Phylogenomics—the estimation of species trees from multilocus data sets—is a common step in many biological studies. However, this estimation is challenged by the fact that genes can evolve under processes, including incomplete lineage sorting (ILS) and gene duplication and loss (GDL), that make their trees different from the species tree. In this article, we address the challenge of estimating the species tree under GDL. We show that species trees are identifiable under a standard stochastic model for GDL, and that the polynomial-time algorithm ASTRAL-multi, a recent development in the ASTRAL suite of methods, is statistically consistent under this GDL model. We also provide a simulation study evaluating ASTRAL-multi for species tree estimation under GDL.

中文翻译：

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基因复制和丢失下物种树的多项式时间统计估计

系统基因组学——从多位点数据集中估计物种树——是许多生物学研究中的一个常见步骤。然而，这一估计受到以下事实的挑战：基因可以在不完全谱系分类 (ILS) 和基因复制和丢失 (GDL) 等过程中进化，这使得它们的树与物种树不同。在本文中，我们解决了在 GDL 下估计物种树的挑战。我们表明，物种树在 GDL 的标准随机模型下是可识别的，并且多项式时间算法 ASTRAL-multi 是 ASTRAL 方法套件的最新发展，在此 GDL 模型下具有统计上的一致性。我们还提供了一项模拟研究，评估 ASTRAL-multi 用于 GDL 下的物种树估计。