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Improved mitochondrial amino acid substitution models for metazoan evolutionary studies
Improved mitochondrial amino acid substitution models for metazoan evolutionary studies
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Improved mitochondrial amino acid substitution models for metazoan evolutionary studies
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Improved mitochondrial amino acid substitution models for metazoan evolutionary studies
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Improved mitochondrial amino acid substitution models for metazoan evolutionary studies
Improved mitochondrial amino acid substitution models for metazoan evolutionary studies
Journal Article

Improved mitochondrial amino acid substitution models for metazoan evolutionary studies

2017
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Overview
Background Amino acid substitution models play an essential role in inferring phylogenies from mitochondrial protein data. However, only few empirical models have been estimated from restricted mitochondrial protein data of a hundred species. The existing models are unlikely to represent appropriately the amino acid substitutions from hundred thousands metazoan mitochondrial protein sequences. Results We selected 125,935 mitochondrial protein sequences from 34,448 species in the metazoan kingdom to estimate new amino acid substitution models targeting metazoa, vertebrates and invertebrate groups. The new models help to find significantly better likelihood phylogenies in comparison with the existing models. We noted remarkable distances from phylogenies with the existing models to the maximum likelihood phylogenies that indicate a considerable number of incorrect bipartitions in phylogenies with the existing models. Finally, we used the new models and mitochondrial protein data to certify that Testudines, Aves, and Crocodylia form one separated clade within amniotes. Conclusions We introduced new mitochondrial amino acid substitution models for metazoan mitochondrial proteins. The new models outperform the existing models in inferring phylogenies from metazoan mitochondrial protein data. We strongly recommend researchers to use the new models in analysing metazoan mitochondrial protein data.