Bayesian analysis of amino acid substitution models

Abstract

Models of amino acid substitution present challenges beyond those often faced with the analysis of DNA sequences. The alignments of amino acid sequences are often small, whereas the number of parameters to be estimated is potentially large when compared with the number of free parameters for nucleotide substitution models. Most approaches to the analysis of amino acid alignments have focused on the use of fixed amino acid models in which all of the potentially free parameters are fixed to values estimated from a large number of sequences. Often, these fixed amino acid models are specific to a gene or taxonomic group (e.g. the Mtmam model, which has parameters that are specific to mammalian mitochondrial gene sequences). Although the fixed amino acid models succeed in reducing the number of free parameters to be estimated-indeed, they reduce the number of free parameters from approximately 200 to 0-it is possible that none of the currently available fixed amino acid models is appropriate for a specific alignment. Here, we present four approaches to the analysis of amino acid sequences. First, we explore the use of a general time reversible model of amino acid substitution using a Dirichlet prior probability distribution on the 190 exchangeability parameters. Second, we then explore the behaviour of prior probability distributions that are 'centred' on the rates specified by the fixed amino acid model. Third, we consider a mixture of fixed amino acid models. Finally, we consider constraints on the exchangeability parameters as partitions, similar to how nucleotide substitution models are specified, and place a Dirichlet process prior model on all the possible partitioning schemes.

Expansion of the APC superfamily of secondary carriers

“…In this respect, the SuperFamilyTree (SFT1 and 2) programs, which are based on BLAST BIT scores for large numbers of binary comparisons, have been shown in six publications to be superior to other programs for depicting deep phylogenies 3,4,33–35,37 . This is in contrast to programs that construct phylogenetic trees that are based on multiple alignments such as Neighbour-Joining 38 , Bayesian integration over alignments 39 , and maximum parsimony 40 . When the proteins are sufficiently similar to generate reliable multiple alignments, the results from SFT agree with those obtained using multiple alignments because similarities can be detected between any set of homologs using variable parts of the sequences (Yen et al 2009; Yen et al 2010; Chen et al 2011).…”

Phylogenetic Characterization of Transport Protein Superfamilies: Superiority of SuperfamilyTree Programs over Those Based on Multiple Alignments

“…For neighbor-joining [Gascuel and Steel, 2006;Saitou and Nei, 1987], parsimony [Felsenstein, 1996;Kolaczkowski and Thornton, 2004], and Bayesian methods [Huelsenbeck et al, 2008], the resulting database was used to create a multiple alignment. In the neighbor-joining method, the multiple alignment was used to generate a neighbor-join phylogenetic tree using the ClustalX program [Thompson et al, 1997].…”

A duplicate gene rooting of seed plants and the phylogenetic position of flowering plants

“…Whelan & Goldman 2001;Le & Gascuel 2008), the available models are not necessarily the most appropriate for a specific dataset. Bayesian analysis of amino acid sequences is appropriate in this case because it does not rely on a fixed model (Huelsenbeck et al 2008). Estimation of an amino acid rate matrix that is specific to the protein to be analysed is also appropriate.…”