@article{Bieda01052006,
author = {Bieda, Mark and Xu, Xiaoqin and Singer, Michael A. and Green, Roland and Farnham, Peggy J.}, 
title = {Unbiased location analysis of E2F1-binding sites suggests a widespread role for E2F1 in the human genome},
volume = {16}, 
number = {5}, 
pages = {595-605}, 
year = {2006}, 
doi = {10.1101/gr.4887606}, 
abstract ={The E2F family of transcription factors regulates basic cellular processes. Here, we take an unbiased approach towards identifying E2F1 target genes by examining localization of E2F1-binding sites using high-density oligonucleotide tiling arrays. To begin, we developed a statistically-based methodology for analysis of ChIP-chip data obtained from arrays that represent 30 Mb of the human genome. Using this methodology, we identified regions bound by E2F1, MYC, and RNA Polymerase II (POLR2A). We found a large number of binding sites for all three factors; extrapolation suggests there may be ∼20,000–30,000 E2F1- and MYC-binding sites and ∼12,000–17,000 active promoters in HeLa cells. In contrast to our results for MYC, we find that the majority of E2F1-binding sites (>80%) are located in core promoters and that 50% of the sites overlap transcription starts. Only a small fraction of E2F1 sites possess the canonical binding motif. Surprisingly, we found that ∼30% of genes in the 30-Mb region possessed an E2F1 binding site in a core promoter and E2F1 was bound near to 83% of POLR2A-bound sites. To determine if these results were representative of the entire human genome, we performed ChIP-chip analyses of ∼24,000 promoters and confirmed that greater than 20% of the promoters were bound by E2F1. Our results suggest that E2F1 is recruited to promoters via a method distinct from recognition of the known consensus site and point toward a new understanding of E2F1 as a factor that contributes to the regulation of a large fraction of human genes.}, 
URL = {http://genome.cshlp.org/content/16/5/595.abstract}, 
eprint = {http://genome.cshlp.org/content/16/5/595.full.pdf+html}, 
journal = {Genome Research} 
}