CHiCAGO: robust detection of DNA looping interactions in Capture Hi-C data

Detecting chromosomal interactions in Capture Hi-C data with CHiCAGO and companion tools

Capture Hi-C is widely used to obtain high-resolution profiles of chromosomal interactions involving, at least on one end, regions of interest such as gene promoters. Signal detection in Capture Hi-C data is challenging and cannot be adequately accomplished with tools developed for other chromosome conformation capture methods, including standard Hi-C. Capture Hi-C Analysis of Genomic Organization (CHiCAGO) is a computational pipeline developed specifically for Capture Hi-C analysis. It implements a statistical model accounting for biological and technical background components, as well as bespoke normalization and multiple testing procedures for this data type. Here we provide a step-by-step guide to the CHiCAGO workflow that is aimed at users with basic experience of the command line and R. We also describe more advanced strategies for tuning the key parameters for custom experiments and provide guidance on data preprocessing and downstream analysis using companion tools. In a typical experiment, CHiCAGO takes ~2-3 h to run, although pre- and postprocessing steps may take much longer.

Seeing the forest through the trees: prioritising potentially functional interactions from Hi-C

Eukaryotic genomes are highly organised within the nucleus of a cell, allowing widely dispersed regulatory elements such as enhancers to interact with gene promoters through physical contacts in three-dimensional space. Recent chromosome conformation capture methodologies such as Hi-C have enabled the analysis of interacting regions of the genome providing a valuable insight into the three-dimensional organisation of the chromatin in the nucleus, including chromosome compartmentalisation and gene expression. Complicating the analysis of Hi-C data, however, is the massive amount of identified interactions, many of which do not directly drive gene function, thus hindering the identification of potentially biologically functional 3D interactions. In this review, we collate and examine the downstream analysis of Hi-C data with particular focus on methods that prioritise potentially functional interactions. We classify three groups of approaches: structural-based discovery methods, e.g. A/B compartments and topologically associated domains, detection of statistically significant chromatin interactions, and the use of epigenomic data integration to narrow down useful interaction information. Careful use of these three approaches is crucial to successfully identifying potentially functional interactions within the genome.

Restriction enzyme selection dictates detection range sensitivity in chromatin conformation capture-based variant-to-gene mapping approaches

Promoter-focused chromatin conformation techniques directly detect interactions between gene promoters and distal genomic sequences, providing structural information relevant to gene regulation without the excessive non-genic architectural data generated by full-scale Hi-C. 3D promoter 'interactome' maps are crucial for understanding how epigenomic features such as histone modifications and open chromatin, or genetic variants identified in genome-wide association studies (GWAS), contribute to biological function. However, variation in sensitivity between such promoter-focused methods, principally due to restriction enzyme selection, has not been systematically assessed. Here, we performed a head-to-head comparison of promoter capture datasets using 4 cutters (DpnII or MboI) versus the 6 cutter HindIII from the same five cell types. While HindIII generally produces a higher signal-to-noise ratio for significant interactions in comparison to 4-cutters, we show that DpnII/MboI detects more proximal interactions and shows little overlap with the HindIII detection range. Promoter-interacting genomic regions mapped by 4-cutters are more enriched for regulatory features and disease-associated genetic variation than 6-cutters maps, suggesting that high-resolution maps better capture gene regulatory architectures than do lower resolution approaches.

Assessment of 3D Interactions Between Promoters and Distal Regulatory Elements with Promoter Capture Hi-C (PCHi-C)

Chromosome conformation capture and its variants interrogate population-average chromatin structure at a higher resolution and throughput than microscopic methods. Capture Hi-C is a variant tailored for the simultaneous assessment of all interactions with thousands of specific bait sequences, so is particularly suited to genome-wide studies of promoter interactions with distal regulatory elements, such as enhancers. We present the principles and methods for Promoter Capture Hi-C (PCHi-C), from experimental design to data analysis.

Chromatin Looping Links Target Genes with Genetic Risk Loci for Dermatological Traits

Chromatin looping between regulatory elements and gene promoters presents a potential mechanism whereby disease risk variants affect their target genes. In this study, we use H3K27ac HiChIP, a method for assaying the active chromatin interactome in two cell lines: keratinocytes and skin lymphoma-derived CD8+ T cells. We integrate public datasets for a lymphoblastoid cell line and primary CD4+ T cells and identify gene targets at risk loci for skin-related disorders. Interacting genes enrich for pathways of known importance in each trait, such as cytokine response (psoriatic arthritis and psoriasis) and replicative senescence (melanoma). We show examples of how our analysis can inform changes in the current understanding of multiple psoriasis-associated risk loci. For example, the variant rs10794648, which is generally assigned to IFNLR1, was linked to GRHL3, a gene essential in skin repair and development, in our dataset. Our findings, therefore, indicate a renewed importance of skin-related factors in the risk of disease.

The Pol II preinitiation complex (PIC) influences Mediator binding but not promoter-enhancer looping

Knowledge of how Mediator and TFIID cross-talk contributes to promoter-enhancer (P-E) communication is important for elucidating the mechanism of enhancer function. We conducted an shRNA knockdown screen in murine embryonic stem cells to identify the functional overlap between Mediator and TFIID subunits on gene expression. Auxin-inducible degrons were constructed for TAF12 and MED4, the subunits eliciting the greatest overlap. Degradation of TAF12 led to a dramatic genome-wide decrease in gene expression accompanied by destruction of TFIID, loss of Pol II preinitiation complex (PIC) at promoters, and significantly decreased Mediator binding to promoters and enhancers. Interestingly, loss of the PIC elicited only a mild effect on P-E looping by promoter capture Hi-C (PCHi-C). Degradation of MED4 had a minor effect on Mediator integrity but led to a consistent twofold loss in gene expression, decreased binding of Pol II to Mediator, and decreased recruitment of Pol II to the promoters, but had no effect on the other PIC components. PCHi-C revealed no consistent effect of MED4 degradation on P-E looping. Collectively, our data show that TAF12 and MED4 contribute mechanistically in different ways to P-E communication but neither factor appears to directly control P-E looping, thereby dissociating P-E communication from physical looping.

Identification of 22 susceptibility loci associated with testicular germ cell tumors

Testicular germ cell tumors (TGCT) are the most common tumor in young white men and have a high heritability. In this study, the international Testicular Cancer Consortium assemble 10,156 and 179,683 men with and without TGCT, respectively, for a genome-wide association study. This meta-analysis identifies 22 TGCT susceptibility loci, bringing the total to 78, which account for 44% of disease heritability. Men with a polygenic risk score (PRS) in the 95th percentile have a 6.8-fold increased risk of TGCT compared to men with median scores. Among men with independent TGCT risk factors such as cryptorchidism, the PRS may guide screening decisions with the goal of reducing treatment-related complications causing long-term morbidity in survivors. These findings emphasize the interconnected nature of two known pathways that promote TGCT susceptibility: male germ cell development within its somatic niche and regulation of chromosomal division and structure, and implicate an additional biological pathway, mRNA translation.

Genome-Wide Association Analyses Identify Variants in IRF4 Associated With Acute Myeloid Leukemia and Myelodysplastic Syndrome Susceptibility

The role of common genetic variation in susceptibility to acute myeloid leukemia (AML), and myelodysplastic syndrome (MDS), a group of rare clonal hematologic disorders characterized by dysplastic hematopoiesis and high mortality, remains unclear. We performed AML and MDS genome-wide association studies (GWAS) in the DISCOVeRY-BMT cohorts (2,309 cases and 2,814 controls). Association analysis based on subsets (ASSET) was used to conduct a summary statistics SNP-based analysis of MDS and AML subtypes. For each AML and MDS case and control we used PrediXcan to estimate the component of gene expression determined by their genetic profile and correlate this imputed gene expression level with risk of developing disease in a transcriptome-wide association study (TWAS). ASSET identified an increased risk for de novo AML and MDS (OR = 1.38, 95% CI, 1.26-1.51, Pmeta = 2.8 × 10-12) in patients carrying the T allele at s12203592 in Interferon Regulatory Factor 4 (IRF4), a transcription factor which regulates myeloid and lymphoid hematopoietic differentiation. Our TWAS analyses showed increased IRF4 gene expression is associated with increased risk of de novo AML and MDS (OR = 3.90, 95% CI, 2.36-6.44, Pmeta = 1.0 × 10-7). The identification of IRF4 by both GWAS and TWAS contributes valuable insight on the role of genetic variation in AML and MDS susceptibility.

Multi-Omics Approaches in Immunological Research

The immune system plays a vital role in health and disease, and is regulated through a complex interactive network of many different immune cells and mediators. To understand the complexity of the immune system, we propose to apply a multi-omics approach in immunological research. This review provides a complete overview of available methodological approaches for the different omics data layers relevant for immunological research, including genetics, epigenetics, transcriptomics, proteomics, metabolomics, and cellomics. Thereafter, we describe the various methods for data analysis as well as how to integrate different layers of omics data. Finally, we discuss the possible applications of multi-omics studies and opportunities they provide for understanding the complex regulatory networks as well as immune variation in various immune-related diseases.

The global and promoter-centric 3D genome organization temporally resolved during a circadian cycle

BACKGROUND

Circadian gene expression is essential for organisms to adjust their physiology and anticipate daily changes in the environment. The molecular mechanisms controlling circadian gene transcription are still under investigation. In particular, how chromatin conformation at different genomic scales and regulatory elements impact rhythmic gene expression has been poorly characterized.

RESULTS

Here we measure changes in the spatial chromatin conformation in mouse liver using genome-wide and promoter-capture Hi-C alongside daily oscillations in gene transcription. We find topologically associating domains harboring circadian genes that switch assignments between the transcriptionally active and inactive compartment at different hours of the day, while their boundaries stably maintain their structure over time. To study chromatin contacts of promoters at high resolution over time, we apply promoter capture Hi-C. We find circadian gene promoters displayed a maximal number of chromatin contacts at the time of their peak transcriptional output. Furthermore, circadian genes, as well as contacted and transcribed regulatory elements, reach maximal expression at the same timepoints. Anchor sites of circadian gene promoter loops are enriched in DNA binding sites for liver nuclear receptors and other transcription factors, some exclusively present in either rhythmic or stable contacts. Finally, by comparing the interaction profiles between core clock and output circadian genes, we show that core clock interactomes are more dynamic compared to output circadian genes.

CONCLUSION

Our results identify chromatin conformation dynamics at different scales that parallel oscillatory gene expression and characterize the repertoire of regulatory elements that control circadian gene transcription through rhythmic or stable chromatin configurations.

3D promoter architecture re-organization during iPSC-derived neuronal cell differentiation implicates target genes for neurodevelopmental disorders

Neurodevelopmental disorders are thought to arise from interrupted development of the brain at an early age. Genome-wide association studies (GWAS) have identified hundreds of loci associated with susceptibility to neurodevelopmental disorders; however, which noncoding variants regulate which genes at these loci is often unclear. To implicate neuronal GWAS effector genes, we performed an integrated analysis of transcriptomics, epigenomics and chromatin conformation changes during the development from Induced pluripotent stem cell-derived neuronal progenitor cells (NPCs) into neurons using a combination of high-resolution promoter-focused Capture-C, ATAC-seq and RNA-seq. We observed that gene expression changes during the NPC-to-neuron transition were highly dependent on both promoter accessibility changes and long-range interactions which connect distal cis-regulatory elements (enhancer or silencers) to developmental-stage-specific genes. These genome-scale promoter-cis-regulatory-element atlases implicated 454 neurodevelopmental disorder-associated, putative causal variants mapping to 600 distal targets. These putative effector genes were significantly enriched for pathways involved in the regulation of neuronal development and chromatin organization, with 27 % expressed in a stage-specific manner. The intersection of open chromatin and chromatin conformation revealed development-stage-specific gene regulatory architectures during neuronal differentiation, providing a rich resource to aid characterization of the genetic and developmental basis of neurodevelopmental disorders.

covNorm: An R package for coverage based normalization of Hi-C and capture Hi-C data

Hi-C and capture Hi-C have greatly advanced our understanding of the principles of higher-order chromatin structure. In line with the evolution of the Hi-C protocols, there is a demand for an advanced computational method that can be applied to the various forms of Hi-C protocols and effectively remove innate biases. To resolve this issue, we developed an implicit normalization method named “covNorm” and implemented it as an R package. The proposed method can perform a complete procedure of data processing for Hi-C and its variants. Starting from the negative binomial model-based normalization for DNA fragment coverages, removal of genomic distance-dependent background and calling of the significant interactions can be applied sequentially. The performance evaluation of covNorm showed enhanced or similar reproducibility in terms of HiC-spector score, correlation of compartment A/B profiles, and detection of reproducible significant long-range chromatin contacts compared to baseline methods in the benchmark datasets. The developed method is powerful in terms of effective normalization of Hi-C and capture Hi-C data, detection of long-range chromatin contacts, and readily extendibility to the other derivative Hi-C protocols. The covNorm R package is freely available at GitHub: https://github.com/kaistcbfg/covNormRpkg.

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

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

TOP1 inhibition therapy protects against SARS-CoV-2-induced lethal inflammation

The ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently affecting millions of lives worldwide. Large retrospective studies indicate that an elevated level of inflammatory cytokines and pro-inflammatory factors are associated with both increased disease severity and mortality. Here, using multidimensional epigenetic, transcriptional, in vitro, and in vivo analyses, we report that topoisomerase 1 (TOP1) inhibition suppresses lethal inflammation induced by SARS-CoV-2. Therapeutic treatment with two doses of topotecan (TPT), an FDA-approved TOP1 inhibitor, suppresses infection-induced inflammation in hamsters. TPT treatment as late as 4 days post-infection reduces morbidity and rescues mortality in a transgenic mouse model. These results support the potential of TOP1 inhibition as an effective host-directed therapy against severe SARS-CoV-2 infection. TPT and its derivatives are inexpensive clinical-grade inhibitors available in most countries. Clinical trials are needed to evaluate the efficacy of repurposing TOP1 inhibitors for severe coronavirus disease 2019 (COVID-19) in humans.

Epstein-Barr virus inactivates the transcriptome and disrupts the chromatin architecture of its host cell in the first phase of lytic reactivation

Epstein-Barr virus (EBV), a herpes virus also termed HHV 4 and the first identified human tumor virus, establishes a stable, long-term latent infection in human B cells, its preferred host. Upon induction of EBV's lytic phase, the latently infected cells turn into a virus factory, a process that is governed by EBV. In the lytic, productive phase, all herpes viruses ensure the efficient induction of all lytic viral genes to produce progeny, but certain of these genes also repress the ensuing antiviral responses of the virally infected host cells, regulate their apoptotic death or control the cellular transcriptome. We now find that EBV causes previously unknown massive and global alterations in the chromatin of its host cell upon induction of the viral lytic phase and prior to the onset of viral DNA replication. The viral initiator protein of the lytic cycle, BZLF1, binds to >105 binding sites with different sequence motifs in cellular chromatin in a concentration dependent manner implementing a binary molar switch probably to prevent noise-induced erroneous induction of EBV's lytic phase. Concomitant with DNA binding of BZLF1, silent chromatin opens locally as shown by ATAC-seq experiments, while previously wide-open cellular chromatin becomes inaccessible on a global scale within hours. While viral transcripts increase drastically, the induction of the lytic phase results in a massive reduction of cellular transcripts and a loss of chromatin-chromatin interactions of cellular promoters with their distal regulatory elements as shown in Capture-C experiments. Our data document that EBV's lytic cycle induces discrete early processes that disrupt the architecture of host cellular chromatin and repress the cellular epigenome and transcriptome likely supporting the efficient de novo synthesis of this herpes virus.

A model of active transcription hubs that unifies the roles of active promoters and enhancers

An essential questions of gene regulation is how large number of enhancers and promoters organize into gene regulatory loops. Using transcription-factor binding enrichment as an indicator of enhancer strength, we identified a portion of H3K27ac peaks as potentially strong enhancers and found a universal pattern of promoter and enhancer distribution: At actively transcribed regions of length of ∼200-300 kb, the numbers of active promoters and enhancers are inversely related. Enhancer clusters are associated with isolated active promoters, regardless of the gene's cell-type specificity. As the number of nearby active promoters increases, the number of enhancers decreases. At regions where multiple active genes are closely located, there are few distant enhancers. With Hi-C analysis, we demonstrate that the interactions among the regulatory elements (active promoters and enhancers) occur predominantly in clusters and multiway among linearly close elements and the distance between adjacent elements shows a preference of ∼30 kb. We propose a simple rule of spatial organization of active promoters and enhancers: Gene transcriptions and regulations mainly occur at local active transcription hubs contributed dynamically by multiple elements from linearly close enhancers and/or active promoters. The hub model can be represented with a flower-shaped structure and implies an enhancer-like role of active promoters.

HCMB: A stable and efficient algorithm for processing the normalization of highly sparse Hi-C contact data

The high-throughput genome-wide chromosome conformation capture (Hi-C) method has recently become an important tool to study chromosomal interactions where one can extract meaningful biological information including P(s) curve, topologically associated domains, A/B compartments, and other biologically relevant signals. Normalization is a critical pre-processing step of downstream analyses for the elimination of systematic and technical biases from chromatin contact matrices due to different mappability, GC content, and restriction fragment lengths. Especially, the problem of high sparsity puts forward a huge challenge on the correction, indicating the urgent need for a stable and efficient method for Hi-C data normalization. Recently, some matrix balancing methods have been developed to normalize Hi-C data, such as the Knight-Ruiz (KR) algorithm, but it failed to normalize contact matrices with high sparsity. Here, we presented an algorithm, Hi-C Matrix Balancing (HCMB), based on an iterative solution of equations, combining with linear search and projection strategy to normalize the Hi-C original interaction data. Both the simulated and experimental data demonstrated that HCMB is robust and efficient in normalizing Hi-C data and preserving the biologically relevant Hi-C features even facing very high sparsity. HCMB is implemented in Python and is freely accessible to non-commercial users at GitHub: https://github.com/HUST-DataMan/HCMB.

Genetic perturbation of PU.1 binding and chromatin looping at neutrophil enhancers associates with autoimmune disease

Neutrophils play fundamental roles in innate immune response, shape adaptive immunity, and are a potentially causal cell type underpinning genetic associations with immune system traits and diseases. Here, we profile the binding of myeloid master regulator PU.1 in primary neutrophils across nearly a hundred volunteers. We show that variants associated with differential PU.1 binding underlie genetically-driven differences in cell count and susceptibility to autoimmune and inflammatory diseases. We integrate these results with other multi-individual genomic readouts, revealing coordinated effects of PU.1 binding variants on the local chromatin state, enhancer-promoter contacts and downstream gene expression, and providing a functional interpretation for 27 genes underlying immune traits. Collectively, these results demonstrate the functional role of PU.1 and its target enhancers in neutrophil transcriptional control and immune disease susceptibility.

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

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

Identifying high-confidence capture Hi-C interactions using CHiCANE

The ability to identify regulatory interactions that mediate gene expression changes through distal elements, such as risk loci, is transforming our understanding of how genomes are spatially organized and regulated. Capture Hi-C (CHi-C) is a powerful tool to delineate such regulatory interactions. However, primary analysis and downstream interpretation of CHi-C profiles remains challenging and relies on disparate tools with ad-hoc input/output formats and specific assumptions for statistical modeling. Here we present a data processing and interaction calling toolkit (CHiCANE), specialized for the analysis and meaningful interpretation of CHi-C assays. In this protocol, we demonstrate applications of CHiCANE to region capture Hi-C (rCHi-C) and promoter capture Hi-C (pCHi-C) libraries, followed by quality assessment of interaction peaks, as well as downstream analysis specific to rCHi-C and pCHi-C to aid functional interpretation. For a typical rCHi-C/pCHi-C dataset this protocol takes up to 3 d for users with a moderate understanding of R programming and statistical concepts, although this is dependent on dataset size and compute power available. CHiCANE is freely available at https://cran.r-project.org/web/packages/chicane .

3D reconstruction of genomic regions from sparse interaction data

Chromosome conformation capture (3C) technologies measure the interaction frequency between pairs of chromatin regions within the nucleus in a cell or a population of cells. Some of these 3C technologies retrieve interactions involving non-contiguous sets of loci, resulting in sparse interaction matrices. One of such 3C technologies is Promoter Capture Hi-C (pcHi-C) that is tailored to probe only interactions involving gene promoters. As such, pcHi-C provides sparse interaction matrices that are suitable to characterize short- and long-range enhancer-promoter interactions. Here, we introduce a new method to reconstruct the chromatin structural (3D) organization from sparse 3C-based datasets such as pcHi-C. Our method allows for data normalization, detection of significant interactions and reconstruction of the full 3D organization of the genomic region despite of the data sparseness. Specifically, it builds, with as low as the 2-3% of the data from the matrix, reliable 3D models of similar accuracy of those based on dense interaction matrices. Furthermore, the method is sensitive enough to detect cell-type-specific 3D organizational features such as the formation of different networks of active gene communities.

Global discovery of lupus genetic risk variant allelic enhancer activity

Genome-wide association studies of Systemic Lupus Erythematosus (SLE) nominate 3073 genetic variants at 91 risk loci. To systematically screen these variants for allelic transcriptional enhancer activity, we construct a massively parallel reporter assay (MPRA) library comprising 12,396 DNA oligonucleotides containing the genomic context around every allele of each SLE variant. Transfection into the Epstein-Barr virus-transformed B cell line GM12878 reveals 482 variants with enhancer activity, with 51 variants showing genotype-dependent (allelic) enhancer activity at 27 risk loci. Comparison of MPRA results in GM12878 and Jurkat T cell lines highlights shared and unique allelic transcriptional regulatory mechanisms at SLE risk loci. In-depth analysis of allelic transcription factor (TF) binding at and around allelic variants identifies one class of TFs whose DNA-binding motif tends to be directly altered by the risk variant and a second class of TFs that bind allelically without direct alteration of their motif by the variant. Collectively, our approach provides a blueprint for the discovery of allelic gene regulation at risk loci for any disease and offers insight into the transcriptional regulatory mechanisms underlying SLE.

Thousands of genetic variants have been associated with lupus, but causal variants and mechanisms are unknown. Here, the authors combine a massively parallel reporter assay with genome-wide ChIP experiments to identify risk variants with allelic enhancer activity mediated through transcription factor binding.

Integrative analysis of liver-specific non-coding regulatory SNPs associated with the risk of coronary artery disease

Genetic factors underlying coronary artery disease (CAD) have been widely studied using genome-wide association studies (GWASs). However, the functional understanding of the CAD loci has been limited by the fact that a majority of GWAS variants are located within non-coding regions with no functional role. High cholesterol and dysregulation of the liver metabolism such as non-alcoholic fatty liver disease confer an increased risk of CAD. Here, we studied the function of non-coding single-nucleotide polymorphisms in CAD GWAS loci located within liver-specific enhancer elements by identifying their potential target genes using liver cis-eQTL analysis and promoter Capture Hi-C in HepG2 cells. Altogether, 734 target genes were identified of which 121 exhibited correlations to liver-related traits. To identify potentially causal regulatory SNPs, the allele-specific enhancer activity was analyzed by (1) sequence-based computational predictions, (2) quantification of allele-specific transcription factor binding, and (3) STARR-seq massively parallel reporter assay. Altogether, our analysis identified 1,277 unique SNPs that display allele-specific regulatory activity. Among these, susceptibility enhancers near important cholesterol homeostasis genes (APOB, APOC1, APOE, and LIPA) were identified, suggesting that altered gene regulatory activity could represent another way by which genetic variation regulates serum lipoprotein levels. Using CRISPR-based perturbation, we demonstrate how the deletion/activation of a single enhancer leads to changes in the expression of many target genes located in a shared chromatin interaction domain. Our integrative genomics approach represents a comprehensive effort in identifying putative causal regulatory regions and target genes that could predispose to clinical manifestation of CAD by affecting liver function.

Using functional genomics to advance the understanding of psoriatic arthritis

Psoriatic arthritis (PsA) is a complex disease where susceptibility is determined by genetic and environmental risk factors. Clinically, PsA involves inflammation of the joints and the skin, and, if left untreated, results in irreversible joint damage. There is currently no cure and the few treatments available to alleviate symptoms do not work in all patients. Over the past decade, genome-wide association studies (GWAS) have uncovered a large number of disease-associated loci but translating these findings into functional mechanisms and novel targets for therapeutic use is not straightforward. Most variants have been predicted to affect primarily long-range regulatory regions such as enhancers. There is now compelling evidence to support the use of chromatin conformation analysis methods to discover novel genes that can be affected by disease-associated variants. Here, we will review the studies published in the field that have given us a novel understanding of gene regulation in the context of functional genomics and how this relates to the study of PsA and its underlying disease mechanism.

High-resolution targeted 3C interrogation of cis-regulatory element organization at genome-wide scale

Chromosome conformation capture (3C) provides an adaptable tool for studying diverse biological questions. Current 3C methods generally provide either low-resolution interaction profiles across the entire genome, or high-resolution interaction profiles at limited numbers of loci. Due to technical limitations, generation of reproducible high-resolution interaction profiles has not been achieved at genome-wide scale. Here, to overcome this barrier, we systematically test each step of 3C and report two improvements over current methods. We show that up to 30% of reporter events generated using the popular in situ 3C method arise from ligations between two individual nuclei, but this noise can be almost entirely eliminated by isolating intact nuclei after ligation. Using Nuclear-Titrated Capture-C, we generate reproducible high-resolution genome-wide 3C interaction profiles by targeting 8055 gene promoters in erythroid cells. By pairing high-resolution 3C interaction calls with nascent gene expression we interrogate the role of promoter hubs and super-enhancers in gene regulation.

Biological constraints on GWAS SNPs at suggestive significance thresholds reveal additional BMI loci

To uncover novel significant association signals (p<5×10-8), genome-wide association studies (GWAS) requires increasingly larger sample sizes to overcome statistical correction for multiple testing. As an alternative, we aimed to identify associations among suggestive signals (5 × 10-8≤p<5×10-4) in increasingly powered GWAS efforts using chromatin accessibility and direct contact with gene promoters as biological constraints. We conducted retrospective analyses of three GIANT BMI GWAS efforts using ATAC-seq and promoter-focused Capture C data from human adipocytes and embryonic stem cell (ESC)-derived hypothalamic-like neurons. This approach, with its extremely low false-positive rate, identified 15 loci at p<5×10-5 in the 2010 GWAS, of which 13 achieved genome-wide significance by 2018, including at NAV1, MTIF3, and ADCY3. Eighty percent of constrained 2015 loci achieved genome-wide significance in 2018. We observed similar results in waist-to-hip ratio analyses. In conclusion, biological constraints on sub-significant GWAS signals can reveal potentially true-positive loci for further investigation in existing data sets without increasing sample size.

Transcriptionally active enhancers in human cancer cells

The growth of human cancer cells is driven by aberrant enhancer and gene transcription activity. Here, we use transient transcriptome sequencing (TT-seq) to map thousands of transcriptionally active putative enhancers in fourteen human cancer cell lines covering seven types of cancer. These enhancers were associated with cell type-specific gene expression, enriched for genetic variants that predispose to cancer, and included functionally verified enhancers. Enhancer-promoter (E-P) pairing by correlation of transcription activity revealed ~ 40,000 putative E-P pairs, which were depleted for housekeeping genes and enriched for transcription factors, cancer-associated genes, and 3D conformational proximity. The cell type specificity and transcription activity of target genes increased with the number of paired putative enhancers. Our results represent a rich resource for future studies of gene regulation by enhancers and their role in driving cancerous cell growth.

Algorithmic considerations when analysing capture Hi-C data

Chromosome conformation capture methodologies have provided insight into the effect of 3D genomic architecture on gene regulation. Capture Hi-C (CHi-C) is a recent extension of Hi-C that improves the effective resolution of chromatin interactions by enriching for defined regions of biological relevance. The varying targeting efficiency between capture regions, however, introduces bias not present in conventional Hi-C, making analysis more complicated. Here we consider salient features of an algorithm that should be considered in evaluating the performance of a program used to analyse CHi-C data in order to infer meaningful interactions. We use the program CHICAGO to analyse promotor capture Hi-C data generated on 28 different cell lines as a case study.

Muscle progenitor specification and myogenic differentiation are associated with changes in chromatin topology

Using Hi-C, promoter-capture Hi-C (pCHi-C), and other genome-wide approaches in skeletal muscle progenitors that inducibly express a master transcription factor, Pax7, we systematically characterize at high-resolution the spatio-temporal re-organization of compartments and promoter-anchored interactions as a consequence of myogenic commitment and differentiation. We identify key promoter-enhancer interaction motifs, namely, cliques and networks, and interactions that are dependent on Pax7 binding. Remarkably, Pax7 binds to a majority of super-enhancers, and together with a cadre of interacting transcription factors, assembles feed-forward regulatory loops. During differentiation, epigenetic memory and persistent looping are maintained at a subset of Pax7 enhancers in the absence of Pax7. We also identify and functionally validate a previously uncharacterized Pax7-bound enhancer hub that regulates the essential myosin heavy chain cluster during skeletal muscle cell differentiation. Our studies lay the groundwork for understanding the role of Pax7 in orchestrating changes in the three-dimensional chromatin conformation in muscle progenitors.

Transcriptome and regulatory maps of decidua-derived stromal cells inform gene discovery in preterm birth

While a genetic component of preterm birth (PTB) has long been recognized and recently mapped by genome-wide association studies (GWASs), the molecular determinants underlying PTB remain elusive. This stems in part from an incomplete availability of functional genomic annotations in human cell types relevant to pregnancy and PTB. We generated transcriptome (RNA-seq), epigenome (ChIP-seq of H3K27ac, H3K4me1, and H3K4me3 histone modifications), open chromatin (ATAC-seq), and chromatin interaction (promoter capture Hi-C) annotations of cultured primary decidua-derived mesenchymal stromal/stem cells and in vitro differentiated decidual stromal cells and developed a computational framework to integrate these functional annotations with results from a GWAS of gestational duration in 56,384 women. Using these resources, we uncovered additional loci associated with gestational duration and target genes of associated loci. Our strategy illustrates how functional annotations in pregnancy-relevant cell types aid in the experimental follow-up of GWAS for PTB and, likely, other pregnancy-related conditions.

Mapping the epigenomic and transcriptomic interplay during memory formation and recall in the hippocampal engram ensemble

The epigenome and three-dimensional (3D) genomic architecture are emerging as key factors in the dynamic regulation of different transcriptional programs required for neuronal functions. In this study, we used an activity-dependent tagging system in mice to determine the epigenetic state, 3D genome architecture and transcriptional landscape of engram cells over the lifespan of memory formation and recall. Our findings reveal that memory encoding leads to an epigenetic priming event, marked by increased accessibility of enhancers without the corresponding transcriptional changes. Memory consolidation subsequently results in spatial reorganization of large chromatin segments and promoter-enhancer interactions. Finally, with reactivation, engram neurons use a subset of de novo long-range interactions, where primed enhancers are brought in contact with their respective promoters to upregulate genes involved in local protein translation in synaptic compartments. Collectively, our work elucidates the comprehensive transcriptional and epigenomic landscape across the lifespan of memory formation and recall in the hippocampal engram ensemble.

High-resolution three-dimensional chromatin profiling of the Chinese hamster ovary cell genome

Chinese hamster ovary (CHO) cell lines are the pillars of a multibillion‐dollar biopharmaceutical industry producing recombinant therapeutic proteins. The effects of local chromatin organization and epigenetic repression within these cell lines result in unpredictable and unstable transgene expression following random integration. Limited knowledge of the CHO genome and its higher order chromatin organization has thus far impeded functional genomics approaches required to tackle these issues. Here, we present an integrative three‐dimensional (3D) map of genome organization within the CHOK1SV® 10E9 cell line in conjunction with an improved, less fragmented CHOK1SV 10E9 genome assembly. Using our high‐resolution chromatin conformation datasets, we have assigned ≈90% of sequence to a chromosome‐scale genome assembly. Our genome‐wide 3D map identifies higher order chromatin structures such as topologically associated domains, incorporates our chromatin accessibility data to enhance the identification of active cis‐regulatory elements, and importantly links these cis‐regulatory elements to target promoters in a 3D promoter interactome. We demonstrate the power of our improved functional annotation by evaluating the 3D landscape of a transgene integration site and two phenotypically different cell lines. Our work opens up further novel genome engineering targets, has the potential to inform vital improvements for industrial biotherapeutic production, and represents a significant advancement for CHO cell line development.

A computational framework for identifying the transcription factors involved in enhancer-promoter loop formation

The pairwise interaction between transcription factors (TFs) plays an important role in enhancer-promoter loop formation. Although thousands of TFs in the human genome have been found, only a few TF pairs have been demonstrated to be related to loop formation. It is still a challenge to determine which TF pairs could be involved in the enhancer-promoter regulation network. This work describes a computational framework to identify TF pairs in enhancer-promoter regulation. By integrating different levels of data derived from Promoter Capture Hi-C, chromatin immunoprecipitation sequencing (ChIP-seq) of histone marks, RNA-seq, protein-protein interaction (PPI), and TF motif, we identified 361 significant TF pairs and constructed a TF interaction network. From the network, we found several hub-TFs, which may have important roles in the regulation of long-range interactions. Our studies extended TF pairs identified in other experimental and computational approaches. These findings will help the further study of long-range interactions between enhancers and promoters.

Altered transcriptional and chromatin responses to rhinovirus in bronchial epithelial cells from adults with asthma

There is a life-long relationship between rhinovirus (RV) infection and the development and clinical manifestations of asthma. In this study we demonstrate that cultured primary bronchial epithelial cells from adults with asthma (n = 9) show different transcriptional and chromatin responses to RV infection compared to those without asthma (n = 9). Both the number and magnitude of transcriptional and chromatin responses to RV were muted in cells from asthma cases compared to controls. Pathway analysis of the transcriptionally responsive genes revealed enrichments of apoptotic pathways in controls but inflammatory pathways in asthma cases. Using promoter capture Hi-C we tethered regions of RV-responsive chromatin to RV-responsive genes and showed enrichment of these regions and genes at asthma GWAS loci. Taken together, our studies indicate a delayed or prolonged inflammatory state in cells from asthma cases and highlight genes that may contribute to genetic risk for asthma.

Variant-to-Gene-Mapping Analyses Reveal a Role for the Hypothalamus in Genetic Susceptibility to Inflammatory Bowel Disease

BACKGROUND & AIMS

Inflammatory bowel disease (IBD) is a polygenic disorder characterized principally by dysregulated inflammation impacting the gastrointestinal tract. However, there also is increasing evidence for a clinical association with stress and depression. Given the role of the hypothalamus in stress responses and in the pathogenesis of depression, useful insights could be gleaned from understanding its genetic role in IBD.

METHODS

We conducted genetic correlation analyses on publicly available genome-wide association study summary statistics for depression and IBD traits to identify genetic commonalities. We used partitioned linkage disequilibrium score regression, leveraging our ATAC sequencing and promoter-focused Capture C data, to measure enrichment of IBD single-nucleotide polymorphisms within promoter-interacting open chromatin regions of human embryonic stem cell-derived hypothalamic-like neurons (HNs). Using the same data sets, we performed variant-to-gene mapping to implicate putative IBD effector genes in HNs. To contrast these results, we similarly analyzed 3-dimensional genomic data generated in epithelium-derived colonoids from rectal biopsy specimens from donors without pathologic disease noted at the time of colonoscopy. Finally, we conducted enrichment pathway analyses on the implicated genes to identify putative IBD dysfunctional pathways.

RESULTS

We found significant genetic correlations (rg) of 0.122 with an adjusted P (Padj) = 1.4 × 10-4 for IBD: rg = 0.122; Padj = 2.5 × 10-3 for ulcerative colitis and genetic correlation (rg) = 0.094; Padj = 2.5 × 10-3 for Crohn's disease, and significant approximately 4-fold (P = .005) and approximately 7-fold (P = .03) enrichment of IBD single-nucleotide polymorphisms in HNs and colonoids, respectively. We implicated 25 associated genes in HNs, among which CREM, CNTF, and RHOA encode key regulators of stress. Seven genes also additionally were implicated in the colonoids. We observed an overall enrichment for immune and hormonal signaling pathways, and a colonoid-specific enrichment for microbiota-relevant terms.

CONCLUSIONS

Our results suggest that the hypothalamus warrants further study in the context of IBD pathogenesis.

An enhanced genetic model of relapsed IGH-translocated multiple myeloma evolutionary dynamics

Most patients with multiple myeloma (MM) die from progressive disease after relapse. To advance our understanding of MM evolution mechanisms, we performed whole-genome sequencing of 80 IGH-translocated tumour-normal newly diagnosed pairs and 24 matched relapsed tumours from the Myeloma XI trial. We identify multiple events as potentially important for survival and therapy-resistance at relapse including driver point mutations (e.g., TET2), translocations (MAP3K14), lengthened telomeres, and increased genomic instability (e.g., 17p deletions). Despite heterogeneous mutational processes contributing to relapsed mutations across MM subtypes, increased AID/APOBEC activity is particularly associated with shorter progression time to relapse, and contributes to higher mutational burden at relapse. In addition, we identify three enhanced major clonal evolution patterns of MM relapse, independent of treatment strategies and molecular karyotypes, questioning the viability of "evolutionary herding" approach in treating drug-resistant MM. Our data show that MM relapse is associated with acquisition of new mutations and clonal selection, and suggest APOBEC enzymes among potential targets for therapy-resistant MM.

Highly interconnected enhancer communities control lineage-determining genes in human mesenchymal stem cells

Adipocyte differentiation is driven by waves of transcriptional regulators that reprogram the enhancer landscape and change the wiring of the promoter interactome. Here, we use high-throughput chromosome conformation enhancer capture to interrogate the role of enhancer-to-enhancer interactions during differentiation of human mesenchymal stem cells. We find that enhancers form an elaborate network that is dynamic during differentiation and coupled with changes in enhancer activity. Transcription factors (TFs) at baited enhancers amplify TF binding at target enhancers, a phenomenon we term cross-interaction stabilization of TFs. Moreover, highly interconnected enhancers (HICE) act as integration hubs orchestrating differentiation by the formation of three-dimensional enhancer communities, inside which, HICE, and other enhancers, converge on phenotypically important gene promoters. Collectively, these results indicate that enhancer interactions play a key role in the regulation of enhancer function, and that HICE are important for both signal integration and compartmentalization of the genome.

A modified protocol of Capture-C allows affordable and flexible high-resolution promoter interactome analysis

Large-scale epigenomic projects have mapped hundreds of thousands of potential regulatory sites in the human genome, but only a small proportion of these elements are proximal to transcription start sites. It is believed that the majority of these sequences are remote promoter-activating genomic sites scattered within several hundreds of kilobases from their cognate promoters and referred to as enhancers. It is still unclear what principles, aside from relative closeness in the linear genome, determine which promoter(s) is controlled by a given enhancer; however, this understanding is of great fundamental and clinical relevance. In recent years, C-methods (chromosome conformation capture-based methods) have become a powerful tool for the identification of enhancer-promoter spatial contacts that, in most cases, reflect their functional link. Here, we describe a new hybridisation-based promoter Capture-C protocol that makes use of biotinylated dsDNA probes generated by PCR from a custom pool of long oligonucleotides. The described protocol allows high-resolution promoter interactome description, providing a flexible and cost-effective alternative to the existing promoter Capture-C modifications. Based on the obtained data, we propose several tips on probe design that could potentially improve the results of future experiments.

Spatial Genome Re-organization between Fetal and Adult Hematopoietic Stem Cells

Fetal hematopoietic stem cells (HSCs) undergo a developmental switch to become adult HSCs with distinct functional properties. To better understand the molecular mechanisms underlying the developmental switch, we have conducted deep sequencing of the 3D genome, epigenome, and transcriptome of fetal and adult HSCs in mouse. We find that chromosomal compartments and topologically associating domains (TADs) are largely conserved between fetal and adult HSCs. However, there is a global trend of increased compartmentalization and TAD boundary strength in adult HSCs. In contrast, intra-TAD chromatin interactions are much more dynamic and wide-spread, involving over a thousand gene promoters and distal enhancers. These developmental-stage-specific enhancer-promoter interactions are mediated by different sets of transcription factors, such as TCF3 and MAFB in fetal HSCs, versus NR4A1 and GATA3 in adult HSCs. Loss-of-function studies of TCF3 confirm the role of TCF3 in mediating condition-specific enhancer-promoter interactions and gene regulation in fetal HSCs.

A developmental transition occurs between fetal and adult hematopoietic stem cells. How the 3D genome folding contributes to this transition is poorly understood. Chen et al. show global genome organization is largely conserved, but a large fraction of enhancer-promoter interactions is reorganized and regulate genes contributing to the phenotypic differences.

Ecdysone-Induced 3D Chromatin Reorganization Involves Active Enhancers Bound by Pipsqueak and Polycomb

Evidence suggests that Polycomb (Pc) is present at chromatin loop anchors in Drosophila. Pc is recruited to DNA through interactions with the GAGA binding factors GAF and Pipsqueak (Psq). Using HiChIP in Drosophila cells, we find that the psq gene, which has diverse roles in development and tumorigenesis, encodes distinct isoforms with unanticipated roles in genome 3D architecture. The BR-C, ttk, and bab domain (BTB)-containing Psq isoform (Psq^L) colocalizes genome-wide with known architectural proteins. Conversely, Psq lacking the BTB domain (Psq^S) is consistently found at Pc loop anchors and at active enhancers, including those that respond to the hormone ecdysone. After stimulation by this hormone, chromatin 3D organization is altered to connect promoters and ecdysone-responsive enhancers bound by Psq^S. Our findings link Psq variants lacking the BTB domain to Pc-bound active enhancers, thus shedding light into their molecular function in chromatin changes underlying the response to hormone stimulus.

Analysis of chromatin organization and gene expression in T cells identifies functional genes for rheumatoid arthritis

Genome-wide association studies have identified genetic variation contributing to complex disease risk. However, assigning causal genes and mechanisms has been more challenging because disease-associated variants are often found in distal regulatory regions with cell-type specific behaviours. Here, we collect ATAC-seq, Hi-C, Capture Hi-C and nuclear RNA-seq data in stimulated CD4+ T cells over 24 h, to identify functional enhancers regulating gene expression. We characterise changes in DNA interaction and activity dynamics that correlate with changes in gene expression, and find that the strongest correlations are observed within 200 kb of promoters. Using rheumatoid arthritis as an example of T cell mediated disease, we demonstrate interactions of expression quantitative trait loci with target genes, and confirm assigned genes or show complex interactions for 20% of disease associated loci, including FOXO1, which we confirm using CRISPR/Cas9.

Multiple functional variants in the IL1RL1 region are pretransplant markers for risk of GVHD and infection deaths

Graft-versus-host disease (GVHD) and infections are the 2 main causes of death without relapse after allogeneic hematopoietic cell transplantation (HCT). Elevated soluble serum simulation-2 (sST2), the product of IL1RL1 in plasma/serum post-HCT, is a validated GVHD biomarker. Hundreds of SNPs at 2q12.1 have been shown to be strongly associated with sST2 concentrations in healthy populations. We therefore hypothesized that the donor genetic variants in IL1RL1 correlate with sST2 protein levels associated with patient survival outcomes after HCT. We used DISCOVeRY-BMT (Determining the Influence of Susceptibility Conveying Variants Related to 1-Year Mortality after Blood and Marrow Transplantation), a genomic study of >3000 donor-recipient pairs, to inform our hypothesis. We first measured pre-HCT plasma/serum sST2 levels in a subset of DISCOVeRY-BMT donors (n = 757) and tested the association of donor sST2 levels with donor single nucleotide polymorphisms (SNPs) in the 2q12.1 region. Donor SNPs associated with sST2 levels were then tested for association with recipient death caused by acute GVHD (aGVHD)-, infection-, and transplant-related mortality in cohorts 1 and 2. Meta-analyses of cohorts 1 and 2 were performed using fixed-effects inverse variance weighting, and P values were corrected for multiple comparisons. Donor risk alleles in rs22441131 (P _meta = .00026) and rs2310241 (P _meta = .00033) increased the cumulative incidence of aGVHD death up to fourfold and were associated with high sST2 levels. Donor risk alleles at rs4851601 (P _meta = 9.7 × 10^-7), rs13019803 (P _meta = 8.9 × 10^-6), and rs13015714 (P _meta = 5.3 × 10^-4) increased cumulative incidence of infection death to almost sevenfold and were associated with low sST2 levels. These functional variants are biomarkers of infection or aGVHD death and could facilitate donor selection, prophylaxis, and a conditioning regimen to reduce post-HCT mortality.

Spatial patterns of CTCF sites define the anatomy of TADs and their boundaries

BACKGROUND

Topologically associating domains (TADs) are genomic regions of self-interaction. Additionally, it is known that TAD boundaries are enriched in CTCF binding sites. In turn, CTCF sites are known to be asymmetric, whereby the convergent configuration of a pair of CTCF sites leads to the formation of a chromatin loop in vivo. However, to date, it has been unclear how to reconcile TAD structure with CTCF-based chromatin loops.

RESULTS

We approach this problem by analysing CTCF binding site strengths and classifying clusters of CTCF sites along the genome on the basis of their relative orientation. Analysis of CTCF site orientation classes as a function of their spatial distribution along the human genome reveals that convergent CTCF site clusters are depleted while divergent CTCF clusters are enriched in the 5- to 100-kb range. We then analyse the distribution of CTCF binding sites as a function of TAD boundary conservation across seven primary human blood cell types. This reveals divergent CTCF site enrichment at TAD boundaries. Furthermore, convergent arrays of CTCF sites separate the left and right sections of TADs that harbour internal CTCF sites, resulting in unequal TAD 'halves'.

CONCLUSIONS

The orientation-based CTCF binding site cluster classification that we present reconciles TAD boundaries and CTCF site clusters in a mechanistically elegant fashion. This model suggests that the emergent structure of nuclear chromatin in the form of TADs relies on the obligate alternation of divergent and convergent CTCF site clusters that occur at different length scales along the genome.

Cohesin-Dependent and -Independent Mechanisms Mediate Chromosomal Contacts between Promoters and Enhancers

It is currently assumed that 3D chromosomal organization plays a central role in transcriptional control. However, depletion of cohesin and CTCF affects the steady-state levels of only a minority of transcripts. Here, we use high-resolution Capture Hi-C to interrogate the dynamics of chromosomal contacts of all annotated human gene promoters upon degradation of cohesin and CTCF. We show that a majority of promoter-anchored contacts are lost in these conditions, but many contacts with distinct properties are maintained, and some new ones are gained. The rewiring of contacts between promoters and active enhancers upon cohesin degradation associates with rapid changes in target gene transcription as detected by SLAM sequencing (SLAM-seq). These results provide a mechanistic explanation for the limited, but consistent, effects of cohesin and CTCF depletion on steady-state transcription and suggest the existence of both cohesin-dependent and -independent mechanisms of enhancer-promoter pairing.

A supervised learning framework for chromatin loop detection in genome-wide contact maps

Accurately predicting chromatin loops from genome-wide interaction matrices such as Hi-C data is critical to deepening our understanding of proper gene regulation. Current approaches are mainly focused on searching for statistically enriched dots on a genome-wide map. However, given the availability of orthogonal data types such as ChIA-PET, HiChIP, Capture Hi-C, and high-throughput imaging, a supervised learning approach could facilitate the discovery of a comprehensive set of chromatin interactions. Here, we present Peakachu, a Random Forest classification framework that predicts chromatin loops from genome-wide contact maps. We compare Peakachu with current enrichment-based approaches, and find that Peakachu identifies a unique set of short-range interactions. We show that our models perform well in different platforms, across different sequencing depths, and across different species. We apply this framework to predict chromatin loops in 56 Hi-C datasets, and release the results at the 3D Genome Browser.

Mapping effector genes at lupus GWAS loci using promoter Capture-C in follicular helper T cells

Systemic lupus erythematosus (SLE) is mediated by autoreactive antibodies that damage multiple tissues. Genome-wide association studies (GWAS) link >60 loci with SLE risk, but the causal variants and effector genes are largely unknown. We generated high-resolution spatial maps of SLE variant accessibility and gene connectivity in human follicular helper T cells (TFH), a cell type required for anti-nuclear antibodies characteristic of SLE. Of the ~400 potential regulatory variants identified, 90% exhibit spatial proximity to genes distant in the 1D genome sequence, including variants that loop to regulate the canonical TFH genes BCL6 and CXCR5 as confirmed by genome editing. SLE ‘variant-to-gene’ maps also implicate genes with no known role in TFH/SLE disease biology, including the kinases HIPK1 and MINK1. Targeting these kinases in TFH inhibits production of IL-21, a cytokine crucial for class-switched B cell antibodies. These studies offer mechanistic insight into the SLE-associated regulatory architecture of the human genome.

T cells are a major cell type involved in systemic lupus erythematosus (SLE). Here, the authors use promoter capture-C and ATAC-seq in human follicular T helper cells to identify SLE genes distant from GWAS loci (via 3D interaction) and validate the function of key regulatory elements and genes in vitro.

Chicdiff: a computational pipeline for detecting differential chromosomal interactions in Capture Hi-C data

Summary

Capture Hi-C is a powerful approach for detecting chromosomal interactions involving, at least on one end, DNA regions of interest, such as gene promoters. We present Chicdiff, an R package for robust detection of differential interactions in Capture Hi-C data. Chicdiff enhances a state-of-the-art differential testing approach for count data with bespoke normalization and multiple testing procedures that account for specific statistical properties of Capture Hi-C. We validate Chicdiff on published Promoter Capture Hi-C data in human Monocytes and CD4⁺ T cells, identifying multitudes of cell type-specific interactions, and confirming the overall positive association between promoter interactions and gene expression.

Availability and implementation

Chicdiff is implemented as an R package that is publicly available at https://github.com/RegulatoryGenomicsGroup/chicdiff.

Supplementary information

Supplementary data are available at Bioinformatics online.

Joint reconstruction of cis-regulatory interaction networks across multiple tissues using single-cell chromatin accessibility data

The rapid accumulation of single-cell chromatin accessibility data offers a unique opportunity to investigate common and specific regulatory mechanisms across different cell types. However, existing methods for cis-regulatory network reconstruction using single-cell chromatin accessibility data were only designed for cells belonging to one cell type, and resulting networks may be incomparable directly due to diverse cell numbers of different cell types. Here, we adopt a computational method to jointly reconstruct cis-regulatory interaction maps (JRIM) of multiple cell populations based on patterns of co-accessibility in single-cell data. We applied JRIM to explore common and specific regulatory interactions across multiple tissues from single-cell ATAC-seq dataset containing ~80 000 cells across 13 mouse tissues. Reconstructed common interactions among 13 tissues indeed relate to basic biological functions, and individual cis-regulatory networks show strong tissue specificity and functional relevance. More importantly, tissue-specific regulatory interactions are mediated by coordination of histone modifications and tissue-related TFs, and many of them may reveal novel regulatory mechanisms.

CDK-Mediator and FBXL19 prime developmental genes for activation by promoting atypical regulatory interactions

Appropriate developmental gene regulation relies on the capacity of gene promoters to integrate inputs from distal regulatory elements, yet how this is achieved remains poorly understood. In embryonic stem cells (ESCs), a subset of silent developmental gene promoters are primed for activation by FBXL19, a CpG island binding protein, through its capacity to recruit CDK-Mediator. How mechanistically these proteins function together to prime genes for activation during differentiation is unknown. Here we discover that in mouse ESCs FBXL19 and CDK-Mediator support long-range interactions between silent gene promoters that rely on FBXL19 for their induction during differentiation and gene regulatory elements. During gene induction, these distal regulatory elements behave in an atypical manner, in that the majority do not acquire histone H3 lysine 27 acetylation and no longer interact with their target gene promoter following gene activation. Despite these atypical features, we demonstrate by targeted deletions that these distal elements are required for appropriate gene induction during differentiation. Together these discoveries demonstrate that CpG-island associated gene promoters can prime genes for activation by communicating with atypical distal gene regulatory elements to achieve appropriate gene expression.

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

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