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PMID: 9866196 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S.

Models of amino acid substitution and applications to mitochondrial protein evolution.

Molecular biology and evolution ·Vol. 15 ·No. 12 ·1998-12-00 ·Pages 1600-11

Yang Z, Nielsen R, Hasegawa M

Abstract

Models of amino acid substitution were developed and compared using maximum likelihood. Two kinds of models are considered. "Empirical" models do not explicitly consider factors that shape protein evolution, but attempt to summarize the substitution pattern from large quantities of real data. "Mechanistic" models are formulated at the codon level and separate mutational biases at the nucleotide level from selective constraints at the amino acid level. They account for features of sequence evolution, such as transition-transversion bias and base or codon frequency biases, and make use of physicochemical distances between amino acids to specify nonsynonymous substitution rates. A general approach is presented that transforms a Markov model of codon substitution into a model of amino acid replacement. Protein sequences from the entire mitochondrial genomes of 20 mammalian species were analyzed using different models. The mechanistic models were found to fit the data better than empirical models derived from large databases. Both the mutational distance between amino acids (determined by the genetic code and mutational biases such as the transition-transversion bias) and the physicochemical distance are found to have strong effects on amino acid substitution rates. A significant proportion of amino acid substitutions appeared to have involved more than one codon position, indicating that nucleotide substitutions at neighboring sites may be correlated. Rates of amino acid substitution were found to be highly variable among sites.

MeSH Terms
Amino Acid Substitution Animals DNA, Mitochondrial/genetics Evolution, Molecular Humans Likelihood Functions Mammals/genetics Mitochondria/metabolism Models, Genetic Models, Statistical Phylogeny Proteins/genetics
Chemicals
DNA, Mitochondrial Proteins
Authors & Affiliations
3 authors, click to expand affiliations / ORCID
Yang Z
Department of Biology (Galton Laboratory), University College London, England. [email protected]
Nielsen R
Hasegawa M
Article Info
Journal
Molecular biology and evolution
Abbr.
Mol Biol Evol
ISSN
0737-4038
Published
1998-12-00
Pages
1600-11
Language
English
Region
United States
NLM ID
8501455
Subset
IM
Grants
NIGMS NIH HHS · GM40282 · United States
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