scholarly journals Making New Connections—Chromosome Conformation Capture for Identification of Disease-Associated Target Genes

2019 ◽  
Vol 139 (3) ◽  
pp. 514-517
Author(s):  
Matthew T. Patrick ◽  
Lam C. Tsoi ◽  
Johann E. Gudjonsson
Keyword(s):  
Target Genes ◽  
Chromosome Conformation Capture ◽  
Chromosome Conformation

scholarly journals The DLO Hi-C Tool for Digestion-Ligation-Only Hi-C Chromosome Conformation Capture Data Analysis

Genes ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 289 ◽  
Author(s):  
Ping Hong ◽  
Hao Jiang ◽  
Weize Xu ◽  
Da Lin ◽  
Qian Xu ◽  
...  
Keyword(s):  
Target Genes ◽  
High Efficiency ◽  
New Technology ◽  
Three Dimensional ◽  
Large Data ◽  
Regulatory Elements ◽  
Chromosome Conformation Capture ◽  
Genome Chromosome ◽  
Chromosome Conformation ◽  
3D Genome

It is becoming increasingly important to understand the mechanism of regulatory elements on target genes in long-range genomic distance. 3C (chromosome conformation capture) and its derived methods are now widely applied to investigate three-dimensional (3D) genome organizations and gene regulation. Digestion-ligation-only Hi-C (DLO Hi-C) is a new technology with high efficiency and cost-effectiveness for whole-genome chromosome conformation capture. Here, we introduce the DLO Hi-C tool, a flexible and versatile pipeline for processing DLO Hi-C data from raw sequencing reads to normalized contact maps and for providing quality controls for different steps. It includes more efficient iterative mapping and linker filtering. We applied the DLO Hi-C tool to different DLO Hi-C datasets and demonstrated its ability in processing large data with multithreading. The DLO Hi-C tool is suitable for processing DLO Hi-C and in situ DLO Hi-C datasets. It is convenient and efficient for DLO Hi-C data processing.

scholarly journals DLO Hi-C Tool for Digestion-Ligation-Only Hi-C Chromosome Conformation Capture Data Analysis

2019 ◽  
Author(s):  
Ping Hong ◽  
Hao Jiang ◽  
Weize Xu ◽  
Da Lin ◽  
Qian Xu ◽  
...  
Keyword(s):  
Target Genes ◽  
High Efficiency ◽  
New Technology ◽  
Large Data ◽  
Regulatory Elements ◽  
Chromosome Conformation Capture ◽  
Genome Chromosome ◽  
Chromosome Conformation ◽  
Effective Cost

AbstractBackgroundIt is becoming increasingly important to understand the mechanism of regulatory elements on target genes in long-range genomic distance. 3C (Chromosome Conformation Capture) and its derived methods are now widely applied to investigate genome organizations and gene regulation. Digestion-Ligation-Only Hi-C (DLO Hi-C) is a new technology with high efficiency and effective cost for whole-genome chromosome conformation capture.ResultsHere, we introduce DLO Hi-C Tool, a flexible and versatile pipeline for processing DLO Hi-C data from raw sequencing reads to normalized contact maps and providing quality controls for different steps. It includes more efficient iterative mapping and linker filtering. We applied DLO Hi-C Tool to different DLO Hi-C datasets, and demonstrated its ability of processing large data in multi-threading.ConclusionsDLO Hi-C Tool is suitable for processing DLO Hi-C and in situ DLO Hi-C datasets. It is convenient and efficient for DLO Hi-C data processing.

scholarly journals Closed and High-Quality Bacterial Genome Sequences of the Oligo-Mouse-Microbiota Community

2021 ◽  
Vol 10 (17) ◽  
Author(s):  
Quentin Lamy-Besnier ◽  
Romain Koszul ◽  
Laurent Debarbieux ◽  
Martial Marbouty
Keyword(s):  
Murine Model ◽  
Bacterial Genome ◽  
Chromosome Conformation Capture ◽  
Genome Sequences ◽  
Pacbio Sequencing ◽  
High Quality ◽  
Chromosome Conformation

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.

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 A streamlined tethered chromosome conformation capture protocol

BMC Genomics ◽  
2016 ◽  
Vol 17 (1) ◽  
Author(s):  
Idan Gabdank ◽  
Sreejith Ramakrishnan ◽  
Anne M. Villeneuve ◽  
Andrew Z. Fire
Keyword(s):  
Chromosome Conformation Capture ◽  
Chromosome Conformation

scholarly journals FAN-C: a feature-rich framework for the analysis and visualisation of chromosome conformation capture data

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Kai Kruse ◽  
Clemens B. Hug ◽  
Juan M. Vaquerizas
Keyword(s):  
Chromosome Conformation Capture ◽  
Matrix Analysis ◽  
Set Covering ◽  
Command Line ◽  
Chromosome Conformation ◽  
C Storage ◽  
Data Formats ◽  
Analysis Tools ◽  
Command Line Tool ◽  
Broad Feature

AbstractChromosome conformation capture data, particularly from high-throughput approaches such as Hi-C, are typically very complex to analyse. Existing analysis tools are often single-purpose, or limited in compatibility to a small number of data formats, frequently making Hi-C analyses tedious and time-consuming. Here, we present FAN-C, an easy-to-use command-line tool and powerful Python API with a broad feature set covering matrix generation, analysis, and visualisation for C-like data (https://github.com/vaquerizaslab/fanc). Due to its compatibility with the most prevalent Hi-C storage formats, FAN-C can be used in combination with a large number of existing analysis tools, thus greatly simplifying Hi-C matrix analysis.

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