Grant: Discovery Grants Program - Individual

Transfer RNA (tRNA) genes are among the most important and ancient genes. A large number of studies have addressed tRNA sequence identification, structure prediction and identity elements. However, little is known about the evolution of tRNA genes in terms of number, organization and functional specificity on a genome-wide scale. Having a better understanding of tRNA repertoire evolution is expected to shed light on many important questions related to protein expression, such as the link between tRNA copy number and protein synthesis, the evolution of the genetic code and tRNA functional shift. Moreover, since tRNA genes are dispersed throughout the genome, they represent an interesting subset of genes to study the major evolutionary events that have transformed the genomes. Recently, we inferred the evolutionary history of the tRNA genes in 50 Bacillus strains. We observed that the tRNA genes in Bacillus genomes are mostly affected by duplications and deletions. We also observed large inversions occurring around the axes of replication (origin or terminus). The most interesting and surprising result came from the comparison of the rates of the different types of events in Bacillus and E. coli. The average rate of duplications inferred in Bacillus was 24 times lower than the one that was reported in the E. coli study, while the average rates of losses and inversions were both 12 times lower. These rates were extremely low, suggesting a strong selective pressure acting on tRNA gene repertoires in Bacillus. The goal of my research program is to conduct similar analyses in other bacteria. With the ever-increasing number of bacterial genomes being completely sequenced, there are more and more interesting bacterial genera to analyze: Listeria, Salmonella, Staphylococcus, Streptococcus and Vibrio for example. Comparing the evolution of those other genera with what was inferred in Bacillus and E. coli would help understand if certain genera are clearly more stable than others in terms of the number and the organization of tRNA genes, and if there is a correlation between this stability and the living environment of those different bacteria. However, as most of these newly sequenced bacterial genera exhibit a very high level of divergence compared to Bacillus, new algorithmic methods need to be developed to infer evolutionary histories of tRNA genes in those genomes. In particular, methods taking into account overlapping events and methods considering sequence, genomic context and structural information will be developed for the comparison of two genomes, then will be optimized and generalized to calculate the minimum evolutionary distance in the context of a whole phylogeny.