A de novo transcription-dependent TAD boundary underpins critical multiway interactions during antibody class switch recombination.

Interactions between transcription and cohesin-mediated loop extrusion can influence 3D chromatin architecture. However, their relevance in biology is unclear. Here, we report a direct role for such interactions in the mechanism of antibody class switch recombination (CSR) at the murine immunoglobulin heavy chain locus (Igh). Using Tri-C to measure higher-order multiway interactions on single alleles, we find that the juxtaposition (synapsis) of transcriptionally active donor and acceptor Igh switch (S) sequences, an essential step in CSR, occurs via the interaction of loop extrusion complexes with a de novo topologically associating domain (TAD) boundary formed via transcriptional activity across S regions. Surprisingly, synapsis occurs predominantly in proximity to the 3' CTCF-binding element (3'CBE) rather than the Igh super-enhancer, suggesting a two-step mechanism whereby transcription of S regions is not topologically coupled to synapsis, as has been previously proposed. Altogether, these insights advance our understanding of how 3D chromatin architecture regulates CSR.

Ultrastructural Details of Mammalian Chromosome Architecture.

Over the past decade, 3C-related methods have provided remarkable insights into chromosome folding in vivo. To overcome the limited resolution of prior studies, we extend a recently developed Hi-C variant, Micro-C, to map chromosome architecture at nucleosome resolution in human ESCs and fibroblasts. Micro-C robustly captures known features of chromosome folding including compartment organization, topologically associating domains, and interactions between CTCF binding sites. In addition, Micro-C provides a detailed map of nucleosome positions and localizes contact domain boundaries with nucleosomal precision. Compared to Hi-C, Micro-C exhibits an order of magnitude greater dynamic range, allowing the identification of ∼20,000 additional loops in each cell type. Many newly identified peaks are localized along extrusion stripes and form transitive grids, consistent with their anchors being pause sites impeding cohesin-dependent loop extrusion. Our analyses comprise the highest-resolution maps of chromosome folding in human cells to date, providing a valuable resource for studies of chromosome organization.

Resolving the 3D Landscape of Transcription-Linked Mammalian Chromatin Folding.

Whereas folding of genomes at the large scale of epigenomic compartments and topologically associating domains (TADs) is now relatively well understood, how chromatin is folded at finer scales remains largely unexplored in mammals. Here, we overcome some limitations of conventional 3C-based methods by using high-resolution Micro-C to probe links between 3D genome organization and transcriptional regulation in mouse stem cells. Combinatorial binding of transcription factors, cofactors, and chromatin modifiers spatially segregates TAD regions into various finer-scale structures with distinct regulatory features including stripes, dots, and domains linking promoters-to-promoters (P-P) or enhancers-to-promoters (E-P) and bundle contacts between Polycomb regions. E-P stripes extending from the edge of domains predominantly link co-expressed loci, often in the absence of CTCF and cohesin occupancy. Acute inhibition of transcription disrupts these gene-related folding features without altering higher-order chromatin structures. Our study uncovers previously obscured finer-scale genome organization, establishing functional links between chromatin folding and gene regulation.

Condensin-Dependent Chromatin Compaction Represses Transcription Globally during Quiescence.

Quiescence is a stress-resistant state in which cells reversibly exit the cell cycle and suspend most processes. Quiescence is essential for stem cell maintenance, and its misregulation is implicated in tumor formation. One of the hallmarks of quiescent cells is highly condensed chromatin. Because condensed chromatin often correlates with transcriptional silencing, it has been hypothesized that chromatin compaction represses transcription during quiescence. However, the technology to test this model by determining chromatin structure within cells at gene resolution has not previously been available. Here, we use Micro-C XL to map chromatin contacts at single-nucleosome resolution genome-wide in quiescent Saccharomyces cerevisiae cells. We describe chromatin domains on the order of 10-60 kilobases that, only in quiescent cells, are formed by condensin-mediated loops. Condensin depletion prevents the compaction of chromatin within domains and leads to widespread transcriptional de-repression. Finally, we demonstrate that condensin-dependent chromatin compaction is conserved in quiescent human fibroblasts.

Distinct Classes of Chromatin Loops Revealed by Deletion of an RNA-Binding Region in CTCF.

Mammalian genomes are folded into topologically associating domains (TADs), consisting of chromatin loops anchored by CTCF and cohesin. Some loops are cell-type specific. Here we asked whether CTCF loops are established by a universal or locus-specific mechanism. Investigating the molecular determinants of CTCF clustering, we found that CTCF self-association in vitro is RNase sensitive and that an internal RNA-binding region (RBRi) mediates CTCF clustering and RNA interaction in vivo. Strikingly, deleting the RBRi impairs about half of all chromatin loops in mESCs and causes deregulation of gene expression. Disrupted loop formation correlates with diminished clustering and chromatin binding of RBRi mutant CTCF, which in turn results in a failure to halt cohesin-mediated extrusion. Thus, CTCF loops fall into at least two classes: RBRi-independent and RBRi-dependent loops. We speculate that evidence for RBRi-dependent loops may provide a molecular mechanism for establishing cell-specific CTCF loops, potentially regulated by RNA(s) or other RBRi-interacting partners.

Hi-C techniques: from genome assemblies to transcription regulation.

The invention of chromosome-conformation capture (3C) techniques, in particular the key method Hi-C providing genome-wide information about chromatin contacts, revolutionized the way we study the three-dimensional (3D) organization of the nuclear genome and how it impacts transcription, replication and DNA repair. Since the frequency of chromatin contacts between pairs of genomic segments predictably relates to the distance in the linear genome, the Hi-C information has also proved useful for scaffolding genomic sequences. Here, we review recent enhancements in experimental procedures of Hi-C and its various derivatives such as Micro-C, HiChIP, and Capture Hi-C. We assess advantages and limitations of the techniques, and present examples of their use in recent plant studies. We also report on progress in computational tools used in assembling genome sequences.

A comparison of topologically associating domain callers over mammals at high resolution.

BACKGROUND: Topologically associating domains (TADs) are locally highly-interacting genome regions, which also play a critical role in regulating gene expression in the cell. TADs have been first identified while investigating the 3D genome structure over High-throughput Chromosome Conformation Capture (Hi-C) interaction dataset. Substantial degree of efforts have been devoted to develop techniques for inferring TADs from Hi-C interaction dataset. Many TAD-calling methods have been developed which differ in their criteria and assumptions in TAD inference. Correspondingly, TADs inferred via these callers vary in terms of both similarities and biological features they are enriched in. RESULT: We have carried out a systematic comparison of 27 TAD-calling methods over mammals. We use Micro-C, a recent high-resolution variant of Hi-C, to compare TADs at a very high resolution, and classify the methods into 3 categories: feature-based methods, Clustering methods, Graph-partitioning methods. We have evaluated TAD boundaries, gaps between adjacent TADs, and quality of TADs across various criteria. We also found particularly CTCF and Cohesin proteins to be effective in formation of TADs with corner dots. We have also assessed the callers performance on simulated datasets since a gold standard for TADs is missing. TAD sizes and numbers change remarkably between TAD callers and dataset resolutions, indicating that TADs are hierarchically-organized domains, instead of disjoint regions. A core subset of feature-based TAD callers regularly perform the best while inferring reproducible domains, which are also enriched for TAD related biological properties. CONCLUSION: We have analyzed the fundamental principles of TAD-calling methods, and identified the existing situation in TAD inference across high resolution Micro-C interaction datasets over mammals. We come up with a systematic, comprehensive, and concise framework to evaluate the TAD-calling methods performance across Micro-C datasets. Our research will be useful in selecting appropriate methods for TAD inference and evaluation based on available data, experimental design, and biological question of interest. We also introduce our analysis as a benchmarking tool with publicly available source code.

ProbC: joint modeling of epigenome and transcriptome effects in 3D genome.

BACKGROUND: Hi-C and its high nucleosome resolution variant Micro-C provide a window into the spatial packing of a genome in 3D within the cell. Even though both techniques do not directly depend on the binding of specific antibodies, previous work has revealed enriched interactions and domain structures around multiple chromatin marks; epigenetic modifications and transcription factor binding sites. However, the joint impact of chromatin marks in Hi-C and Micro-C interactions have not been globally characterized, which limits our understanding of 3D genome characteristics. An emerging question is whether it is possible to deduce 3D genome characteristics and interactions by integrative analysis of multiple chromatin marks and associate interactions to functionality of the interacting loci. RESULT: We come up with a probabilistic method PROBC to decompose Hi-C and Micro-C interactions by known chromatin marks. PROBC is based on convex likelihood optimization, which can directly take into account both interaction existence and nonexistence. Through PROBC, we discover histone modifications (H3K27ac, H3K9me3, H3K4me3, H3K4me1) and CTCF as particularly predictive of Hi-C and Micro-C contacts across cell types and species. Moreover, histone modifications are more effective than transcription factor binding sites in explaining the genome's 3D shape through these interactions. PROBC can successfully predict Hi-C and Micro-C interactions in given species, while it is trained on different cell types or species. For instance, it can predict missing nucleosome resolution Micro-C interactions in human ES cells trained on mouse ES cells only from these 5 chromatin marks with above 0.75 AUC. Additionally, PROBC outperforms the existing methods in predicting interactions across almost all chromosomes. CONCLUSION: Via our proposed method, we optimally decompose Hi-C interactions in terms of these chromatin marks at genome and chromosome levels. We find a subset of histone modifications and transcription factor binding sites to be predictive of both Hi-C and Micro-C interactions and TADs across human, mouse, and different cell types. Through learned models, we can predict interactions on species just from chromatin marks for which Hi-C data may be limited.

Nucleosome positions alone can be used to predict domains in yeast chromosomes.

We use molecular dynamics simulations based on publicly available micrococcal nuclease sequencing data for nucleosome positions to predict the 3D structure of chromatin in the yeast genome. Our main aim is to shed light on the mechanism underlying the formation of chromosomal interaction domains, chromosome regions of around 0.5 to 10 kbp which show enriched self-interactions, which were experimentally observed in recent MicroC experiments (importantly these are at a different length scale from the 100- to 1,000-kbp-sized domains observed in higher eukaryotes). We show that the sole input of nucleosome positioning data is already sufficient to determine the patterns of chromatin interactions and domain boundaries seen experimentally to a high degree of accuracy. Since the nucleosome spacing so strongly affects the larger-scale domain structure, we next examine the genome-wide linker-length distribution in more detail, finding that it is highly irregular and varies in different genomic regions such as gene bodies, promoters, and active and inactive genes. Finally we use our simple simulation model to characterize in more detail how irregular nucleosome spacing may affect local chromatin structure.

Unraveling quiescence-specific repressive chromatin domains.

Quiescence is a highly conserved inactive life stage in which the cell reversibly exits the cell cycle in response to external cues. Quiescence is essential for diverse processes such as the maintenance of adult stem cell stores, stress resistance, and longevity, and its misregulation has been implicated in cancer. Although the non-cycling nature of quiescent cells has made obtaining sufficient quantities of quiescent cells for study difficult, the development of a Saccharomyces cerevisiae model of quiescence has recently enabled detailed investigation into mechanisms underlying the quiescent state. Like their metazoan counterparts, quiescent budding yeast exhibit widespread transcriptional silencing and dramatic chromatin condensation. We have recently found that the structural maintenance of chromosomes (SMC) complex condensin binds throughout the quiescent budding yeast genome and induces the formation of large chromatin loop domains. In the absence of condensin, quiescent cell chromatin is decondensed and transcription is de-repressed. Here, we briefly discuss our findings in the larger context of the genome organization field.

C2c: Predicting Micro-C from Hi-C.

MOTIVATION: High-resolution Hi-C data, capable of detecting chromatin features below the level of Topologically Associating Domains (TADs), significantly enhance our understanding of gene regulation. Micro-C, a variant of Hi-C incorporating a micrococcal nuclease (MNase) digestion step to examine interactions between nucleosome pairs, has been developed to overcome the resolution limitations of Hi-C. However, Micro-C experiments pose greater technical challenges compared to Hi-C, owing to the need for precise MNase digestion control and higher-resolution sequencing. Therefore, developing computational methods to derive Micro-C data from existing Hi-C datasets could lead to better usage of a large amount of existing Hi-C data in the scientific community and cost savings. RESULTS: We developed C2c ("high" or upper case C to "micro" or lower case c), a computational tool based on a residual neural network to learn the mapping between Hi-C and Micro-C contact matrices and then predict Micro-C contact matrices based on Hi-C contact matrices. Our evaluation results show that the predicted Micro-C contact matrices reveal more chromatin loops than the input Hi-C contact matrices, and more of the loops detected from predicted Micro-C match the promoter-enhancer interactions. Furthermore, we found that the mutual loops from real and predicted Micro-C better match the ChIA-PET data compared to Hi-C and real Micro-C loops, and the predicted Micro-C leads to more TAD-boundaries detected compared to the Hi-C data. The website URL of C2c can be found in the Data Availability Statement.

Considerations and caveats for analyzing chromatin compartments.

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

Multiple genes in a single GWAS risk locus synergistically mediate aberrant synaptic development and function in human neurons.

The mechanistic tie between genome-wide association study (GWAS)-implicated risk variants and disease-relevant cellular phenotypes remains largely unknown. Here, using human induced pluripotent stem cell (hiPSC)-derived neurons as a neurodevelopmental model, we identify multiple schizophrenia (SZ) risk variants that display allele-specific open chromatin (ASoC) and are likely to be functional. Editing the strongest ASoC SNP, rs2027349, near vacuolar protein sorting 45 homolog (VPS45) alters the expression of VPS45, lncRNA AC244033.2, and a distal gene, C1orf54. Notably, the transcriptomic changes in neurons are associated with SZ and other neuropsychiatric disorders. Neurons carrying the risk allele exhibit increased dendritic complexity and hyperactivity. Interestingly, individual/combinatorial gene knockdown shows that these genes alter cellular phenotypes in a non-additive synergistic manner. Our study reveals that multiple genes at a single GWAS risk locus mediate a compound effect on neural function, providing a mechanistic link between a non-coding risk variant and disease-related cellular phenotypes.

Nucleosome-Omics: A Perspective on the Epigenetic Code and 3D Genome Landscape.

Genetic information is loaded on chromatin, which involves DNA sequence arrangement and the epigenetic landscape. The epigenetic information including DNA methylation, nucleosome positioning, histone modification, 3D chromatin conformation, and so on, has a crucial impact on gene transcriptional regulation. Out of them, nucleosomes, as basal chromatin structural units, play an important central role in epigenetic code. With the discovery of nucleosomes, various nucleosome-level technologies have been developed and applied, pushing epigenetics to a new climax. As the underlying methodology, next-generation sequencing technology has emerged and allowed scientists to understand the epigenetic landscape at a genome-wide level. Combining with NGS, nucleosome-omics (or nucleosomics) provides a fresh perspective on the epigenetic code and 3D genome landscape. Here, we summarized and discussed research progress in technology development and application of nucleosome-omics. We foresee the future directions of epigenetic development at the nucleosome level.

MoDLE: high-performance stochastic modeling of DNA loop extrusion interactions.

DNA loop extrusion emerges as a key process establishing genome structure and function. We introduce MoDLE, a computational tool for fast, stochastic modeling of molecular contacts from DNA loop extrusion capable of simulating realistic contact patterns genome wide in a few minutes. MoDLE accurately simulates contact maps in concordance with existing molecular dynamics approaches and with Micro-C data and does so orders of magnitude faster than existing approaches. MoDLE runs efficiently on machines ranging from laptops to high performance computing clusters and opens up for exploratory and predictive modeling of 3D genome structure in a wide range of settings.

Mapping Mammalian 3D Genomes by Micro-C.

3D genome mapping aims at connecting the physics of chromatin folding to the underlying biological events, and applications of various chromosomal conformation capture (3C) assays continue to discover critical roles of genome folding in regulating nuclear functions. To interrogate the full spectrum of chromatin folding ranging from the level of nucleosomes to full chromosomes in mammals, we developed an enhanced 3C-based method called Micro-C. The protocol employs Micrococcal nuclease (MNase) to fragment the genome, which overcomes the resolution limit of restriction enzyme-based methods, enabling the estimation of contact frequencies between proximal nucleosomes. Such improvements successfully resolve the fine-scale level of chromatin folding, including enhancer-promoter or promoter-promoter interactions, genic and nucleosomal folding, and boost the signal-to-noise ratio in detecting loops and substructures underlying TADs. In this chapter, we will thoroughly discuss the details of the Micro-C protocol and critical parameters to consider for generating high-quality Micro-C maps.

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.

Local chromatin fiber folding represses transcription and loop extrusion in quiescent cells.

A longstanding hypothesis is that chromatin fiber folding mediated by interactions between nearby nucleosomes represses transcription. However, it has been difficult to determine the relationship between local chromatin fiber compaction and transcription in cells. Further, global changes in fiber diameters have not been observed, even between interphase and mitotic chromosomes. We show that an increase in the range of local inter-nucleosomal contacts in quiescent yeast drives the compaction of chromatin fibers genome-wide. Unlike actively dividing cells, inter-nucleosomal interactions in quiescent cells require a basic patch in the histone H4 tail. This quiescence-specific fiber folding globally represses transcription and inhibits chromatin loop extrusion by condensin. These results reveal that global changes in chromatin fiber compaction can occur during cell state transitions, and establish physiological roles for local chromatin fiber folding in regulating transcription and chromatin domain formation.

The macro and micro of chromosome conformation capture.

The 3D organization of the genome facilitates gene regulation, replication, and repair, making it a key feature of genomic function and one that remains to be properly understood. Over the past two decades, a variety of chromosome conformation capture (3C) methods have delineated genome folding from megabase-scale compartments and topologically associating domains (TADs) down to kilobase-scale enhancer-promoter interactions. Understanding the functional role of each layer of genome organization is a gateway to understanding cell state, development, and disease. Here, we discuss the evolution of 3C-based technologies for mapping 3D genome organization. We focus on genomics methods and provide a historical account of the development from 3C to Hi-C. We also discuss ChIP-based techniques that focus on 3D genome organization mediated by specific proteins, capture-based methods that focus on particular regions or regulatory elements, 3C-orthogonal methods that do not rely on restriction digestion and proximity ligation, and methods for mapping the DNA-RNA and RNA-RNA interactomes. We consider the biological discoveries that have come from these methods, examine the mechanistic contributions of CTCF, cohesin, and loop extrusion to genomic folding, and detail the 3D genome field's current understanding of nuclear architecture. Finally, we give special consideration to Micro-C as an emerging frontier in chromosome conformation capture and discuss recent Micro-C findings uncovering fine-scale chromatin organization in unprecedented detail. This article is categorized under: Gene Expression and Transcriptional Hierarchies > Regulatory Mechanisms Gene Expression and Transcriptional Hierarchies > Gene Networks and Genomics.

Cohesin residency determines chromatin loop patterns.

The organization of chromatin into higher order structures is essential for chromosome segregation, the repair of DNA-damage, and the regulation of gene expression. Using Micro-C XL to detect chromosomal interactions, we observed the pervasive presence of cohesin-dependent loops with defined positions throughout the genome of budding yeast, as seen in mammalian cells. In early S phase, cohesin stably binds to cohesin associated regions (CARs) genome-wide. Subsequently, positioned loops accumulate with CARs at the bases of the loops. Cohesin regulators Wpl1 and Pds5 alter the levels and distribution of cohesin at CARs, changing the pattern of positioned loops. From these observations, we propose that cohesin with loop extrusion activity is stopped by preexisting CAR-bound cohesins, generating positioned loops. The patterns of loops observed in a population of wild-type and mutant cells can be explained by this mechanism, coupled with a heterogeneous residency of cohesin at CARs in individual cells.