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关于从三元组和聚类中重建一级系统发育网络的挑战。

On the challenge of reconstructing level-1 phylogenetic networks from triplets and clusters.

作者信息

Gambette Philippe, Huber K T, Kelk S

机构信息

LIGM (UMR 8049), CNRS, ENPC, ESIEE Paris, Université Paris-Est, Marne-la-Vallée, 77454, Paris, France.

School of Computing Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK.

出版信息

J Math Biol. 2017 Jun;74(7):1729-1751. doi: 10.1007/s00285-016-1068-3. Epub 2016 Oct 31.

Abstract

Phylogenetic networks have gained prominence over the years due to their ability to represent complex non-treelike evolutionary events such as recombination or hybridization. Popular combinatorial objects used to construct them are triplet systems and cluster systems, the motivation being that any network N induces a triplet system [Formula: see text] and a softwired cluster system [Formula: see text]. Since in real-world studies it cannot be guaranteed that all triplets/softwired clusters induced by a network are available, it is of particular interest to understand whether subsets of [Formula: see text] or [Formula: see text] allow one to uniquely reconstruct the underlying network N. Here we show that even within the highly restricted yet biologically interesting space of level-1 phylogenetic networks it is not always possible to uniquely reconstruct a level-1 network N, even when all triplets in [Formula: see text] or all clusters in [Formula: see text] are available. On the positive side, we introduce a reasonably large subclass of level-1 networks the members of which are uniquely determined by their induced triplet/softwired cluster systems. Along the way, we also establish various enumerative results, both positive and negative, including results which show that certain special subclasses of level-1 networks N can be uniquely reconstructed from proper subsets of [Formula: see text] and [Formula: see text]. We anticipate these results to be of use in the design of algorithms for phylogenetic network inference.

摘要

多年来,系统发育网络因其能够表示复杂的非树状进化事件(如重组或杂交)而备受关注。用于构建系统发育网络的常见组合对象是三元组系统和聚类系统,其动机在于任何网络(N)都会诱导出一个三元组系统([公式:见正文])和一个软连线聚类系统([公式:见正文])。由于在实际研究中,无法保证由网络诱导出的所有三元组/软连线聚类都可用,因此了解([公式:见正文])或([公式:见正文])的子集是否能让人唯一地重建基础网络(N)就特别有意义。在此我们表明,即使在一级系统发育网络这个高度受限但具有生物学意义的空间内,即使([公式:见正文])中的所有三元组或([公式:见正文])中的所有聚类都可用,也并非总是能够唯一地重建一级网络(N)。从积极的方面来看,我们引入了一个相当大的一级网络子类,其成员由它们诱导的三元组/软连线聚类系统唯一确定。在此过程中,我们还建立了各种枚举结果,有正面的也有负面的,包括表明可以从([公式:见正文])和([公式:见正文])的适当子集唯一重建一级网络(N)的某些特殊子类的结果。我们预计这些结果将用于系统发育网络推断算法的设计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdbf/5420025/7bb375f83459/285_2016_1068_Fig1_HTML.jpg

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