Evolutionary Bioinformatics

We have analysed the efficiency of all mitochondrial protein coding genes and six nuclear markers (Adora3, Adrb2, Bdnf, Irbp, Rag2 and Vwf) in reconstructing and statistically supporting known amniote groups (murines, rodents, primates, eutherians, metatherians, therians). The efficiencies of maximum likelihood, Bayesian inference, maximum parsimony, neighbor-joining and UPGMA were also evaluated, by assessing the number of correct and incorrect recovered groupings. In addition, we have compared support values using the conservative bootstrap test and the Bayesian posterior probabilities. First, no correlation was observed between gene size and marker efficiency in recovering or supporting correct nodes. As expected, tree-building methods performed similarly, even UPGMA that, in some cases, outperformed other most extensively used methods. Bayesian posterior probabilities tend to show much higher support values than the conservative bootstrap test, for correct and incorrect nodes. Our results also suggest that nuclear markers do not necessarily show a better performance than mitochondrial genes. The so-called dependency among mitochondrial markers was not observed comparing genome performances. Finally, the amniote groups with lowest recovery rates were therians and rodents, despite the morphological support for their monophyletic status. We suggest that, regardless of the tree-building method, a few carefully selected genes are able to unfold a detailed and robust scenario of phylogenetic hypotheses, particularly if taxon sampling is increased.