In search of the determinants of enhancer-promoter interaction specificity

Integration of chromosome locations and functional aspects of enhancers and topologically associating domains in knowledge graphs enables versatile queries about gene regulation

Knowledge about transcription factor binding and regulation, target genes, cis-regulatory modules and topologically associating domains is not only defined by functional associations like biological processes or diseases but also has a determinative genome location aspect. Here, we exploit these location and functional aspects together to develop new strategies to enable advanced data querying. Many databases have been developed to provide information about enhancers, but a schema that allows the standardized representation of data, securing interoperability between resources, has been lacking. In this work, we use knowledge graphs for the standardized representation of enhancers and topologically associating domains, together with data about their target genes, transcription factors, location on the human genome, and functional data about diseases and gene ontology annotations. We used this schema to integrate twenty-five enhancer datasets and two domain datasets, creating the most powerful integrative resource in this field to date. The knowledge graphs have been implemented using the Resource Description Framework and integrated within the open-access BioGateway knowledge network, generating a resource that contains an interoperable set of knowledge graphs (enhancers, TADs, genes, proteins, diseases, GO terms, and interactions between domains). We show how advanced queries, which combine functional and location restrictions, can be used to develop new hypotheses about functional aspects of gene expression regulation.

Enhancer selectivity in space and time: from enhancer-promoter interactions to promoter activation

The primary regulators of metazoan gene expression are enhancers, originally functionally defined as DNA sequences that can activate transcription at promoters in an orientation-independent and distance-independent manner. Despite being crucial for gene regulation in animals, what mechanisms underlie enhancer selectivity for promoters, and more fundamentally, how enhancers interact with promoters and activate transcription, remain poorly understood. In this Review, we first discuss current models of enhancer-promoter interactions in space and time and how enhancers affect transcription activation. Next, we discuss different mechanisms that mediate enhancer selectivity, including repression, biochemical compatibility and regulation of 3D genome structure. Through 3D polymer simulations, we illustrate how the ability of 3D genome folding mechanisms to mediate enhancer selectivity strongly varies for different enhancer-promoter interaction mechanisms. Finally, we discuss how recent technical advances may provide new insights into mechanisms of enhancer-promoter interactions and how technical biases in methods such as Hi-C and Micro-C and imaging techniques may affect their interpretation.

Comparative cofactor screens show the influence of transactivation domains and core promoters on the mechanisms of transcription

Eukaryotic transcription factors (TFs) activate gene expression by recruiting cofactors to promoters. However, the relationships between TFs, promoters and their associated cofactors remain poorly understood. Here we combine GAL4-transactivation assays with comparative CRISPR-Cas9 screens to identify the cofactors used by nine different TFs and core promoters in human cells. Using this dataset, we associate TFs with cofactors, classify cofactors as ubiquitous or specific and discover transcriptional co-dependencies. Through a reductionistic, comparative approach, we demonstrate that TFs do not display discrete mechanisms of activation. Instead, each TF depends on a unique combination of cofactors, which influences distinct steps in transcription. By contrast, the influence of core promoters appears relatively discrete. Different promoter classes are constrained by either initiation or pause-release, which influences their dynamic range and compatibility with cofactors. Overall, our comparative cofactor screens characterize the interplay between TFs, cofactors and core promoters, identifying general principles by which they influence transcription.

Characterizing nascent transcription patterns of PROMPTs, eRNAs, and readthrough transcripts in the ENCODE4 deeply profiled cell lines

Arising as co-products of canonical gene expression, transcription-associated lincRNAs, such as promoter upstream transcripts (PROMPTs), enhancer RNAs (eRNAs), and readthrough (RT) transcripts, are often regarded as byproducts of transcription, although they may be important for the expression of nearby genes. We identified regions of nascent expression of these lincRNA in 16 human cell lines using Bru-seq techniques, and found distinctly regulated patterns of PROMPT, eRNA, and RT transcription using the diverse biochemical approaches in the ENCODE4 deeply profiled cell lines collection. Transcription of these lincRNAs was influenced by sequence-specific features and the local or 3D chromatin landscape. However, these sequence and chromatin features do not describe the full spectrum of lincRNA expression variability we identify, highlighting the complexity of their regulation. This may suggest that transcription-associated lincRNAs are not merely byproducts, but rather that the transcript itself, or the act of its transcription, is important for genomic function.

Enhancer-promoter specificity in gene transcription: molecular mechanisms and disease associations

Although often located at a distance from their target gene promoters, enhancers are the primary genomic determinants of temporal and spatial transcriptional specificity in metazoans. Since the discovery of the first enhancer element in simian virus 40, there has been substantial interest in unraveling the mechanism(s) by which enhancers communicate with their partner promoters to ensure proper gene expression. These research efforts have benefited considerably from the application of increasingly sophisticated sequencing- and imaging-based approaches in conjunction with innovative (epi)genome-editing technologies; however, despite various proposed models, the principles of enhancer-promoter interaction have still not been fully elucidated. In this review, we provide an overview of recent progress in the eukaryotic gene transcription field pertaining to enhancer-promoter specificity. A better understanding of the mechanistic basis of lineage- and context-dependent enhancer-promoter engagement, along with the continued identification of functional enhancers, will provide key insights into the spatiotemporal control of gene expression that can reveal therapeutic opportunities for a range of enhancer-related diseases.

Enhancer-promoter interactions can form independently of genomic distance and be functional across TAD boundaries

Topologically Associating Domains (TADs) have been suggested to facilitate and constrain enhancer-promoter interactions. However, the role of TAD boundaries in effectively restricting these interactions remains unclear. Here, we show that a significant proportion of enhancer-promoter interactions are established across TAD boundaries in Drosophila embryos, but that developmental genes are strikingly enriched in intra- but not inter-TAD interactions. We pursued this observation using the twist locus, a master regulator of mesoderm development, and systematically relocated one of its enhancers to various genomic locations. While this developmental gene can establish inter-TAD interactions with its enhancer, the functionality of these interactions remains limited, highlighting the existence of topological constraints. Furthermore, contrary to intra-TAD interactions, the formation of inter-TAD enhancer-promoter interactions is not solely driven by genomic distance, with distal interactions sometimes favored over proximal ones. These observations suggest that other general mechanisms must exist to establish and maintain specific enhancer-promoter interactions across large distances.

ISL1 and POU4F1 Directly Interact to Regulate the Differentiation and Survival of Inner Ear Sensory Neurons

The inner ear sensory neurons play a pivotal role in auditory processing and balance control. Though significant progresses have been made, the underlying mechanisms controlling the differentiation and survival of the inner ear sensory neurons remain largely unknown. During development, ISL1 and POU4F transcription factors are co-expressed and are required for terminal differentiation, pathfinding, axon outgrowth and the survival of neurons in the central and peripheral nervous systems. However, little is understood about their functional relationship and regulatory mechanism in neural development. Here, we have knocked out Isl1 or Pou4f1 or both in mice of both sexes. In the absence of Isl1, the differentiation of cochleovestibular ganglion (CVG) neurons is disturbed and with that Isl1-deficient CVG neurons display defects in migration and axon pathfinding. Compound deletion of Isl1 and Pou4f1 causes a delay in CVG differentiation and results in a more severe CVG defect with a loss of nearly all of spiral ganglion neurons (SGNs). Moreover, ISL1 and POU4F1 interact directly in developing CVG neurons and act cooperatively as well as independently in regulating the expression of unique sets of CVG-specific genes crucial for CVG development and survival by binding to the cis-regulatory elements including the promoters of Fgf10, Pou4f2, and Epha5 and enhancers of Eya1 and Ntng2 These findings demonstrate that Isl1 and Pou4f1 are indispensable for CVG development and maintenance by acting epistatically to regulate genes essential for CVG development.

An encyclopedia of enhancer-gene regulatory interactions in the human genome

Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the impact of human genetic variation on disease1-6. Here we create and evaluate a resource of >13 million enhancer-gene regulatory interactions across 352 cell types and tissues, by integrating predictive models, measurements of chromatin state and 3D contacts, and largescale genetic perturbations generated by the ENCODE Consortium7. We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,411 elementgene pairs measured in CRISPR perturbation experiments, >30,000 fine-mapped eQTLs, and 569 fine-mapped GWAS variants linked to a likely causal gene. Using this framework, we develop a new predictive model, ENCODE-rE2G, that achieves state-of-the-art performance across multiple prediction tasks, demonstrating a strategy involving iterative perturbations and supervised machine learning to build increasingly accurate predictive models of enhancer regulation. Using the ENCODE-rE2G model, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, which reveals global properties of enhancer networks, identifies differences in the functions of genes that have more or less complex regulatory landscapes, and improves analyses to link noncoding variants to target genes and cell types for common, complex diseases. By interpreting the model, we find evidence that, beyond enhancer activity and 3D enhancer-promoter contacts, additional features guide enhancerpromoter communication including promoter class and enhancer-enhancer synergy. Altogether, these genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models, and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics.

CENTRE: a gradient boosting algorithm for Cell-type-specific ENhancer-Target pREdiction

MOTIVATION

Identifying target promoters of active enhancers is a crucial step for realizing gene regulation and deciphering phenotypes and diseases. Up to now, several computational methods were developed to predict enhancer gene interactions, but they require either many epigenomic and transcriptomic experimental assays to generate cell-type (CT)-specific predictions or a single experiment applied to a large cohort of CTs to extract correlations between activities of regulatory elements. Thus, inferring CT-specific enhancer gene interactions in unstudied or poorly annotated CTs becomes a laborious and costly task.

RESULTS

Here, we aim to infer CT-specific enhancer target interactions, using minimal experimental input. We introduce Cell-specific ENhancer Target pREdiction (CENTRE), a machine learning framework that predicts enhancer target interactions in a CT-specific manner, using only gene expression and ChIP-seq data for three histone modifications for the CT of interest. CENTRE exploits the wealth of available datasets and extracts cell-type agnostic statistics to complement the CT-specific information. CENTRE is thoroughly tested across many datasets and CTs and achieves equivalent or superior performance than existing algorithms that require massive experimental data.

AVAILABILITY AND IMPLEMENTATION

CENTRE's open-source code is available at GitHub via https://github.com/slrvv/CENTRE.

Leveraging molecular quantitative trait loci to comprehend complex diseases/traits from the omics perspective

Comprehending the molecular basis of quantitative genetic variation is a principal goal for complex diseases or traits. Molecular quantitative trait loci (molQTLs) have made it possible to investigate the effects of genetic variants hiding behind large-scale omics data. A deeper understanding of molQTL is urgently required in light of the multi-dimensionalization of omics data to more fully elucidate the pertinent biological mechanisms. Herein, we reviewed molQTLs with the corresponding resource from the omics perspective and further discussed the integrative strategy of GWAS-molQTL to infer their causal effects. Subsequently, we described the opportunities and challenges encountered by molQTL. The case studies showed that molQTL is essential for complex diseases and traits, whether single- or multi-omics QTLs. Overall, we highlighted the functional significance of genetic variants to employ the discovery of molQTL in complex diseases and traits.

International Union of Basic and Clinical Pharmacology CXIII: Nuclear Receptor Superfamily-Update 2023

The NR superfamily comprises 48 transcription factors in humans that control a plethora of gene network programs involved in a wide range of physiologic processes. This review will summarize and discuss recent progress in NR biology and drug development derived from integrating various approaches, including biophysical techniques, structural studies, and translational investigation. We also highlight how defective NR signaling results in various diseases and disorders and how NRs can be targeted for therapeutic intervention via modulation via binding to synthetic lipophilic ligands. Furthermore, we also review recent studies that improved our understanding of NR structure and signaling. SIGNIFICANCE STATEMENT: Nuclear receptors (NRs) are ligand-regulated transcription factors that are critical regulators of myriad physiological processes. NRs serve as receptors for an array of drugs, and in this review, we provide an update on recent research into the roles of these drug targets.

From Genotype to Phenotype: How Enhancers Control Gene Expression and Cell Identity in Hematopoiesis

Blood comprises a wide array of specialized cells, all of which share the same genetic information and ultimately derive from the same precursor, the hematopoietic stem cell (HSC). This diversity of phenotypes is underpinned by unique transcriptional programs gradually acquired in the process known as hematopoiesis. Spatiotemporal regulation of gene expression depends on many factors, but critical among them are enhancers-sequences of DNA that bind transcription factors and increase transcription of genes under their control. Thus, hematopoiesis involves the activation of specific enhancer repertoires in HSCs and their progeny, driving the expression of sets of genes that collectively determine morphology and function. Disruption of this tightly regulated process can have catastrophic consequences: in hematopoietic malignancies, dysregulation of transcriptional control by enhancers leads to misexpression of oncogenes that ultimately drive transformation. This review attempts to provide a basic understanding of enhancers and their role in transcriptional regulation, with a focus on normal and malignant hematopoiesis. We present examples of enhancers controlling master regulators of hematopoiesis and discuss the main mechanisms leading to enhancer dysregulation in leukemia and lymphoma.

Recapitulation of patient-specific 3D chromatin conformation using machine learning

Regulatory networks containing enhancer-gene edges define cellular states. Multiple efforts have revealed these networks for reference tissues and cell lines by integrating multi-omics data. However, the methods developed cannot be applied for large patient cohorts due to the infeasibility of chromatin immunoprecipitation sequencing (ChIP-seq) for limited biopsy material. We trained machine-learning models using chromatin interaction analysis with paired-end tag sequencing (ChIA-PET) and high-throughput chromosome conformation capture combined with chromatin immunoprecipitation (HiChIP) data that can predict connections using only assay for transposase-accessible chromatin using sequencing (ATAC-seq) and RNA-seq data as input, which can be generated from biopsies. Our method overcomes limitations of correlation-based approaches that cannot distinguish between distinct target genes of given enhancers or between active vs. poised states in different samples, a hallmark of network rewiring in cancer. Application of our model on 371 samples across 22 cancer types revealed 1,780 enhancer-gene connections for 602 cancer genes. Using CRISPR interference (CRISPRi), we validated enhancers predicted to regulate ESR1 in estrogen receptor (ER)+ breast cancer and A1CF in liver hepatocellular carcinoma.

Using Synthetic DNA Libraries to Investigate Chromatin and Gene Regulation

Despite the recent explosion in genome-wide studies in chromatin and gene regulation, we are still far from extracting a set of genetic rules that can predict the function of the regulatory genome. One major reason for this deficiency is that gene regulation is a multi-layered process that involves an enormous variable space, which cannot be fully explored using native genomes. This problem can be partially solved by introducing synthetic DNA libraries into cells, a method that can test the regulatory roles of thousands to millions of sequences with limited variables. Here, we review recent applications of this method to study transcription factor (TF) binding, nucleosome positioning, and transcriptional activity. We discuss the design principles, experimental procedures, and major findings from these studies and compare the pros and cons of different approaches.

Molecular features driving cellular complexity of human brain evolution

Human-specific genomic changes contribute to the unique functionalities of the human brain1-5. The cellular heterogeneity of the human brain6,7 and the complex regulation of gene expression highlight the need to characterize human-specific molecular features at cellular resolution. Here we analysed single-nucleus RNA-sequencing and single-nucleus assay for transposase-accessible chromatin with sequencing datasets for human, chimpanzee and rhesus macaque brain tissue from posterior cingulate cortex. We show a human-specific increase of oligodendrocyte progenitor cells and a decrease of mature oligodendrocytes across cortical tissues. Human-specific regulatory changes were accelerated in oligodendrocyte progenitor cells, and we highlight key biological pathways that may be associated with the proportional changes. We also identify human-specific regulatory changes in neuronal subtypes, which reveal human-specific upregulation of FOXP2 in only two of the neuronal subtypes. We additionally identify hundreds of new human accelerated genomic regions associated with human-specific chromatin accessibility changes. Our data also reveal that FOS::JUN and FOX motifs are enriched in the human-specifically accessible chromatin regions of excitatory neuronal subtypes. Together, our results reveal several new mechanisms underlying the evolutionary innovation of human brain at cell-type resolution.

Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases

Genome-wide association studies (GWASs) are a valuable tool for understanding the biology of complex human traits and diseases, but associated variants rarely point directly to causal genes. In the present study, we introduce a new method, polygenic priority score (PoPS), that learns trait-relevant gene features, such as cell-type-specific expression, to prioritize genes at GWAS loci. Using a large evaluation set of genes with fine-mapped coding variants, we show that PoPS and the closest gene individually outperform other gene prioritization methods, but observe the best overall performance by combining PoPS with orthogonal methods. Using this combined approach, we prioritize 10,642 unique gene-trait pairs across 113 complex traits and diseases with high precision, finding not only well-established gene-trait relationships but nominating new genes at unresolved loci, such as LGR4 for estimated glomerular filtration rate and CCR7 for deep vein thrombosis. Overall, we demonstrate that PoPS provides a powerful addition to the gene prioritization toolbox.

Function and Evolution of the Loop Extrusion Machinery in Animals

Structural maintenance of chromosomes (SMC) complexes are essential proteins found in genomes of all cellular organisms. Essential functions of these proteins, such as mitotic chromosome formation and sister chromatid cohesion, were discovered a long time ago. Recent advances in chromatin biology showed that SMC proteins are involved in many other genomic processes, acting as active motors extruding DNA, which leads to the formation of chromatin loops. Some loops formed by SMC proteins are highly cell type and developmental stage specific, such as SMC-mediated DNA loops required for VDJ recombination in B-cell progenitors, or dosage compensation in Caenorhabditis elegans and X-chromosome inactivation in mice. In this review, we focus on the extrusion-based mechanisms that are common for multiple cell types and species. We will first describe an anatomy of SMC complexes and their accessory proteins. Next, we provide biochemical details of the extrusion process. We follow this by the sections describing the role of SMC complexes in gene regulation, DNA repair, and chromatin topology.

Hi-TrAC reveals division of labor of transcription factors in organizing chromatin loops

The three-dimensional genomic structure plays a critical role in gene expression, cellular differentiation, and pathological conditions. It is pivotal to elucidate fine-scale chromatin architectures, especially interactions of regulatory elements, to understand the temporospatial regulation of gene expression. In this study, we report Hi-TrAC as a proximity ligation-free, robust, and sensitive technique to profile genome-wide chromatin interactions at high-resolution among regulatory elements. Hi-TrAC detects chromatin looping among accessible regions at single nucleosome resolution. With almost half-million identified loops, we reveal a comprehensive interaction network of regulatory elements across the genome. After integrating chromatin binding profiles of transcription factors, we discover that cohesin complex and CTCF are responsible for organizing long-range chromatin loops, related to domain formation; whereas ZNF143 and HCFC1 are involved in structuring short-range chromatin loops between regulatory elements, which directly regulate gene expression. Thus, we introduce a methodology to identify a delicate and comprehensive network of cis-regulatory elements, revealing the complexity and a division of labor of transcription factors in organizing chromatin loops for genome organization and gene expression.

Single-cell RNA sequencing highlights the functional role of human endogenous retroviruses in gallbladder cancer

Background

Gallbladder cancer (GBC), the most common malignancy of the biliary tract, shows late diagnosis and low survival rate and requires continued search for new diagnostic biomarkers and therapeutic targets. Human endogenous retroviruses (HERVs) are specifically prone to be reactivated in diverse cancers and are implicated in cancer progression and immunotherapy.

Methods

Single-cell RNA sequencing was performed on tumor tissues and paired adjacent tissues from 4 GBC patients. Dual-luciferase reporter assay was applied to measure enhancer activity of HERV sequences.

Findings

We dissected the cellular diversity and described the HERV transcriptomic landscape for GBC. We found that HERVs were transcribed in a cell type-specific manner and different HERV families were associated with diverse biological effects. HERVs could function as enhancers, presumably causing altered expression of neighboring genes. The transcription level of HERVH was gradually elevated with the malignant transformation of epithelial cells, suggesting HERVH may be a potential early diagnostic biomarker of GBC. HHLA2, a newly emerging immune checkpoint, was derived by HERVH, exhibited an expressional correlation with HERVH, and was identified as a promising target for immunotherapy.

Interpretation

Exploring the transcriptional landscape and potential functional impact of HERVs highlights the important role of HERVs in GBC and provides a fresh perspective on managing GBC.

Funding

This study was supported by the National Natural Science Foundation of China (31970176, 81972256) and the research grants from the Innovation Capacity Building Project of Jiangsu province (BM2020019).

Developmental and housekeeping transcriptional programs in Drosophila require distinct chromatin remodelers

Gene transcription is a highly regulated process in all animals. In Drosophila, two major transcriptional programs, housekeeping and developmental, have promoters with distinct regulatory compatibilities and nucleosome organization. However, it remains unclear how the differences in chromatin structure relate to the distinct regulatory properties and which chromatin remodelers are required for these programs. Using rapid degradation of core remodeler subunits in Drosophila melanogaster S2 cells, we demonstrate that developmental gene transcription requires SWI/SNF-type complexes, primarily to maintain distal enhancer accessibility. In contrast, wild-type-level housekeeping gene transcription requires the Iswi and Ino80 remodelers to maintain nucleosome positioning and phasing at promoters. These differential remodeler dependencies relate to different DNA-sequence-intrinsic nucleosome affinities, which favor a default ON state for housekeeping but a default OFF state for developmental gene transcription. Overall, our results demonstrate how different transcription-regulatory strategies are implemented by DNA sequence, chromatin structure, and remodeler activity.

Every gene everywhere all at once: High-precision measurement of 3D chromosome architecture with single-cell Hi-C

The three-dimensional (3D) structure of chromosomes influences essential biological processes such as gene expression, genome replication, and DNA damage repair and has been implicated in many developmental and degenerative diseases. In the past two centuries, two complementary genres of technology-microscopy, such as fluorescence in situ hybridization (FISH), and biochemistry, such as chromosome conformation capture (3C or Hi-C)-have revealed general principles of chromosome folding in the cell nucleus. However, the extraordinary complexity and cell-to-cell variability of the chromosome structure necessitate new tools with genome-wide coverage and single-cell precision. In the past decade, single-cell Hi-C emerges as a new approach that builds upon yet conceptually differs from bulk Hi-C assays. Instead of measuring population-averaged statistical properties of chromosome folding, single-cell Hi-C works as a proximity-based "biochemical microscope" that measures actual 3D structures of individual genomes, revealing features hidden in bulk Hi-C such as radial organization, multi-way interactions, and chromosome intermingling. Single-cell Hi-C has been used to study highly dynamic processes such as the cell cycle, cell-type-specific chromosome architecture ("structure types"), and structure-expression interplay, deepening our understanding of DNA organization and function.

Repression and 3D-restructuring resolves regulatory conflicts in evolutionarily rearranged genomes

Regulatory landscapes drive complex developmental gene expression, but it remains unclear how their integrity is maintained when incorporating novel genes and functions during evolution. Here, we investigated how a placental mammal-specific gene, Zfp42, emerged in an ancient vertebrate topologically associated domain (TAD) without adopting or disrupting the conserved expression of its gene, Fat1. In ESCs, physical TAD partitioning separates Zfp42 and Fat1 with distinct local enhancers that drive their independent expression. This separation is driven by chromatin activity and not CTCF/cohesin. In contrast, in embryonic limbs, inactive Zfp42 shares Fat1's intact TAD without responding to active Fat1 enhancers. However, neither Fat1 enhancer-incompatibility nor nuclear envelope-attachment account for Zfp42's unresponsiveness. Rather, Zfp42's promoter is rendered inert to enhancers by context-dependent DNA methylation. Thus, diverse mechanisms enabled the integration of independent Zfp42 regulation in the Fat1 locus. Critically, such regulatory complexity appears common in evolution as, genome wide, most TADs contain multiple independently expressed genes.

Confined migration induces heterochromatin formation and alters chromatin accessibility

During migration, cells often squeeze through small constrictions, requiring extensive deformation. We hypothesized that nuclear deformation associated with such confined migration could alter chromatin organization and function. By studying cells migrating through microfluidic devices that mimic interstitial spaces in vivo, we found that confined migration results in increased H3K9me3 and H3K27me3 heterochromatin marks that persist for days. This "confined migration-induced heterochromatin" (CMiH) was distinct from heterochromatin formation during migration initiation. Confined migration decreased chromatin accessibility at intergenic regions near centromeres and telomeres, suggesting heterochromatin spreading from existing sites. Consistent with the overall decrease in accessibility, global transcription was decreased during confined migration. Intriguingly, we also identified increased accessibility at promoter regions of genes linked to chromatin silencing, tumor invasion, and DNA damage response. Inhibiting CMiH reduced migration speed, suggesting that CMiH promotes confined migration. Together, our findings indicate that confined migration induces chromatin changes that regulate cell migration and other functions.

EPI-Mind: Identifying Enhancer-Promoter Interactions Based on Transformer Mechanism

MOTIVATION

Enhancer-Promoter Interactions (EPIs) is an essential step in the gene regulation process. However, the detection of EPIs by traditional wet experimental techniques is time-consuming and expensive. Thus, computational methods would be very useful for understanding the mechanism of EPIs. A number of approaches have been proposed to address this problem. Nevertheless, there is room for exploration and improvement for the existing research methods.

METHODS

In this study, a novel deep-learning model named EPI-Mind was proposed to predict EPIs with sequences features. First, we encoded enhancers and promoters sequences with pre-trained DNA vectors. Then, the Convolutional Neural Network (CNN) was utilized to rough extract the global and local features. Finally, the transformer mechanism was introduced to further extract the feature. We first trained a model named EPI-Mind_spe which can predict EPIs in one cell line. To achieve general prediction across different cell lines and further improve the performance of the model, a second-time training was carried on. The redivided dataset were used to train a new model called EPI-Mind_gen which can predict EPIs across different cell lines. To further improve the accuracy, a new model named EPI-Mind_best was trained which used the EPI-Mind_gen as a pre-trained model.

RESULTS

EPI-Mind_spe has the ability of predict EPIs with average AUROC above 90% and average AUPR above 70% but with cell lines specificity. EPI-Mind_gen can predict EPIs across different cell lines and its average AUROC is higher than the EPI-Mind_spe about 4.8%. EPI-Mind_best is superior to the state-of-the-art predictors on benchmarking datasets. EPI-Mind_best achieved best in 5 indicators within 12 indicators consists of AUPR and AUROC which is better than pioneers.

CONCLUSION

This research proposed a method, which was called EPI-Mind, to predict EPIs only with enhancer and promoters sequences, the framework of which was based on deep learning. This manuscript may provide a new route to solve the problem.

Enhancer looping protein LDB1 regulates hepatocyte gene expression by cooperating with liver transcription factors

Enhancers establish proximity with distant target genes to regulate temporospatial gene expression and specify cell identity. Lim domain binding protein 1 (LDB1) is a conserved and widely expressed protein that functions as an enhancer looping factor. Previous studies in erythroid cells and neuronal cells showed that LDB1 forms protein complexes with different transcription factors to regulate cell-specific gene expression. Here, we show that LDB1 regulates expression of liver genes by occupying enhancer elements and cooperating with hepatic transcription factors HNF4A, FOXA1, TCF7 and GATA4. Using the glucose transporter SLC2A2 gene, encoding GLUT2, as an example, we find that LDB1 regulates gene expression by mediating enhancer-promoter interactions. In vivo, we find that LDB1 deficiency in primary mouse hepatocytes dysregulates metabolic gene expression and changes the enhancer landscape. Conditional deletion of LDB1 in adult mouse liver induces glucose intolerance. However, Ldb1 knockout hepatocytes show improved liver pathology under high-fat diet conditions associated with increased expression of genes related to liver fatty acid metabolic processes. Thus, LDB1 is linked to liver metabolic functions under normal and obesogenic conditions.

Endogenous Retroviral Sequences Behave as Putative Enhancers Controlling Gene Expression through HP1-Regulated Long-Range Chromatin Interactions

About half of the mammalian genome is constituted of repeated elements, among which endogenous retroviruses (ERVs) are known to influence gene expression and cancer development. The HP1 (Heterochromatin Protein 1) proteins are known to be essential for heterochromatin establishment and function and its loss in hepatocytes leads to the reactivation of specific ERVs and to liver tumorigenesis. Here, by studying two ERVs located upstream of genes upregulated upon loss of HP1, Mbd1 and Trim24, we show that these HP1-dependent ERVs behave as either alternative promoters or as putative enhancers forming a loop with promoters of endogenous genes depending on the genomic context and HP1 expression level. These ERVs are characterised by a specific HP1-independent enrichment in heterochromatin-associated marks H3K9me3 and H4K20me3 as well as in the enhancer-specific mark H3K4me1, a combination that might represent a bookmark of putative ERV-derived enhancers. These ERVs are further enriched in a HP1-dependent manner in H3K27me3, suggesting a critical role of this mark together with HP1 in the silencing of the ERVs, as well as for the repression of the associated genes. Altogether, these results lead to the identification of a new regulatory hub involving the HP1-dependent formation of a physical loop between specific ERVs and endogenous genes.

Xist exerts gene-specific silencing during XCI maintenance and impacts lineage-specific cell differentiation and proliferation during hematopoiesis

X chromosome inactivation (XCI) is a dosage compensation phenomenon that occurs in females. Initiation of XCI depends on Xist RNA, which triggers silencing of one of the two X chromosomes, except for XCI escape genes that continue to be biallelically expressed. In the soma XCI is stably maintained with continuous Xist expression. How Xist impacts XCI maintenance remains an open question. Here we conditionally delete Xist in hematopoietic system of mice and report differentiation and cell cycle defects in female hematopoietic stem and progenitor cells (HSPCs). By utilizing female HSPCs and mouse embryonic fibroblasts, we find that X-linked genes show variable tolerance to Xist loss. Specifically, XCI escape genes exhibit preferential transcriptional upregulation, which associates with low H3K27me3 occupancy and high chromatin accessibility that accommodates preexisting binding of transcription factors such as Yin Yang 1 (YY1) at the basal state. We conclude that Xist is necessary for gene-specific silencing during XCI maintenance and impacts lineage-specific cell differentiation and proliferation during hematopoiesis.

Here the authors investigate the functional relevance of X-chromosome inactivation (XCI) regulator Xist in hematopoiesis. They find that Xist loss leads to changes in the ratio of hematopoietic progenitor cells and results in chromatin accessibility and transcriptional upregulation on the inactive X chromosome, including XCI escape genes known to be associated with cell cycle and immune response.

The Cupid shuffle: Do enhancers prefer specific promoters?

Two recent reports (Martinez-Ara et al., 2022; Bergman et al., 2022) explore the compatibility between enhancers and promoters and find that enhancers preferentially activate promoters with low intrinsic activity rather than favoring housekeeping or cell-type-specific promoters.

ISR8/IRF1-AS1 Is Relevant for IFNα and NF-κB Responses

The study of the interferon (IFN) α-induced cell transcriptome has shown altered expression of several long non-coding RNAs (lncRNAs). ISR8/IRF1-AS1 (IFN stimulated RNA 8), located close to IFN regulatory factor 1 (IRF1) coding gene, transcribes a lncRNA induced at early times after IFNα treatment or IRF1 or NF-κB activation. Depletion or overexpression of ISR8 RNA does not lead to detected deregulation of the IFN response. Surprisingly, disruption of ISR8 locus with CRISPR-Cas9 genome editing results in cells that fail to induce several key ISGs and pro-inflammatory cytokines after a trigger with IFNα or overexpression of IRF1 or the NF-κB subunit RELA. This suggests that the ISR8 locus may play a relevant role in IFNα and NF-κB pathways. Interestingly, IFNα, IRFs and NF-κB-responding luciferase reporters are normally induced in ISR8-disrupted cells when expressed from a plasmid but not when integrated into the genome. Therefore, IFNα and NF-κB pathways are functional to induce the expression of exogenous episomic transcripts but fail to activate transcription from genomic promoters. Transcription from these promoters is not restored with silencing inhibitors, by decreasing the levels of several negative regulators or by overexpression of inducers. Transcriptome analyses indicate that ISR8-disrupted cells have a drastic increase in the levels of negative regulators such as XIST and Zinc finger proteins. Our results agree with ISR8 loci being an enhancer region that is fundamental for proper antiviral and proinflammatory responses. These results are relevant because several SNPs located in the ISR8 region are associated with chronic inflammatory and autoimmune diseases including Crohn’s disease, inflammatory bowel disease, ulcerative colitis or asthma.

Predicting causal genes from psychiatric genome-wide association studies using high-level etiological knowledge

Genome-wide association studies have discovered hundreds of genomic loci associated with psychiatric traits, but the causal genes underlying these associations are often unclear, a research gap that has hindered clinical translation. Here, we present a Psychiatric Omnilocus Prioritization Score (PsyOPS) derived from just three binary features encapsulating high-level assumptions about psychiatric disease etiology - namely, that causal psychiatric disease genes are likely to be mutationally constrained, be specifically expressed in the brain, and overlap with known neurodevelopmental disease genes. To our knowledge, PsyOPS is the first method specifically tailored to prioritizing causal genes at psychiatric GWAS loci. We show that, despite its extreme simplicity, PsyOPS achieves state-of-the-art performance at this task, comparable to a prior domain-agnostic approach relying on tens of thousands of features. Genes prioritized by PsyOPS are substantially more likely than other genes at the same loci to have convergent evidence of direct regulation by the GWAS variant according to both DNA looping assays and expression or splicing quantitative trait locus (QTL) maps. We provide examples of genes hundreds of kilobases away from the lead variant, like GABBR1 for schizophrenia, that are prioritized by all three of PsyOPS, DNA looping and QTLs. Our results underscore the power of incorporating high-level knowledge of trait etiology into causal gene prediction at GWAS loci, and comprise a resource for researchers interested in experimentally characterizing psychiatric gene candidates.

Compatibility rules of human enhancer and promoter sequences

Gene regulation in the human genome is controlled by distal enhancers that activate specific nearby promoters1. A proposed model for this specificity is that promoters have sequence-encoded preferences for certain enhancers, for example, mediated by interacting sets of transcription factors or cofactors2. This 'biochemical compatibility' model has been supported by observations at individual human promoters and by genome-wide measurements in Drosophila3-9. However, the degree to which human enhancers and promoters are intrinsically compatible has not yet been systematically measured, and how their activities combine to control RNA expression remains unclear. Here we design a high-throughput reporter assay called enhancer × promoter self-transcribing active regulatory region sequencing (ExP STARR-seq) and applied it to examine the combinatorial compatibilities of 1,000 enhancer and 1,000 promoter sequences in human K562 cells. We identify simple rules for enhancer-promoter compatibility, whereby most enhancers activate all promoters by similar amounts, and intrinsic enhancer and promoter activities multiplicatively combine to determine RNA output (R2 = 0.82). In addition, two classes of enhancers and promoters show subtle preferential effects. Promoters of housekeeping genes contain built-in activating motifs for factors such as GABPA and YY1, which decrease the responsiveness of promoters to distal enhancers. Promoters of variably expressed genes lack these motifs and show stronger responsiveness to enhancers. Together, this systematic assessment of enhancer-promoter compatibility suggests a multiplicative model tuned by enhancer and promoter class to control gene transcription in the human genome.

Embryonic heat conditioning in chicks induces transgenerational heat/immunological resilience via methylation on regulatory elements

The question of whether behavioral traits are heritable is under debate. An obstacle in demonstrating transgenerational inheritance in mammals originates from the maternal environment's effect on offspring phenotype. Here, we used in ovo embryonic heat conditioning (EHC) of first-generation chicks, demonstrating heredity of both heat and immunological resilience, confirmed by a reduced fibril response in their untreated offspring to either heat or LPS challenge. Concordantly, transcriptome analysis confirmed that EHC induces changes in gene expression in the anterior preoptic hypothalamus (APH) that contribute to these phenotypes in the offspring. To study the association between epigenetic mechanisms and trait heritability, DNA-methylation patterns in the APH of offspring of control versus EHC fathers were evaluated. Genome-wide analysis revealed thousands of differentially methylated sites (DMSs), which were highly enriched in enhancers and CCCTC-binding factor (CTCF) sites. Overlap analysis revealed 110 differentially expressed genes that were associated with altered methylation, predominantly on enhancers. Gene-ontology analysis shows pathways associated with immune response, chaperone-mediated protein folding, and stress response. For the proof of concept, we focused on HSP25 and SOCS3, modulators of heat and immune responses, respectively. Chromosome conformational capture (3C) assay identified interactions between their promoters and methylated enhancers, with the strongest frequency on CTCF binding sites. Furthermore, gene expression corresponded with the differential methylation patterns, and presented increased CTCF binding in both hyper- and hypomethylated DMSs. Collectively, we demonstrate that EHC induces transgenerational thermal and immunological resilience traits. We propose that one of the mechanisms underlying inheritance depends on three-dimensional (3D) chromatin reorganization.

Altering enhancer-promoter linear distance impacts promoter competition in cis and in trans

In Drosophila, pairing of maternal and paternal homologs can permit trans-interactions between enhancers on one homolog and promoters on another, an example of a phenomenon called transvection. When chromosomes are paired, promoters in cis and in trans to an enhancer can compete for the enhancer's activity, but the parameters that govern this competition are as yet poorly understood. To assess how the linear spacing between an enhancer and promoter can influence promoter competition in Drosophila, we employed transgenic constructs wherein the eye-specific enhancer GMR is placed at varying distances from a heterologous hsp70 promoter driving a fluorescent reporter. While GMR activates the reporter to a high degree when the enhancer and promoter are spaced by a few hundred base pairs, activation is strongly attenuated when the enhancer is moved 3 kilobases away. By examining transcription of endogenous genes near the point of transgene insertion, we show that linear spacing of 3 kb between GMR and the hsp70 promoter results in elevated transcription of neighboring promoters, suggesting a loss of specificity between the enhancer and its intended transgenic target promoter. Furthermore, increasing spacing between GMR and hsp70 by just 100 bp can enhance transvection, resulting in increased activation of a promoter on a paired homolog at the expense of a promoter in cis to the enhancer. Finally, cis-/trans-promoter competition assays in which one promoter carries mutations to key core promoter elements show that GMR will skew its activity toward a wild type promoter, suggesting that an enhancer is in a balanced competition between its potential target promoters in cis and in trans.

Enhancer-promoter interaction maps provide insights into skeletal muscle-related traits in pig genome

Background

Gene expression programs are intimately linked to the interplay of active cis regulatory elements mediated by chromatin contacts and associated RNAs. Genome-wide association studies (GWAS) have identified many variants in these regulatory elements that can contribute to phenotypic diversity. However, the functional interpretation of these variants remains nontrivial due to the lack of chromatin contact information or limited contact resolution. Furthermore, the distribution and role of chromatin-associated RNAs in gene expression and chromatin conformation remain poorly understood. To address this, we first present a comprehensive interaction map of nuclear dynamics of 3D chromatin-chromatin interactions (H3K27ac BL-HiChIP) and RNA-chromatin interactions (GRID-seq) to reveal genomic variants that contribute to complex skeletal muscle traits.

Results

In a genome-wide scan, we provide systematic fine mapping and gene prioritization from GWAS leading signals that underlie phenotypic variability of growth rate, meat quality, and carcass performance. A set of candidate functional variants and 54 target genes previously not detected were identified, with 71% of these candidate functional variants choosing to skip over their nearest gene to regulate the target gene in a long-range manner. The effects of three functional variants regulating KLF6 (related to days to 100 kg), MXRA8 (related to lean meat percentage), and TAF11 (related to loin muscle depth) were observed in two pig populations. Moreover, we find that this multi-omics interaction map consists of functional communities that are enriched in specific biological functions, and GWAS target genes can serve as core genes for exploring peripheral trait-relevant genes.

Conclusions

Our results provide a valuable resource of candidate functional variants for complex skeletal muscle-related traits and establish an integrated approach to complement existing 3D genomics by exploiting RNA-chromatin and chromatin-chromatin interactions for future association studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01322-2.

Analysis of the landscape of human enhancer sequences in biological databases

The process of gene regulation extends as a network in which both genetic sequences and proteins are involved. The levels of regulation and the mechanisms involved are multiple. Transcription is the main control mechanism for most genes, being the downstream steps responsible for refining the transcription patterns. In turn, gene transcription is mainly controlled by regulatory events that occur at promoters and enhancers. Several studies are focused on analyzing the contribution of enhancers in the development of diseases and their possible use as therapeutic targets. The study of regulatory elements has advanced rapidly in recent years with the development and use of next generation sequencing techniques. All this information has generated a large volume of information that has been transferred to a growing number of public repositories that store this information. In this article, we analyze the content of those public repositories that contain information about human enhancers with the aim of detecting whether the knowledge generated by scientific research is contained in those databases in a way that could be computationally exploited. The analysis will be based on three main aspects identified in the literature: types of enhancers, type of evidence about the enhancers, and methods for detecting enhancer-promoter interactions. Our results show that no single database facilitates the optimal exploitation of enhancer data, most types of enhancers are not represented in the databases and there is need for a standardized model for enhancers. We have identified major gaps and challenges for the computational exploitation of enhancer data.

Detecting TAD-like domains from RNA-associated interactions

Topologically associated domains (TADs) are crucial chromatin structural units. Evidence has illustrated that RNA–chromatin and RNA–RNA spatial interactions, so-called RNA-associated interactions (RAIs), may be associated with TAD-like domains (TLDs). To decode hierarchical TLDs from RAIs, we proposed SuperTLD, a domain detection algorithm incorporating imputation. We applied SuperTLD on four RAI data sets and compared TLDs with the TADs identified from the corresponding Hi-C datasets. The TLDs and TADs share a moderate similarity of hierarchies ≥ 0.5312 and the finest structures ≥ 0.8295. Comparison between boundaries and domains further demonstrated the novelty of TLDs. Enrichment analysis of epigenetic characteristics illustrated that the novel TLDs exhibit an enriched CTCF by 0.6245 fold change and H3 histone marks enriched within domains. GO analysis on the TLD novel boundaries exhibited enriched diverse terms, revealing TLDs’ formation mechanism related closely to gene regulation.

Inflammatory Immune-Associated eRNA: Mechanisms, Functions and Therapeutic Prospects

The rapid development of multiple high-throughput sequencing technologies has made it possible to explore the critical roles and mechanisms of functional enhancers and enhancer RNAs (eRNAs). The inflammatory immune response, as a fundamental pathological process in infectious diseases, cancers and immune disorders, coordinates the balance between the internal and external environment of the organism. It has been shown that both active enhancers and intranuclear eRNAs are preferentially expressed over inflammation-related genes in response to inflammatory stimuli, suggesting that enhancer transcription events and their products influence the expression and function of inflammatory genes. Therefore, in this review, we summarize and discuss the relevant inflammatory roles and regulatory mechanisms of eRNAs in inflammatory immune cells, non-inflammatory immune cells, inflammatory immune diseases and tumors, and explore the potential therapeutic effects of enhancer inhibitors affecting eRNA production for diseases with inflammatory immune responses.

Regulatory elements can be essential for maintaining broad chromatin organization and cell viability

Increasing evidence shows that promoters and enhancers could be related to 3D chromatin structure, thus affecting cellular functions. Except for their roles in forming canonical chromatin loops, promoters and enhancers have not been well studied regarding the maintenance of broad chromatin organization. Here, we focused on the active promoters/enhancers predicted to form many 3D contacts with other active promoters/enhancers (referred to as hotspots) and identified dozens of loci essential for cell growth and survival through CRISPR screening. We found that the deletion of an essential hotspot could lead to changes in broad chromatin organization and the expression of distal genes. We showed that the essentiality of hotspots does not result from their association with individual genes that are essential for cell viability but rather from their association with multiple dysregulated non-essential genes to synergistically impact cell fitness.

Systematic identification of genomic elements that regulate FCGR2A expression and harbor variants linked with autoimmune disease

BACKGROUND

FCGR2A binds antibody-antigen complexes to regulate the abundance of circulating and deposited complexes along with downstream immune and autoimmune responses. Although the abundance of FCRG2A may be critical in immune-mediated diseases, little is known about whether its surface expression is regulated through cis genomic elements and non-coding variants. In the current study, we aimed to characterize the regulation of FCGR2A expression, the impact of genetic variation and its association with autoimmune disease.

METHODS

We applied CRISPR-based interference and editing to scrutinize 1.7 Mb of open chromatin surrounding the FCGR2A gene to identify regulatory elements. Relevant transcription factors (TFs) binding to these regions were defined through public databases. Genetic variants affecting regulation were identified using luciferase reporter assays and were verified in a cohort of 1996 genotyped healthy individuals using flow cytometry.

RESULTS

We identified a complex proximal region and five distal enhancers regulating FCGR2A. The proximal region split into subregions upstream and downstream of the transcription start site, was enriched in binding of inflammation-regulated TFs, and harbored a variant associated with FCGR2A expression in primary myeloid cells. One distal enhancer region was occupied by CCCTC-binding factor (CTCF) whose binding site was disrupted by a rare genetic variant, altering gene expression.

CONCLUSIONS

The FCGR2A gene is regulated by multiple proximal and distal genomic regions, with links to autoimmune disease. These findings may open up novel therapeutic avenues where fine-tuning of FCGR2A levels may constitute a part of treatment strategies for immune-mediated diseases.

Two promoters integrate multiple enhancer inputs to drive wild-type knirps expression in the Drosophila melanogaster embryo

Proper development depends on precise spatiotemporal gene expression patterns. Most developmental genes are regulated by multiple enhancers and often by multiple core promoters that generate similar transcripts. We hypothesize that multiple promoters may be required either because enhancers prefer a specific promoter or because multiple promoters serve as a redundancy mechanism. To test these hypotheses, we studied the expression of the knirps locus in the early Drosophila melanogaster embryo, which is mediated by multiple enhancers and core promoters. We found that one of these promoters resembles a typical "sharp" developmental promoter, while the other resembles a "broad" promoter usually associated with housekeeping genes. Using synthetic reporter constructs, we found that some, but not all, enhancers in the locus show a preference for one promoter, indicating that promoters provide both redundancy and specificity. By analyzing the reporter dynamics, we identified specific burst properties during the transcription process, namely burst size and frequency, that are most strongly tuned by the combination of promoter and enhancer. Using locus-sized reporters, we discovered that enhancers with no promoter preference in a synthetic setting have a preference in the locus context. Our results suggest that the presence of multiple promoters in a locus is due both to enhancer preference and a need for redundancy and that "broad" promoters with dispersed transcription start sites are common among developmental genes. They also imply that it can be difficult to extrapolate expression measurements from synthetic reporters to the locus context, where other variables shape a gene's overall expression pattern.

Integrative epigenomic and high-throughput functional enhancer profiling reveals determinants of enhancer heterogeneity in gastric cancer

BACKGROUND

Enhancers are distal cis-regulatory elements required for cell-specific gene expression and cell fate determination. In cancer, enhancer variation has been proposed as a major cause of inter-patient heterogeneity-however, most predicted enhancer regions remain to be functionally tested.

METHODS

We analyzed 132 epigenomic histone modification profiles of 18 primary gastric cancer (GC) samples, 18 normal gastric tissues, and 28 GC cell lines using Nano-ChIP-seq technology. We applied Capture-based Self-Transcribing Active Regulatory Region sequencing (CapSTARR-seq) to assess functional enhancer activity. An Activity-by-contact (ABC) model was employed to explore the effects of histone acetylation and CapSTARR-seq levels on enhancer-promoter interactions.

RESULTS

We report a comprehensive catalog of 75,730 recurrent predicted enhancers, the majority of which are GC-associated in vivo (> 50,000) and associated with lower somatic mutation rates inferred by whole-genome sequencing. Applying CapSTARR-seq to the enhancer catalog, we observed significant correlations between CapSTARR-seq functional activity and H3K27ac/H3K4me1 levels. Super-enhancer regions exhibited increased CapSTARR-seq signals compared to regular enhancers, even when decoupled from native chromatin contexture. We show that combining histone modification and CapSTARR-seq functional enhancer data improves the prediction of enhancer-promoter interactions and pinpointing of germline single nucleotide polymorphisms (SNPs), somatic copy number alterations (SCNAs), and trans-acting TFs involved in GC expression. We identified cancer-relevant genes (ING1, ARL4C) whose expression between patients is influenced by enhancer differences in genomic copy number and germline SNPs, and HNF4α as a master trans-acting factor associated with GC enhancer heterogeneity.

CONCLUSIONS

Our results indicate that combining histone modification and functional assay data may provide a more accurate metric to assess enhancer activity than either platform individually, providing insights into the relative contribution of genetic (cis) and regulatory (trans) mechanisms to GC enhancer functional heterogeneity.

How subtle changes in 3D structure can create large changes in transcription

Animal genomes are organized into topologically associated domains (TADs). TADs are thought to contribute to gene regulation by facilitating enhancer-promoter (E-P) contacts within a TAD and preventing these contacts across TAD borders. However, the absolute difference in contact frequency across TAD boundaries is usually less than 2-fold, even though disruptions of TAD borders can change gene expression by 10-fold. Existing models fail to explain this hypersensitive response. Here, we propose a futile cycle model of enhancer-mediated regulation that can exhibit hypersensitivity through bistability and hysteresis. Consistent with recent experiments, this regulation does not exhibit strong correlation between E-P contact and promoter activity, even though regulation occurs through contact. Through mathematical analysis and stochastic simulation, we show that this system can create an illusion of E-P biochemical specificity and explain the importance of weak TAD boundaries. It also offers a mechanism to reconcile apparently contradictory results from recent global TAD disruption with local TAD boundary deletion experiments. Together, these analyses advance our understanding of cis-regulatory contacts in controlling gene expression and suggest new experimental directions.

Multiscale modeling of genome organization with maximum entropy optimization

Three-dimensional (3D) organization of the human genome plays an essential role in all DNA-templated processes, including gene transcription, gene regulation, and DNA replication. Computational modeling can be an effective way of building high-resolution genome structures and improving our understanding of these molecular processes. However, it faces significant challenges as the human genome consists of over 6 × 109 base pairs, a system size that exceeds the capacity of traditional modeling approaches. In this perspective, we review the progress that has been made in modeling the human genome. Coarse-grained models parameterized to reproduce experimental data via the maximum entropy optimization algorithm serve as effective means to study genome organization at various length scales. They have provided insight into the principles of whole-genome organization and enabled de novo predictions of chromosome structures from epigenetic modifications. Applications of these models at a near-atomistic resolution further revealed physicochemical interactions that drive the phase separation of disordered proteins and dictate chromatin stability in situ. We conclude with an outlook on the opportunities and challenges in studying chromosome dynamics.

Enhancer release and retargeting activates disease-susceptibility genes

The functional engagement between an enhancer and its target promoter ensures precise gene transcription1. Understanding the basis of promoter choice by enhancers has important implications for health and disease. Here we report that functional loss of a preferred promoter can release its partner enhancer to loop to and activate an alternative promoter (or alternative promoters) in the neighbourhood. We refer to this target-switching process as 'enhancer release and retargeting'. Genetic deletion, motif perturbation or mutation, and dCas9-mediated CTCF tethering reveal that promoter choice by an enhancer can be determined by the binding of CTCF at promoters, in a cohesin-dependent manner-consistent with a model of 'enhancer scanning' inside the contact domain. Promoter-associated CTCF shows a lower affinity than that at chromatin domain boundaries and often lacks a preferred motif orientation or a partnering CTCF at the cognate enhancer, suggesting properties distinct from boundary CTCF. Analyses of cancer mutations, data from the GTEx project and risk loci from genome-wide association studies, together with a focused CRISPR interference screen, reveal that enhancer release and retargeting represents an overlooked mechanism that underlies the activation of disease-susceptibility genes, as exemplified by a risk locus for Parkinson's disease (NUCKS1-RAB7L1) and three loci associated with cancer (CLPTM1L-TERT, ZCCHC7-PAX5 and PVT1-MYC).

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

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

Implications of Enhancer Transcription and eRNAs in Cancer

Despite extensive progress in developing anticancer therapies, therapy resistance remains a major challenge that promotes disease relapse. The changes that lead to therapy resistance can be intrinsically present or may be initiated during treatment. Genetic and epigenetic heterogeneity in tumors make it more challenging to deal with therapy resistance. Recent advances in genome-wide analyses have revealed that the deregulation of distal gene regulatory elements, such as enhancers, appears in several pathophysiological conditions, including cancer. Beyond the conventional function of enhancers in recruiting transcription factors to gene promoters, enhancer elements are also transcribed into noncoding RNAs known as enhancer RNAs (eRNA). Accumulating evidence suggests that uncontrolled enhancer activity with aberrant eRNA expression promotes oncogenesis. Interestingly, tissue-specific, transcribed eRNAs from active enhancers can serve as potential therapeutic targets or biomarkers in several cancer types. This review provides a comprehensive overview of the mechanisms of enhancer transcription and eRNAs as well as their potential roles in cancer and drug resistance.

Enhancer rewiring in tumors: an opportunity for therapeutic intervention

Enhancers are cis-regulatory sequences that fine-tune expression of their target genes in a spatiotemporal manner. They are recognized by sequence-specific transcription factors, which in turn recruit transcriptional coactivators that facilitate transcription by promoting assembly and activation of the basal transcriptional machinery. Their functional importance is underscored by the fact that they are often the target of genetic and nongenetic events in human disease that disrupt their sequence, interactome, activation potential, and/or chromatin environment. Dysregulation of transcription and addiction to transcriptional effectors that interact with and modulate enhancer activity are common features of cancer cells and are amenable to therapeutic intervention. Here, we discuss the current knowledge on enhancer biology, the broad spectrum of mechanisms that lead to their malfunction in tumor cells, and recent progress in developing drugs that efficaciously target their dependencies.

Genome-wide enhancer maps link risk variants to disease genes

Genome-wide association studies (GWAS) have identified thousands of noncoding loci that are associated with human diseases and complex traits, each of which could reveal insights into the mechanisms of disease¹. Many of the underlying causal variants may affect enhancers^2,3, but we lack accurate maps of enhancers and their target genes to interpret such variants. We recently developed the activity-by-contact (ABC) model to predict which enhancers regulate which genes and validated the model using CRISPR perturbations in several cell types⁴. Here we apply this ABC model to create enhancer-gene maps in 131 human cell types and tissues, and use these maps to interpret the functions of GWAS variants. Across 72 diseases and complex traits, ABC links 5,036 GWAS signals to 2,249 unique genes, including a class of 577 genes that appear to influence multiple phenotypes through variants in enhancers that act in different cell types. In inflammatory bowel disease (IBD), causal variants are enriched in predicted enhancers by more than 20-fold in particular cell types such as dendritic cells, and ABC achieves higher precision than other regulatory methods at connecting noncoding variants to target genes. These variant-to-function maps reveal an enhancer that contains an IBD risk variant and that regulates the expression of PPIF to alter the membrane potential of mitochondria in macrophages. Our study reveals principles of genome regulation, identifies genes that affect IBD and provides a resource and generalizable strategy to connect risk variants of common diseases to their molecular and cellular functions.