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Gene Block Evolution In Proteobacteria

Introduction

How do gene blocks evolve? Gene blocks are proximal genes in the bacterial genome that operate together. Known special cases of gene blocks are operons, where the genes are typically co-transcribed in a polycistronic mRNA. Several models have been proposed to explain observed patterns of gene block evolution. However, there is no universal method to describe gene block evolution, which is necessary for a comprehensive examination of the forces affecting this genomic feature. Here we propose such a method that will enable us to examine how gene blocks evolve on a case-by-case basis, and classify their evolutionary parameters.

We propose that the construction and/or destruction of gene blocks can be described as a sequential series of defined events which include: gene duplication, gene deletion, and gene(s) splitting from the block. By examining these events we can employ statistical learning to classify evolutionary paths of gene blocks, and connect these paths with biological function.

Methods

1. Choose a reference organism: E. coli K-12 MG1655, whose operons are well annotated in RegulonDB (ref), as our gene block dataset.
2. In a set of related proteobacteria, locate the homologs of the genes that constitute the gene blocks in E. coli.
3. Establish events which describe the changes in the gene block and its constituent genes throughout the targeted genomes.
4. See if these attributes correlate with function or evolutionary distance.

Conclusions

Using a set of 35 proteobacteria species and 38 different E. coli operons with 5 genes or more, we have looked at the frequency of events for the study of gene block evolution. These events enable us to explore the evolutionary trajectory of a single gene block from a reference organism throughout a designated phylogenetic tree. Some events correlate with evolutionary distance between taxa, while others do not. Some gene neighborhoods appear to have consistently high or low number of events making them fast or slow evolving, respectively. Fast evolvers include transporters & two-component systems. Slow evolvers include essential gene complexes and information processing operons.