Project description:Chemical cross-linking and DNA sequencing have revealed regions of intra-chromosomal interaction, referred to as topologically associating domains (TADs), interspersed with regions of little or no interaction, in interphase nuclei. We find that TADs and the regions between them correspond with the bands and interbands of polytene chromosomes of Drosophila. We further establish the conservation of TADs between polytene and diploid cells of Drosophila. From direct measurements on light micrographs of polytene chromosomes, we then deduce the states of chromatin folding in the diploid cell nucleus. Two states of folding, fully extended fibers containing regulatory regions and promoters, and fibers condensed up to 10-fold containing coding regions of active genes, constitute the euchromatin of the nuclear interior. Chromatin fibers condensed up to 30-fold, containing coding regions of inactive genes, represent the heterochromatin of the nuclear periphery. A convergence of molecular analysis with direct observation thus reveals the architecture of interphase chromosomes.
Project description:SummaryComplementary advances in genomic technology and public data resources have created opportunities for researchers to conduct multifaceted examination of the genome on a large scale. To meet the need for integrative genome wide exploration, we present epiTAD. This web-based tool enables researchers to compare genomic 3D organization and annotations across multiple databases in an interactive manner to facilitate in silico discovery.Availability and implementationepiTAD can be accessed at https://apps.gerkelab.com/epiTAD/ where we have additionally made publicly available the source code and a Docker containerized version of the application.
Project description:Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data structures, computational methods and visualization tools available in Bioconductor to investigate Hi-C, micro-C and other 3C-related data, in R. An online book ( https://bioconductor.org/books/OHCA/ ) further provides prospective end users with a number of workflows to process, import, analyze and visualize any type of chromosome conformation capture data.
Project description:Since Jacob and Monod's characterization of the role of DNA elements in gene control, it has been recognized that the linear organization of genome structure is important for the regulation of gene transcription and hence the manifestation of phenotypes. Similarly, it has long been hypothesized that the spatial organization (in three dimensions evolving through time), as part of the epigenome, makes a significant contribution to the genotype-phenotype transition. Proximity ligation assays commonly known as chromosome conformation capture (3C) and 3C based methodologies (e.g., GCC, HiC and ChIA-Pet) are increasingly being incorporated into empirical studies to investigate the role that three-dimensional genome structure plays in the regulation of phenotype. The apparent simplicity of these methodologies-crosslink chromatin, digest, dilute, ligate, detect interactions-belies the complexity of the data and the considerations that should be taken into account to ensure the generation and accurate interpretation of reliable data. Here we discuss the probabilistic nature of these methodologies and how this contributes to their endogenous limitations.
Project description:BackgroundIdentification of locus-locus contacts at the chromatin level provides a valuable foundation for understanding of nuclear architecture and function and a valuable tool for inferring long-range linkage relationships. As one approach to this, chromatin conformation capture-based techniques allow creation of genome spatial organization maps. While such approaches have been available for some time, methodological advances will be of considerable use in minimizing both time and input material required for successful application.ResultsHere we report a modified tethered conformation capture protocol that utilizes a series of rapid and efficient molecular manipulations. We applied the method to Caenorhabditis elegans, obtaining chromatin interaction maps that provide a sequence-anchored delineation of salient aspects of Caenorhabditis elegans chromosome structure, demonstrating a high level of consistency in overall chromosome organization between biological samples collected under different conditions. In addition to the application of the method to defining nuclear architecture, we found the resulting chromatin interaction maps to be of sufficient resolution and sensitivity to enable detection of large-scale structural variants such as inversions or translocations.ConclusionOur streamlined protocol provides an accelerated, robust, and broadly applicable means of generating chromatin spatial organization maps and detecting genome rearrangements without a need for cellular or chromatin fractionation.
Project description:Chromosome conformation capture (3C) assays are used to map chromatin interactions genome-wide. Chromatin interaction maps provide insights into the spatial organization of chromosomes and the mechanisms by which they fold. Hi-C and Micro-C are widely used 3C protocols that 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 3C experimental parameters. We identified optimal protocol variants for either loop or compartment detection, optimizing fragment size and cross-linking chemistry. We used this knowledge to develop a greatly improved Hi-C protocol (Hi-C 3.0) that can detect both loops and compartments relatively effectively. In addition to providing benchmarked protocols, this work produced ultra-deep chromatin interaction maps using Micro-C, conventional Hi-C and Hi-C 3.0 for key cell lines used by the 4D Nucleome project.
Project description:Chemical cross-linking and high-throughput sequencing have revealed regions of intra-chromosomal interaction, referred to as topologically associating domains (TADs), interspersed with regions of little or no such interaction, in interphase nuclei. We find that TADs and the regions between them correspond with the bands and interbands of polytene chromosomes of Drosophila. We further establish the conservation of TADs between polytene and diploid cells of Drosophila. From direct measurements on light micrographs of polytene chromosomes, we then deduce the states of chromatin folding in the diploid cell nucleus. Two states of chromatin folding, fully extended fibers containing regulatory regions and promoters, and fibers condensed up to ten-fold containing coding regions of active genes, constitute the euchromatin of the nuclear interior. Chromatin fibers condensed up to 30-fold, containing coding regions of inactive genes, represent the heterochromatin of the nuclear periphery. A convergence of molecular analysis with direct observation thus reveals the architecture of interphase chromosomes. This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
Project description:We review currently available technologies for deconvoluting metagenomic data into individual genomes that represent populations, strains, or genotypes present in the community. An evaluation of chromosome conformation capture (3C) and related techniques in the context of metagenomics is presented, using mock microbial communities as a reference. We provide the first independent reproduction of the metagenomic 3C technique described last year, propose some simple improvements to that protocol, and compare the quality of the data with that provided by the more complex Hi-C protocol.
Project description:The representation, integration, and interpretation of omic data is a complex task, in particular considering the huge amount of information that is daily produced in molecular biology laboratories all around the world. The reason is that sequencing data regarding expression profiles, methylation patterns, and chromatin domains is difficult to harmonize in a systems biology view, since genome browsers only allow coordinate-based representations, discarding functional clusters created by the spatial conformation of the DNA in the nucleus. In this context, recent progresses in high throughput molecular biology techniques and bioinformatics have provided insights into chromatin interactions on a larger scale and offer a formidable support for the interpretation of multi-omic data. In particular, a novel sequencing technique called Chromosome Conformation Capture allows the analysis of the chromosome organization in the cell's natural state. While performed genome wide, this technique is usually called Hi-C. Inspired by service applications such as Google Maps, we developed NuChart, an R package that integrates Hi-C data to describe the chromosomal neighborhood starting from the information about gene positions, with the possibility of mapping on the achieved graphs genomic features such as methylation patterns and histone modifications, along with expression profiles. In this paper we show the importance of the NuChart application for the integration of multi-omic data in a systems biology fashion, with particular interest in cytogenetic applications of these techniques. Moreover, we demonstrate how the integration of multi-omic data can provide useful information in understanding why genes are in certain specific positions inside the nucleus and how epigenetic patterns correlate with their expression.
Project description:Chromosome conformation capture (3C) methods measure the spatial proximity between DNA elements in the cell nucleus. Many methods have been developed to sample 3C material, including the Capture-C family of protocols. Capture-C methods use oligonucleotides to enrich for interactions of interest from sequencing-ready 3C libraries. This approach is modular and has been adapted and optimized to work for sampling of disperse DNA elements (NuTi Capture-C), including from low cell inputs (LI Capture-C), as well as to generate Hi-C like maps for specific regions of interest (Tiled-C) and to interrogate multiway interactions (Tri-C). We present the design, experimental protocol and analysis pipeline for NuTi Capture-C in addition to the variations for generation of LI Capture-C, Tiled-C and Tri-C data. The entire procedure can be performed in 3 weeks and requires standard molecular biology skills and equipment, access to a next-generation sequencing platform, and basic bioinformatic skills. Implemented with other sequencing technologies, these methods can be used to identify regulatory interactions and to compare the structural organization of the genome in different cell types and genetic models.