THEORY

Introduction

In addition to maximum parsimony (MP) and likelihood methods (see Chapters 6, and 8), pairwise distance methods form the third large group of methods to infer evolutionary trees from sequence data (Fig. 5.1). In principle, distance methods try to fit a tree to a matrix of pairwise genetic distances (Felsenstein, 1988). For every two sequences, the distance is a single value based on the fraction of positions in which the two sequences differ, defined as p-distance (see Chapter 4). The p-distance is an underestimation of the true genetic distance because some of the nucleotide positions may have experienced multiple substitution events. Indeed, because mutations are continuously fixed in the genes, there has been an increasing chance of multiple substitutions occurring at the same sequence position as evolutionary time elapses. Therefore, in distance-based methods, one tries to estimate the number of substitutions that have actually occurred by applying a specific evolutionary model that makes particular assumptions about the nature of evolutionary changes (see Chapter 4). When all the pairwise distances have been computed for a set of sequences, a tree topology can then be inferred by a variety of methods (Fig. 5.2).

Correct estimation of the genetic distance is crucial and, in most cases, more important than the choice of method to infer the tree topology.