Abstract
BackgroundInteractions between transcription factors and their specific binding sites are a key component of regulation of gene expression. Until recently, it was generally assumed that most bacterial transcription factor binding sites are located at or near promoters. However, several recent works utilizing high-throughput technology to detect transcription factor binding sites in bacterial genomes found a large number of binding sites in unexpected locations, particularly inside genes, as opposed to known or expected promoter regions. While some of these intragenic binding sites likely have regulatory functions, an alternative scenario is that many of these binding sites arise by chance in the absence of selective constraints. The latter possibility was supported by in silico simulations for σ54 binding sites in Salmonella.ResultsIn this work, we extend these simulations to more than forty transcription factors from E. coli and other bacteria. The results suggest that binding sites for all analyzed transcription factors are likely to arise throughout the genome by random genetic drift and many transcription factor binding sites found in genomes may not have specific regulatory functions. In addition, when comparing observed and expected patterns of occurrence of binding sites in genomes, we observed distinct differences among different transcription factors.ConclusionsWe speculate that transcription factor binding sites randomly occurring throughout the genome could be beneficial in promoting emergence of new regulatory interactions and thus facilitating evolution of gene regulatory networks.
Highlights
Interactions between transcription factors and their specific binding sites are a key component of regulation of gene expression
Considering the different mechanisms for regulating transcription and wide-ranging roles of transcription factors that bind to numerous intragenic sites, we have extended the simulation performed for σ54 binding sites to more than 40 additional transcription factors to investigate whether our results for σ54 apply generally to transcription factors and whether there are significant differences among different regulatory proteins
In model ‘bb’, the genome annotation is used to divide the genome into segments consisting of individual protein-coding genes and intergenic regions; a random sequence is generated for each segment to mimic its nucleotide composition, and the randomized genome is reassembled from these segments
Summary
We extend these simulations to more than forty transcription factors from E. coli and other bacteria. When comparing observed and expected patterns of occurrence of binding sites in genomes, we observed distinct differences among different transcription factors
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