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Robust Hi-C maps of enhancer-promoter interactions reveal the function of non-coding genome in neural development and diseases

ABSTRACT: Robust Hi-C maps of enhancer-promoter interactions reveal the function of non-coding genome in neural development and diseases

PROVIDER: PRJNA480299 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR7501060_1.fastq.gz	Fastqsanger.gz
	SRR7501060_2.fastq.gz	Fastqsanger.gz
	SRR7501070_1.fastq.gz	Fastqsanger.gz
	SRR7501070_2.fastq.gz	Fastqsanger.gz
	SRR7501080_1.fastq.gz	Fastqsanger.gz

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Robust Hi-C maps of enhancer-promoter interactions reveal the function of non-coding genome in neural development and diseases

Project description:Genome-wide mapping of chromatin interactions at high resolution remains experimentally and computationally challenging. Here we used a low-input “easy Hi-C” protocol to map the 3D genome architecture in human neurogenesis and brain tissues and also demonstrated that a rigorous Hi-C bias-correction pipeline (HiCorr) can significantly improve the sensitivity and robustness of Hi-C loop identification at sub-TAD level, especially the enhancer-promoter (E-P) interactions. We used HiCorr to compare the high-resolution maps of chromatin interactions from 10 tissue or cell types with a focus on neurogenesis and brain tissues. We found that dynamic chromatin loops are better hallmarks for cellular differentiation than compartment switching. HiCorr allowed direct observation of cell-type- and differentiation-specific E-P aggregates spanning large neighborhoods, suggesting a mechanism that stabilizes enhancer contacts during development. Interestingly, we concluded that Hi-C loop outperforms eQTL in explaining neurological GWAS results, revealing a unique value of high-resolution 3D genome maps in elucidating the disease etiology.

2020-07-31 | GSE116825 | GEO

Robust Hi-C maps of enhancer-promoter interactions reveal the function of non-coding genome in neural development and diseases

Project description:Robust Hi-C maps of enhancer-promoter interactions reveal the function of non-coding genome in neural development and diseases

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Robust Hi-C maps of enhancer-promoter interactions reveal the function of non-coding genome in neural development and diseases

Project description:Despite recent progress in mammalian 3D genome studies, it remains experimentally and computationally challenging to identify chromatin interactions genome-wide. Here we developed a highly efficient “easy Hi-C” (eHi-C) protocol that generates high-yield libraries with 0.1 million cells. After rigorous bias-correction with a significantly improved Hi-C analysis pipeline, we can directly recognize the dynamic long- and short-range chromatin loops from contact heatmaps. We compared 10 ultra-deep Hi-C or eHi-C datasets (billion- read scale) from human tissue- or cell types focusing on brain and neurogenesis. We found that H3K9me3 marks a 3D genome compartmental barrier for induced pluripotency. Dynamic chromatin loops, but not genome compartments, are hallmarks of neuronal differentiation and neuron-related diseases. Interestingly, we observed many neuron-specific enhancer-promoter looping clusters spanning Mb-scale neighborhoods, supporting a phase-separation model leading to enhancer aggregation during brain development. Taken together, our 3D genome analyses shed light on the regulation of brain development and complex neuronal diseases.

2020-06-26 | GSE115407 | GEO

Robust Hi-C Maps of Enhancer-Promoter Interactions Reveal the Function of Non-coding Genome in Neural Development and Diseases.

Project description:Genome-wide mapping of chromatin interactions at high resolution remains experimentally and computationally challenging. Here we used a low-input "easy Hi-C" protocol to map the 3D genome architecture in human neurogenesis and brain tissues and also demonstrated that a rigorous Hi-C bias-correction pipeline (HiCorr) can significantly improve the sensitivity and robustness of Hi-C loop identification at sub-TAD level, especially the enhancer-promoter (E-P) interactions. We used HiCorr to compare the high-resolution maps of chromatin interactions from 10 tissue or cell types with a focus on neurogenesis and brain tissues. We found that dynamic chromatin loops are better hallmarks for cellular differentiation than compartment switching. HiCorr allowed direct observation of cell-type- and differentiation-specific E-P aggregates spanning large neighborhoods, suggesting a mechanism that stabilizes enhancer contacts during development. Interestingly, we concluded that Hi-C loop outperforms eQTL in explaining neurological GWAS results, revealing a unique value of high-resolution 3D genome maps in elucidating the disease etiology.

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Project description:Capture Hi-C (CHi-C) is a state-of-the art method for profiling chromosomal interactions involving targeted regions of interest (such as gene promoters) globally and at high resolution. Signal detection in CHi-C data involves a number of statistical challenges that are not observed when using other Hi-C-like techniques. We present a background model, and algorithms for normalisation and multiple testing that are specifically adapted to CHi-C experiments, in which many spatially dispersed regions are captured, such as in Promoter CHi-C. We implement these procedures in CHiCAGO (http://regulatorygenomicsgroup.org/chicago), an open-source package for robust interaction detection in CHi-C. We validate CHiCAGO by showing that promoter-interacting regions detected with this method are enriched for regulatory features and disease-associated SNPs. Three human CHi-C biological replicates were generated (comprising 1, 2and 3 technical replicates). Two mouse CHi-C biological replicates were generated (both comprising three technical replicates) and a mouse Hi-C dataset. The publicly available HiCUP pipeline (doi: 10.12688/f1000research.7334.1) was used to process the raw sequencing reads. This pipeline was used to map the read pairs against the mouse (mm9) and human (hg19) genomes, to filter experimental artefacts (such as circularized reads and re-ligations), and to remove duplicate reads. For the CHi-C data, the resulting BAM files were processed into CHiCAGO input files, retaining only those read pairs that mapped, at least on one end, to a captured bait. CHiCAGO then identified Hi-C restriction fragments interacting, with statistical significant, to captured baits.

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Hi-C and Capture Hi-C maps in WT and Zfp661 knockout mESCs

Project description:In this assay, we aimed to investigate the impacts of ZFP661 on the permeability of CTCF barriers to chromatin interactions. To achieve this, we generated high-resolution Hi-C maps using WT and Zfp661 knockout (KO) mESCs. Our findings demonstrate that ZFP661 suppresses the trapping of cohesin at the CTCF barriers and modulates their permeability.

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