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arXiv 2301.00992q-bio.PE
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一种通过比对谱系分类单元字符串从系统发育树快速且可扩展地推断系统发育网络的方法

A Fast and Scalable Method for Inferring Phylogenetic Networks from Trees by Aligning Lineage Taxon Strings

Louxin Zhang, Niloufar Abhari, Caroline Colijn, Yufeng Wu

AI总结:

本文提出ALTS方法,通过比对系统发育树中的谱系分类单元字符串快速推断最小树-子网络,突破了现有工具在大规模网状事件推断上的局限。

摘要:

系统发育网络的重建是系统发育学与基因组进化中一个重要但具有挑战性的问题,因为系统发育网络的空间极其庞大,难以被充分采样。解决该问题的一种途径是求解最小系统发育网络问题,即首先推断系统发育树,然后计算能够展示所有这些树的最小系统发育网络。该方法利用了系统发育树理论已经成熟这一优势,并且已有优秀的工具可用于从大量生物分子序列中推断系统发育树。树-子网络是一种系统发育网络,其满足每个非叶节点至少有一个入度为一的子节点这一条件。在此,我们开发了一种新方法,通过比对系统发育树中的谱系分类单元字符串来推断最小树-子网络。这一算法创新使我们能够绕过现有系统发育网络推断程序的局限性。我们的新程序名为ALTS,其速度足够快,对于一组多达50棵、包含50个分类单元且仅具有平凡公共簇的系统发育树,平均约15分钟即可推断出具有大量网状事件的树-子网络。

英文摘要:

The reconstruction of phylogenetic networks is an important but challenging problem in phylogenetics and genome evolution, as the space of phylogenetic networks is vast and cannot be sampled well. One approach to the problem is to solve the minimum phylogenetic network problem, in which phylogenetic trees are first inferred, then the smallest phylogenetic network that displays all the trees is computed. The approach takes advantage of the fact that the theory of phylogenetic trees is mature and there are excellent tools available for inferring phylogenetic trees from a large number of biomolecular sequences. A tree-child network is a phylogenetic network satisfying the condition that every non-leaf node has at least one child that is of indegree one. Here, we develop a new method that infers the minimum tree-child network by aligning lineage taxon strings in the phylogenetic trees. This algorithmic innovation enables us to get around the limitations of the existing programs for phylogenetic network inference. Our new program, named ALTS, is fast enough to infer a tree-child network with a large number of reticulations for a set of up to 50 phylogenetic trees with 50 taxa that have only trivial common clusters in about a quarter of an hour on average.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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