title: The slow:fast substitution ratio reveals changing patterns of natural selection in gamma-proteobacterial genomes.
abstract: Different microbial species are thought to occupy distinct ecological niches, subjecting each species to unique selective constraints, which may leave a recognizable signal in their genomes. Thus, it may be possible to extract insight into the genetic basis of ecological differences among lineages by identifying unusual patterns of substitutions in orthologous gene or protein sequences. We used the ratio of substitutions in slow- versus fast-evolving sites (nucleotides in DNA, or amino acids in protein sequence) to quantify deviations from the typical pattern of selective constraint observed across bacterial lineages. We propose that elevated S:F in one branch (an excess of slow-site substitutions) can indicate a functionally relevant change, due to either positive selection or relaxed evolutionary constraint. In a genome-wide comparative study of gamma-proteobacterial proteins, we find that cell-surface proteins involved with motility and secretion functions often have high S:F ratios, whereas information-processing genes do not. Change in evolutionary constraints in some species is evidenced by increased S:F ratios within functionally related sets of genes (for example, energy production in Pseudomonas fluorescens), whereas other species apparently evolve mostly by drift (for example, uniformly elevated S:F across most genes in Buchnera spp.). Overall, S:F reveals several species-specific, protein-level changes with potential functional/ecological importance. As microbial genome projects yield more species-rich gene trees, the S:F ratio will become an increasingly powerful tool for uncovering functional genetic differences among species.
authors.affiliation: Program in Computational and Systems Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.
authors.forename: B Jesse
authors.initials: BJ
authors.lastname: Shapiro
authors.forename: Eric
authors.initials: E
authors.lastname: Alm
mesh_terms: D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D004269:DNA, Bacterial / Q000235:genetics*; D019143:Evolution, Molecular; D020563:Gammaproteobacteria / Q000235:genetics*; D005798:Genes, Bacterial; D016680:Genome, Bacterial; D009154:Mutation; D012641:Selection, Genetic
chemical_list: D004269:DNA, Bacterial