Dataset Information

Molecular interactions between HNF4a, FOXA2 and GABP identified at regulatory DNA elements through ChIP-sequencing.

ABSTRACT: Gene expression is regulated by combinations of transcription factors, which can be mapped to regulatory elements on a genome-wide scale using ChIP experiments. In a previous ChIP-chip study of USF1 and USF2 we found evidence also of binding of GABP, FOXA2 and HNF4a within the enriched regions. Here, we have applied ChIP-seq for these transcription factors and identified 3064 peaks of enrichment for GABP, 7266 for FOXA2 and 18783 for HNF4a. Distal elements with USF2 signal was frequently bound also by HNF4a and FOXA2. GABP peaks were found at transcription start sites, whereas 94% of FOXA2 and 90% of HNF4a peaks were located at other positions. We developed a method to accurately define TFBS within peaks, and found the predicted sites to have an elevated conservation level compared to peak centers; however the majority of bindings were not evolutionary conserved. An interaction between HNF4a and GABP was seen at TSS, with one-third of the HNF4a positive promoters being bound also by GABP, and this interaction was verified by co-immunoprecipitations.

SUBMITTER: Wallerman O

PROVIDER: S-EPMC2794179 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature

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Molecular interactions between HNF4a, FOXA2 and GABP identified at regulatory DNA elements through ChIP-sequencing.

Wallerman Ola O Motallebipour Mehdi M Enroth Stefan S Patra Kalicharan K Bysani Madhu Sudhan Reddy MS Komorowski Jan J Wadelius Claes C

Nucleic acids research 20091201 22

Gene expression is regulated by combinations of transcription factors, which can be mapped to regulatory elements on a genome-wide scale using ChIP experiments. In a previous ChIP-chip study of USF1 and USF2 we found evidence also of binding of GABP, FOXA2 and HNF4a within the enriched regions. Here, we have applied ChIP-seq for these transcription factors and identified 3064 peaks of enrichment for GABP, 7266 for FOXA2 and 18783 for HNF4a. Distal elements with USF2 signal was frequently bound a ...[more]

PMID: 19822575

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Project description:BackgroundIn eukaryotes, transcriptional regulation is usually mediated by interactions of multiple transcription factors (TFs) with their respective specific cis-regulatory elements (CREs) in the so-called cis-regulatory modules (CRMs) in DNA. Although the knowledge of CREs and CRMs in a genome is crucial to elucidate gene regulatory networks and understand many important biological phenomena, little is known about the CREs and CRMs in most eukaryotic genomes due to the difficulty to characterize them by either computational or traditional experimental methods. However, the exponentially increasing number of TF binding location data produced by the recent wide adaptation of chromatin immunoprecipitation coupled with microarray hybridization (ChIP-chip) or high-throughput sequencing (ChIP-seq) technologies has provided an unprecedented opportunity to identify CRMs and CREs in genomes. Nonetheless, how to effectively mine these large volumes of ChIP data to identify CREs and CRMs at nucleotide resolution is a highly challenging task.ResultsWe have developed a novel graph-theoretic based algorithm DePCRM for genome-wide de novo predictions of CREs and CRMs using a large number of ChIP datasets. DePCRM predicts CREs and CRMs by identifying overrepresented combinatorial CRE motif patterns in multiple ChIP datasets in an effective way. When applied to 168 ChIP datasets of 56 TFs from D. melanogaster, DePCRM identified 184 and 746 overrepresented CRE motifs and their combinatorial patterns, respectively, and predicted a total of 115,932 CRMs in the genome. The predictions recover 77.9% of known CRMs in the datasets and 89.3% of known CRMs containing at least one predicted CRE. We found that the putative CRMs as well as CREs as a whole in a CRM are more conserved than randomly selected sequences.ConclusionOur results suggest that the CRMs predicted by DePCRM are highly likely to be functional. Our algorithm is the first of its kind for de novo genome-wide prediction of CREs and CRMs using larger number of transcription factor ChIP datasets. The algorithm and predictions will hopefully facilitate the elucidation of gene regulatory networks in eukaryotes. All the predicted CREs, CRMs, and their target genes are available at http://bioinfo.uncc.edu/mniu/pcrms/www/.

Project description:BackgroundChIP-chip and ChIP-seq are widely used methods to map protein-DNA interactions on a genomic scale in vivo. Waldminghaus and Skarstad recently reported, in this journal, a modified method for ChIP-chip. Based on a comparison of our previously-published ChIP-chip data for Escherichia coli ?32 with their own data, Waldminghaus and Skarstad concluded that many of the ?32 targets identified in our earlier work are false positives. In particular, we identified many non-canonical ?32 targets that are located inside genes or are associated with genes that show no detectable regulation by ?32. Waldminghaus and Skarstad propose that such non-canonical sites are artifacts, identified due to flaws in the standard ChIP methodology. Waldminghaus and Skarstad suggest specific changes to the standard ChIP procedure that reportedly eliminate the claimed artifacts.ResultsWe reanalyzed our published ChIP-chip datasets for ?32 and the datasets generated by Waldminghaus and Skarstad to assess data quality and reproducibility. We also performed targeted ChIP/qPCR for ?32 and an unrelated transcription factor, AraC, using the standard ChIP method and the modified ChIP method proposed by Waldminghaus and Skarstad. Furthermore, we determined the association of core RNA polymerase with disputed ?32 promoters, with and without overexpression of ?32. We show that (i) our published ?32 ChIP-chip datasets have a consistently higher dynamic range than those of Waldminghaus and Skarstad, (ii) our published ?32 ChIP-chip datasets are highly reproducible, whereas those of Waldminghaus and Skarstad are not, (iii) non-canonical ?32 target regions are enriched in a ?32 ChIP in a heat shock-dependent manner, regardless of the ChIP method used, (iv) association of core RNA polymerase with some disputed ?32 target genes is induced by overexpression of ?32, (v) ?32 targets disputed by Waldminghaus and Skarstad are predominantly those that are most weakly bound, and (vi) the modifications to the ChIP method proposed by Waldminghaus and Skarstad reduce enrichment of all protein-bound genomic regions.ConclusionsThe modifications to the ChIP-chip method suggested by Waldminghaus and Skarstad reduce rather than increase the quality of ChIP data. Hence, the non-canonical ?32 targets identified in our previous study are likely to be genuine. We propose that the failure of Waldminghaus and Skarstad to identify many of these ?32 targets is due predominantly to the lower data quality in their study. We conclude that surprising ChIP-chip results are not artifacts to be ignored, but rather indications that our understanding of DNA-binding proteins is incomplete.

Dataset Information

Molecular interactions between HNF4a, FOXA2 and GABP identified at regulatory DNA elements through ChIP-sequencing.

Publications

Molecular interactions between HNF4a, FOXA2 and GABP identified at regulatory DNA elements through ChIP-sequencing.

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