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Identification and Validation of Novel Hedgehog-Responsive Enhancers Predicted by Computational Analysis of Ci/Gli Binding Site Density.

ABSTRACT: The Hedgehog (Hh) signaling pathway directs a multitude of cellular responses during embryogenesis and adult tissue homeostasis. Stimulation of the pathway results in activation of Hh target genes by the transcription factor Ci/Gli, which binds to specific motifs in genomic enhancers. In Drosophila, only a few enhancers (patched, decapentaplegic, wingless, stripe, knot, hairy, orthodenticle) have been shown by in vivo functional assays to depend on direct Ci/Gli regulation. All but one (orthodenticle) contain more than one Ci/Gli site, prompting us to directly test whether homotypic clustering of Ci/Gli binding sites is sufficient to define a Hh-regulated enhancer. We therefore developed a computational algorithm to identify Ci/Gli clusters that are enriched over random expectation, within a given region of the genome. Candidate genomic regions containing Ci/Gli clusters were functionally tested in chicken neural tube electroporation assays and in transgenic flies. Of the 22 Ci/Gli clusters tested, seven novel enhancers (and the previously known patched enhancer) were identified as Hh-responsive and Ci/Gli-dependent in one or both of these assays, including: Cuticular protein 100A (Cpr100A); invected (inv), which encodes an engrailed-related transcription factor expressed at the anterior/posterior wing disc boundary; roadkill (rdx), the fly homolog of vertebrate Spop; the segment polarity gene gooseberry (gsb); and two previously untested regions of the Hh receptor-encoding patched (ptc) gene. We conclude that homotypic Ci/Gli clustering is not sufficient information to ensure Hh-responsiveness; however, it can provide a clue for enhancer recognition within putative Hedgehog target gene loci.

SUBMITTER: Gurdziel K

PROVIDER: S-EPMC4692483 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Identification and Validation of Novel Hedgehog-Responsive Enhancers Predicted by Computational Analysis of Ci/Gli Binding Site Density.

Gurdziel Katherine K Lorberbaum David S DS Udager Aaron M AM Song Jane Y JY Richards Neil N Parker David S DS Johnson Lisa A LA Allen Benjamin L BL Barolo Scott S Gumucio Deborah L DL

PloS one 20151228 12

The Hedgehog (Hh) signaling pathway directs a multitude of cellular responses during embryogenesis and adult tissue homeostasis. Stimulation of the pathway results in activation of Hh target genes by the transcription factor Ci/Gli, which binds to specific motifs in genomic enhancers. In Drosophila, only a few enhancers (patched, decapentaplegic, wingless, stripe, knot, hairy, orthodenticle) have been shown by in vivo functional assays to depend on direct Ci/Gli regulation. All but one (orthoden ...[more]

PMID: 26710299

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Project description:The Hedgehog (Hh) signaling pathway, acting through three homologous transcription factors (GLI1, GLI2, GLI3) in vertebrates, plays multiple roles in embryonic organ development and adult tissue homeostasis. At the level of the genome, GLI factors bind to specific motifs in enhancers, some of which are hundreds of kilobases removed from the gene promoter. These enhancers integrate the Hh signal in a context-specific manner to control the spatiotemporal pattern of target gene expression. Importantly, a number of genes that encode Hh pathway molecules are themselves targets of Hh signaling, allowing pathway regulation by an intricate balance of feed-back activation and inhibition. However, surprisingly few of the critical enhancer elements that control these pathway target genes have been identified despite the fact that such elements are central determinants of Hh signaling activity. Recently, ChIP studies have been carried out in multiple tissue contexts using mouse models carrying FLAG-tagged GLI proteins (GLI(FLAG)). Using these datasets, we tested whether a meta-analysis of GLI binding sites, coupled with a machine learning approach, could reveal genomic features that could be used to empirically identify Hh-regulated enhancers linked to loci of the Hh signaling pathway.A meta-analysis of four existing GLI(FLAG) datasets revealed a library of GLI binding motifs that was substantially more restricted than the potential sites predicted by previous in vitro binding studies. A machine learning method (kmer-SVM) was then applied to these datasets and enriched k-mers were identified that, when applied to the mouse genome, predicted as many as 37,000 potential Hh enhancers. For functional analysis, we selected nine regions which were annotated to putative Hh pathway molecules and found that seven exhibited GLI-dependent activity, indicating that they are directly regulated by Hh signaling (78% success rate).The results suggest that Hh enhancer regions share common sequence features. The kmer-SVM machine learning approach identifies those features and can successfully predict functional Hh regulatory regions in genomic DNA surrounding Hh pathway molecules and likely, other Hh targets. Additionally, the library of enriched GLI binding motifs that we have identified may allow improved identification of functional GLI binding sites.

Project description:Aberrant activation of Hedgehog (HH) signaling has been identified as a key etiologic factor of many human malignancies. Signal strength, target gene specificity, and oncogenic activity of HH signaling profoundly depend on interactions with other pathways such as epidermal growth factor receptor-mediated signaling which has been shown to cooperate with HH/GLI in basal cell carcinoma and pancreatic cancer. We demonstrate that the human medulloblastoma cell line Daoy possesses a fully inducible endogenous HH pathway. Treatment of Daoy cells with Sonic Hedgehog or Smoothened agonist induced expression of GLI1 protein and prevented processing of GLI3 to its repressor form. To study interactions between HH- and EGF-induced signaling in greater detail, time-resolved measurements were carried out and analyzed on the transcriptomic as well as proteomic level. Daoy cells responded to the co-treatment by downregulating GLI1, PTCH, and HHIP on the transcript level which was also seen when Amphiregulin (AREG) was used instead of EGF. The finding that EGFR signaling silences proteins acting as negative regulators of HH signaling is firstly described here as a novel crosstalk mechanism. Furthermore, combined EGFR/HH signaling maintains high GLI1 protein levels contrasting its downregulation on the transcript level. On the other hand, high level synergism was observed with respect to a strong and significant upregulation of numerous canonical EGF-targets with putative tumor-promoting properties such as MMP7, VEGFA, and IL-8. In conclusion, synergistic effects between EGFR and HH signaling can selectively induce a switch from a canonical HH/GLI profile to a modulated specific target gene profile pointing to more wide-spread, yet context-dependent, interactions between HH/GLI and growth factor receptor signaling in human malignancies. To study interactions between HH- and EGF-induced signaling, time-resolved measurements were carried out over a period of 24 h at 14 different time points after stimulation by EGF with and without additional stimulation by SHH. Furthermore, as a control, cells without any stimulation by EGF and SHH (control) and cells in the presents of SHH were analyzed. Overall, three biological replicates of 60 different treatment/timepoints were analyzed yielding 180 different samples.

Dataset Information

Identification and Validation of Novel Hedgehog-Responsive Enhancers Predicted by Computational Analysis of Ci/Gli Binding Site Density.

Publications

Identification and Validation of Novel Hedgehog-Responsive Enhancers Predicted by Computational Analysis of Ci/Gli Binding Site Density.

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