Search

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.)

Histone H3 lysine 9 dimethylation (H3K9me2) is a highly conserved silencing epigenetic mark. Chromatin marked with H3K9me2 forms large domains in mammalian cells and overlaps well with lamina-associated domains and the B compartment defined by Hi-C. However, the role of H3K9me2 in 3-dimensional (3D) genome organization remains unclear. Here, we investigated genome-wide H3K9me2 distribution, transcriptome, and 3D genome organization in mouse embryonic stem cells following the inhibition or depletion of H3K9 methyltransferases (MTases): G9a, GLP, SETDB1, SUV39H1, and SUV39H2. We show that H3K9me2 is regulated by all five MTases; however, H3K9me2 and transcription in the A and B compartments are regulated by different MTases. H3K9me2 in the A compartments is primarily regulated by G9a/GLP and SETDB1, while H3K9me2 in the B compartments is regulated by all five MTases. Furthermore, decreased H3K9me2 correlates with changes to more active compartmental state that accompanied transcriptional activation. Thus, H3K9me2 contributes to inactive compartment setting.

The one-dimensional information of genomic DNA is hierarchically packed inside the eukaryotic cell nucleus and organized in a three-dimensional (3D) space. Genome-wide chromosome conformation capture (Hi-C) methods have uncovered the 3D genome organization and revealed multiscale chromatin domains of compartments and topologically associating domains (TADs). Moreover, single-nucleosome live-cell imaging experiments have revealed the dynamic organization of chromatin domains caused by stochastic thermal fluctuations. However, the mechanism underlying the dynamic regulation of such hierarchical and structural chromatin units within the microscale thermal medium remains unclear. Microrheology is a way to measure dynamic viscoelastic properties coupling between thermal microenvironment and mechanical response. Here, we propose a new, to our knowledge, microrheology for Hi-C data to analyze the dynamic compliance property as a measure of rigidness and flexibility of genomic regions along with the time evolution. Our method allows the conversion of an Hi-C matrix into the spectrum of the dynamic rheological property along the genomic coordinate of a single chromosome. To demonstrate the power of the technique, we analyzed Hi-C data during the neural differentiation of mouse embryonic stem cells. We found that TAD boundaries behave as more rigid nodes than the intra-TAD regions. The spectrum clearly shows the dynamic viscoelasticity of chromatin domain formation at different timescales. Furthermore, we characterized the appearance of synchronous and liquid-like intercompartment interactions in differentiated cells. Together, our microrheology data derived from Hi-C data provide physical insights into the dynamics of the 3D genome organization., (Copyright © 2020 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

Background: Hi-C is derived from chromosome conformation capture (3C) and targets chromatin contacts on a genomic scale. This method has also been used frequently in scaffolding nucleotide sequences obtained by de novo genome sequencing and assembly, in which the number of resultant sequences rarely converges to the chromosome number. Despite its prevalent use, the sample preparation methods for Hi-C have not been intensively discussed, especially from the standpoint of genome scaffolding., Results: To gain insight into the best practice of Hi-C scaffolding, we performed a multifaceted methodological comparison using vertebrate samples and optimized various factors during sample preparation, sequencing, and computation. As a result, we identified several key factors that helped improve Hi-C scaffolding, including the choice and preparation of tissues, library preparation conditions, the choice of restriction enzyme(s), and the choice of scaffolding program and its usage., Conclusions: This study provides the first comparison of multiple sample preparation kits/protocols and computational programs for Hi-C scaffolding by an academic third party. We introduce a customized protocol designated "inexpensive and controllable Hi-C (iconHi-C) protocol," which incorporates the optimal conditions identified in this study, and demonstrate this technique on chromosome-scale genome sequences of the Chinese softshell turtle Pelodiscus sinensis., (© The Author(s) 2020. Published by Oxford University Press.)

Multicellular organisms consist of multiple cell types. The identity of these cells is primarily maintained by cell-type-specific gene expression programs; however, mechanisms that suppress these programs are poorly defined. Here we show that serum response factor (Srf), a transcription factor that is activated by various extracellular stimuli, can repress cell-type-specific genes and promote cellular reprogramming to pluripotency. Manipulations that decrease β-actin monomer quantity result in the nuclear accumulation of Mkl1 and the activation of Srf, which downregulate cell-type-specific genes and alter the epigenetics of regulatory regions and chromatin organization. Mice overexpressing Srf exhibit various pathologies including an ulcerative colitis-like symptom and a metaplasia-like phenotype in the pancreas. Our results demonstrate an unexpected function of Srf via a mechanism by which extracellular stimuli actively destabilize cell identity and suggest Srf involvement in a wide range of diseases.

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.

To identify evolutionarily conserved features of replication timing and their relationship to epigenetic properties, we profiled replication timing genome-wide in four human embryonic stem cell (hESC) lines, hESC-derived neural precursor cells (NPCs), lymphoblastoid cells, and two human induced pluripotent stem cell lines (hiPSCs), and compared them with related mouse cell types. Results confirm the conservation of coordinately replicated megabase-sized "replication domains" punctuated by origin-suppressed regions. Differentiation-induced replication timing changes in both species occur in 400- to 800-kb units and are similarly coordinated with transcription changes. A surprising degree of cell-type-specific conservation in replication timing was observed across regions of conserved synteny, despite considerable species variation in the alignment of replication timing to isochore GC/LINE-1 content. Notably, hESC replication timing profiles were significantly more aligned to mouse epiblast-derived stem cells (mEpiSCs) than to mouse ESCs. Comparison with epigenetic marks revealed a signature of chromatin modifications at the boundaries of early replicating domains and a remarkably strong link between replication timing and spatial proximity of chromatin as measured by Hi-C analysis. Thus, early and late initiation of replication occurs in spatially separate nuclear compartments, but rarely within the intervening chromatin. Moreover, cell-type-specific conservation of the replication program implies conserved developmental changes in spatial organization of chromatin. Together, our results reveal evolutionarily conserved aspects of developmentally regulated replication programs in mammals, demonstrate the power of replication profiling to distinguish closely related cell types, and strongly support the hypothesis that replication timing domains are spatially compartmentalized structural and functional units of three-dimensional chromosomal architecture.