A rapid and scalable method for multilocus species delimitation using Bayesian model comparison and rooted triplets

Multilocus sequence data provide far greater power to resolve species limits than the single locus data typically used for broad surveys of clades. However, current statistical methods based on a multispecies coalescent framework are computationally demanding, because of the number of possible delimitations that must be compared and time-consuming likelihood calculations. New methods are therefore needed to open up the power of multilocus approaches to larger systematic surveys. Here, we present a rapid and scalable method that introduces 2 new innovations. First, the method reduces the complexity of likelihood calculations by decomposing the tree into rooted triplets. The distribution of topologies for a triplet across multiple loci has a uniform trinomial distribution when the 3 individuals belong to the same species, but a skewed distribution if they belong to separate species with a form that is specified by the multispecies coalescent. A Bayesian model comparison framework was deve...多基因座序列数据（Multilocus sequence data）相较于通常用于支系（clades）大范围系统调研的单基因座数据（single locus data），在解析物种界定问题上具备更优异的分辨能力。然而，当前基于多物种溯祖框架（multispecies coalescent framework）的统计方法计算负荷极高：一方面需要比对大量潜在的物种界定方案，另一方面似然计算（likelihood calculations）过程耗时冗长。因此，亟需开发新型方法，以将多基因座分析方法的效能拓展至更大规模的系统性分类学调研中。在此，我们提出一种快速且可扩展的分析方法，该方法引入两项全新创新。其一，该方法通过将系统发育树拆解为有根三联体（rooted triplets），降低似然计算的复杂度。当3个个体隶属于同一物种时，其在多个基因座上的三联体拓扑结构分布服从均匀三项分布；若3个个体分属不同物种，则其拓扑结构分布将呈现偏态，且该偏态分布的具体形式由多物种溯祖框架所规定。本文开发了贝叶斯模型比较框架（Bayesian model comparison framework）并