Transcription Factor Binding Probabilities in Orthologous Promoters: An Alignment-Free Approach to the Inference of Functional Regulatory Targets

Abstract

Using a physically principled method of scoring genomic sequences for the potential to be bound by transcription factors, we have developed an algorithm for assessing the conservation of predicted binding occupancy that does not rely on sequence alignment of promoters. The method, which we call ortholog-weighting, assesses the degree to which the predicted binding occupancy of a transcription factor in a reference gene is also predicted in the promoters of orthologous genes. The analysis was performed separately for over 100 different transcription factors in S. cerevisiae. Statistical significance was evaluated by simulation using permuted versions of the position weight matrices. Ortholog-weighting produced about twice as many significantly high scoring genes as were obtained from the S. cerevisiae genome alone. Gene Ontology analysis found a similar two-fold enrichment of genes. Both analyses suggest that ortholog-weighting improves the prediction of true regulatory targets. Interestingly, the method has only a marginal effect on the prediction of binding by chromatin immunoprecipitation (ChIP) assays. We suggest several possibilities for reconciling this result with the improved enrichment that we observe for functionally related promoters and for promoters that are under positive selection.