Probabilistic models of eukaryotic evolution: time for integration.
In spite of substantial work and recent progress, a global and fully resolved picture of the macroevolutionary history of eukaryotes is still under construction. This concerns not only the phylogenetic relations among major groups, but also the general characteristics of the underlying macroevolutionary processes, including the patterns of gene family evolution associated with endosymbioses, as well as their impact on the sequence evolutionary process. All these questions raise formidable methodological challenges, calling for a more powerful statistical paradigm. In this direction, model-based probabilistic approaches have played an increasingly important role. In particular, improved models of sequence evolution accounting for heterogeneities across sites and across lineages have led to significant, although insufficient, improvement in phylogenetic accuracy. More recently, one main trend has been to move away from simple parametric models and stepwise approaches, towards integrative models explicitly considering the intricate interplay between multiple levels of macroevolutionary processes. Such integrative models are in their infancy, and their application to the phylogeny of eukaryotes still requires substantial improvement of the underlying models, as well as additional computational developments.
Laboratoire de Biométrie et Biologie Evolutive, UMR CNRS 5558, Université Claude Bernard Lyon 1, F-69622 Villeurbanne Cedex, France nicolas.lartillot@univ-lyon1.fr.
Nicolas
N
Lartillot
D001499:Bayes Theorem; D005075:Biological Evolution; D005057:Eukaryotic Cells / Q000166:cytology*; D023281:Genomics / Q000379:methods; D008957:Models, Genetic; D009010:Monte Carlo Method
Bayesian inference; Monte Carlo; gene/species tree reconciliation methods; integrative models; non-parametric; phylogenomics