Constant relative rate of protein evolution and detection of functional diversification among bacterial, archaeal and eukaryotic proteins
National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD20894, USA
Genome Biology 2001, 2:research0053-research0053.9 doi:10.1186/gb-2001-2-12-research0053Published: 20 November 2001
Detection of changes in a protein's evolutionary rate may reveal cases of change in that protein's function. We developed and implemented a simple relative rates test in an attempt to assess the rate constancy of protein evolution and to detect cases of functional diversification between orthologous proteins. The test was performed on clusters of orthologous protein sequences from complete bacterial genomes (Chlamydia trachomatis, C. muridarum and Chlamydophila pneumoniae), complete archaeal genomes (Pyrococcus horikoshii, P. abyssi and P. furiosus) and partially sequenced mammalian genomes (human, mouse and rat).
Amino-acid sequence evolution rates are significantly correlated on different branches of phylogenetic trees representing the great majority of analyzed orthologous protein sets from all three domains of life. However, approximately 1% of the proteins from each group of species deviates from this pattern and instead shows variation that is consistent with an acceleration of the rate of amino-acid substitution, which may be due to functional diversification. Most of the putative functionally diversified proteins from all three species groups are predicted to function at the periphery of the cells and mediate their interaction with the environment.
Relative rates of protein evolution are remarkably constant for the three species groups analyzed here. Deviations from this rate constancy are probably due to changes in selective constraints associated with diversification between orthologs. Functional diversification between orthologs is thought to be a relatively rare event. However, the resolution afforded by the test designed specifically for genomic-scale datasets allowed us to identify numerous cases of possible functional diversification between orthologous proteins.