Ortega-Del Vecchyo Diego, Piñero Daniel, Jardón-Barbolla Lev, van Heerwaarden Joost
Departamento de Ecologia Evolutiva, Instituto de Ecologia, Universidad Nacional Autónoma de México, Mexico City, Mexico.
Department of Integrative Biology, University of California, Berkeley, USA.
BMC Evol Biol. 2017 Sep 11;17(1):213. doi: 10.1186/s12862-017-1046-4.
Homoplasy affects demographic inference estimates. This effect has been recognized and corrective methods have been developed. However, no studies so far have defined what homoplasy metrics best describe the effects on demographic inference, or have attempted to estimate such metrics in real data. Here we study how homoplasy in chloroplast microsatellites (cpSSR) affects inference of population expansion time. cpSSRs are popular markers for inferring historical demography in plants due to their high mutation rate and limited recombination.
In cpSSRs, homoplasy is usually quantified as the probability that two markers or haplotypes that are identical by state are not identical by descent (Homoplasy index, P). Here we propose a new measure of multi-locus homoplasy in linked SSR called Distance Homoplasy (DH), which measures the proportion of pairwise differences not observed due to homoplasy, and we compare it to P and its per cpSSR locus average, which we call Mean Size Homoplasy (MSH). We use simulations and analytical derivations to show that, out of the three homoplasy metrics analyzed, MSH and DH are more correlated to changes in the population expansion time and to the underestimation of that demographic parameter using cpSSR. We perform simulations to show that Approximate Bayesian Computation (ABC) can be used to obtain reasonable estimates of MSH and DH. Finally, we use ABC to estimate the expansion time, MSH and DH from a chloroplast SSR dataset in Pinus caribaea. To our knowledge, this is the first time that homoplasy has been estimated in population genetic data.
We show that MSH and DH should be used to quantify how homoplasy affects estimates of population expansion time. We also demonstrate how ABC provides a methodology to estimate homoplasy in population genetic data.
同塑性会影响群体推断估计。这种影响已被认识到，并且已经开发出了校正方法。然而，到目前为止，尚无研究确定哪种同塑性指标最能描述对群体推断的影响，也没有尝试在实际数据中估计此类指标。在此，我们研究叶绿体微卫星（cpSSR）中的同塑性如何影响群体扩张时间的推断。由于cpSSR具有高突变率和有限的重组，因此它们是推断植物历史群体统计学的常用标记。
在cpSSR中，同塑性通常被量化为两个状态相同的标记或单倍型并非同源相同的概率（同塑性指数，P）。在此，我们提出了一种新的衡量连锁SSR中多位点同塑性的方法，称为距离同塑性（DH），它衡量因同塑性未观察到的成对差异的比例，并将其与P及其每个cpSSR位点平均值（我们称为平均大小同塑性，MSH）进行比较。我们使用模拟和分析推导表明，在所分析的三个同塑性指标中，MSH和DH与群体扩张时间的变化以及使用cpSSR对该群体参数的低估更相关。我们进行模拟以表明近似贝叶斯计算（ABC）可用于获得MSH和DH的合理估计值。最后，我们使用ABC从加勒比松的叶绿体SSR数据集中估计扩张时间、MSH和DH。据我们所知，这是首次在群体遗传数据中估计同塑性。
我们表明应使用MSH和DH来量化同塑性如何影响群体扩张时间的估计。我们还展示了ABC如何提供一种在群体遗传数据中估计同塑性的方法。
