Synonymous codon substitution matrices

  • Authors:
  • Adrian Schneider;Gaston H. Gonnet;Gina M. Cannarozzi

  • Affiliations:
  • Computational Biology Research Group, Institute for Computational Science, ETH Zürich, Zürich, Switzerland;Computational Biology Research Group, Institute for Computational Science, ETH Zürich, Zürich, Switzerland;Computational Biology Research Group, Institute for Computational Science, ETH Zürich, Zürich, Switzerland

  • Venue:
  • ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part II
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

Abstract

Observing differences between DNA or protein sequences and estimating the true amount of substitutions from them is a prominent problem in molecular evolution as many analyses are based on distance measures between biological sequences. Since the relationship between the observed and the actual amount of mutations is very complex, more than four decades of research have been spent to improve molecular distance measures. In this article we present a method called SynPAM which can be used to estimate the amount of synonymous change between sequences of coding DNA. The method is novel in that it is based on an empirical model of codon evolution and that it uses a maximum-likelihood formalism to measure synonymous change in terms of codon substitutions, while reducing the need for assumptions about DNA evolution to an absolute minimum. We compared the SynPAM method with two established methods for measuring synonymous sequence divergence. Our results suggest that this new method not only shows less variance, but is also able to capture weaker phylogenetic signals than the other methods.