Article

Choosing Appropriate Substitution Models for the Phylogenetic Analysis of Protein-Coding Sequences

University of Oxford, Oxford, England, United Kingdom
Molecular Biology and Evolution (Impact Factor: 9.11). 02/2006; 23(1):7-9. DOI: 10.1093/molbev/msj021
Source: PubMed

ABSTRACT

Although phylogenetic inference of protein-coding sequences continues to dominate the literature, few analyses incorporate evolutionary models that consider the genetic code. This problem is exacerbated by the exclusion of codon-based models from commonly employed model selection techniques, presumably due to the computational cost associated with codon models. We investigated an efficient alternative to standard nucleotide substitution models, in which codon position (CP) is incorporated into the model. We determined the most appropriate model for alignments of 177 RNA virus genes and 106 yeast genes, using 11 substitution models including one codon model and four CP models. The majority of analyzed gene alignments are best described by CP substitution models, rather than by standard nucleotide models, and without the computational cost of full codon models. These results have significant implications for phylogenetic inference of coding sequences as they make it clear that substitution models incorporating CPs not only are a computationally realistic alternative to standard models but may also frequently be statistically superior.

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Available from: Alexei J Drummond, Nov 25, 2015
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    • "ddarriba/jmodeltest2; Posada, 2008) to compare substitution models based on the Bayesian Information Criterion (Alizon and Fraser 2013); the resulting substitution models were the Tamura-Nei (TnR) model (lp-fragment) and the Hasegawa, Kashino and Yano (HKY) model (vp3-and RdRp-fragments), both with Gamma variation. For the DWV-subtype data set, we compared the general time-reversible model and the SRD06 model (Shapiro et al., 2006) using path sampling. We partitioned substitution rates between the first and second and third codon positions as, for all data sets, the third codon position had a significantly higher rate. "
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