Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity

Node features of chromosome structure networks and their connections to genome annotation

The 3D conformations of chromosomes can encode biological significance, and the implications of such structures have been increasingly appreciated recently. Certain chromosome structural features, such as A/B compartmentalization, are frequently extracted from Hi-C pairwise genome contact information (physical association between different regions of the genome) and compared with linear annotations of the genome, such as histone modifications and lamina association. We investigate how additional properties of chromosome structure can be deduced using an abstract graph representation of the contact heatmap, and describe specific network properties that can have a strong connection with some of these biological annotations. We constructed chromosome structure networks (CSNs) from bulk Hi-C data and calculated a set of site-resolved (node-based) network properties. These properties are useful for characterizing certain aspects of chromosomal structure. We examined the ability of network properties to differentiate several scenarios, such as haploid vs diploid cells, partially inverted nuclei vs conventional architecture, depletion of chromosome architectural proteins, and structural changes during cell development. We also examined the connection between network properties and a series of other linear annotations, such as histone modifications and chromatin states including poised promoter and enhancer labels. We found that semi-local network properties exhibit greater capability in characterizing genome annotations compared to diffusive or ultra-local node features. For example, the local square clustering coefficient can be a strong classifier of lamina-associated domains. We demonstrated that network properties can be useful for highlighting large-scale chromosome structure differences that emerge in different biological situations.

Evolutionary analysis of gene ages across TADs associates chromatin topology with whole-genome duplications

Topologically associated domains (TADs) are interaction subnetworks of chromosomal regions in 3D genomes. TAD boundaries frequently coincide with genome breaks while boundary deletion is under negative selection, suggesting that TADs may facilitate genome rearrangements and evolution. We show that genes co-localize by evolutionary age in humans and mice, resulting in TADs having different proportions of younger and older genes. We observe a major transition in the age co-localization patterns between the genes born during vertebrate whole-genome duplications (WGDs) or before and those born afterward. We also find that genes recently duplicated in primates and rodents are more frequently essential when they are located in old-enriched TADs and interact with genes that last duplicated during the WGD. Therefore, the evolutionary relevance of recent genes may increase when located in TADs with established regulatory networks. Our data suggest that TADs could play a role in organizing ancestral functions and evolutionary novelty.

Targeting the chromatin structural changes of antitumor immunity

Epigenomic imbalance drives abnormal transcriptional processes, promoting the onset and progression of cancer. Although defective gene regulation generally affects carcinogenesis and tumor suppression networks, tumor immunogenicity and immune cells involved in antitumor responses may also be affected by epigenomic changes, which may have significant implications for the development and application of epigenetic therapy, cancer immunotherapy, and their combinations. Herein, we focus on the impact of epigenetic regulation on tumor immune cell function and the role of key abnormal epigenetic processes, DNA methylation, histone post-translational modification, and chromatin structure in tumor immunogenicity, and introduce these epigenetic research methods. We emphasize the value of small-molecule inhibitors of epigenetic modulators in enhancing antitumor immune responses and discuss the challenges of developing treatment plans that combine epigenetic therapy and immunotherapy through the complex interaction between cancer epigenetics and cancer immunology.

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.

Interplay between epigenome and 3D chromatin structure

Epigenetic mechanisms, primarily mediated through histone and DNA modifications, play a pivotal role in orchestrating the functional identity of a cell and its response to environmental cues. Similarly, the spatial arrangement of chromatin within the threedimensional (3D) nucleus has been recognized as a significant factor influencing genomic function. Investigating the relationship between epigenetic regulation and 3D chromatin structure has revealed correlation and causality between these processes, from the global alignment of average chromatin structure with chromatin marks to the nuanced correlations at smaller scales. This review aims to dissect the biological significance and the interplay between the epigenome and 3D chromatin structure, while also exploring the underlying molecular mechanisms. By synthesizing insights from both experimental and modeling perspectives, we seek to provide a comprehensive understanding of cellular functions. [BMB Reports 2023; 56(12): 633-644].

3D chromatin interactions involving Drosophila insulators are infrequent but preferential and arise before TADs and transcription

In mammals, insulators contribute to the regulation of loop extrusion to organize chromatin into topologically associating domains. In Drosophila the role of insulators in 3D genome organization is, however, under current debate. Here, we addressed this question by combining bioinformatics analysis and multiplexed chromatin imaging. We describe a class of Drosophila insulators enriched at regions forming preferential chromatin interactions genome-wide. Notably, most of these 3D interactions do not involve TAD borders. Multiplexed imaging shows that these interactions occur infrequently, and only rarely involve multiple genomic regions coalescing together in space in single cells. Finally, we show that non-border preferential 3D interactions enriched in this class of insulators are present before TADs and transcription during Drosophila development. Our results are inconsistent with insulators forming stable hubs in single cells, and instead suggest that they fine-tune existing 3D chromatin interactions, providing an additional regulatory layer for transcriptional regulation.

Esearch3D: propagating gene expression in chromatin networks to illuminate active enhancers

Most cell type-specific genes are regulated by the interaction of enhancers with their promoters. The identification of enhancers is not trivial as enhancers are diverse in their characteristics and dynamic in their interaction partners. We present Esearch3D, a new method that exploits network theory approaches to identify active enhancers. Our work is based on the fact that enhancers act as a source of regulatory information to increase the rate of transcription of their target genes and that the flow of this information is mediated by the folding of chromatin in the three-dimensional (3D) nuclear space between the enhancer and the target gene promoter. Esearch3D reverse engineers this flow of information to calculate the likelihood of enhancer activity in intergenic regions by propagating the transcription levels of genes across 3D genome networks. Regions predicted to have high enhancer activity are shown to be enriched in annotations indicative of enhancer activity. These include: enhancer-associated histone marks, bidirectional CAGE-seq, STARR-seq, P300, RNA polymerase II and expression quantitative trait loci (eQTLs). Esearch3D leverages the relationship between chromatin architecture and transcription, allowing the prediction of active enhancers and an understanding of the complex underpinnings of regulatory networks. The method is available at: https://github.com/InfOmics/Esearch3D and https://doi.org/10.5281/zenodo.7737123.

Mapping Multi-factor-mediated Chromatin Interactions to Assess Dysregulation of Lung Cancer-related Genes

Studies on the lung cancer genome are indispensable for developing a cure for lung cancer. Whole-genome resequencing, genome-wide association studies, and transcriptome sequencing have greatly improved our understanding of the cancer genome. However, dysregulation of long-range chromatin interactions in lung cancer remains poorly described. To better understand the three-dimensional (3D) genomic interaction features of the lung cancer genome, we used the A549 cell line as a model system and generated high-resolution chromatin interactions associated with RNA polymerase II (RNAPII), CCCTC-binding factor (CTCF), enhancer of zeste homolog 2 (EZH2), and histone 3 lysine 27 trimethylation (H3K27me3) using long-read chromatin interaction analysis by paired-end tag sequencing (ChIA-PET). Analysis showed that EZH2/H3K27me3-mediated interactions further repressed target genes, either through loops or domains, and their distributions along the genome were distinct from and complementary to those associated with RNAPII. Cancer-related genes were highly enriched with chromatin interactions, and chromatin interactions specific to the A549 cell line were associated with oncogenes and tumor suppressor genes, such as additional repressive interactions on FOXO4 and promoter-promoter interactions between NF1 and RNF135. Knockout of an anchor associated with chromatin interactions reversed the dysregulation of cancer-related genes, suggesting that chromatin interactions are essential for proper expression of lung cancer-related genes. These findings demonstrate the 3D landscape and gene regulatory relationships of the lung cancer genome.

Network models of chromatin structure

Increasing numbers of datasets and experimental assays that capture the organization of chromatin inside the nucleus warrant an effort to develop tools to visualize and analyze these structures. Alongside polymer physics or constraint-based modeling, network theory approaches to describe 3D epigenome organization have gained in popularity. Representing genomic regions as nodes in a network enables visualization of 1D epigenomics datasets in the context of chromatin structure maps, while network theory metrics can be used to describe 3D epigenome organization and dynamics. In this review, we summarize the most salient applications of network theory to the study of chromatin contact maps, demonstrating its potential in revealing epigenomic patterns and relating them to cellular phenotypes.

3D chromatin connectivity underlies replication origin efficiency in mouse embryonic stem cells

In mammalian cells, chromosomal replication starts at thousands of origins at which replisomes are assembled. Replicative stress triggers additional initiation events from 'dormant' origins whose genomic distribution and regulation are not well understood. In this study, we have analyzed origin activity in mouse embryonic stem cells in the absence or presence of mild replicative stress induced by aphidicolin, a DNA polymerase inhibitor, or by deregulation of origin licensing factor CDC6. In both cases, we observe that the majority of stress-responsive origins are also active in a small fraction of the cell population in a normal S phase, and stress increases their frequency of activation. In a search for the molecular determinants of origin efficiency, we compared the genetic and epigenetic features of origins displaying different levels of activation, and integrated their genomic positions in three-dimensional chromatin interaction networks derived from high-depth Hi-C and promoter-capture Hi-C data. We report that origin efficiency is directly proportional to the proximity to transcriptional start sites and to the number of contacts established between origin-containing chromatin fragments, supporting the organization of origins in higher-level DNA replication factories.

D2 Plot, a Matrix of DNA Density and Distance to Periphery, Reveals Functional Genome Regions

The execution of biological activities inside space-limited cell nuclei requires sophisticated organization. Current studies on the 3D genome focus on chromatin interactions and local structures, e.g., topologically associating domains (TADs). In this study, two global physical properties: DNA density and distance to nuclear periphery (DisTP), are introduced and a 2D matrix, D² plot, is constructed for mapping genetic and epigenetic markers. Distinct patterns of functional markers on the D² plot, indicating its ability to compartmentalize functional genome regions, are observed. Furthermore, enrichments of transcription-related markers are concatenated into a cross-species transcriptional activation model, where the nucleus is divided into four areas: active, intermediate, repress and histone, and repress and repeat. Based on the trajectories of the genomic regions on D² plot, the constantly active and newly activated genes are successfully identified during olfactory sensory neuron maturation. The analysis reveals that the D² plot effectively categorizes functional regions and provides a universal and transcription-related measurement for the 3D genome.

Mapping nucleosome and chromatin architectures: A survey of computational methods

With ever-growing genomic sequencing data, the data variabilities and the underlying biases of the sequencing technologies pose significant computational challenges ranging from the need for accurately detecting the nucleosome positioning or chromatin interaction to the need for developing normalization methods to eliminate systematic biases. This review mainly surveys the computational methods for mapping the higher-resolution nucleosome and higher-order chromatin architectures. While a detailed discussion of the underlying algorithms is beyond the scope of our survey, we have discussed the methods and tools that can detect the nucleosomes in the genome, then demonstrated the computational methods for identifying 3D chromatin domains and interactions. We further illustrated computational approaches for integrating multi-omics data with Hi-C data and the advance of single-cell (sc)Hi-C data analysis. Our survey provides a comprehensive and valuable resource for biomedical scientists interested in studying nucleosome organization and chromatin structures as well as for computational scientists who are interested in improving upon them.

STAG2 loss-of-function affects short-range genomic contacts and modulates the basal-luminal transcriptional program of bladder cancer cells

Cohesin exists in two variants containing STAG1 or STAG2. STAG2 is one of the most mutated genes in cancer and a major bladder tumor suppressor. Little is known about how its inactivation contributes to tumorigenesis. Here, we analyze the genomic distribution of STAG1 and STAG2 and perform STAG2 loss-of-function experiments using RT112 bladder cancer cells; we then analyze the genomic effects by integrating gene expression and chromatin interaction data. Functional compartmentalization exists between the cohesin complexes: cohesin-STAG2 displays a distinctive genomic distribution and mediates short and mid-ranged interactions that engage genes at higher frequency than those established by cohesin-STAG1. STAG2 knockdown results in down-regulation of the luminal urothelial signature and up-regulation of the basal transcriptional program, mirroring differences between STAG2-high and STAG2-low human bladder tumors. This is accompanied by rewiring of DNA contacts within topological domains, while compartments and domain boundaries remain refractive. Contacts lost upon depletion of STAG2 are assortative, preferentially occur within silent chromatin domains, and are associated with de-repression of lineage-specifying genes. Our findings indicate that STAG2 participates in the DNA looping that keeps the basal transcriptional program silent and thus sustains the luminal program. This mechanism may contribute to the tumor suppressor function of STAG2 in the urothelium.

Chromatin Network Analyses: Towards Structure-Function Relationships in Epigenomics

Recent technological advances have allowed us to map chromatin conformation and uncover the genome’s spatial organization of the genome inside the nucleus. These experiments have revealed the complexities of genome folding, characterized by the presence of loops and domains at different scales, which can change across development and in different cell types. There is strong evidence for a relationship between the topological properties of chromatin contacts and cellular phenotype. Chromatin can be represented as a network, in which genomic fragments are the nodes and connections represent experimentally observed spatial proximity of two genomically distant regions in a specific cell type or biological condition. With this approach we can consider a variety of chromatin features in association with the 3D structure, investigating how nuclear chromatin organization can be related to gene regulation, replication, malignancy, phenotypic variability and plasticity. We briefly review the results obtained on genome architecture through network theoretic approaches. As previously observed in protein-protein interaction networks and many types of non-biological networks, external conditions could shape network topology through a yet unidentified structure-function relationship. Similar to scientists studying the brain, we are confronted with a duality between a spatially embedded network of physical contacts, a related network of correlation in the dynamics of network nodes and, finally, an abstract definition of function of this network, related to phenotype. We summarise major developments in the study of networks in other fields, which we think can suggest a path towards better understanding how 3D genome configuration can impact biological function and adaptation to the environment.

From DNA human sequence to the chromatin higher order organisation and its biological meaning: Using biomolecular interaction networks to understand the influence of structural variation on spatial genome organisation and its functional effect

The three-dimensional structure of the human genome has been proven to have a significant functional impact on gene expression. The high-order spatial chromatin is organised first by looping mediated by multiple protein factors, and then it is further formed into larger structures of topologically associated domains (TADs) or chromatin contact domains (CCDs), followed by A/B compartments and finally the chromosomal territories (CTs). The genetic variation observed in human population influences the multi-scale structures, posing a question regarding the functional impact of structural variants reflected by the variability of the genes expression patterns. The current methods of evaluating the functional effect include eQTLs analysis which uses statistical testing of influence of variants on spatially close genes. Rarely, non-coding DNA sequence changes are evaluated by their impact on the biomolecular interaction network (BIN) reflecting the cellular interactome that can be analysed by the classical graph-theoretic algorithms. Therefore, in the second part of the review, we introduce the concept of BIN, i.e. a meta-network model of the complete molecular interactome developed by integrating various biological networks. The BIN meta-network model includes DNA-protein binding by the plethora of protein factors as well as chromatin interactions, therefore allowing connection of genomics with the downstream biomolecular processes present in a cell. As an illustration, we scrutinise the chromatin interactions mediated by the CTCF protein detected in a ChIA-PET experiment in the human lymphoblastoid cell line GM12878. In the corresponding BIN meta-network the DNA spatial proximity is represented as a graph model, combined with the Proteins-Interaction Network (PIN) of human proteome using the Gene Association Network (GAN). Furthermore, we enriched the BIN with the signalling and metabolic pathways and Gene Ontology (GO) terms to assert its functional context. Finally, we mapped the Single Nucleotide Polymorphisms (SNPs) from the GWAS studies and identified the chromatin mutational hot-spots associated with a significant enrichment of SNPs related to autoimmune diseases. Afterwards, we mapped Structural Variants (SVs) from healthy individuals of 1000 Genomes Project and identified an interesting example of the missing protein complex associated with protein Q6GYQ0 due to a deletion on chromosome 14. Such an analysis using the meta-network BIN model is therefore helpful in evaluating the influence of genetic variation on spatial organisation of the genome and its functional effect in a cell.

TAD cliques predict key features of chromatin organization

BACKGROUND

Mechanisms underlying genome 3D organization and domain formation in the mammalian nucleus are not completely understood. Multiple processes such as transcriptional compartmentalization, DNA loop extrusion and interactions with the nuclear lamina dynamically act on chromatin at multiple levels. Here, we explore long-range interaction patterns between topologically associated domains (TADs) in several cell types.

RESULTS

We find that TAD long-range interactions are connected to many key features of chromatin organization, including open and closed compartments, compaction and loop extrusion processes. Domains that form large TAD cliques tend to be repressive across cell types, when comparing gene expression, LINE/SINE repeat content and chromatin subcompartments. Further, TADs in large cliques are larger in genomic size, less dense and depleted of convergent CTCF motifs, in contrast to smaller and denser TADs formed by a loop extrusion process.

CONCLUSIONS

Our results shed light on the organizational principles that govern repressive and active domains in the human genome.

Chrom-Lasso: a lasso regression-based model to detect functional interactions using Hi-C data

Hi-C is a genome-wide assay based on Chromosome Conformation Capture and high-throughput sequencing to decipher 3D chromatin organization in the nucleus. However, computational methods to detect functional interactions utilizing Hi-C data face challenges including the correction for various sources of biases and the identification of functional interactions with low counts of interacting fragments. We present Chrom-Lasso, a lasso linear regression model that removes complex biases assumption-free and identifies functional interacting loci with increased power by combining information of local reads distribution surrounding the area of interest. We showed that interacting regions identified by Chrom-Lasso are more enriched for 5C validated interactions and functional GWAS hits than that of GOTHiC and Fit-Hi-C. To further demonstrate the ability of Chrom-Lasso to detect interactions of functional importance, we performed time-series Hi-C and RNA-seq during T cell activation and exhaustion. We showed that the dynamic changes in gene expression and chromatin interactions identified by Chrom-Lasso were largely concordant with each other. Finally, we experimentally confirmed Chrom-Lasso’s finding that Erbb3 was co-regulated with distinct neighboring genes at different states during T cell activation. Our results highlight Chrom-Lasso’s utility in detecting weak functional interaction between cis-regulatory elements, such as promoters and enhancers.

Widespread reorganisation of pluripotent factor binding and gene regulatory interactions between human pluripotent states

The transition from naive to primed pluripotency is accompanied by an extensive reorganisation of transcriptional and epigenetic programmes. However, the role of transcriptional enhancers and three-dimensional chromatin organisation in coordinating these developmental programmes remains incompletely understood. Here, we generate a high-resolution atlas of gene regulatory interactions, chromatin profiles and transcription factor occupancy in naive and primed human pluripotent stem cells, and develop a network-graph approach to examine the atlas at multiple spatial scales. We uncover highly connected promoter hubs that change substantially in interaction frequency and in transcriptional co-regulation between pluripotent states. Small hubs frequently merge to form larger networks in primed cells, often linked by newly-formed Polycomb-associated interactions. We identify widespread state-specific differences in enhancer activity and interactivity that correspond with an extensive reconfiguration of OCT4, SOX2 and NANOG binding and target gene expression. These findings provide multilayered insights into the chromatin-based gene regulatory control of human pluripotent states.

Correlated Evolution of Large DNA Fragments in the 3D Genome of Arabidopsis thaliana

In eukaryotes, the three-dimensional (3D) conformation of the genome is far from random, and this nonrandom chromatin organization is strongly correlated with gene expression and protein function, which are two critical determinants of the selective constraints and evolutionary rates of genes. However, whether genes and other elements that are located close to each other in the 3D genome evolve in a coordinated way has not been investigated in any organism. To address this question, we constructed chromatin interaction networks (CINs) in Arabidopsis thaliana based on high-throughput chromosome conformation capture data and demonstrated that adjacent large DNA fragments in the CIN indeed exhibit more similar levels of polymorphism and evolutionary rates than random fragment pairs. Using simulations that account for the linear distance between fragments, we proved that the 3D chromosomal organization plays a role in the observed correlated evolution. Spatially interacting fragments also exhibit more similar mutation rates and functional constraints in both coding and noncoding regions than the random expectations, indicating that the correlated evolution between 3D neighbors is a result of combined evolutionary forces. A collection of 39 genomic and epigenomic features can explain much of the variance in genetic diversity and evolutionary rates across the genome. Moreover, features that have a greater effect on the evolution of regional sequences tend to show higher similarity between neighboring fragments in the CIN, suggesting a pivotal role of epigenetic modifications and chromatin organization in determining the correlated evolution of large DNA fragments in the 3D genome.

Aggregated network centrality shows non-random structure of genomic and proteomic networks

Network analysis is a powerful tool for modelling biological systems. We propose a new approach that integrates the genomic interaction data at population level with the proteomic interaction data. In our approach we use chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) data from human genome to construct a set of genomic interaction networks, considering the natural partitioning of chromatin into chromatin contact domains (CCD). The genomic networks are then mapped onto proteomic interactions, to create protein-protein interaction (PPI) subnetworks. Furthermore, the network-based topological properties of these proteomic subnetworks are investigated, namely closeness centrality, betweenness centrality and clustering coefficient. We statistically confirm, that networks identified by our method significantly differ from random networks in these network properties. Additionally, we identify one of the regions, namely chr6:32014923-33217929, as having an above-random concentration of the single nucleotide polymorphisms (SNPs) related to autoimmune diseases. Then we present it in the form of a meta-network, which includes multi-omic data: genomic contact sites (anchors), genes, proteins and SNPs. Using this example we demonstrate, that the created networks provide a valid mapping of genes to SNPs, expanding on the raw SNP dataset used.

Using GARDEN-NET and ChAseR to explore human haematopoietic 3D chromatin interaction networks

We introduce an R package and a web-based visualization tool for the representation, analysis and integration of epigenomic data in the context of 3D chromatin interaction networks. GARDEN-NET allows for the projection of user-submitted genomic features on pre-loaded chromatin interaction networks, exploiting the functionalities of the ChAseR package to explore the features in combination with chromatin network topology properties. We demonstrate the approach using published epigenomic and chromatin structure datasets in haematopoietic cells, including a collection of gene expression, DNA methylation and histone modifications data in primary healthy myeloid cells from hundreds of individuals. These datasets allow us to test the robustness of chromatin assortativity, which highlights which epigenomic features, alone or in combination, are more strongly associated with 3D genome architecture. We find evidence for genomic regions with specific histone modifications, DNA methylation, and gene expression levels to be forming preferential contacts in 3D nuclear space, to a different extent depending on the cell type and lineage. Finally, we examine replication timing data and find it to be the genomic feature most strongly associated with overall 3D chromatin organization at multiple scales, consistent with previous results from the literature.

Transcription-driven genome organization: a model for chromosome structure and the regulation of gene expression tested through simulations

Current models for the folding of the human genome see a hierarchy stretching down from chromosome territories, through A/B compartments and topologically-associating domains (TADs), to contact domains stabilized by cohesin and CTCF. However, molecular mechanisms underlying this folding, and the way folding affects transcriptional activity, remain obscure. Here we review physical principles driving proteins bound to long polymers into clusters surrounded by loops, and present a parsimonious yet comprehensive model for the way the organization determines function. We argue that clusters of active RNA polymerases and their transcription factors are major architectural features; then, contact domains, TADs and compartments just reflect one or more loops and clusters. We suggest tethering a gene close to a cluster containing appropriate factors—a transcription factory—increases the firing frequency, and offer solutions to many current puzzles concerning the actions of enhancers, super-enhancers, boundaries and eQTLs (expression quantitative trait loci). As a result, the activity of any gene is directly influenced by the activity of other transcription units around it in 3D space, and this is supported by Brownian-dynamics simulations of transcription factors binding to cognate sites on long polymers.

A subset of topologically associating domains fold into mesoscale core-periphery networks

Mammalian genomes are folded into a hierarchy of compartments, topologically associating domains (TADs), subTADs, and long-range looping interactions. The higher-order folding patterns of chromatin contacts within TADs and how they localize to disease-associated single nucleotide variants (daSNVs) remains an open area of investigation. Here, we analyze high-resolution Hi-C data with graph theory to understand possible mesoscale network architecture within chromatin domains. We identify a subset of TADs exhibiting strong core-periphery mesoscale structure in embryonic stem cells, neural progenitor cells, and cortical neurons. Hyper-connected core nodes co-localize with genomic segments engaged in multiple looping interactions and enriched for occupancy of the architectural protein CCCTC binding protein (CTCF). CTCF knockdown and in silico deletion of CTCF-bound core nodes disrupts core-periphery structure, whereas in silico mutation of cell type-specific enhancer or gene nodes has a negligible effect. Importantly, neuropsychiatric daSNVs are significantly more likely to localize with TADs folded into core-periphery networks compared to domains devoid of such structure. Together, our results reveal that a subset of TADs encompasses looping interactions connected into a core-periphery mesoscale network. We hypothesize that daSNVs in the periphery of genome folding networks might preserve global nuclear architecture but cause local topological and functional disruptions contributing to human disease. By contrast, daSNVs co-localized with hyper-connected core nodes might cause severe topological and functional disruptions. Overall, these findings shed new light into the mesoscale network structure of fine scale genome folding within chromatin domains and its link to common genetic variants in human disease.

ChiCMaxima: a robust and simple pipeline for detection and visualization of chromatin looping in Capture Hi-C

Capture Hi-C (CHi-C) is a new technique for assessing genome organization based on chromosome conformation capture coupled to oligonucleotide capture of regions of interest, such as gene promoters. Chromatin loop detection is challenging because existing Hi-C/4C-like tools, which make different assumptions about the technical biases presented, are often unsuitable. We describe a new approach, ChiCMaxima, which uses local maxima combined with limited filtering to detect DNA looping interactions, integrating information from biological replicates. ChiCMaxima shows more stringency and robustness compared to previously developed tools. The tool includes a GUI browser for flexible visualization of CHi-C profiles alongside epigenomic tracks.

Integrating Hi-C and FISH data for modeling of the 3D organization of chromosomes

The new advances in various experimental techniques that provide complementary information about the spatial conformations of chromosomes have inspired researchers to develop computational methods to fully exploit the merits of individual data sources and combine them to improve the modeling of chromosome structure. Here we propose GEM-FISH, a method for reconstructing the 3D models of chromosomes through systematically integrating both Hi-C and FISH data with the prior biophysical knowledge of a polymer model. Comprehensive tests on a set of chromosomes, for which both Hi-C and FISH data are available, demonstrate that GEM-FISH can outperform previous chromosome structure modeling methods and accurately capture the higher order spatial features of chromosome conformations. Moreover, our reconstructed 3D models of chromosomes revealed interesting patterns of spatial distributions of super-enhancers which can provide useful insights into understanding the functional roles of these super-enhancers in gene regulation.

Deciphering Hi-C: from 3D genome to function

Hi-C is a commonly used technology in 3D genomics which can depict global chromatin interactions across eukaryotic genome. Integrating with different datasets, it can also be applied to studying various biological questions, such as nuclear organization, gene transcription regulation, spatiotemporal development, genome assembly, and cancer genomics. During the last decade, the development and application of Hi-C have dramatically changed the view of genome architecture, chromatin conformation, and gene interaction. So far, Hi-C-related studies remain vivacious and controversial; thus, a unified standard of library construction and bioinformatics analysis are urgently needed. In this review, we have summarized its history, development, methodologies, advances, applications, shortages, and future perspectives. We discuss a few limitations of the current Hi-C technologies and future directions for improvement and highlight how Hi-C can bridge 3D structure to gene function. This review will be helpful for scientists who want to engage in the 3D genomics field; it also shows some future tracks.

Exploring chromatin hierarchical organization via Markov State Modelling

We propose a new computational method for exploring chromatin structural organization based on Markov State Modelling of Hi-C data represented as an interaction network between genomic loci. A Markov process describes the random walk of a traveling probe in the corresponding energy landscape, mimicking the motion of a biomolecule involved in chromatin function. By studying the metastability of the associated Markov State Model upon annealing, the hierarchical structure of individual chromosomes is observed, and corresponding set of structural partitions is identified at each level of hierarchy. Then, the notion of effective interaction between partitions is derived, delineating the overall topology and architecture of chromosomes. Mapping epigenetic data on the graphs of intra-chromosomal effective interactions helps in understanding how chromosome organization facilitates its function. A sketch of whole-genome interactions obtained from the analysis of 539 partitions from all 23 chromosomes, complemented by distributions of gene expression regulators and epigenetic factors, sheds light on the structure-function relationships in chromatin, delineating chromosomal territories, as well as structural partitions analogous to topologically associating domains and active / passive epigenomic compartments. In addition to the overall genome architecture shown by effective interactions, the affinity between partitions of different chromosomes was analyzed as an indicator of the degree of association between partitions in functionally relevant genomic interactions. The overall static picture of whole-genome interactions obtained with the method presented in this work provides a foundation for chromatin structural reconstruction, for the modelling of chromatin dynamics, and for exploring the regulation of genome function. The algorithms used in this study are implemented in a freely available Python package ChromaWalker (https://bitbucket.org/ZhenWahTan/chromawalker).

Formation of correlated chromatin domains at nanoscale dynamic resolution during transcription

Intrinsic dynamics of chromatin contribute to gene regulation. How chromatin mobility responds to genomic processes, and whether this response relies on coordinated chromatin movement is still unclear. Here, we introduce an approach called Dense Flow reConstruction and Correlation (DFCC), to quantify correlation of chromatin motion with sub-pixel sensitivity at the level of the whole nucleus. DFCC reconstructs dense global flow fields of fluorescent images acquired in real-time. We applied our approach to analyze stochastic movements of DNA and histones, based on direction and magnitude at different time lags in human cells. We observe long-range correlations extending over several μm between coherently moving regions over the entire nucleus. Spatial correlation of global chromatin dynamics was reduced by inhibiting elongation by RNA polymerase II, and abolished in quiescent cells. Furthermore, quantification of spatial smoothness over time intervals up to 30 s points to clear-cut boundaries between distinct regions, while smooth transitions in small (<1 μm) neighborhoods dominate for short time intervals. Rough transitions between regions of coherent motion indicate directed squeezing or stretching of chromatin boundaries, suggestive of changes in local concentrations of actors regulating gene expression. The DFCC approach hence allows characterizing stochastically forming domains of nuclear activity.

Epigenomic annotation-based interpretation of genomic data: from enrichment analysis to machine learning

Motivation

One of the goals of functional genomics is to understand the regulatory implications of experimentally obtained genomic regions of interest (ROIs). Most sequencing technologies now generate ROIs distributed across the whole genome. The interpretation of these genome-wide ROIs represents a challenge as the majority of them lie outside of functionally well-defined protein coding regions. Recent efforts by the members of the International Human Epigenome Consortium have generated volumes of functional/regulatory data (reference epigenomic datasets), effectively annotating the genome with epigenomic properties. Consequently, a wide variety of computational tools has been developed utilizing these epigenomic datasets for the interpretation of genomic data.

Results

The purpose of this review is to provide a structured overview of practical solutions for the interpretation of ROIs with the help of epigenomic data. Starting with epigenomic enrichment analysis, we discuss leading tools and machine learning methods utilizing epigenomic and 3D genome structure data. The hierarchy of tools and methods reviewed here presents a practical guide for the interpretation of genome-wide ROIs within an epigenomic context.

Contact

mikhail.dozmorov@vcuhealth.org.

Supplementary information

Supplementary data are available at Bioinformatics online.

Widespread Enhancer Activity from Core Promoters

Gene expression in higher eukaryotes is precisely regulated in time and space through the interplay between promoters and gene-distal regulatory regions, known as enhancers. The original definition of enhancers implies the ability to activate gene expression remotely, while promoters entail the capability to locally induce gene expression. Despite the conventional distinction between them, promoters and enhancers share many genomic and epigenomic features. One intriguing finding in the gene regulation field comes from the observation that many core promoter regions display enhancer activity. Recent high-throughput reporter assays along with clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9-related approaches have indicated that this phenomenon is common and might have a strong impact on our global understanding of genome organisation and gene expression regulation.

Epigenetic and Transcriptional Variability Shape Phenotypic Plasticity

Epigenetic and transcriptional variability contribute to the vast diversity of cellular and organismal phenotypes and are key in human health and disease. In this review, we describe different types, sources, and determinants of epigenetic and transcriptional variability, enabling cells and organisms to adapt and evolve to a changing environment. We highlight the latest research and hypotheses on how chromatin structure and the epigenome influence gene expression variability. Further, we provide an overview of challenges in the analysis of biological variability. An improved understanding of the molecular mechanisms underlying epigenetic and transcriptional variability, at both the intra- and inter-individual level, provides great opportunity for disease prevention, better therapeutic approaches, and personalized medicine.

Advances in Genomic Profiling and Analysis of 3D Chromatin Structure and Interaction

Recent sequence-based profiling technologies such as high-throughput sequencing to detect fragment nucleotide sequence (Hi-C) and chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) have revolutionized the field of three-dimensional (3D) chromatin architecture. It is now recognized that human genome functions as folded 3D chromatin units and looping paradigm is the basic principle of gene regulation. To better interpret the 3D data dramatically accumulating in past five years and to gain deep biological insights, huge efforts have been made in developing novel quantitative analysis methods. However, the full understanding of genome regulation requires thorough knowledge in both genomic technologies and their related data analyses. We summarize the recent advances in genomic technologies in identifying the 3D chromatin structure and interaction, and illustrate the quantitative analysis methods to infer functional domains and chromatin interactions, and further elucidate the emerging single-cell Hi-C technique and its computational analysis, and finally discuss the future directions such as advances of 3D chromatin techniques in diseases.

Connected Gene Communities Underlie Transcriptional Changes in Cornelia de Lange Syndrome

Cornelia de Lange syndrome (CdLS) is a complex multisystem developmental disorder caused by mutations in cohesin subunits and regulators. While its precise molecular mechanisms are not well defined, they point toward a global deregulation of the transcriptional gene expression program. Cohesin is associated with the boundaries of chromosome domains and with enhancer and promoter regions connecting the three-dimensional genome organization with transcriptional regulation. Here, we show that connected gene communities, structures emerging from the interactions of noncoding regulatory elements and genes in the three-dimensional chromosomal space, provide a molecular explanation for the pathoetiology of CdLS associated with mutations in the cohesin-loading factor NIPBL and the cohesin subunit SMC1A NIPBL and cohesin are important constituents of connected gene communities that are centrally positioned at noncoding regulatory elements. Accordingly, genes deregulated in CdLS are positioned within reach of NIPBL- and cohesin-occupied regions through promoter-promoter interactions. Our findings suggest a dynamic model where NIPBL loads cohesin to connect genes in communities, offering an explanation for the gene expression deregulation in the CdLS.

Uncovering direct and indirect molecular determinants of chromatin loops using a computational integrative approach

Chromosomal organization in 3D plays a central role in regulating cell-type specific transcriptional and DNA replication timing programs. Yet it remains unclear to what extent the resulting long-range contacts depend on specific molecular drivers. Here we propose a model that comprehensively assesses the influence on contacts of DNA-binding proteins, cis-regulatory elements and DNA consensus motifs. Using real data, we validate a large number of predictions for long-range contacts involving known architectural proteins and DNA motifs. Our model outperforms existing approaches including enrichment test, random forests and correlation, and it uncovers numerous novel long-range contacts in Drosophila and human. The model uncovers the orientation-dependent specificity for long-range contacts between CTCF motifs in Drosophila, highlighting its conserved property in 3D organization of metazoan genomes. Our model further unravels long-range contacts depending on co-factors recruited to DNA indirectly, as illustrated by the influence of cohesin in stabilizing long-range contacts between CTCF sites. It also reveals asymmetric contacts such as enhancer-promoter contacts that highlight opposite influences of the transcription factors EBF1, EGR1 or MEF2C depending on RNA Polymerase II pausing.

The International Human Epigenome Consortium: A Blueprint for Scientific Collaboration and Discovery

The International Human Epigenome Consortium (IHEC) coordinates the generation of a catalog of high-resolution reference epigenomes of major primary human cell types. The studies now presented (see the Cell Press IHEC web portal at http://www.cell.com/consortium/IHEC) highlight the coordinated achievements of IHEC teams to gather and interpret comprehensive epigenomic datasets to gain insights in the epigenetic control of cell states relevant for human health and disease. PAPERCLIP.

Chrom3D: three-dimensional genome modeling from Hi-C and nuclear lamin-genome contacts

Current three-dimensional (3D) genome modeling platforms are limited by their inability to account for radial placement of loci in the nucleus. We present Chrom3D, a user-friendly whole-genome 3D computational modeling framework that simulates positions of topologically-associated domains (TADs) relative to each other and to the nuclear periphery. Chrom3D integrates chromosome conformation capture (Hi-C) and lamin-associated domain (LAD) datasets to generate structure ensembles that recapitulate radial distributions of TADs detected in single cells. Chrom3D reveals unexpected spatial features of LAD regulation in cells from patients with a laminopathy-causing lamin mutation. Chrom3D is freely available on github.