Improvement of molecular phylogenetic inference and the phylogeny of Bilateria

Abstract

Inferring the relationships among Bilateria has been an active and controversial research area since Haeckel. The lack of a sufficient number of phylogenetically reliable characters was the main limitation of traditional phylogenies based on morphology. With the advent of molecular data, this problem has been replaced by another one, statistical inconsistency, which stems from an erroneous interpretation of convergences induced by multiple changes. The analysis of alignments rich in both genes and species, combined with a probabilistic method (maximum likelihood or Bayesian) using sophisticated models of sequence evolution, should alleviate these two major limitations. We applied this approach to a dataset of 94 genes and 79 species using CAT, a previously developed model accounting for site-specific amino acid replacement patterns. The resulting tree is in good agreement with current knowledge: the monophyly of most major groups (e.g. Chordata, Arthropoda, Lophotrochozoa, Ecdysozoa, Protostomia) was recovered with high support. Two results are surprising and are discussed in an evo-devo framework: the sister-group relationship of Platyhelminthes and Annelida to the exclusion of Mollusca, contradicting the Neotrochozoa hypothesis, and, with a lower statistical support, the paraphyly of Deuterostomia. These results, in particular the status of deuterostomes, need further confirmation, both through increased taxonomic sampling, and future improvements of probabilistic models.

Figure 1

Phylogeny inferred using the CAT model. The alignment consists of 19 993 unambiguously aligned positions (94 genes and 79 species). The tree was rooted using sponges and cnidarians as an out-group. Nodes supported by 100% bootstrap values are denoted by black circles while lower values are given in plain text. The scale bar indicates the number of changes per site.

Figure 2

Phylogeny inferred using the WAG model. See figure legend 1 for details.

Figure 3

Posterior predictive tests. The observed value (arrow) of the test statistic is compared with the null distributions under CAT and WAG models. (a) Mean biochemical diversity per site. (b) Maximum compositional deviation over taxa.