3D structures of individual mammalian genomes studied by single-cell Hi-C

Chromatin Remodelers in the 3D Nuclear Compartment

Chromatin remodeling complexes (CRCs) use ATP hydrolysis to maintain correct expression profiles, chromatin stability, and inherited epigenetic states. More than 20 CRCs have been described to date, which encompass four large families defined by their ATPase subunits. These complexes and their subunits are conserved from yeast to humans through evolution. Their activities depend on their catalytic subunits which through ATP hydrolysis provide the energy necessary to fulfill cellular functions such as gene transcription, DNA repair, and transposon silencing. These activities take place at the first levels of chromatin compaction, and CRCs have been recognized as essential elements of chromatin dynamics. Recent studies have demonstrated an important role for these complexes in the maintenance of higher order chromatin structure. In this review, we present an overview of the organization of the genome within the cell nucleus, the different levels of chromatin compaction, and importance of the architectural proteins, and discuss the role of CRCs and how their functions contribute to the dynamics of the 3D genome organization.

Regulation of single-cell genome organization into TADs and chromatin nanodomains

The genome folds into a hierarchy of three-dimensional structures within the nucleus. At the sub-megabase scale, chromosomes form topologically associating domains (TADs)1-4. However, how TADs fold in single cells is elusive. Here, we reveal TAD features inaccessible to cell population analysis by using super-resolution microscopy. TAD structures and physical insulation associated with their borders are variable between individual cells, yet chromatin intermingling is enriched within TADs compared to adjacent TADs in most cells. The spatial segregation of TADs is further exacerbated during cell differentiation. Favored interactions within TADs are regulated by cohesin and CTCF through distinct mechanisms: cohesin generates chromatin contacts and intermingling while CTCF prevents inter-TAD contacts. Furthermore, TADs are subdivided into discrete nanodomains, which persist in cells depleted of CTCF or cohesin, whereas disruption of nucleosome contacts alters their structural organization. Altogether, these results provide a physical basis for the folding of individual chromosomes at the nanoscale.

How chromosome topologies get their shape: views from proximity ligation and microscopy methods

The 3D organization of our genome is an important determinant for the transcriptional output of a gene in (patho)physiological contexts. The spatial organization of linear chromosomes within nucleus is dominantly inferred using two distinct approaches, chromosome conformation capture (3C) and DNA fluorescent in situ hybridization (DNA-FISH). While 3C and its derivatives score genomic interaction frequencies based on proximity ligation events, DNA-FISH methods measure physical distances between genomic loci. Despite these approaches probe different characteristics of chromosomal topologies, they provide a coherent picture of how chromosomes are organized in higher-order structures encompassing chromosome territories, compartments, and topologically associating domains. Yet, at the finer topological level of promoter-enhancer communication, the imaging-centered and the 3C methods give more divergent and sometimes seemingly paradoxical results. Here, we compare and contrast observations made applying visual DNA-FISH and molecular 3C approaches. We emphasize that the 3C approach, due to its inherently competitive ligation step, measures only 'relative' proximities. A 3C interaction enriched between loci, therefore does not necessarily translates into a decrease in absolute spatial distance. Hence, we advocate caution when modeling chromosome conformations.

Exploring chromosomal structural heterogeneity across multiple cell lines

Using computer simulations, we generate cell-specific 3D chromosomal structures and compare them to recently published chromatin structures obtained through microscopy. We demonstrate using machine learning and polymer physics simulations that epigenetic information can be used to predict the structural ensembles of multiple human cell lines. Theory predicts that chromosome structures are fluid and can only be described by an ensemble, which is consistent with the observation that chromosomes exhibit no unique fold. Nevertheless, our analysis of both structures from simulation and microscopy reveals that short segments of chromatin make two-state transitions between closed conformations and open dumbbell conformations. Finally, we study the conformational changes associated with the switching of genomic compartments observed in human cell lines. The formation of genomic compartments resembles hydrophobic collapse in protein folding, with the aggregation of denser and predominantly inactive chromatin driving the positioning of active chromatin toward the surface of individual chromosomal territories.

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.

Single-Cell Genomics and Epigenomics: Technologies and Applications in Plants

The development of genomics and epigenomics has allowed rapid advances in our understanding of plant biology. However, conventional bulk analysis dilutes cell-specific information by providing only average information, thereby limiting the resolution of genomic and functional genomic studies. Recent advances in single-cell sequencing technology concerning genomics and epigenomics open new avenues to dissect cell heterogeneity in multiple biological processes. Recent applications of these approaches to plants have provided exciting insights into diverse biological questions. We highlight the methodologies underlying the current techniques of single-cell genomics and epigenomics before covering their recent applications, potential significance, and future perspectives in plant biology.

The Self-Organizing Genome: Principles of Genome Architecture and Function

Genomes have complex three-dimensional architectures. The recent convergence of genetic, biochemical, biophysical, and cell biological methods has uncovered several fundamental principles of genome organization. They highlight that genome function is a major driver of genome architecture and that structural features of chromatin act as modulators, rather than binary determinants, of genome activity. The interplay of these principles in the context of self-organization can account for the emergence of structural chromatin features, the diversity and single-cell heterogeneity of nuclear architecture in cell types and tissues, and explains evolutionarily conserved functional features of genomes, including plasticity and robustness.

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.

Capturing cell type-specific chromatin compartment patterns by applying topic modeling to single-cell Hi-C data

Single-cell Hi-C (scHi-C) interrogates genome-wide chromatin interaction in individual cells, allowing us to gain insights into 3D genome organization. However, the extremely sparse nature of scHi-C data poses a significant barrier to analysis, limiting our ability to tease out hidden biological information. In this work, we approach this problem by applying topic modeling to scHi-C data. Topic modeling is well-suited for discovering latent topics in a collection of discrete data. For our analysis, we generate nine different single-cell combinatorial indexed Hi-C (sci-Hi-C) libraries from five human cell lines (GM12878, H1Esc, HFF, IMR90, and HAP1), consisting over 19,000 cells. We demonstrate that topic modeling is able to successfully capture cell type differences from sci-Hi-C data in the form of “chromatin topics.” We further show enrichment of particular compartment structures associated with locus pairs in these topics.

The genomes of higher organisms are intricately folded and organized in a dynamic manner that has strong implications for many biological processes. Each chromosome undergoes dramatic changes to their three dimensional conformation during the cell cycle, whereas the positioning of chromosomes within the nucleus plays an important role in controlling the activation of specific genes. Recently, it has become possible to investigate the 3D conformations of the genomes of individual cells using a high throughput sequencing assay called single cell Hi-C (scHi-C). However, data from these assays are sparse and noisy, making analysis and interpretation of scHi-C data challenging. In this work, we generated a scHi-C dataset of over 19,000 cells from five human cell lines and applied a natural language processing method called topic modeling to discover cell type-specific “chromatin” topics. We show that these topics can be used to distinguish between cells at different stages of the cell cycle and cells from different tissues based on the 3D conformation of their genomes, despite the sparsity of the data. We further show that the 3D conformations of single cells are linked to the expression of cell type-specific genes and to cell cycle-associated conformational patterns.

Advances in Chromatin and Chromosome Research: Perspectives from Multiple Fields

Nucleosomes package genomic DNA into chromatin. By regulating DNA access for transcription, replication, DNA repair, and epigenetic modification, chromatin forms the nexus of most nuclear processes. In addition, dynamic organization of chromatin underlies both regulation of gene expression and evolution of chromosomes into individualized sister objects, which can segregate cleanly to different daughter cells at anaphase. This collaborative review shines a spotlight on technologies that will be crucial to interrogate key questions in chromatin and chromosome biology including state-of-the-art microscopy techniques, tools to physically manipulate chromatin, single-cell methods to measure chromatin accessibility, computational imaging with neural networks and analytical tools to interpret chromatin structure and dynamics. In addition, this review provides perspectives on how these tools can be applied to specific research fields such as genome stability and developmental biology and to test concepts such as phase separation of chromatin.

Genome-Scale Imaging of the 3D Organization and Transcriptional Activity of Chromatin

The 3D organization of chromatin regulates many genome functions. Our understanding of 3D genome organization requires tools to directly visualize chromatin conformation in its native context. Here we report an imaging technology for visualizing chromatin organization across multiple scales in single cells with high genomic throughput. First we demonstrate multiplexed imaging of hundreds of genomic loci by sequential hybridization, which allows high-resolution conformation tracing of whole chromosomes. Next we report a multiplexed error-robust fluorescence in situ hybridization (MERFISH)-based method for genome-scale chromatin tracing and demonstrate simultaneous imaging of more than 1,000 genomic loci and nascent transcripts of more than 1,000 genes together with landmark nuclear structures. Using this technology, we characterize chromatin domains, compartments, and trans-chromosomal interactions and their relationship to transcription in single cells. We envision broad application of this high-throughput, multi-scale, and multi-modal imaging technology, which provides an integrated view of chromatin organization in its native structural and functional context.

Network Approaches for Dissecting the Immune System

The immune system is a complex biological network composed of hierarchically organized genes, proteins, and cellular components that combat external pathogens and monitor the onset of internal disease. To meet and ultimately defeat these challenges, the immune system orchestrates an exquisitely complex interplay of numerous cells, often with highly specialized functions, in a tissue-specific manner. One of the major methodologies of systems immunology is to measure quantitatively the components and interaction levels in the immunologic networks to construct a computational network and predict the response of the components to perturbations. The recent advances in high-throughput sequencing techniques have provided us with a powerful approach to dissecting the complexity of the immune system. Here we summarize the latest progress in integrating omics data and network approaches to construct networks and to infer the underlying signaling and transcriptional landscape, as well as cell-cell communication, in the immune system, with a focus on hematopoiesis, adaptive immunity, and tumor immunology. Understanding the network regulation of immune cells has provided new insights into immune homeostasis and disease, with important therapeutic implications for inflammation, cancer, and other immune-mediated disorders.

Plant and animal chromatin three-dimensional organization: similar structures but different functions

Chromatin is the main carrier of genetic information and is non-randomly distributed within the nucleus. Next-generation sequence-based chromatin conformation capture technologies have enabled us to directly examine its three-dimensional organization at an unprecedented scale and resolution. In the best-studied mammalian models, chromatin folding can be broken down into three hierarchical levels, compartment, domains, and loops, which play important roles in transcriptional regulation. Although similar structures have now been identified in plants, they might not possess exactly the same functions as the mammalian ones. Here, we review recent Hi-C studies in plants, compare plant chromatin structures with their mammalian counterparts, and discuss the differences between plants with different genome sizes.

Genomic Cytometry and New Modalities for Deep Single-Cell Interrogation

In the past few years, the rapid development of single-cell analysis techniques has allowed for increasingly in-depth analysis of DNA, RNA, protein, and epigenetic states, at the level of the individual cell. This unprecedented characterization ability has been enabled through the combination of cytometry, microfluidics, genomics, and informatics. Although traditionally discrete, when properly integrated, these fields create the synergistic field of Genomic Cytometry. In this review, we look at the individual methods that together gave rise to the broad field of Genomic Cytometry. We further outline the basic concepts that drive the field and provide a framework to understand this increasingly complex, technology-intensive space. Thus, we introduce Genomic Cytometry as an emerging field and propose that synergistic rationalization of disparate modalities of cytometry, microfluidics, genomics, and informatics under one banner will enable massive leaps forward in the understanding of complex biology. © 2020 International Society for Advancement of Cytometry.

Diploid genome architecture revealed by multi-omic data of hybrid mice

Although mammalian genomes are diploid, previous studies extensively investigated the average chromatin architectures without considering the differences between homologous chromosomes. We generated Hi-C, ChIP-seq, and RNA-seq data sets from CD4 T cells of B6, Cast, and hybrid mice, to investigate the diploid chromatin organization and epigenetic regulation. Our data indicate that inter-chromosomal interaction patterns between homologous chromosomes are similar, and the similarity is highly correlated with their allelic coexpression levels. Reconstruction of the 3D nucleus revealed that distances of the homologous chromosomes to the center of nucleus are almost the same. The inter-chromosomal interactions at centromere ends are significantly weaker than those at telomere ends, suggesting that they are located in different regions within the chromosome territories. The majority of A|B compartments or topologically associated domains (TADs) are consistent between B6 and Cast. We found 58% of the haploids in hybrids maintain their parental compartment status at B6/Cast divergent compartments owing to cis effect. About 95% of the trans-effected B6/Cast divergent compartments converge to the same compartment status potentially because of a shared cellular environment. We showed the differentially expressed genes between the two haploids in hybrid were associated with either genetic or epigenetic effects. In summary, our multi-omics data from the hybrid mice provided haploid-specific information on the 3D nuclear architecture and a rich resource for further understanding the epigenetic regulation of haploid-specific gene expression.

Chd4 choreographs self-antigen expression for central immune tolerance

Autoreactive T cells are eliminated in the thymus to prevent autoimmunity by promiscuous expression of tissue-restricted self-antigens in medullary thymic epithelial cells. This expression is dependent on the transcription factor Fezf2, as well as the transcriptional regulator Aire, but the entire picture of the transcriptional program has been obscure. Here, we found that the chromatin remodeler Chd4, also called Mi-2β, plays a key role in the self-antigen expression in medullary thymic epithelial cells. To maximize the diversity of self-antigen expression, Fezf2 and Aire utilized completely distinct transcriptional mechanisms, both of which were under the control of Chd4. Chd4 organized the promoter regions of Fezf2-dependent genes, while contributing to the Aire-mediated induction of self-antigens via super-enhancers. Mice deficient in Chd4 specifically in thymic epithelial cells exhibited autoimmune phenotypes, including T cell infiltration. Thus, Chd4 plays a critical role in integrating Fezf2- and Aire-mediated gene induction to establish central immune tolerance.

Cancer systems immunology

Tumor immunology is undergoing a renaissance due to the recent profound clinical successes of tumor immunotherapy. These advances have coincided with an exponential growth in the development of -omics technologies. Armed with these technologies and their associated computational and modeling toolsets, systems biologists have turned their attention to tumor immunology in an effort to understand the precise nature and consequences of interactions between tumors and the immune system. Such interactions are inherently multivariate, spanning multiple time and size scales, cell types, and organ systems, rendering systems biology approaches particularly amenable to their interrogation. While in its infancy, the field of 'Cancer Systems Immunology' has already influenced our understanding of tumor immunology and immunotherapy. As the field matures, studies will move beyond descriptive characterizations toward functional investigations of the emergent behavior that govern tumor-immune responses. Thus, Cancer Systems Immunology holds incredible promise to advance our ability to fight this disease.

Polymer physics indicates chromatin folding variability across single-cells results from state degeneracy in phase separation

The spatial organization of chromosomes has key functional roles, yet how chromosomes fold remains poorly understood at the single-molecule level. Here, we employ models of polymer physics to investigate DNA loci in human HCT116 and IMR90 wild-type and cohesin depleted cells. Model predictions on single-molecule structures are validated against single-cell imaging data, providing evidence that chromosomal architecture is controlled by a thermodynamics mechanism of polymer phase separation whereby chromatin self-assembles in segregated globules by combinatorial interactions of chromatin factors that include CTCF and cohesin. The thermodynamics degeneracy of single-molecule conformations results in broad structural and temporal variability of TAD-like contact patterns. Globules establish stable environments where specific contacts are highly favored over stochastic encounters. Cohesin depletion reverses phase separation into randomly folded states, erasing average interaction patterns. Overall, globule phase separation appears to be a robust yet reversible mechanism of chromatin organization where stochasticity and specificity coexist.

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.

Stable H3K4me3 is associated with transcription initiation during early embryo development

MOTIVATION

During development of the mammalian embryo, histone modification H3K4me3 plays an important role in regulating gene expression and exhibits extensive reprograming on the parental genomes. In addition to these dramatic epigenetic changes, certain unchanging regulatory elements are also essential for embryonic development.

RESULTS

Using large-scale H3K4me3 chromatin immunoprecipitation sequencing data, we identified a form of H3K4me3 that was present during all eight stages of the mouse embryo before implantation. This 'stable H3K4me3' was highly accessible and much longer than normal H3K4me3. Moreover, most of the stable H3K4me3 was in the promoter region and was enriched in higher chromatin architecture. Using in-depth analysis, we demonstrated that stable H3K4me3 was related to higher gene expression levels and transcriptional initiation during embryonic development. Furthermore, stable H3K4me3 was much more active in blood tumor cells than in normal blood cells, suggesting a potential mechanism of cancer progression.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

90 YEARS OF PROGESTERONE: Molecular mechanisms of progesterone receptor action on the breast cancer genome

Gene regulation by steroid hormones has been at the forefront in elucidating the intricacies of transcriptional regulation in eukaryotes ever since the discovery by Karlson and Clever that the insect steroid hormone ecdysone induces chromatin puffs in giant chromosomes. After the successful cloning of the hormone receptors toward the end of the past century, detailed mechanistic insight emerged in some model systems, in particular the MMTV provirus. With the arrival of next generation DNA sequencing and the omics techniques, we have gained even further insight into the global cellular response to steroid hormones that in the past decades also extended to the function of the 3D genome topology. More recently, advances in high resolution microcopy, single cell genomics and the new vision of liquid-liquid phase transitions in the context of nuclear space bring us closer than ever to unravelling the logic of gene regulation and its complex integration of global cellular signaling networks. Using the function of progesterone and its cellular receptor in breast cancer cells, we will briefly summarize the history and describe the present extent of our knowledge on how regulatory proteins deal with the chromatin structure to gain access to DNA sequences and interpret the genomic instructions that enable cells to respond selectively to external signals by reshaping their gene regulatory networks.

Vascular Homeostasis and Inflammation in Health and Disease-Lessons from Single Cell Technologies

The vascular system is critical infrastructure that transports oxygen and nutrients around the body, and dynamically adapts its function to an array of environmental changes. To fulfil the demands of diverse organs, each with unique functions and requirements, the vascular system displays vast regional heterogeneity as well as specialized cell types. Our understanding of the heterogeneity of vascular cells and the molecular mechanisms that regulate their function is beginning to benefit greatly from the rapid development of single cell technologies. Recent studies have started to analyze and map vascular beds in a range of organs in healthy and diseased states at single cell resolution. The current review focuses on recent biological insights on the vascular system garnered from single cell analyses. We cover the themes of vascular heterogeneity, phenotypic plasticity of vascular cells in pathologies such as atherosclerosis and cardiovascular disease, as well as the contribution of defective microvasculature to the development of neurodegenerative disorders such as Alzheimer's disease. Further adaptation of single cell technologies to study the vascular system will be pivotal in uncovering the mechanisms that drive the array of diseases underpinned by vascular dysfunction.

Evaluating Enhancer Function and Transcription

Cell-type- and condition-specific profiles of gene expression require coordination between protein-coding gene promoters and cis-regulatory sequences called enhancers. Enhancers can stimulate gene activity at great genomic distances from their targets, raising questions about how enhancers communicate with specific gene promoters and what molecular mechanisms underlie enhancer function. Characterization of enhancer loci has identified the molecular features of active enhancers that accompany the binding of transcription factors and local opening of chromatin. These characteristics include coactivator recruitment, histone modifications, and noncoding RNA transcription. However, it remains unclear which of these features functionally contribute to enhancer activity. Here, we discuss what is known about how enhancers regulate their target genes and how enhancers and promoters communicate. Further, we describe recent data demonstrating many similarities between enhancers and the gene promoters they control, and we highlight unanswered questions in the field, such as the potential roles of transcription at enhancers.

Simultaneous quantification of protein-DNA interactions and transcriptomes in single cells with scDam&T-seq

Protein-DNA interactions are essential for establishing cell type-specific chromatin architecture and gene expression. We recently developed scDam&T-seq, a multi-omics method that can simultaneously quantify protein-DNA interactions and the transcriptome in single cells. The method effectively combines two existing methods: DNA adenine methyltransferase identification (DamID) and CEL-Seq2. DamID works through the tethering of a protein of interest (POI) to the Escherichia coli DNA adenine methyltransferase (Dam). Upon expression of this fusion protein, DNA in proximity to the POI is methylated by Dam and can be selectively digested and amplified. CEL-Seq2, in contrast, makes use of poly-dT primers to reverse transcribe mRNA, followed by linear amplification through in vitro transcription. scDam&T-seq is the first technique capable of providing a combined readout of protein-DNA contact and transcription from single-cell samples. Once suitable cell lines have been established, the protocol can be completed in 5 d, with a throughput of hundreds to thousands of cells. The processing of raw sequencing data takes an additional 1-2 d. Our method can be used to understand the transcriptional changes a cell undergoes upon the DNA binding of a POI. It can be performed in any laboratory with access to FACS, robotic and high-throughput-sequencing facilities.

Architectural proteins for the formation and maintenance of the 3D genome

Eukaryotic genomes are densely packaged into hierarchical three-dimensional (3D) structures that contain information about gene regulation and many other biological processes. With the development of imaging and sequencing-based technologies, 3D genome studies have revealed that the high-order chromatin structure is composed of hierarchical levels, including chromosome territories, A/B compartments, topologically associated domains, and chromatin loops. However, how this chromatin architecture is formed and maintained is not completely clear. In this review, we introduce experimental methods to investigate the 3D genome, review major architectural proteins that regulate 3D chromatin organization in mammalian cells, such as CTCF (CCCTC-binding factor), cohesin, lamins, and transcription factors, and discuss relevant mechanisms such as phase separation.

The corrected gene proximity map for analyzing the 3D genome organization using Hi-C data

BACKGROUND

Genome-wide ligation-based assays such as Hi-C provide us with an unprecedented opportunity to investigate the spatial organization of the genome. Results of a typical Hi-C experiment are often summarized in a chromosomal contact map, a matrix whose elements reflect the co-location frequencies of genomic loci. To elucidate the complex structural and functional interactions between those genomic loci, networks offer a natural and powerful framework.

RESULTS

We propose a novel graph-theoretical framework, the Corrected Gene Proximity (CGP) map to study the effect of the 3D spatial organization of genes in transcriptional regulation. The starting point of the CGP map is a weighted network, the gene proximity map, whose weights are based on the contact frequencies between genes extracted from genome-wide Hi-C data. We derive a null model for the network based on the signal contributed by the 1D genomic distance and use it to "correct" the gene proximity for cell type 3D specific arrangements. The CGP map, therefore, provides a network framework for the 3D structure of the genome on a global scale. On human cell lines, we show that the CGP map can detect and quantify gene co-regulation and co-localization more effectively than the map obtained by raw contact frequencies. Analyzing the expression pattern of metabolic pathways of two hematopoietic cell lines, we find that the relative positioning of the genes, as captured and quantified by the CGP, is highly correlated with their expression change. We further show that the CGP map can be used to form an inter-chromosomal proximity map that allows large-scale abnormalities, such as chromosomal translocations, to be identified.

CONCLUSIONS

The Corrected Gene Proximity map is a map of the 3D structure of the genome on a global scale. It allows the simultaneous analysis of intra- and inter- chromosomal interactions and of gene co-regulation and co-localization more effectively than the map obtained by raw contact frequencies, thus revealing hidden associations between global spatial positioning and gene expression. The flexible graph-based formalism of the CGP map can be easily generalized to study any existing Hi-C datasets.

Technologies to study spatial genome organization: beyond 3C

The way that chromatin is organized in three-dimensional nuclear space is now acknowledged as a factor critical for the major cell processes, like transcription, replication and cell division. Researchers have been armed with new molecular and imaging technologies to study this structure-to-function link of genomes, spearheaded by the introduction of the 'chromosome conformation capture' technology more than a decade ago. However, this technology is not without shortcomings, and novel variants and orthogonal approaches are being developed to overcome these. As a result, the field of nuclear organization is constantly fueled by methods of increasing resolution and/or throughput that strive to eliminate systematic biases and increase precision. In this review, we attempt to highlight the most recent advances in technology that promise to provide novel insights on how chromosomes fold and function.

Zooming in on chromosome dynamics

Until recently, our understanding of chromosome organization in higher eukaryotic cells has been based on analyses of large-scale, low-resolution changes in chromosomes structure. More recently, CRISPR-Cas9 technologies have allowed us to "zoom in" and visualize specific chromosome regions in live cells so that we can begin to examine in detail the dynamics of chromosome organization in individual cells. In this review, we discuss traditional methods of chromosome locus visualization and look at how CRISPR-Cas9 gene-targeting methodologies have helped improve their application. We also describe recent developments of the CRISPR-Cas9 technology that enable visualization of specific chromosome regions without the requirement for complex genetic manipulation.

Advances in technologies for 3D genomics research

The spatial structure of the orderly organized chromatin in the nucleus has important roles in maintaining normal cell function and in regulation of gene expression, and the high-throughput Hi-C and ChIA-PET methods have been widely used in various biological studies for determining potential spatial genome structures and their functions. However, there are still great difficulties and challenges in three-dimensional (3D) genomics research. More efficient, economical, and unbiased approaches to studying 3D genomics need to be developed for more widespread and easier applications. Here, we review the most recent studies on new 3D genomics research technologies, such as improvements of the traditional Hi-C and ChIA-PET methods, new approaches based on non-proximal-ligation strategies, and imaging-based methods improved in recent years. Especially, we review the CRISPR-based methods for functional validations in 3D genomics, which could be the forthcoming directions. We hope this review can show some insights into the potential improvements for future 3D genomics.

Coolpup.py: versatile pile-up analysis of Hi-C data

MOTIVATION

Hi-C is currently the method of choice to investigate the global 3D organization of the genome. A major limitation of Hi-C is the sequencing depth required to robustly detect loops in the data. A popular approach used to mitigate this issue, even in single-cell Hi-C data, is genome-wide averaging (piling-up) of peaks, or other features, annotated in high-resolution datasets, to measure their prominence in less deeply sequenced data. However, current tools do not provide a computationally efficient and versatile implementation of this approach.

RESULTS

Here, we describe coolpup.py-a versatile tool to perform pile-up analysis on Hi-C data. We demonstrate its utility by replicating previously published findings regarding the role of cohesin and CTCF in 3D genome organization, as well as discovering novel details of Polycomb-driven interactions. We also present a novel variation of the pile-up approach that can aid the statistical analysis of looping interactions. We anticipate that coolpup.py will aid in Hi-C data analysis by allowing easy to use, versatile and efficient generation of pile-ups.

AVAILABILITY AND IMPLEMENTATION

Coolpup.py is cross-platform, open-source and free (MIT licensed) software. Source code is available from https://github.com/Phlya/coolpuppy and it can be installed from the Python Packaging Index.

GiniQC: a measure for quantifying noise in single-cell Hi-C data

SUMMARY

Single-cell Hi-C (scHi-C) allows the study of cell-to-cell variability in chromatin structure and dynamics. However, the high level of noise inherent in current scHi-C protocols necessitates careful assessment of data quality before biological conclusions can be drawn. Here, we present GiniQC, which quantifies unevenness in the distribution of inter-chromosomal reads in the scHi-C contact matrix to measure the level of noise. Our examples show the utility of GiniQC in assessing the quality of scHi-C data as a complement to existing quality control measures. We also demonstrate how GiniQC can help inform the impact of various data processing steps on data quality.

AVAILABILITY AND IMPLEMENTATION

Source code and documentation are freely available at https://github.com/4dn-dcic/GiniQC.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Monitoring the spatio-temporal organization and dynamics of the genome

The spatio-temporal organization of chromatin in the eukaryotic cell nucleus is of vital importance for transcription, DNA replication and genome maintenance. Each of these activities is tightly regulated in both time and space. While we have a good understanding of chromatin organization in space, for example in fixed snapshots as a result of techniques like FISH and Hi-C, little is known about chromatin dynamics in living cells. The rapid development of flexible genomic loci imaging approaches can address fundamental questions on chromatin dynamics in a range of model organisms. Moreover, it is now possible to visualize not only single genomic loci but the whole genome simultaneously. These advances have opened many doors leading to insight into several nuclear processes including transcription and DNA repair. In this review, we discuss new chromatin imaging methods and how they have been applied to study transcription.

Transposable elements contribute to cell and species-specific chromatin looping and gene regulation in mammalian genomes

Chromatin looping is important for gene regulation, and studies of 3D chromatin structure across species and cell types have improved our understanding of the principles governing chromatin looping. However, 3D genome evolution and its relationship with natural selection remains largely unexplored. In mammals, the CTCF protein defines the boundaries of most chromatin loops, and variations in CTCF occupancy are associated with looping divergence. While many CTCF binding sites fall within transposable elements (TEs), their contribution to 3D chromatin structural evolution is unknown. Here we report the relative contributions of TE-driven CTCF binding site expansions to conserved and divergent chromatin looping in human and mouse. We demonstrate that TE-derived CTCF binding divergence may explain a large fraction of variable loops. These variable loops contribute significantly to corresponding gene expression variability across cells and species, possibly by refining sub-TAD-scale loop contacts responsible for cell-type-specific enhancer-promoter interactions.

Mixed secondary chromatin structure revealed by modeling radiation-induced DNA fragment length distribution

Spatial chromatin structure plays fundamental roles in many vital biological processes including DNA replication, transcription, damage and repair. However, the current understanding of the secondary structure of chromatin formed by local nucleosome-nucleosome interactions remains controversial, especially for the existence and conformation of 30 nm structure. Since chromatin structure influences the fragment length distribution (FLD) of ionizing radiation-induced DNA strand breaks, a 3D chromatin model fitting FLD patterns can help to distinguish different models of chromatin structure. Here, we developed a novel "30-C" model combining 30 nm chromatin structure models with Hi-C data, which measured the spatial contact frequency between different loci in the genome. We first reconstructed the 3D coordinates of the 25 kb bins from Hi-C heatmaps. Within the 25 kb bins, lower level chromatin structures supported by recent studies were filled. Simulated FLD patterns based on the 30-C model were compared to published FLD patterns induced by heavy ion radiation to validate the models. Importantly, the 30-C model predicted that the most probable chromatin fiber structure for human interphase fibroblasts in vivo was 45% zig-zag 30 nm fibers and 55% 10 nm fibers.

"Looping In" Mechanics: Mechanobiologic Regulation of the Nucleus and the Epigenome

Cells respond to physical cues in their microenvironment. These cues result in changes in cell behavior, some of which are transient, and others of which are permanent. Understanding and leveraging permanent alteration of cell behavior induced by mechanical cues, or "mechanical memories," is an important aim in cell and tissue engineering. Herein, this paper reviews the existing literature outlining how cells may store memories of biophysical cues with a specific focus on the nucleus, the storehouse of information in eukaryotic cells. In particular, this review details mechanically driven adaptations in nuclear structure and genome organization and outlines potential mechanisms by which mechanical memories may be encoded within the structure and organization of the nucleus and chromatin.

Bayesian inference of chromatin structure ensembles from population-averaged contact data

Mounting experimental evidence suggests a role for the spatial organization of chromatin in crucial processes of the cell nucleus such as transcription regulation. Chromosome conformation capture techniques allow us to characterize chromatin structure by mapping contacts between chromosomal loci on a genome-wide scale. The most widespread modality is to measure contact frequencies averaged over a population of cells. Single-cell variants exist, but suffer from low contact numbers and have not yet gained the same resolution as population methods. While intriguing biological insights have already been garnered from ensemble-averaged data, information about three-dimensional (3D) genome organization in the underlying individual cells remains largely obscured because the contact maps show only an average over a huge population of cells. Moreover, computational methods for structure modeling of chromatin have mostly focused on fitting a single consensus structure, thereby ignoring any cell-to-cell variability in the model itself. Here, we propose a fully Bayesian method to infer ensembles of chromatin structures and to determine the optimal number of states in a principled, objective way. We illustrate our approach on simulated data and compute multistate models of chromatin from chromosome conformation capture carbon copy (5C) data. Comparison with independent data suggests that the inferred ensembles represent the underlying sample population faithfully. Harnessing the rich information contained in multistate models, we investigate cell-to-cell variability of chromatin organization into topologically associating domains, thus highlighting the ability of our approach to deliver insights into chromatin organization of great biological relevance.

Differences in the intrinsic spatial dynamics of the chromatin contribute to cell differentiation

Advances in chromosome conformation capture techniques as well as computational characterization of genomic loci structural dynamics open new opportunities for exploring the mechanistic aspects of genome-scale differences across different cell types. We examined here the dynamic basis of variabilities between different cell types by investigating their chromatin mobility profiles inferred from Hi-C data using an elastic network model representation of the chromatin. Our comparative analysis of sixteen cell lines reveals close similarities between chromosomal dynamics across different cell lines on a global scale, but notable cell-specific variations emerge in the detailed spatial mobilities of genomic loci. Closer examination reveals that the differences in spatial dynamics mainly originate from the difference in the frequencies of their intrinsically accessible modes of motion. Thus, even though the chromosomes of different types of cells have access to similar modes of collective movements, not all modes are deployed by all cells, such that the effective mobilities and cross-correlations of genomic loci are cell-type-specific. Comparison with RNA-seq expression data reveals a strong overlap between highly expressed genes and those distinguished by high mobilities in the present study, in support of the role of the intrinsic spatial dynamics of chromatin as a determinant of cell differentiation.

Epigenetic regulation for acquiring glial identity by neural stem cells during cortical development

The nervous system consists of several hundred neuronal subtypes and glial cells that show specific gene expression and are generated from common ancestors, neural stem cells (NSCs). As the experimental techniques and molecular tools to analyze epigenetics and chromatin structures are rapidly advancing, the comprehensive events and genome-wide states of DNA methylation, histone modifications, and chromatin accessibility in developing NSCs are gradually being unveiled. Here, we review recent advances in elucidating the role of epigenetic and chromatin regulation in NSCs, especially focusing on the acquisition of glial identity and how epigenetic regulation enables the temporal regulation of NSCs during murine cortical development.

Three-dimensional genome: developmental technologies and applications in precision medicine

In the 20th century, our familiar structure of DNA was the double helix. Due to technical limitations, we do not have a good way to understand the finer structure of the genome, let alone its transcriptional regulation. Until the advent of 3C technologies, we were no longer blind to this one. Three-dimensional (3D) genomics is a new subject, which mainly studies the 3D structure and transcriptional regulation of eukaryotic genomes. Now, this field mainly has Hi-C series and CHIA-PET series technologies. Through 3D genomics, we can understand the basic structure of DNA, understand the growth and development of organisms and the occurrence of diseases, so as to promote human medical and health undertakings. The review introduces the main research techniques of 3D genomics and their characteristics, the latest development of 3D genome structure, the relationship between diseases and 3D genome structure, the applications of 3D genome in precision medicine, and the development of the 4D nucleome project.

Metabolism, Epigenetics, and Causal Inference in Heart Failure

Eukaryotes must balance the metabolic and cell death actions of mitochondria via control of gene expression and cell fate by chromatin, thereby functionally binding the metabolome and epigenome. This interaction has far-reaching implications for chronic diseases in humans, the most common of which are those of the cardiovascular system. The most devastating consequence of cardiovascular disease, heart failure, is not a single disease, diagnosis, or endpoint. Human and animal studies have revealed that, regardless of etiology and symptoms, heart failure is universally associated with abnormal metabolism and gene expression - to frame this as cause or consequence, however, may be to wrongfoot the question. This essay aims to challenge current thinking on metabolic-epigenetic crosstalk in heart failure, presenting hypotheses for how chronic diseases arise, take hold, and persist. We unpack assumptions about the order of operations for gene expression and metabolism, exploring recent findings in noncardiac systems that link metabolic intermediates directly to chromatin remodeling. Lastly, we discuss potential mechanisms by which chromatin may serve as a substrate for metabolic memory, and how changes in cellular transcriptomes (and hence in cellular behavior) in response to stress correspond to global changes in chromatin accessibility and structure.

Exploring 3D chromatin contacts in gene regulation: The evolution of approaches for the identification of functional enhancer-promoter interaction

Mechanisms underlying gene regulation are key to understand how multicellular organisms with various cell types develop from the same genetic blueprint. Dynamic interactions between enhancers and genes are revealed to play central roles in controlling gene transcription, but the determinants to link functional enhancer-promoter pairs remain elusive. A major challenge is the lack of reliable approach to detect and verify functional enhancer-promoter interactions (EPIs). In this review, we summarized the current methods for detecting EPIs and described how developing techniques facilitate the identification of EPI through assessing the merits and drawbacks of these methods. We also reviewed recent state-of-art EPI prediction methods in terms of their rationale, data usage and characterization. Furthermore, we briefly discussed the evolved strategies for validating functional EPIs.

Lamina-Dependent Stretching and Unconventional Chromosome Compartments in Early C. elegans Embryos

Current models suggest that chromosome domains segregate into either an active (A) or inactive (B) compartment. B-compartment chromatin is physically separated from the A compartment and compacted by the nuclear lamina. To examine these models in the developmental context of C. elegans embryogenesis, we undertook chromosome tracing to map the trajectories of entire autosomes. Early embryonic chromosomes organized into an unconventional barbell-like configuration, with two densely folded B compartments separated by a central A compartment. Upon gastrulation, this conformation matured into conventional A/B compartments. We used unsupervised clustering to uncover subpopulations with differing folding properties and variable positioning of compartment boundaries. These conformations relied on tethering to the lamina to stretch the chromosome; detachment from the lamina compacted, and allowed intermingling between, A/B compartments. These findings reveal the diverse conformations of early embryonic chromosomes and uncover a previously unappreciated role for the lamina in systemic chromosome stretching.

Assessing stationary distributions derived from chromatin contact maps

Background

The spatial configuration of chromosomes is essential to various cellular processes, notably gene regulation, while architecture related alterations, such as translocations and gene fusions, are often cancer drivers. Thus, eliciting chromatin conformation is important, yet challenging due to compaction, dynamics and scale. However, a variety of recent assays, in particular Hi-C, have generated new details of chromatin structure, spawning a number of novel biological findings. Many findings have resulted from analyses on the level of native contact data as generated by the assays. Alternatively, reconstruction based approaches often proceed by first converting contact frequencies into distances, then generating a three dimensional (3D) chromatin configuration that best recapitulates these distances. Subsequent analyses can enrich contact level analyses via superposition of genomic attributes on the reconstruction. But, such advantages depend on the accuracy of the reconstruction which, absent gold standards, is inherently difficult to assess. Attempts at accuracy evaluation have relied on simulation and/or FISH imaging that typically features a handful of low resolution probes. While newly advanced multiplexed FISH imaging offers possibilities for refined 3D reconstruction accuracy evaluation, availability of such data is limited due to assay complexity and the resolution thereof is appreciably lower than the reconstructions being assessed. Accordingly, there is demand for new methods of reconstruction accuracy appraisal.

Results

Here we explore the potential of recently proposed stationary distributions, hereafter StatDns, derived from Hi-C contact matrices, to serve as a basis for reconstruction accuracy assessment. Current usage of such StatDns has focussed on the identification of highly interactive regions (HIRs): computationally defined regions of the genome purportedly involved in numerous long-range intra-chromosomal contacts. Consistent identification of HIRs would be informative with respect to inferred 3D architecture since the corresponding regions of the reconstruction would have an elevated number of k nearest neighbors (kNNs). More generally, we anticipate a monotone decreasing relationship between StatDn values and kNN distances. After initially evaluating the reproducibility of StatDns across replicate Hi-C data sets, we use this implied StatDn - kNN relationship to gauge the utility of StatDns for reconstruction validation, making recourse to both real and simulated examples.

Conclusions

Our analyses demonstrate that, as constructed, StatDns do not provide a suitable measure for assessing the accuracy of 3D genome reconstructions. Whether this is attributable to specific choices surrounding normalization in defining StatDns or to the logic underlying their very formulation remains to be determined.

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.

Radial Organization in the Mammalian Nucleus

In eukaryotic cells, most of the genetic material is contained within a highly specialized organelle-the nucleus. A large body of evidence indicates that, within the nucleus, chromatinized DNA is spatially organized at multiple length scales. The higher-order organization of chromatin is crucial for proper execution of multiple genome functions, including DNA replication and transcription. Here, we review our current knowledge on the spatial organization of chromatin in the nucleus of mammalian cells, focusing in particular on how chromatin is radially arranged with respect to the nuclear lamina. We then discuss the possible mechanisms by which the radial organization of chromatin in the cell nucleus is established. Lastly, we propose a unifying model of nuclear spatial organization, and suggest novel approaches to test it.

Organelle size scaling over embryonic development

Cell division without growth results in progressive cell size reductions during early embryonic development. How do the sizes of intracellular structures and organelles scale with cell size and what are the functional implications of such scaling relationships? Model organisms, in particular Caenorhabditis elegans worms, Drosophila melanogaster flies, Xenopus laevis frogs, and Mus musculus mice, have provided insights into developmental size scaling of the nucleus, mitotic spindle, and chromosomes. Nuclear size is regulated by nucleocytoplasmic transport, nuclear envelope proteins, and the cytoskeleton. Regulators of microtubule dynamics and chromatin compaction modulate spindle and mitotic chromosome size scaling, respectively. Developmental scaling relationships for membrane-bound organelles, like the endoplasmic reticulum, Golgi, mitochondria, and lysosomes, have been less studied, although new imaging approaches promise to rectify this deficiency. While models that invoke limiting components and dynamic regulation of assembly and disassembly can account for some size scaling relationships in early embryos, it will be exciting to investigate the contribution of newer concepts in cell biology such as phase separation and interorganellar contacts. With a growing understanding of the underlying mechanisms of organelle size scaling, future studies promise to uncover the significance of proper scaling for cell function and embryonic development, as well as how aberrant scaling contributes to disease. This article is categorized under: Establishment of Spatial and Temporal Patterns > Regulation of Size, Proportion, and Timing Early Embryonic Development > Fertilization to Gastrulation Comparative Development and Evolution > Model Systems.

Understanding the mechanistic insight of arsenic exposure and decoding the histone cipher

BACKGROUND

The study of heritable epigenetic changes in arsenic exposure has intensified over the last decade. Groundwater arsenic contamination causes a great threat to humans and, to date, no accurate measure has been formulated for remediation. The fascinating possibilities of epi-therapeutics identify the need for an in-depth mechanistic understanding of the epigenetic landscape.

OBJECTIVE

In this comprehensive review, we have set to analyze major studies pertaining to histone post-translational modifications in arsenic-mediated disease development and carcinogenesis during last ten years (2008-2018).

RESULTS

The role of the specific histone marks in arsenic toxicity has been detailed. A comprehensive list that includes major arsenic-induced histone modifications identified for the last 10 years has been documented and details of different states of arsenic, organisms, exposure type, study platform, and findings were provided. An arsenic signature panel was suggested to help in early prognosis. An attempt has been made to identify the grey areas of research.

PROSPECTS

Future prospective multi-target analyses of the inter-molecular crosstalk among different histone marks are needed to be explored further in order to understand the mechanism of arsenic toxicity and carcinogenicity and to confirm the suitability of these epi-marks as prognostic markers.

CHROMATIX: computing the functional landscape of many-body chromatin interactions in transcriptionally active loci from deconvolved single cells

Chromatin interactions are important for gene regulation and cellular specialization. Emerging evidence suggests many-body spatial interactions play important roles in condensing super-enhancer regions into a cohesive transcriptional apparatus. Chromosome conformation studies using Hi-C are limited to pairwise, population-averaged interactions; therefore unsuitable for direct assessment of many-body interactions. We describe a computational model, CHROMATIX, which reconstructs ensembles of single-cell chromatin structures by deconvolving Hi-C data and identifies significant many-body interactions. For a diverse set of highly active transcriptional loci with at least 2 super-enhancers, we detail the many-body functional landscape and show DNase accessibility, POLR2A binding, and decreased H3K27me3 are predictive of interaction-enriched regions.