Journal
GENOME RESEARCH
Volume 16, Issue 12, Pages 1585-1595Publisher
COLD SPRING HARBOR LAB PRESS, PUBLICATIONS DEPT
DOI: 10.1101/gr.5520206
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Funding
- NCI NIH HHS [CA45250] Funding Source: Medline
- NHGRI NIH HHS [HG003129, R01 HG003129] Funding Source: Medline
- NIDDK NIH HHS [R56 DK067889, DK067889, R01 DK067889] Funding Source: Medline
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Advances in high-throughput technologies, such as ChIP-chip, and the completion of human and mouse genomic sequences now allow analysis of the mechanisms of gene regulation on a systems level. In this study, we have developed a computational genomics approach (termed ChIPModules), which begins with experimentally determined binding sites and integrates positional weight matrices constructed from transcription factor binding sites, a comparative genomics approach, and statistical learning methods to identify transcriptional regulatory modules. We began with E2F1 binding site information obtained from ChIP-chip analyses of ENCODE regions, from both HeLa and MCF7 cells. Our approach not only distinguished targets from nontargets with a high specificity, but it also identified five regulatory modules for E2F1. One of the identified modules predicted a colocalization of E2F1 and AP-2 alpha on a set of target promoters with an intersite distance of < 270 bp. We tested this prediction using ChIP-chip assays with arrays containing similar to 14,000 human promoters. We found that both E2F1 and AP- 2 alpha bind within the predicted distance to a large number of human promoters, demonstrating the strength of our sequence-based, unbiased, and universal protocol. Finally, we have used our ChIPModules approach to develop a database that includes thousands of computationally identified and/or experimentally verified E2F1 target promoters.
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