scholarly journals Algorithmic considerations when analysing capture Hi-C data

2020 ◽  
Vol 5 ◽  
pp. 289
Author(s):  
Linden Disney-Hogg ◽  
Ben Kinnersley ◽  
Richard Houlston
Keyword(s):  
Gene Regulation ◽  
Cell Lines ◽  
Chromosome Conformation Capture ◽  
Chromosome Conformation ◽  
Targeting Efficiency ◽  
Chromatin Interactions ◽  
Genomic Architecture ◽  
Insight Into ◽  
Recent Extension

Chromosome conformation capture methodologies have provided insight into the effect of 3D genomic architecture on gene regulation. Capture Hi-C (CHi-C) is a recent extension of Hi-C that improves the effective resolution of chromatin interactions by enriching for defined regions of biological relevance. The varying targeting efficiency between capture regions, however, introduces bias not present in conventional Hi-C, making analysis more complicated. Here we consider salient features of an algorithm that should be considered in evaluating the performance of a program used to analyse CHi-C data in order to infer meaningful interactions. We use the program CHICAGO to analyse promotor capture Hi-C data generated on 28 different cell lines as a case study.

scholarly journals SisterC: A novel 3C-technique to detect chromatin interactions between and along sister chromatids

2020 ◽  
Author(s):  
Marlies E. Oomen ◽  
Adam K. Hedger ◽  
Jonathan K. Watts ◽  
Job Dekker
Keyword(s):  
Cell Cycle ◽  
Single Strand ◽  
Chromosome Conformation Capture ◽  
Brdu Incorporation ◽  
Chromosome Conformation ◽  
Strand Breaks ◽  
Chromatin Interactions ◽  
Sister Chromatids ◽  
Single Strand Breaks ◽  
Capture Techniques

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.

scholarly journals Super-Resolution Microscopy of Chromatin

Genes ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 493 ◽  
Author(s):  
Birk
Keyword(s):  
Gene Regulation ◽  
Data Analysis ◽  
Super Resolution ◽  
Fluorescence Labeling ◽  
Cellular Processes ◽  
Direct Assessment ◽  
Chromatin Interactions ◽  
Resolution Imaging ◽  
Super Resolution Microscopy ◽  
Insight Into

Since the advent of super-resolution microscopy, countless approaches and studies have been published contributing significantly to our understanding of cellular processes. With the aid of chromatin-specific fluorescence labeling techniques, we are gaining increasing insight into gene regulation and chromatin organization. Combined with super-resolution imaging and data analysis, these labeling techniques enable direct assessment not only of chromatin interactions but also of the function of specific chromatin conformational states.

A T-Cell Specific Element Activates the TAL1 Oncogene Via an Interchromosomal Interaction During Leukemogenesis

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 3507-3507
Author(s):  
Yuanyuan Kang ◽  
Bhavita Patel ◽  
Kairong Cui ◽  
Keji Zhao ◽  
Yi Qiu ◽  
...  
Keyword(s):  
T Cells ◽  
Transcription Factor ◽  
T Cell ◽  
Cell Lines ◽  
Cd4 T Cells ◽  
K562 Cells ◽  
Chromosome Conformation Capture ◽  
Luciferase Reporter ◽  
Erythroid Progenitor ◽  
Chromosome Conformation

Abstract Abstract 3507 T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive malignant disease of thymocytes that mainly affects children and has very poor prognosis with high rates of relapse. A prominent feature observed in 60% of T-ALL childhood patients is the ectopic expression of a key hematopoietic transcription factor TAL1/SCL. Although several enhancers has been identified to play an important role in normal hematopoietic differentiation, the histone modification patterns and chromatin organization over the whole TAL1 locus reveled that none of them is active in T-ALL cell lines such as Jurkat and Rex cells. It remains currently unknown how TAL1 is activated in the majority of T-ALL patients lacking the TAL1 locus rearrangements. To understand the molecular mechanism underlying regulation of the TAL1 oncogene in leukemic T-cells, we employed circularized chromosome conformation capture (4C) methodology to identify new regulatory elements that activate TAL1 specifically in T-ALL leukemia. Using the TAL1 promoter 1a as the bait, we discovered that the TAL1 promoter 1a interacts with the TIL16 element (TAL1 interacting locus in chromosome 16) that is located at ∼15 Kb downstream of T-cell specific CD2BP2 gene in T-ALL cell line Jurkat, but not in erythroid progenitor K562 cells. The CD2BP2 protein is a cellular adapter protein that was originally identified as a binding partner of the T cell adhesion protein CD2 in the context of T cell signaling. The TIL16 element contains the bind sites for several transcription factors that are important for hematopoiesis such as C-Maf, Pax5, HoxA7 and USF2. The inter-chromosomal interaction between the TIL16 and the TAL1 promoter 1a was further confirmed by chromosome conformation capture (3C) assay in three TAL1 over-expressing T-ALL cell lines, Jurkat, REX and Molt4, but not in K562 cells. Recent genome wide study has correlates H3K4 mono- or dimethyl marks with distal enhancers while trimethyl H3K4 is enriched in promoters of active genes. To further test if the TIL16 acts as T-cell specific enhancer for TAL1 activation in T-ALL cells, we carried out ChIP-seq and ChIP analysis in CD4 T cells, Jurkat, and K562 cells. We found that the TIL16 element is specifically marked by H3K4me1 in Jurkat and CD4+ T-cells but not in K562 cells. The enrichment of H3K4me1 is correlated with the binding of c-Maf, a T-cell specific transcription factor. To further test whether the TIL16 element contributes to transcription activity, a DNA fragments containing the TIL16 element were cloneed into SV40 minimal promoter driven luciferase reporter and introduced into K562 and several T-ALL cell lines. Compared to the pGL3-SV40 vector that showed only minimal luciferase activity, the 1 Kb TIL element specifically activated transcription of the luciferase reporter in T-ALL cells, but not in erythroid progenitor K562 cells suggesting that the TIL16 element functions as a T-cell specific TAL1 enhancer. Thus, our data revealed a novel epigenetic mechanism by which the TAL1 oncogene is ectopically activated in T-cell leukemia. Disclosures: No relevant conflicts of interest to declare.

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

2019 ◽  
Author(s):  
Pavel P. Kuksa ◽  
Alexandre Amlie-Wolf ◽  
Yih-Chii Hwang ◽  
Otto Valladares ◽  
Brian D. Gregory ◽  
...  
Keyword(s):  
High Resolution ◽  
Cell Line ◽  
Cell Lines ◽  
Dna Looping ◽  
Open Chromatin ◽  
Fine Scale ◽  
Long Distance ◽  
Chromosome Conformation ◽  
Chromatin Interactions ◽  
Distance Regulation

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.

scholarly journals Analysis of long-range chromatin interactions using Chromosome Conformation Capture

Methods ◽  
2012 ◽  
Vol 58 (3) ◽  
pp. 192-203 ◽  
Author(s):  
Natalia Naumova ◽  
Emily M. Smith ◽  
Ye Zhan ◽  
Job Dekker
Keyword(s):  
Long Range ◽  
Chromosome Conformation Capture ◽  
Chromosome Conformation ◽  
Chromatin Interactions

scholarly journals The interdependent nature of multi-loci associations can be revealed by 4C-Seq

2015 ◽  
Author(s):  
Tingting Jiang ◽  
Ramya Raviram ◽  
Pedro P Rocha ◽  
Valentina Snetkova ◽  
Charlotte Proudhon ◽  
...  
Keyword(s):  
Gene Regulation ◽  
Population Based ◽  
Data Sets ◽  
Low Resolution ◽  
Chromosome Conformation ◽  
Chromatin Interactions ◽  
Pairwise Interactions ◽  
Capture Techniques ◽  
Transcriptional Output ◽  
Resolution Single

Use of low resolution single cell DNA FISH and population based high resolution chromosome conformation capture techniques have highlighted the importance of pairwise chromatin interactions in gene regulation. However, it is unlikely that these associations act in isolation of other interacting partners within the genome. Indeed, the influence of multi-loci interactions in gene control remains something of an enigma as beyond low-resolution DNA FISH we do not have the appropriate tools to analyze these. Here we present a method that uses standard 4C-seq data to identify multi-loci interactions from the same cell. We demonstrate the feasibility of our method using 4C-seq data sets that identify known pairwise interactions involving the Tcrb and Igk antigen receptor enhancers, in addition to novel tri-loci associations. We further show that enhancer deletions not only interfere with tri-loci interactions in which they participate, but they also disrupt pairwise interactions between other partner enhancers and this disruption is linked to a reduction in their transcriptional output. These findings underscore the functional importance of hubs and provide new insight into chromatin organization as a whole. Our method opens the door for studying multi-loci interactions and their impact on gene regulation in other biological settings.

scholarly journals Integrative analyses of multi-tissue Hi-C and eQTL data demonstrate close spatial proximity between eQTLs and their target genes

2018 ◽  
Author(s):  
Jingting Yu ◽  
Ming Hu ◽  
Chun Li
Keyword(s):  
Gene Regulation ◽  
Cell Lines ◽  
Quantitative Trait ◽  
Target Genes ◽  
Chromatin Interaction ◽  
Interaction Frequency ◽  
Tissue Specific ◽  
Chromatin Interactions ◽  
Integrative Analyses ◽  
Detailed Picture

AbstractGene regulation is important for cells and tissues to function. At the genomic level, it has been studied from two aspects, the identification of expression quantitative trait loci (eQTLs) and identification of long-range chromatin interactions. It is important to understand their relationship, such as whether eQTLs regulate their target genes through physical chromatin interaction. Although previous studies have suggested enrichment of eQTLs in regions with a high chromatin interaction frequency, it is unclear whether this relationship is consistent across different tissues and cell lines and whether there would be any tissue-specific patterns. Here, we performed integrative analyses of eQTL and high-throughput chromatin conformation capture (Hi-C) data from 11 human primary tissue types and 2 human cell lines. We found that chromatin interaction frequency is positively correlated with the number of genes having eQTLs, and eQTLs and their target genes are more likely to fall in the same topologically associating domains than that expected from randomly generated control datasets. These results are consistent across all tissues and cell lines we evaluated. Moreover, in dorsolateral prefrontal cortex, spleen, hippocampus, pancreas and aorta, tissue-specific eQTLs are enriched in tissue-specific frequently interacting regions. These results reveal a more detailed picture of the complicated relationship between different mechanisms of gene regulation.Author summaryWhole-genome gene regulation has been studied in tissues and cell lines from multiple perspectives, including identification of expression quantitative trait loci (eQTLs) and identification of long-range chromatin interactions. These two complementary approaches focus on different aspects of gene regulation, one being statistical across individuals while the other being physical within a sample. Integrating results from these two approaches will help us understand their relationships, such as whether eQTLs regulate their target genes through physical chromatin interaction. We performed comprehensive analyses using data from multiple human tissues and cell lines, and showed that chromatin interaction frequency is positively associated with eQTL results in all evaluated tissues and cell lines. The observed relationships also displayed tissue-specific pattern in some tissues. Our results revealed a more detailed picture of the complicated relationship between the different mechanisms of gene regulation.

scholarly journals Studying physical chromatin interactions in plants using Chromosome Conformation Capture (3C)

2009 ◽  
Vol 4 (8) ◽  
pp. 1216-1229 ◽  
Author(s):  
Marieke Louwers ◽  
Erik Splinter ◽  
Roel van Driel ◽  
Wouter de Laat ◽  
Maike Stam
Keyword(s):  
Chromosome Conformation Capture ◽  
Chromosome Conformation ◽  
Chromatin Interactions

scholarly journals 7C: Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Jonas Ibn-Salem ◽  
Miguel A. Andrade-Navarro
Keyword(s):  
Three Dimensional ◽  
Prediction Method ◽  
Cell Types ◽  
Chromosome Conformation Capture ◽  
Dimensional Structure ◽  
Single Chip ◽  
Chromosome Conformation ◽  
Chromatin Looping ◽  
Chromatin Interactions ◽  
Cross Links

Abstract Background Knowledge of the three-dimensional structure of the genome is necessary to understand how gene expression is regulated. Recent experimental techniques such as Hi-C or ChIA-PET measure long-range chromatin interactions genome-wide but are experimentally elaborate, have limited resolution and such data is only available for a limited number of cell types and tissues. Results While ChIP-seq was not designed to detect chromatin interactions, the formaldehyde treatment in the ChIP-seq protocol cross-links proteins with each other and with DNA. Consequently, also regions that are not directly bound by the targeted TF but interact with the binding site via chromatin looping are co-immunoprecipitated and sequenced. This produces minor ChIP-seq signals at loop anchor regions close to the directly bound site. We use the position and shape of ChIP-seq signals around CTCF motif pairs to predict whether they interact or not. We implemented this approach in a prediction method, termed Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs (7C). We applied 7C to all CTCF motif pairs within 1 Mb in the human genome and validated predicted interactions with high-resolution Hi-C and ChIA-PET. A single ChIP-seq experiment from known architectural proteins (CTCF, Rad21, Znf143) but also from other TFs (like TRIM22 or RUNX3) predicts loops accurately. Importantly, 7C predicts loops in cell types and for TF ChIP-seq datasets not used in training. Conclusion 7C predicts chromatin loops which can help to associate TF binding sites to regulated genes. Furthermore, profiling of hundreds of ChIP-seq datasets results in novel candidate factors functionally involved in chromatin looping. Our method is available as an R/Bioconductor package: http://bioconductor.org/packages/sevenC.

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