Data from: Assessing the impacts of positive selection on coalescent-based species tree estimation and species delimitation.

The assumption of strictly neutral evolution is fundamental to the multispecies coalescent model and permits the derivation of gene tree distributions and coalescent times conditioned on a given species tree. In this study, we conduct computer simulations to explore the effects of violating this assumption in the form of species-specific positive selection when estimating species trees, species delimitations, and coalescent parameters under the model. We simulated datasets under an array of evolutionary scenarios that differ in both speciation parameters (i.e., divergence times, strength of selection) and experimental design (i.e., number of loci sampled) and incorporated species-specific positive selection occurring within branches of a species tree to identify the effects of selection on multispecies coalescent inferences. Our results highlight particular evolutionary scenarios and parameter combinations in which inferences may be more, or less, susceptible to the effects of positive selection. In some extreme cases, selection can decrease error in species delimitation and increase error in species tree estimation, yet these inferences appear to be largely robust to the effects of positive selection under many conditions likely to be encountered in empirical datasets.

严格中性进化假设（strictly neutral evolution）是多物种溯祖模型（multispecies coalescent model）的核心基础，该假设允许在给定物种树（species tree）的条件下推导基因树分布（gene tree distributions）与溯祖时间（coalescent times）。本研究通过计算机模拟，探究在该模型框架下估计物种树、物种界定（species delimitations）与溯祖参数（coalescent parameters）时，以物种特异性正选择（species-specific positive selection）形式违背该假设所产生的影响。我们基于一系列演化场景模拟数据集，这些场景在物种形成参数（即分化时间、选择强度）与实验设计（即采样基因位点数目）上均存在差异，并引入发生于物种树分支内的物种特异性正选择，以明确选择对多物种溯祖推断（multispecies coalescent inferences）的影响。本研究结果揭示了若干演化场景与参数组合，在这些场景与组合下，推断结果对正选择影响的敏感性或高或低。在部分极端场景中，正选择可降低物种界定的误差，却会提升物种树估计的误差；但在实证数据集（empirical datasets）中常见的多数条件下，上述推断结果整体上对正选择的影响表现出较强的稳健性。