Maximum-Likelihood Tree Estimation Using Codon Substitution Models with Multiple Partitions.
Many protein sequences have distinct domains that evolve with different rates, different selective pressures, or may differ in codon bias. Instead of modeling these differences by more and more complex models of molecular evolution, we present a multipartition approach that allows maximum-likelihood phylogeny inference using different codon models at predefined partitions in the data. Partition models can, but do not have to, share free parameters in the estimation process. We test this approach with simulated data as well as in a phylogenetic study of the origin of the leucin-rich repeat regions in the type III effector proteins of the pythopathogenic bacteria Ralstonia solanacearum. Our study does not only show that a simple two-partition model resolves the phylogeny better than a one-partition model but also gives more evidence supporting the hypothesis of lateral gene transfer events between the bacterial pathogens and its eukaryotic hosts.
Computational Biochemistry Research Group, ETH Zürich, Zürich, Switzerland Swiss Institute of Bioinformatics, Switzerland.
Stefan
S
Zoller
Computational Biochemistry Research Group, ETH Zürich, Zürich, Switzerland.
Veronika
V
Boskova
Institute of Applied Simulations, School of Life Sciences and Facility Management, Zurich University of Applied Sciences, Wädenswil, Switzerland maria.anisimova@zhaw.ch.
Maria
M
Anisimova
D001426:Bacterial Proteins / Q000235:genetics*; D003062:Codon; D008957:Models, Genetic; D043368:Ralstonia solanacearum / Q000235:genetics*
D001426:Bacterial Proteins; D003062:Codon
Markov model; amino acid substitution model; codon substitution model; maximum-likelihood tree