A comparative genomics approach to prediction of new members of regulons

Identifying the complete transcriptional regulatory network for an organism is a major challenge. For each regulatory protein, we want to know all the genes it regulates, that is, its regulon. Examples of known binding sites can be used to estimate the binding specificity of the protein and to predi ct other binding sites. However, binding site predictions can be unreliable because determining the true specificity of the protein is difficult becau se of the considerable variability of binding sites. Because regulatory sys tems tend to be conserved through evolution, we can use comparisons between species to increase the reliability of binding site predictions. In this a rticle, an approach is presented to evaluate the computational predicitions of regulatory sites. We combine the prediction of transcription units havi ng orthologous genes with the prediction of transcription factor binding si tes based on probabilistic models. We augment the sets of genes in Escheric hia coli that are expected to be regulated by two transcription factors, th e cAMP receptor. protein and the fumarate and nitrate reduction regulatory protein, through a comparison with the Haemophilus influenzae genome. At th e same time, we learned more about the regulatory networks of H. influenzae , a species with much less experimental knowledge than E. coll. By studying orthologous genes subject to regulation by the same transcription factor, we also gained understanding of the evolution of the entire regulatory syst ems.