MAJORITY-RULE CONSENSUS OF PHYLOGENETIC TREES OBTAINED BY MAXIMUM-LIKELIHOOD ANALYSIS

The maximum-likelihood (ML) approach is a powerful tool for reconstruc ting molecular phylogenies. In conjunction with the Kishino-Hasegawa t est, it allows direct comparison of alternative evolutionary hypothese s. A commonly occurring outcome is that several trees are not signific antly different from the ML tree, and thus there is residual uncertain ty about the correct tree topology. We present a new method for produc ing a majority-rule consensus tree that is based on those trees that a re not significantly less likely than the ML tree. Five types of conse nsus trees are considered. These differ in the weighting schemes that are employed. Apart from incorporating the topologies of alternative t rees, some of the weighting schemes also make use of the differences b etween the log likelihood estimate of the ML tree and those of the oth er trees and the standard errors of those differences. The new approac h is used to analyze the phylogenetic relationship of psbA proteins fr om four free-living photosynthetic prokaryotes and a chloroplast from green plants. We conclude that the most promising weighting scheme inv olves exponential weighting of differences between the log likelihood estimate of the ML tree and those of the other trees standardized by t he standard errors of the differences. A consensus tree that is based on this weighting scheme is referred to as a standardized, exponential ly weighted consensus tree. The new approach is a valuable alternative to existing tree-evaluating methods, because it integrates phylogenet ic information from the ML tree with that of trees that do not differ significantly from the ML tree.