Using models of nucleotide evolution to build phylogenetic trees.

Molecular phylogenetics and its applications are popular and useful tools for making comparative investigations in genetics; however, estimating phylogenetic trees is not always straightforward. Some phylogenetic estimators use an explicit model of nucleotide evolution to estimate evolutionary parameters such as branch lengths and tree topology. There are many models to choose from, and use of the optimal model for a particular data set is important to avoid a loss of power and accuracy in phylogenetic estimations. Here, we review some molecular evolutionary forces and the parameters included in some common models of evolution used to interpret resulting patterns of molecular variation. We present some statistical methods of selecting a particular model of nucleotide evolution, and provide an empirical example of model selection. Statistical model selection strikes a balance between the bias introduced by some models and the increased variance of parameter estimates that results from using other models.