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Empirical codon substitution matrix.
Schneider, Adrian; Cannarozzi, Gina M; Gonnet, Gaston H.
Afiliação
  • Schneider A; Institute of Computational Science, Swiss Federal Institute of Technology, Zurich, Switzerland. schneadr@inf.ethz.ch <schneadr@inf.ethz.ch>
BMC Bioinformatics ; 6: 134, 2005 Jun 01.
Article em En | MEDLINE | ID: mdl-15927081
BACKGROUND: Codon substitution probabilities are used in many types of molecular evolution studies such as determining Ka/Ks ratios, creating ancestral DNA sequences or aligning coding DNA. Until the recent dramatic increase in genomic data enabled construction of empirical matrices, researchers relied on parameterized models of codon evolution. Here we present the first empirical codon substitution matrix entirely built from alignments of coding sequences from vertebrate DNA and thus provide an alternative to parameterized models of codon evolution. RESULTS: A set of 17,502 alignments of orthologous sequences from five vertebrate genomes yielded 8.3 million aligned codons from which the number of substitutions between codons were counted. From this data, both a probability matrix and a matrix of similarity scores were computed. They are 64 x 64 matrices describing the substitutions between all codons. Substitutions from sense codons to stop codons are not considered, resulting in block diagonal matrices consisting of 61 x 61 entries for the sense codons and 3 x 3 entries for the stop codons. CONCLUSION: The amount of genomic data currently available allowed for the construction of an empirical codon substitution matrix. However, more sequence data is still needed to construct matrices from different subsets of DNA, specific to kingdoms, evolutionary distance or different amount of synonymous change. Codon mutation matrices have advantages for alignments up to medium evolutionary distances and for usages that require DNA such as ancestral reconstruction of DNA sequences and the calculation of Ka/Ks ratios.
Assuntos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Códon / Biologia Computacional / Modelos Genéticos Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Animals / Humans Idioma: En Revista: BMC Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2005 Tipo de documento: Article

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Códon / Biologia Computacional / Modelos Genéticos Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Animals / Humans Idioma: En Revista: BMC Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2005 Tipo de documento: Article