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Phylogenetic estimation of context-dependent substitution rates by maximum likelihood
1Center for Biomolecular Science and Engineering, University of California, Santa Cruz, USA. acs@soe.ucsc.edu
Molecular Biology and Evolution
|December 9, 2003
Summary
New phylogenetic models accurately capture context-dependent nucleotide substitution rates, improving genomic data analysis. These models reveal complex substitution patterns in coding and noncoding DNA, enhancing evolutionary insights.
Area of Science:
- Computational Biology
- Evolutionary Genetics
- Bioinformatics
Background:
- Nucleotide substitution rates are influenced by neighboring bases (context-dependent substitution).
- Existing phylogenetic models have limited ability to incorporate context-dependent substitution, especially for complex phylogenies.
Purpose of the Study:
- To extend standard phylogenetic models to effectively handle context-dependent nucleotide substitution.
- To enable exact inference at a reasonable computational cost for improved phylogenetic analysis.
Main Methods:
- Developed extensions to standard phylogenetic models to incorporate context-dependent substitution within N-tuples of adjacent sites.
- Utilized an expectation-maximization algorithm with a quasi-Newton method for parameter estimation.
- Extended Felsenstein's algorithm to compute conditional probabilities for overlapping N-tuples, assuming Markov dependence.
Main Results:
- The new models significantly improve goodness of fit for both coding and noncoding genomic data compared to standard models or models with rate variation across sites.
- Context dependence provides a larger improvement than richer substitution models or site-specific rate variation.
- Analysis of mammalian genomes revealed a pronounced CpG effect and complex context-dependent substitution patterns in noncoding regions.
- Nucleotide-level analysis of coding regions showed significant context effects across codon boundaries, influencing amino acid substitution rates.
Conclusions:
- Enhanced phylogenetic models incorporating context-dependent nucleotide substitution offer substantial improvements in data fitting and biological insight.
- These models provide a more accurate representation of evolutionary processes, particularly in mammalian genomes.
- Understanding context-dependent substitution at the nucleotide level is crucial for accurately inferring amino acid substitution rates and evolutionary histories.
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