dcHiC detects differential compartments across multiple Hi-C datasets

Machine and Deep Learning Methods for Predicting 3D Genome Organization

Three-dimensional (3D) chromatin interactions, such as enhancer-promoter interactions (EPIs), loops, topologically associating domains (TADs), and A/B compartments, play critical roles in a wide range of cellular processes by regulating gene expression. Recent development of chromatin conformation capture technologies has enabled genome-wide profiling of various 3D structures, even with single cells. However, current catalogs of 3D structures remain incomplete and unreliable due to differences in technology, tools, and low data resolution. Machine learning methods have emerged as an alternative to obtain missing 3D interactions and/or improve resolution. Such methods frequently use genome annotation data (ChIP-seq, DNAse-seq, etc.), DNA sequencing information (k-mers and transcription factor binding site (TFBS) motifs), and other genomic properties to learn the associations between genomic features and chromatin interactions. In this review, we discuss computational tools for predicting three types of 3D interactions (EPIs, chromatin interactions, and TAD boundaries) and analyze their pros and cons. We also point out obstacles to the computational prediction of 3D interactions and suggest future research directions.

Temporally distinct 3D multi-omic dynamics in the developing human brain

The human hippocampus and prefrontal cortex play critical roles in learning and cognition1,2, yet the dynamic molecular characteristics of their development remain enigmatic. Here we investigated the epigenomic and three-dimensional chromatin conformational reorganization during the development of the hippocampus and prefrontal cortex, using more than 53,000 joint single-nucleus profiles of chromatin conformation and DNA methylation generated by single-nucleus methyl-3C sequencing (snm3C-seq3)3. The remodelling of DNA methylation is temporally separated from chromatin conformation dynamics. Using single-cell profiling and multimodal single-molecule imaging approaches, we have found that short-range chromatin interactions are enriched in neurons, whereas long-range interactions are enriched in glial cells and non-brain tissues. We reconstructed the regulatory programs of cell-type development and differentiation, finding putatively causal common variants for schizophrenia strongly overlapping with chromatin loop-connected, cell-type-specific regulatory regions. Our data provide multimodal resources for studying gene regulatory dynamics in brain development and demonstrate that single-cell three-dimensional multi-omics is a powerful approach for dissecting neuropsychiatric risk loci.

Genome structural dynamics: insights from Gaussian network analysis of Hi-C data

Characterization of the spatiotemporal properties of the chromatin is essential to gaining insights into the physical bases of gene co-expression, transcriptional regulation and epigenetic modifications. The Gaussian network model (GNM) has proven in recent work to serve as a useful tool for modeling chromatin structural dynamics, using as input high-throughput chromosome conformation capture data. We focus here on the exploration of the collective dynamics of chromosomal structures at hierarchical levels of resolution, from single gene loci to topologically associating domains or entire chromosomes. The GNM permits us to identify long-range interactions between gene loci, shedding light on the role of cross-correlations between distal regions of the chromosomes in regulating gene expression. Notably, GNM analysis performed across diverse cell lines highlights the conservation of the global/cooperative movements of the chromatin across different types of cells. Variations driven by localized couplings between genomic loci, on the other hand, underlie cell differentiation, underscoring the significance of the four-dimensional properties of the genome in defining cellular identity. Finally, we demonstrate the close relation between the cell type-dependent mobility profiles of gene loci and their gene expression patterns, providing a clear demonstration of the role of chromosomal 4D features in defining cell-specific differential expression of genes.

Unraveling the key role of chromatin structure in cancer development through epigenetic landscape characterization of oral cancer

Epigenetic alterations, such as those in chromatin structure and DNA methylation, have been extensively studied in a number of tumor types. But oral cancer, particularly oral adenocarcinoma, has received far less attention. Here, we combined laser-capture microdissection and muti-omics mini-bulk sequencing to systematically characterize the epigenetic landscape of oral cancer, including chromatin architecture, DNA methylation, H3K27me3 modification, and gene expression. In carcinogenesis, tumor cells exhibit reorganized chromatin spatial structures, including compromised compartment structures and altered gene-gene interaction networks. Notably, some structural alterations are observed in phenotypically non-malignant paracancerous but not in normal cells. We developed transformer models to identify the cancer propensity of individual genome loci, thereby determining the carcinogenic status of each sample. Insights into cancer epigenetic landscapes provide evidence that chromatin reorganization is an important hallmark of oral cancer progression, which is also linked with genomic alterations and DNA methylation reprogramming. In particular, regions of frequent copy number alternations in cancer cells are associated with strong spatial insulation in both cancer and normal samples. Aberrant methylation reprogramming in oral squamous cell carcinomas is closely related to chromatin structure and H3K27me3 signals, which are further influenced by intrinsic sequence properties. Our findings indicate that structural changes are both significant and conserved in two distinct types of oral cancer, closely linked to transcriptomic alterations and cancer development. Notably, the structural changes remain markedly evident in oral adenocarcinoma despite the considerably lower incidence of genomic copy number alterations and lesser extent of methylation alterations compared to squamous cell carcinoma. We expect that the comprehensive analysis of epigenetic reprogramming of different types and subtypes of primary oral tumors can provide additional guidance to the design of novel detection and therapy for oral cancer.

Obtention of viable cell suspensions from breast cancer tumor biopsies for 3D chromatin conformation and single-cell transcriptome analysis

Molecular and cellular characterization of tumors is essential due to the complex and heterogeneous nature of cancer. In recent decades, many bioinformatic tools and experimental techniques have been developed to achieve personalized characterization of tumors. However, sample handling continues to be a major challenge as limitations such as prior treatments before sample acquisition, the amount of tissue obtained, transportation, or the inability to process fresh samples pose a hurdle for experimental strategies that require viable cell suspensions. Here, we present an optimized protocol that allows the recovery of highly viable cell suspensions from breast cancer primary tumor biopsies. Using these cell suspensions we have successfully characterized genome architecture through Hi-C. Also, we have evaluated single-cell gene expression and the tumor cellular microenvironment through single-cell RNAseq. Both technologies are key in the detailed and personalized molecular characterization of tumor samples. The protocol described here is a cost-effective alternative to obtain viable cell suspensions from biopsies simply and efficiently.

Loss of multi-level 3D genome organization during breast cancer progression

Breast cancer entails intricate alterations in genome organization and expression. However, how three-dimensional (3D) chromatin structure changes in the progression from a normal to a breast cancer malignant state remains unknown. To address this, we conducted an analysis combining Hi-C data with lamina-associated domains (LADs), epigenomic marks, and gene expression in an in vitro model of breast cancer progression. Our results reveal that while the fundamental properties of topologically associating domains (TADs) are overall maintained, significant changes occur in the organization of compartments and subcompartments. These changes are closely correlated with alterations in the expression of oncogenic genes. We also observe a restructuring of TAD-TAD interactions, coinciding with a loss of spatial compartmentalization and radial positioning of the 3D genome. Notably, we identify a previously unrecognized interchromosomal insertion event, wherein a locus on chromosome 8 housing the MYC oncogene is inserted into a highly active subcompartment on chromosome 10. This insertion is accompanied by the formation of de novo enhancer contacts and activation of MYC, illustrating how structural genomic variants can alter the 3D genome to drive oncogenic states. In summary, our findings provide evidence for the loss of genome organization at multiple scales during breast cancer progression revealing novel relationships between genome 3D structure and oncogenic processes.

Enhancing Hi-C contact matrices for loop detection with Capricorn: a multiview diffusion model

MOTIVATION

High-resolution Hi-C contact matrices reveal the detailed three-dimensional architecture of the genome, but high-coverage experimental Hi-C data are expensive to generate. Simultaneously, chromatin structure analyses struggle with extremely sparse contact matrices. To address this problem, computational methods to enhance low-coverage contact matrices have been developed, but existing methods are largely based on resolution enhancement methods for natural images and hence often employ models that do not distinguish between biologically meaningful contacts, such as loops and other stochastic contacts.

RESULTS

We present Capricorn, a machine learning model for Hi-C resolution enhancement that incorporates small-scale chromatin features as additional views of the input Hi-C contact matrix and leverages a diffusion probability model backbone to generate a high-coverage matrix. We show that Capricorn outperforms the state of the art in a cross-cell-line setting, improving on existing methods by 17% in mean squared error and 26% in F1 score for chromatin loop identification from the generated high-coverage data. We also demonstrate that Capricorn performs well in the cross-chromosome setting and cross-chromosome, cross-cell-line setting, improving the downstream loop F1 score by 14% relative to existing methods. We further show that our multiview idea can also be used to improve several existing methods, HiCARN and HiCNN, indicating the wide applicability of this approach. Finally, we use DNA sequence to validate discovered loops and find that the fraction of CTCF-supported loops from Capricorn is similar to those identified from the high-coverage data. Capricorn is a powerful Hi-C resolution enhancement method that enables scientists to find chromatin features that cannot be identified in the low-coverage contact matrix.

AVAILABILITY AND IMPLEMENTATION

Implementation of Capricorn and source code for reproducing all figures in this paper are available at https://github.com/CHNFTQ/Capricorn.

Three-dimensional chromatin reorganization regulates B cell development during ageing

The contribution of three-dimensional genome organization to physiological ageing is not well known. Here we show that large-scale chromatin reorganization distinguishes young and old bone marrow progenitor (pro-) B cells. These changes result in increased interactions at the compartment level and reduced interactions within topologically associated domains (TADs). The gene encoding Ebf1, a key B cell regulator, switches from compartment A to B with age. Genetically reducing Ebf1 recapitulates some features of old pro-B cells. TADs that are most reduced with age contain genes important for B cell development, including the immunoglobulin heavy chain (Igh) locus. Weaker intra-TAD interactions at Igh correlate with altered variable (V), diversity (D) and joining (J) gene recombination. Our observations implicate three-dimensional chromatin reorganization as a major driver of pro-B cell phenotypes that impair B lymphopoiesis with age.

Droplet Hi-C for Fast and Scalable Profiling of Chromatin Architecture in Single Cells

Comprehensive analysis of chromatin architecture is crucial for understanding the gene regulatory programs during development and in disease pathogenesis, yet current methods often inadequately address the unique challenges presented by analysis of heterogeneous tissue samples. Here, we introduce Droplet Hi-C, which employs a commercial microfluidic device for high-throughput, single-cell chromatin conformation profiling in droplets. Using Droplet Hi-C, we mapped the chromatin architecture at single-cell resolution from the mouse cortex and analyzed gene regulatory programs in major cortical cell types. Additionally, we used this technique to detect copy number variation (CNV), structural variations (SVs) and extrachromosomal DNA (ecDNA) in cancer cells, revealing clonal dynamics and other oncogenic events during treatment. We further refined this technique to allow for joint profiling of chromatin architecture and transcriptome in single cells, facilitating a more comprehensive exploration of the links between chromatin architecture and gene expression in both normal tissues and tumors. Thus, Droplet Hi-C not only addresses critical gaps in chromatin analysis of heterogeneous tissues but also emerges as a versatile tool enhancing our understanding of gene regulation in health and disease.

Analysis of long-range chromatin contacts, compartments and looping between mouse embryonic stem cells, lens epithelium and lens fibers

BACKGROUND

Nuclear organization of interphase chromosomes involves individual chromosome territories, "open" and "closed" chromatin compartments, topologically associated domains (TADs) and chromatin loops. The DNA- and RNA-binding transcription factor CTCF together with the cohesin complex serve as major organizers of chromatin architecture. Cellular differentiation is driven by temporally and spatially coordinated gene expression that requires chromatin changes of individual loci of various complexities. Lens differentiation represents an advantageous system to probe transcriptional mechanisms underlying tissue-specific gene expression including high transcriptional outputs of individual crystallin genes until the mature lens fiber cells degrade their nuclei.

RESULTS

Chromatin organization between mouse embryonic stem (ES) cells, newborn (P0.5) lens epithelium and fiber cells were analyzed using Hi-C. Localization of CTCF in both lens chromatins was determined by ChIP-seq and compared with ES cells. Quantitative analyses show major differences between number and size of TADs and chromatin loop size between these three cell types. In depth analyses show similarities between lens samples exemplified by overlaps between compartments A and B. Lens epithelium-specific CTCF peaks are found in mostly methylated genomic regions while lens fiber-specific and shared peaks occur mostly within unmethylated DNA regions. Major differences in TADs and loops are illustrated at the ~ 500 kb Pax6 locus, encoding the critical lens regulatory transcription factor and within a larger ~ 15 Mb WAGR locus, containing Pax6 and other loci linked to human congenital diseases. Lens and ES cell Hi-C data (TADs and loops) together with ATAC-seq, CTCF, H3K27ac, H3K27me3 and ENCODE cis-regulatory sites are shown in detail for the Pax6, Sox1 and Hif1a loci, multiple crystallin genes and other important loci required for lens morphogenesis. The majority of crystallin loci are marked by unexpectedly high CTCF-binding across their transcribed regions.

CONCLUSIONS

Our study has generated the first data on 3-dimensional (3D) nuclear organization in lens epithelium and lens fibers and directly compared these data with ES cells. These findings generate novel insights into lens-specific transcriptional gene control, open new research avenues to study transcriptional condensates in lens fiber cells, and enable studies of non-coding genetic variants linked to cataract and other lens and ocular abnormalities.

Hi-C profiling in tissues reveals 3D chromatin-regulated breast tumor heterogeneity and tumor-specific looping-mediated biological pathways

Current knowledge in three-dimensional (3D) chromatin regulation in normal and disease states was mostly accumulated through Hi-C profiling in in vitro cell culture system. The limitations include failing to recapitulate disease-specific physiological properties and often lacking clinically relevant disease microenvironment. In this study, we conduct tissue-specific Hi-C profiling in a pilot cohort of 12 breast tissues comprising of two normal tissues (NTs) and ten ER+ breast tumor tissues (TTs) including five primary tumors (PTs), and five tamoxifen-treated recurrent tumors (RTs). We find largely preserved compartments, highly heterogeneous topological associated domains (TADs) and intensively variable chromatin loops among breast tumors, demonstrating 3D chromatin-regulated breast tumor heterogeneity. Further cross-examination identifies RT-specific looping-mediated biological pathways and suggests CA2, an enhancer-promoter looping (EPL)-mediated target gene within the bicarbonate transport metabolism pathway, might play a role in driving the tamoxifen resistance. Remarkably, the inhibition of CA2 not only impedes tumor growth both in vitro and in vivo , but also reverses chromatin looping. Our study thus yields significant mechanistic insights into the role and clinical relevance of 3D chromatin architecture in breast cancer endocrine resistance.

A Cyclic Permutation Approach to Removing Spatial Dependency between Clustered Gene Ontology Terms

Traditional gene set enrichment analysis falters when applied to large genomic domains, where neighboring genes often share functions. This spatial dependency creates misleading enrichments, mistaking mere physical proximity for genuine biological connections. Here we present Spatial Adjusted Gene Ontology (SAGO), a novel cyclic permutation-based approach, to tackle this challenge. SAGO separates enrichments due to spatial proximity from genuine biological links by incorporating the genes' spatial arrangement into the analysis. We applied SAGO to various datasets in which the identified genomic intervals are large, including replication timing domains, large H3K9me3 and H3K27me3 domains, HiC compartments and lamina-associated domains (LADs). Intriguingly, applying SAGO to prostate cancer samples with large copy number alteration (CNA) domains eliminated most of the enriched GO terms, thus helping to accurately identify biologically relevant gene sets linked to oncogenic processes, free from spatial bias.

Machine and deep learning methods for predicting 3D genome organization

Three-Dimensional (3D) chromatin interactions, such as enhancer-promoter interactions (EPIs), loops, Topologically Associating Domains (TADs), and A/B compartments play critical roles in a wide range of cellular processes by regulating gene expression. Recent development of chromatin conformation capture technologies has enabled genome-wide profiling of various 3D structures, even with single cells. However, current catalogs of 3D structures remain incomplete and unreliable due to differences in technology, tools, and low data resolution. Machine learning methods have emerged as an alternative to obtain missing 3D interactions and/or improve resolution. Such methods frequently use genome annotation data (ChIP-seq, DNAse-seq, etc.), DNA sequencing information (k-mers, Transcription Factor Binding Site (TFBS) motifs), and other genomic properties to learn the associations between genomic features and chromatin interactions. In this review, we discuss computational tools for predicting three types of 3D interactions (EPIs, chromatin interactions, TAD boundaries) and analyze their pros and cons. We also point out obstacles of computational prediction of 3D interactions and suggest future research directions.

Gene-to-gene coordinated regulation of transcription and alternative splicing by 3D chromatin remodeling upon NF-κB activation

The NF-κB protein p65/RelA plays a pivotal role in coordinating gene expression in response to diverse stimuli, including viral infections. At the chromatin level, p65/RelA regulates gene transcription and alternative splicing through promoter enrichment and genomic exon occupancy, respectively. The intricate ways in which p65/RelA simultaneously governs these functions across various genes remain to be fully elucidated. In this study, we employed the HTLV-1 Tax oncoprotein, a potent activator of NF-κB, to investigate its influence on the three-dimensional organization of the genome, a key factor in gene regulation. We discovered that Tax restructures the 3D genomic landscape, bringing together genes based on their regulation and splicing patterns. Notably, we found that the Tax-induced gene-gene contact between the two master genes NFKBIA and RELA is associated with their respective changes in gene expression and alternative splicing. Through dCas9-mediated approaches, we demonstrated that NFKBIA-RELA interaction is required for alternative splicing regulation and is caused by an intragenic enrichment of p65/RelA on RELA. Our findings shed light on new regulatory mechanisms upon HTLV-1 Tax and underscore the integral role of p65/RelA in coordinated regulation of NF-κB-responsive genes at both transcriptional and splicing levels in the context of the 3D genome.

SATB2 organizes the 3D genome architecture of cognition in cortical neurons

The DNA-binding protein SATB2 is genetically linked to human intelligence. We studied its influence on the three-dimensional (3D) epigenome by mapping chromatin interactions and accessibility in control versus SATB2-deficient cortical neurons. We find that SATB2 affects the chromatin looping between enhancers and promoters of neuronal-activity-regulated genes, thus influencing their expression. It also alters A/B compartments, topologically associating domains, and frequently interacting regions. Genes linked to SATB2-dependent 3D genome changes are implicated in highly specialized neuronal functions and contribute to cognitive ability and risk for neuropsychiatric and neurodevelopmental disorders. Non-coding DNA regions with a SATB2-dependent structure are enriched for common variants associated with educational attainment, intelligence, and schizophrenia. Our data establish SATB2 as a cell-type-specific 3D genome modulator, which operates both independently and in cooperation with CCCTC-binding factor (CTCF) to set up the chromatin landscape of pyramidal neurons for cognitive processes.

DiffDomain enables identification of structurally reorganized topologically associating domains

Topologically associating domains (TADs) are critical structural units in three-dimensional genome organization of mammalian genome. Dynamic reorganizations of TADs between health and disease states are associated with essential genome functions. However, computational methods for identifying reorganized TADs are still in the early stages of development. Here, we present DiffDomain, an algorithm leveraging high-dimensional random matrix theory to identify structurally reorganized TADs using high-throughput chromosome conformation capture (Hi-C) contact maps. Method comparison using multiple real Hi-C datasets reveals that DiffDomain outperforms alternative methods for false positive rates, true positive rates, and identifying a new subtype of reorganized TADs. Applying DiffDomain to Hi-C data from different cell types and disease states demonstrates its biological relevance. Identified reorganized TADs are associated with structural variations and epigenomic changes such as changes in CTCF binding sites. By applying to a single-cell Hi-C data from mouse neuronal development, DiffDomain can identify reorganized TADs between cell types with reasonable reproducibility using pseudo-bulk Hi-C data from as few as 100 cells per condition. Moreover, DiffDomain reveals differential cell-to-population variability and heterogeneous cell-to-cell variability in TADs. Therefore, DiffDomain is a statistically sound method for better comparative analysis of TADs using both Hi-C and single-cell Hi-C data.

Stage-specific dynamic reorganization of genome topology shapes transcriptional neighborhoods in developing human retinal organoids

We have generated a high-resolution Hi-C map of developing human retinal organoids to elucidate spatiotemporal dynamics of genomic architecture and its relationship with gene expression patterns. We demonstrate progressive stage-specific alterations in DNA topology and correlate these changes with transcription of cell-type-restricted gene markers during retinal differentiation. Temporal Hi-C reveals a shift toward A compartment for protein-coding genes and B compartment for non-coding RNAs, displaying high and low expression, respectively. Notably, retina-enriched genes are clustered near lost boundaries of topologically associated domains (TADs), and higher-order assemblages (i.e., TAD cliques) localize in active chromatin regions with binding sites for eye-field transcription factors. These genes gain chromatin contacts at their transcription start site as organoid differentiation proceeds. Our study provides a global view of chromatin architecture dynamics associated with diversification of cell types during retinal development and serves as a foundational resource for in-depth functional investigations of retinal developmental traits.

The counterpart congenital overgrowth syndromes Beckwith-Wiedemann Syndrome in human and large offspring syndrome in bovine involve alterations in DNA methylation, transcription, and chromatin configuration

Beckwith-Wiedemann Syndrome (BWS, OMIM #130650) is a congenital epigenetic disorder in humans which affects approximately 1 in 10,340 children. The incidence is likely an underestimation as the condition is usually recognized based on observable phenotypes at birth. BWS children have up to a 28% risk of developing tumors and currently, only 80% of patients can be corroborated molecularly (epimutations/variants). It is unknown how the subtypes of this condition are molecularly similar/dissimilar globally, therefore there is a need to deeply characterize the syndrome at the molecular level. Here we characterize the methylome, transcriptome and chromatin configuration of 18 BWS individuals together with the animal model of the condition, the bovine large offspring syndrome (LOS). Sex specific comparisons are performed for a subset of the BWS patients and LOS. Given that this epigenetic overgrowth syndrome has been characterized as a loss-of-imprinting condition, parental allele-specific comparisons were performed using the bovine animal model. In general, the differentially methylated regions (DMRs) detected in BWS and LOS showed significant enrichment for CTCF binding sites. Altered chromosome compartments in BWS and LOS were positively correlated with gene expression changes, and the promoters of differentially expressed genes showed significant enrichment for DMRs, differential topologically associating domains, and differential A/B compartments in some comparisons of BWS subtypes and LOS. We show shared regions of dysregulation between BWS and LOS, including several HOX gene clusters, and also demonstrate that altered DNA methylation differs between the clinically epigenetically identified BWS patients and those identified as having DNA variants (i.e. CDKN1C microdeletion). Lastly, we highlight additional genes and genomic regions that have the potential to serve as targets for biomarker development to improve current molecular methodologies. In summary, our results suggest that genome-wide alternation of chromosome architecture, which is partially caused by DNA methylation changes, also contribute to the development of BWS and LOS.

Lineage-specific 3D genome organization is assembled at multiple scales by IKAROS

A generic level of chromatin organization generated by the interplay between cohesin and CTCF suffices to limit promiscuous interactions between regulatory elements, but a lineage-specific chromatin assembly that supersedes these constraints is required to configure the genome to guide gene expression changes that drive faithful lineage progression. Loss-of-function approaches in B cell precursors show that IKAROS assembles interactions across megabase distances in preparation for lymphoid development. Interactions emanating from IKAROS-bound enhancers override CTCF-imposed boundaries to assemble lineage-specific regulatory units built on a backbone of smaller invariant topological domains. Gain of function in epithelial cells confirms IKAROS' ability to reconfigure chromatin architecture at multiple scales. Although the compaction of the Igκ locus required for genome editing represents a function of IKAROS unique to lymphocytes, the more general function to preconfigure the genome to support lineage-specific gene expression and suppress activation of extra-lineage genes provides a paradigm for lineage restriction.

Single-cell DNA methylation and 3D genome architecture in the human brain

Delineating the gene-regulatory programs underlying complex cell types is fundamental for understanding brain function in health and disease. Here, we comprehensively examined human brain cell epigenomes by probing DNA methylation and chromatin conformation at single-cell resolution in 517 thousand cells (399 thousand neurons and 118 thousand non-neurons) from 46 regions of three adult male brains. We identified 188 cell types and characterized their molecular signatures. Integrative analyses revealed concordant changes in DNA methylation, chromatin accessibility, chromatin organization, and gene expression across cell types, cortical areas, and basal ganglia structures. We further developed single-cell methylation barcodes that reliably predict brain cell types using the methylation status of select genomic sites. This multimodal epigenomic brain cell atlas provides new insights into the complexity of cell-type-specific gene regulation in adult human brains.

Identifying quantitatively differential chromosomal compartmentalization changes and their biological significance from Hi-C data using DARIC

BACKGROUND

Chromosomal compartmentalization plays a critical role in maintaining proper transcriptional programs in cell differentiation and oncogenesis. However, currently the prevalent method for comparative analysis of compartmentalization landscapes between different cell types is limited to the qualitative switched compartments.

RESULTS

To identify genomic regions with quantitatively differential compartmentalization changes from genome-wide chromatin conformation data like Hi-C, we developed a computational framework named DARIC. DARIC includes three modules: compartmentalization quantification, normalization, and differential analysis. Comparing DARIC with the conventional compartment switching analysis reveals substantial regions characterized by quantitatively significant compartmentalization changes without switching. These changes are accompanied by changes in gene expression, chromatin accessibility, H3K27ac intensity, as well as the interactions with nuclear lamina proteins and nuclear positioning, highlighting the functional importance of such quantitative changes in gene regulation. We applied DARIC to dissect the quantitative compartmentalization changes during human cardiomyocyte differentiation and identified two distinct mechanisms for gene activation based on the association with compartmentalization changes. Using the quantitative compartmentalization measurement module from DARIC, we further dissected the compartment variability landscape in the human genome by analyzing a compendium of 32 Hi-C datasets from 4DN. We discovered an interesting correlation between compartmentalization variability and sub-compartments.

CONCLUSIONS

DARIC is a useful tool for analyzing quantitative compartmentalization changes and mining novel biological insights from increasing Hi-C data. Our results demonstrate the functional significance of quantitative compartmentalization changes in gene regulation, and provide new insights into the relationship between compartmentalization variability and sub-compartments in the human genome.

The shape of chromatin: insights from computational recognition of geometric patterns in Hi-C data

The three-dimensional organization of chromatin plays a crucial role in gene regulation and cellular processes like deoxyribonucleic acid (DNA) transcription, replication and repair. Hi-C and related techniques provide detailed views of spatial proximities within the nucleus. However, data analysis is challenging partially due to a lack of well-defined, underpinning mathematical frameworks. Recently, recognizing and analyzing geometric patterns in Hi-C data has emerged as a powerful approach. This review provides a summary of algorithms for automatic recognition and analysis of geometric patterns in Hi-C data and their correspondence with chromatin structure. We classify existing algorithms on the basis of the data representation and pattern recognition paradigm they make use of. Finally, we outline some of the challenges ahead and promising future directions.

snHiC: a complete and simplified snakemake pipeline for grouped Hi-C data analysis

Summary

Genome-wide chromosome conformation capture (Hi-C) is a technique that allows the study of 3D genome organization. Despite being widely used, analysis of Hi-C data is technically challenging and involves several time-consuming steps that often require manual involvement making it error prone, potentially affecting data reproducibility. In order to facilitate and simplify these analyses we implemented snHiC, a snakemake-based pipeline that allows for the generation of contact matrices at multiple resolutions in one single run, aggregation of individual samples into user-specified groups, detection of domains, compartments, loops and stripes and performance of differential compartment and chromatin interaction analyses.

Availability and implementation

Source code is freely available at https://github.com/sebastian-gregoricchio/snHiC. A yaml-formatted file (snHiC/workflow/envs/snHiC_conda_env_stable.yaml) is available to build a compatible conda environment.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Assignment of the somatic A/B compartments to chromatin domains in giant transcriptionally active lampbrush chromosomes

BACKGROUND

The three-dimensional configuration of the eukaryotic genome is an emerging area of research. Chromosome conformation capture outlined genome segregation into large scale A and B compartments corresponding mainly to transcriptionally active and repressive chromatin. It remains unknown how the compartmentalization of the genome changes in growing oocytes of animals with hypertranscriptional type of oogenesis. Such oocytes are characterized by highly elongated chromosomes, called lampbrush chromosomes, which acquire a typical chromomere-loop appearance, representing one of the classical model systems for exploring the structural and functional organization of chromatin domains.

RESULTS

Here, we compared the distribution of A/B compartments in chicken somatic cells with chromatin domains in lampbrush chromosomes. We found that in lampbrush chromosomes, the extended chromatin domains, restricted by compartment boundaries in somatic cells, disintegrate into individual chromomeres. Next, we performed FISH-mapping of the genomic loci, which belong to A or B chromatin compartments as well as to A/B compartment transition regions in embryonic fibroblasts on isolated lampbrush chromosomes. We found, that in chicken lampbrush chromosomes, clusters of dense compact chromomeres bearing short lateral loops and enriched with repressive epigenetic modifications generally correspond to constitutive B compartments in somatic cells. A compartments align with lampbrush chromosome segments with smaller, less compact chromomeres, longer lateral loops, and a higher transcriptional status. Clusters of small loose chromomeres with relatively long lateral loops show no obvious correspondence with either A or B compartment identity. Some genes belonging to facultative B (sub-) compartments can be tissue-specifically transcribed during oogenesis, forming distinct lateral loops.

CONCLUSIONS

Here, we established a correspondence between the A/B compartments in somatic interphase nucleus and chromatin segments in giant lampbrush chromosomes from diplotene stage oocytes. The chromomere-loop structure of the genomic regions corresponding to interphase A and B compartments reveals the difference in how they are organized at the level of chromatin domains. The results obtained also suggest that gene-poor regions tend to be packed into chromomeres.

Identifying Quantitatively Differential Chromosomal Compartmentalization Changes and Their Biological Significance from Hi-C data using DARIC

Background

Chromosomal compartmentalization plays a critical role in maintaining proper transcriptional programs in cell differentiation and oncogenesis. However, currently the prevalent method for comparative analysis of compartmentalization landscapes between different cell types is limited to the qualitative switched compartments.

Results

To identify genomic regions with quantitatively differential compartmentalization changes from genome-wide chromatin conformation data like Hi-C, we developed a computational framework named DARIC. DARIC includes three modules: compartmentalization quantification, normalization, and differential analysis. Comparing DARIC with the conventional compartment switching analysis reveals substantial regions characterized by quantitatively significant compartmentalization changes without switching. These changes are accompanied by changes in gene expression, chromatin accessibility, H3K27ac intensity, as well as the interactions with nuclear lamina proteins and nuclear positioning, highlighting the functional importance of such quantitative changes in gene regulation. We applied DARIC to dissect the quantitative compartmentalization changes during human cardiomyocyte differentiation and identified two distinct mechanisms for gene activation based on the association with compartmentalization changes. Using the quantitative compartmentalization measurement module from DARIC, we further dissected the compartment variability landscape in the human genome by analyzing a compendium of 32 Hi-C datasets from 4DN. We discovered an interesting correlation between compartmentalization variability and sub-compartments.

Conclusions

DARIC is a useful tool for analyzing quantitative compartmentalization changes and mining novel biological insights from increasing Hi-C data. Our results demonstrate the functional significance of quantitative compartmentalization changes in gene regulation, and provide new insights into the relationship between compartmentalization variability and sub-compartments in the human genome.

Considerations and caveats for analyzing chromatin compartments

Genomes are organized into nuclear compartments, separating active from inactive chromatin. Chromatin compartments are readily visible in a large number of species by experiments that map chromatin conformation genome-wide. When analyzing these maps, a common step is the identification of genomic intervals that interact within A (active) and B (inactive) compartments. It has also become increasingly common to identify and analyze subcompartments. We review different strategies to identify A/B and subcompartment intervals, including a discussion of various machine-learning approaches to predict these features. We then discuss the strengths and limitations of current strategies and examine how these aspects of analysis may have impacted our understanding of chromatin compartments.

A DNA tumor virus globally reprograms host 3D genome architecture to achieve immortal growth

Epstein-Barr virus (EBV) immortalization of resting B lymphocytes (RBLs) to lymphoblastoid cell lines (LCLs) models human DNA tumor virus oncogenesis. RBL and LCL chromatin interaction maps are compared to identify the spatial and temporal genome architectural changes during EBV B cell transformation. EBV induces global genome reorganization where contact domains frequently merge or subdivide during transformation. Repressed B compartments in RBLs frequently switch to active A compartments in LCLs. LCLs gain 40% new contact domain boundaries. Newly gained LCL boundaries have strong CTCF binding at their borders while in RBLs, the same sites have much less CTCF binding. Some LCL CTCF sites also have EBV nuclear antigen (EBNA) leader protein EBNALP binding. LCLs have more local interactions than RBLs at LCL dependency factors and super-enhancer targets. RNA Pol II HiChIP and FISH of RBL and LCL further validate the Hi-C results. EBNA3A inactivation globally alters LCL genome interactions. EBNA3A inactivation reduces CTCF and RAD21 DNA binding. EBNA3C inactivation rewires the looping at the CDKN2A/B and AICDA loci. Disruption of a CTCF site at AICDA locus increases AICDA expression. These data suggest that EBV controls lymphocyte growth by globally reorganizing host genome architecture to facilitate the expression of key oncogenes.

HIV integration in the human brain is linked to microglial activation and 3D genome remodeling

To explore genome organization and function in the HIV-infected brain, we applied single-nuclei transcriptomics, cell-type-specific chromosomal conformation mapping, and viral integration site sequencing (IS-seq) to frontal cortex from individuals with encephalitis (HIVE) and without (HIV+). Derepressive changes in 3D genomic compartment structures in HIVE microglia were linked to the transcriptional activation of interferon (IFN) signaling and cell migratory pathways, while transcriptional downregulation and repressive compartmentalization of neuronal health and signaling genes occurred in both HIVE and HIV+ microglia. IS-seq recovered 1,221 brain integration sites showing distinct genomic patterns compared with peripheral lymphocytes, with enrichment for sequences newly mobilized into a permissive chromatin environment after infection. Viral transcription occurred in a subset of highly activated microglia comprising 0.33% of all nuclei in HIVE brain. Our findings point to disrupted microglia-neuronal interactions in HIV and link retroviral integration to remodeling of the microglial 3D genome during infection.