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21 - Split networks. A tool for exploring complex evolutionary relationships in molecular data

from Section VIII - Additional topics

Published online by Cambridge University Press:  05 June 2012

Philippe Lemey
Affiliation:
University of Oxford
Marco Salemi
Affiliation:
University of California, Irvine
Anne-Mieke Vandamme
Affiliation:
Katholieke Universiteit Leuven, Belgium
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Summary

THEORY

Understanding evolutionary relationships through networks

The standard way to represent evolutionary relationships between a given set of taxa is to use a bifurcating leaf-labeled tree, in which internal nodes represent hypothetical ancestors and leaves are labeled by present-day species (see Chapter 1). Using such a tree presumes that the underlying evolutionary processes are bifurcating. However, in instances where this is not the case, it is questionable whether a bifurcating tree is the best structure to represent phylogenetic relationships. For example, the phenomena of explosive evolutionary radiation, e.g. when an AIDS virus infects a healthy person, might be best modeled not by a bifurcating tree, but by a multifurcating tree (see Chapter 1). In addition, it may be necessary to label internal nodes by taxa if ancestors and present-day species co-exist, as has also been observed with fast evolving viruses.

In certain cases, one might want to allow even more general structures than multifurcating trees to represent evolutionary histories. For example, certain viruses/plants/bacteria are known to exhibit recombination/hybridization/gene transfer, and this process might not always be best represented by a tree. In particular, a tree implicitly assumes that once two lineages are created they subsequently never interact with one another later on. However, if it is assumed that such interactions might have occurred, then a simplistic representation of this might look something like the network (or labeled-graph) presented in Fig. 21.1.

Type
Chapter
Information
The Phylogenetic Handbook
A Practical Approach to Phylogenetic Analysis and Hypothesis Testing
, pp. 631 - 653
Publisher: Cambridge University Press
Print publication year: 2009

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