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Identifying site-specific substitution rates.

Sonja Meyer·Arndt von Haeseler
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Abstract

A maximum likelihood framework for estimating site-specific substitution rates is presented that does not require any prior assumptions about the rate distribution. We show that, when the branching pattern of the underlying tree is known, the analysis of pairs of positions is sufficient to estimate site-specific rates. In the abscense of a known topology, we introduce an iterative procedure to estimate simultaneously the branching pattern, the branch lengths, and site-specific substitution rates. Simulations show that the evolutionary rate of fast-evolving sites can be reliably inferred and that the accuracy of rate estimates depends mainly on the number of sequences in the data set. Thus, large sets of aligned sequences are necessary for reliable site-specific rate estimates. The method is applied to the complete mitochondrial DNA sequence of 53 humans, providing a complete picture of the site-specific substitution rates in human mitochondrial DNA.

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AlgorithmsDNA, MitochondrialHumansLikelihood FunctionsLinear ModelsModels, GeneticModels, StatisticalMutationJournal ArticleResearch Support, Non-U.S. Gov't

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Sonja Meyer, Arndt von Haeseler. 2003. Identifying site-specific substitution rates.. https://doi.org/10.1093/molbev%2Fmsg019

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