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The STAT (signal transducer and activator of transcription) proteins play a crucial role in the regulation of gene expression, but their targets and the manner in which they select them remain largely unknown. Using chromatin immunoprecipitation and DNA microarray analysis (ChIP-chip), we have identified the regions of human chromosome 22 bound by STAT1 and STAT2 in interferon-treated cells. Analysis of the genomic loci proximal to these binding sites introduced new candidate STAT1 and STAT2 target genes, several of which are affiliated with proliferation and apoptosis. The genes on chromosome 22 that exhibited interferon-induced up- or down-regulated expression were determined and correlated with the STAT-binding site information, revealing the potential regulatory effects of STAT1 and STAT2 on their target genes. Importantly, the comparison of STAT1-binding sites upon interferon (IFN)-γ and IFN-α treatments revealed dramatic changes in binding locations between the two treatments. The IFN-α induction revealed nonconserved STAT1 occupancy at IFN-γ-induced sites, as well as novel sites of STAT1 binding not evident in IFN-γ-treated cells. Many of these correlated with binding by STAT2, but others were STAT2 independent, suggesting that multiple mechanisms direct STAT1 binding to its targets under different activation conditions. Overall, our results reveal a wealth of new information regarding IFN/STAT-binding targets and also fundamental insights into mechanisms of regulation of gene expression in different cell states. [ABSTRACT FROM AUTHOR]

We have mapped the chromosomal binding site distribution of a transcription factor in human cells. The NF-KB family of transcription factors plays an essential role in regulating the induction of genes involved in several physiological processes, including apoptosis, immunity, and inflammation. The binding sites of the NF-&key;B family member p65 were determined by using chromatin immunoprecipiration and a genomic microarray of human chromosome 22 DNA. Sites of binding were observed along the entire chromosome in both ceding and noncoding regions, with an enrichment at the 5' end of genes. Strikingly, a significant proportion of binding was seen in intronic regions, demonstrating that transcription factor binding is not restricted to promoter regions. NF-&key;B binding was also found at genes whose expression was regulated by tumor necrosis factor a, a known inducer of NF-&key;B-dependent gene expression, as well as adjacent to genes whose expression is not affected by tumor necrosis factor α. Many of these latter genes are either known to be activated by NF-&key;B under other conditions or are consistent with NF-&key;B's role in the immune and apoptotic responses. Our results suggest that binding is not restricted to promoter regions and that NF-&key;B binding occurs at a significant number of genes whose expression is not altered, thereby suggesting that binding alone is not sufficient for gene activation. [ABSTRACT FROM AUTHOR]

Recent progress in mapping transcription factor (TF) binding regions can largely be credited to chromatin immunoprecipitation (ChIP) technologies. We compared strategies for mapping TF binding regions in mammalian cells using two different ChIP schemes: ChIP with DNA microarray analysis (ChIP-chip) and ChIP with DNA sequencing (ChIP-PET). We first investigated parameters central to obtaining robust ChIP-chip data sets by analyzing STAT1 targets in the ENCODE regions of the human genome, and then compared ChIP-chip to ChIP-PET. We devised methods for scoring and comparing results among various tiling arrays and examined parameters such as DNA microarray format, oligonucleotide length, hybridization conditions, and the use of competitor Cot-1 DNA. The best performance was achieved with high-density oligonucleotide arrays, oligonucleotides ≥50 bases (b), the presence of competitor Cot-1 DNA and hybridizations conducted in microfluidics stations. When target identification was evaluated as a function of array number, 80%-86% of targets were identified with three or more arrays. Comparison of ChIP-chip with ChIP-PET revealed strong agreement for the highest ranked targets with less overlap for the low ranked targets. With advantages and disadvantages unique to each approach, we found that ChIP-chip and ChIP-PET are frequently complementary in their relative abilities to detect STAT1 targets for the lower ranked targets; each method detected validated targets that were missed by the other method. The most comprehensive list of STAT1 binding regions is obtained by merging results from ChIP-chip and ChIP-sequencing. Overall, this study provides information for robust identification, scoring, and validation of TF targets using ChIP-based technologies. [ABSTRACT FROM AUTHOR]