This article is part of the supplement: Eleventh International Conference on Bioinformatics (InCoB2012): Computational Biology
A novel unbiased measure for motif co-occurrence predicts combinatorial regulation of transcription
- Equal contributors
1 Laboratory of Systems Immunology, Immunology Frontier Research Center, Osaka University, 3-1 Yamada-oka, Suita, Osaka 565-0871, Japan
2 Laboratory of Host Defense, Immunology Frontier Research Center, Osaka University, 3-1 Yamada-oka, Suita, Osaka 565-0871, Japan
3 Department of Host Defense, Research Institute for Microbial Diseases, Osaka University, 3-1 Yamada-oka, Suita, Osaka 565-0871, Japan
Citation and License
BMC Genomics 2012, 13(Suppl 7):S11 doi:10.1186/1471-2164-13-S7-S11Published: 13 December 2012
Multiple transcription factors (TFs) are involved in the generation of gene expression patterns, such as tissue-specific gene expression and pleiotropic immune responses. However, how combinations of TFs orchestrate diverse gene expression patterns is poorly understood. Here we propose a new measure for regulatory motif co-occurrence and a new methodology to systematically identify TF pairs significantly co-occurring in a set of promoter sequences.
Initial analyses suggest that non-CpG promoters have a higher potential for combinatorial regulation than CpG island-associated promoters, and that co-occurrences are strongly influenced by motif similarity. We applied our method to large-scale gene expression data from various tissues, and showed how our measure for motif co-occurrence is not biased by motif over-representation. Our method identified, amongst others, the binding motifs of HNF1 and FOXP1 to be significantly co-occurring in promoters of liver/kidney specific genes. Binding sites tend to be positioned proximally to each other, suggesting interactions exist between this pair of transcription factors. Moreover, the binding sites of several TFs were found to co-occur with NF-κB and IRF sites in sets of genes with similar expression patterns in dendritic cells after Toll-like receptor stimulation. Of these, we experimentally verified that CCAAT enhancer binding protein alpha positively regulates its target promoters synergistically with NF-κB.
Both computational and experimental results indicate that the proposed method can clarify TF interactions that could not be observed by currently available prediction methods.