Journal of Molecular Evolution

, Volume 32, Issue 1, pp 79–91 | Cite as

Robustness of maximum likelihood tree estimation against different patterns of base substitutions

  • Kaoru Fukami-Kobayashi
  • Yoshio Tateno


In the maximum likelihood (ML) method for estimating a molecular phylogenetic tree, the pattern of nucleotide substitutions for computing likelihood values is assumed to be simpler than that of the actual evolutionary process, simply because the process, considered to be quite devious, is unknown. The problem, however, is that there has been no guarantee to endorse the simplification.

To study this problem, we first evaluated the robustness of the ML method in the estimation of molecular trees against different nucleotide substitution patterns, including Jukes and Cantor's, the simplest ever proposed. Namely, we conducted computer simulations in which we could set up various evolutionary models of a hypothetical gene, and define a true tree to which an estimated tree by the ML method was to be compared. The results show that topology estimation by the ML method is considerably robust against different ratios of transitions to transversions and different GC contents, but branch length estimation is not so. The ML tree estimation based on Jukes and Cantor's model is also revealed to be resistant to GC content, but rather sensitive to the ratio of transitions to transversions.

We then applied the ML method with different substitution patterns to nucleotide sequence data ontax gene from T-cell leukemia viruses whose evolutionary process must have been more complicated than that of the hypothetical gene. The results are in accordance with those from the simulation study, showing that Jukes and Cantor's model is as useful as a more complicated one for making inferences about molecular phylogeny of the viruses.

Key words

Molecular tree estimation Maximum likelihood Base substitution pattern Computer simulation T-cell leukemia virus 


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Copyright information

© Springer-Verlag New York Inc. 1991

Authors and Affiliations

  • Kaoru Fukami-Kobayashi
    • 1
  • Yoshio Tateno
    • 2
  1. 1.Ochanomizu UniversityTokyoJapan
  2. 2.National Institute of GeneticsMishimaJapan

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