Abstract
The divergent evolution of protein sequences from genomic databases can be analyzed by the use of different mathematical models. The most common treat all sites in a protein sequence as equally variable. More sophisticated models acknowledge the fact that purifying selection generally tolerates variable amounts of amino acid replacement at different positions in a protein sequence. In their "stationary" versions, such models assume that the replacement rate at individual positions remains constant throughout evolutionary history. "Nonstationary" covarion versions, however, allow the replacement rate at a position to vary in different branches of the evolutionary tree. Recently, statistical methods have been developed that highlight this type of variation in replacement rates. Here, we show how positions that have variable rates of divergence in different regions of a tree ("covarion behavior"), coupled with analyses of experimental three-dimensional structures, can provide experimentally testable hypotheses that relate individual amino acid residues to specific functional differences in those branches. We illustrate this in the elongation factor family of proteins as a paradigm for applications of this type of analysis in functional genomics generally.