Should the rate variation across sites be Gamma?

Sep 26, 2017 | By: Lars Jermiin

It is often hard to predict the significance and long-term impact of new innovations, but the introduction of ModelFinder (1), a novel model-selection method for accurate phylogenetic estimates, is likely to be on par with Yang’s ground-breaking discovery, in 1994, of a simple one-parameter Gamma model (2) of rate heterogeneity across sites, the first model-selection method (3) to be widely used in molecular phylogenetics, and the rise of Bayesian phylogenetic methods (4), (5).

Published in 1994, Yang’s one-parameter model has been used in most of the subsequent molecular phylogenetic research but its success has perhaps also led to his other discovery, in 1995, of a more versatile model (6) of rate heterogeneity across sites being overlooked. ModelFinder includes both models, and the first results show that the more flexible model often is needed to obtain accurate estimates of phylogenetic trees and evolutionary processes.

These results call into question much of the last two decades of phylogenetic research, which relied on phylogenetic methodology that ignored the more versatile model of rate heterogeneity across sites.

The advent of ModelFinder opens a new era of opportunities, where accurate phylogenetic estimates can be obtained and used to answer important biological questions, and where controversial as well as long-standing evolutionary hypotheses can be tested using novel ways of modelling sequence evolution.


  1. Kalyaanamoorthy, S. et al. (2017) ModelFinder: fast model selection for accurate phylogenetic estimates. Nat Methods 14, 587-589. https://doi.org/10.1038/nmeth.4285
  2. Yang, Z. (1994) Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: approximate methods. J Mol Evol 39 (3), 306-314. http://dx.doi.org/10.1007/BF00160154
  3. Posada, D. and Crandall, K.A. (1998) MODELTEST: testing the model of DNA substitution. Bioinformatics 14, 817-818. https://www.ncbi.nlm.nih.gov/pubmed/9918953
  4. Larget, B. and Simon, D. (1999) Markov chain Monte Carlo algorithms for the Bayesian analysis of phylogenetic trees. Mol Biol Evol 16, 750-759. https://doi.org/10.1093/oxfordjournals.molbev.a026160
  5. Huelsenbeck, J.P. and Ronquist, F. (2001) MrBayes: Bayesian inference of phylogenetic trees. Bioinformatics 17, 754-755. https://doi.org/10.1093/bioinformatics/17.8.754
  6. Yang, Z. (1995) A space-time process model for the evolution of DNA sequences. Genetics 139, 993-1005. http://www.genetics.org/content/139/2/993.abstract

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