title: Identifying the conserved network of cis-regulatory sites of a eukaryotic genome.
abstract: A major focus of genome research has been to decipher the cis-regulatory code that governs complex transcriptional regulation. We report a computational approach for identifying conserved regulatory motifs of an organism directly from whole genome sequences of several related species without reliance on additional information. We first construct phylogenetic profiles for each promoter, then use a BLAST-like algorithm to efficiently search through the entire profile space of all of the promoters in the genome to identify conserved motifs and the promoters that contain them. Statistical significance is estimated by modified Karlin-Altschul statistics. We applied this approach to the analysis of 3,524 Saccharomyces cerevisiae promoters and identified a highly organized regulatory network involving 3,315 promoters and 296 motifs. This network includes nearly all of the currently known motifs and covers >90% of known transcription factor binding sites. Most of the predicted coregulated gene clusters in the network have additional supporting evidence. Theoretical analysis suggests that our algorithm should be applicable to much larger genomes, such as the human genome, without reaching its statistical limitation.
authors.affiliation: Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA.
authors.forename: Ting
authors.initials: T
authors.lastname: Wang
authors.forename: Gary D
authors.initials: GD
authors.lastname: Stormo
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D015966:Gene Expression Regulation, Fungal / Q000235:genetics*; D023281:Genomics / Q000379:methods*; D008957:Models, Genetic; D011401:Promoter Regions, Genetic / Q000235:genetics; D050436:Regulatory Elements, Transcriptional / Q000235:genetics*; D012441:Saccharomyces cerevisiae / Q000235:genetics*; D013045:Species Specificity