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PHYLOGENY ESTIMATION: TRADITIONAL AND BAYESIAN APPROACHES
Mark Holder and Paul O. Lewis
The construction of evolutionary trees is now a standard part of exploratory sequence analysis. Bayesian methods for estimating trees have recently been proposed as a faster method of incorporating the power of complex statistical models into the process. Researchers who rely on comparativeanalyses need to understand the theoretical and practical motivations that underlie these new techniques, and how they differ from previous methods. The ability of the new approaches to address previously intractable questions is making phylogenetic analysis an essential tool in an increasing number of areas of genetic research.
PHYLOGENETIC TREE

A graph depicting the ancestor–descendantrelationships between organisms or gene sequences. The sequences are the tips of the tree. Branches of the tree connect the tips to their (unobservable) ancestral sequences.
SYSTEMATICS

The biological discipline that is devoted to characterizing the diversity of life and organizing our knowledge about this diversity (primarily through estimating the phylogenetic relationships between organisms).Department of Ecology and Evolutionary Biology, 75 North Eagleville Road, University of Connecticut, Storrs, Connecticut 06269–3043, USA. Correspondence to M.H. email: mholder@uconn.edu
doi:10.1038/nrg1044

Comparative sequence analysis is an important tool for geneticists. Minutes after obtaining a new sequence, BLAST searches can give researchers hints about the function and other properties of agene. Comparing several sequences along their entire length can show which parts are changing rapidly (and therefore might be less functionally constrained) and which residues show evidence of being shaped by natural selection1. Reconstructing ancestral sequences can show the timing and directionality of mutations2. These comparative analyses rely on a PHYLOGENETIC TREE that describes theevolutionary relationships between the sequences. Estimating phylogenetic trees is not just an academic exercise: in some cases it can literally be a matter of life or death. For example, phylogenetic trees provided crucial evidence in the murder trial of a dentist that infected one of his patients with human immunodeficiency virus (HIV)3. Evolutionary trees also showed that cases of encephalitis in NewYork and New England represented the first examples of the mosquito-borne West Nile virus in the western hemisphere4,5. Any comparison of more than two related sequences implicitly assumes an underlying phylogeny. For some tasks, pairwise sequence comparisons are sufficient (for example, BLAST), but even these algorithms can be made more powerful by considering information from

more than twosequences simultaneously (for example, PSI-BLAST). Given the potential power of comparative genomics (and its relatively low cost), even researchers with no interest in the evolution of organisms or genes per se should be aware of these approaches (BOX 1). Entire journals (such as Systematic Biology and Molecular Phylogenetics and Evolution) are largely devoted to estimating phylogenies. The myriadof conflicting approaches and the rich terminology of SYSTEMATICS can be intimidating to those who are interested in simply applying the methods. Nevertheless, the possibility of inaccurate tree estimates is real, so anyone who relies on comparative approaches should be familiar with the pitfalls in tree reconstruction. Proceeding from the simple assumption that as the time increases since twosequences diverged from their last common ancestor, so does the number of differences between them, tree estimation seems to be a relatively simple exercise: count the number of differences between sequences and group those that are most similar. The simplicity of such an algorithm underestimates the complexity of the phylogenetic-inference problem. The rate of sequence evolution is not constant...
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