The three-dimensional folding of the α-globin gene domain reveals formation of chromatin globules

Integrated analysis of differential intra-chromosomal community interactions: A study of breast cancer

It is challenging to analyze the dynamics of intra-chromosomal interactions when considering multiple high-dimensional epigenetic datasets. A computational approach, differential network analysis in intra-chromosomal community interaction (DNAICI), was proposed here to elucidate these dynamics by integrating Hi-C data with other epigenetic data. DNAICI utilized a novel hyperparameter tuning method, for optimizing the network clustering, to identify valid intra-chromosomal community interactions at different resolutions. The approach was first trained on Hi-C data and other epigenetic data in an untreated and one hour estrogen (E2)-treated breast cancer cell line, MCF7, and uncovered two major types of valid intra-chromosomal community interactions (active/repressive) that resembles the properties of A/B compartments (or open/closed chromatin domains). It was further tested on the breast cancer cell line MCF7 and its corresponding tamoxifen-resistant (TR) derivative, MCF7TR, and identified 515 differentially interacting and expressed genes (DIEGs) within intra-chromosomal community interactions. In silico analysis of these DIEGs revealed that endocrine resistance is among the top biological pathways, suggesting an interacting/looping-mediated mechanism in regulating breast cancer tamoxifen resistance. This novel integrated network analysis approach offers a broad application in diverse biological systems for identifying a biological-context-specific differential community interaction.

An unusual transfusion-dependent hemoglobin H disease caused by a novel complex inverted duplication involving the α-globin regulatory elements and α-thalassemia--SEA deletion

Four multi-species conserved sequences (MCSs) are important enhancers which affect α-globin expression. Deletions of MCS can cause α-thalassemia. So far, duplication of MCS has never been reported to account for thalassemia. In this study, an unusual transfusion-dependent case of hemoglobin H disease was identified by whole-genome sequencing, optical genome mapping and longer PCR with special primers, which was caused by a familial 96,620-bp inverted duplication (from MCS-R1 to MCS-R4), inserted between chr16:199348 and 199349 (GRCh37/hg19) within MCSs. The duplication segment included an inverted repeat sequence from chr16:102712 to176193 and one direct repeat sequence from chr16:176208 to 199348. The associated α-thalassemia trait was confirmed to result from disrupted topological chromatin domains using ATAC-seq and the dual‑luciferase reporter assay system. This case presents a new mechanism of α-thalassemia, and may aid our understanding of the effects of enhancers on gene expression and the differential contribution of the four enhancer elements in the human a-globin locus.

Advancements and future directions in single-cell Hi-C based 3D chromatin modeling

Single-cell Hi-C data provides valuable insights into the three-dimensional organization of chromatin within individual cells, yet modeling this data poses significant challenges due to its inherent sparsity and variability. This review comprehensively explores the predominant approaches to reconstructing 3D chromatin structures from single-cell Hi-C data, positioning these methods within the broader contexts of single-cell Hi-C research and bulk Hi-C data modeling. We categorize the modeling strategies based on their objective functions, which are framed in terms of force fields, potentials, cost functions, or likelihood probabilities. Despite their diverse methodologies, these approaches exhibit deep underlying similarities. We further dissect the basic components of these models, such as attractive restraint forces and repulsive forces, and discuss additional terms like fluid viscosity and variation penalties. The review also critically evaluates the current state of model validation, highlighting the inconsistencies across various studies and emphasizing the need for a comprehensive validation framework. We detail common validation techniques, including the comparison of distance matrices and the assessment of contact violations. We argue that the future of single-cell Hi-C modeling lies in integrating multiple data modalities and incorporating cell cycle trajectory information. Such integration could significantly advance our understanding of chromatin conformation dynamics during cell cycle progression and cell differentiation. We also foresee the continued growth of optimization-based and molecular dynamics approaches, supported by general molecular dynamics toolkits.

Nonequilibrium switching of segmental states can influence compaction of chromatin

Knowledge about the dynamic nature of chromatin organization is essential to understand the regulation of processes like DNA transcription and repair. The existing models of chromatin assume that protein organization and chemical states along chromatin are static and the 3D organization is purely a result of protein-mediated intra-chromatin interactions. Here we present a new hypothesis that certain nonequilibrium processes, such as switching of chemical and physical states due to nucleosome assembly/disassembly or gene repression/activation, can also simultaneously influence chromatin configurations. To understand the implications of this inherent nonequilibrium switching, we present a block copolymer model of chromatin, with switching of its segmental states between two states, mimicking active/repressed or protein unbound/bound states. We show that competition between switching timescale Tt, polymer relaxation timescale τp, and segmental relaxation timescale τs can lead to non-trivial changes in chromatin organization, leading to changes in local compaction and contact probabilities. As a function of the switching timescale, the radius of gyration of chromatin shows a non-monotonic behavior with a prominent minimum when Tt ≈ τp and a maximum when Tt ≈ τs. We find that polymers with a small segment length exhibit a more compact structure than those with larger segment lengths. We also find that the switching can lead to higher contact probability and better mixing of far-away segments. Our study also shows that the nature of the distribution of chromatin clusters varies widely as we change the switching rate.

Multiscale Bayesian simulations reveal functional chromatin condensation of gene loci

Chromatin, the complex assembly of DNA and associated proteins, plays a pivotal role in orchestrating various genomic functions. To aid our understanding of the principles underlying chromatin organization, we introduce Hi-C metainference, a Bayesian approach that integrates Hi-C contact frequencies into multiscale prior models of chromatin. This approach combines both bottom-up (the physics-based prior) and top-down (the data-driven posterior) strategies to characterize the 3D organization of a target genomic locus. We first demonstrate the capability of this method to accurately reconstruct the structural ensemble and the dynamics of a system from contact information. We then apply the approach to investigate the Sox2, Pou5f1, and Nanog loci of mouse embryonic stem cells using a bottom-up chromatin model at 1 kb resolution. We observe that the studied loci are conformationally heterogeneous and organized as crumpled globules, favoring contacts between distant enhancers and promoters. Using nucleosome-resolution simulations, we then reveal how the Nanog gene is functionally organized across the multiple scales of chromatin. At the local level, we identify diverse tetranucleosome folding motifs with a characteristic distribution along the genome, predominantly open at cis-regulatory elements and compact in between. At the larger scale, we find that enhancer-promoter contacts are driven by the transient condensation of chromatin into compact domains stabilized by extensive internucleosome interactions. Overall, this work highlights the condensed, but dynamic nature of chromatin in vivo, contributing to a deeper understanding of gene structure-function relationships.

Boundary stacking interactions enable cross-TAD enhancer-promoter communication during limb development

Although promoters and their enhancers are frequently contained within a topologically associating domain (TAD), some developmentally important genes have their promoter and enhancers within different TADs. Hypotheses about molecular mechanisms enabling cross-TAD interactions remain to be assessed. To test these hypotheses, we used optical reconstruction of chromatin architecture to characterize the conformations of the Pitx1 locus on single chromosomes in developing mouse limbs. Our data support a model in which neighboring boundaries are stacked as a result of loop extrusion, bringing boundary-proximal cis-elements into contact. This stacking interaction also contributes to the appearance of architectural stripes in the population average maps. Through molecular dynamics simulations, we found that increasing boundary strengths facilitates the formation of the stacked boundary conformation, counter-intuitively facilitating border bypass. This work provides a revised view of the TAD borders' function, both facilitating and preventing cis-regulatory interactions, and introduces a framework to distinguish border-crossing from border-respecting enhancer-promoter pairs.

Computational methods for analysing multiscale 3D genome organization

Recent progress in whole-genome mapping and imaging technologies has enabled the characterization of the spatial organization and folding of the genome in the nucleus. In parallel, advanced computational methods have been developed to leverage these mapping data to reveal multiscale three-dimensional (3D) genome features and to provide a more complete view of genome structure and its connections to genome functions such as transcription. Here, we discuss how recently developed computational tools, including machine-learning-based methods and integrative structure-modelling frameworks, have led to a systematic, multiscale delineation of the connections among different scales of 3D genome organization, genomic and epigenomic features, functional nuclear components and genome function. However, approaches that more comprehensively integrate a wide variety of genomic and imaging datasets are still needed to uncover the functional role of 3D genome structure in defining cellular phenotypes in health and disease.

Evaluating the role of the nuclear microenvironment in gene function by population-based modeling

The nuclear folding of chromosomes relative to nuclear bodies is an integral part of gene function. Here, we demonstrate that population-based modeling-from ensemble Hi-C data-provides a detailed description of the nuclear microenvironment of genes and its role in gene function. We define the microenvironment by the subnuclear positions of genomic regions with respect to nuclear bodies, local chromatin compaction, and preferences in chromatin compartmentalization. These structural descriptors are determined in single-cell models, thereby revealing the structural variability between cells. We demonstrate that the microenvironment of a genomic region is linked to its functional potential in gene transcription, replication, and chromatin compartmentalization. Some chromatin regions feature a strong preference for a single microenvironment, due to association with specific nuclear bodies in most cells. Other chromatin shows high structural variability, which is a strong indicator of functional heterogeneity. Moreover, we identify specialized nuclear microenvironments, which distinguish chromatin in different functional states and reveal a key role of nuclear speckles in chromosome organization. We demonstrate that our method produces highly predictive three-dimensional genome structures, which accurately reproduce data from a variety of orthogonal experiments, thus considerably expanding the range of Hi-C data analysis.

Multiomic analysis of cohesin reveals that ZBTB transcription factors contribute to chromatin interactions

One bottleneck in understanding the principles of 3D chromatin structures is caused by the paucity of known regulators. Cohesin is essential for 3D chromatin organization, and its interacting partners are candidate regulators. Here, we performed proteomic profiling of the cohesin in chromatin and identified transcription factors, RNA-binding proteins and chromatin regulators associated with cohesin. Acute protein degradation followed by time-series genomic binding quantitation and BAT Hi-C analysis were conducted, and the results showed that the transcription factor ZBTB21 contributes to cohesin chromatin binding, 3D chromatin interactions and transcriptional repression. Strikingly, multiomic analyses revealed that the other four ZBTB factors interacted with cohesin, and double degradation of ZBTB21 and ZBTB7B led to a further decrease in cohesin chromatin occupancy. We propose that multiple ZBTB transcription factors orchestrate the chromatin binding of cohesin to regulate chromatin interactions, and we provide a catalog of many additional proteins associated with cohesin that warrant further investigation.

Integrative studies of 3D genome organization and chromatin structure

The structural organization of the genome is emerging as a crucial regulator of the cell state, affecting gene transcription, DNA replication, and repair. Over the last twenty years, increasing evidence prompted the development of new experimental techniques to study genome structure. In parallel with the complexity of the novel techniques, computational approaches have become an essential tool in any structural genomics laboratory to analyze and model the data. For biologists to be able to apply the most appropriate modeling approach, it is fundamental to understand the conceptual bases of distinct methods and the insights they can provide. Here, we will discuss recent advances that were possible thanks to 3D genome modeling, discuss their limitations and highlight future perspectives.

Heterogeneous interactions and polymer entropy decide organization and dynamics of chromatin domains

Chromatin is known to be organized into multiple domains of varying sizes and compaction. While these domains are often imagined as static structures, they are highly dynamic and show cell-to-cell variability. Since processes such as gene regulation and DNA replication occur in the context of these domains, it is important to understand their organization, fluctuation, and dynamics. To simulate chromatin domains, one requires knowledge of interaction strengths among chromatin segments. Here, we derive interaction-strength parameters from experimentally known contact maps and use them to predict chromatin organization and dynamics. Taking two domains on the human chromosome as examples, we investigate its three-dimensional organization, size/shape fluctuations, and dynamics of different segments within a domain, accounting for hydrodynamic effects. Considering different cell types, we quantify changes in interaction strengths and chromatin shape fluctuations in different epigenetic states. Perturbing the interaction strengths systematically, we further investigate how epigenetic-like changes can alter the spatio-temporal nature of the domains. Our results show that heterogeneous weak interactions are crucial in determining the organization of the domains. Computing effective stiffness and relaxation times, we investigate how perturbations in interactions affect the solid- and liquid-like nature of chromatin domains. Quantifying dynamics of chromatin segments within a domain, we show how the competition between polymer entropy and interaction energy influence the timescales of loop formation and maintenance of stable loops.

Integrative genome modeling platform reveals essentiality of rare contact events in 3D genome organizations

A multitude of sequencing-based and microscopy technologies provide the means to unravel the relationship between the three-dimensional organization of genomes and key regulatory processes of genome function. Here, we develop a multimodal data integration approach to produce populations of single-cell genome structures that are highly predictive for nuclear locations of genes and nuclear bodies, local chromatin compaction and spatial segregation of functionally related chromatin. We demonstrate that multimodal data integration can compensate for systematic errors in some of the data and can greatly increase accuracy and coverage of genome structure models. We also show that alternative combinations of different orthogonal data sources can converge to models with similar predictive power. Moreover, our study reveals the key contributions of low-frequency (‘rare’) interchromosomal contacts to accurately predicting the global nuclear architecture, including the positioning of genes and chromosomes. Overall, our results highlight the benefits of multimodal data integration for genome structure analysis, available through the Integrative Genome Modeling software package.

The Integrative Genome Modeling platform is a tool for population-based three-dimensional genome structure modeling and analysis by integrating various experimental data sources.

Uncovering the Principles of Genome Folding by 3D Chromatin Modeling

Our understanding of how genomic DNA is tightly packed inside the nucleus, yet is still accessible for vital cellular processes, has grown dramatically over recent years with advances in microscopy and genomics technologies. Computational methods have played a pivotal role in the structural interpretation of experimental data, which helped unravel some organizational principles of genome folding. Here, we give an overview of current computational efforts in mechanistic and data-driven 3D chromatin structure modeling. We discuss strengths and limitations of different methods and evaluate the added value and benefits of computational approaches to infer the 3D structural and dynamic properties of the genome and its underlying mechanisms at different scales and resolution, ranging from the dynamic formation of chromatin loops and topological associated domains to nuclear compartmentalization of chromatin and nuclear bodies.

Epigenetic-structural changes in X chromosomes promote Xic pairing during early differentiation of mouse embryonic stem cells

X chromosome inactivation center (Xic) pairing occurs during the differentiation of embryonic stem (ES) cells from female mouse embryos, and is related to X chromosome inactivation, the circadian clock, intra-nucleus architecture, and metabolism. However, the mechanisms underlying the identification and approach of X chromosome pairs in the crowded nucleus are unclear. To elucidate the driving force of Xic pairing, we developed a coarse-grained molecular dynamics model of intranuclear chromosomes in ES cells and in cells 2 days after the onset of differentiation (2-day cells) by considering intrachromosomal epigenetic-structural feature-dependent mechanics. The analysis of the experimental data showed that X-chromosomes exhibit the rearrangement of their distributions of open/closed chromatin regions on their surfaces during cell differentiation. By simulating models where the excluded volume effects of closed chromatin regions are stronger than those of open chromatin regions, such rearrangement of open/closed chromatin regions on X-chromosome surfaces promoted the mutual approach of the Xic pair. These findings suggested that local intrachromosomal epigenetic features may contribute to the regulation of cell species-dependent differences in intranuclear architecture.

Physical mechanisms of chromatin spatial organization

In higher eukaryotes, chromosomes have a complex three-dimensional (3D) conformation in the cell nucleus serving vital functional purposes, yet their folding principles remain poorly understood at the single-molecule level. Here, we summarize recent approaches from polymer physics to comprehend the physical mechanisms underlying chromatin architecture. In particular, we focus on two models that have been supported by recent, growing experimental evidence, the Loop Extrusion model and the Strings&Binders phase separation model. We discuss their key ingredients, how they compare to experimental data and some insight they provide on chromatin architecture and gene regulation. Progress in that research field are opening the possibility to predict how genomic mutations alter the network of contacts between genes and their regulators and how that is linked to genetic diseases, such as congenital disorders and cancer.

Integrative approaches in genome structure analysis

New technological advances in integrated imaging, sequencing-based assays, and computational analysis have revolutionized our view of genomes in terms of their structure and dynamics in space and time. These advances promise a deeper understanding of genome functions and mechanistic insights into how the nucleus is spatially organized and functions. These wide arrays of complementary data provide an opportunity to produce quantitative integrative models of nuclear organization. In this article, we highlight recent key developments and discuss the outlook for these fields.

ChromeBat: A Bio-Inspired Approach to 3D Genome Reconstruction

With the advent of Next Generation Sequencing and the Hi-C experiment, high quality genome-wide contact data are becoming increasingly available. These data represents an empirical measure of how a genome interacts inside the nucleus. Genome conformation is of particular interest as it has been experimentally shown to be a driving force for many genomic functions from regulation to transcription. Thus, the Three Dimensional-Genome Reconstruction Problem (3D-GRP) seeks to take Hi-C data and produces a complete physical genome structure as it appears in the nucleus for genomic analysis. We propose and develop a novel method to solve the Chromosome and Genome Reconstruction problem based on the Bat Algorithm (BA) which we called ChromeBat. We demonstrate on real Hi-C data that ChromeBat is capable of state-of-the-art performance. Additionally, the domain of Genome Reconstruction has been criticized for lacking algorithmic diversity, and the bio-inspired nature of ChromeBat contributes algorithmic diversity to the problem domain. ChromeBat is an effective approach for solving the Genome Reconstruction Problem.

Three-dimensional genome organization via triplex-forming RNAs

An increasing number of long noncoding RNAs (lncRNAs) have been proposed to act as nuclear organization factors during interphase. Direct RNA-DNA interactions can be achieved by the formation of triplex helix structures where a single-stranded RNA molecule hybridizes by complementarity into the major groove of double-stranded DNA. However, whether and how these direct RNA-DNA associations influence genome structure in interphase chromosomes remain poorly understood. Here we theorize that RNA organizes the genome in space via a triplex-forming mechanism. To test this theory, we apply a computational modeling approach of chromosomes that combines restraint-based modeling with polymer physics. Our models suggest that colocalization of triplex hotspots targeted by lncRNAs could contribute to large-scale chromosome compartmentalization cooperating, rather than competing, with architectural transcription factors such as CTCF.

Chromatin Conformation in Development and Disease

Chromatin domains and loops are important elements of chromatin structure and dynamics, but much remains to be learned about their exact biological role and nature. Topological associated domains and functional loops are key to gene expression and hold the answer to many questions regarding developmental decisions and diseases. Here, we discuss new findings, which have linked chromatin conformation with development, differentiation and diseases and hypothesized on various models while integrating all recent findings on how chromatin architecture affects gene expression during development, evolution and disease.

Chromatin Alterations in Neurological Disorders and Strategies of (Epi)Genome Rescue

Neurological disorders (NDs) comprise a heterogeneous group of conditions that affect the function of the nervous system. Often incurable, NDs have profound and detrimental consequences on the affected individuals' lives. NDs have complex etiologies but commonly feature altered gene expression and dysfunctions of the essential chromatin-modifying factors. Hence, compounds that target DNA and histone modification pathways, the so-called epidrugs, constitute promising tools to treat NDs. Yet, targeting the entire epigenome might reveal insufficient to modify a chosen gene expression or even unnecessary and detrimental to the patients' health. New technologies hold a promise to expand the clinical toolkit in the fight against NDs. (Epi)genome engineering using designer nucleases, including CRISPR-Cas9 and TALENs, can potentially help restore the correct gene expression patterns by targeting a defined gene or pathway, both genetically and epigenetically, with minimal off-target activity. Here, we review the implication of epigenetic machinery in NDs. We outline syndromes caused by mutations in chromatin-modifying enzymes and discuss the functional consequences of mutations in regulatory DNA in NDs. We review the approaches that allow modifying the (epi)genome, including tools based on TALENs and CRISPR-Cas9 technologies, and we highlight how these new strategies could potentially change clinical practices in the treatment of NDs.

Understanding 3D genome organization by multidisciplinary methods

Understanding how chromatin is folded in the nucleus is fundamental to understanding its function. Although 3D genome organization has been historically difficult to study owing to a lack of relevant methodologies, major technological breakthroughs in genome-wide mapping of chromatin contacts and advances in imaging technologies in the twenty-first century considerably improved our understanding of chromosome conformation and nuclear architecture. In this Review, we discuss methods of 3D genome organization analysis, including sequencing-based techniques, such as Hi-C and its derivatives, Micro-C, DamID and others; microscopy-based techniques, such as super-resolution imaging coupled with fluorescence in situ hybridization (FISH), multiplex FISH, in situ genome sequencing and live microscopy methods; and computational and modelling approaches. We describe the most commonly used techniques and their contribution to our current knowledge of nuclear architecture and, finally, we provide a perspective on up-and-coming methods that open possibilities for future major discoveries.

Multiscale modeling of genome organization with maximum entropy optimization

Three-dimensional (3D) organization of the human genome plays an essential role in all DNA-templated processes, including gene transcription, gene regulation, and DNA replication. Computational modeling can be an effective way of building high-resolution genome structures and improving our understanding of these molecular processes. However, it faces significant challenges as the human genome consists of over 6 × 109 base pairs, a system size that exceeds the capacity of traditional modeling approaches. In this perspective, we review the progress that has been made in modeling the human genome. Coarse-grained models parameterized to reproduce experimental data via the maximum entropy optimization algorithm serve as effective means to study genome organization at various length scales. They have provided insight into the principles of whole-genome organization and enabled de novo predictions of chromosome structures from epigenetic modifications. Applications of these models at a near-atomistic resolution further revealed physicochemical interactions that drive the phase separation of disordered proteins and dictate chromatin stability in situ. We conclude with an outlook on the opportunities and challenges in studying chromosome dynamics.

Tetranucleosome Interactions Drive Chromatin Folding

The multiscale organizational structure of chromatin in eukaryotic cells is instrumental to DNA transcription, replication, and repair. At mesoscopic length scales, nucleosomes pack in a manner that serves to regulate gene expression through condensation and expansion of the genome. The particular structures that arise and their respective thermodynamic stabilities, however, have yet to be fully resolved. In this study, we combine molecular modeling using the 1CPN mesoscale model of chromatin with nonlinear manifold learning to identify and characterize the structure and free energy of metastable states of short chromatin segments comprising between 4- and 16-nucleosomes. Our results reveal the formation of two previously characterized tetranucleosomal conformations, the "α-tetrahedron" and the "β-rhombus", which have been suggested to play an important role in the accessibility of DNA and, respectively, induce local chromatin compaction or elongation. The spontaneous formation of these motifs is potentially responsible for the slow nucleosome dynamics observed in experimental studies. Increases of the nucleosome repeat length are accompanied by more pronounced structural irregularity and flexibility and, ultimately, a dynamic liquid-like behavior that allows for frequent structural reorganization. Our findings indicate that tetranucleosome motifs are intrinsically stable structural states, driven by local internucleosomal interactions, and support a mechanistic picture of chromatin packing, dynamics, and accessibility that is strongly influenced by emergent local mesoscale structure.

Transcriptionally inactive hepatitis B virus episome DNA preferentially resides in the vicinity of chromosome 19 in 3D host genome upon infection

The hepatitis B virus (HBV) infects 257 million people worldwide. HBV infection requires establishment and persistence of covalently closed circular (ccc) DNA, a viral episome, in nucleus. Here, we study cccDNA spatial localization in the 3D host genome by using chromosome conformation capture-based sequencing analysis and fluorescence in situ hybridization (FISH). We show that transcriptionally inactive cccDNA is not randomly distributed in host nucleus. Rather, it is preferentially accumulated at specialized areas, including regions close to chromosome 19 (chr.19). Activation of the cccDNA is apparently associated with its re-localization, from a pre-established heterochromatin hub formed by 5 regions of chr.19 to transcriptionally active regions formed by chr.19 and nearby chromosomes including chr.16, 17, 20, and 22. This active versus inactive positioning at discrete regions of the host genome is primarily controlled by the viral HBx protein and by host factors including the structural maintenance of chromosomes protein 5/6 (SMC5/6) complex.

Application of Hi-C and other omics data analysis in human cancer and cell differentiation research

With the development of 3C (chromosome conformation capture) and its derivative technology Hi-C (High-throughput chromosome conformation capture) research, the study of the spatial structure of the genomic sequence in the nucleus helps researchers understand the functions of biological processes such as gene transcription, replication, repair, and regulation. In this paper, we first introduce the research background and purpose of Hi-C data visualization analysis. After that, we discuss the Hi-C data analysis methods from genome 3D structure, A/B compartment, TADs (topologically associated domain), and loop detection. We also discuss how to apply genome visualization technologies to the identification of chromosome feature structures. We continue with a review of correlation analysis differences among multi-omics data, and how to apply Hi-C and other omics data analysis into cancer and cell differentiation research. Finally, we summarize the various problems in joint analyses based on Hi-C and other multi-omics data. We believe this review can help researchers better understand the progress and applications of 3D genome technology.

3D reconstruction of genomic regions from sparse interaction data

Chromosome conformation capture (3C) technologies measure the interaction frequency between pairs of chromatin regions within the nucleus in a cell or a population of cells. Some of these 3C technologies retrieve interactions involving non-contiguous sets of loci, resulting in sparse interaction matrices. One of such 3C technologies is Promoter Capture Hi-C (pcHi-C) that is tailored to probe only interactions involving gene promoters. As such, pcHi-C provides sparse interaction matrices that are suitable to characterize short- and long-range enhancer-promoter interactions. Here, we introduce a new method to reconstruct the chromatin structural (3D) organization from sparse 3C-based datasets such as pcHi-C. Our method allows for data normalization, detection of significant interactions and reconstruction of the full 3D organization of the genomic region despite of the data sparseness. Specifically, it builds, with as low as the 2-3% of the data from the matrix, reliable 3D models of similar accuracy of those based on dense interaction matrices. Furthermore, the method is sensitive enough to detect cell-type-specific 3D organizational features such as the formation of different networks of active gene communities.

Computational approaches for inferring 3D conformations of chromatin from chromosome conformation capture data

Chromosome conformation capture (3C) and its variants are powerful experimental techniques for probing intra- and inter-chromosomal interactions within cell nuclei at high resolution and in a high-throughput, quantitative manner. The contact maps derived from such experiments provide an avenue for inferring the 3D spatial organization of the genome. This review provides an overview of the various computational methods developed in the past decade for addressing the very important but challenging problem of deducing the detailed 3D structure or structure population of chromosomal domains, chromosomes, and even entire genomes from 3C contact maps.

Inference of chromosome 3D structures from GAM data by a physics computational approach

The combination of modelling and experimental advances can provide deep insights for understanding chromatin 3D organization and ultimately its underlying mechanisms. In particular, models of polymer physics can help comprehend the complexity of genomic contact maps, as those emerging from technologies such as Hi-C, GAM or SPRITE. Here we discuss a method to reconstruct 3D structures from Genome Architecture Mapping (GAM) data, based on PRISMR, a computational approach introduced to find the minimal polymer model best describing Hi-C input data from only polymer physics. After recapitulating the PRISMR procedure, we describe how we extended it for treating GAM data. We successfully test the method on a 6 Mb region around the Sox9 gene and, at a lower resolution, on the whole chromosome 7 in mouse embryonic stem cells. The PRISMR derived 3D structures from GAM co-segregation data are finally validated against independent Hi-C contact maps. The method results to be versatile and robust, hinting that it can be similarly applied to different experimental data, such as SPRITE or microscopy distance data.

Network-based method for regions with statistically frequent interchromosomal interactions at single-cell resolution

BACKGROUND

Chromosome conformation capture-based methods, especially Hi-C, enable scientists to detect genome-wide chromatin interactions and study the spatial organization of chromatin, which plays important roles in gene expression regulation, DNA replication and repair etc. Thus, developing computational methods to unravel patterns behind the data becomes critical. Existing computational methods focus on intrachromosomal interactions and ignore interchromosomal interactions partly because there is no prior knowledge for interchromosomal interactions and the frequency of interchromosomal interactions is much lower while the search space is much larger. With the development of single-cell technologies, the advent of single-cell Hi-C makes interrogating the spatial structure of chromatin at single-cell resolution possible. It also brings a new type of frequency information, the number of single cells with chromatin interactions between two disjoint chromosome regions.

RESULTS

Considering the lack of computational methods on interchromosomal interactions and the unsurprisingly frequent intrachromosomal interactions along the diagonal of a chromatin contact map, we propose a computational method dedicated to analyzing interchromosomal interactions of single-cell Hi-C with this new frequency information. To the best of our knowledge, our proposed tool is the first to identify regions with statistically frequent interchromosomal interactions at single-cell resolution. We demonstrate that the tool utilizing networks and binomial statistical tests can identify interesting structural regions through visualization, comparison and enrichment analysis and it also supports different configurations to provide users with flexibility.

CONCLUSIONS

It will be a useful tool for analyzing single-cell Hi-C interchromosomal interactions.

Multi-contact 3C reveals that the human genome during interphase is largely not entangled

During interphase the eukaryotic genome is organized into chromosome territories that are spatially segregated into compartment domains. The extent to which interacting domains or chromosomes are entangled is not known. We analyze series of co-occurring chromatin interactions using multi-contact 3C (MC-3C) in human cells to provide insights into the topological entanglement of chromatin. Multi-contact interactions represent percolation paths (C-walks) through 3D chromatin space. We find that the order of interactions within C-walks that occur across interfaces where chromosomes or compartment domains interact is not random. Polymer simulations show that such C-walks are consistent with distal domains being topologically insulated, i.e. not catenated. Simulations show that even low levels of random strand passage, e.g. by topoisomerase II, would result in entanglements, increased mixing at domain interfaces and an order of interactions within C-walks not consistent with experimental MC-3C data. Our results indicate that during interphase entanglements between chromosomes and chromosomal domains are rare.

Analysis, Modeling, and Visualization of Chromosome Conformation Capture Experiments

Chromatin Conformation Capture techniques have unveiled several layers of chromosome organization such as the segregation in compartments, the folding in topologically associating domains (TADs), and site-specific looping interactions. The discovery of this genome hierarchical organization emerged from the computational analysis of chromatin capture data. With the increasing availability of such data, automatic pipelines for the robust comparison, grouping, and classification of multiple experiments are needed. Here we present a pipeline based on the TADbit framework that emphasizes reproducibility, automation, quality check, and statistical robustness. This comprehensive modular pipeline covers all the steps from the sequencing products to the visualization of reconstructed 3D models of the chromatin.

SCL: a lattice-based approach to infer 3D chromosome structures from single-cell Hi-C data

MOTIVATION

In contrast to population-based Hi-C data, single-cell Hi-C data are zero-inflated and do not indicate the frequency of proximate DNA segments. There are a limited number of computational tools that can model the 3D structures of chromosomes based on single-cell Hi-C data.

RESULTS

We developed single-cell lattice (SCL), a computational method to reconstruct 3D structures of chromosomes based on single-cell Hi-C data. We designed a loss function and a 2 D Gaussian function specifically for the characteristics of single-cell Hi-C data. A chromosome is represented as beads-on-a-string and stored in a 3 D cubic lattice. Metropolis-Hastings simulation and simulated annealing are used to simulate the structure and minimize the loss function. We evaluated the SCL-inferred 3 D structures (at both 500 and 50 kb resolutions) using multiple criteria and compared them with the ones generated by another modeling software program. The results indicate that the 3 D structures generated by SCL closely fit single-cell Hi-C data. We also found similar patterns of trans-chromosomal contact beads, Lamin-B1 enriched topologically associating domains (TADs), and H3K4me3 enriched TADs by mapping data from previous studies onto the SCL-inferred 3 D structures.

AVAILABILITY AND IMPLEMENTATION

The C++ source code of SCL is freely available at http://dna.cs.miami.edu/SCL/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Mechanistic modeling of chromatin folding to understand function

Experimental approaches have been applied to address questions in understanding three-dimensional chromatin organization and function. As datasets increase in size and complexity, it becomes a challenge to reach a mechanistic interpretation of experimental results. Polymer simulations and mechanistic modeling have been applied to explain experimental observations and their links to different aspects of genome function. Here we provide a guide for biologists, explaining different simulation approaches and the contexts in which they have been used.

IGAP-integrative genome analysis pipeline reveals new gene regulatory model associated with nonspecific TF-DNA binding affinity

The human genome is regulated in a multi-dimensional way. While biophysical factors like Non-specific Transcription factor Binding Affinity (nTBA) act at DNA sequence level, other factors act above sequence levels such as histone modifications and 3-D chromosomal interactions. This multidimensionality of regulation requires many of these factors for a proper understanding of the regulatory landscape of the human genome. Here, we propose a new biophysical model for estimating nTBA. Integration of nTBA with chromatin modifications and chromosomal interactions, using a new Integrative Genome Analysis Pipeline (IGAP), reveals additive effects of nTBA to regulatory DNA sequences and identifies three types of genomic zones in the human genome (Inactive Genomic Zones, Poised Genomic Zones, and Active Genomic Zones). It also unveils a novel long distance gene regulatory model: chromosomal interactions reduce the physical distance between the high occupancy target (HOT) regions that results in high nTBA to DNA in the area, which in turn attract TFs to such regions with higher binding potential. These findings will help to elucidate the three-dimensional diffusion process that TFs use during their search for the right targets.

Transcriptional activation during cell reprogramming correlates with the formation of 3D open chromatin hubs

Chromosome structure is a crucial regulatory factor for a wide range of nuclear processes. Chromosome conformation capture (3C)-based experiments combined with computational modelling are pivotal for unveiling 3D chromosome structure. Here, we introduce TADdyn, a tool that integrates time-course 3C data, restraint-based modelling, and molecular dynamics to simulate the structural rearrangements of genomic loci in a completely data-driven way. We apply TADdyn on in situ Hi-C time-course experiments studying the reprogramming of murine B cells to pluripotent cells, and characterize the structural rearrangements that take place upon changes in the transcriptional state of 21 genomic loci of diverse expression dynamics. By measuring various structural and dynamical properties, we find that during gene activation, the transcription starting site contacts with open and active regions in 3D chromatin domains. We propose that these 3D hubs of open and active chromatin may constitute a general feature to trigger and maintain gene transcription.

Computing 3D Chromatin Configurations from Contact Probability Maps by Inverse Brownian Dynamics

The three-dimensional (3D) organization of chromatin, on the length scale of a few genes, is crucial in determining the functional state-accessibility and amount of gene expression-of the chromatin. Recent advances in chromosome conformation capture experiments provide partial information on the chromatin organization in a cell population, namely the contact count between any segment pairs, but not on the interaction strength that leads to these contact counts. However, given the contact matrix, determining the complete 3D organization of the whole chromatin polymer is an inverse problem. In this work, a novel inverse Brownian dynamics method based on a coarse-grained bead-spring chain model has been proposed to compute the optimal interaction strengths between different segments of chromatin such that the experimentally measured contact count probability constraints are satisfied. Applying this method to the α-globin gene locus in two different cell types, we predict the 3D organizations corresponding to active and repressed states of chromatin at the locus. We show that the average distance between any two segments of the region has a broad distribution and cannot be computed as a simple inverse relation based on the contact probability alone. The results presented for multiple normalization methods suggest that all measurable quantities may crucially depend on the nature of normalization. We argue that by experimentally measuring predicted quantities, one may infer the appropriate form of normalization.

4D Genome Rewiring during Oncogene-Induced and Replicative Senescence

To understand the role of the extensive senescence-associated 3D genome reorganization, we generated genome-wide chromatin interaction maps, epigenome, replication-timing, whole-genome bisulfite sequencing, and gene expression profiles from cells entering replicative senescence (RS) or upon oncogene-induced senescence (OIS). We identify senescence-associated heterochromatin domains (SAHDs). Differential intra- versus inter-SAHD interactions lead to the formation of senescence-associated heterochromatin foci (SAHFs) in OIS but not in RS. This OIS-specific configuration brings active genes located in genomic regions adjacent to SAHDs in close spatial proximity and favors their expression. We also identify DNMT1 as a factor that induces SAHFs by promoting HMGA2 expression. Upon DNMT1 depletion, OIS cells transition to a 3D genome conformation akin to that of cells in replicative senescence. These data show how multi-omics and imaging can identify critical features of RS and OIS and discover determinants of acute senescence and SAHF formation.

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Deep multi-omics characterization of replicative and oncogene-induced senescence

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Senescence-associated heterochromatin domains (SAHDs) form SAHFs via 3D changes

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DNMT1 is required for SAHF formation via regulation of HMGA2 expression

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SAHF formation leads to expression of SAHF-adjacent genes via 3D chromatin contacts

Principles for Integrative Structural Biology Studies

Integrative structure determination is a powerful approach to modeling the structures of biological systems based on data produced by multiple experimental and theoretical methods, with implications for our understanding of cellular biology and drug discovery. This Primer introduces the theory and methods of integrative approaches, emphasizing the kinds of data that can be effectively included in developing models and using the nuclear pore complex as an example to illustrate the practice and challenges involved. These guidelines are intended to aid the researcher in understanding and applying integrative structural methods to systems of their interest and thus take advantage of this rapidly evolving field.

Chromosome Conformation Capture and Beyond: Toward an Integrative View of Chromosome Structure and Function

Rapidly developing technologies have recently fueled an exciting era of discovery in the field of chromosome structure and nuclear organization. In addition to chromosome conformation capture (3C) methods, new alternative techniques have emerged to study genome architecture and biological processes in the nucleus, often in single or living cells. This sets an unprecedented stage for exploring the mechanisms that link chromosome structure and biological function. Here we review popular as well as emerging approaches to study chromosome organization, focusing on the contribution of complementary methodologies to our understanding of structures revealed by 3C methods and their biological implications, and discuss the next technical and conceptual frontiers.

A Dynamic Folded Hairpin Conformation Is Associated with α-Globin Activation in Erythroid Cells

We investigate the three-dimensional (3D) conformations of the α-globin locus at the single-allele level in murine embryonic stem cells (ESCs) and erythroid cells, combining polymer physics models and high-resolution Capture-C data. Model predictions are validated against independent fluorescence in situ hybridization (FISH) data measuring pairwise distances, and Tri-C data identifying three-way contacts. The architecture is rearranged during the transition from ESCs to erythroid cells, associated with the activation of the globin genes. We find that in ESCs, the spatial organization conforms to a highly intermingled 3D structure involving non-specific contacts, whereas in erythroid cells the α-globin genes and their enhancers form a self-contained domain, arranged in a folded hairpin conformation, separated from intermingling flanking regions by a thermodynamic mechanism of micro-phase separation. The flanking regions are rich in convergent CTCF sites, which only marginally participate in the erythroid-specific gene-enhancer contacts, suggesting that beyond the interaction of CTCF sites, multiple molecular mechanisms cooperate to form an interacting domain.

In silico prediction of high-resolution Hi-C interaction matrices

The three-dimensional (3D) organization of the genome plays an important role in gene regulation bringing distal sequence elements in 3D proximity to genes hundreds of kilobases away. Hi-C is a powerful genome-wide technique to study 3D genome organization. Owing to experimental costs, high resolution Hi-C datasets are limited to a few cell lines. Computational prediction of Hi-C counts can offer a scalable and inexpensive approach to examine 3D genome organization across multiple cellular contexts. Here we present HiC-Reg, an approach to predict contact counts from one-dimensional regulatory signals. HiC-Reg predictions identify topologically associating domains and significant interactions that are enriched for CCCTC-binding factor (CTCF) bidirectional motifs and interactions identified from complementary sources. CTCF and chromatin marks, especially repressive and elongation marks, are most important for HiC-Reg’s predictive performance. Taken together, HiC-Reg provides a powerful framework to generate high-resolution profiles of contact counts that can be used to study individual locus level interactions and higher-order organizational units of the genome.

Existing computational approaches to predict long-range regulatory interactions do not fully exploit high-resolution Hi-C datasets. Here the authors present a Random Forests regression-based approach to predict high-resolution Hi-C counts using one-dimensional regulatory genomic signals.

Inferring the three-dimensional structures of the X-chromosome during X-inactivation

The Hi-C experiment can capture the genome-wide spatial proximities of the DNA, based on which it is possible to computationally reconstruct the three-dimensional (3D) structures of chromosomes. The transcripts of the long non-coding RNA (lncRNA) Xist spread throughout the entire X-chromosome and alter the 3D structure of the X-chromosome, which also inactivates one copy of the two X-chromosomes in a cell. The Hi-C experiments are expensive and time-consuming to conduct, but the Hi-C data of the active and inactive X-chromosomes are available. However, the Hi-C data of the X-chromosome during the process of X-chromosome inactivation (XCI) are not available. Therefore, the 3D structure of the X-chromosome during the process of X-chromosome inactivation (XCI) remains to be unknown. We have developed a new approach to reconstruct the 3D structure of the X-chromosome during XCI, in which the chain of DNA beads representing a chromosome is stored and simulated inside a 3D cubic lattice. A 2D Gaussian function is used to model the zero values in the 2D Hi-C contact matrices. By applying simulated annealing and Metropolis-Hastings simulations, we first generated the 3D structures of the X-chromosome before and after XCI. Then, we used Xist localization intensities on the X-chromosome (RAP data) to model the traveling speeds or acceleration between all bead pairs during the process of XCI. The 3D structures of the X-chromosome at 3 hours, 6 hours, and 24 hours after the start of the Xist expression, which initiates the XCI process, have been reconstructed. The source code and the reconstructed 3D structures of the X-chromosome can be downloaded from http://dna.cs.miami.edu/3D-XCI/.

High-resolution 3D models of Caulobacter crescentus chromosome reveal genome structural variability and organization

High-resolution three-dimensional models of Caulobacter crescentus nucleoid structures were generated via a multi-scale modeling protocol. Models were built as a plectonemically supercoiled circular DNA and by incorporating chromosome conformation capture based data to generate an ensemble of base pair resolution models consistent with the experimental data. Significant structural variability was found with different degrees of bending and twisting but with overall similar topologies and shapes that are consistent with C. crescentus cell dimensions. The models allowed a direct mapping of the genomic sequence onto the three-dimensional nucleoid structures. Distinct spatial distributions were found for several genomic elements such as AT-rich sequence elements where nucleoid associated proteins (NAPs) are likely to bind, promoter sites, and some genes with common cellular functions. These findings shed light on the correlation between the spatial organization of the genome and biological functions.

Reconstructing spatial organizations of chromosomes through manifold learning

Decoding the spatial organizations of chromosomes has crucial implications for studying eukaryotic gene regulation. Recently, chromosomal conformation capture based technologies, such as Hi-C, have been widely used to uncover the interaction frequencies of genomic loci in a high-throughput and genome-wide manner and provide new insights into the folding of three-dimensional (3D) genome structure. In this paper, we develop a novel manifold learning based framework, called GEM (Genomic organization reconstructor based on conformational Energy and Manifold learning), to reconstruct the three-dimensional organizations of chromosomes by integrating Hi-C data with biophysical feasibility. Unlike previous methods, which explicitly assume specific relationships between Hi-C interaction frequencies and spatial distances, our model directly embeds the neighboring affinities from Hi-C space into 3D Euclidean space. Extensive validations demonstrated that GEM not only greatly outperformed other state-of-art modeling methods but also provided a physically and physiologically valid 3D representations of the organizations of chromosomes. Furthermore, we for the first time apply the modeled chromatin structures to recover long-range genomic interactions missing from original Hi-C data.

Heterogeneous Loop Model to Infer 3D Chromosome Structures from Hi-C

Adapting a well-established formalism in polymer physics, we develop a minimalist approach to infer three-dimensional folding of chromatin from Hi-C data. The three-dimensional chromosome structures generated from our heterogeneous loop model (HLM) are used to visualize chromosome organizations that can substantiate the measurements from fluorescence in situ hybridization, chromatin interaction analysis by paired-end tag sequencing, and RNA-seq signals. We demonstrate the utility of the HLM with several case studies. Specifically, the HLM-generated chromosome structures, which reproduce the spatial distribution of topologically associated domains from fluorescence in situ hybridization measurement, show the phase segregation between two types of topologically associated domains explicitly. We discuss the origin of cell-type-dependent gene-expression level by modeling the chromatin globules of α-globin and SOX2 gene loci for two different cell lines. We also use the HLM to discuss how the chromatin folding and gene-expression level of Pax6 loci, associated with mouse neural development, are modulated by interactions with two enhancers. Finally, HLM-generated structures of chromosome 19 of mouse embryonic stem cells, based on single-cell Hi-C data collected over each cell-cycle phase, visualize changes in chromosome conformation along the cell-cycle. Given a contact frequency map between chromatic loci supplied from Hi-C, HLM is a computationally efficient and versatile modeling tool to generate chromosome structures that can complement interpreting other experimental data.

Models of polymer physics for the architecture of the cell nucleus

The depth and complexity of data now available on chromosome 3D architecture, derived by new technologies such as Hi-C, have triggered the development of models based on polymer physics to explain the observed patterns and the underlying molecular folding mechanisms. Here, we give an overview of some of the ideas and models from physics introduced to date, along with their progresses and limitations in the description of experimental data. In particular, we focus on the Strings&Binders and the Loop Extrusion model of chromatin architecture. This article is categorized under: Analytical and Computational Methods > Computational Methods.

Archiving and disseminating integrative structure models

Limitations in the applicability, accuracy, and precision of individual structure characterization methods can sometimes be overcome via an integrative modeling approach that relies on information from all available sources, including all available experimental data and prior models. The open-source Integrative Modeling Platform (IMP) is one piece of software that implements all computational aspects of integrative modeling. To maximize the impact of integrative structures, the coordinates should be made publicly available, as is already the case for structures based on X-ray crystallography, NMR spectroscopy, and electron microscopy. Moreover, the associated experimental data and modeling protocols should also be archived, such that the original results can easily be reproduced. Finally, it is essential that the integrative structures are validated as part of their publication and deposition. A number of research groups have already developed software to implement integrative modeling and have generated a number of structures, prompting the formation of an Integrative/Hybrid Methods Task Force. Following the recommendations of this task force, the existing PDBx/mmCIF data representation used for atomic PDB structures has been extended to address the requirements for archiving integrative structural models. This IHM-dictionary adds a flexible model representation, including coarse graining, models in multiple states and/or related by time or other order, and multiple input experimental information sources. A prototype archiving system called PDB-Dev ( https://pdb-dev.wwpdb.org ) has also been created to archive integrative structural models, together with a Python library to facilitate handling of integrative models in PDBx/mmCIF format.

Human pancreatic islet three-dimensional chromatin architecture provides insights into the genetics of type 2 diabetes

Genetic studies promise to provide insight into the molecular mechanisms underlying type 2 diabetes (T2D). Variants associated with T2D are often located in tissue-specific enhancer clusters or super-enhancers. So far, such domains have been defined through clustering of enhancers in linear genome maps rather than in three-dimensional (3D) space. Furthermore, their target genes are often unknown. We have created promoter capture Hi-C maps in human pancreatic islets. This linked diabetes-associated enhancers to their target genes, often located hundreds of kilobases away. It also revealed >1,300 groups of islet enhancers, super-enhancers and active promoters that form 3D hubs, some of which show coordinated glucose-dependent activity. We demonstrate that genetic variation in hubs impacts insulin secretion heritability, and show that hub annotations can be used for polygenic scores that predict T2D risk driven by islet regulatory variants. Human islet 3D chromatin architecture, therefore, provides a framework for interpretation of T2D genome-wide association study (GWAS) signals.

C-TALE, a new cost-effective method for targeted enrichment of Hi-C/3C-seq libraries

Studies performed using Hi-C and other high-throughput whole-genome C-methods have demonstrated that 3D organization of eukaryotic genomes is functionally relevant. Unfortunately, ultra-deep sequencing of Hi-C libraries necessary to detect loop structures in large vertebrate genomes remains rather expensive. However, many studies are in fact aimed at determining the fine-scale 3D structure of comparatively small genomic regions up to several Mb in length. Such studies typically focus on the spatial structure of domains of coregulated genes, molecular mechanisms of loop formation, and interrogation of functional significance of GWAS-revealed polymorphisms. Therefore, a handful of molecular techniques based on Hi-C have been developed to address such issues. These techniques commonly rely on in-solution hybridization of Hi-C/3C-seq libraries with pools of biotinylated baits covering the region of interest, followed by deep sequencing of the enriched library. Here, we describe a new protocol of this kind, C-TALE (Chromatin TArget Ligation Enrichment). Preparation of hybridization probes from bacterial artificial chromosomes and an additional round of enrichment make C-TALE a cost-effective alternative to existing many-versus-all C-methods.