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Over a decade has passed since the development of the Hi-C method for genome-wide analysis of 3D genome organization. Hi-C utilizes next-generation sequencing (NGS) technology to generate large-scale chromatin interaction data, which has accumulated across a diverse range of species and cell types, particularly in eukaryotes. There is thus a growing need to streamline the process of Hi-C data analysis to utilize these data sets effectively. Hi-C generates data that are much larger compared to other NGS techniques such as chromatin immunoprecipitation sequencing (ChIP-seq) or RNA-seq, making the data reanalysis process computationally expensive. In an effort to bridge this resource gap, the 4D Nucleome (4DN) Data Portal has reanalyzed approximately 600 Hi-C data sets, allowing users to access and utilize the analyzed data. In this chapter, we provide detailed instructions for the implementation of the common workflow language (CWL)-based Hi-C analysis pipeline adopted by the 4DN Data Portal ecosystem. This reproducible and portable pipeline generates standard Hi-C contact matrices in formats such as .hic or .mcool from FASTQ files. It enables users to output their own Hi-C data in the same format as those registered in the 4DN Data portal, facilitating comparative analysis using data registered in the portal. Our custom-made scripts are available on GitHub at https://github.com/kuzobuta/4dn_cwl_pipeline ., (© 2025. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Assay of transposase-accessible chromatin with visualization (ATAC-see), a transposase-mediated imaging technology that enables direct imaging of the accessible genome in situ and deep sequencing to reveal the identity of the imaged elements. Here we image spatial organization of the accessible genome in HT1080 cells with this method., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Structural variations (SVs) are large genomic rearrangements that can be challenging to identify with current short read sequencing technology due to various confounding factors such as existence of genomic repeats and complex SV structures. Hi-C breakfinder is the first computational tool that utilizes the technology of high-throughput chromatin conformation capture assay (Hi-C) to systematically identify SVs, without being interfered by regular confounding factors. SVs change the spatial distance of genomic regions and cause discontinuous signals in Hi-C, which are difficult to analyze by routine informatics practice. Here we provide step-by-step guidance for how to identify SVs using Hi-C data and how to reconstruct Hi-C maps in the presence of SVs., (© 2022. Springer Science+Business Media, LLC, part of Springer Nature.)

High-throughput chromosome conformation capture (Hi-C) enables the global quantification of chromatin interaction frequency in eukaryotic nuclei. This method is based on in situ Hi-C, in which chromatin is cross-linked with formaldehyde, then digested with restriction enzyme. Biotin-labeled nucleotide is incorporated before the spatially adjacent DNA ends are ligated, making it possible to enrich specifically the chimeric ligation products for deep sequencing. In this chapter, we describe a modified in situ Hi-C protocol for the global chromatin interaction analysis in plants., (© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Over the past two decades, the development of chromosome conformation capture technologies has allowed to intensively probe the properties of genome folding in various cell types. High-throughput versions of these C-based assays (named Hi-C) have released the mapping of 3D chromosome folding for the entire genomes. Applied to mammalian preimplantation embryos, it has revealed a unique chromosome organization after fertilization when a new individual is being formed. However, the questions of whether specific structures could arise depending on their parental origins or of their transcriptional status remain open. Our method chapter is dedicated to the technical description on how applying scHi-C to mouse embryos at different stages of preimplantation development. This approach capitalized with the limited amount of material available at these developmental stages. It also provides new research avenues, such as the study of mutant embryos for further functional studies.

Epigenetic mechanisms govern the quality, the stability, and the responsiveness of transcriptional programs to the environment. This regulation is ensured via the concerted action of different players (transcription factors, "reader" and "writer" enzymes, histone marks, structural proteins, noncoding regulatory RNAs) that flow in the 3D organization of the genome. Indeed, nuclear architecture participates in the punctual and cell-type-specific regulation of transcription. Hence, the fine dissection of these mechanisms will allow a deeper understanding of the gene expression machinery. In this chapter, we propose a challenging imaging-based method to study the reciprocal interactions between chromatin-associated RNAs, genomic loci, and chromatin compartment with a procedure of 3D COMBO chrRNA-DNA-ImmunoFISH, specifically developed to preserve the nuclear integrity and topology of human primary T cells. We believe that our protocol will contribute to the improvement of epigenetic studies on the 3D nuclear structure of T cell subsets, possibly shedding light on the still hidden epigenetic players responsible for the great plasticity and functional diversification exerted by T cells.

Recent advances in next-generation sequencing (NGS) and chromosome conformation capture (3C) analysis have led to the development of Hi-C, a genome-wide version of the 3C method. Hi-C has identified new levels of chromosome organization such as A/B compartments, topologically associating domains (TADs) as well as large megadomains on the inactive X chromosome, while allowing the identification of chromatin loops at the genome scale. Despite its powerfulness, Hi-C data analysis is much more involved compared to conventional NGS applications such as RNA-seq or ChIP-seq and requires many more steps. This presents a significant hurdle for those who wish to implement Hi-C technology into their laboratory. On the other hand, genomics data repository sites sometimes contain processed Hi-C data sets, allowing researchers to perform further analysis without the need for high-spec workstations and servers. In this chapter, we provide a detailed description on how to calculate A/B compartment profiles from processed Hi-C data on the autosomes and the active/inactive X chromosomes.

The introduction of chromosome conformation capture (3C) technologies boosted the field of 3D-genome research and significantly enhanced the available toolset to study chromosomal architecture. 3C technologies not only offer increased resolution compared to the previously dominant cytological approaches but also allow the simultaneous study of genome-wide 3D chromatin contacts, thereby enabling a candidate-free perspective on 3D-genome architecture. Since its introduction in 2002, 3C technologies evolved rapidly and now constitute a collection of tools, each with their strengths and pitfalls with respect to specific research questions. This chapter aims at guiding 3C novices through the labyrinth of potential applications of the various family members, hopefully providing a valuable basis for choosing the appropriate strategy for different research questions.