Data from: Parsimonious inference of hybridization in the presence of incomplete lineage sorting

Hybridization plays an important evolutionary role in several groups of organisms. A phylogenetic approach to detect hybridization entails sequencing multiple loci across the genomes of a group of species of interest, reconstructing their gene trees, and taking their differences as indicators of hybridization. However, methods that follow this approach mostly ignore population effects, such as incomplete lineage sorting (ILS). Given that hybridization occurs between closely related organisms, ILS may very well be at play and, hence, must be accounted for in the analysis framework. To address this issue, we present a parsimony criterion for reconciling gene trees within the branches of a phylogenetic network, and a local search heuristic for inferring phylogenetic networks from collections of gene-tree topologies under this criterion. This framework enables phylogenetic analyses while accounting for both hybridization and ILS. Further, we propose two techniques for incorporating information about uncertainty in gene-tree estimates. Our simulation studies demonstrate the good performance of our framework in terms of identifying the location of hybridization events, as well as estimating the proportions of genes that underwent hybridization. Also, our framework shows good performance in terms of efficiency on handling large data sets in our experiments. Further, in analysing a yeast data set, we demonstrate issues that arise when analysing real data sets. Although a probabilistic approach was recently introduced for this problem, and although parsimonious reconciliations have accuracy issues under certain settings, our parsimony framework provides a much more computationally efficient technique for this type of analysis. Our framework now allows for genome-wide scans for hybridization, while also accounting for ILS.

杂交在多个生物类群中发挥着重要的进化作用。用于检测杂交的系统发育研究方法，需要对目标类群物种的全基因组多个基因座（locus，复数loci）进行测序，重建其基因树（gene tree），并以不同基因树之间的差异作为杂交事件的指示信号。然而，遵循该思路的多数方法都忽略了种群效应，例如不完全谱系分选（incomplete lineage sorting, ILS）。鉴于杂交多发生在亲缘关系较近的生物类群之间，不完全谱系分选很可能发挥作用，因此在分析框架中必须将其纳入考量。为解决这一问题，本文提出了一种在系统发育网络（phylogenetic network）分支内协调基因树的简约性准则（parsimony criterion），并基于该准则设计了一种从多组基因树拓扑结构中推断系统发育网络的局部搜索启发式算法。该框架可在兼顾杂交与不完全谱系分选的同时开展系统发育分析。此外，本文还提出了两种用于整合基因树推断结果不确定性信息的方法。模拟实验结果表明，本文提出的框架在识别杂交事件发生位置以及估算发生杂交的基因比例两方面均表现优异。同时，实验结果显示该框架在处理大型数据集时也具备良好的运算效率。此外，通过对一组酵母数据集的分析，本文还展示了分析真实数据集时可能遇到的各类问题。尽管近期已有针对该问题的概率方法被提出，且简约性协调在特定场景下存在精度局限，但本文提出的简约性框架为这类分析提供了计算效率大幅提升的解决方案。现如今，该框架可实现全基因组范围的杂交检测扫描，同时将不完全谱系分选纳入考量范畴。