从基因树推断物种树的梯度。

IF 2.3 Q2 ECOLOGY BMC ecology and evolution Pub Date : 2024-11-04 DOI:10.1186/s12862-024-02309-z
Mursalin Habib, Kowshic Roy, Saem Hasan, Atif Hasan Rahman, Md Shamsuzzoha Bayzid
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摘要

系统发生树空间中的梯田是指所有系统发生树都包含相同子树的区域,这是由于采样分类群中存在某些缺失数据模式,从而导致给定数据集的最优性得分相同。这首先是在使用最大似然法(ML)和最大解析法(MP)从序列排列中估计系统发生树时进行研究的。后来,它被扩展到从基因树集合中推断物种树的问题,其中一组同样最优的物种树被称为 "伪 "物种树梯度,它不考虑因某些缺失数据模式而产生的诱导子树在拓扑上的接近性。在本研究中,我们从数学角度描述了物种树梯田的特征,并研究了由于数据缺失而导致多棵物种树诱导/显示相同的特定位点子树的数学特性和条件。我们发现,物种树阶梯与基因树的异质性无关。因此,我们引入并描述了一种特殊类型的基因树拓扑感知梯田,我们称之为 "峰值梯田"。此外,我们通过使用模拟和真实生物数据进行广泛的实证研究,探讨了与物种树梯田相关的各种挑战和机遇。我们证明了物种树梯田的普遍性以及由此给树搜索算法带来的模糊性。值得注意的是,我们的研究结果表明,梯田的识别有可能带来进步,提高总结方法的准确性,并提供合理准确的分支支持。
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Terraces in species tree inference from gene trees.

A terrace in a phylogenetic tree space is a region where all trees contain the same set of subtrees, due to certain patterns of missing data among the taxa sampled, resulting in an identical optimality score for a given data set. This was first investigated in the context of phylogenetic tree estimation from sequence alignments using maximum likelihood (ML) and maximum parsimony (MP). It was later extended to the species tree inference problem from a collection of gene trees, where a set of equally optimal species trees was referred to as a "pseudo" species tree terrace which does not consider the topological proximity of the trees in terms of the induced subtrees resulting from certain patterns of missing data. In this study, we mathematically characterize species tree terraces and investigate the mathematical properties and conditions that lead multiple species trees to induce/display an identical set of locus-specific subtrees owing to missing data. We report that species tree terraces are agnostic to gene tree heterogeneity. Therefore, we introduce and characterize a special type of gene tree topology-aware terrace which we call "peak terrace". Moreover, we empirically investigated various challenges and opportunities related to species tree terraces through extensive empirical studies using simulated and real biological data. We demonstrate the prevalence of species tree terraces and the resulting ambiguity created for tree search algorithms. Remarkably, our findings indicate that the identification of terraces could potentially lead to advances that enhance the accuracy of summary methods and provide reasonably accurate branch support.

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