Journal of Molecular Evolution

, Volume 59, Issue 1, pp 121–132

A Maximum Likelihood Method for Detecting Functional Divergence at Individual Codon Sites, with Application to Gene Family Evolution


DOI: 10.1007/s00239-004-2597-8

Cite this article as:
Bielawski, J.P. & Yang, Z. J Mol Evol (2004) 59: 121. doi:10.1007/s00239-004-2597-8


The tailoring of existing genetic systems to new uses is called genetic co-option. Mechanisms of genetic co-option have been difficult to study because of difficulties in identifying functionally important changes. One way to study genetic co-option in protein-coding genes is to identify those amino acid sites that have experienced changes in selective pressure following a genetic co-option event. In this paper we present a maximum likelihood method useful for measuring divergent selective pressures and identifying the amino acid sites affected by divergent selection. The method is based on a codon model of evolution and uses the nonsynonymous-to-synonymous rate ratio (ω) as a measure of selection on the protein, with ω = 1, <1, and >1 indicating neutral evolution, purifying selection, and positive selection, respectively. The model allows variation in ω among sites, with a fraction of sites evolving under divergent selective pressures. Divergent selection is indicated by different ω’s between clades, such as between paralogous clades of a gene family. We applied the codon model to duplication followed by functional divergence of (i) the ε and γ globin genes and (ii) the eosinophil cationic protein (ECP) and eosinophil-derived neurotoxin (EDN) genes. In both cases likelihood ratio tests suggested the presence of sites evolving under divergent selective pressures. Results of the ε and γ globin analysis suggested that divergent selective pressures might be a consequence of a weakened relationship between fetal hemoglobin and 2,3-diphosphoglycerate. We suggest that empirical Bayesian identification of sites evolving under divergent selective pressures, combined with structural and functional information, can provide a valuable framework for identifying and studying mechanisms of genetic co-option. Limitations of the new method are discussed.


Maximum likelihoodFunctional divergenceCodon modelECPEDNGlobins

Copyright information

© Springer-Verlag 2004

Authors and Affiliations

  1. 1.Department of BiologyUniversity College LondonLondonUK
  2. 2.Department of BiologyDalhousie UniversityHalifaxCanada