scholarly journals Mapping Cis- and Trans- Chromatin Interaction Networks Using Chromosome Conformation Capture (3C)

Author(s):  
Adriana Miele ◽  
Job Dekker
2020 ◽  
Author(s):  
Betul Akgol Oksuz ◽  
Liyan Yang ◽  
Sameer Abraham ◽  
Sergey V. Venev ◽  
Nils Krietenstein ◽  
...  

AbstractChromosome conformation capture (3C)-based assays are used to map chromatin interactions genome-wide. Quantitative analyses of chromatin interaction maps can lead to insights into the spatial organization of chromosomes and the mechanisms by which they fold. A number of protocols such as in situ Hi-C and Micro-C are now widely used and these differ in key experimental parameters including cross-linking chemistry and chromatin fragmentation strategy. To understand how the choice of experimental protocol determines the ability to detect and quantify aspects of chromosome folding we have performed a systematic evaluation of experimental parameters of 3C-based protocols. We find that different protocols capture different 3D genome features with different efficiencies. First, the use of cross-linkers such as DSG in addition to formaldehyde improves signal-to-noise allowing detection of thousands of additional loops and strengthens the compartment signal. Second, fragmenting chromatin to the level of nucleosomes using MNase allows detection of more loops. On the other hand, protocols that generate larger multi-kb fragments produce stronger compartmentalization signals. We confirmed our results for multiple cell types and cell cycle stages. We find that cell type-specific quantitative differences in chromosome folding are not detected or underestimated by some protocols. Based on these insights we developed Hi-C 3.0, a single protocol that can be used to both efficiently detect chromatin loops and to quantify compartmentalization. Finally, this study produced ultra-deeply sequenced reference interaction maps using conventional Hi-C, Micro-C and Hi-C 3.0 for commonly used cell lines in the 4D Nucleome Project.


2016 ◽  
Author(s):  
Hui Zhang ◽  
Feifei Li ◽  
Yan Jia ◽  
Bingxiang Xu ◽  
Yiqun Zhang ◽  
...  

AbstractHigh-throughput chromosome conformation capture technologies, such as Hi-C, have made it possible to survey 3D genome structure. However, the ability to obtain 3D profiles at kilobase resolution at low cost remains a major challenge. Therefore, we herein report a computational method to precisely identify chromatin interaction sites at kilobase resolution from MNase-seq data, termed chromatin interaction site detector (CISD), and a CISD-based chromatin loop predictor (CISD_loop) that predicts chromatin-chromatin interaction (CCI) from low-resolution Hi-C data. The methods are built on a hypothesis that CCIs result in a characteristic nucleosome arrangement pattern flanking the interaction sites. Accordingly, we show that the predictions of CISD and CISD_loop overlap closely with chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) anchors and loops, respectively. Moreover, the methods trained in one cell type can be applied to other cell types with high accuracy. The validity of the methods was further supported by chromosome conformation capture (3C) experiments at 5kb resolution. Finally, we demonstrate that only modest amounts of MNase-seq and Hi-C data are sufficient to achieve ultrahigh resolution CCI map. The predictive power of CISD/CISD_loop supports the hypothesis that CCIs induce local nucleosome rearrangement and that the pattern may serve as probes for 3D dynamics of the genome. Thus, our method will facilitate precise and systematic investigations of the interactions between distal regulatory elements on a larger scale than hitherto have been possible.


Methods ◽  
2020 ◽  
Vol 170 ◽  
pp. 4-16 ◽  
Author(s):  
Surabhi Chowdhary ◽  
Amoldeep S. Kainth ◽  
David S. Gross

2019 ◽  
Author(s):  
Yizhou Zhu ◽  
Yousin Suh

AbstractThe resolution limit of chromatin conformation capture methodologies (3Cs) has restrained their application in detection of fine-level chromatin structure mediated by cis-regulatory elements (CREs). Here we report two 3C-derived methods, Tri-4C and Tri-HiC, which utilize mult-restriction enzyme digestions for ultrafine mapping of targeted and genome-wide chromatin interaction, respectively, at up to one hundred basepair resolution. Tri-4C identified CRE loop interaction networks and quantifatively revealed their alterations underlying dynamic gene control. Tri-HiC uncovered global fine-gage regulatory interaction networks, identifying > 20-fold more enhancer:promoter (E:P) loops than in situ HiC. In addition to vasly improved identification of subkilobase-sized E:P loops, Tri-HiC also uncovered interaction stripes and contact domain insulation from promoters and enhancers, revealing their loop extrusion behaviors resembling the topologically-associated domain (TAD) boundaries. Tri-4C and Tri-HiC provide robust approaches to achieve the high resolution interactome maps required for characterizing fine-gage regulatory chromatin interactions in analysis of development, homeostasis and disease.


2021 ◽  
Vol 10 (17) ◽  
Author(s):  
Quentin Lamy-Besnier ◽  
Romain Koszul ◽  
Laurent Debarbieux ◽  
Martial Marbouty

ABSTRACT The Oligo-Mouse-Microbiota (OMM12) gnotobiotic murine model is an increasingly popular model in microbiota studies. However, following Illumina and PacBio sequencing, the genomes of the 12 strains could not be closed. Here, we used genomic chromosome conformation capture (Hi-C) data to reorganize, close, and improve the quality of these 12 genomes.


2020 ◽  
Author(s):  
Marlies E. Oomen ◽  
Adam K. Hedger ◽  
Jonathan K. Watts ◽  
Job Dekker

Abstract Current chromosome conformation capture techniques are not able to distinguish sister chromatids. Here we describe the protocol of SisterC1: a novel Hi-C technique that leverages BrdU incorporation and UV/Hoechst-induced single strand breaks to identify interactions along and between sister chromatids. By synchronizing cells, BrdU is incorporated only on the newly replicated strand, which distinguishes the two sister chromatids2,3. This is followed by Hi-C4 of cells that can be arrested in different stages of the cell cycle, e.g. in mitosis. Before final amplification of the Hi-C library, strands containing BrdU are specifically depleted by UV/Hoechst treatment. SisterC libraries are then sequenced using 50bp paired end reads, followed by mapping using standard Hi-C processing tools. Interactions can then be assigned as inter- or intra-sister interactions based on read orientation.


2021 ◽  
Author(s):  
Alireza Karbalayghareh ◽  
Merve Sahin ◽  
Christina S Leslie

Linking distal enhancers to genes and modeling their impact on target gene expression are longstanding unresolved problems in regulatory genomics and critical for interpreting non-coding genetic variation. Here we present a new deep learning approach called GraphReg that exploits 3D interactions from chromosome conformation capture assays in order to predict gene expression from 1D epigenomic data or genomic DNA sequence. By using graph attention networks to exploit the connectivity of distal elements and promoters, GraphReg more faithfully models gene regulation and more accurately predicts gene expression levels than dilated convolutional neural networks (CNNs), the current state-of-the-art deep learning approach for this task. Feature attribution used with GraphReg accurately identifies functional enhancers of genes, as validated by CRISPRi-FlowFISH and TAP-seq assays, outperforming both CNNs and the recently proposed Activity-by-Contact model. GraphReg therefore represents an important advance in modeling the regulatory impact of epigenomic and sequence elements.


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