Application of phylogenetic networks in evolutionary studies
Application of phylogenetic networks in evolutionary studies
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DOI：
10.1093/molbev/msj030
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发表时间：
2006-02-01
影响因子：
10.7
通讯作者：
Bryant, D
中科院分区：
文献类型：
--
作者：
Huson, DH;Bryant, D
一组分类群的进化历史通常用系统发育树来表示，这种模型极大地促进了假说的讨论和检验。然而，众所周知，更复杂的进化情景很难被这样的模型描述。此外，即使当进化以树状方式进行时，对数据的分析也可能不是通过使用强制树结构的方法来最好地服务，而是通过对数据进行更丰富的可视化来评估其属性，至少作为必要的第一步。因此，系统发育网络应采用网状事件，如杂交，水平基因转移，重组，或基因复制和丢失被认为是参与，即使在没有这样的事件，系统发育网络有一个有用的作用。本文回顾了用于系统发育网络的术语，包括分裂网络和网状网络，它们是如何定义的，以及如何解释它们。此外，本文概述了一个全面的统计框架应用分裂网络方法的开始。我们将展示如何分裂网络可以表示树的置信度集，并介绍了一个保守的统计测试网络中的冲突信号是否是树状的。最后，本文介绍了一个新的程序，SplitsTree4，一个交互式的和全面的工具，用于推断不同类型的系统发育网络的序列，距离和树。
The evolutionary history of a set of taxa is usually represented by a phylogenetic tree, and this model has greatly facilitated the discussion and testing of hypotheses. However, it is well known that more complex evolutionary scenarios are poorly described by such models. Further, even when evolution proceeds in a tree-like manner, analysis of the data may not be best served by using methods that enforce a tree structure but rather by a richer visualization of the data to evaluate its properties, at least as an essential first step. Thus, phylogenetic networks should be employed when reticulate events such as hybridization, horizontal gene transfer, recombination, or gene duplication and loss are believed to be involved, and, even in the absence of such events, phylogenetic networks have a useful role to play. This article reviews the terminology used for phylogenetic networks and covers both split networks and reticulate networks, how they are defined, and how they can be interpreted. Additionally, the article outlines the beginnings of a comprehensive statistical framework for applying split network methods. We show how split networks can represent confidence sets of trees and introduce a conservative statistical test for whether the conflicting signal in a network is treelike. Finally, this article describes a new program, SplitsTree4, an interactive and comprehensive tool for inferring different types of phylogenetic networks from sequences, distances, and trees.