Integrative Method for Identifying Combinatorial Regulation of Transcription Factors

摘要

To identify combinatorial regulation of transcription factors (TFs) and their binding motifs is important for understanding gene expression. However, the customary approach in computational microarray analysis is to cluster gene expression patterns and to identify individual sequence motifs specific to each gene cluster. The limitations of this approach are: 1) it does not directly address combinatorial regulation by TFs; 2) Even if a sequence motif is found, it cannot identify the relevant TF(s) tothe motif. To overcome these limitations, we propose a novel method that integrates chromatin immunoprecipitation (ChIP) microarray data, DNA microarray data, and combinatorial motif analysis to identify combinatorial regulation of TFs and their bindingmotifs. We applied this method to yeast cell cycle, and searched up to 3-order combinations of motifs with 6-9 mer.