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Efficient likelihood computations with nonreversible models of evolution.

Bastien Boussau1, Manolo Gouy

  • 1Laboratoire de Biométrie et Biologie Evolutive (UMR 5558); CNRS, Université Lyon 1, Villeurbanne Cedex, France. boussau@biomserv.univ-lyon1.fr

Systematic Biology
|October 25, 2006
PubMed
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This study introduces a computational method for efficient phylogenetic tree estimation using nonreversible models of evolution. This advance enables broader application of advanced heuristics in evolutionary biology research.

Area of Science:

  • Computational Biology
  • Evolutionary Biology
  • Phylogenetics

Background:

  • Maximum likelihood phylogenetic tree estimation is computationally intensive.
  • Current efficient algorithms are limited to reversible models of evolution.

Purpose of the Study:

  • To develop an efficient method for phylogenetic tree estimation using nonreversible models.
  • To adapt a nonhomogeneous, nonstationary model (Galtier and Gouy, 1998) for phylogenetic analysis.

Main Methods:

  • Reorganized likelihood computation for efficient tree evaluation from any node.
  • Introduced nhPhyML, integrating a nonhomogeneous, nonstationary model into PhyML.
  • Developed an approximation for the model with limited equilibrium frequencies.

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Main Results:

  • Efficient computation of likelihood for nonreversible models, compatible with reversible models.
  • nhPhyML demonstrated improved exploration of tree topologies.
  • Accurate ancestral G+C content estimation was achieved.

Conclusions:

  • The new method enhances phylogenetic inference capabilities.
  • Application to rRNA sequences suggests against a hyperthermophilic last universal common ancestor.
  • Model and taxonomic sampling impact evolutionary conclusions.