Regulation of T helper cell differentiation by the interplay between histone modification and chromatin interaction.

The development and function of the immune system are controlled by temporospatial gene expression programs, which are regulated by cis-regulatory elements, chromatin structure, and trans-acting factors. In this study, we cataloged the dynamic histone modifications and chromatin interactions at regulatory regions during T helper (Th) cell differentiation. Our data revealed that the H3K4me1 landscape established by MLL4 in naive CD4+ T cells is critical for restructuring the regulatory interaction network and orchestrating gene expression during the early phase of Th differentiation. GATA3 plays a crucial role in further configuring H3K4me1 modification and the chromatin interaction network during Th2 differentiation. Furthermore, we demonstrated that HSS3-anchored chromatin loops function to restrict the activity of the Th2 locus control region (LCR), thus coordinating the expression of Th2 cytokines. Our results provide insights into the mechanisms of how the interplay between histone modifications, chromatin looping, and trans-acting factors contributes to the differentiation of Th cells.

Restraint of IFN-γ expression through a distal silencer CNS-28 for tissue homeostasis.

Interferon-γ (IFN-γ) is a key cytokine in response to viral or intracellular bacterial infection in mammals. While a number of enhancers are described to promote IFN-γ responses, to the best of our knowledge, no silencers for the Ifng gene have been identified. By examining H3K4me1 histone modification in naive CD4+ T cells within Ifng locus, we identified a silencer (CNS-28) that restrains Ifng expression. Mechanistically, CNS-28 maintains Ifng silence by diminishing enhancer-promoter interactions within Ifng locus in a GATA3-dependent but T-bet-independent manner. Functionally, CNS-28 restrains Ifng transcription in NK cells, CD4+ cells, and CD8+ T cells during both innate and adaptive immune responses. Moreover, CNS-28 deficiency resulted in repressed type 2 responses due to elevated IFN-γ expression, shifting Th1 and Th2 paradigm. Thus, CNS-28 activity ensures immune cell quiescence by cooperating with other regulatory cis elements within the Ifng gene locus to minimize autoimmunity.

Chromosome structure modeling tools and their evaluation in bacteria.

The three-dimensional (3D) structure of bacterial chromosomes is crucial for understanding chromosome function. With the growing availability of high-throughput chromosome conformation capture (3C/Hi-C) data, the 3D structure reconstruction algorithms have become powerful tools to study bacterial chromosome structure and function. It is highly desired to have a recommendation on the chromosome structure reconstruction tools to facilitate the prokaryotic 3D genomics. In this work, we review existing chromosome 3D structure reconstruction algorithms and classify them based on their underlying computational models into two categories: constraint-based modeling and thermodynamics-based modeling. We briefly compare these algorithms utilizing 3C/Hi-C datasets and fluorescence microscopy data obtained from Escherichia coli and Caulobacter crescentus, as well as simulated datasets. We discuss current challenges in the 3D reconstruction algorithms for bacterial chromosomes, primarily focusing on software usability. Finally, we briefly prospect future research directions for bacterial chromosome structure reconstruction algorithms.

Antigen exposure reshapes chromatin architecture in central memory CD8+ T cells and imprints enhanced recall capacity.

CD62L+ central memory CD8+ T (TCM) cells provide enhanced protection than naive cells; however, the underlying mechanism, especially the contribution of higher-order genomic organization, remains unclear. Systematic Hi-C analyses reveal that antigen-experienced CD8+ T cells undergo extensive rewiring of chromatin interactions (ChrInt), with TCM cells harboring specific interaction hubs compared with naive CD8+ T cells, as observed at cytotoxic effector genes such as Ifng and Tbx21. TCM cells also acquire de novo CTCF (CCCTC-binding factor) binding sites, which are not only strongly associated with TCM-specific hubs but also linked to increased activities of local gene promoters and enhancers. Specific ablation of CTCF in TCM cells impairs rapid induction of genes in cytotoxic program, energy supplies, transcription, and translation by recall stimulation. Therefore, acquisition of CTCF binding and ChrInt hubs by TCM cells serves as a chromatin architectural basis for their transcriptomic dynamics in primary response and for imprinting the code of "recall readiness" against secondary challenge.

iEnhance: a multi-scale spatial projection encoding network for enhancing chromatin interaction data resolution.

Although sequencing-based high-throughput chromatin interaction data are widely used to uncover genome-wide three-dimensional chromatin architecture, their sparseness and high signal-noise-ratio greatly restrict the precision of the obtained structural elements. To improve data quality, we here present iEnhance (chromatin interaction data resolution enhancement), a multi-scale spatial projection and encoding network, to predict high-resolution chromatin interaction matrices from low-resolution and noisy input data. Specifically, iEnhance projects the input data into matrix spaces to extract multi-scale global and local feature sets, then hierarchically fused these features by attention mechanism. After that, dense channel encoding and residual channel decoding are used to effectively infer robust chromatin interaction maps. iEnhance outperforms state-of-the-art Hi-C resolution enhancement tools in both visual and quantitative evaluation. Comprehensive analysis shows that unlike other tools, iEnhance can recover both short-range structural elements and long-range interaction patterns precisely. More importantly, iEnhance can be transferred to data enhancement of other tissues or cell lines of unknown resolution. Furthermore, iEnhance performs robustly in enhancement of diverse chromatin interaction data including those from single-cell Hi-C and Micro-C experiments.

Improving comparative analyses of Hi-C data via contrastive self-supervised learning.

Hi-C is a widely applied chromosome conformation capture (3C)-based technique, which has produced a large number of genomic contact maps with high sequencing depths for a wide range of cell types, enabling comprehensive analyses of the relationships between biological functionalities (e.g. gene regulation and expression) and the three-dimensional genome structure. Comparative analyses play significant roles in Hi-C data studies, which are designed to make comparisons between Hi-C contact maps, thus evaluating the consistency of replicate Hi-C experiments (i.e. reproducibility measurement) and detecting statistically differential interacting regions with biological significance (i.e. differential chromatin interaction detection). However, due to the complex and hierarchical nature of Hi-C contact maps, it remains challenging to conduct systematic and reliable comparative analyses of Hi-C data. Here, we proposed sslHiC, a contrastive self-supervised representation learning framework, for precisely modeling the multi-level features of chromosome conformation and automatically producing informative feature embeddings for genomic loci and their interactions to facilitate comparative analyses of Hi-C contact maps. Comprehensive computational experiments on both simulated and real datasets demonstrated that our method consistently outperformed the state-of-the-art baseline methods in providing reliable measurements of reproducibility and detecting differential interactions with biological meanings.

Target genes regulated by CLEC16A intronic region associated with common variable immunodeficiency.

BACKGROUND: CLEC16A intron 19 has been identified as a candidate locus for common variable immunodeficiency (CVID). OBJECTIVES: This study sought to elucidate the molecular mechanism by which variants at the CLEC16A intronic locus may contribute to the pathogenesis of CVID. METHODS: The investigators performed fine-mapping of the CLEC16A locus in a CVID cohort, then deleted the candidate functional SNP in T-cell lines by the CRISPR-Cas9 technique and conducted RNA-sequencing to identify target gene(s). The interactions between the CLEC16A locus and its target genes were identified using circular chromosome conformation capture. The transcription factor complexes mediating the chromatin interactions were determined by proteomic approach. The molecular pathways regulated by the CLEC16A locus were examined by RNA-sequencing and reverse phase protein array. RESULTS: This study showed that the CLEC16A locus is an enhancer regulating expression of multiple target genes including a distant gene ATF7IP2 through chromatin interactions. Distinct transcription factor complexes mediate the chromatin interactions in an allele-specific manner. Disruption of the CLEC16A locus affects the AKT signaling pathway, as well as the molecular response of CD4+ T cells to immune stimulation. CONCLUSIONS: Through multiomics and targeted experimental approaches, this study elucidated the underlying target genes and signaling pathways involved in the genetic association of CLEC16A with CVID, and highlighted plausible molecular targets for developing novel therapeutics.

Chromatin accessibility analysis and architectural profiling of human kidneys reveal key cell types and a regulator of diabetic kidney disease.

Diabetes is the leading cause of kidney disease that progresses to kidney failure. However, the key molecular and cellular pathways involved in diabetic kidney disease (DKD) pathogenesis are largely unknown. Here, we performed a comparative analysis of adult human kidneys by examining cell type-specific chromatin accessibility by single-nucleus ATAC-seq (snATAC-seq) and analyzing three-dimensional chromatin architecture via high-throughput chromosome conformation capture (Hi-C method) of paired samples. We mapped the cell type-specific and DKD-specific open chromatin landscape and found that genetic variants associated with kidney diseases were significantly enriched in the proximal tubule- (PT) and injured PT-specific open chromatin regions in samples from patients with DKD. BACH1 was identified as a core transcription factor of injured PT cells; its binding target genes were highly associated with fibrosis and inflammation, which were also key features of injured PT cells. Additionally, Hi-C analysis revealed global chromatin architectural changes in DKD, accompanied by changes in local open chromatin patterns. Combining the snATAC-seq and Hi-C data identified direct target genes of BACH1, and indicated that BACH1 binding regions showed increased chromatin contact frequency with promoters of their target genes in DKD. Thus, our multi-omics analysis revealed BACH1 target genes in injured PTs and highlighted the role of BACH1 as a novel regulator of tubular inflammation and fibrosis.

Identification of susceptibility loci for Takayasu arteritis through a large multi-ancestral genome-wide association study.

Takayasu arteritis is a rare inflammatory disease of large arteries. We performed a genetic study in Takayasu arteritis comprising 6,670 individuals (1,226 affected individuals) from five different populations. We discovered HLA risk factors and four non-HLA susceptibility loci in VPS8, SVEP1, CFL2, and chr13q21 and reinforced IL12B, PTK2B, and chr21q22 as robust susceptibility loci shared across ancestries. Functional analysis proposed plausible underlying disease mechanisms and pinpointed ETS2 as a potential causal gene for chr21q22 association. We also identified >60 candidate loci with suggestive association (p < 5 × 10-5) and devised a genetic risk score for Takayasu arteritis. Takayasu arteritis was compared to hundreds of other traits, revealing the closest genetic relatedness to inflammatory bowel disease. Epigenetic patterns within risk loci suggest roles for monocytes and B cells in Takayasu arteritis. This work enhances understanding of the genetic basis and pathophysiology of Takayasu arteritis and provides clues for potential new therapeutic targets.

Promoter-centred chromatin interactions associated with EVI1 expression in EVI1+3q- myeloid leukaemia cells.

EVI1 expression is associated with poor prognosis in myeloid leukaemia, which can result from Chr.3q alterations that juxtapose enhancers to induce EVI1 expression via long-range chromatin interactions. More often, however, EVI1 expression occurs unrelated to 3q alterations, and it remained unclear if, in these cases, EVI1 expression is similarly caused by aberrant enhancer activation. Here, we report that, in EVI1+3q- myeloid leukaemia cells, the EVI1 promoter interacts via long-range chromatin interactions with promoters of distally located, active genes, rather than with enhancer elements. Unlike in 3q+ cells, EVI1 expression and long-range interactions appear to not depend on CTCF/cohesin, though EVI1+3q- cells utilise an EVI1 promoter-proximal site to enhance its expression that is also involved in CTCF-mediated looping in 3q+ cells. Long-range interactions in 3q- cells connect EVI1 to promoters of multiple genes, whose transcription correlates with EVI1 in EVI1+3q- cell lines, suggesting a shared mechanism of transcriptional regulation. In line with this, CRISPR interference-induced silencing of two of these sites minimally, but consistently reduced EVI1 expression. Together, we provide novel evidence of features associated with EVI1 expression in 3q- leukaemia and consolidate the view that EVI1 in 3q- leukaemia is largely promoter-driven, potentially involving long-distance promoter clustering.

Integrative modeling of lncRNA-chromatin interaction maps reveals diverse mechanisms of nuclear retention.

BACKGROUND: Many long non-coding RNAs, known to be involved in transcriptional regulation, are enriched in the nucleus and interact with chromatin. However, their mechanisms of chromatin interaction and the served cellular functions are poorly understood. We sought to characterize the mechanisms of lncRNA nuclear retention by systematically mapping the sequence and chromatin features that distinguish lncRNA-interacting genomic segments. RESULTS: We found DNA 5-mer frequencies to be predictive of chromatin interactions for all lncRNAs, suggesting sequence-specificity as a global theme in the interactome. Sequence features representing protein-DNA and protein-RNA binding motifs revealed potential mechanisms for specific lncRNAs. Complementary to these global themes, transcription-related features and DNA-RNA triplex formation potential were noted to be highly predictive for two mutually exclusive sets of lncRNAs. DNA methylation was also noted to be a significant predictor, but only when combined with other epigenomic features. CONCLUSIONS: Taken together, our statistical findings suggest that a group of lncRNAs interacts with transcriptionally inactive chromatin through triplex formation, whereas another group interacts with transcriptionally active regions and is involved in DNA Damage Response (DDR) through formation of R-loops. Curiously, we observed a strong pattern of enrichment of 5-mers in four potentially interacting entities: lncRNA-bound DNA tiles, lncRNAs, miRNA seed sequences, and repeat elements. This finding points to a broad sequence-based network of interactions that may underlie regulation of fundamental cellular functions. Overall, this study reveals diverse sequence and chromatin features related to lncRNA-chromatin interactions, suggesting potential mechanisms of nuclear retention and regulatory function.

TADreg: a versatile regression framework for TAD identification, differential analysis and rearranged 3D genome prediction.

BACKGROUND/AIM: In higher eukaryotes, the three-dimensional (3D) organization of the genome is intimately related to numerous key biological functions including gene expression, DNA repair and DNA replication regulations. Alteration of 3D organization, in particular topologically associating domains (TADs), is detrimental to the organism and can give rise to a broad range of diseases such as cancers. METHODS: Here, we propose a versatile regression framework which not only identifies TADs in a fast and accurate manner, but also detects differential TAD borders across conditions for which few methods exist, and predicts 3D genome reorganization after chromosomal rearrangement. Moreover, the framework is biologically meaningful, has an intuitive interpretation and is easy to visualize. RESULT AND CONCLUSION: The novel regression ranks among top TAD callers. Moreover, it identifies new features of the genome we called TAD facilitators, and that are enriched with specific transcription factors. It also unveils the importance of cell-type specific transcription factors in establishing novel TAD borders during neuronal differentiation. Lastly, it compares favorably with the state-of-the-art method for predicting rearranged 3D genome.

CTCF-binding element regulates ESC differentiation via orchestrating long-range chromatin interaction between enhancers and HoxA.

Proper expression of Homeobox A cluster genes (HoxA) is essential for embryonic stem cell (ESC) differentiation and individual development. However, mechanisms controlling precise spatiotemporal expression of HoxA during early ESC differentiation remain poorly understood. Herein, we identified a functional CTCF-binding element (CBE+47) closest to the 3'-end of HoxA within the same topologically associated domain (TAD) in ESC. CRISPR-Cas9-mediated deletion of CBE+47 significantly upregulated HoxA expression and enhanced early ESC differentiation induced by retinoic acid (RA) relative to wild-type cells. Mechanistic analysis by chromosome conformation capture assay (Capture-C) revealed that CBE+47 deletion decreased interactions between adjacent enhancers, enabling formation of a relatively loose enhancer-enhancer interaction complex (EEIC), which overall increased interactions between that EEIC and central regions of HoxA chromatin. These findings indicate that CBE+47 organizes chromatin interactions between its adjacent enhancers and HoxA. Furthermore, deletion of those adjacent enhancers synergistically inhibited HoxA activation, suggesting that these enhancers serve as an EEIC required for RA-induced HoxA activation. Collectively, these results provide new insight into RA-induced HoxA expression during early ESC differentiation, also highlight precise regulatory roles of the CTCF-binding element in orchestrating high-order chromatin structure.

Identification of enhancers responsible for the coordinated expression of myosin heavy chain isoforms in skeletal muscle.

BACKGROUND: Skeletal muscles consist of fibers of differing contractility and metabolic properties, which are primarily determined by the content of myosin heavy chain (MYH) isoforms (MYH7, MYH2, MYH1, and MYH4). The regulation of Myh genes transcription depends on three-dimensional chromatin conformation interaction, but the mechanistic details remain to be determined. RESULTS: In this study, we characterized the interaction profiles of Myh genes using 4C-seq (circular chromosome conformation capture coupled to high-throughput sequencing). The interaction profile of Myh genes changed between fast quadriceps and slow soleus muscles. Combining chromatin immunoprecipitation-sequencing (ChIP-seq) and transposase accessible chromatin with high-throughput sequencing (ATAC-seq), we found that a 38 kb intergenic region interacting simultaneously with fast Myh genes promoters controlled the coordinated expression of fast Myh genes. We also identified four active enhancers of Myh7, and revealed that binding of MYOG and MYOD increased the activity of Myh7 enhancers. CONCLUSIONS: This study provides new insight into the chromatin interactions that regulate Myh genes expression.

Chromatin Interactions and Regulatory Elements in Cancer: From Bench to Bedside.

Chromatin interactions regulate gene expression by bringing distal regulatory elements, such as super-enhancers, to promoters in close spatial proximity. It has been recognized that in cancer, chromatin interactions can be dysregulated, leading to aberrant oncogene expression. Chromatin interactions may potentially serve as biomarkers, or be modulated via CRISPR therapy and small molecule inhibitors against transcription. However, these methods face challenges that must be resolved and raise questions for further research. Understanding chromatin interactions is essential for safety aspects of anticancer therapies, such as the mechanism of action of epigenetic regulators and transcription factors in cancer, and potential off-target effects arising from targeting super-enhancers and promoters. In this review article, we discuss how chromatin interactions and regulatory elements may become dysregulated in cancer, potential methods to target them for clinical therapy, and outline outstanding questions that require addressing before epigenetic therapies can translate to the clinic safely and effectively.

When 3D genome technology meets viral infection, including SARS-CoV-2.

Mammalian chromosomes undergo varying degrees of compression to form three-dimensional genome structures. These three-dimensional structures undergo dynamic and precise chromatin interactions to achieve precise spatial and temporal regulation of gene expression. Most eukaryotic DNA viruses can invade their genomes into the nucleus. However, it is still poorly understood how the viral genome is precisely positioned after entering the host cell nucleus to find the most suitable location and whether it can specifically interact with the host genome to hijack the host transcriptional factories or even integrate into the host genome to complete its transcription and replication rapidly. Chromosome conformation capture technology can reveal long-range chromatin interactions between different chromosomal sites in the nucleus, potentially providing a reference for viral DNA-host chromatin interactions. This review summarized the research progress on the three-dimensional interaction between virus and host genome and the impact of virus integration into the host genome on gene transcription regulation, aiming to provide new insights into chromatin interaction and viral gene transcription regulation, laying the foundation for the treatment of infectious diseases.

Multiple CTCF sites cooperate with each other to maintain a TAD for enhancer-promoter interaction in the ß-globin locus.

Insulators are cis-regulatory elements that block enhancer activity and prevent heterochromatin spreading. The binding of CCCTC-binding factor (CTCF) protein is essential for insulators to play the roles in a chromatin context. The ß-globin locus, consisting of multiple genes and enhancers, is flanked by two insulators 3'HS1 and HS5. However, it has been reported that the absence of these insulators did not affect the ß-globin transcription. To explain the unexpected finding, we have deleted a CTCF motif at 3'HS1 or HS5 in the human ß-globin locus and analyzed chromatin interactions around the locus. It was found that a topologically associating domain (TAD) containing the ß-globin locus is maintained by neighboring CTCF sites in the CTCF motif-deleted loci. The additional deletions of neighboring CTCF motifs disrupted the ß-globin TAD, resulting in decrease of the ß-globin transcription. Chromatin interactions of the ß-globin enhancers with gene promoter were weakened in the multiple CTCF motifs-deleted loci, even though the enhancers have still active chromatin features such as histone H3K27ac and histone H3 depletion. Genome-wide analysis using public CTCF ChIA-PET and ChIP-seq data showed that chromatin domains possessing multiple CTCF binding sites tend to contain super-enhancers like the ß-globin enhancers. Taken together, our results show that multiple CTCF sites surrounding the ß-globin locus cooperate with each other to maintain a TAD. The ß-globin TAD appears to provide a compact spatial environment that enables enhancers to interact with promoter.

Discover novel disease-associated genes based on regulatory networks of long-range chromatin interactions.

Identifying genes and non-coding genetic variants that are genetically associated with complex diseases and the underlying mechanisms is one of the most important questions in functional genomics. Due to the limited statistical power and the lack of mechanistic modeling, traditional genome-wide association studies (GWAS) is restricted to fully address this question. Based on multi-omics data integration, cell-type specific regulatory networks can be built to improve GWAS analysis. In this study, we developed a new computational infrastructure, APRIL, to incorporate 3D chromatin interactions into regulatory network construction, which can extend the networks to include long-range cis-regulatory links between non-coding GWAS SNPs and target genes. Combinatorial transcription factors that co-regulate groups of genes are also inferred to further expand the networks with trans-regulation. A suite of machine learning predictions and statistical tests are incorporated in APRIL to predict novel disease-associated genes based on the expanded regulatory networks. Important features of non-coding regulatory elements and genetic variants are prioritized in network-based predictions, providing systems-level insights on the mechanisms of transcriptional dysregulation associated with complex diseases.

Deciphering hierarchical organization of topologically associated domains through change-point testing.

BACKGROUND: The nucleus of eukaryotic cells spatially packages chromosomes into a hierarchical and distinct segregation that plays critical roles in maintaining transcription regulation. High-throughput methods of chromosome conformation capture, such as Hi-C, have revealed topologically associating domains (TADs) that are defined by biased chromatin interactions within them. RESULTS: We introduce a novel method, HiCKey, to decipher hierarchical TAD structures in Hi-C data and compare them across samples. We first derive a generalized likelihood-ratio (GLR) test for detecting change-points in an interaction matrix that follows a negative binomial distribution or general mixture distribution. We then employ several optimal search strategies to decipher hierarchical TADs with p values calculated by the GLR test. Large-scale validations of simulation data show that HiCKey has good precision in recalling known TADs and is robust against random collisions of chromatin interactions. By applying HiCKey to Hi-C data of seven human cell lines, we identified multiple layers of TAD organization among them, but the vast majority had no more than four layers. In particular, we found that TAD boundaries are significantly enriched in active chromosomal regions compared to repressed regions. CONCLUSIONS: HiCKey is optimized for processing large matrices constructed from high-resolution Hi-C experiments. The method and theoretical result of the GLR test provide a general framework for significance testing of similar experimental chromatin interaction data that may not fully follow negative binomial distributions but rather more general mixture distributions.

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

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