Molecular Biology and Evolution, Vol 16, 1315-1328, Copyright © 1999 by Society for Molecular Biology and Evolution
Y Suzuki and T Gojobori
A method was developed for detecting the selective force at single amino
acid sites given a multiple alignment of protein-coding sequences. The
phylogenetic tree was reconstructed using the number of synonymous
substitutions. Then, the neutrality was tested for each codon site using
the numbers of synonymous and nonsynonymous changes throughout the
phylogenetic tree. Computer simulation showed that this method accurately
estimated the numbers of synonymous and nonsynonymous substitutions per
site, as long as the substitution number on each branch was relatively
small. The false-positive rate for detecting the selective force was
generally low. On the other hand, the true-positive rate for detecting the
selective force depended on the parameter values. Within the range of
parameter values used in the simulation, the true-positive rate increased
as the strength of the selective force and the total branch length (namely
the total number of synonymous substitutions per site) in the phylogenetic
tree increased. In particular, with the relative rate of nonsynonymous
substitutions to synonymous substitutions being 5.0, most of the positively
selected codon sites were correctly detected when the total branch length
in the phylogenetic tree was > or = 2.5. When this method was applied to
the human leukocyte antigen (HLA) gene, which included antigen recognition
sites (ARSs), positive selection was detected mainly on ARSs. This finding
confirmed the effectiveness of the present method with actual data.
Moreover, two amino acid sites were newly identified as positively selected
in non-ARSs. The three-dimensional structure of the HLA molecule indicated
that these sites might be involved in antigen recognition. Positively
selected amino acid sites were also identified in the envelope protein of
human immunodeficiency virus and the influenza virus hemagglutinin protein.
This method may be helpful for predicting functions of amino acid sites in
proteins, especially in the present situation, in which sequence data are
accumulating at an enormous speed.
ORIGINAL ARTICLE
A method for detecting positive selection at single amino acid sites
Center for Information Biology, National Institute of Genetics, Mishima, Japan.
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