Machine and Deep Learning Methods for Predicting 3D Genome Organization.

Three-dimensional (3D) chromatin interactions, such as enhancer-promoter interactions (EPIs), loops, topologically associating domains (TADs), and A/B compartments, play critical roles in a wide range of cellular processes by regulating gene expression. Recent development of chromatin conformation capture technologies has enabled genome-wide profiling of various 3D structures, even with single cells. However, current catalogs of 3D structures remain incomplete and unreliable due to differences in technology, tools, and low data resolution. Machine learning methods have emerged as an alternative to obtain missing 3D interactions and/or improve resolution. Such methods frequently use genome annotation data (ChIP-seq, DNAse-seq, etc.), DNA sequencing information (k-mers and transcription factor binding site (TFBS) motifs), and other genomic properties to learn the associations between genomic features and chromatin interactions. In this review, we discuss computational tools for predicting three types of 3D interactions (EPIs, chromatin interactions, and TAD boundaries) and analyze their pros and cons. We also point out obstacles to the computational prediction of 3D interactions and suggest future research directions.

Prediction of Enhancer-Gene Interactions Using Chromatin-Conformation Capture and Epigenome Data Using STARE.

Disentangling the relationship of enhancers and genes is an ongoing challenge in epigenomics. We present STARE, our software to quantify the strength of enhancer-gene interactions based on enhancer activity and chromatin contact data. It implements the generalized Activity-by-Contact (gABC) score, which allows predicting putative target genes of candidate enhancers over any desired genomic distance. The only requirement for its application is a measurement of enhancer activity. In addition to regulatory interactions, STARE calculates transcription factor (TF) affinities on gene level. We illustrate its usage on a public single-cell data set of the human heart by predicting regulatory interactions on cell type level, by giving examples on how to integrate them with other data modalities, and by constructing TF affinity matrices.

Learning Enhancer-Gene associations from Bulk Transcriptomic and Epigenetic Sequencing Data with STITCHIT.

To reveal gene regulation mechanisms, it is essential to understand the role of regulatory elements, which are possibly distant from gene promoters. Integrative analysis of epigenetic and transcriptomic data can be used to gain insights into gene-expression regulation in specific phenotypes. Here, we discuss STITCHIT, an approach to dissect epigenetic variation in a gene-specific manner across many samples for the identification of regulatory elements without relying on peak calling algorithms. The obtained genomic regions are then further refined using a regularized linear model approach, which can also be used to predict gene expression. We illustrate the use of STITCHIT using H3k27ac ChIP-seq and RNA-seq data from the International Human Epigenome Consortium (IHEC).

Dynamic chromatin architecture identifies new autoimmune-associated enhancers for IL2 and novel genes regulating CD4+ T cell activation.

Genome-wide association studies (GWAS) have identified hundreds of genetic signals associated with autoimmune disease. The majority of these signals are located in non-coding regions and likely impact cis-regulatory elements (cRE). Because cRE function is dynamic across cell types and states, profiling the epigenetic status of cRE across physiological processes is necessary to characterize the molecular mechanisms by which autoimmune variants contribute to disease risk. We localized risk variants from 15 autoimmune GWAS to cRE active during TCR-CD28 co-stimulation of naïve human CD4+ T cells. To characterize how dynamic changes in gene expression correlate with cRE activity, we measured transcript levels, chromatin accessibility, and promoter-cRE contacts across three phases of naive CD4+ T cell activation using RNA-seq, ATAC-seq, and HiC. We identified ~1200 protein-coding genes physically connected to accessible disease-associated variants at 423 GWAS signals, at least one-third of which are dynamically regulated by activation. From these maps, we functionally validated a novel stretch of evolutionarily conserved intergenic enhancers whose activity is required for activation-induced IL2 gene expression in human and mouse, and is influenced by autoimmune-associated genetic variation. The set of genes implicated by this approach are enriched for genes controlling CD4+ T cell function and genes involved in human inborn errors of immunity, and we pharmacologically validated eight implicated genes as novel regulators of T cell activation. These studies directly show how autoimmune variants and the genes they regulate influence processes involved in CD4+ T cell proliferation and activation.

Nr2f1 enhancers have distinct functions in controlling Nr2f1 expression during cortical development.

There is evidence that transcription factor (TF) encoding genes, which temporally control development in multiple cell types, can have tens of enhancers that regulate their expression. The NR2F1 TF developmentally promotes caudal and ventral cortical regional fates. Here, we epigenomically compared the activity of Nr2f1's enhancers during mouse cortical development with their activity in a transgenic assay. We identified at least six that are likely to be important in prenatal cortical development, with three harboring de novo mutants identified in ASD individuals. We chose to study the function of two of the most robust enhancers by deleting them singly or together. We found that they have distinct and overlapping functions in driving Nr2f1's regional and laminar expression in the developing cortex. Thus, these two enhancers, probably in combination with the others that we defined epigenetically, precisely tune Nr2f1's regional, cell type, and temporal expression during corticogenesis.

A Ctnnb1 enhancer transcriptionally regulates Wnt signaling dosage to balance homeostasis and tumorigenesis of intestinal epithelia.

The ß-catenin-dependent canonical Wnt signaling is pivotal in organ development, tissue homeostasis, and cancer. Here, we identified an upstream enhancer of Ctnnb1 - the coding gene for ß-catenin, named ieCtnnb1 (intestinal enhancer of Ctnnb1), which is crucial for intestinal homeostasis. ieCtnnb1 is predominantly active in the base of small intestinal crypts and throughout the epithelia of large intestine. Knockout of ieCtnnb1 led to a reduction in Ctnnb1 transcription, compromising the canonical Wnt signaling in intestinal crypts. Single-cell sequencing revealed that ieCtnnb1 knockout altered epithelial compositions and potentially compromised functions of small intestinal crypts. While deletion of ieCtnnb1 hampered epithelial turnovers in physiologic conditions, it prevented occurrence and progression of Wnt/ß-catenin-driven colorectal cancers. Human ieCTNNB1 drove reporter gene expression in a pattern highly similar to mouse ieCtnnb1. ieCTNNB1 contains a single-nucleotide polymorphism associated with CTNNB1 expression levels in human gastrointestinal epithelia. The enhancer activity of ieCTNNB1 in colorectal cancer tissues was stronger than that in adjacent normal tissues. HNF4α and phosphorylated CREB1 were identified as key trans-factors binding to ieCTNNB1 and regulating CTNNB1 transcription. Together, these findings unveil an enhancer-dependent mechanism controlling the dosage of Wnt signaling and homeostasis in intestinal epithelia.

Three-dimensional chromatin mapping of sensory neurons reveals that promoter-enhancer looping is required for axonal regeneration.

The in vivo three-dimensional genomic architecture of adult mature neurons at homeostasis and after medically relevant perturbations such as axonal injury remains elusive. Here, we address this knowledge gap by mapping the three-dimensional chromatin architecture and gene expression program at homeostasis and after sciatic nerve injury in wild-type and cohesin-deficient mouse sensory dorsal root ganglia neurons via combinatorial Hi-C, promoter-capture Hi-C, CUT&Tag for H3K27ac and RNA-seq. We find that genes involved in axonal regeneration form long-range, complex chromatin loops, and that cohesin is required for the full induction of the regenerative transcriptional program. Importantly, loss of cohesin results in disruption of chromatin architecture and severely impaired nerve regeneration. Complex enhancer-promoter loops are also enriched in the human fetal cortical plate, where the axonal growth potential is highest, and are lost in mature adult neurons. Together, these data provide an original three-dimensional chromatin map of adult sensory neurons in vivo and demonstrate a role for cohesin-dependent long-range promoter interactions in nerve regeneration.

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.

Sexually dimorphic renal expression of mouse Klotho is directed by a kidney-specific distal enhancer responsive to HNF1b.

Transcription enhancers are genomic sequences regulating common and tissue-specific genes and their disruption can contribute to human disease development and progression. Klotho, a sexually dimorphic gene specifically expressed in kidney, is well-linked to kidney dysfunction and its deletion from the mouse genome leads to premature aging and death. However, the sexually dimorphic regulation of Klotho is not understood. Here, we characterize two candidate Klotho enhancers using H3K27ac epigenetic marks and transcription factor binding and investigate their functions, individually and combined, through CRISPR-Cas9 genome engineering. We discovered that only the distal (E1), but not the proximal (E2) candidate region constitutes a functional enhancer, with the double deletion not causing Klotho expression to further decrease. E1 activity is dependent on HNF1b transcription factor binding site within the enhancer. Further, E1 controls the sexual dimorphism of Klotho as evidenced by qPCR and RNA-seq. Despite the sharp reduction of Klotho mRNA, unlike germline Klotho knockouts, mutant mice present normal phenotype, including weight, lifespan, and serum biochemistry. Lastly, only males lacking E1 display more prominent acute, but not chronic kidney injury responses, indicating a remarkable range of potential adaptation to isolated Klotho loss, especially in female E1 knockouts, retaining renoprotection despite over 80% Klotho reduction.

Multiplex, single-cell CRISPRa screening for cell type specific regulatory elements.

CRISPR-based gene activation (CRISPRa) is a strategy for upregulating gene expression by targeting promoters or enhancers in a tissue/cell-type specific manner. Here, we describe an experimental framework that combines highly multiplexed perturbations with single-cell RNA sequencing (sc-RNA-seq) to identify cell-type-specific, CRISPRa-responsive cis-regulatory elements and the gene(s) they regulate. Random combinations of many gRNAs are introduced to each of many cells, which are then profiled and partitioned into test and control groups to test for effect(s) of CRISPRa perturbations of both enhancers and promoters on the expression of neighboring genes. Applying this method to a library of 493 gRNAs targeting candidate cis-regulatory elements in both K562 cells and iPSC-derived excitatory neurons, we identify gRNAs capable of specifically upregulating intended target genes and no other neighboring genes within 1 Mb, including gRNAs yielding upregulation of six autism spectrum disorder (ASD) and neurodevelopmental disorder (NDD) risk genes in neurons. A consistent pattern is that the responsiveness of individual enhancers to CRISPRa is restricted by cell type, implying a dependency on either chromatin landscape and/or additional trans-acting factors for successful gene activation. The approach outlined here may facilitate large-scale screens for gRNAs that activate genes in a cell type-specific manner.

Notch1 Phase Separation Coupled Percolation facilitates target gene expression and enhancer looping.

The Notch receptor is a pleiotropic signaling protein that translates intercellular ligand interactions into changes in gene expression via the nuclear localization of the Notch intracellular Domain (NICD). Using a combination of immunohistochemistry, RNA in situ, Optogenetics and super-resolution live imaging of transcription in human cells, we show that the N1ICD can form condensates that positively facilitate Notch target gene expression. We determined that N1ICD undergoes Phase Separation Coupled Percolation (PSCP) into transcriptional condensates, which recruit, enrich, and encapsulate a broad set of core transcriptional proteins. We show that the capacity for condensation is due to the intrinsically disordered transcriptional activation domain of the N1ICD. In addition, the formation of such transcriptional condensates acts to promote Notch-mediated super enhancer-looping and concomitant activation of the MYC protooncogene expression. Overall, we introduce a novel mechanism of Notch1 activity in which discrete changes in nuclear N1ICD abundance are translated into the assembly of transcriptional condensates that facilitate gene expression by enriching essential transcriptional machineries at target genomic loci.

Heat shock transcription factor 1 facilitates liver cancer progression by driving super-enhancer-mediated transcription of MYCN.

BACKGROUND: Heat shock transcription factors (HSFs) play crucial roles in the development of malignancies. However, the specific roles of HSFs in hepatocellular carcinoma (HCC) have yet to be fully elucidated. AIMS: To explore the involvement of the HSF family, particularly HSF1, in the progression and prognosis of HCC. MATERIALS & METHODS: We conducted a thorough analysis of HSF expression and copy number variations across various cancer datasets. Specifically focusing on HSF1, we examined its expression levels and prognostic implications in HCC. In vitro and in vivo experiments were carried out to evaluate the impact of HSF1 on liver cancer cell proliferation. Additionally, we utilized CUT&Tag, H3K27 acetylation enrichment, and RNA sequencing (RNA-seq) to investigate the super-enhancer (SE) regulatory landscapes of HSF1 in liver cancer cell lines. RESULTS: HSF1 expression is elevated in HCC and is linked to poor prognosis in several datasets. HSF1 stimulates liver cancer cell proliferation both in vitro and in vivo, partly through modulation of H3K27ac levels, influencing enhancer distribution. Mechanistically, our findings demonstrate that HSF1 transcriptionally activates MYCN expression by binding to its promoter and SE elements, thereby promoting liver cancer cell proliferation. Moreover, increased MYCN expression was detected in HCC tumors and correlated with unfavorable patient outcomes. DISCUSSION: Our study sheds light on previously unexplored aspects of HSF1 biology, identifying it as a transcription factor capable of shaping the epigenetic landscape in the context of HCC. Given HSF1's potential as an epigenetic regulator, targeting the HSF1-MYCN axis could open up new therapeutic possibilities for HCC treatment. CONCLUSION: The HSF1-MYCN axis constitutes a transcription-dependent regulatory mechanism that may function as both a prognostic indicator and a promising therapeutic target in liver cancer. Further exploration of this axis could yield valuable insights into novel treatment strategies for HCC.

LXR-dependent enhancer activation regulates the temporal organization of the liver's response to refeeding leading to lipogenic gene overshoot.

Transitions between the fed and fasted state are common in mammals. The liver orchestrates adaptive responses to feeding/fasting by transcriptionally regulating metabolic pathways of energy usage and storage. Transcriptional and enhancer dynamics following cessation of fasting (refeeding) have not been explored. We examined the transcriptional and chromatin events occurring upon refeeding in mice, including kinetic behavior and molecular drivers. We found that the refeeding response is temporally organized with the early response focused on ramping up protein translation while the later stages of refeeding drive a bifurcated lipid synthesis program. While both the cholesterol biosynthesis and lipogenesis pathways were inhibited during fasting, most cholesterol biosynthesis genes returned to their basal levels upon refeeding while most lipogenesis genes markedly overshoot above pre-fasting levels. Gene knockout, enhancer dynamics, and ChIP-seq analyses revealed that lipogenic gene overshoot is dictated by LXRα. These findings from unbiased analyses unravel the mechanism behind the long-known phenomenon of refeeding fat overshoot.

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.

Enhlink infers distal and context-specific enhancer-promoter linkages.

Enhlink is a computational tool for scATAC-seq data analysis, facilitating precise interrogation of enhancer function at the single-cell level. It employs an ensemble approach incorporating technical and biological covariates to infer condition-specific regulatory DNA linkages. Enhlink can integrate multi-omic data for enhanced specificity, when available. Evaluation with simulated and real data, including multi-omic datasets from the mouse striatum and novel promoter capture Hi-C data, demonstrate that Enhlink outperfoms alternative methods. Coupled with eQTL analysis, it identified a putative super-enhancer in striatal neurons. Overall, Enhlink offers accuracy, power, and potential for revealing novel biological insights in gene regulation.

A novel super-enhancer-related risk model for predicting prognosis and guiding personalized treatment in hepatocellular carcinoma.

BACKGROUND: Our research endeavored to develop a robust predictive signature grounded in super-enhancer-related genes (SERGs), with the dual objectives of forecasting survival outcomes and evaluating the tumor immune microenvironment (TiME) in hepatocellular carcinoma (HCC). METHODS: HCC RNA-sequencing data were retrieved from The Cancer Genome Atlas (TCGA), and 365 patients were randomly assigned to training or testing sets in 1:1 ratio. SERGs of HCC were downloaded from Super-Enhancer Database (SEdb). On the basis of training set, a SERGs signature was identified, and its prognostic value was confirmed by internal and external validation (GSE14520) sets. We subsequently examined the model for potential functional enrichment and the degree of tumor immune infiltration. Additionally, we carried out in vitro experiments to delve into the biological functions of CBX2 gene. RESULTS: An SE-related prognostic model including CBX2, TPX2, EFNA3, DNASE1L3 and SOCS2 was established and validated. According to this risk model, patients in the high-risk group had a significantly worse prognosis, and their immune cell infiltration was significantly different from that of low-risk group. Moreover, the high-risk group exhibited a significant enrichment of tumor-associated pathological pathways. The SERGs signature can generally be utilized to screen HCC patients who are likely to respond to immunotherapy, as there is a positive correlation between the risk score and the Tumor Immune Dysfunction and Exclusion (TIDE) score. Furthermore, the downregulation of the CBX2 gene expression was found to inhibit HCC cell viability, migration, and cell cycle progression, while simultaneously promoting apoptosis. CONCLUSIONS: We developed a novel HCC prognostic model utilizing SERGs, indicating that patients with high-risk score not only face a poorer prognosis but also may exhibit a diminished therapeutic response to immune checkpoint inhibitors (ICIs). This model is designed to tailor personalized treatment strategies to the individual needs of each patient, thereby improving the overall clinical outcomes for HCC patients. Furthermore, CBX2 is a promising candidate for therapeutic intervention in HCC.

Progress on SOX9 and its enhancers in mammalian sex determination.

The sex determination in mammals refers to the development of an initial bipotential organ, termed the bipotential gonad/genital ridge, into either a testis or an ovary at the early stages of embryonic development, under the precise regulation of transcription factors. SOX9 (SRY-box transcription factor 9) is a multifunctional transcription factor in mammalian development and plays a critical role in sex determination and subsequent male reproductive organs development. Recent studies have shown that several enhancers upstream of SOX9 also play an important role in the process of sex determination. In this review, we summarize the progress on the role of SOX9 and its gonadal enhancers in sex determination. This review will facilitate to understand the regulatory mechanism of sex determination of SOX9 and provides a theoretical basis for the further development of animal sex manipulation technologies.

Anatomy of a superenhancer.

Interferon regulatory factor-8 (IRF8) is the lineage determining transcription factor for the type one classical dendritic cell (cDC1) subset, a terminal selector for plasmacytoid dendritic cells and important for the function of monocytes. Studies of Irf8 gene regulation have identified several enhancers controlling its activity during development of progenitors in the bone marrow that precisely regulate expression at distinct developmental stages. Each enhancer responds to distinct transcription factors that are expressed at each stage. IRF8 is first expressed in early progenitors that form the monocyte dendritic cell progenitor (MDP) in response to induction of the transcription factor CCAAT/enhancer-binding protein alpha (C/EBPα) acting at the Irf8 +56 kb enhancer. IRF8 levels increase further as the MDP transits into the common dendritic cell progenitor (CDP) in response to E protein activity at the Irf8 +41 kb enhancer. Upon Nfil3-induction in CDPs leading to specification of the cDC1 progenitor, abrupt induction of BATF3 forms the JUN/BATF3/IRF8 heterotrimer that activates the Irf8 +32 kb enhancer that sustains Irf8 autoactivation throughout the cDC1 lifetime. Deletions of each of these enhancers has revealed their stage dependent activation. Surprisingly, studies of compound heterozygotes for each combination of enhancer deletions revealed that activation of each subsequent enhancer requires the successful activation of the previous enhancer in strictly cis-dependent mechanism. Successful progression of enhancer activation is finely tuned to alter the functional accessibility of subsequent enhancers to factors active in the next stage of development. The molecular basis for these phenomenon is still obscure but could have implications for genomic regulation in a broader developmental context.

Oncogenic transcription factors instruct promoter-enhancer hubs in individual triple negative breast cancer cells.

Sequencing-based mapping of ensemble pairwise interactions among regulatory elements support the existence of topological assemblies known as promoter-enhancer hubs or cliques in cancer. Yet, prevalence, regulators, and functions of promoter-enhancer hubs in individual cancer cells remain unclear. Here, we systematically integrated functional genomics, transcription factor screening, and optical mapping of promoter-enhancer interactions to identify key promoter-enhancer hubs, examine heterogeneity of their assembly, determine their regulators, and elucidate their role in gene expression control in individual triple negative breast cancer (TNBC) cells. Optical mapping of individual SOX9 and MYC alleles revealed the existence of frequent multiway interactions among promoters and enhancers within spatial hubs. Our single-allele studies further demonstrated that lineage-determining SOX9 and signaling-dependent NOTCH1 transcription factors compact MYC and SOX9 hubs. Together, our findings suggest that promoter-enhancer hubs are dynamic and heterogeneous topological assemblies, which are controlled by oncogenic transcription factors and facilitate subtype-restricted gene expression in cancer.

CRISPR screening uncovers a long-range enhancer for ONECUT1 in pancreatic differentiation and links a diabetes risk variant.

Functional enhancer annotation is critical for understanding tissue-specific transcriptional regulation and prioritizing disease-associated non-coding variants. However, unbiased enhancer discovery in disease-relevant contexts remains challenging. To identify enhancers pertinent to diabetes, we conducted a CRISPR interference (CRISPRi) screen in the human pluripotent stem cell (hPSC) pancreatic differentiation system. Among the enhancers identified, we focused on an enhancer we named ONECUT1e-664kb, ∼664 kb from the ONECUT1 promoter. Previous studies have linked ONECUT1 coding mutations to pancreatic hypoplasia and neonatal diabetes. We found that homozygous deletion of ONECUT1e-664kb in hPSCs leads to a near-complete loss of ONECUT1 expression and impaired pancreatic differentiation. ONECUT1e-664kb contains a type 2 diabetes-associated variant (rs528350911) disrupting a GATA motif. Introducing the risk variant into hPSCs reduced binding of key pancreatic transcription factors (GATA4, GATA6, and FOXA2), supporting its causal role in diabetes. This work highlights the utility of unbiased enhancer discovery in disease-relevant settings for understanding monogenic and complex disease.