Analysis of bidirectional promoters in vertebrates

Abstract: The order of genes in eukaryotes is by and large random as a result of recombination events during evolution. However, there is a certain element of non-random gene order. For instance, genes of similar expression tend to cluster more commonly than by chance and functionally related genes tend to colocalize. Genome wide analyses of mammalian genomes have demonstrated an abundance of divergently transcribed genes in short intergenic regions of approximately 1000 bp. This means that the genes of such pairs have transcription start sites in close proximity. The gene pairs are thought to share an intervening regulatory sequence, a bi-directional promoter. There is evidence that bidirectional gene pairs are evolutionarily conserved and this may imply a functional significance. They are often associated with genes involved in DNA repair. Interestingly, expression profiles of ovarian and breast cancer show an enrichment of bidirectional gene pairs that include DNA repair genes, such as BRCA1, BRCA2, CKEK1 and FANC family members. The two genes of a bidirectional promoter are likely to be related in terms of transcriptional control. Therefore, through analyses of such gene pairs in eukaryotes we may obtain important information regarding transcriptional control mechanisms.

In this project, intergenic regions of bidirectional gene pairs were explored by sequence analysis. The aim was to examine whether promoters of such pairs have characteristics that are different from the promoter regions of other genes. A number of such pairs were therefore collected from a set of mammalian species, including human. Then these regions were analyzed in a profile based approach with respect to known transcription factor binding sites (TFBSs) and with respect to the TATA box, one of the core promoter elements. Furthermore, in a more unbiased approach MEME was used to identify motifs characteristic of bidirectional promoters. The results reveal a number of over-represented TFBSs as well as motifs identified by MEME. The overlap of these two datasets reveals previously identified TFBSs as well as motifs of potential biological interest.