Department of Biology, Indiana University, Bloomington, Indiana 47405
Department of Biology, Indiana University, Bloomington, Indiana 47405.
Genetics. 2019 Mar;211(3):1059-1073. doi: 10.1534/genetics.118.301831. Epub 2019 Jan 22.
Introgression is a pervasive biological process, and many statistical methods have been developed to infer its presence from genomic data. However, many of the consequences and genomic signatures of introgression remain unexplored from a methodological standpoint. Here, we develop a model for the timing and direction of introgression based on the multispecies network coalescent, and from it suggest new approaches for testing introgression hypotheses. We suggest two new statistics, and , which can be used in conjunction with other information to test hypotheses relating to the timing and direction of introgression, respectively. may find use in evaluating cases of homoploid hybrid speciation (HHS), while provides a four-taxon test for polarizing introgression. Although analytical expectations for our statistics require a number of assumptions to be met, we show how simulations can be used to test hypotheses about introgression when these assumptions are violated. We apply the statistic to genomic data from the wild yeast -a proposed example of HHS-demonstrating its use as a test of this model. These methods provide new and powerful ways to address questions relating to the timing and direction of introgression.
渗入是一种普遍存在的生物过程，已经开发出许多统计方法来从基因组数据中推断其存在。然而，从方法论的角度来看，渗入的许多后果和基因组特征仍然没有得到探索。在这里，我们基于多物种网络凝聚开发了一个关于渗入时间和方向的模型，并由此提出了测试渗入假设的新方法。我们建议了两个新的统计量 和 ，它们可以与其他信息一起用于分别测试与渗入时间和方向有关的假设。 可能在评估同倍杂种形成（HHS）的情况时有用，而 则提供了一个用于极化渗入的四分类检验。尽管我们的统计量的分析预期需要满足许多假设，但我们展示了如何在违反这些假设时使用模拟来测试关于渗入的假设。我们将 统计量应用于来自野生酵母的基因组数据 - 这是 HHS 的一个建议示例 - 证明了它作为该模型检验的用途。这些方法为解决与渗入时间和方向有关的问题提供了新的、强大的方法。
