Chromosome conformation capture

The three-dimensional (3D) structure of chromatin is intrinsically associated with gene regulation and cell function1–3. Methods based on chromatin conformation capture have mapped chromatin structures in neuronal systems such as in vitro differentiated neurons, neurons isolated through fluorescence-activated cell sorting from cortical tissues pooled from different animals and from dissociated whole hippocampi4–6. However, changes in chromatin organization captured by imaging, such as the relocation of Bdnf away from the nuclear periphery after activation7, are invisible with such approaches8. Here we developed immunoGAM, an extension of genome architecture mapping (GAM)2,9, to map 3D chromatin topology genome-wide in specific brain cell types, without tissue disruption, from single animals. GAM is a ligation-free technology that maps genome topology by sequencing the DNA content from thin (about 220 nm) nuclear cryosections. Chromatin interactions are identified from the increased ...

Retroviral vectors are currently the most suitable vehicles for therapeutic gene transfer in hematopoietic stem cells. However, these vectors are known to integrate rather randomly throughout the genome, suffering the so called chromosomal position effects (PE). Such a critical occurrence most probably depends upon the ability of heterochromatin to spread in the inserted vector sequences. Moreover, the use of transgenes imply genotoxicity effects, since the cis-regulatory sequences harbored by the vector can disturb the proper transcription of the resident genes neighboring the integration site, potentially leading to malignant transformation. Due to their enhancer blocker activity, the incorporation of chromatin insulators in flanking position to the transferred unit can reduce the mentioned dangerous effects. Moreover, by acting as barriers to the spread of heterochromatin, chromatin insulators can also mitigate vector silencing. We have previously shown that the sea urchin sns5 c...

Polycomb-repressive complex 1 (PRC1) has a strong influence on 3D genome organization, mediating local chromatin compaction as well as localized and chromosome-wide clustering of target loci. Several subunits of PRC1 have been shown to have the capacity to form biomolecular condensates through liquid-liquid phase separationin vitroand when tagged and over-expressed in cells. Here, we use 1,6-hexandiol, which disrupts liquid-like condensates, to examine the role of endogenous PRC1 biomolecular condensates on local and chromosome-wide clustering of PRC1-bound loci. Using imaging and chromatin immunoprecipitation combined with deep sequencing analyses, we show that PRC1-mediated chromatin compaction and clustering of targeted genomic loci – at megabase and tens of megabase length scales – can be reversibly disrupted by the addition and subsequent removal of 1,6-hexandiol to mouse embryonic stem cells. Decompaction and dispersal of polycomb domains and clusters cannot be solely attribut...

Aging, particularly in the brain, involves impairments in multiple cellular and molecular functions, many of which are regulated at the nucleus. Chromatin structure plays a critical role in the regulation of gene expression and the maintenance of genomic stability. During differentiation, chromosomes acquire their unique topology depending on the cell type that should be kept for a lifetime, but this may deteriorate as we age. However, the effects of aging on the chromatin 3D structure of neurons remain largely unknown and much has been inferred from senescent cells. By combining chromosome conformation capture and microscopy techniques, we investigated cortical neurons of young and aged mice and discovered neuronal nuclear expansion during neuronal aging, leading to increased distances between chromosomes. This expansion alters the topology of compartments, topologically associating domains (TADs) and chromatin loops. While larger TADs tend to dissociate, smaller TADs and loops exhibit strengthened interactions to maintain the cohesiveness of chromatin in aged neurons. These topological changes impact the borders of TADs, resulting in their overall weakening. Interestingly, we attribute these alterations to changes in the physical forces of an expanding nucleus, filling a growing nuclear area, affecting downstream gene expression and chromatin topology, further contributing to the functional declines observed during aging.

Single-cell chromosome conformation capture approaches are revealing the extent of cell-to-cell variability in the organization and packaging of genomes. These single-cell methods, unlike their multi-cell counterparts, allow straightforward computation of realistic chromosome conformations that may be compared and combined with other, independent, techniques to study 3D structure. Here we discuss how single-cell Hi-C and subsequent 3D genome structure determination allows comparison with data from microscopy. We then carry out a systematic evaluation of recently published single-cell Hi-C datasets to establish a computational approach for the evaluation of single-cell Hi-C protocols. We show that the calculation of genome structures provides a useful tool for assessing the quality of single-cell Hi-C data because it requires a self-consistent network of interactions, relating to the underlying 3D conformation, with few errors, as well as sufficient longer-range cis- and trans-chromo...

Large-scale chromosome structure and spatial nuclear arrangement have been linked to control of gene expression and DNA replication and repair. Genomic techniques based on chromosome conformation capture assess contacts for millions of loci simultaneously, but do so by averaging chromosome conformations from millions of nuclei. Here we introduce single cell Hi-C, combined with genome-wide statistical analysis and structural modeling of single copy X chromosomes, to show that individual chromosomes maintain domain organisation at the megabase scale, but show variable cell-to-cell chromosome territory structures at larger scales. Despite this structural stochasticity, localisation of active gene domains to boundaries of territories is a hallmark of chromosomal conformation. Single cell Hi-C data bridge current gaps between genomics and microscopy studies of chromosomes, demonstrating how modular organisation underlies dynamic chromosome structure, and how this structure is probabilistically linked with genome activity patterns. Chromosome conformation capture 1 (3C) and derivative methods (4C, 5C and Hi-C) 2-6 have enabled the detection of chromosome organisation in the 3D space of the nucleus. These methods assess millions of cells and are increasingly used to calculate conformations of a range of genomic regions, from individual loci to whole genomes 3,7-11 . However, fluorescence in situ hybridisation (FISH) analyses show that genotypically and phenotypically identical cells have non-random, but highly variable genome and chromosome conformations probably due to the dynamic and stochastic nature of chromosomal structures . Therefore, whilst 3C-based analyses can be used to estimate

The folding of genomic DNA from the beads-on-a-string-like structure of nucleosomes into higher-order assemblies is crucially linked to nuclear processes. Here we calculate 3D structures of entire mammalian genomes using data from a new chromosome conformation capture procedure that allows us to first image and then process single cells. The technique enables genome folding to be examined at a scale of less than 100 kb, and chromosome structures to be validated. The structures of individual topological-associated domains and loops vary substantially from cell to cell. By contrast, A and B compartments, lamina-associated domains and active enhancers and promoters are organized in a consistent way on a genome-wide basis in every cell, suggesting that they could drive chromosome and genome folding. By studying genes regulated by pluripotency factor and nucleosome remodelling deacetylase (NuRD), we illustrate how the determination of single-cell genome structure provides a new approach ...

T-cell receptor (TCR) diversity is generated by VDJ recombination. The classical course of TCR beta (TRB) chain production starts with D and J segment recombination and finishes with subsequent recombination between the resulting DJ junction and V segment. In this study, we performed deep sequencing of poorly explored incomplete TRBD1 to TRBD2 rearrangements in T-cell genomic DNA. We reconstructed full repertoires of human incomplete TRB DD rearrangements and validated its authenticity by detecting excision circles with RSS (recombination signal sequence) junctions for the first time. The identified rearrangements generated in compliance with the classical 12/23 rule are common for humans, rats, and mice and contain typical VDJ recombination footprints. Detected bimodal distribution of DD junctions indicates two active recombination sites producing long and short DD rearrangements. Unlike long DD rearrangements, the short ones have unusual origin resulting from non-canonical intrach...

Non-random spatial organization of the chromosomal material inside the nuclei of brain cells emerges as an important regulatory layer of genome organization and function in health and disease. Here, we discuss how integrative approaches assessing chromatin in context of the 3D genome is providing new insights into normal and diseased neurodevelopment. Studies in primate (incl. human) and rodent brain have confirmed that chromosomal organization in neurons and glia undergoes highly dynamic changes during pre-and early postnatal development, with potential for plasticity across a much wider age window. For example, neuronal 3D genomes from juvenile and adult cerebral cortex and hippocampus undergo chromosomal conformation changes at hundreds of loci in the context of learning and environmental enrichment, viral infection, and neuroinflammation. Furthermore, locus-specific structural DNA variations, such as micro-deletions, duplications, repeat expansions, and retroelement insertions carry the potential to disrupt the broader epigenomic and transcriptional landscape far beyond the boundaries of the site-specific variation, highlighting the critical importance of long-range intra-and inter-chromosomal contacts for neuronal and glial function.

Non-random spatial organization of the chromosomal material inside the nuclei of brain cells emerges as an important regulatory layer of genome organization and function in health and disease. Here, we discuss how integrative approaches assessing chromatin in context of the 3D genome is providing new insights into normal and diseased neurodevelopment. Studies in primate (incl. human) and rodent brain have confirmed that chromosomal organization in neurons and glia undergoes highly dynamic changes during pre- and early postnatal development, with potential for plasticity across a much wider age window. For example, neuronal 3D genomes from juvenile and adult cerebral cortex and hippocampus undergo chromosomal conformation changes at hundreds of loci in the context of learning and environmental enrichment, viral infection, and neuroinflammation. Furthermore, locus-specific structural DNA variations, such as micro-deletions, duplications, repeat expansions, and retroelement insertions ...

Chromatin from different regions of the genome frequently forms steady associations that play important roles in regulating gene expression. The widely used chromatin conformation capture (3C) assay allows determination of the in vivo structural organization of an active endogenous locus. However, unpredicted chromatin associations within a given genomic locus can not be identified by 3C. Here, we describe a new strategy, quantitative associated chromatin trap (QACT), which incorporates a modified 3C method and a quantitative assay tool, to capture and quantitatively analyzes all possible associated chromatin partners (ACPs) of a given chromatin fragment. Using QACT, we have analyzed the chromatin conformation of the mouse α‐globin gene cluster and proved the extensive interaction between HS26 and α‐globin genes. In addition, we have identified a candidate α1‐globin gene specific silencer 475A8 which shows the differentiation‐stage specific DNase I hypersensitivity. Functional analy...

Genome layout and gene regulation appear to be interdependent. Understanding this interdependence is key to exploring the dynamic nature of chromosome conformation and to engineering functional genomes. Evidence for non-random genome layout, defined as the relative positioning of either co-functional or co-regulated genes, stems from two main approaches. Firstly, the analysis of contiguous genome segments across species, has highlighted the conservation of gene arrangement (synteny) along chromosomal regions. Secondly, the study of long-range interactions along a chromosome has emphasised regularities in the positioning of microbial genes that are co-regulated, co-expressed or evolutionarily correlated. While one-dimensional pattern analysis is a mature field, it is often powerless on biological datasets which tend to be incomplete, and partly incorrect. Moreover, there is a lack of comprehensive, user-friendly tools to systematically analyse, visualise, integrate and exploit regula...

Repeated extragenic palindromes ( REP s) in the enterobacterial genomes are usually composed of individual palindromic units separated by linker sequences. A total of 355 annotated REP s are distributed along the Escherichia coli genome. RNA sequence (RNAseq) analysis showed that almost 80% of the REP s in E. coli are transcribed. The DNA sequence of REP 325 showed that it is a cluster of six repeats, each with two palindromic units capable of forming cruciform structures in supercoiled DNA. Here, we report that components of the REP 325 element and at least one of its RNA products play a role in bacterial nucleoid DNA condensation. These RNA not only are present in the purified nucleoid but bind to the bacterial nucleoid-associated HU protein as revealed by RNA IP followed by microarray analysis (RIP-Chip) assays. Deletion of REP 325 resulted in a dramatic increase of the nucleoid size as observed using transmission electron microscopy (TEM), and expression of one of the REP 325 RN...

Nor Cen T19B17 (106 kbp) 5 µm 0.5 µm A B C Arabidopsis thaliana Chr. 4 T27D20 (80 kbp) Simulation of Single Chromosomes The 30 nm chromatin fiber is modeled as a polymer chain with stretching, bending, and excluded volume interactions. Monte Carlo and Brownian Dynamic methods lead to thermodynamical equilibrium configurations. All models form chromosome territories with big voids and different chromatin morphologies. Experimental territory and subcompartment diameters agree best with an MLS model with 80 to 120 kbp loops and linkers. RW/GL model, loop size 5 Mbp, after ~80.000 MC and 1000 relaxing BD steps. Large loops intermingle freely and reach out of the chromsome territory, thus forming no distinct features like in MLS model. MLS model, loop size 126kbp, linker size 126 kbp, after ~50.000 MC and 1000 relaxing BD steps. Here rosettes form subcompartments as separated organizational and dynamic entities. RW/GL model, loop size 126 kbp, after ~80.000 MC and 1000 relaxing BD steps. Large loops intermingle freely thus forming no distinct features like in MLS model. Metaphase starting configuration with ideogram bands in red/green, linker in grey. RW/GL model, loop size 5 Mbp, after ~80.000 MC and 1000 relaxing BD steps. Large loops intermingle freely and reach out of the chromsome territory, thus forming no distinct features like in MLS model. MLS model, loop size 126kbp, linker size 126 kbp, after ~50.000 MC and 1000 relaxing BD steps. Here rosettes form subcompartments as separated organizational and dynamic entities. RW/GL model, loop size 126 kbp, after ~80.000 MC and 1000 relaxing BD steps. Large loops intermingle freely thus forming no distinct features like in MLS model. Metaphase starting configuration with ideogram bands in red/green, linker in grey. Fluorescence in situ hybridization with various protocols of small probes within the Prader-Willi region combined with spectral precision distance confocal laser scanning microscopy and comparison with large-scale computer simulations shows a Multi-Loop Subcompartiment organization of the Prader-Willi region. λ48.1 λ48.17 17.8kbp λ48.14 13.0kbp λ48.7 15.6kbp centromer telomer y457B4 ~300kbp y378A12 ~300kbp 650

-Loop-Subcompartment model (MLS) Münkel et al. (1997) backbone (non DNA) chromatin fiber, 30nm thick loop size: 3Mbp-5Mbp G bands loop size: 126kbp rosette size: 1-2Mbp (according to interphase ideogram bands) Linker consists of DNA (126 kbp)

MicroRNA is an oligonucleotide that plays a role in the pathogenesis of several diseases (mentioning Cancer). It is a non-coding RNA that is involved in the control of gene expression through the binding and inhibition of mRNA. In this study, three algorithms were implemented in WEKA software using two testing modes to analyze five datasets of miRNA families. The data mining techniques are used to compare the interactions of miRNA-mRNA that it either belongs to the same gene-family or to different families, and to establish a biological scheme that explains how the biological parameters are involved or less involved in miRNA-mRNA prediction. The factors that were involved in the prediction process includs match, mismatch, bulge, loop, and score to represent the binding characteristics, while the position, 3'UTR length, and chromosomal location and chromosomal categorizations represent the characteristics of the target mRNA. These attributes can provide an empirical guidance for study of specific miRNA family to scan the whole human genome for novel targets. This research provides promising results that can be utilized for current and future research in this field.

Chromatin architecture, a key regulator of gene expression, can be inferred using chromatin contact data from chromosome conformation capture, or Hi-C. However, classical Hi-C does not preserve multi-way contacts. Here we use long sequencing reads to map genome-wide multi-way contacts and investigate higher order chromatin organization in the human genome. We use hypergraph theory for data representation and analysis, and quantify higher order structures in neonatal fibroblasts, biopsied adult fibroblasts, and B lymphocytes. By integrating multi-way contacts with chromatin accessibility, gene expression, and transcription factor binding, we introduce a data-driven method to identify cell type-specific transcription clusters. We provide transcription factor-mediated functional building blocks for cell identity that serve as a global signature for cell types. Structural features of the genome are integral to the regulation of gene expression and corresponding generation of cellular phenotypes 1-3 . Aspects of genome structure have been inferred by studying genomic regions that are in close physical proximity. Chromosome conformation capture (3C)-based methods capture these interactions (contacts) through chemical fixation, digestion of DNA, and proximity ligation, followed by sequencing of ligated DNA to identify genomic regions that are in contact. A variety of cell types have now been characterized using Hi-C, a genome-wide 3C-based method, adding substantially to our understanding of genome architecture. However, limitations on read length during sequencing lead to over-representation of simple interactions, predominantly pairwise. Identification of more complex, higher-order interactions can help us build a more complete set of principles of genome architecture. Multi-way contacts have been identified using targeted 3C-based methods 4-6 , through inference from pairwise contacts 7 , and on occasion using classical Hi-C 8 . Ligation-free approaches, such as GAM, SPRITE, and ChIA-Drop, have recently enabled large scale capture of multi-way interactions , though comparisons of different methods find under-and over-representation of higher order contacts in the absence of proximity ligation . A recent extension of Hi-C preserves multi-way interactions and uses sequencing of long reads (e.g. Pore-C) 12 to unambiguously identify sets of contacts among multiple loci. Multi-contact 4C sequencing (MC-4C) also uses long-read sequencing to capture contact complexity 14 , however, it was designed to capture local topology for individual genes and regulatory regions and does not generate multi-way contacts genome-wide. While direct capture of multi-way contacts can clarify higher order structures in the genome, new frameworks are needed to address unique analysis and representation challenges posed by the multiway data.

Chromatin architecture, a key regulator of gene expression, can be inferred using chromatin contact data from chromosome conformation capture, or Hi-C. However, classical Hi-C does not preserve multi-way contacts. Here we use long sequencing reads to map genome-wide multi-way contacts and investigate higher order chromatin organization in the human genome. We use hypergraph theory for data representation and analysis, and quantify higher order structures in neonatal fibroblasts, biopsied adult fibroblasts, and B lymphocytes. By integrating multi-way contacts with chromatin accessibility, gene expression, and transcription factor binding, we introduce a data-driven method to identify cell type-specific transcription clusters. We provide transcription factor-mediated functional building blocks for cell identity that serve as a global signature for cell types.

How spatial chromosome organization influences genome integrity is still poorly understood. Here we show that DNA double-strand breaks (DSBs) mediated by topoisomerase 2 (TOP2) activities, are enriched at chromatin loop anchors with high transcriptional activity. Recurrent DSBs occur at CTCF/cohesin bound sites at the bases of chromatin loops and their frequency positively correlates with transcriptional output and directionality. The physiological relevance of this preferential positioning is indicated by the finding that genes recurrently translocating to drive leukemias, are highly transcribed and are enriched at loop anchors. These genes accumulate DSBs at recurrent hot spots that give rise to chromosomal fusions relying on the activity of both TOP2 isoforms and on transcriptional elongation. We propose that transcription and 3D chromosome folding jointly pose a threat to genomic stability, and are key contributors to the occurrence of genome rearrangements that drive cancer.

Clustering of proteins is crucial for many cellular processes and can be imaged at nanoscale resolution using single-molecule localization microscopy (SMLM). Ideally, molecular clustering in regions of interest (ROIs) from SMLM images would be assessed using computational methods that are robust to sample and experimental heterogeneity, account for uncertainties in localization data, can analyze both 2D and 3D data, and have practical computational requirements in terms of time and hardware. While analyzing surface protein clustering on B lymphocytes using SMLM, we encountered limitations with existing cluster analysis methods. This inspired us to develop StormGraph, an algorithm using graph theory and community detection to identify clusters in heterogeneous sets of 2D and 3D SMLM data while accounting for localization uncertainties. StormGraph generates both multi-level and single-level clusterings and can quantify cluster overlap for two-color SMLM data. Importantly, StormGraph a...

Using the massively parallel technique of sequencing by oligonucleotide ligation and detection (SOLiD; Applied Biosystems), we have assessed the in vivo positions of more than 44 million putative nucleosome cores in the multicellular genetic model organism Caenorhabditis elegans. These analyses provide a global view of the chromatin architecture of a multicellular animal at extremely high density and resolution. While we observe some degree of reproducible positioning throughout the genome in our mixed stage population of animals, we note that the major chromatin feature in the worm is a diversity of allowed nucleosome positions at the vast majority of individual loci. While absolute positioning of nucleosomes can vary substantially, relative positioning of nucleosomes (in a repeated array structure likely to be maintained at least in part by steric constraints) appears to be a significant property of chromatin structure. The high density of nucleosomal reads enabled a substantial e...

Variants within non-coding genomic regions can greatly affect disease. In recent years, increasing focus has been given to these variants, and how they can alter regulatory elements, such as enhancers, transcription factor binding sites and DNA methylation regions. Such variants can be considered regulatory variants. Concurrently, much effort has been put into establishing international consortia to undertake large projects aimed at discovering regulatory elements in different tissues, cell lines and organisms, and probing the effects of genetic variants on regulation by measuring gene expression. Here, we describe methods and techniques for discovering disease-associated non-coding variants using sequencing technologies. We then explain the computational procedures that can be used for annotating these variants using the information from the aforementioned projects, and prediction of their putative effects, including potential pathogenicity, based on rule-based and machine learning approaches. We provide the details of techniques to validate these predictions, by mapping chromatin-chromatin and chromatin-protein interactions, and introduce Clustered Regularly Interspaced Short Palindromic Repeats-Associated Protein 9 (CRISPR-Cas9) technology, which has already been used in this field and is likely to have a big impact on its future evolution. We also give examples of regulatory variants associated with multiple complex diseases. This review is aimed at bioinformaticians interested in the characterization of regulatory variants, molecular biologists and geneticists interested in understanding more about the nature and potential role of such variants from a functional point of views, and clinicians who may wish to learn about variants in non-coding genomic regions associated with a given disease and find out what to do next to uncover how they impact on the underlying mechanisms.

Nor Cen T19B17 (106 kbp) 5 µm 0.5 µm A B C Arabidopsis thaliana Chr. 4 T27D20 (80 kbp) 3D Architecture of the Prader-Willi Region Fluorescence in situ hybridization with various protocols of small probes within the Prader-Willi region combined with spectral precision distance confocal laser scanning microscopy and comparison with large-scale computer simulations shows a Multi-Loop Subcompartiment organization of the Prader-Willi region. λ48.1 17.3kbp λ48.17 17.8kbp λ48.14 13.0kbp λ48.7 15.6kbp centromer telomer y457B4 ~300kbp y378A12 ~300kbp 650

Nor Cen T19B17 (106 kbp) 5 µm 0.5 µm A B C Arabidopsis thaliana Chr. 4 T27D20 (80 kbp) 3D Architecture of the Prader-Willi Region Fluorescence in situ hybridization with various protocols of small probes within the Prader-Willi region combined with spectral precision distance confocal laser scanning microscopy and comparison with large-scale computer simulations shows a Multi-Loop Subcompartiment organization of the Prader-Willi region. λ48.1 17.3kbp λ48.17 17.8kbp λ48.14 13.0kbp λ48.7 15.6kbp centromer telomer y457B4 ~300kbp y378A12 ~300kbp 650

Nor Cen T19B17 (106 kbp) 5 µm 0.5 µm A B C Arabidopsis thaliana Chr. 4 T27D20 (80 kbp) 3D Architecture of the Prader-Willi Region Fluorescence in situ hybridization with various protocols of small probes within the Prader-Willi region combined with spectral precision distance confocal laser scanning microscopy and comparison with large-scale computer simulations shows a Multi-Loop Subcompartiment organization of the Prader-Willi region. λ48.1 17.3kbp λ48.17 17.8kbp λ48.14 13.0kbp λ48.7 15.6kbp centromer telomer y457B4 ~300kbp y378A12 ~300kbp 650

The dynamic three-dimensional chromatin architecture of genomes and the obvious co-evolutionary connection to its function -the storage and expression of genetic information -is still, after ~170 years, a central question of current research. With a systems genomics approach using a novel selective high-throughput chromosomal interaction capture (T2C) technique together with quantitative polymer simulations and scaling analysis of genomic structures and the DNA sequence, we determined the architecture of genomes with unprecedented molecular resolution and dynamic range from single base pair entire chromosomes: for several genetic loci of different species, cell type, and functional states we find a chromatin quasi-fibre exists with 5±1 nucleosome per 11 nm, which folds into 40-100 kbp loops forming aggregates/rosettes which are connected by a ~50 kbp chromatin linker. Polymer simulations using Monte Carlo and Brownian dynamics approaches confirm T2C results and allow to predict and explain additional experimental findings. This agrees also with novel dynamics information from fluorescence correlation spectroscopy (FCS) analysis of chromatin relaxations in vivo (see abstract M. Wachsmuth & T. A. Knoch, Dynamic and structural properties of interphase chromatin mapped in vivo with fluorescence correlation spectroscopy and quantitative modelling). Beyond, we find a fine-structured multi-scaling behaveour of both the architecture and the DNA sequence which shows for the first time, that genome architecture and DNA sequence organiztion are directly linked -again in detail on the base pair level. Hence, we determined the three-dimensional organization and dynamics for the first time in a consistent system genomics manner from several angles which are all in agreement as well as additionally also with the heuristics of the research of the last 170 years. Consequently, T2C allows to reach an optimal combination of resolution, interaction frequency range, multiplexing, and an unseen signal-to-noise ratio at molecular resolution and hence at the level of the "genomic" uncertainty principle and statistical mechanics, this opens the door to architectural sequencing of genomes and thus a detailed understanding of the genome with fundamental new insights with perspectives for diagnosis and treatment.

The three-dimensional organization of chromosomes of eukaryotic interphase cells is emerging as an important parameter for the regulation of genes as well as the storage, replication and expression of genetic information in general. Whereas a couple of techniques like electrone microscopy (EM), fluorescentce in situ hybridization, or chromosome capture techniques as 3C, 4C, 5C, HiC, or the novel T2C have been used for researching genomic architecture, its dynamics has remained underexplored. Here, we present a novel approach to dissect intramolecular polymer dynamics from fluorescence intensity fluctuations measured with fluorescence correlation spectroscopy (FCS) to investigate the higher order chromatin dynamics in living cells. Using fluorescently tagged linker histone H1 and core histones H2A and H2B as tracer molecules, we found distinct chromatin relaxation times of ~160 ms for open and ~90 ms for dense chromatin areas, corresponding to radii of gyration of 240 and 300 nm for the topologically independent chromatin units. According to their genomic content of ~1 Mb, these domains correspond to subchromosomal domains, already seen by FISH, and histone GFP labelling beforehand and correspond to so called distinct topologically associating domains (TADs). This is an impressive advancements in the field, since details on the dynamic and structural properties of subchromosomal domains/TADs in living cells are scarce. Based on these results, quantitative analytical and numerical modelling provided access to mass density, persistence length and topological information of chromatin. It allowed to extract these parameters from 3C/5C/HiC/T2C results, to predict chromatin conformation and distance data, and to identify complex looping as crucial for domain formation. Especially, in combination with T2C, a recently developed selective highthroughput high-resolution chromosomal interaction capture technique (see abstract T.A. Knoch & M. Wachsmuth, Determination of the three-dimensional organization of chromatin by modelling-supported selective chromosomal interaction capture (T2C)), which provides very good signal-to-noise ratio, we present a comprehensive systematic approach for the understanding of chromatin dynamics and structure as well as for insight into their impact on gene regulation. As an outlook, we show light-sheet microscopy-based FCS maps of chromatin domain dynamics.

Polycomb-repressive complex 1 (PRC1) has a strong influence on 3D genome organization, mediating local chromatin compaction as well as localized and chromosome-wide clustering of target loci. Several subunits of PRC1 have been shown to have the capacity to form biomolecular condensates through liquid-liquid phase separation in vitro and when tagged and over-expressed in cells. Here, we use 1,6-hexandiol, which disrupts liquid-like condensates, to examine the role of endogenous PRC1 biomolecular condensates on local and chromosomewide clustering of PRC1-bound loci. Using imaging and chromatin immunoprecipitation combined with deep sequencing analyses, we show that PRC1-mediated chromatin compaction and clustering of targeted genomic loci -at megabase and tens of megabase length scales -can be reversibly disrupted by the addition and subsequent removal of 1,6-hexandiol to mouse embryonic stem cells. Decompaction and dispersal of polycomb domains and clusters cannot be solely attributable to the reduction of PRC1 binding following 1,6-hexandiol treatment as the addition of 2,5-hexandiol has similar effects on binding despite this alcohol not perturbing PRC1-mediated 3D clustering, at least at the sub-megabase and megabase scales. These results suggest that weak hydrophobic interactions between PRC1 molecules, characteristic of liquidliquid phase separation, have a role in polycomb-mediated genome organization.

Genome-wide association studies (GWAS) have identified hundreds of genetic loci associated with autoimmune disease, but the causal variants and their contribution to immune dysregulation remain largely unknown. We measured the dynamics of chromosome conformation, chromatin accessibility, and gene transcription across three phases of naive human CD4+ T cell activation and co-localized active cis-regulatory elements with the 95% credible set of variants from 15 autoimmune GWAS. Reorganization of chromosome structure placed these elements in direct contact with ~1,200 protein-coding genes, at least one-third of which were dynamically regulated by stimulation. The set of implicated genes is enriched for high-throughput CRISPR screen targets that control multiple aspects of CD4+ T cell activation, and we pharmacologically validated eight novel gene products as potent regulators of T cell proliferation. These maps also allowed the identification and functional validation of a novel stretch of intergenic enhancers for the autoimmune gene IL2 whose activity is influenced by autoimmune-associated genetic variation. This study represents a powerful strategy and resource for assigning physiologic relevance to autoimmune-risk variants and identify novel genes that control T cell activation and function.

Background High-throughput sequencing Chromosome Conformation Capture (Hi-C) allows the study of DNA interactions and 3D chromosome folding at the genome-wide scale. Usually, these data are represented as matrices describing the binary contacts among the different chromosome regions. On the other hand, a graph-based representation can be advantageous to describe the complex topology achieved by the DNA in the nucleus of eukaryotic cells. Methods Here we discuss the use of a graph database for storing and analysing data achieved by performing Hi-C experiments. The main issue is the size of the produced data and, working with a graph-based representation, the consequent necessity of adequately managing a large number of edges (contacts) connecting nodes (genes), which represents the sources of information. For this, currently available graph visualisation tools and libraries fall short with Hi-C data. The use of graph databases, instead, supports both the analysis and the visualisatio...

We review the picture of chromatin large-scale 3D organization emerging from the analysis of Hi-C data and polymer modeling. In higher mammals, Hi-C contact maps reveal a complex higher-order organization, extending from the sub-Mb to chromosomal scales, hierarchically folded in a structure of domains-within-domains (metaTADs). The domain folding hierarchy is partially conserved throughout differentiation, and deeply correlated to epigenomic features. Rearrangements in the metaTAD topology relate to gene expression modifications: in particular, in neuronal differentiation models, topologically associated domains (TADs) tend to have coherent expression changes within architecturally conserved metaTAD niches. To identify the nature of architectural domains and their molecular determinants within a principled approach, we discuss models based on polymer physics. We show that basic concepts of interacting polymer physics explain chromatin spatial organization across chromosomal scales and cell types. The 3D structure of genomic loci can be derived with high accuracy and its molecular determinants identified by crossing information with epigenomic databases. In particular, we illustrate the case of the Sox9 locus, linked to human congenital disorders. The model in-silico predictions on the effects of genomic rearrangements are confirmed by available 5C data. That can help establishing new diagnostic tools for diseases linked to chromatin mis-folding, such as congenital disorders and cancer.

The identification of regulatory elements for a given target gene poses a significant technical challenge owing to the variability in the positioning and effect sizes of regulatory elements to a target gene. Some progress has been made with the bioinformatic prediction of the existence and function of proximal epigenetic modifications associated with activated gene expression using conserved transcription factor binding sites. Chromatin conformation capture studies have revolutionized our ability to discover physical chromatin contacts between sequences and even within an entire genome. Circular chromatin conformation capture coupled with next-generation sequencing (4C-seq), in particular, is designed to discover all possible physical chromatin interactions for a given sequence of interest (viewpoint), such as a target gene or a regulatory enhancer. Current 4C-seq strategies directly sequence from within the viewpoint but require numerous and diverse viewpoints to be simultaneously sequenced to avoid the technical challenges of uniform base calling (imaging) with next generation sequencing platforms. This volume of experiments may not be practical for many laboratories. Here, we report a modified approach to the 4C-seq protocol that incorporates both an additional restriction enzyme digest and qPCR-based amplification steps that are designed to facilitate a greater capture of diverse sequence reads and mitigate the potential for PCR bias, respectively. Our modified 4C method is amenable to the standard molecular biology lab for assessing chromatin architecture.

The identification of regulatory elements for a given target gene poses a significant technical challenge owing to the variability in the positioning and effect sizes of regulatory elements to a target gene. Some progress has been made with the bioinformatic prediction of the existence and function of proximal epigenetic modifications associated with activated gene expression using conserved transcription factor binding sites. Chromatin conformation capture studies have revolutionized our ability to discover physical chromatin contacts between sequences and even within an entire genome. Circular chromatin conformation capture coupled with next-generation sequencing (4C-seq), in particular, is designed to discover all possible physical chromatin interactions for a given sequence of interest (viewpoint), such as a target gene or a regulatory enhancer. Current 4C-seq strategies directly sequence from within the viewpoint but require numerous and diverse viewpoints to be simultaneously sequenced to avoid the technical challenges of uniform base calling (imaging) with next generation sequencing platforms. This volume of experiments may not be practical for many laboratories. Here, we report a modified approach to the 4C-seq protocol that incorporates both an additional restriction enzyme digest and qPCR-based amplification steps that are designed to facilitate a greater capture of diverse sequence reads and mitigate the potential for PCR bias, respectively. Our modified 4C method is amenable to the standard molecular biology lab for assessing chromatin architecture.

The identification of cell-type-specific 3D chromatin interactions between regulatory elements can help to decipher gene regulation and to interpret the function of disease-associated non-coding variants. However, current chromosome conformation capture (3C) technologies are unable to resolve interactions at this resolution when only small numbers of cells are available as input. We therefore present ChromaFold, a deep learning model that predicts 3D contact maps and regulatory interactions from single-cell ATAC sequencing (scATAC-seq) data alone. ChromaFold uses pseudobulk chromatin accessibility, co-accessibility profiles across metacells, and predicted CTCF motif tracks as input features and employs a lightweight architecture to enable training on standard GPUs. Once trained on paired scATAC-seq and Hi-C data in human cell lines and tissues, ChromaFold can accurately predict both the 3D contact map and peak-level interactions across diverse human and mouse test cell types. In ben...

The transcription factor Runx1 is essential for definitive hematopoiesis, and the RUNX1 gene is frequently translocated or mutated in leukemia. Runx1 is transcribed from two promoters, P1 and P2, to give rise to different protein isoforms. Although the expression of Runx1 must be tightly regulated for normal blood development, the mechanisms that regulate Runx1 isoform expression during hematopoiesis remain poorly understood. Gene regulatory elements located in non-coding DNA are likely to be important for Runx1 transcription. Here we use circular chromosome conformation capture sequencing to identify DNA interactions with the P1 and P2 promoters of Runx1, and the previously identified +24 enhancer, in the mouse multipotent hematopoietic progenitor cell line HPC-7. The active promoter, P1, interacts with nine non-coding regions that are occupied by transcription factors within a 1 Mb topologically associated domain. Eight of nine regions function as blood-specific enhancers in zebra...

Chromatin architecture, a key regulator of gene expression, can be inferred using chromatin contact data from chromosome conformation capture, or Hi-C. However, classical Hi-C does not preserve multi-way contacts. Here we use long sequencing reads to map genome-wide multi-way contacts and investigate higher order chromatin organization in the human genome. We use hypergraph theory for data representation and analysis, and quantify higher order structures in neonatal fibroblasts, biopsied adult fibroblasts, and B lymphocytes. By integrating multi-way contacts with chromatin accessibility, gene expression, and transcription factor binding, we introduce a data-driven method to identify cell type-specific transcription clusters. We provide transcription factor-mediated functional building blocks for cell identity that serve as a global signature for cell types.

The dynamic three-dimensional chromatin architecture of genomes and the obvious co-evolutionary connection to its function – the storage and expression of genetic information – is still debated after ~170 years. With a systems genomics approach combining a novel selective high-throughput chromosomal interaction capture (T2C) with quantitative polymer simulations and scaling analysis of architecture and DNA sequence, we determined and cross-proved the final architecture of genomes with unprecedented molecular resolution and dynamic range from single base pairs to entire chromosomes: for several genetic loci of different species, cell type, cell cycle, and functional states a chromatin quasi-fibre exists with 5±1 nucleosome per 11 nm, which folds into stable(!) 40-100 kbp loops forming stable(!) aggregates/rosettes which are connected by a ~50 kbp chromatin linker. Polymer simulations using Monte Carlo and Brownian dynamics approaches confirm this and predict and explain additional ex...

Despite all the efforts the three-dimensional higher-order architecture and dynamics in the cell nucleus are still debated. The regulation of genes, their transcription, replication, as well as differentiation in Eukarya is, however, closely connected to this architecture and dynamics. Here, an evaluation and review framework is setup to investigate the folding of a 30 nm chromatin fibre into chromosome territories by comparing computer simulations of two different chromatin topologies to experiments: The Multi-Loop-Subcompartment (MLS) model, in which small loops form rosettes connected by chromatin linkers, and the Random-Walk/Giant-Loop (RW/GL) model, in which large loops are attached to a flexible nonprotein backbone, were simulated for various loop, rosette, and linker sizes. The 30 nm chromatin fibre was modelled as a polymer chain with stretching, bending, and excluded volume interactions. A spherical boundary potential simulated the confinement by other chromosomes and the nuclear envelope. Monte Carlo and Brownian Dynamics methods were applied to generate chain configurations at thermodynamic equilibrium. Both the MLS and the RW/GL models form chromosome territories, with different morphologies: The MLS rosettes form distinct subchromosomal domains, compatible in size as those from light microscopic observations. In contrast, the big RW/GL loops lead to a more homogeneous chromatin distribution. Only the MLS model agrees with the low overlap of chromosomes, their arms, and subchromosomal domains found experimentally. A review of experimental spatial distance measurements between genomic markers labelled by FISH as a function of their genomic separation from different publications and comparison to simulated spatial distances also favours an MLS-like model with loops and linkers of 63 to 126 kbp. The chromatin folding topology also reduces the apparent persistence length of the chromatin fibre to a value significantly lower than the free solution persistence length, explaining the low persistence lengths found various experiments. The predicted large spaces between the chromatin fibres allow typically sized biological molecules to reach nearly every location in the nucleus by moderately obstructed diffusion and disagrees with the much simplified assumption that defined channels between territories for molecular transport as in the Interchromosomal Domain (ICD) hypothesis exist. All this is also in agreement with recent selective high-resolution chromosome interaction capture (T2C) experiments, the scaling behaviour of the DNA sequence, the dynamics of the chromatin fibre, the nuclear diffusion of molecules, as well as other experiments. In summary, this polymer simulation framework compared to experimental data clearly favours only a quasi-chromatin fibre forming a stable multi-loop aggregate/rosette like genome organization and dynamics whose local topology is tightly connected to the global morphology and dynamics of the cell nucleus.

High-throughput chromosome conformation capture (Hi-C) technology enables the investigation of genome-wide interactions among chromosome loci. Current algorithms focus on topologically associating domains (TADs), that are contiguous clusters along the genome coordinate, to describe the hierarchical structure of chromosomes. However, high resolution Hi-C displays a variety of interaction patterns beyond what current TAD detection methods can capture. Here, we present BHi-Cect, a novel top-down algorithm that finds clusters by considering every locus with no assumption of genomic contiguity using spectral clustering. Our results reveal that the hierarchical structure of chromosome is organized as ‘enclaves’, which are complex interwoven clusters at both local and global scales. We show that the nesting of local clusters within global clusters characterizing enclaves, is associated with the epigenomic activity found on the underlying DNA. Furthermore, we show that the hierarchical nest...

Chromatin conformation capture followed by next-generation sequencing in combination with large-scale polymer simulations (4DHiC) produces detailed information on genomic loci interactions, allowing for the interrogation of 3D spatial genomic structures. Here, Hi-C data was acquired from the infection of fetal lung fibroblast (MRC5) cells with α-coronavirus 229E (CoV229E). Experimental Hi-C contact maps were used to determine viral-induced changes in genomic architecture over a 48-hour time period following viral infection, revealing substantial alterations in contacts within chromosomes and in contacts between different chromosomes. To gain further structural insight and quantify the underlying changes, we applied the 4DHiC polymer simulation method to reconstruct the 3D genomic structures and dynamics corresponding to the Hi-C maps. The models successfully reproduced experimental Hi-C data, including the changes in contacts induced by viral infection. Our 3D spatial simulations uncovered widespread chromatin restructuring, including increased chromosome compactness and A-B compartment mixing arising from infection. Our model also suggests increased spatial accessibility to regions containing interferon-stimulated genes upon infection with CoV229E, followed by chromatin restructuring at later time points, potentially inducing the migration of chromatin into more compact regions. This is consistent with previously observed suppression of gene expression. Our spatial genomics study provides a mechanistic structural basis for changes in chromosome architecture induced by coronavirus infection in lung cells.

The High-throughput Chromosome Conformation Capture (Hi-C) technique combines the power of the Next Generation Sequencing technologies with chromosome conformation capture approach to study the 3D chromatin organization at the genome-wide scale. Although such a technique is quite recent, many tools are already available for preprocessing and analyzing Hi-C data, allowing to identify chromatin loops, topological associating domains and A/B compartments. However, only a few of them provide an exhaustive analysis pipeline or allow to easily integrate and visualize other omic layers. Moreover, most of the available tools are designed for expert users, who have great confidence with command-line applications. In this paper, we present HiCeekR (), a novel R Graphical User Interface (GUI) that allows researchers to easily perform a complete Hi-C data analysis. With the aid of the Shiny libraries, it integrates several R/Bioconductor packages for Hi-C data analysis and visualization, guiding the user during the entire process. Here, we describe its architecture and functionalities, then illustrate its capabilities using a publicly available dataset.

The High-throughput Chromosome Conformation Capture (Hi-C) technique combines the power of the Next Generation Sequencing technologies with chromosome conformation capture approach to study the 3D chromatin organization at the genome-wide scale. Although such a technique is quite recent, many tools are already available for preprocessing and analyzing Hi-C data, allowing to identify chromatin loops, topological associating domains and A/B compartments. However, only a few of them provide an exhaustive analysis pipeline or allow to easily integrate and visualize other omic layers. Moreover, most of the available tools are designed for expert users, who have great confidence with command-line applications. In this paper, we present HiCeekR (https:// github.com/lucidif/HiCeekR), a novel R Graphical User Interface (GUI) that allows researchers to easily perform a complete Hi-C data analysis. With the aid of the Shiny libraries, it integrates several R/Bioconductor packages for Hi-C data analysis and visualization, guiding the user during the entire process. Here, we describe its architecture and functionalities, then illustrate its capabilities using a publicly available dataset.