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Codon-substitution models to detect adaptive evolution that account for heterogeneous selective pressures among site
Ziheng Yang1, Willie J Swanson
1Galton Laboratory, Department of Biology, University College London, 4 Stephenson Way, London NW1 2HE, UK. z.yang@ucl.ac.uk
Molecular Biology and Evolution
|December 26, 2001
Summary
New fixed-sites models detect positive selection in protein sites using structural information. These models, applied to MHC and abalone lysin, confirm findings from random-sites models, highlighting evolutionary pressures.
Area of Science:
- Evolutionary biology
- Molecular evolution
- Bioinformatics
Background:
- The nonsynonymous to synonymous substitution rate ratio (omega) measures selective pressure on proteins.
- Existing random-sites models account for variable selective pressures across amino acid sites.
- Prior structural information can partition protein sites into classes with expected differential selective pressures.
Purpose of the Study:
- To implement and evaluate maximum likelihood models for pre-partitioned data sets (fixed-sites models).
- To account for heterogeneity among site partitions using distinct omega parameters.
- To analyze selective pressures on Major Histocompatibility Complex (MHC) class I alleles and abalone sperm lysin genes.
Main Methods:
- Developed and applied fixed-sites maximum likelihood models for codon substitution.
- Utilized tertiary protein structure to partition sites into functional classes (e.g., antigen recognition site, buried vs. solvent-exposed).
- Compared results with established random-sites models.
Main Results:
- Fixed-sites models detected positive selection in the antigen recognition site of MHC class I alleles.
- Positive selection was also identified at solvent-exposed sites of abalone sperm lysin.
- Results were consistent with and elaborated by random-sites models.
Conclusions:
- Fixed-sites models effectively incorporate prior structural information to detect site-specific selection.
- These models enhance the analysis of evolutionary pressures, particularly in functionally distinct protein regions.
- Both fixed-sites and random-sites models provide valuable insights into molecular evolution.
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