sites model with heterogeneity of mutation rates. We also propose an alternative way to derive confidence intervals around the estimated parameters, based on a bootstrap approach. By checking the validity of these confidence intervals by simulations, we find that only those associated with the timing of the expansion are approximately correctly estimated, while those around the population sizes are overly large. We also propose a test of the validity of the estimated demographic expansion scenario, whose proper behavior is verified by simulation. We illustrate our method with human mitochondrial DNA, where estimates of expansion times are found to be 10-20% larger when taking into account heterogeneity of mutation rates than under the infinite-sites model.