Department of Evolutionary Biology, University of Haifa, 31905, Haifa, Israel.
Department of Computer Scienece, University of Haifa, 31905, Haifa, Israel.
J Mol Evol. 2018 Feb;86(2):150-165. doi: 10.1007/s00239-018-9833-0. Epub 2018 Feb 19.
Despite impressive advancements in technological and theoretical tools, construction of phylogenetic (evolutionary) trees is still a challenging task. The availability of enormous quantities of molecular data has made large-scale phylogenetic reconstruction involving thousands of species, a more viable goal. For this goal, separate trees over different, overlapping subsets of species, representing histories of various markers of these species, are collected. These trees, typically with conflicting signals, are subsequently combined into a single tree over the full set, an operation denoted as supertree construction. The amalgamation of such trees into a single tree lies at the heart of many tasks in phylogenetics, yet remains a daunting endeavor, especially in light of conflicting signals. In this work, we study the performance of matrix representation with parsimony (MRP), the most widely used supertree method to date, when confronted with quartet trees. Quartet trees are the most basic informational unit when amalgamation of unrooted trees is attempted, and they remain relevant in more general settings even though standard supertree methods are not necessarily confined to quartets. This study involves both real and simulated data, and the effects of several parameters on the results are evaluated, revealing a number of anomalies associated with MRP. We show that these anomalies are surmountable when using a recently introduced supertree method, weighted quartet MaxCut (wQMC).
尽管在技术和理论工具方面取得了令人印象深刻的进展,但构建系统发育(进化)树仍然是一项具有挑战性的任务。大量分子数据的出现使得涉及数千个物种的大规模系统发育重建成为一个更可行的目标。为此,我们收集了不同、重叠的物种子集上的单独树,这些树代表了这些物种的各种标记物的历史。这些树通常具有相互冲突的信号,随后会被合并到整个集合的一棵树中,这个操作被称为超树构建。在系统发育学中,许多任务都需要将这些树合并成一棵树,但这仍然是一项艰巨的任务,尤其是在存在冲突信号的情况下。在这项工作中,我们研究了当面对四分树时,最广泛使用的超级树方法——简约矩阵表示法(MRP)的性能。四分树是合并无根树时最基本的信息单元,即使标准超级树方法不一定局限于四分树,它们在更一般的情况下仍然是相关的。这项研究涉及真实数据和模拟数据,并评估了几个参数对结果的影响,揭示了与 MRP 相关的一些异常。我们表明,当使用最近引入的超级树方法——加权四分体最大切割法(wQMC)时,这些异常是可以克服的。