Selecting models of evolution THEORY

Phylogenetic reconstruction is regarded as a problem of statistical inference. Because statistical inferences cannot be drawn in the absence of a probability model, the use of a model of nucleotide or amino-acid substitution – an evolutionary model – becomes necessary when using DNA or amino-acid sequences to estimate phylogenetic relationships among organisms. Evolutionary models are sets of assumptions about the process of nucleotide or amino-acid substitution (see Chapters 4 and 8). They describe the different probabilities of change from one nucleotide or amino acid to another, with the aim of correcting for unseen changes along the phylogeny. Although this chapter focuses on models of nucleotide substitution, all the points made herein can be applied directly to models of amino-acid replacement. Comprehensive reviews of models of evolution are offered by Swofford et al. (1996) and Lió and Goldman (1998). As discussed in the previous chapters, the methods used in molecular phylogeny are based on a number of assumptions about how the evolutionary process works. These assumptions can be implicit, like in parsimony methods (see Chapter 7), or explicit, like in distance or maximum-likelihood methods (see Chapters 5 and 6). The advantage of making a model explicit is that the parameters of the model may be estimated. Distance methods may estimate only from the data of a single parameter of the model – the number of substitutions per site. However, maximum likelihood can estimate all the relevant parameters of the substitution model. Parameters estimated via maximum likelihood have desirable statistical properties: as sample sizes get large, they converge to the true parameter value and have the smallest possible variance among all estimates with the same expected value. Most important, as shown in the following sections, maximum likelihood provides a framework in