Cis-regulatory modules in the mammalian liver: Composition depends on strength of Foxa2 consensus site

Department of Genetics, Genomics and Computational Biology Graduate Group, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA.
Nucleic Acids Research (Impact Factor: 9.11). 08/2008; 36(12):4149-57. DOI: 10.1093/nar/gkn366
Source: PubMed


Foxa2 is a critical transcription factor that controls liver development and plays an important role in hepatic gluconeogensis in adult mice. Here, we use genome-wide location analysis for Foxa2 to identify its targets in the adult liver. We then show by computational analyses that Foxa2 containing cis-regulatory modules are not constructed from a random assortment of binding sites for other transcription factors expressed in the liver, but rather that their composition depends on the strength of the Foxa2 consensus site present. Genes containing a cis-regulatory module with a medium or weak Foxa2 consensus site are much more liver-specific than the genes with a strong consensus site. We not only provide a better understanding of the mechanisms of Foxa2 regulation but also introduce a novel method for identification of different cis-regulatory modules involving a single factor.


Available from: Klaus H Kaestner
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    • "2.10. ChIP-Seq analyses Islet chromatin was prepared from approximately 600 mouse islets each for two biological replicates, as previously described in Ref. [29]. "
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    Molecular Metabolism 08/2014; 3(8). DOI:10.1016/j.molmet.2014.08.001
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    • "Liver chromatin from fasted and re-fed mice was prepared as previously described [53]. Immunoprecipitations were performed and ChIP-Seq libraries were prepared as previously described [16], using anti-CREB (Santa Cruz Biotech, sc-186), anti-NR3C1/GR (mix of: Santa Cruz Biotech, sc-1004 and Thermo Scientific, PA1-511A), and anti-CEBPB (Santa Cruz Biotech, sc-150) antibodies. "
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    ABSTRACT: Background Metabolic homeostasis in mammals critically depends on the regulation of fasting-induced genes by CREB in the liver. Previous genome-wide analysis has shown that only a small percentage of CREB target genes are induced in response to fasting-associated signaling pathways. The precise molecular mechanisms by which CREB specifically targets these genes in response to alternating hormonal cues remain to be elucidated. Results We performed chromatin immunoprecipitation coupled to high-throughput sequencing of CREB in livers from both fasted and re-fed mice. In order to quantitatively compare the extent of CREB-DNA interactions genome-wide between these two physiological conditions we developed a novel, robust analysis method, termed the ‘single sample independence’ (SSI) test that greatly reduced the number of false-positive peaks. We found that CREB remains constitutively bound to its target genes in the liver regardless of the metabolic state. Integration of the CREB cistrome with expression microarrays of fasted and re-fed mouse livers and ChIP-seq data for additional transcription factors revealed that the gene expression switches between the two metabolic states are associated with co-localization of additional transcription factors at CREB sites. Conclusions Our results support a model in which CREB is constitutively bound to thousands of target genes, and combinatorial interactions between DNA-binding factors are necessary to achieve the specific transcriptional response of the liver to fasting. Furthermore, our genome-wide analysis identifies thousands of novel CREB target genes in liver, and suggests a previously unknown role for CREB in regulating ER stress genes in response to nutrient influx.
    BMC Genomics 05/2013; 14(1):337. DOI:10.1186/1471-2164-14-337 · 3.99 Impact Factor
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    • "nsus binding sequence were at genes that are much more liver - specific than genes with a strong consensus sequence ( Tuteja et al . 2008 ) . Simple target site affinity was not a predictor of FoxA occupancy , at least in terminally differentiated cells . While the nature of this is discussed in detail below ( and see also Hoffman et al . 2010 ) , Tuteja et al . ( 2008 ) did find that medium - and lower - affinity , liver - specific targets were highly enriched for binding of other hepatic nuclear fac - tors , suggesting a role for cooperative binding during the maintenance of differentiation . Furthermore , in adult liver tissue , FoxA1 and FoxA2 binding was not required to maintain local nucleosome "
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    ABSTRACT: Transcription factors are adaptor molecules that detect regulatory sequences in the DNA and target the assembly of protein complexes that control gene expression. Yet much of the DNA in the eukaryotic cell is in nucleosomes and thereby occluded by histones, and can be further occluded by higher-order chromatin structures and repressor complexes. Indeed, genome-wide location analyses have revealed that, for all transcription factors tested, the vast majority of potential DNA-binding sites are unoccupied, demonstrating the inaccessibility of most of the nuclear DNA. This raises the question of how target sites at silent genes become bound de novo by transcription factors, thereby initiating regulatory events in chromatin. Binding cooperativity can be sufficient for many kinds of factors to simultaneously engage a target site in chromatin and activate gene expression. However, in cases in which the binding of a series of factors is sequential in time and thus not initially cooperative, special "pioneer transcription factors" can be the first to engage target sites in chromatin. Such initial binding can passively enhance transcription by reducing the number of additional factors that are needed to bind the DNA, culminating in activation. In addition, pioneer factor binding can actively open up the local chromatin and directly make it competent for other factors to bind. Passive and active roles for the pioneer factor FoxA occur in embryonic development, steroid hormone induction, and human cancers. Herein we review the field and describe how pioneer factors may enable cellular reprogramming.
    Genes & development 11/2011; 25(21):2227-41. DOI:10.1101/gad.176826.111 · 10.80 Impact Factor
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