High Resolution Mapping of Enhancer-Promoter Interactions

RNA Polymerase II ChIA-PET data has revealed enhancers that are active in a profiled cell type and the genes that the enhancers regulate through chromatin interactions. The most commonly used computational method for analyzing ChIA-PET data, the ChIA-PET Tool, discovers interaction anchors at a spatial resolution that is insufficient to accurately identify individual enhancers. We introduce Germ, a computational method that estimates the likelihood that any two narrowly defined genomic locations are jointly occupied by RNA Polymerase II. Germ takes a blind deconvolution approach to simultaneously estimate the likelihood of RNA Polymerase II occupation as well as a model of the arrangement of read alignments relative to locations occupied by RNA Polymerase II. Both types of information are utilized to estimate the likelihood that RNA Polymerase II jointly occupies any two genomic locations. We apply Germ to RNA Polymerase II ChIA-PET data from embryonic stem cells to identify the genomic locations that are jointly occupied along with transcription start sites. We show that these genomic locations align more closely with features of active enhancers measured by ChIP-Seq than the locations identified using the ChIA-PET Tool. We also apply Germ to RNA Polymerase II ChIA-PET data from motor neuron progenitors. Based on the Germ results, we observe that a combination of cell type specific and cell type independent regulatory interactions are utilized by cells to regulate gene expression.National Institutes of Health (U.S.) (Grant 1U01HG007037

Cross-enhancement of ANGPTL4 transcription by HIF1 alpha and PPAR beta/delta is the result of the conformational proximity of two response elements

BACKGROUND: Synergistic transcriptional activation by different stimuli has been reported along with a diverse array of mechanisms, but the full scope of these mechanisms has yet to be elucidated. RESULTS: We present a detailed investigation of hypoxia-inducible factor (HIF) 1 dependent gene expression in endothelial cells which suggests the importance of crosstalk between the peroxisome proliferator-activated receptor (PPAR) β/δ and HIF signaling axes. A migration assay shows a synergistic interaction between these two stimuli, and we identify angiopoietin-like 4 (ANGPTL4) as a common target gene by using a combination of microarray and ChIP-seq analysis. We profile changes of histone marks at enhancers under hypoxia, PPARβ/δ agonist and dual stimulations and these suggest that the spatial proximity of two response elements is the principal cause of the synergistic transcription induction. A newly developed quantitative chromosome conformation capture assay shows the quantitative change of the frequency of proximity of the two response elements. CONCLUSIONS: To the best of our knowledge, this is the first report that two different transcription factors cooperate in transcriptional regulation in a synergistic fashion through conformational change of their common target genes

TNFα signals through specialized factories where responsive coding and miRNA genes are transcribed: Specialized transcription factories

Tumour necrosis factor alpha (TNFα) is a potent cytokine that signals through nuclear factor kappa B (NFκB) to activate a subset of human genes. It is usually assumed that this involves RNA polymerases transcribing responsive genes wherever they might be in the nucleus. Using primary human endothelial cells, variants of chromosome conformation capture (including 4C and chromatin interaction analysis with paired-end tag sequencing), and fluorescence in situ hybridization to detect single nascent transcripts, we show that TNFα induces responsive genes to congregate in discrete ‘NFκB factories'. Some factories further specialize in transcribing responsive genes encoding micro-RNAs that target downregulated mRNAs. We expect all signalling pathways to contain this extra leg, where responding genes are transcribed in analogous specialized factories

Recurrent Fusion Genes in Gastric Cancer: CLDN18-ARHGAP26 Induces Loss of Epithelial Integrity.

Genome rearrangements, a hallmark of cancer, can result in gene fusions with oncogenic properties. Using DNA paired-end-tag (DNA-PET) whole-genome sequencing, we analyzed 15 gastric cancers (GCs) from Southeast Asians. Rearrangements were enriched in open chromatin and shaped by chromatin structure. We identified seven rearrangement hot spots and 136 gene fusions. In three out of 100 GC cases, we found recurrent fusions between CLDN18, a tight junction gene, and ARHGAP26, a gene encoding a RHOA inhibitor. Epithelial cell lines expressing CLDN18-ARHGAP26 displayed a dramatic loss of epithelial phenotype and long protrusions indicative of epithelial-mesenchymal transition (EMT). Fusion-positive cell lines showed impaired barrier properties, reduced cell-cell and cell-extracellular matrix adhesion, retarded wound healing, and inhibition of RHOA. Gain of invasion was seen in cancer cell lines expressing the fusion. Thus, CLDN18-ARHGAP26 mediates epithelial disintegration, possibly leading to stomach H(+) leakage, and the fusion might contribute to invasiveness once a cell is transformed. Cell Rep 2015 Jul 14; 12(2):272-285

Direct evidence for pitavastatin induced chromatin structure change in the KLF4 gene in endothelial cells.

Statins exert atheroprotective effects through the induction of specific transcriptional factors in multiple organs. In endothelial cells, statin-dependent atheroprotective gene up-regulation is mediated by Kruppel-like factor (KLF) family transcription factors. To dissect the mechanism of gene regulation, we sought to determine molecular targets by performing microarray analyses of human umbilical vein endothelial cells (HUVECs) treated with pitavastatin, and KLF4 was determined to be the most highly induced gene. In addition, it was revealed that the atheroprotective genes induced with pitavastatin, such as nitric oxide synthase 3 (NOS3) and thrombomodulin (THBD), were suppressed by KLF4 knockdown. Myocyte enhancer factor-2 (MEF2) family activation is reported to be involved in pitavastatin-dependent KLF4 induction. We focused on MEF2C among the MEF2 family members and identified a novel functional MEF2C binding site 148 kb upstream of the KLF4 gene by chromatin immunoprecipitation along with deep sequencing (ChIP-seq) followed by luciferase assay. By applying whole genome and quantitative chromatin conformation analysis {chromatin interaction analysis with paired end tag sequencing (ChIA-PET), and real time chromosome conformation capture (3C) assay}, we observed that the MEF2C-bound enhancer and transcription start site (TSS) of KLF4 came into closer spatial proximity by pitavastatin treatment. 3D-Fluorescence in situ hybridization (FISH) imaging supported the conformational change in individual cells. Taken together, dynamic chromatin conformation change was shown to mediate pitavastatin-responsive gene induction in endothelial cells

Extensive Promoter-Centered Chromatin Interactions Provide a Topological Basis for Transcription Regulation

Higher-order chromosomal organization for transcription regulation is poorly understood in eukaryotes. Using genome-wide Chromatin Interaction Analysis with Paired-End-Tag sequencing (ChIAPET), we mapped long-range chromatin interactions associated with RNA polymerase II in human cells and uncovered widespread promoter-centered intragenic, extragenic, and intergenic interactions. These interactions further aggregated into higher-order clusters, wherein proximal and distal genes were engaged through promoter-promoter interactions. Most genes with promoter-promoter interactions were active and transcribed cooperatively, and some interacting promoters could influence each other implying combinatorial complexity of transcriptional controls. Comparative analyses of different cell lines showed that cell-specific chromatin interactions could provide structural frameworks for cell-specific transcription, and suggested significant enrichment of enhancer-promoter interactions for cell-specific functions. Furthermore, genetically-identified disease-associated noncoding elements were found to be spatially engaged with corresponding genes through long-range interactions. Overall, our study provides insights into transcription regulation by three-dimensional chromatin interactions for both housekeeping and cell-specific genes in human cells

Enrichment for enhancer associated marks is correlated with the number of TSSs with which a nonTSS location interacts.

<p>All nonTSS locations that are involved in an interaction with a TSS in at least one of the cell types were considered. The nonTSS locations were categorized based on the number of TSSs that they interact with in ESCs. RPKM values were computed from ChIP-Seq data in 1 kb windows centered on each nonTSS location. The boxplots reflect the distributions of RPKM values for the nonTSS locations in each group for each ChIP-Seq dataset.</p

A typical read spread function estimated from RNA PolII ChIA-PET data.

<p>A typical read spread function estimated from RNA PolII ChIA-PET data.</p

Enhancer usage reflects cell-type appropriate motif enrichment.

<p>1 kb windows centered on Med1 binding events involved in interactions with TSSs in one or both cell types were scanned for matches to known transcription factor motifs. Med1 binding events were categorized based on whether they interact with TSSs in one or both cell types. The bar graphs reflect the percentages of Med1 binding events in each group that have a motif match within 500 bp for several important transcription factors.</p