OnTAD: hierarchical domain structure reveals the divergence of activity among TADs and boundaries

RobusTAD: reference panel based annotation of nested topologically associating domains

Topologically associating domains (TADs) are fundamental units of 3D genomes and play essential roles in gene regulation. Hi-C data suggests a hierarchical organization of TADs. Accurately annotating nested TADs from Hi-C data remains challenging, both in terms of the precise identification of boundaries and the correct inference of hierarchies. While domain boundary is relatively well conserved across cells, few approaches have taken advantage of this fact. Here, we present RobusTAD to annotate TAD hierarchies. It incorporates additional Hi-C data to refine boundaries annotated from the study sample. RobusTAD outperforms existing tools at boundary and domain annotation across several benchmarking tasks.

BINDER achieves accurate identification of hierarchical TADs by comprehensively characterizing consensus TAD boundaries

As crucial chromatin structures, hierarchical TADs play important roles in epigenetic organization, transcriptional activity, gene regulation, and cell differentiation. Currently, it remains a highly challenging task to accurately identify hierarchical TADs in a computational manner. The key bottleneck for existing TAD callers lies in the difficulty in the prediction of precise TAD boundaries. We solve this problem by introducing a novel algorithm, called BINDER, which conducts a boundary consensus approach, and then precisely locate hierarchical TAD boundaries by developing a multifaceted boundary characterization strategy. In comparison with other leading TAD callers, BINDER shows significant improvement in identifying hierarchical TADs and exhibits the strongest robustness with ultrasparse data, which supports the importance of boundary identification in calling hierarchical TADs. Applying BINDER to experimental data and mouse hematopoietic cases, we find that the hierarchical TADs identified by BINDER show strong biological relevance in their epigenetic organization, transcriptional activity, DNA motifs, and coregulation during cellular differentiation. BINDER discovers differences in the enrichment of two specific transcription factors, CHD1 and CHD2, at TAD boundaries with different hierarchies. It also observes variations in the gene expression of TADs with different hierarchies during cellular differentiation.

Complex determinants of R-loop formation at transposable elements and major DNA satellites

Aberrant activation of transposable elements (TEs) has been a well-documented source of genomic instability and disease, stemming from their insertion into genes and their imposition of epigenetic effects on nearby loci. However, the extent to which their disruptive effects involve concomitant or subsequent formation of DNA:RNA hybrids (R-loops) remains unknown. Here, we used DNA:RNA immunoprecipitation followed by high-throughput sequencing (DRIP-seq) to map the R-loop profiles of TEs and satellites in Drosophila melanogaster ovaries in control and rhino knockout flies, where dozens of TE families are derepressed. We observe that R-loops form primarily in LTR retrotransposons that carry A/T-rich sequence motifs, which are known to favor R-loop formation at genes in Drosophila and other species. We also report evidence of R-loop formation at 11 of 14 highly abundant D. melanogaster DNA satellites. R-loop formation is positively correlated with expression level for both TEs and satellites; however, neither sequence content nor expression fully explain which repeat families form R-loops, suggesting other factors are at play. Finally, by analyzing population frequencies of R-loop-forming TEs, we present evidence that TE copies with high R-loop signal may be under stronger negative selection, which suggests that R-loop formation by TEs may be deleterious to their host. Collectively, these results provide insight into the determinants of R-loop formation at repetitive elements.

deepTAD: an approach for identifying topologically associated domains based on convolutional neural network and transformer model

MOTIVATION

Topologically associated domains (TADs) play a key role in the 3D organization and function of genomes, and accurate detection of TADs is essential for revealing the relationship between genomic structure and function. Most current methods are developed to extract features in Hi-C interaction matrix to identify TADs. However, due to complexities in Hi-C contact matrices, it is difficult to directly extract features associated with TADs, which prevents current methods from identifying accurate TADs.

RESULTS

In this paper, a novel method is proposed, deepTAD, which is developed based on a convolutional neural network (CNN) and transformer model. First, based on Hi-C contact matrix, deepTAD utilizes CNN to directly extract features associated with TAD boundaries. Next, deepTAD takes advantage of the transformer model to analyze the variation features around TAD boundaries and determines the TAD boundaries. Second, deepTAD uses the Wilcoxon rank-sum test to further identify false-positive boundaries. Finally, deepTAD computes cosine similarity among identified TAD boundaries and assembles TAD boundaries to obtain hierarchical TADs. The experimental results show that TAD boundaries identified by deepTAD have a significant enrichment of biological features, including structural proteins, histone modifications, and transcription start site loci. Additionally, when evaluating the completeness and accuracy of identified TADs, deepTAD has a good performance compared with other methods. The source code of deepTAD is available at https://github.com/xiaoyan-wang99/deepTAD.

3D genome landscape of primary and metastatic colorectal carcinoma reveals the regulatory mechanism of tumorigenic and metastatic gene expression

Colorectal carcinoma (CRC) is a deadly cancer with an aggressive nature, and how CRC tumor cells manage to translocate and proliferate in a new tissue environment remains not fully understood. Recently, higher-order chromatin structures and spatial genome organization are increasingly implicated in diseases including cancer, but in-depth studies of three-dimensional genome (3D genome) of metastatic cancer are currently lacking, preventing the understanding of the roles of genome organization during metastasis. Here we perform multi-omics profiling of matched normal colon, primary tumor, lymph node metastasis, liver metastasis and normal liver tissue from CRC patients using Hi-C, ATAC-seq and RNA-seq technologies. We find that widespread alteration of 3D chromatin structure is accompanied by dysregulation of genes including SPP1 during the tumorigenesis or metastasis of CRC. Remarkably, the hierarchy of topological associating domain (TAD) changes dynamically, which challenges the traditional view that the TAD structure between tumor and normal tissue is conservative. In addition, we define compartment stability score to measure large-scale alteration in metastatic tumors. To integrate multi-omics data and recognize candidate genes driving cancer metastasis, a pipeline is developed based on Hi-C, RNA-seq and ATAC-seq data. And three candidate genes ARL4C, FLNA, and RGCC are validated to be associated with CRC cell migration and invasion using in vitro knockout experiments. Overall, these data resources and results offer new insights into the involvement of 3D genome in cancer metastasis.

Multi-omics analysis in primary T cells elucidates mechanisms behind disease-associated genetic loci

BACKGROUND

Genome-wide association studies (GWAS) have uncovered the genetic basis behind many diseases and conditions. However, most of these genetic loci affect regulatory regions, making the interpretation challenging. Chromatin conformation has a fundamental role in gene regulation and is frequently used to associate potential target genes to regulatory regions. However, previous studies mostly used small sample sizes and immortalized cell lines instead of primary cells.

RESULTS

Here we present the most extensive dataset of chromatin conformation with matching gene expression and chromatin accessibility from primary CD4+ and CD8+ T cells to date, isolated from psoriatic arthritis patients and healthy controls. We generated 108 Hi-C libraries (49 billion reads), 128 RNA-seq libraries and 126 ATAC-seq libraries. These data enhance our understanding of the mechanisms by which GWAS variants impact gene regulation, revealing how genetic variation alters chromatin accessibility and structure in primary cells at an unprecedented scale. We refine the mapping of GWAS loci to implicated regulatory elements, such as CTCF binding sites and other enhancer elements, aiding gene assignment. We uncover BCL2L11 as the probable causal gene within the rheumatoid arthritis (RA) locus rs13396472, despite the GWAS variants' intronic positioning relative to ACOXL, and we identify mechanisms involving SESN3 dysregulation in the RA locus rs4409785.

CONCLUSIONS

Given these genes' significant role in T cell development and maturation, our work deepens our comprehension of autoimmune disease pathogenesis, suggesting potential treatment targets. In addition, our dataset provides a valuable resource for the investigation of immune-mediated diseases and gene regulatory mechanisms.

Uncovering topologically associating domains from three-dimensional genome maps with TADGATE

Topologically associating domains (TADs) are essential components of three-dimensional (3D) genome organization and significantly influence gene transcription regulation. However, accurately identifying TADs from sparse chromatin contact maps and exploring the structural and functional elements within TADs remain challenging. To this end, we develop TADGATE, a graph attention auto-encoder that can generate imputed maps from sparse Hi-C contact maps while adaptively preserving or enhancing the underlying topological structures, thereby facilitating TAD identification. TADGATE captures specific attention patterns with two types of units within TADs and demonstrates TAD organization relates to chromatin compartmentalization with diverse biological properties. We identify many structural and functional elements within TADs, with their abundance reflecting the overall properties of these domains. We applied TADGATE to sparse and noisy Hi-C contact maps from 21 human tissues or cell lines. That improved the clarity of TAD structures, allowing us to investigate conserved and cell-type-specific boundaries and uncover cell-type-specific transcriptional regulatory mechanisms associated with topological domains. We also demonstrated TADGATE's capability to fill in sparse single-cell Hi-C contact maps and identify TAD-like domains within them, revealing the specific domain boundaries with distinct heterogeneity and the shared backbone boundaries characterized by strong CTCF enrichment and high gene expression levels.

Hi-GDT: A Hi-C-based 3D gene domain analysis tool for analyzing local chromatin contacts in plants

BACKGROUND

Three-dimensional (3D) chromatin organization is emerging as a key factor in gene regulation in eukaryotes. Recent studies using high-resolution Hi-C analysis have explored fine-scale local chromatin contact domains in plants, as exemplified by the basic contact domains established at accessible gene border regions in Arabidopsis (Arabidopsis thaliana). However, we lack effective tools to identify these contact domains and examine their structural dynamics.

RESULTS

We developed the Hi-C-based 3D Gene Domain analysis Tool (Hi-GDT) to identify fine-scale local chromatin contact domains in plants, with a particular focus on gene borders. Hi-GDT successfully identifies local contact domains, including single-gene and multigene domains, with high reproducibility. Hi-GDT can also be used to discover local contact domains that are differentially organized in association with differences in gene expression between tissue types, genotypes, or in response to environmental stimuli.

CONCLUSIONS

Hi-GDT is a valuable tool for identifying genes regulated by dynamic 3D conformational changes, expanding our understanding of the structural and functional relevance of local 3D chromatin organization in plants. Hi-GDT is publicly available at https://github.com/CDL-HongwooLee/Hi-GDT.

Role of the Egr2 Promoter Antisense RNA in Modulating the Schwann Cell Chromatin Landscape

Background: Schwann cells (SCs) and their plasticity contribute to the peripheral nervous system's capacity for nerve regeneration after injury. The Egr2/Krox20 promoter antisense RNA (Egr2-AS) recruits chromatin remodeling complexes to inhibit Egr2 transcription following peripheral nerve injury. Methods: RNA-seq and ATAC-seq were performed on control cells, Lenti-GFP-transduced cells, and cells overexpressing Egr2-AS (Lenti-AS). Egr2 AS-RNA was cloned into the pLVX-DsRed-Express2-N1 lentiviral expression vector (Clontech, Mountain View, CA, USA), and the levels of AS-RNA expression were determined. Ezh2 and Wdr5 were immunoprecipitated from rat SCs and RT-qPCR was performed against AS-Egr2 RNA. ChIP followed by DNA purification columns was used to perform qPCR for relevant promoters. Hi-C, HiC-DC+, R, Bioconductor, and TOBIAS were used for significant and differential loop analysis, identifications of COREs and CORE-promotor loops, comparisons of TF activity at promoter sites, and identification of site-specific TF footprints. OnTAD was used to detect TADs, and Juicer was used to identify A/B compartments. Results: Here we show that a Neuregulin-ErbB2/3 signaling axis mediates binding of the Egr2-AS to YY1Ser184 and regulates its expression. Egr2-AS modulates the chromatin accessibility of Schwann cells and interacts with two distinct histone modification complexes. It binds to EZH2 and WDR5 and enables targeting of H3K27me3 and H3K4me3 to promoters of Egr2 and C-JUN, respectively. Expression of the Egr2-AS results in reorganization of the global chromatin landscape and quantitative changes in the loop formation and contact frequency at domain boundaries exhibiting enrichment for AP-1 genes. In addition, the Egr2-AS induces changes in the hierarchical TADs and increases transcription factor binding scores on an inter-TAD loop between a super-enhancer regulatory hub and the promoter of mTOR. Conclusions: Our results show that Neuregulin-ErbB2/3-YY1 regulates the expression of Egr2-AS, which mediates remodeling of the chromatin landscape in Schwann cells.

TAD hierarchy restricts poised LTR activation and loss of TAD hierarchy promotes LTR co-option in cancer

Transposable elements (TEs) are abundant in the human genome, and they provide the sources for genetic and functional diversity. The regulation of TEs expression and their functional consequences in physiological conditions and cancer development remain to be fully elucidated. Previous studies suggested TEs are repressed by DNA methylation and chromatin modifications. The effect of 3D chromatin topology on TE regulation remains elusive. Here, by integrating transcriptome and 3D genome architecture studies, we showed that haploinsufficient loss of NIPBL selectively activates alternative promoters at the long terminal repeats (LTRs) of the TE subclasses. This activation occurs through the reorganization of topologically associating domain (TAD) hierarchical structures and recruitment of proximal enhancers. These observations indicate that TAD hierarchy restricts transcriptional activation of LTRs that already possess open chromatin features. In cancer, perturbation of the hierarchical chromatin topology can lead to co-option of LTRs as functional alternative promoters in a context-dependent manner and drive aberrant transcriptional activation of novel oncogenes and other divergent transcripts. These data uncovered a new layer of regulatory mechanism of TE expression beyond DNA and chromatin modification in human genome. They also posit the TAD hierarchy dysregulation as a novel mechanism for alternative promoter-mediated oncogene activation and transcriptional diversity in cancer, which may be exploited therapeutically.

Stratifying TAD boundaries pinpoints focal genomic regions of regulation, damage, and repair

Advances in chromatin mapping have exposed the complex chromatin hierarchical organization in mammals, including topologically associating domains (TADs) and their substructures, yet the functional implications of this hierarchy in gene regulation and disease progression are not fully elucidated. Our study delves into the phenomenon of shared TAD boundaries, which are pivotal in maintaining the hierarchical chromatin structure and regulating gene activity. By integrating high-resolution Hi-C data, chromatin accessibility, and DNA double-strand breaks (DSBs) data from various cell lines, we systematically explore the complex regulatory landscape at high-level TAD boundaries. Our findings indicate that these boundaries are not only key architectural elements but also vibrant hubs, enriched with functionally crucial genes and complex transcription factor binding site-clustered regions. Moreover, they exhibit a pronounced enrichment of DSBs, suggesting a nuanced interplay between transcriptional regulation and genomic stability. Our research provides novel insights into the intricate relationship between the 3D genome structure, gene regulation, and DNA repair mechanisms, highlighting the role of shared TAD boundaries in maintaining genomic integrity and resilience against perturbations. The implications of our findings extend to understanding the complexities of genomic diseases and open new avenues for therapeutic interventions targeting the structural and functional integrity of TAD boundaries.

A comprehensive benchmarking with interpretation and operational guidance for the hierarchy of topologically associating domains

Topologically associating domains (TADs), megabase-scale features of chromatin spatial architecture, are organized in a domain-within-domain TAD hierarchy. Within TADs, the inner and smaller subTADs not only manifest cell-to-cell variability, but also precisely regulate transcription and differentiation. Although over 20 TAD callers are able to detect TAD, their usability in biomedicine is confined by a disagreement of outputs and a limit in understanding TAD hierarchy. We compare 13 computational tools across various conditions and develop a metric to evaluate the similarity of TAD hierarchy. Although outputs of TAD hierarchy at each level vary among callers, data resolutions, sequencing depths, and matrices normalization, they are more consistent when they have a higher similarity of larger TADs. We present comprehensive benchmarking of TAD hierarchy callers and operational guidance to researchers of life science researchers. Moreover, by simulating the mixing of different types of cells, we confirm that TAD hierarchy is generated not simply from stacking Hi-C heatmaps of heterogeneous cells. Finally, we propose an air conditioner model to decipher the role of TAD hierarchy in transcription.

Interspecies regulatory landscapes and elements revealed by novel joint systematic integration of human and mouse blood cell epigenomes

Knowledge of locations and activities of cis-regulatory elements (CREs) is needed to decipher basic mechanisms of gene regulation and to understand the impact of genetic variants on complex traits. Previous studies identified candidate CREs (cCREs) using epigenetic features in one species, making comparisons difficult between species. In contrast, we conducted an interspecies study defining epigenetic states and identifying cCREs in blood cell types to generate regulatory maps that are comparable between species, using integrative modeling of eight epigenetic features jointly in human and mouse in our Validated Systematic Integration (VISION) Project. The resulting catalogs of cCREs are useful resources for further studies of gene regulation in blood cells, indicated by high overlap with known functional elements and strong enrichment for human genetic variants associated with blood cell phenotypes. The contribution of each epigenetic state in cCREs to gene regulation, inferred from a multivariate regression, was used to estimate epigenetic state Regulatory Potential (esRP) scores for each cCRE in each cell type, which were used to categorize dynamic changes in cCREs. Groups of cCREs displaying similar patterns of regulatory activity in human and mouse cell types, obtained by joint clustering on esRP scores, harbored distinctive transcription factor binding motifs that were similar between species. An interspecies comparison of cCREs revealed both conserved and species-specific patterns of epigenetic evolution. Finally, we showed that comparisons of the epigenetic landscape between species can reveal elements with similar roles in regulation, even in the absence of genomic sequence alignment.

Identifying TAD-like domains on single-cell Hi-C data by graph embedding and changepoint detection

MOTIVATION

Topologically associating domains (TADs) are fundamental building blocks of 3D genome. TAD-like domains in single cells are regarded as the underlying genesis of TADs discovered in bulk cells. Understanding the organization of TAD-like domains helps to get deeper insights into their regulatory functions. Unfortunately, it remains a challenge to identify TAD-like domains on single-cell Hi-C data due to its ultra-sparsity.

RESULTS

We propose scKTLD, an in silico tool for the identification of TAD-like domains on single-cell Hi-C data. It takes Hi-C contact matrix as the adjacency matrix for a graph, embeds the graph structures into a low-dimensional space with the help of sparse matrix factorization followed by spectral propagation, and the TAD-like domains can be identified using a kernel-based changepoint detection in the embedding space. The results tell that our scKTLD is superior to the other methods on the sparse contact matrices, including downsampled bulk Hi-C data as well as simulated and experimental single-cell Hi-C data. Besides, we demonstrated the conservation of TAD-like domain boundaries at single-cell level apart from heterogeneity within and across cell types, and found that the boundaries with higher frequency across single cells are more enriched for architectural proteins and chromatin marks, and they preferentially occur at TAD boundaries in bulk cells, especially at those with higher hierarchical levels.

AVAILABILITY AND IMPLEMENTATION

scKTLD is freely available at https://github.com/lhqxinghun/scKTLD.

Multi-omic analysis of human kidney tissue identified medulla-specific gene expression patterns

The kidney medulla is a specialized region with important homeostatic functions. It has been implicated in genetic and developmental disorders along with ischemic and drug-induced injuries. Despite its role in kidney function and disease, the medulla's baseline gene expression and epigenomic signatures have not been well described in the adult human kidney. Here we generated and analyzed gene expression (RNA-seq), chromatin accessibility (ATAC-seq), chromatin conformation (Hi-C) and spatial transcriptomic data from the adult human kidney cortex and medulla. Tissue samples were obtained from macroscopically dissected cortex and medulla of tumor-adjacent normal material in nephrectomy specimens from five male patients. We used these carefully annotated specimens to reassign incorrectly labeled samples in the larger public Genotype-Tissue Expression (GTEx) Project, and to extract meaningful medullary gene expression signatures. Using integrated analysis of gene expression, chromatin accessibility and conformation profiles, we found insights into medulla development and function and then validated this by spatial transcriptomics and immunohistochemistry. Thus, our datasets provide a valuable resource for functional annotation of variants from genome-wide association studies and are freely accessible through an epigenome browser portal.

Integrative functional genomic analyses identify genetic variants influencing skin pigmentation in Africans

Skin color is highly variable in Africans, yet little is known about the underlying molecular mechanism. Here we applied massively parallel reporter assays to screen 1,157 candidate variants influencing skin pigmentation in Africans and identified 165 single-nucleotide polymorphisms showing differential regulatory activities between alleles. We combine Hi-C, genome editing and melanin assays to identify regulatory elements for MFSD12, HMG20B, OCA2, MITF, LEF1, TRPS1, BLOC1S6 and CYB561A3 that impact melanin levels in vitro and modulate human skin color. We found that independent mutations in an OCA2 enhancer contribute to the evolution of human skin color diversity and detect signals of local adaptation at enhancers of MITF, LEF1 and TRPS1, which may contribute to the light skin color of Khoesan-speaking populations from Southern Africa. Additionally, we identified CYB561A3 as a novel pigmentation regulator that impacts genes involved in oxidative phosphorylation and melanogenesis. These results provide insights into the mechanisms underlying human skin color diversity and adaptive evolution.

JMnorm: a novel joint multi-feature normalization method for integrative and comparative epigenomics

Combinatorial patterns of epigenetic features reflect transcriptional states and functions of genomic regions. While many epigenetic features have correlated relationships, most existing data normalization approaches analyze each feature independently. Such strategies may distort relationships between functionally correlated epigenetic features and hinder biological interpretation. We present a novel approach named JMnorm that simultaneously normalizes multiple epigenetic features across cell types, species, and experimental conditions by leveraging information from partially correlated epigenetic features. We demonstrate that JMnorm-normalized data can better preserve cross-epigenetic-feature correlations across different cell types and enhance consistency between biological replicates than data normalized by other methods. Additionally, we show that JMnorm-normalized data can consistently improve the performance of various downstream analyses, which include candidate cis-regulatory element clustering, cross-cell-type gene expression prediction, detection of transcription factor binding and changes upon perturbations. These findings suggest that JMnorm effectively minimizes technical noise while preserving true biologically significant relationships between epigenetic datasets. We anticipate that JMnorm will enhance integrative and comparative epigenomics.

The shape of chromatin: insights from computational recognition of geometric patterns in Hi-C data

The three-dimensional organization of chromatin plays a crucial role in gene regulation and cellular processes like deoxyribonucleic acid (DNA) transcription, replication and repair. Hi-C and related techniques provide detailed views of spatial proximities within the nucleus. However, data analysis is challenging partially due to a lack of well-defined, underpinning mathematical frameworks. Recently, recognizing and analyzing geometric patterns in Hi-C data has emerged as a powerful approach. This review provides a summary of algorithms for automatic recognition and analysis of geometric patterns in Hi-C data and their correspondence with chromatin structure. We classify existing algorithms on the basis of the data representation and pattern recognition paradigm they make use of. Finally, we outline some of the challenges ahead and promising future directions.

Revisiting Assessment of Computational Methods for Hi-C Data Analysis

The performances of algorithms for Hi-C data preprocessing, the identification of topologically associating domains, and the detection of chromatin interactions and promoter-enhancer interactions have been mostly evaluated using semi-quantitative or synthetic data approaches, without utilizing the most recent methods, since 2017. In this study, we comprehensively evaluated 24 popular state-of-the-art methods for the complete end-to-end pipeline of Hi-C data analysis, using manually curated or experimentally validated benchmark datasets, including a CRISPR dataset for promoter-enhancer interaction validation. Our results indicate that, although no single method exhibited superior performance in all situations, HiC-Pro, DomainCaller, and Fit-Hi-C2 showed relatively balanced performances of most evaluation metrics for preprocessing, topologically associating domain identification, and chromatin interaction/promoter-enhancer interaction detection, respectively. The comprehensive comparison presented in this manuscript provides a reference for researchers to choose Hi-C analysis tools that best suit their needs.

DeDoc2 Identifies and Characterizes the Hierarchy and Dynamics of Chromatin TAD-Like Domains in the Single Cells

Topologically associating domains (TADs) are functional chromatin units with hierarchical structure. However, the existence, prevalence, and dynamics of such hierarchy in single cells remain unexplored. Here, a new generation TAD-like domain (TLD) detection algorithm, named deDoc2, to decode the hierarchy of TLDs in single cells, is reported. With dynamic programming, deDoc2 seeks genome partitions with global minimal structure entropy for both whole and local contact matrix. Notably, deDoc2 outperforms state-of-the-art tools and is one of only two tools able to identify the hierarchy of TLDs in single cells. By applying deDoc2, it is showed that the hierarchy of TLDs in single cells is highly dynamic during cell cycle, as well as among human brain cortex cells, and that it is associated with cellular identity and functions. Thus, the results demonstrate the abundance of information potentially encoded by TLD hierarchy for functional regulation. The deDoc2 can be freely accessed at https://github.com/zengguangjie/deDoc2.

Chromatin alternates between A and B compartments at kilobase scale for subgenic organization

Nuclear compartments are prominent features of 3D chromatin organization, but sequencing depth limitations have impeded investigation at ultra fine-scale. CTCF loops are generally studied at a finer scale, but the impact of looping on proximal interactions remains enigmatic. Here, we critically examine nuclear compartments and CTCF loop-proximal interactions using a combination of in situ Hi-C at unparalleled depth, algorithm development, and biophysical modeling. Producing a large Hi-C map with 33 billion contacts in conjunction with an algorithm for performing principal component analysis on sparse, super massive matrices (POSSUMM), we resolve compartments to 500 bp. Our results demonstrate that essentially all active promoters and distal enhancers localize in the A compartment, even when flanking sequences do not. Furthermore, we find that the TSS and TTS of paused genes are often segregated into separate compartments. We then identify diffuse interactions that radiate from CTCF loop anchors, which correlate with strong enhancer-promoter interactions and proximal transcription. We also find that these diffuse interactions depend on CTCF's RNA binding domains. In this work, we demonstrate features of fine-scale chromatin organization consistent with a revised model in which compartments are more precise than commonly thought while CTCF loops are more protracted.

DRAVA: Aligning Human Concepts with Machine Learning Latent Dimensions for the Visual Exploration of Small Multiples

Latent vectors extracted by machine learning (ML) are widely used in data exploration (e.g., t-SNE) but suffer from a lack of interpretability. While previous studies employed disentangled representation learning (DRL) to enable more interpretable exploration, they often overlooked the potential mismatches between the concepts of humans and the semantic dimensions learned by DRL. To address this issue, we propose Drava, a visual analytics system that supports users in 1) relating the concepts of humans with the semantic dimensions of DRL and identifying mismatches, 2) providing feedback to minimize the mismatches, and 3) obtaining data insights from concept-driven exploration. Drava provides a set of visualizations and interactions based on visual piles to help users understand and refine concepts and conduct concept-driven exploration. Meanwhile, Drava employs a concept adaptor model to fine-tune the semantic dimensions of DRL based on user refinement. The usefulness of Drava is demonstrated through application scenarios and experimental validation.

Widespread allele-specific topological domains in the human genome are not confined to imprinted gene clusters

BACKGROUND

There is widespread interest in the three-dimensional chromatin conformation of the genome and its impact on gene expression. However, these studies frequently do not consider parent-of-origin differences, such as genomic imprinting, which result in monoallelic expression. In addition, genome-wide allele-specific chromatin conformation associations have not been extensively explored. There are few accessible bioinformatic workflows for investigating allelic conformation differences and these require pre-phased haplotypes which are not widely available.

RESULTS

We developed a bioinformatic pipeline, "HiCFlow," that performs haplotype assembly and visualization of parental chromatin architecture. We benchmarked the pipeline using prototype haplotype phased Hi-C data from GM12878 cells at three disease-associated imprinted gene clusters. Using Region Capture Hi-C and Hi-C data from human cell lines (1-7HB2, IMR-90, and H1-hESCs), we can robustly identify the known stable allele-specific interactions at the IGF2-H19 locus. Other imprinted loci (DLK1 and SNRPN) are more variable and there is no "canonical imprinted 3D structure," but we could detect allele-specific differences in A/B compartmentalization. Genome-wide, when topologically associating domains (TADs) are unbiasedly ranked according to their allele-specific contact frequencies, a set of allele-specific TADs could be defined. These occur in genomic regions of high sequence variation. In addition to imprinted genes, allele-specific TADs are also enriched for allele-specific expressed genes. We find loci that have not previously been identified as allele-specific expressed genes such as the bitter taste receptors (TAS2Rs).

CONCLUSIONS

This study highlights the widespread differences in chromatin conformation between heterozygous loci and provides a new framework for understanding allele-specific expressed genes.

Defining the separation landscape of topological domains for decoding consensus domain organization of the 3D genome

Topologically associating domains (TADs) have emerged as basic structural and functional units of genome organization and have been determined by many computational methods from Hi-C contact maps. However, the TADs obtained by different methods vary greatly, which makes the accurate determination of TADs a challenging issue and hinders subsequent biological analyses about their organization and functions. Obvious inconsistencies among the TADs identified by different methods indeed make the statistical and biological properties of TADs overly depend on the chosen method rather than on the data. To this end, we use the consensus structural information captured by these methods to define the TAD separation landscape for decoding the consensus domain organization of the 3D genome. We show that the TAD separation landscape could be used to compare domain boundaries across multiple cell types for discovering conserved and divergent topological structures, decipher three types of boundary regions with diverse biological features, and identify consensus TADs (ConsTADs). We illustrate that these analyses could deepen our understanding of the relationships between the topological domains and chromatin states, gene expression, and DNA replication timing.

Genomic profiling of HIV-1 integration in microglia cells links viral integration to the topologically associated domains

HIV-1 encounters the hierarchically organized host chromatin to stably integrate and persist in anatomically distinct latent reservoirs. The contribution of genome organization in HIV-1 infection has been largely understudied across different HIV-1 targets. Here, we determine HIV-1 integration sites (ISs), associate them with chromatin and expression signatures at different genomic scales in a microglia cell model, and profile them together with the primary T cell reservoir. HIV-1 insertions into introns of actively transcribed genes with IS hotspots in genic and super-enhancers, characteristic of blood cells, are maintained in the microglia cell model. Genome organization analysis reveals dynamic CCCTC-binding factor (CTCF) clusters in cells with active and repressed HIV-1 transcription, whereas CTCF removal impairs viral integration. We identify CTCF-enriched topologically associated domain (TAD) boundaries with signatures of transcriptionally active chromatin as HIV-1 integration determinants in microglia and CD4+ T cells, highlighting the importance of host genome organization in HIV-1 infection.

HSFA1a modulates plant heat stress responses and alters the 3D chromatin organization of enhancer-promoter interactions

The complex and dynamic three-dimensional organization of chromatin within the nucleus makes understanding the control of gene expression challenging, but also opens up possible ways to epigenetically modulate gene expression. Because plants are sessile, they evolved sophisticated ways to rapidly modulate gene expression in response to environmental stress, that are thought to be coordinated by changes in chromatin conformation to mediate specific cellular and physiological responses. However, to what extent and how stress induces dynamic changes in chromatin reorganization remains poorly understood. Here, we comprehensively investigated genome-wide chromatin changes associated with transcriptional reprogramming response to heat stress in tomato. Our data show that heat stress induces rapid changes in chromatin architecture, leading to the transient formation of promoter-enhancer contacts, likely driving the expression of heat-stress responsive genes. Furthermore, we demonstrate that chromatin spatial reorganization requires HSFA1a, a transcription factor (TF) essential for heat stress tolerance in tomato. In light of our findings, we propose that TFs play a key role in controlling dynamic transcriptional responses through 3D reconfiguration of promoter-enhancer contacts.

HPTAD: A computational method to identify topologically associating domains from HiChIP and PLAC-seq datasets

High-throughput chromatin conformation capture technologies, such as Hi-C and Micro-C, have enabled genome-wide view of chromatin spatial organization. Most recently, Hi-C-derived enrichment-based technologies, including HiChIP and PLAC-seq, offer attractive alternatives due to their high signal-to-noise ratio and low cost. While a series of computational tools have been developed for Hi-C data, methods tailored for HiChIP and PLAC-seq data are still under development. Here we present HPTAD, a computational method to identify topologically associating domains (TADs) from HiChIP and PLAC-seq data. We performed comprehensive benchmark analysis to demonstrate its superior performance over existing TAD callers designed for Hi-C data. HPTAD is freely available at https://github.com/yunliUNC/HPTAD.

A Comparison of Topologically Associating Domain Callers Based on Hi-C Data

Topologically associating domains (TADs) are local chromatin interaction domains, which have been shown to play an important role in gene expression regulation. TADs were originally discovered in the investigation of 3D genome organization based on High-throughput Chromosome Conformation Capture (Hi-C) data. Continuous considerable efforts have been dedicated to developing methods for detecting TADs from Hi-C data. Different computational methods for TADs identification vary in their assumptions and criteria in calling TADs. As a consequence, the TADs called by these methods differ in their similarities and biological features they are enriched in. In this work, we performed a systematic comparison of twenty-six TAD callers. We first compared the TADs and gaps between adjacent TADs across different methods, resolutions, and sequencing depths. We then assessed the quality of TADs and TAD boundaries according to three criteria: the decay of contact frequencies over the genomic distance, enrichment and depletion of regulatory elements around TAD boundaries, and reproducibility of TADs and TAD boundaries in replicate samples. Last, due to the lack of a gold standard of TADs, we also evaluated the performance of the methods on synthetic datasets. We discussed the key principles of TAD callers, and pinpointed current situation in the detection of TADs. We provide a concise, comprehensive, and systematic framework for evaluating the performance of TAD callers, and expect our work will provide useful guidance in choosing suitable approaches for the detection and evaluation of TADs.

Reference panel guided topological structure annotation of Hi-C data

Accurately annotating topological structures (e.g., loops and topologically associating domains) from Hi-C data is critical for understanding the role of 3D genome organization in gene regulation. This is a challenging task, especially at high resolution, in part due to the limited sequencing coverage of Hi-C data. Current approaches focus on the analysis of individual Hi-C data sets of interest, without taking advantage of the facts that (i) several hundred Hi-C contact maps are publicly available, and (ii) the vast majority of topological structures are conserved across multiple cell types. Here, we present RefHiC, an attention-based deep learning framework that uses a reference panel of Hi-C datasets to facilitate topological structure annotation from a given study sample. We compare RefHiC against tools that do not use reference samples and find that RefHiC outperforms other programs at both topological associating domain and loop annotation across different cell types, species, and sequencing depths.

Nucleome programming is required for the foundation of totipotency in mammalian germline development

Germ cells are unique in engendering totipotency, yet the mechanisms underlying this capacity remain elusive. Here, we perform comprehensive and in-depth nucleome analysis of mouse germ-cell development in vitro, encompassing pluripotent precursors, primordial germ cells (PGCs) before and after epigenetic reprogramming, and spermatogonia/spermatogonial stem cells (SSCs). Although epigenetic reprogramming, including genome-wide DNA de-methylation, creates broadly open chromatin with abundant enhancer-like signatures, the augmented chromatin insulation safeguards transcriptional fidelity. These insulatory constraints are then erased en masse for spermatogonial development. Notably, despite distinguishing epigenetic programming, including global DNA re-methylation, the PGCs-to-spermatogonia/SSCs development entails further euchromatization. This accompanies substantial erasure of lamina-associated domains, generating spermatogonia/SSCs with a minimal peripheral attachment of chromatin except for pericentromeres-an architecture conserved in primates. Accordingly, faulty nucleome maturation, including persistent insulation and improper euchromatization, leads to impaired spermatogenic potential. Given that PGCs after epigenetic reprogramming serve as oogenic progenitors as well, our findings elucidate a principle for the nucleome programming that creates gametogenic progenitors in both sexes, defining a basis for nuclear totipotency.

Multiple epigenetic factors co-localize with HMGN proteins in A-compartment chromatin

Background

Nucleosomal binding proteins, HMGN, is a family of chromatin architectural proteins that are expressed in all vertebrate nuclei. Although previous studies have discovered that HMGN proteins have important roles in gene regulation and chromatin accessibility, whether and how HMGN proteins affect higher order chromatin status remains unknown.

Results

We examined the roles that HMGN1 and HMGN2 proteins play in higher order chromatin structures in three different cell types. We interrogated data generated in situ, using several techniques, including Hi–C, Promoter Capture Hi–C, ChIP-seq, and ChIP–MS. Our results show that HMGN proteins occupy the A compartment in the 3D nucleus space. In particular, HMGN proteins occupy genomic regions involved in cell-type-specific long-range promoter–enhancer interactions. Interestingly, depletion of HMGN proteins in the three different cell types does not cause structural changes in higher order chromatin, i.e., in topologically associated domains (TADs) and in A/B compartment scores. Using ChIP-seq combined with mass spectrometry, we discovered protein partners that are directly associated with or neighbors of HMGNs on nucleosomes.

Conclusions

We determined how HMGN chromatin architectural proteins are positioned within a 3D nucleus space, including the identification of their binding partners in mononucleosomes. Our research indicates that HMGN proteins localize to active chromatin compartments but do not have major effects on 3D higher order chromatin structure and that their binding to chromatin is not dependent on specific protein partners.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13072-022-00457-4.

TADfit is a multivariate linear regression model for profiling hierarchical chromatin domains on replicate Hi-C data

Topologically associating domains (TADs) are fundamental building blocks of three dimensional genome, and organized into complex hierarchies. Identifying hierarchical TADs on Hi-C data helps to understand the relationship between genome architectures and gene regulation. Herein we propose TADfit, a multivariate linear regression model for profiling hierarchical chromatin domains, which tries to fit the interaction frequencies in Hi-C contact matrix with and without replicates using all-possible hierarchical TADs, and the significant ones can be determined by the regression coefficients obtained with the help of an online learning solver called Follow-The-Regularized-Leader (FTRL). Beyond the existing methods, TADfit has an ability to handle multiple contact matrix replicates and find partially overlapping TADs on them, which helps to find the comprehensive underlying TADs across replicates from different experiments. The comparative results tell that TADfit has better accuracy and reproducibility, and the hierarchical TADs called by it exhibit a reasonable biological relevance.

Sex-specific variation in R-loop formation in Drosophila melanogaster

R-loops are three-stranded nucleotide structures consisting of a DNA:RNA hybrid and a displaced ssDNA non-template strand. Previous work suggests that R-loop formation is primarily determined by the thermodynamics of DNA:RNA binding, which are governed by base composition (e.g., GC skew) and transcription-induced DNA superhelicity. However, R-loops have been described at genomic locations that lack these properties, suggesting that they may serve other context-specific roles. To better understand the genetic determinants of R-loop formation, we have characterized the Drosophila melanogaster R-loop landscape across strains and between sexes using DNA:RNA immunoprecipitation followed by high-throughput sequencing (DRIP-seq). We find that R-loops are associated with sequence motifs that are G-rich or exhibit G/C skew, as well as highly expressed genes, tRNAs, and small nuclear RNAs, consistent with a role for DNA sequence and torsion in R-loop specification. However, we also find motifs associated with R-loops that are A/T-rich and lack G/C skew as well as a subset of R-loops that are enriched in polycomb-repressed chromatin. Differential enrichment analysis reveals a small number of sex-biased R-loops: while non-differentially enriched and male-enriched R-loops form at similar genetic features and chromatin states and contain similar sequence motifs, female-enriched R-loops form at unique genetic features, chromatin states, and sequence motifs and are associated with genes that show ovary-biased expression. Male-enriched R-loops are most abundant on the dosage-compensated X chromosome, where R-loops appear stronger compared to autosomal R-loops. R-loop-containing genes on the X chromosome are dosage-compensated yet show lower MOF binding and reduced H4K16ac compared to R-loop-absent genes, suggesting that H4K16ac or MOF may attenuate R-loop formation. Collectively, these results suggest that R-loop formation in vivo is not fully explained by DNA sequence and topology and raise the possibility that a distinct subset of these hybrid structures plays an important role in the establishment and maintenance of epigenetic differences between sexes.

Sister chromatid-sensitive Hi-C to map the conformation of replicated genomes

Chromosome conformation capture (Hi-C) techniques map the 3D organization of entire genomes. How sister chromatids fold in replicated chromosomes, however, cannot be determined with conventional Hi-C because of the identical DNA sequences of sister chromatids. Here, we present a protocol for sister chromatid-sensitive Hi-C (scsHi-C) that enables the distinction of DNA contacts within individual sister chromatids (cis sister contacts) from those between sister chromatids (trans sister contacts), thereby allowing investigation of the organization of replicated genomes. scsHi-C is based on live-cell labeling of nascent DNA by the synthetic nucleoside 4-thio-thymidine (4sT), which incorporates into a distinct DNA strand on each sister chromatid because of semi-conservative DNA replication. After purification of genomic DNA and in situ Hi-C library preparation, 4sT is chemically converted into 5-methyl-cytosine in the presence of OsO4/NH4Cl to introduce T-to-C signature point mutations on 4sT-labeled DNA. The Hi-C library is then sequenced, and ligated fragments are assigned to sister chromatids on the basis of strand orientation and the presence of signature mutations. The ensemble of scsHi-C contacts thereby represents genome-wide contact probabilities within and across sister chromatids. scsHi-C can be completed in 2 weeks, has been successfully applied in HeLa cells and can potentially be established for any cell type that allows proper cell cycle synchronization and incorporation of sufficient amounts of 4sT. The genome-wide maps of replicated chromosomes detected by scsHi-C enable investigation of the molecular mechanisms shaping sister chromatid topologies and the relevance of sister chromatid conformation in crucial processes like DNA repair, mitotic chromosome formation and potentially other biological processes.

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.

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.

FISH Going Meso-Scale: A Microscopic Search for Chromatin Domains

The intimate relationships between genome structure and function direct efforts toward deciphering three-dimensional chromatin organization within the interphase nuclei at different genomic length scales. For decades, major insights into chromatin structure at the level of large-scale euchromatin and heterochromatin compartments, chromosome territories, and subchromosomal regions resulted from the evolution of light microscopy and fluorescence in situ hybridization. Studies of nanoscale nucleosomal chromatin organization benefited from a variety of electron microscopy techniques. Recent breakthroughs in the investigation of mesoscale chromatin structures have emerged from chromatin conformation capture methods (C-methods). Chromatin has been found to form hierarchical domains with high frequency of local interactions from loop domains to topologically associating domains and compartments. During the last decade, advances in super-resolution light microscopy made these levels of chromatin folding amenable for microscopic examination. Here we are reviewing recent developments in FISH-based approaches for detection, quantitative measurements, and validation of contact chromatin domains deduced from C-based data. We specifically focus on the design and application of Oligopaint probes, which marked the latest progress in the imaging of chromatin domains. Vivid examples of chromatin domain FISH-visualization by means of conventional, super-resolution light and electron microscopy in different model organisms are provided.

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.

Systematic inference and comparison of multi-scale chromatin sub-compartments connects spatial organization to cell phenotypes

Chromatin compartmentalization reflects biological activity. However, inference of chromatin sub-compartments and compartment domains from chromosome conformation capture (Hi-C) experiments is limited by data resolution. As a result, these have been characterized only in a few cell types and systematic comparisons across multiple tissues and conditions are missing. Here, we present Calder, an algorithmic approach that enables the identification of multi-scale sub-compartments at variable data resolution. Calder allows to infer and compare chromatin sub-compartments and compartment domains in >100 cell lines. Our results reveal sub-compartments enriched for poised chromatin states and undergoing spatial repositioning during lineage differentiation and oncogenic transformation.

The hierarchical folding dynamics of topologically associating domains are closely related to transcriptional abnormalities in cancers

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The hierarchical levels of TAD boundaries were tissue- and cell type-specific.

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The TAD nesting level of genes in tumors is different from that in normal tissue.

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Hierarchical TAD level of genes is related to abnormal transcription and prognosis in cancers.

Recent studies have shown that the three-dimensional (3D) structure of chromatin is associated with cancer progression. However, the roles of the 3D genome structure and its dynamics in cancer remains largely unknown. In this study, we investigated hierarchical topologically associating domain (TAD) structures in cancers and defined a “TAD hierarchical score (TH score)” for genes, which allowed us to assess the TAD nesting level of all genes in a simplified way. We demonstrated that the TAD nesting levels of genes in a tumor differ from those in normal tissue. Furthermore, the hierarchical TAD level dynamics were related to transcriptional changes in cancer, and some of the genes in which the hierarchical level was altered were significantly related to the prognosis of cancer patients. Overall, the results of this study suggest that the folding dynamics of TADs are closely related to transcriptional abnormalities in cancers, emphasizing that the function of hierarchical chromatin organization goes beyond simple chromatin packaging efficiency.

Topologically associating domain boundaries that are stable across diverse cell types are evolutionarily constrained and enriched for heritability

Topologically associating domains (TADs) are fundamental units of three-dimensional (3D) nuclear organization. The regions bordering TADs-TAD boundaries-contribute to the regulation of gene expression by restricting interactions of cis-regulatory sequences to their target genes. TAD and TAD-boundary disruption have been implicated in rare-disease pathogenesis; however, we have a limited framework for integrating TADs and their variation across cell types into the interpretation of common-trait-associated variants. Here, we investigate an attribute of 3D genome architecture-the stability of TAD boundaries across cell types-and demonstrate its relevance to understanding how genetic variation in TADs contributes to complex disease. By synthesizing TAD maps across 37 diverse cell types with 41 genome-wide association studies (GWASs), we investigate the differences in disease association and evolutionary pressure on variation in TADs versus TAD boundaries. We demonstrate that genetic variation in TAD boundaries contributes more to complex-trait heritability, especially for immunologic, hematologic, and metabolic traits. We also show that TAD boundaries are more evolutionarily constrained than TADs. Next, stratifying boundaries by their stability across cell types, we find substantial variation. Compared to boundaries unique to a specific cell type, boundaries stable across cell types are further enriched for complex-trait heritability, evolutionary constraint, CTCF binding, and housekeeping genes. Thus, considering TAD boundary stability across cell types provides valuable context for understanding the genome's functional landscape and enabling variant interpretation that takes 3D structure into account.

SuperTAD: robust detection of hierarchical topologically associated domains with optimized structural information

Topologically associating domains (TADs) are the organizational units of chromosome structures. TADs can contain TADs, thus forming a hierarchy. TAD hierarchies can be inferred from Hi-C data through coding trees. However, the current method for computing coding trees is not optimal. In this paper, we propose optimal algorithms for this computation. In comparison with seven state-of-art methods using two public datasets, from GM12878 and IMR90 cells, SuperTAD shows a significant enrichment of structural proteins around detected boundaries and histone modifications within TADs and displays a high consistency between various resolutions of identical Hi-C matrices.

H1 histones control the epigenetic landscape by local chromatin compaction

H1 linker histones are the most abundant chromatin-binding proteins1. In vitro studies indicate that their association with chromatin determines nucleosome spacing and enables arrays of nucleosomes to fold into more compact chromatin structures. However, the in vivo roles of H1 are poorly understood2. Here we show that the local density of H1 controls the balance of repressive and active chromatin domains by promoting genomic compaction. We generated a conditional triple-H1-knockout mouse strain and depleted H1 in haematopoietic cells. H1 depletion in T cells leads to de-repression of T cell activation genes, a process that mimics normal T cell activation. Comparison of chromatin structure in normal and H1-depleted CD8+ T cells reveals that H1-mediated chromatin compaction occurs primarily in regions of the genome containing higher than average levels of H1: the chromosome conformation capture (Hi-C) B compartment and regions of the Hi-C A compartment marked by PRC2. Reduction of H1 stoichiometry leads to decreased H3K27 methylation, increased H3K36 methylation, B-to-A-compartment shifting and an increase in interaction frequency between compartments. In vitro, H1 promotes PRC2-mediated H3K27 methylation and inhibits NSD2-mediated H3K36 methylation. Mechanistically, H1 mediates these opposite effects by promoting physical compaction of the chromatin substrate. Our results establish H1 as a critical regulator of gene silencing through localized control of chromatin compaction, 3D genome organization and the epigenetic landscape.

Conformation of sister chromatids in the replicated human genome

The three-dimensional organization of the genome supports regulated gene expression, recombination, DNA repair, and chromosome segregation during mitosis. Chromosome conformation capture (Hi-C)1,2 analysis has revealed a complex genomic landscape of internal chromosomal structures in vertebrate cells3-7, but the identical sequence of sister chromatids has made it difficult to determine how they topologically interact in replicated chromosomes. Here we describe sister-chromatid-sensitive Hi-C (scsHi-C), which is based on labelling of nascent DNA with 4-thio-thymidine and nucleoside conversion chemistry. Genome-wide conformation maps of human chromosomes reveal that sister-chromatid pairs interact most frequently at the boundaries of topologically associating domains (TADs). Continuous loading of a dynamic cohesin pool separates sister-chromatid pairs inside TADs and is required to focus sister-chromatid contacts at TAD boundaries. We identified a subset of TADs that are overall highly paired and are characterized by facultative heterochromatin and insulated topological domains that form separately within individual sister chromatids. The rich pattern of sister-chromatid topologies and our scsHi-C technology will make it possible to investigate how physical interactions between identical DNA molecules contribute to DNA repair, gene expression, chromosome segregation, and potentially other biological processes.

Spatial density of open chromatin: an effective metric for the functional characterization of topologically associated domains

Topologically associated domains (TADs) are spatial and functional units of metazoan chromatin structure. Interpretation of the interplay between regulatory factors and chromatin structure within TADs is crucial to understand the spatial and temporal regulation of gene expression. However, a computational metric for the sensitive characterization of TAD regulatory landscape is lacking. Here, we present the spatial density of open chromatin (SDOC) metric as a quantitative measurement of intra-TAD chromatin state and structure. SDOC sensitively reflects epigenetic properties and gene transcriptional activity in TADs. During mouse T-cell development, we found that TADs with decreased SDOC are enriched in repressed developmental genes, and the joint effect of SDOC-decreasing and TAD clustering corresponds to the highest level of gene repression. In addition, we revealed a pervasive preference for TADs with similar SDOC to interact with each other, which may reflect the principle of chromatin organization.

SpectralTAD: an R package for defining a hierarchy of topologically associated domains using spectral clustering

BACKGROUND

The three-dimensional (3D) structure of the genome plays a crucial role in gene expression regulation. Chromatin conformation capture technologies (Hi-C) have revealed that the genome is organized in a hierarchy of topologically associated domains (TADs), sub-TADs, and chromatin loops. Identifying such hierarchical structures is a critical step in understanding genome regulation. Existing tools for TAD calling are frequently sensitive to biases in Hi-C data, depend on tunable parameters, and are computationally inefficient.

METHODS

To address these challenges, we developed a novel sliding window-based spectral clustering framework that uses gaps between consecutive eigenvectors for TAD boundary identification.

RESULTS

Our method, implemented in an R package, SpectralTAD, detects hierarchical, biologically relevant TADs, has automatic parameter selection, is robust to sequencing depth, resolution, and sparsity of Hi-C data. SpectralTAD outperforms four state-of-the-art TAD callers in simulated and experimental settings. We demonstrate that TAD boundaries shared among multiple levels of the TAD hierarchy were more enriched in classical boundary marks and more conserved across cell lines and tissues. In contrast, boundaries of TADs that cannot be split into sub-TADs showed less enrichment and conservation, suggesting their more dynamic role in genome regulation.

CONCLUSION

SpectralTAD is available on Bioconductor, http://bioconductor.org/packages/SpectralTAD/ .

TADBD: a sensitive and fast method for detection of typologically associated domain boundaries

A topologically associated domain (TAD) is a self-interacting genomic block. Detection of TAD boundaries on Hi-C contact matrix is one of the most important issues in the analysis of 3D genome architecture at TAD level. Here, we present TAD boundary detection (TADBD), a sensitive and fast computational method for detection of TAD boundaries on Hi-C contact matrix. This method implements a Haar-based algorithm by considering Haar diagonal template, acceleration via a compact integrogram, multi-scale aggregation at template size and statistical filtering. In most cases, comparison results from simulated and experimental data show that TADBD outperforms the other five methods. In addition, a new R package for TADBD is freely available online.

An integrative view of the regulatory and transcriptional landscapes in mouse hematopoiesis

Thousands of epigenomic data sets have been generated in the past decade, but it is difficult for researchers to effectively use all the data relevant to their projects. Systematic integrative analysis can help meet this need, and the VISION project was established for validated systematic integration of epigenomic data in hematopoiesis. Here, we systematically integrated extensive data recording epigenetic features and transcriptomes from many sources, including individual laboratories and consortia, to produce a comprehensive view of the regulatory landscape of differentiating hematopoietic cell types in mouse. By using IDEAS as our integrative and discriminative epigenome annotation system, we identified and assigned epigenetic states simultaneously along chromosomes and across cell types, precisely and comprehensively. Combining nuclease accessibility and epigenetic states produced a set of more than 200,000 candidate cis-regulatory elements (cCREs) that efficiently capture enhancers and promoters. The transitions in epigenetic states of these cCREs across cell types provided insights into mechanisms of regulation, including decreases in numbers of active cCREs during differentiation of most lineages, transitions from poised to active or inactive states, and shifts in nuclease accessibility of CTCF-bound elements. Regression modeling of epigenetic states at cCREs and gene expression produced a versatile resource to improve selection of cCREs potentially regulating target genes. These resources are available from our VISION website to aid research in genomics and hematopoiesis.