Publication | Open Access
Application of Phylogenetic Networks in Evolutionary Studies
8.9K
Citations
50
References
2005
Year
BiologySplit NetworksPhylogeneticsMolecular EcologyPhylogenetic NetworksTree StructureGeneticsEvolutionary BiologyNatural SciencesMedicinePhylogenetic TreePhylogenetic MethodCladisticsGenetic VariationPhylogenomicsPopulation GeneticsPhylogeny ComparisonPhylogenetic Analysis
Phylogenetic trees are widely used but fail to capture complex evolutionary scenarios, necessitating richer visualizations to assess data properties. The article advocates using phylogenetic networks for reticulate events and reviews terminology, split and reticulate networks, and their interpretation. It outlines a statistical framework for split networks and introduces SplitsTree4, a tool for inferring various phylogenetic networks from sequences, distances, and trees. Split networks can represent confidence sets of trees and provide a conservative test for whether the conflicting signal in a network is treelike.
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.
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