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

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Abstract
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 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.