Identification of significant chromatin contacts from HiChIP data by FitHiChIP

Comprehensive dissection of cis-regulatory elements in a 2.8 Mb topologically associated domain in six human cancers

Cis-regulatory elements (CREs), such as enhancers and promoters, are fundamental regulators of gene expression and, across different cell types, the MYC locus utilizes a diverse regulatory architecture driven by multiple CREs. To better understand differences in CRE function, we perform pooled CRISPR inhibition (CRISPRi) screens to comprehensively probe the 2.8 Mb topologically-associated domain containing MYC in 6 human cancer cell lines with nucleotide resolution. We map 32 CREs where inhibition leads to changes in cell growth, including 8 that overlap previously identified enhancers. Targeting specific CREs decreases MYC expression by as much as 60%, and cell growth by as much as 50%. Using 3-D enhancer contact mapping, we find that these CREs almost always contact MYC but less than 10% of total MYC contacts impact growth when silenced, highlighting the utility of our approach to identify phenotypically-relevant CREs. We also detect an enrichment of lineage-specific transcription factors (TFs) at MYC CREs and, for some of these TFs, find a strong, tumor-specific correlation between TF and MYC expression not found in normal tissue. Taken together, these CREs represent systematically identified, functional regulatory regions and demonstrate how the same region of the human genome can give rise to complex, tissue-specific gene regulation.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

Nucleosome fibre topology guides transcription factor binding to enhancers

Cellular identity requires the concerted action of multiple transcription factors (TFs) bound together to enhancers of cell-type-specific genes. Despite TFs recognizing specific DNA motifs within accessible chromatin, this information is insufficient to explain how TFs select enhancers1. Here we compared four different TF combinations that induce different cell states, analysing TF genome occupancy, chromatin accessibility, nucleosome positioning and 3D genome organization at the nucleosome resolution. We show that motif recognition on mononucleosomes can decipher only the individual binding of TFs. When bound together, TFs act cooperatively or competitively to target nucleosome arrays with defined 3D organization, displaying motifs in particular patterns. In one combination, motif directionality funnels TF combinatorial binding along chromatin loops, before infiltrating laterally to adjacent enhancers. In other combinations, TFs assemble on motif-dense and highly interconnected loop junctions, and subsequently translocate to nearby lineage-specific sites. We propose a guided-search model in which motif grammar on nucleosome fibres acts as signpost elements, directing TF combinatorial binding to enhancers.

Super-silencer perturbation by EZH2 and REST inhibition leads to large loss of chromatin interactions and reduction in cancer growth

Human silencers have been shown to regulate developmental gene expression. However, the functional importance of human silencers needs to be elucidated, such as whether they can form 'super-silencers' and whether they are linked to cancer progression. Here, we show two silencer components of the FGF18 gene can cooperate through compensatory chromatin interactions to form a super-silencer. Double knockout of two silencers exhibited synergistic upregulation of FGF18 expression and changes in cell identity. To perturb the super-silencers, we applied combinational treatment of an enhancer of zeste homolog 2 inhibitor GSK343, and a repressor element 1-silencing transcription factor inhibitor, X5050 ('GR'). Interestingly, GR led to severe loss of topologically associated domains and loops, which were associated with reduced CTCF and TOP2A mRNA levels. Moreover, GR synergistically upregulated super-silencer-controlled genes related to cell cycle, apoptosis and DNA damage, leading to anticancer effects in vivo. Overall, our data demonstrated a super-silencer example and showed that GR can disrupt super-silencers, potentially leading to cancer ablation.

Three-dimensional regulatory hubs support oncogenic programs in glioblastoma

Dysregulation of enhancer-promoter communication in the context of the three-dimensional (3D) nucleus is increasingly recognized as a potential driver of oncogenic programs. Here, we profiled the 3D enhancer-promoter networks of primary patient-derived glioblastoma stem cells (GSCs) in comparison with neuronal stem cells (NSCs) to identify potential central nodes and vulnerabilities in the regulatory logic of this devastating cancer. Specifically, we focused on hyperconnected 3D regulatory hubs and demonstrated that hub-interacting genes exhibit high and coordinated expression at the single-cell level and strong association with oncogenic programs that distinguish IDH-wt glioblastoma patients from low-grade glioma. Epigenetic silencing of a recurrent 3D enhancer hub-with an uncharacterized role in glioblastoma-was sufficient to cause concordant downregulation of multiple hub-connected genes along with significant shifts in transcriptional states and reduced clonogenicity. By integrating published datasets from other cancer types, we also identified both universal and cancer type-specific 3D regulatory hubs which enrich for varying oncogenic programs and nominate specific factors associated with worse outcomes. Genetic alterations, such as focal duplications, could explain only a small fraction of the detected hyperconnected hubs and their increased activity. Overall, our study provides computational and experimental support for the potential central role of 3D regulatory hubs in controlling oncogenic programs and properties.

HIGHLIGHTS

- 3D regulatory "hubs" in glioblastoma enrich for highly coregulated genes at a single-cell level and expand oncogenic regulatory networks.- Targeted perturbation of a highly recurrent 3D regulatory hub in GSCs results in altered transcriptional states and cellular properties.- 3D regulatory hubs across cancer types associate with tumor-specific and universal oncogenic programs and worse outcomes.- The majority of hyperconnected hubs do not overlap with structural variants, suggesting epigenetic mechanisms.

eTOC

Here we profile the 3D enhancer connectomes of primary patient-derived human glioblastoma stem cells (GSCs), identify hyperconnected 3D regulatory "hubs", and examine the impact of 3D hub perturbation on the transcriptional program and oncogenic properties.

E-box independent chromatin recruitment turns MYOD into a transcriptional repressor

MYOD is an E-box sequence-specific basic Helix-Loop-Helix (bHLH) transcriptional activator that, when expressed in non-muscle cells, induces nuclear reprogramming toward skeletal myogenesis by promoting chromatin accessibility at previously silent loci. Here, we report on the identification of a previously unrecognized property of MYOD as repressor of gene expression, via E-box-independent chromatin binding within accessible genomic elements, which invariably leads to reduced chromatin accessibility. MYOD-mediated repression requires the integrity of functional domains previously implicated in MYOD-mediated activation of gene expression. Repression of mitogen- and growth factor-responsive genes occurs through promoter binding and requires a highly conserved domain within the first helix. Repression of cell-of-origin/alternative lineage genes occurs via binding and decommissioning of distal regulatory elements, such as super-enhancers (SE), which requires the N-terminal activation domain as well as two chromatin-remodeling domains and leads to reduced strength of CTCF-mediated chromatin interactions. Surprisingly, MYOD-mediated chromatin compaction and repression of transcription do not associate with reduction of H3K27ac, the conventional histone mark of enhancer or promoter activation, but with reduced levels of the recently discovered histone H4 acetyl-methyl lysine modification (Kacme). These results extend MYOD biological properties beyond the current dogma that restricts MYOD function to a monotone transcriptional activator and reveal a previously unrecognized functional versatility arising from an alternative chromatin recruitment through E-box or non-E-box sequences. The E-box independent repression of gene expression by MYOD might provide a promiscuous mechanism to reduce chromatin accessibility and repress cell-of-origin/alternative lineage and growth factor/mitogen-responsive genes to safeguard the integrity of cell identity during muscle progenitor commitment toward the myogenic lineage.

TAD-dependent sub-TAD is required for enhancer-promoter interaction enabling the β-globin transcription

Topologically associating domains (TADs) are chromatin domains in the eukaryotic genome. TADs often comprise several sub-TADs. The boundaries of TADs and sub-TADs are enriched in CTCF, an architectural protein. Deletion of CTCF-binding motifs at one boundary disrupts the domains, often resulting in a transcriptional decrease in genes inside the domains. However, it is not clear how TAD and sub-TAD affect each other in the domain formation. Unaffected gene transcription was observed in the β-globin locus when one boundary of TAD or sub-TAD was destroyed. Here, we disrupted β-globin TAD and sub-TAD by deleting CTCF motifs at both boundaries in MEL/ch11 cells. Disruption of TAD impaired sub-TAD, but sub-TAD disruption did not affect TAD. Both TAD and sub-TAD disruption compromised the β-globin transcription, accompanied by the loss of enhancer-promoter interactions. However, histone H3 occupancy and H3K27ac were largely maintained across the β-globin locus. Genome-wide analysis showed that putative enhancer-promoter interactions and gene transcription were decreased by the disruption of CTCF-mediated topological domains in neural progenitor cells. Collectively, our results indicate that there is unequal relationship between TAD and sub-TAD formation. TAD is likely not sufficient for gene transcription, and, therefore, sub-TAD appears to be required. TAD-dependently formed sub-TADs are considered to provide chromatin environments for enhancer-promoter interactions enabling gene transcription.

Functional characteristics and computational model of abundant hyperactive loci in the human genome

Enhancers and promoters are classically considered to be bound by a small set of transcription factors (TFs) in a sequence-specific manner. This assumption has come under increasing skepticism as the datasets of ChIP-seq assays of TFs have expanded. In particular, high-occupancy target (HOT) loci attract hundreds of TFs with often no detectable correlation between ChIP-seq peaks and DNA-binding motif presence. Here, we used a set of 1003 TF ChIP-seq datasets (HepG2, K562, H1) to analyze the patterns of ChIP-seq peak co-occurrence in combination with functional genomics datasets. We identified 43,891 HOT loci forming at the promoter (53%) and enhancer (47%) regions. HOT promoters regulate housekeeping genes, whereas HOT enhancers are involved in tissue-specific process regulation. HOT loci form the foundation of human super-enhancers and evolve under strong negative selection, with some of these loci being located in ultraconserved regions. Sequence-based classification analysis of HOT loci suggested that their formation is driven by the sequence features, and the density of mapped ChIP-seq peaks across TF-bound loci correlates with sequence features and the expression level of flanking genes. Based on the affinities to bind to promoters and enhancers we detected five distinct clusters of TFs that form the core of the HOT loci. We report an abundance of HOT loci in the human genome and a commitment of 51% of all TF ChIP-seq binding events to HOT locus formation thus challenging the classical model of enhancer activity and propose a model of HOT locus formation based on the existence of large transcriptional condensates.

Single cell variant to enhancer to gene map for coronary artery disease

Although genome wide association studies (GWAS) in large populations have identified hundreds of variants associated with common diseases such as coronary artery disease (CAD), most disease-associated variants lie within non-coding regions of the genome, rendering it difficult to determine the downstream causal gene and cell type. Here, we performed paired single nucleus gene expression and chromatin accessibility profiling from 44 human coronary arteries. To link disease variants to molecular traits, we developed a meta-map of 88 samples and discovered 11,182 single-cell chromatin accessibility quantitative trait loci (caQTLs). Heritability enrichment analysis and disease variant mapping demonstrated that smooth muscle cells (SMCs) harbor the greatest genetic risk for CAD. To capture the continuum of SMC cell states in disease, we used dynamic single cell caQTL modeling for the first time in tissue to uncover QTLs whose effects are modified by cell state and expand our insight into genetic regulation of heterogenous cell populations. Notably, we identified a variant in the COL4A1/COL4A2 CAD GWAS locus which becomes a caQTL as SMCs de-differentiate by changing a transcription factor binding site for EGR1/2. To unbiasedly prioritize functional candidate genes, we built a genome-wide single cell variant to enhancer to gene (scV2E2G) map for human CAD to link disease variants to causal genes in cell types. Using this approach, we found several hundred genes predicted to be linked to disease variants in different cell types. Next, we performed genome-wide Hi-C in 16 human coronary arteries to build tissue specific maps of chromatin conformation and link disease variants to integrated chromatin hubs and distal target genes. Using this approach, we show that rs4887091 within the ADAMTS7 CAD GWAS locus modulates function of a super chromatin interactome through a change in a CTCF binding site. Finally, we used CRISPR interference to validate a distal gene, AMOTL2, liked to a CAD GWAS locus. Collectively we provide a disease-agnostic framework to translate human genetic findings to identify pathologic cell states and genes driving disease, producing a comprehensive scV2E2G map with genetic and tissue level convergence for future mechanistic and therapeutic studies.

A Bioconductor/R Workflow for the Detection and Visualization of Differential Chromatin Loops

Background

Chromatin loops play a critical role in gene regulation by connecting regulatory loci and gene promoters. The identification of changes in chromatin looping between cell types or biological conditions is an important task for understanding gene regulation; however, the manipulation, statistical analysis, and visualization of data sets describing 3D chromatin structure is challenging due to the large and complex nature of the relevant data sets.

Methods

Here, we describe a workflow for identifying and visualizing differential chromatin loops from Hi-C data from two biological conditions using the 'mariner', 'DESeq2' and 'plotgardener' Bioconductor/R packages. The workflow assumes that Hi-C data has been processed into '.hic' or '.cool' files and that loops have been identified using an existing loop-calling algorithm.

Results

First, the 'mariner' package is used to merge redundant loop calls and extract interaction frequency counts. Next, 'DESeq2' is used to identify loops that exhibit differential contact frequencies between conditions. Finally, 'plotgardener' is used to visualize differential loops.

Conclusion

Chromatin interaction data is an important modality for understanding the mechanisms of transcriptional regulation. The workflow presented here outlines the use of 'mariner' as a tool to manipulate, extract, and aggregate chromatin interaction data, 'DESeq2' to perform differential analysis of these data across conditions, samples, and replicates, and 'plotgardener' to explore and visualize the results.

Decoding the epigenetics and chromatin loop dynamics of androgen receptor-mediated transcription

Androgen receptor (AR)-mediated transcription plays a critical role in development and prostate cancer growth. AR drives gene expression by binding to thousands of cis-regulatory elements (CRE) that loop to hundreds of target promoters. With multiple CREs interacting with a single promoter, it remains unclear how individual AR bound CREs contribute to gene expression. To characterize the involvement of these CREs, we investigate the AR-driven epigenetic and chromosomal chromatin looping changes by generating a kinetic multi-omic dataset comprised of steady-state mRNA, chromatin accessibility, transcription factor binding, histone modifications, chromatin looping, and nascent RNA. Using an integrated regulatory network, we find that AR binding induces sequential changes in the epigenetic features at CREs, independent of gene expression. Further, we show that binding of AR does not result in a substantial rewiring of chromatin loops, but instead increases the contact frequency of pre-existing loops to target promoters. Our results show that gene expression strongly correlates to the changes in contact frequency. We then propose and experimentally validate an unbalanced multi-enhancer model where the impact on gene expression of AR-bound enhancers is heterogeneous, and is proportional to their contact frequency with target gene promoters. Overall, these findings provide insights into AR-mediated gene expression upon acute androgen simulation and develop a mechanistic framework to investigate nuclear receptor mediated perturbations.

GEEES: inferring cell-specific gene-enhancer interactions from multi-modal single-cell data

MOTIVATION

Gene-enhancer interactions are central to transcriptional regulation. Current multi-modal single-cell datasets that profile transcriptome and chromatin accessibility simultaneously in a single cell are yielding opportunities to infer gene-enhancer associations in a cell type specific manner. Computational efforts for such multi-modal single-cell datasets thus far focused on methods for identification and refinement of cell types and trajectory construction. While initial attempts for inferring gene-enhancer interactions have emerged, these have not been evaluated against benchmark datasets that materialized from bulk genomic experiments. Furthermore, existing approaches are limited to inferring gene-enhancer associations at the level of grouped cells as opposed to individual cells, thereby ignoring regulatory heterogeneity among the cells.

RESULTS

We present a new approach, GEEES for "Gene EnhancEr IntEractions from Multi-modal Single Cell Data," for inferring gene-enhancer associations at the single-cell level using multi-modal single-cell transcriptome and chromatin accessibility data. We evaluated GEEES alongside several multivariate regression-based alternatives we devised and state-of-the-art methods using a large number of benchmark datasets, providing a comprehensive assessment of current approaches. This analysis revealed significant discrepancies between gold-standard interactions and gene-enhancer associations derived from multi-modal single-cell data. Notably, incorporating gene-enhancer distance into the analysis markedly improved performance across all methods, positioning GEEES as a leading approach in this domain. While the overall improvement in performance metrics by GEEES is modest, it provides enhanced cell representation learning which can be leveraged for more effective downstream analysis. Furthermore, our review of existing experimentally driven benchmark datasets uncovers their limited concordance, underscoring the necessity for new high-throughput experiments to validate gene-enhancer interactions inferred from single-cell data.

AVAILABILITY AND IMPLEMENTATION

https://github.com/keleslab/GEEES.

Epigenetic Explorations of Neurological Disorders, the Identification Methods, and Therapeutic Avenues

Neurodegenerative disorders are major health concerns globally, especially in aging societies. The exploration of brain epigenomes, which consist of multiple forms of DNA methylation and covalent histone modifications, offers new and unanticipated perspective into the mechanisms of aging and neurodegenerative diseases. Initially, chromatin defects in the brain were thought to be static abnormalities from early development associated with rare genetic syndromes. However, it is now evident that mutations and the dysregulation of the epigenetic machinery extend across a broader spectrum, encompassing adult-onset neurodegenerative diseases. Hence, it is crucial to develop methodologies that can enhance epigenetic research. Several approaches have been created to investigate alterations in epigenetics on a spectrum of scales-ranging from low to high-with a particular focus on detecting DNA methylation and histone modifications. This article explores the burgeoning realm of neuroepigenetics, emphasizing its role in enhancing our mechanistic comprehension of neurodegenerative disorders and elucidating the predominant techniques employed for detecting modifications in the epigenome. Additionally, we ponder the potential influence of these advancements on shaping future therapeutic approaches.

The impact of the embryonic DNA methylation program on CTCF-mediated genome regulation

During mammalian embryogenesis, both the 5-cytosine DNA methylation (5meC) landscape and three dimensional (3D) chromatin architecture are profoundly remodeled during a process known as 'epigenetic reprogramming.' An understudied aspect of epigenetic reprogramming is how the 5meC flux, per se, affects the 3D genome. This is pertinent given the 5meC-sensitivity of DNA binding for a key regulator of chromosome folding: CTCF. We profiled the CTCF binding landscape using a mouse embryonic stem cell (ESC) differentiation protocol that models embryonic 5meC dynamics. Mouse ESCs lacking DNA methylation machinery are able to exit naive pluripotency, thus allowing for dissection of subtle effects of CTCF on gene expression. We performed CTCF HiChIP in both wild-type and mutant conditions to assess gained CTCF-CTCF contacts in the absence of 5meC. We performed H3K27ac HiChIP to determine the impact that ectopic CTCF binding has on cis-regulatory contacts. Using 5meC epigenome editing, we demonstrated that the methyl-mark is able to impair CTCF binding at select loci. Finally, a detailed dissection of the imprinted Zdbf2 locus showed how 5meC-antagonism of CTCF allows for proper gene regulation during differentiation. This work provides a comprehensive overview of how 5meC impacts the 3D genome in a relevant model for early embryonic events.

A systematic analyses of different bioinformatics pipelines for genomic data and its impact on deep learning models for chromatin loop prediction

Genomic data analysis has witnessed a surge in complexity and volume, primarily driven by the advent of high-throughput technologies. In particular, studying chromatin loops and structures has become pivotal in understanding gene regulation and genome organization. This systematic investigation explores the realm of specialized bioinformatics pipelines designed specifically for the analysis of chromatin loops and structures. Our investigation incorporates two protein (CTCF and Cohesin) factor-specific loop interaction datasets from six distinct pipelines, amassing a comprehensive collection of 36 diverse datasets. Through a meticulous review of existing literature, we offer a holistic perspective on the methodologies, tools and algorithms underpinning the analysis of this multifaceted genomic feature. We illuminate the vast array of approaches deployed, encompassing pivotal aspects such as data preparation pipeline, preprocessing, statistical features and modelling techniques. Beyond this, we rigorously assess the strengths and limitations inherent in these bioinformatics pipelines, shedding light on the interplay between data quality and the performance of deep learning models, ultimately advancing our comprehension of genomic intricacies.

Cell-type-specific mapping of enhancers and target genes from single-cell multimodal data

Mapping enhancers and target genes in disease-related cell types has provided critical insights into the functional mechanisms of genetic variants identified by genome-wide association studies (GWAS). However, most existing analyses rely on bulk data or cultured cell lines, which may fail to identify cell-type-specific enhancers and target genes. Recently, single-cell multimodal data measuring both gene expression and chromatin accessibility within the same cells have enabled the inference of enhancer-gene pairs in a cell-type-specific and context-specific manner. However, this task is challenged by the data's high sparsity, sequencing depth variation, and the computational burden of analyzing a large number of enhancer-gene pairs. To address these challenges, we propose scMultiMap, a statistical method that infers enhancer-gene association from sparse multimodal counts using a joint latent-variable model. It adjusts for technical confounding, permits fast moment-based estimation and provides analytically derived p -values. In systematic analyses of blood and brain data, scMultiMap shows appropriate type I error control, high statistical power with greater reproducibility across independent datasets and stronger consistency with orthogonal data modalities. Meanwhile, its computational cost is less than 1% of existing methods. When applied to single-cell multimodal data from postmortem brain samples from Alzheimer's disease (AD) patients and controls, scMultiMap gave the highest heritability enrichment in microglia and revealed new insights into the regulatory mechanisms of AD GWAS variants in microglia.

Large-scale multi-omic analysis identifies noncoding somatic driver mutations and nominates ZFP36L2 as a driver gene for pancreatic ductal adenocarcinoma

Identification of somatic driver mutations in the noncoding genome remains challenging. To comprehensively characterize noncoding driver mutations for pancreatic ductal adenocarcinoma (PDAC), we first created genome-scale maps of accessible chromatin regions (ACRs) and histone modification marks (HMMs) in pancreatic cell lines and purified pancreatic acinar and duct cells. Integration with whole-genome mutation calls from 506 PDACs revealed 314 ACRs/HMMs significantly enriched with 3,614 noncoding somatic mutations (NCSMs). Functional assessment using massively parallel reporter assays (MPRA) identified 178 NCSMs impacting reporter activity (19.45% of those tested). Focused luciferase validation confirmed negative effects on gene regulatory activity for NCSMs near CDKN2A and ZFP36L2. For the latter, CRISPR interference (CRISPRi) further identified ZFP36L2 as a target gene (16.0 - 24.0% reduced expression, P = 0.023-0.0047) with disrupted KLF9 binding likely mediating the effect. Our integrative approach provides a catalog of potentially functional noncoding driver mutations and nominates ZFP36L2 as a PDAC driver gene.

Integration of CTCF loops, methylome, and transcriptome in differentiating LUHMES as a model for imprinting dynamics of the 15q11-q13 locus in human neurons

Human cell line models, including the neuronal precursor line LUHMES, are important for investigating developmental transcriptional dynamics within imprinted regions, particularly the 15q11-q13 Angelman (AS) and Prader-Willi (PWS) syndrome locus. AS results from loss of maternal UBE3A in neurons, where the paternal allele is silenced by a convergent antisense transcript UBE3A-ATS, a lncRNA that terminates at PWAR1 in non-neurons. qRT-PCR analysis confirmed the exclusive and progressive increase in UBE3A-ATS in differentiating LUHMES neurons, validating their use for studying UBE3A silencing. Genome-wide transcriptome analyses revealed changes to 11 834 genes during neuronal differentiation, including the upregulation of most genes within the 15q11-q13 locus. To identify dynamic changes in chromatin loops linked to transcriptional activity, we performed a HiChIP validated by 4C, which identified two neuron-specific CTCF loops between MAGEL2-SNRPN and PWAR1-UBE3A. To determine if allele-specific differentially methylated regions (DMR) may be associated with CTCF loop anchors, whole genome long-read nanopore sequencing was performed. We identified a paternally hypomethylated DMR near the SNRPN upstream loop anchor exclusive to neurons and a paternally hypermethylated DMR near the PWAR1 CTCF anchor exclusive to undifferentiated cells, consistent with increases in neuronal transcription. Additionally, DMRs near CTCF loop anchors were observed in both cell types, indicative of allele-specific differences in chromatin loops regulating imprinted transcription. These results provide an integrated view of the 15q11-q13 epigenetic landscape during LUHMES neuronal differentiation, underscoring the complex interplay of transcription, chromatin looping, and DNA methylation. They also provide insights for future therapeutic approaches for AS and PWS.

Identifying genetic variants associated with chromatin looping and genome function

Here we present a comprehensive HiChIP dataset on naïve CD4 T cells (nCD4) from 30 donors and identify QTLs that associate with genotype-dependent and/or allele-specific variation of HiChIP contacts defining loops between active regulatory regions (iQTLs). We observe a substantial overlap between iQTLs and previously defined eQTLs and histone QTLs, and an enrichment for fine-mapped QTLs and GWAS variants. Furthermore, we describe a distinct subset of nCD4 iQTLs, for which the significant variation of chromatin contacts in nCD4 are translated into significant eQTL trends in CD4 T cell memory subsets. Finally, we define connectivity-QTLs as iQTLs that are significantly associated with concordant genotype-dependent changes in chromatin contacts over a broad genomic region (e.g., GWAS SNP in the RNASET2 locus). Our results demonstrate the importance of chromatin contacts as a complementary modality for QTL mapping and their power in identifying previously uncharacterized QTLs linked to cell-specific gene expression and connectivity.

Enhancer-promoter hubs organize transcriptional networks promoting oncogenesis and drug resistance

Recent advances in high-resolution mapping of spatial interactions among regulatory elements support the existence of complex topological assemblies of enhancers and promoters known as enhancer-promoter hubs or cliques. Yet, organization principles of these multi-interacting enhancer-promoter hubs and their potential role in regulating gene expression in cancer remain unclear. Here, we systematically identify enhancer-promoter hubs in breast cancer, lymphoma, and leukemia. We find that highly interacting enhancer-promoter hubs form at key oncogenes and lineage-associated transcription factors potentially promoting oncogenesis of these diverse cancer types. Genomic and optical mapping of interactions among enhancer and promoter elements further show that topological alterations in hubs coincide with transcriptional changes underlying acquired resistance to targeted therapy in T cell leukemia and B cell lymphoma. Together, our findings suggest that enhancer-promoter hubs are dynamic and heterogeneous topological assemblies with the potential to control gene expression circuits promoting oncogenesis and drug resistance.

Predictive Prioritization of Enhancers Associated with Pancreas Disease Risk

Genetic and epigenetic variations in regulatory enhancer elements increase susceptibility to a range of pathologies. Despite recent advances, linking enhancer elements to target genes and predicting transcriptional outcomes of enhancer dysfunction remain significant challenges. Using 3D chromatin conformation assays, we generated an extensive enhancer interaction dataset for the human pancreas, encompassing more than 20 donors and five major cell types, including both exocrine and endocrine compartments. We employed a network approach to parse chromatin interactions into enhancer-promoter tree models, facilitating a quantitative, genome-wide analysis of enhancer connectivity. With these tree models, we developed a machine learning algorithm to estimate the impact of enhancer perturbations on cell type-specific gene expression in the human pancreas. Orthogonal to our computational approach, we perturbed enhancer function in primary human pancreas cells using CRISPR interference and quantified the effects at the single-cell level through RNA FISH coupled with high-throughput imaging. Our enhancer tree models enabled the annotation of common germline risk variants associated with pancreas diseases, linking them to putative target genes in specific cell types. For pancreatic ductal adenocarcinoma, we found a stronger enrichment of disease susceptibility variants within acinar cell regulatory elements, despite ductal cells historically being assumed as the primary cell-of-origin. Our integrative approach-combining cell type-specific enhancer-promoter interaction mapping, computational models, and single-cell enhancer perturbation assays-produced a robust resource for studying the genetic basis of pancreas disorders.

Improved simultaneous mapping of epigenetic features and 3D chromatin structure via ViCAR

Methods to measure chromatin contacts at genomic regions bound by histone modifications or proteins are important tools to investigate chromatin organization. However, such methods do not capture the possible involvement of other epigenomic features such as G-quadruplex DNA secondary structures (G4s). To bridge this gap, we introduce ViCAR (viewpoint HiCAR), for the direct antibody-based capture of chromatin interactions at folded G4s. Through ViCAR, we showcase the first G4-3D interaction landscape. Using histone marks, we also demonstrate how ViCAR improves on earlier approaches yielding increased signal-to-noise. ViCAR is a practical and powerful tool to explore epigenetic marks and 3D genome interactomes.

GenomicLinks: deep learning predictions of 3D chromatin interactions in the maize genome

Gene regulation in eukaryotes is partly shaped by the 3D organization of chromatin within the cell nucleus. Distal interactions between cis-regulatory elements and their target genes are widespread, and many causal loci underlying heritable agricultural traits have been mapped to distal non-coding elements. The biology underlying chromatin loop formation in plants is poorly understood. Dissecting the sequence features that mediate distal interactions is an important step toward identifying putative molecular mechanisms. Here, we trained GenomicLinks, a deep learning model, to identify DNA sequence features predictive of 3D chromatin interactions in maize. We found that the presence of binding motifs of specific transcription factor classes, especially bHLH, is predictive of chromatin interaction specificities. Using an in silico mutagenesis approach we show the removal of these motifs from loop anchors leads to reduced interaction probabilities. We were able to validate these predictions with single-cell co-accessibility data from different maize genotypes that harbor natural substitutions in these TF binding motifs. GenomicLinks is currently implemented as an open-source web tool, which should facilitate its wider use in the plant research community.

SnapHiC-G: identifying long-range enhancer-promoter interactions from single-cell Hi-C data via a global background model

Harnessing the power of single-cell genomics technologies, single-cell Hi-C (scHi-C) and its derived technologies provide powerful tools to measure spatial proximity between regulatory elements and their target genes in individual cells. Using a global background model, we propose SnapHiC-G, a computational method, to identify long-range enhancer-promoter interactions from scHi-C data. We applied SnapHiC-G to scHi-C datasets generated from mouse embryonic stem cells and human brain cortical cells. SnapHiC-G achieved high sensitivity in identifying long-range enhancer-promoter interactions. Moreover, SnapHiC-G can identify putative target genes for noncoding genome-wide association study (GWAS) variants, and the genetic heritability of neuropsychiatric diseases is enriched for single-nucleotide polymorphisms (SNPs) within SnapHiC-G-identified interactions in a cell-type-specific manner. In sum, SnapHiC-G is a powerful tool for characterizing cell-type-specific enhancer-promoter interactions from complex tissues and can facilitate the discovery of chromatin interactions important for gene regulation in biologically relevant cell types.

Beyond the Chromosome: Recent Developments in Decoding the Significance of Extrachromosomal Circular DNA (eccDNA) in Human Malignancies

Extrachromosomal circular DNA (eccDNA) is a form of a circular double-stranded DNA that exists independently of conventional chromosomes. eccDNA exhibits a broad and random distribution across eukaryotic cells and has been associated with tumor-related properties due to its ability to harbor the complete gene information of oncogenes. The complex and multifaceted mechanisms underlying eccDNA formation include pathways such as DNA damage repair, breakage-fusion-bridge (BFB) mechanisms, chromothripsis, and cell apoptosis. Of note, eccDNA plays a pivotal role in tumor development, genetic heterogeneity, and therapeutic resistance. The high copy number and transcriptional activity of oncogenes carried by eccDNA contribute to the accelerated growth of tumors. Notably, the amplification of oncogenes on eccDNA is implicated in the malignant progression of cancer cells. The improvement of high-throughput sequencing techniques has greatly enhanced our knowledge of eccDNA by allowing for a detailed examination of its genetic structures and functions. However, we still lack a comprehensive and efficient annotation for eccDNA, while challenges persist in the study and understanding of the functional role of eccDNA, emphasizing the need for the development of robust methodologies. The potential clinical applications of eccDNA, such as its role as a measurable biomarker or therapeutic target in diseases, particularly within the spectrum of human malignancies, is a promising field for future research. In conclusion, eccDNA represents a quite dynamic and multifunctional genetic entity with far-reaching implications in cancer pathogenesis and beyond. Further research is essential to unravel the molecular pathways of eccDNA formation, elucidate its functional roles, and explore its clinical applications. Addressing these aspects is crucial for advancing our understanding of genomic instability and developing novel strategies for tailored therapeutics, especially in cancer.

MethNet: a robust approach to identify regulatory hubs and their distal targets from cancer data

Aberrations in the capacity of DNA/chromatin modifiers and transcription factors to bind non-coding regions can lead to changes in gene regulation and impact disease phenotypes. However, identifying distal regulatory elements and connecting them with their target genes remains challenging. Here, we present MethNet, a pipeline that integrates large-scale DNA methylation and gene expression data across multiple cancers, to uncover cis regulatory elements (CREs) in a 1 Mb region around every promoter in the genome. MethNet identifies clusters of highly ranked CREs, referred to as 'hubs', which contribute to the regulation of multiple genes and significantly affect patient survival. Promoter-capture Hi-C confirmed that highly ranked associations involve physical interactions between CREs and their gene targets, and CRISPR interference based single-cell RNA Perturb-seq validated the functional impact of CREs. Thus, MethNet-identified CREs represent a valuable resource for unraveling complex mechanisms underlying gene expression, and for prioritizing the verification of predicted non-coding disease hotspots.

TWEAK/Fn14 signalling driven super-enhancer reprogramming promotes pro-metastatic metabolic rewiring in triple-negative breast cancer

Triple Negative Breast Cancer (TNBC) is the most aggressive breast cancer subtype suffering from limited targeted treatment options. Following recent reports correlating Fibroblast growth factor-inducible 14 (Fn14) receptor overexpression in Estrogen Receptor (ER)-negative breast cancers with metastatic events, we show that Fn14 is specifically overexpressed in TNBC patients and associated with poor survival. We demonstrate that constitutive Fn14 signalling rewires the transcriptomic and epigenomic landscape of TNBC, leading to enhanced tumour growth and metastasis. We further illustrate that such mechanisms activate TNBC-specific super enhancers (SE) to drive the transcriptional activation of cancer dependency genes via chromatin looping. In particular, we uncover the SE-driven upregulation of Nicotinamide phosphoribosyltransferase (NAMPT), which promotes NAD+ and ATP metabolic reprogramming critical for filopodia formation and metastasis. Collectively, our study details the complex mechanistic link between TWEAK/Fn14 signalling and TNBC metastasis, which reveals several vulnerabilities which could be pursued for the targeted treatment of TNBC patients.

Enhancer-promoter hubs organize transcriptional networks promoting oncogenesis and drug resistance

Recent advances in high-resolution mapping of spatial interactions among regulatory elements support the existence of complex topological assemblies of enhancers and promoters known as enhancer-promoter hubs or cliques. Yet, organization principles of these multi-interacting enhancer-promoter hubs and their potential role in regulating gene expression in cancer remains unclear. Here, we systematically identified enhancer-promoter hubs in breast cancer, lymphoma, and leukemia. We found that highly interacting enhancer-promoter hubs form at key oncogenes and lineage-associated transcription factors potentially promoting oncogenesis of these diverse cancer types. Genomic and optical mapping of interactions among enhancer and promoter elements further showed that topological alterations in hubs coincide with transcriptional changes underlying acquired resistance to targeted therapy in T cell leukemia and B cell lymphoma. Together, our findings suggest that enhancer-promoter hubs are dynamic and heterogeneous topological assemblies with the potential to control gene expression circuits promoting oncogenesis and drug resistance.

Evolutionary conservation of VSX2 super-enhancer modules in retinal development

Super-enhancers (SEs) are expansive regions of genomic DNA that regulate the expression of genes involved in cell identity and cell fate. We recently identified developmental stage- and cell type-specific modules within the murine Vsx2 SE. Here, we show that the human VSX2 SE modules have similar developmental stage- and cell type-specific activity in reporter gene assays. By inserting the human sequence of one VSX2 SE module into a mouse with microphthalmia, eye size was rescued. To understand the function of these SE modules during human retinal development, we deleted individual modules in human embryonic stem cells and generated retinal organoids. Deleting one module results in small organoids, recapitulating the small-eyed phenotype of mice with microphthalmia, while deletion of the other module led to disruptions in bipolar neuron development. This prototypical SE serves as a model for understanding developmental stage- and cell type-specific effects of neurogenic transcription factors with complex expression patterns. Moreover, by elucidating the gene regulatory mechanisms, we can begin to examine how dysregulation of these mechanisms contributes to phenotypic diversity and disease.

Cell type- and transcription-independent spatial proximity between enhancers and promoters

Cell type-specific enhancers are critically important for lineage specification. The mechanisms that determine cell-type specificity of enhancer activity, however, are not fully understood. Most current models for how enhancers function invoke physical proximity between enhancer elements and their target genes. Here, we use an imaging-based approach to examine the spatial relationship of cell type-specific enhancers and their target genes with single-cell resolution. Using high-throughput microscopy, we measure the spatial distance from target promoters to their cell type-specific active and inactive enhancers in individual pancreatic cells derived from distinct lineages. We find increased proximity of all promoter-enhancer pairs relative to non-enhancer pairs separated by similar genomic distances. Strikingly, spatial proximity between enhancers and target genes was unrelated to tissue-specific enhancer activity. Furthermore, promoter-enhancer proximity did not correlate with the expression status of target genes. Our results suggest that promoter-enhancer pairs exist in a distinctive chromatin environment but that genome folding is not a universal driver of cell-type specificity in enhancer function.

Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions

To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five histotype-specific EOC risk regions (p value <5 × 10-8) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (p value <10-5). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue datasets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (false discovery rate <0.05). Finally, by integrating genome-wide HiChIP interactome analysis with transcriptome-wide association study (TWAS), variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8, and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by a genome-wide association study.

Integrated enhancer regulatory network by enhancer-promoter looping in gastric cancer

Enhancer cis-regulatory elements play critical roles in gene regulation at many stages of cell growth. Enhancers in cancer cells also regulate the transcription of oncogenes. In this study, we performed a comprehensive analysis of long-range chromatin interactions, histone modifications, chromatin accessibility and expression in two gastric cancer (GC) cell lines compared to normal gastric epithelial cells. We found that GC-specific enhancers marked by histone modifications can activate a population of genes, including some oncogenes, by interacting with their proximal promoters. In addition, motif analysis of enhancer-promoter interacting enhancers showed that GC-specific transcription factors are enriched. Among them, we found that MYB is crucial for GC cell growth and activated by the enhancer with an enhancer-promoter loop and TCF7 upregulation. Clinical GC samples showed epigenetic activation of enhancers at the MYB locus and significant upregulation of TCF7 and MYB, regardless of molecular GC subtype and clinicopathological factors. Single-cell RNA sequencing of gastric mucosa with intestinal metaplasia showed high expression of TCF7 and MYB in intestinal stem cells. When we inactivated the loop-forming enhancer at the MYB locus using CRISPR interference (dCas9-KRAB), GC cell growth was significantly inhibited. In conclusion, we identified MYB as an oncogene activated by a loop-forming enhancer and contributing to GC cell growth.

Human cytomegalovirus infection coopts chromatin organization to diminish TEAD1 transcription factor activity

Human cytomegalovirus (HCMV) infects up to 80% of the world's population. Here, we show that HCMV infection leads to widespread changes in human chromatin accessibility and chromatin looping, with hundreds of thousands of genomic regions affected 48 hours after infection. Integrative analyses reveal HCMV-induced perturbation of Hippo signaling through drastic reduction of TEAD1 transcription factor activity. We confirm extensive concordant loss of TEAD1 binding, active H3K27ac histone marks, and chromatin looping interactions upon infection. Our data position TEAD1 at the top of a hierarchy involving multiple altered important developmental pathways. HCMV infection reduces TEAD1 activity through four distinct mechanisms: closing of TEAD1-bound chromatin, reduction of YAP1 and phosphorylated YAP1 levels, reduction of TEAD1 transcript and protein levels, and alteration of TEAD1 exon-6 usage. Altered TEAD1-based mechanisms are highly enriched at genetic risk loci associated with eye and ear development, providing mechanistic insight into HCMV's established roles in these processes.

Comparative 3D genome analysis between neural retina and retinal pigment epithelium reveals differential cis-regulatory interactions at retinal disease loci

BACKGROUND

Vision depends on the interplay between photoreceptor cells of the neural retina and the underlying retinal pigment epithelium (RPE). Most genes involved in inherited retinal diseases display specific spatiotemporal expression within these interconnected retinal components through the local recruitment of cis-regulatory elements (CREs) in 3D nuclear space.

RESULTS

To understand the role of differential chromatin architecture in establishing tissue-specific expression at inherited retinal disease loci, we mapped genome-wide chromatin interactions using in situ Hi-C and H3K4me3 HiChIP on neural retina and RPE/choroid from human adult donor eyes. We observed chromatin looping between active promoters and 32,425 and 8060 candidate CREs in the neural retina and RPE/choroid, respectively. A comparative 3D genome analysis between these two retinal tissues revealed that 56% of 290 known inherited retinal disease genes were marked by differential chromatin interactions. One of these was ABCA4, which is implicated in the most common autosomal recessive inherited retinal disease. We zoomed in on retina- and RPE-specific cis-regulatory interactions at the ABCA4 locus using high-resolution UMI-4C. Integration with bulk and single-cell epigenomic datasets and in vivo enhancer assays in zebrafish revealed tissue-specific CREs interacting with ABCA4.

CONCLUSIONS

Through comparative 3D genome mapping, based on genome-wide, promoter-centric, and locus-specific assays of human neural retina and RPE, we have shown that gene regulation at key inherited retinal disease loci is likely mediated by tissue-specific chromatin interactions. These findings do not only provide insight into tissue-specific regulatory landscapes at retinal disease loci, but also delineate the search space for non-coding genomic variation underlying unsolved inherited retinal diseases.

Hi-Tag: a simple and efficient method for identifying protein-mediated long-range chromatin interactions with low cell numbers

Protein-mediated chromatin interactions can be revealed by coupling proximity-based ligation with chromatin immunoprecipitation. However, these techniques require complex experimental procedures and millions of cells per experiment, which limits their widespread application in life science research. Here, we develop a novel method, Hi-Tag, that identifies high-resolution, long-range chromatin interactions through transposase tagmentation and chromatin proximity ligation (with a phosphorothioate-modified linker). Hi-Tag can be implemented using as few as 100,000 cells, involving simple experimental procedures that can be completed within 1.5 days. Meanwhile, Hi-Tag is capable of using its own data to identify the binding sites of specific proteins, based on which, it can acquire accurate interaction information. Our results suggest that Hi-Tag has great potential for advancing chromatin interaction studies, particularly in the context of limited cell availability.

Loop Catalog: a comprehensive HiChIP database of human and mouse samples

HiChIP enables cost-effective and high-resolution profiling of regulatory and structural loops. To leverage the increasing number of publicly available HiChIP datasets from diverse cell lines and primary cells, we developed the Loop Catalog (https://loopcatalog.lji.org), a web-based database featuring HiChIP loop calls for 1319 samples across 133 studies and 44 high-resolution Hi-C loop calls. We demonstrate its utility in interpreting fine-mapped GWAS variants (SNP-to-gene linking), in identifying enriched sequence motifs and motif pairs at loop anchors, and in network-level analysis of loops connecting regulatory elements (community detection). Our comprehensive catalog, spanning over 4M unique 5kb loops, along with the accompanying analysis modalities constitutes an important resource for studies in gene regulation and genome organization.

Rewiring of the epigenome and chromatin architecture by exogenously induced retinoic acid signaling during zebrafish embryonic development

Retinoic acid (RA) is the ligand of RA receptors (RARs), transcription factors that bind to RA response elements. RA signaling is required for multiple processes during embryonic development, including body axis extension, hindbrain antero-posterior patterning and forelimb bud initiation. Although some RA target genes have been identified, little is known about the genome-wide effects of RA signaling during in vivo embryonic development. Here, we stimulate the RA pathway by treating zebrafish embryos with all-trans-RA (atRA) and use a combination of RNA-seq, ATAC-seq, ChIP-seq and HiChIP to gain insight into the molecular mechanisms by which exogenously induced RA signaling controls gene expression. We find that RA signaling is involved in anterior/posterior patterning, central nervous system development, and the transition from pluripotency to differentiation. AtRA treatment also alters chromatin accessibility during early development and promotes chromatin binding of RARαa and the RA targets Hoxb1b, Meis2b and Sox3, which cooperate in central nervous system development. Finally, we show that exogenous RA induces a rewiring of chromatin architecture, with alterations in chromatin 3D interactions involving target genes. Altogether, our findings identify genome-wide targets of RA signaling and provide a molecular mechanism by which developmental signaling pathways regulate target gene expression by altering chromatin topology.

A noncoding regulatory variant in IKZF1 increases acute lymphoblastic leukemia risk in Hispanic/Latino children

Hispanic/Latino children have the highest risk of acute lymphoblastic leukemia (ALL) in the US compared to other racial/ethnic groups, yet the basis of this remains incompletely understood. Through genetic fine-mapping analyses, we identified a new independent childhood ALL risk signal near IKZF1 in self-reported Hispanic/Latino individuals, but not in non-Hispanic White individuals, with an effect size of ∼1.44 (95% confidence interval = 1.33-1.55) and a risk allele frequency of ∼18% in Hispanic/Latino populations and <0.5% in European populations. This risk allele was positively associated with Indigenous American ancestry, showed evidence of selection in human history, and was associated with reduced IKZF1 expression. We identified a putative causal variant in a downstream enhancer that is most active in pro-B cells and interacts with the IKZF1 promoter. This variant disrupts IKZF1 autoregulation at this enhancer and results in reduced enhancer activity in B cell progenitors. Our study reveals a genetic basis for the increased ALL risk in Hispanic/Latino children.

Aberrant non-canonical NF-κB signalling reprograms the epigenome landscape to drive oncogenic transcriptomes in multiple myeloma

In multiple myeloma, abnormal plasma cells establish oncogenic niches within the bone marrow by engaging the NF-κB pathway to nurture their survival while they accumulate pro-proliferative mutations. Under these conditions, many cases eventually develop genetic abnormalities endowing them with constitutive NF-κB activation. Here, we find that sustained NF-κB/p52 levels resulting from such mutations favours the recruitment of enhancers beyond the normal B-cell repertoire. Furthermore, through targeted disruption of p52, we characterise how such enhancers are complicit in the formation of super-enhancers and the establishment of cis-regulatory interactions with myeloma dependencies during constitutive activation of p52. Finally, we functionally validate the pathological impact of these cis-regulatory modules on cell and tumour phenotypes using in vitro and in vivo models, confirming RGS1 as a p52-dependent myeloma driver. We conclude that the divergent epigenomic reprogramming enforced by aberrant non-canonical NF-κB signalling potentiates transcriptional programs beneficial for multiple myeloma progression.

Comparative study on chromatin loop callers using Hi-C data reveals their effectiveness

BACKGROUND

Chromosome is one of the most fundamental part of cell biology where DNA holds the hierarchical information. DNA compacts its size by forming loops, and these regions house various protein particles, including CTCF, SMC3, H3 histone. Numerous sequencing methods, such as Hi-C, ChIP-seq, and Micro-C, have been developed to investigate these properties. Utilizing these data, scientists have developed a variety of loop prediction techniques that have greatly improved their methods for characterizing loop prediction and related aspects.

RESULTS

In this study, we categorized 22 loop calling methods and conducted a comprehensive study of 11 of them. Additionally, we have provided detailed insights into the methodologies underlying these algorithms for loop detection, categorizing them into five distinct groups based on their fundamental approaches. Furthermore, we have included critical information such as resolution, input and output formats, and parameters. For this analysis, we utilized the GM12878 Hi-C datasets at 5 KB, 10 KB, 100 KB and 250 KB resolutions. Our evaluation criteria encompassed various factors, including memory usages, running time, sequencing depth, and recovery of protein-specific sites such as CTCF, H3K27ac, and RNAPII.

CONCLUSION

This analysis offers insights into the loop detection processes of each method, along with the strengths and weaknesses of each, enabling readers to effectively choose suitable methods for their datasets. We evaluate the capabilities of these tools and introduce a novel Biological, Consistency, and Computational robustness score ( B C C score ) to measure their overall robustness ensuring a comprehensive evaluation of their performance.

MMCT-Loop: a mix model-based pipeline for calling targeted 3D chromatin loops

Protein-specific Chromatin Conformation Capture (3C)-based technologies have become essential for identifying distal genomic interactions with critical roles in gene regulation. The standard techniques include Chromatin Interaction Analysis by Paired-End Tag (ChIA-PET), in situ Hi-C followed by chromatin immunoprecipitation (HiChIP) also known as PLAC-seq. To identify chromatin interactions from these data, a variety of computational methods have emerged. Although these state-of-art methods address many issues with loop calling, only few methods can fit different data types simultaneously, and the accuracy as well as the efficiency these approaches remains limited. Here we have generated a pipeline, MMCT-Loop, which ensures the accurate identification of strong loops as well as dynamic or weak loops through a mixed model. MMCT-Loop outperforms existing methods in accuracy, and the detected loops show higher activation functionality. To highlight the utility of MMCT-Loop, we applied it to conformational data derived from neural stem cell (NSCs) and uncovered several previously unidentified regulatory regions for key master regulators of stem cell identity. MMCT-Loop is an accurate and efficient loop caller for targeted conformation capture data, which supports raw data or pre-processed valid pairs as input, the output interactions are formatted and easily uploaded to a genome browser for visualization.

Oncogenic enhancers prime quiescent metastatic cells to escape NK immune surveillance by eliciting transcriptional memory

Metastasis arises from disseminated tumour cells (DTCs) that are characterized by intrinsic phenotypic plasticity and the capability of seeding to secondary organs. DTCs can remain latent for years before giving rise to symptomatic overt metastasis. In this context, DTCs fluctuate between a quiescent and proliferative state in response to systemic and microenvironmental signals including immune-mediated surveillance. Despite its relevance, how intrinsic mechanisms sustain DTCs plasticity has not been addressed. By interrogating the epigenetic state of metastatic cells, we find that tumour progression is coupled with the activation of oncogenic enhancers that are organized in variable interconnected chromatin domains. This spatial chromatin context leads to the activation of a robust transcriptional response upon repeated exposure to retinoic acid (RA). We show that this adaptive mechanism sustains the quiescence of DTCs through the activation of the master regulator SOX9. Finally, we determine that RA-stimulated transcriptional memory increases the fitness of metastatic cells by supporting the escape of quiescent DTCs from NK-mediated immune surveillance. Overall, these findings highlight the contribution of oncogenic enhancers in establishing transcriptional memories as an adaptive mechanism to reinforce cancer dormancy and immune escape, thus amenable for therapeutic intervention.

Aberrant Upregulation of RUNX3 Activates Developmental Genes to Drive Metastasis in Gastric Cancer

Gastric cancer metastasis is a major cause of mortality worldwide. Inhibition of RUNX3 in gastric cancer cell lines reduced migration, invasion, and anchorage-independent growth in vitro. Following splenic inoculation, CRISPR-mediated RUNX3-knockout HGC-27 cells show suppression of xenograft growth and liver metastasis. We interrogated the potential of RUNX3 as a metastasis driver in gastric cancer by profiling its target genes. Transcriptomic analysis revealed strong involvement of RUNX3 in the regulation of multiple developmental pathways, consistent with the notion that Runt domain transcription factor (RUNX) family genes are master regulators of development. RUNX3 promoted "cell migration" and "extracellular matrix" programs, which are necessary for metastasis. Of note, we found pro-metastatic genes WNT5A, CD44, and VIM among the top differentially expressed genes in RUNX3 knockout versus control cells. Chromatin immunoprecipitation sequencing and HiChIP analyses revealed that RUNX3 bound to the enhancers and promoters of these genes, suggesting that they are under direct transcriptional control by RUNX3. We show that RUNX3 promoted metastasis in part through its upregulation of WNT5A to promote migration, invasion, and anchorage-independent growth in various malignancies. Our study therefore reveals the RUNX3-WNT5A axis as a key targetable mechanism for gastric cancer metastasis.

SIGNIFICANCE

Subversion of RUNX3 developmental gene targets to metastasis program indicates the oncogenic nature of inappropriate RUNX3 regulation in gastric cancer.

Decoding the Epigenetics and Chromatin Loop Dynamics of Androgen Receptor-Mediated Transcription

Androgen receptor (AR)-mediated transcription plays a critical role in normal prostate development and prostate cancer growth. AR drives gene expression by binding to thousands of cis-regulatory elements (CRE) that loop to hundreds of target promoters. With multiple CREs interacting with a single promoter, it remains unclear how individual AR bound CREs contribute to gene expression. To characterize the involvement of these CREs, we investigated the AR-driven epigenetic and chromosomal chromatin looping changes. We collected a kinetic multi-omic dataset comprised of steady-state mRNA, chromatin accessibility, transcription factor binding, histone modifications, chromatin looping, and nascent RNA. Using an integrated regulatory network, we found that AR binding induces sequential changes in the epigenetic features at CREs, independent of gene expression. Further, we showed that binding of AR does not result in a substantial rewiring of chromatin loops, but instead increases the contact frequency of pre-existing loops to target promoters. Our results show that gene expression strongly correlates to the changes in contact frequency. We then proposed and experimentally validated an unbalanced multi-enhancer model where the impact on gene expression of AR-bound enhancers is heterogeneous, and is proportional to their contact frequency with target gene promoters. Overall, these findings provide new insight into AR-mediated gene expression upon acute androgen simulation and develop a mechanistic framework to investigate nuclear receptor mediated perturbations.

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

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

Repression of latent NF-κB enhancers by PDX1 regulates β cell functional heterogeneity

Interactions between lineage-determining and activity-dependent transcription factors determine single-cell identity and function within multicellular tissues through incompletely known mechanisms. By assembling a single-cell atlas of chromatin state within human islets, we identified β cell subtypes governed by either high or low activity of the lineage-determining factor pancreatic duodenal homeobox-1 (PDX1). β cells with reduced PDX1 activity displayed increased chromatin accessibility at latent nuclear factor κB (NF-κB) enhancers. Pdx1 hypomorphic mice exhibited de-repression of NF-κB and impaired glucose tolerance at night. Three-dimensional analyses in tandem with chromatin immunoprecipitation (ChIP) sequencing revealed that PDX1 silences NF-κB at circadian and inflammatory enhancers through long-range chromatin contacts involving SIN3A. Conversely, Bmal1 ablation in β cells disrupted genome-wide PDX1 and NF-κB DNA binding. Finally, antagonizing the interleukin (IL)-1β receptor, an NF-κB target, improved insulin secretion in Pdx1 hypomorphic islets. Our studies reveal functional subtypes of single β cells defined by a gradient in PDX1 activity and identify NF-κB as a target for insulinotropic therapy.

3D Enhancer-promoter networks provide predictive features for gene expression and coregulation in early embryonic lineages

Mammalian embryogenesis commences with two pivotal and binary cell fate decisions that give rise to three essential lineages: the trophectoderm, the epiblast and the primitive endoderm. Although key signaling pathways and transcription factors that control these early embryonic decisions have been identified, the non-coding regulatory elements through which transcriptional regulators enact these fates remain understudied. Here, we characterize, at a genome-wide scale, enhancer activity and 3D connectivity in embryo-derived stem cell lines that represent each of the early developmental fates. We observe extensive enhancer remodeling and fine-scale 3D chromatin rewiring among the three lineages, which strongly associate with transcriptional changes, although distinct groups of genes are irresponsive to topological changes. In each lineage, a high degree of connectivity, or 'hubness', positively correlates with levels of gene expression and enriches for cell-type specific and essential genes. Genes within 3D hubs also show a significantly stronger probability of coregulation across lineages compared to genes in linear proximity or within the same contact domains. By incorporating 3D chromatin features, we build a predictive model for transcriptional regulation (3D-HiChAT) that outperforms models using only 1D promoter or proximal variables to predict levels and cell-type specificity of gene expression. Using 3D-HiChAT, we identify, in silico, candidate functional enhancers and hubs in each cell lineage, and with CRISPRi experiments, we validate several enhancers that control gene expression in their respective lineages. Our study identifies 3D regulatory hubs associated with the earliest mammalian lineages and describes their relationship to gene expression and cell identity, providing a framework to comprehensively understand lineage-specific transcriptional behaviors.

Protocol to capture transcription factor-mediated 3D chromatin interactions using affinity tag-based BL-HiChIP

Pioneer transcription factors (TFs) can directly establish higher-order chromatin interactions to instruct gene transcription. Here, we present a protocol for capturing TF-mediated 3D chromatin interactions using affinity tag-based bridge linker (BL)-Hi-chromatin immunoprecipitation (HiChIP). We describe steps for constructing FLAG-tagged TF, performing BL-HiChIP, and preparing the library. We then detail procedures for sequencing, data analysis, and quality control. This protocol has potential applications in 3D chromatin analysis centered on any specific TF in any type of cells without the need of optimal antibodies. For complete details on the use and execution of this protocol, please refer to Ren et al. (2022).1.

Nuclear RNA catabolism controls endogenous retroviruses, gene expression asymmetry, and dedifferentiation

Endogenous retroviruses (ERVs) are remnants of ancient parasitic infections and comprise sizable portions of most genomes. Although epigenetic mechanisms silence most ERVs by generating a repressive environment that prevents their expression (heterochromatin), little is known about mechanisms silencing ERVs residing in open regions of the genome (euchromatin). This is particularly important during embryonic development, where induction and repression of distinct classes of ERVs occur in short temporal windows. Here, we demonstrate that transcription-associated RNA degradation by the nuclear RNA exosome and Integrator is a regulatory mechanism that controls the productive transcription of most genes and many ERVs involved in preimplantation development. Disrupting nuclear RNA catabolism promotes dedifferentiation to a totipotent-like state characterized by defects in RNAPII elongation and decreased expression of long genes (gene-length asymmetry). Our results indicate that RNA catabolism is a core regulatory module of gene networks that safeguards RNAPII activity, ERV expression, cell identity, and developmental potency.

The PENGUIN approach to reconstruct protein interactions at enhancer-promoter regions and its application to prostate cancer

We introduce Promoter-Enhancer-Guided Interaction Networks (PENGUIN), a method for studying protein-protein interaction (PPI) networks within enhancer-promoter interactions. PENGUIN integrates H3K27ac-HiChIP data with tissue-specific PPIs to define enhancer-promoter PPI networks (EPINs). We validated PENGUIN using cancer (LNCaP) and benign (LHSAR) prostate cell lines. Our analysis detected EPIN clusters enriched with the architectural protein CTCF, a regulator of enhancer-promoter interactions. CTCF presence was coupled with the prevalence of prostate cancer (PrCa) single nucleotide polymorphisms (SNPs) within the same EPIN clusters, suggesting functional implications in PrCa. Within the EPINs displaying enrichments in both CTCF and PrCa SNPs, we also show enrichment in oncogenes. We substantiated our identified SNPs through CRISPR/Cas9 knockout and RNAi screens experiments. Here we show that PENGUIN provides insights into the intricate interplay between enhancer-promoter interactions and PPI networks, which are crucial for identifying key genes and potential intervention targets. A dedicated server is available at https://penguin.life.bsc.es/ .