High-throughput identification of long-range regulatory elements and their target promoters in the human genome

Hwang, Yi‐Ting; Zheng, Qi; Wang, Li-San

doi:10.1093/nar/gkt188

Cited by 25 publications

(14 citation statements)

References 48 publications

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“…By comparing against samples of length-matched background intervals (Methods), we found that the PIRs involved in significant interactions were enriched for overlaps with all of the active epigenomic marks in every cell line except for NHEK, where PIRs were depleted of overlaps with all annotations except H3K4me3 ( Figure 5b ). The repressive mark H3K27me3 had the smallest average enrichment (40.75%) across cell lines, suggesting that significant PIR interactions are associated with active regulatory elements (Hwang et al, 2013; Rao et al, 2014), which showed much stronger enrichments.…”

Section: Resultsmentioning

confidence: 99%

HIPPIE2: a method for fine-scale identification of physically interacting chromatin regions

Kuksa

Amlie‐Wolf

Hwang

et al. 2019

Preprint

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AbstractMost regulatory chromatin interactions are mediated by various transcription factors (TFs) and involve physically-interacting elements such as enhancers, insulators, or promoters. To map these elements and interactions, we developed HIPPIE2 which analyzes raw reads from high-throughput chromosome conformation (Hi-C) experiments to identify fine-scale physically-interacting regions (PIRs). Unlike standard genome binning approaches (e.g., 10K-1Mbp bins), HIPPIE2 dynamically calls physical locations of PIRs with better precision and higher resolution based on the pattern of restriction events and relative locations of interacting sites inferred from the sequencing readout.We applied HIPPIE2 to in situ Hi-C datasets across 6 human cell lines (GM12878, IMR90, K562, HMEC, HUVEC, NHEK) with matched ENCODE and Roadmap functional genomic data. HIPPIE2 detected 1,042,738 distinct PIRs across cell lines, with high resolution (average PIR length of 1,006bps) and high reproducibility (92.3% in GM12878 replicates). 32.8% of PIRs were shared among cell lines. PIRs are enriched for epigenetic marks (H3K27ac, H3K4me1) and open chromatin, suggesting active regulatory roles. HIPPIE2 identified 2.8M significant intrachromosomal PIR–PIR interactions, 27.2% of which were enriched for TF binding sites. 50,608 interactions were enhancer–promoter interactions and were enriched for 33 TFs (31 in enhancers/29 in promoters), several of which are known to mediate DNA looping/long-distance regulation. 29 TFs were enriched in >1 cell line and 4 were cell line-specific. These findings demonstrate that the dynamic approach used in HIPPIE2 (https://bitbucket.com/wanglab-upenn/HIPPIE2) characterizes PIR–PIR interactions with high resolution and reproducibility.

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Section: Resultsmentioning

confidence: 99%

HIPPIE2: a method for fine-scale identification of physically interacting chromatin regions

Kuksa

Amlie‐Wolf

Hwang

et al. 2019

Preprint

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“…The rs71372224 SNP was however found to occur within the three overlapping binding sites for transcription factors p300 , c-Fos and c-Jun. Recent studies [30] have shown that enhancer elements have a high propensity to be bound by p300 , an enhancer-binding transcription factor. One may therefore speculate that a mutation in this putative enhancer element could influence the expression of the NF1 gene in a spatially specific manner.…”

Section: Resultsmentioning

confidence: 99%

Screening in silico predicted remotely acting NF1gene regulatory elements for mutations in patients with neurofibromatosis type 1

et al. 2013

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Neurofibromatosis type 1 (NF1), a neuroectodermal disorder, is caused by germline mutations in the NF1 gene. NF1 affects approximately 1/3,000 individuals worldwide, with about 50% of cases representing de novo mutations. Although the NF1 gene was identified in 1990, the underlying gene mutations still remain undetected in a small but obdurate minority of NF1 patients. We postulated that in these patients, hitherto undetected pathogenic mutations might occur in regulatory elements far upstream of the NF1 gene. In an attempt to identify such remotely acting regulatory elements, we reasoned that some of them might reside within DNA sequences that (1) have the potential to interact at distance with the NF1 gene and (2) lie within a histone H3K27ac-enriched region, a characteristic of active enhancers. Combining Hi-C data, obtained by means of the chromosome conformation capture technique, with data on the location and level of histone H3K27ac enrichment upstream of the NF1 gene, we predicted in silico the presence of two remotely acting regulatory regions, located, respectively, approximately 600 kb and approximately 42 kb upstream of the NF1 gene. These regions were then sequenced in 47 NF1 patients in whom no mutations had been found in either the NF1 or SPRED1 gene regions. Five patients were found to harbour DNA sequence variants in the distal H3K27ac-enriched region. Although these variants are of uncertain pathological significance and still remain to be functionally characterized, this approach promises to be of general utility for the detection of mutations underlying other inherited disorders that may be caused by mutations in remotely acting regulatory elements.

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“…One recent method used a geometric distribution- based model to form hotspots (or clusters) of adjacent Hi-C reads that represent potential sites of DNA–DNA interaction [98]. This first step was done without any consideration of read pairing that provides connection in Hi-C. Next interaction hotspots are extended by ~3 kb to account for Hi-C reads being enriched at the cut sites of the restriction enzymes used in the assay.…”

Section: Identifying the Location Of Enhancersmentioning

confidence: 99%

Computational schemes for the prediction and annotation of enhancers from epigenomic assays

Whitaker

Nguyen

Zhu

et al. 2015

Methods

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Identifying and annotating distal regulatory enhancers is critical to understand the mechanisms that control gene expression and cell-type-specific activities. Next-generation sequencing techniques have provided us an exciting toolkit of genome-wide assays that can be used to predict and annotate enhancers. However, each assay comes with its own specific set of analytical needs if enhancer prediction is to be optimal. Furthermore, integration of multiple genome-wide assays allows for different genomic features to be combined, and can improve predictive performance. Herein, we review the genome-wide assays and analysis schemes that are used to predict and annotate enhancers. In particular, we focus on three key computational topics: predicting enhancer locations, determining the cell-type-specific activity of enhancers, and linking enhancers to their target genes.

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High-throughput identification of long-range regulatory elements and their target promoters in the human genome

Cited by 25 publications

References 48 publications

HIPPIE2: a method for fine-scale identification of physically interacting chromatin regions

HIPPIE2: a method for fine-scale identification of physically interacting chromatin regions

Screening in silico predicted remotely acting NF1gene regulatory elements for mutations in patients with neurofibromatosis type 1

Computational schemes for the prediction and annotation of enhancers from epigenomic assays

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