Mechanisms of enhancer action: the known and the unknown

Single chromatin fiber profiling and nucleosome position mapping in the human brain

We apply a single-molecule chromatin fiber sequencing (Fiber-seq) protocol designed for amplification-free cell-type-specific mapping of the regulatory architecture at nucleosome resolution along extended ∼10-kb chromatin fibers to neuronal and non-neuronal nuclei sorted from human brain tissue. Specifically, application of this method enables the resolution of cell-selective promoter and enhancer architectures on single fibers, including transcription factor footprinting and position mapping, with sequence-specific fixation of nucleosome arrays flanking transcription start sites and regulatory motifs. We uncover haplotype-specific chromatin patterns, multiple regulatory elements cis-aligned on individual fibers, and accessible chromatin at 20,000 unique sites encompassing retrotransposons and other repeat sequences hitherto "unmappable" by short-read epigenomic sequencing. Overall, we show that Fiber-seq is applicable to human brain tissue, offering sharp demarcation of nucleosome-depleted regions at sites of open chromatin in conjunction with multi-kilobase nucleosomal positioning at single-fiber resolution on a genome-wide scale.

Central control of dynamic gene circuits governs T cell rest and activation

The ability of cells to maintain distinct identities and respond to transient environmental signals requires tightly controlled regulation of gene networks1-3. These dynamic regulatory circuits that respond to extracellular cues in primary human cells remain poorly defined. The need for context-dependent regulation is prominent in T cells, where distinct lineages must respond to diverse signals to mount effective immune responses and maintain homeostasis4-8. Here we performed CRISPR screens in multiple primary human CD4+ T cell contexts to identify regulators that control expression of IL-2Rα, a canonical marker of T cell activation transiently expressed by pro-inflammatory effector T cells and constitutively expressed by anti-inflammatory regulatory T cells where it is required for fitness9-11. Approximately 90% of identified regulators of IL-2Rα had effects that varied across cell types and/or stimulation states, including a subset that even had opposite effects across conditions. Using single-cell transcriptomics after pooled perturbation of context-specific screen hits, we characterized specific factors as regulators of overall rest or activation and constructed state-specific regulatory networks. MED12 - a component of the Mediator complex - serves as a dynamic orchestrator of key regulators, controlling expression of distinct sets of regulators in different T cell contexts. Immunoprecipitation-mass spectrometry revealed that MED12 interacts with the histone methylating COMPASS complex. MED12 was required for histone methylation and expression of genes encoding key context-specific regulators, including the rest maintenance factor KLF2 and the versatile regulator MYC. CRISPR ablation of MED12 blunted the cell-state transitions between rest and activation and protected from activation-induced cell death. Overall, this work leverages CRISPR screens performed across conditions to define dynamic gene circuits required to establish resting and activated T cell states.

Advancing microbiota therapeutics: the role of synthetic biology in engineering microbial communities for precision medicine

Over recent years, studies on microbiota research and synthetic biology have explored novel approaches microbial manipulation for therapeutic purposes. However, fragmented information is available on this aspect with key insights scattered across various disciplines such as molecular biology, genetics, bioengineering, and medicine. This review aims to the transformative potential of synthetic biology in advancing microbiome research and therapies, with significant implications for healthcare, agriculture, and environmental sustainability. By merging computer science, engineering, and biology, synthetic biology allows for precise design and modification of biological systems via cutting edge technologies like CRISPR/Cas9 gene editing, metabolic engineering, and synthetic oligonucleotide synthesis, thus paving the way for targeted treatments such as personalized probiotics and engineered microorganisms. The review will also highlight the vital role of gut microbiota in disorders caused by its dysbiosis and suggesting microbiota-based therapies and innovations such as biosensors for real-time gut health monitoring, non-invasive diagnostic tools, and automated bio foundries for better outcomes. Moreover, challenges including genetic stability, environmental safety, and robust regulatory frameworks will be discussed to understand the importance of ongoing research to ensure safe and effective microbiome interventions.

Neurodevelopmental functions and activities of the KAT3 class of lysine acetyltransferases

The human lysine acetyltransferases KAT3A (CREBBP) and KAT3B (EP300) are essential enzymes in gene regulation in the nucleus. Their ubiquitous expression in metazoan cell types controls cell proliferation and differentiation during development. This comprehensive review delves into the biological roles of KAT3A and KAT3B in neurodevelopment, shedding light on how alterations in their regulation or activity can potentially contribute to a spectrum of neurodegenerative diseases (e.g., Huntington's and Alzheimer's). We explore the pathophysiological implications of KAT3 function loss in these disorders, considering their conserved protein domains and biochemical functions in chromatin regulation. The discussion also underscores the crucial role of KAT3 proteins and their substrates in supporting the integration of key cell signaling pathways. Furthermore, the narrative highlights the interdependence of KAT3-mediated lysine acetylation with lysine methylation and arginine methylation. From a cellular perspective, KAT3-dependent signal integration at subnuclear domains is mediated by liquid-liquid phase separation in response to KAT3-mediated lysine acetylation. The disruption of these finely tuned regulatory processes underscores their pathological roles in neurodegeneration. This review also points to the exciting potential for future research in this field, inspiring further investigation and discovery in the area of neurodevelopment and neurodegenerative diseases.

Two coacting shadow enhancers regulate twin of eyeless expression during early Drosophila development

The Drosophila PAX6 homolog twin of eyeless (toy) sits at the pinnacle of the genetic pathway controlling eye development, the retinal determination network. Expression of toy in the embryo is first detectable at cellular blastoderm stage 5 in an anterior-dorsal band in the presumptive procephalic neuroectoderm, which gives rise to the primordia of the visual system and brain. Although several maternal and gap transcription factors that generate positional information in the embryo have been implicated in controlling toy, the regulation of toy expression in the early embryo is currently not well characterized. In this study, we adopt an integrated experimental approach utilizing bioinformatics, molecular genetic testing of putative enhancers in transgenic reporter gene assays and quantitative analysis of expression patterns in the early embryo, to identify 2 novel coacting enhancers at the toy gene. In addition, we apply mathematical modeling to dissect the regulatory landscape for toy. We demonstrate that relatively simple thermodynamic-based models, incorporating only 5 TF binding sites, can accurately predict gene expression from the 2 coacting enhancers and that the HUNCHBACK TF plays a critical regulatory role through a dual-modality function as an activator and repressor. Our analysis also reveals that the molecular architecture of the 2 enhancers is very different, indicating that the underlying regulatory logic they employ is distinct.

A novel interpretable deep learning-based computational framework designed synthetic enhancers with broad cross-species activity

Enhancers play a critical role in dynamically regulating spatial-temporal gene expression and establishing cell identity, underscoring the significance of designing them with specific properties for applications in biosynthetic engineering and gene therapy. Despite numerous high-throughput methods facilitating genome-wide enhancer identification, deciphering the sequence determinants of their activity remains challenging. Here, we present the DREAM (DNA cis-Regulatory Elements with controllable Activity design platforM) framework, a novel deep learning-based approach for synthetic enhancer design. Proficient in uncovering subtle and intricate patterns within extensive enhancer screening data, DREAM achieves cutting-edge sequence-based enhancer activity prediction and highlights critical sequence features implicating strong enhancer activity. Leveraging DREAM, we have engineered enhancers that surpass the potency of the strongest enhancer within the Drosophila genome by approximately 3.6-fold. Remarkably, these synthetic enhancers exhibited conserved functionality across species that have diverged more than billion years, indicating that DREAM was able to learn highly conserved enhancer regulatory grammar. Additionally, we designed silencers and cell line-specific enhancers using DREAM, demonstrating its versatility. Overall, our study not only introduces an interpretable approach for enhancer design but also lays out a general framework applicable to the design of other types of cis-regulatory elements.

Entangled and non-modular enhancer sequences producing independent spatial activities

The modularity of transcriptional enhancers is central to our understanding of morphological evolution, allowing specific changes to a gene expression pattern component, without affecting others. Enhancer modularity refers to physically separated stretches of regulatory sequence producing discrete spatiotemporal transcriptional activity. This concept stems from assays that test the sufficiency of a DNA segment to drive spatial reporter expression resembling that of the corresponding gene. Focusing on spatial patterns, it overlooks quantitative aspects of gene expression, underestimating the regulatory sequence actually required to reach full endogenous expression levels. Here, we show that five regulatory activities of the gene yellow in Drosophila, classically described as modular, result from extensively overlapping sequences, with broadly distributed regulatory information. Nevertheless, the independent regulatory activities of these entangled enhancers appear to be nucleated by specific segments that we called enhancer cores. Our work calls for a reappraisal of enhancer definition and properties, as well as of the consequences on regulatory evolution.

A LANA peptide inhibits tumor growth by inducing CHD4 protein cleavage and triggers cell death

Kaposi's sarcoma-associated herpesvirus (KSHV) establishes a latent infection, and viral genes are poised to be transcribed in the latent chromatin. In the poised chromatins, KSHV latency-associated nuclear antigen (LANA) interacts with cellular chromodomain-helicase-DNA-binding protein 4 (CHD4) and inhibits viral promoter activation. CHD4 is known to regulate cell differentiation by preventing enhancers from activating promoters. Here, we identified a putative CHD4 inhibitor peptide (VGN73) from the LANA sequence corresponding to the LANA-CHD4 interaction surface. The VGN73 interacts with CHD4 at its PHD domain with a dissociation constant (KD) of 14 nM. Pre-treatment with VGN73 enhanced monocyte differentiation into macrophages and globally altered the repertoire of activated genes in U937 cells. Furthermore, the introduction of the peptide into the cancer cells induced caspase-mediated CHD4 cleavage, triggered cell death, and inhibited tumor growth in a xenograft mouse model. The VGN73 may facilitate cell differentiation therapy.

Characterization of the Cannabis sativa glandular trichome epigenome

BACKGROUND

The relationship between epigenomics and plant specialised metabolism remains largely unexplored despite the fundamental importance of epigenomics in gene regulation and, potentially, yield of products of plant specialised metabolic pathways. The glandular trichomes of Cannabis sativa are an emerging model system that produce large quantities of cannabinoid and terpenoid specialised metabolites with known medicinal and commercial value. To address this lack of epigenomic data, we mapped H3K4 trimethylation, H3K56 acetylation, H3K27 trimethylation post-translational modifications and the histone variant H2A.Z, using chromatin immunoprecipitation, in C. sativa glandular trichomes, leaf, and stem tissues. Corresponding transcriptomic (RNA-seq) datasets were integrated, and tissue-specific analyses conducted to relate chromatin states to glandular trichome specific gene expression.

RESULTS

The promoters of cannabinoid and terpenoid biosynthetic genes, specialised metabolite transporter genes, defence related genes, and starch and sucrose metabolism were enriched specifically in trichomes for histone marks H3K4me3 and H3K56ac, consistent with active transcription. We identified putative trichome-specific enhancer elements by identifying intergenic regions of H3K56ac enrichment, a histone mark that maintains enhancer accessibility, then associated these to putative target genes using the tissue specific gene transcriptomic data. Bi-valent chromatin loci specific to glandular trichomes, marked with H3K4 trimethylation and H3K27 trimethylation, were associated with genes of MAPK signalling pathways and plant specialised metabolism pathways, supporting recent hypotheses that implicate bi-valent chromatin in plant defence. The histone variant H2A.Z was largely found in intergenic regions and enriched in chromatin that contained genes involved in DNA homeostasis.

CONCLUSION

We report the first genome-wide histone post-translational modification maps for C. sativa glandular trichomes, and more broadly for glandular trichomes in plants. Our findings have implications in plant adaptation and stress responses and provide a basis for enhancer-mediated, targeted, gene transformation studies in plant glandular trichomes.

Transcription factor clusters as information transfer agents

Deciphering how genes interpret information from the concentration of transcription factors (TFs) within the cell nucleus remains a fundamental question in gene regulation. Recent advancements have unveiled the heterogeneous distribution of TF molecules in the nucleus, posing challenges to the precise decoding of concentration signals. To explore this phenomenon, we employ high-resolution single-cell imaging of a fluorescently tagged TF protein, Bicoid, in living fly embryos. We show that accumulation of Bicoid in submicron clusters preserves the spatial information of the maternal Bicoid gradient, and that cluster intensity, size, and frequency offer remarkably precise spatial cues. We further discover that various known gene targets of Bicoid activation colocalize with clusters and that for the target gene Hunchback, this colocalization is dependent on its enhancer binding affinity. Modeling information transfer through these clusters suggests that clustering offers a more rapid sensing mechanism for global nuclear concentrations than freely diffusing TF molecules detected by simple enhancers.

Epigenetic basis for the establishment of ruminal tissue-specific functions in bovine fetuses and adults

Epigenetic regulation in the rumen, a unique ruminant organ, remains largely unexplored compared with other tissues studied in model species. In this study, we perform an in-depth analysis of the epigenetic and transcriptional landscapes across fetal and adult bovine tissues as well as pluripotent stem cells. Among the extensive methylation differences across various stages and tissues, we identify tissue-specific differentially methylated regions (tsDMRs) unique to the rumen, which are crucial for regulating epithelial development and energy metabolism. These tsDMRs cluster within super-enhancer regions that overlap with transcription factor (TF) binding sites. Regression models indicate that DNA methylation, along with H3K27me3 and H3K27ac, can be used to predict enhancer activity. Key upstream TFs, including SOX2, FOSL1/2, and SMAD2/3, primarily maintain an inhibitory state through bivalent modifications during fetal development. Downstream functional genes are maintained mainly in a stable repressive state via DNA methylation until differentiation is complete. Our study underscores the critical role of tsDMRs in regulating distal components of rumen morphology and function, providing key insights into the epigenetic regulatory mechanisms that may influence bovine production traits.

DeepDualEnhancer: A Dual-Feature Input DNABert Based Deep Learning Method for Enhancer Recognition

Enhancers are cis-regulatory DNA sequences that are widely distributed throughout the genome. They can precisely regulate the expression of target genes. Since the features of enhancer segments are difficult to detect, we propose DeepDualEnhancer, a DNABert-based method using a multi-scale convolutional neural network, BiLSTM, for enhancer identification. We first designed the DeepDualEnhancer method based only on the DNA sequence input. It mainly consists of a multi-scale Convolutional Neural Network, and BiLSTM to extract features by DNABert and embedding, respectively. Meanwhile, we collected new datasets from the enhancer-promoter interaction field and designed the method DeepDualEnhancer-genomic for inputting DNA sequences and genomic signals, which consists of the transformer sequence attention. Extensive comparisons of our method with 20 other excellent methods through 5-fold cross validation, ablation experiments, and an independent test demonstrated that DeepDualEnhancer achieves the best performance. It is also found that the inclusion of genomic signals helps the enhancer recognition task to be performed better.

Repeated Shifts in Sociality Are Associated With Fine-tuning of Highly Conserved and Lineage-Specific Enhancers in a Socially Flexible Bee

Comparative genomic studies of social insects suggest that changes in gene regulation are associated with evolutionary transitions in social behavior, but the activity of predicted regulatory regions has not been tested empirically. We used self-transcribing active regulatory region sequencing, a high-throughput enhancer discovery tool, to identify and measure the activity of enhancers in the socially variable sweat bee, Lasioglossum albipes. We identified over 36,000 enhancers in the L. albipes genome from 3 social and 3 solitary populations. Many enhancers were identified in only a subset of L. albipes populations, revealing rapid divergence in regulatory regions within this species. Population-specific enhancers were often proximal to the same genes across populations, suggesting compensatory gains and losses of regulatory regions may preserve gene activity. We also identified 1,182 enhancers with significant differences in activity between social and solitary populations, some of which are conserved regulatory regions across species of bees. These results indicate that social trait variation in L. albipes is associated with the fine-tuning of ancient enhancers as well as lineage-specific regulatory changes. Combining enhancer activity with population genetic data revealed variants associated with differences in enhancer activity and identified a subset of differential enhancers with signatures of selection associated with social behavior. Together, these results provide the first empirical map of enhancers in a socially flexible bee and highlight links between cis-regulatory variation and the evolution of social behavior.

CRISPR tiling deletion screens reveal functional enhancers of neuropsychiatric risk genes and allelic compensation effects (ACE) on transcription

Precise transcriptional regulation is critical for cellular function and development, yet the mechanism of this process remains poorly understood for many genes. To gain a deeper understanding of the regulation of neuropsychiatric disease risk genes, we identified a total of 39 functional enhancers for four dosage-sensitive genes, APP, FMR1, MECP2, and SIN3A, using CRISPR tiling deletion screening in human induced pluripotent stem cell (iPSC)-induced excitatory neurons. We found that enhancer annotation provides potential pathological insights into disease-associated copy number variants. More importantly, we discovered that allelic enhancer deletions at SIN3A could be compensated by increased transcriptional activities from the other intact allele. Such allelic compensation effects (ACE) on transcription is stably maintained during differentiation and, once established, cannot be reversed by ectopic SIN3A expression. Further, ACE at SIN3A occurs through dosage sensing by the promoter. Together, our findings unravel a regulatory compensation mechanism that ensures stable and precise transcriptional output for SIN3A, and potentially other dosage-sensitive genes.

Predicting genome-wide tissue-specific enhancers via combinatorial transcription factor genomic occupancy analysis

Enhancers are non-coding cis-regulatory elements crucial for transcriptional regulation. Mutations in enhancers can disrupt gene regulation, leading to disease phenotypes. Identifying enhancers and their tissue-specific activity is challenging due to their lack of stereotyped sequences. This study presents a sequence-based computational model that uses combinatorial transcription factor (TF) genomic occupancy to predict tissue-specific enhancers. Trained on diverse datasets, including ENCODE and Vista enhancer browser data, the model predicted 25 000 forebrain-specific cis-regulatory modules (CRMs) in the human genome. Validation using biochemical features, disease-associated SNPs, and in vivo zebrafish analysis confirmed its effectiveness. This model aids in predicting enhancers lacking well-characterized chromatin features, complementing experimental approaches in tissue-specific enhancer discovery.

Congenital microcoria deletion in mouse links Sox21 dysregulation to disease and suggests a role for TGFB2 in glaucoma and myopia

Congenital microcoria (MCOR) is a rare hereditary developmental defect of the iris dilator muscle frequently associated with high axial myopia and high intraocular pressure (IOP) glaucoma. The condition is caused by submicroscopic rearrangements of chromosome 13q32.1. However, the mechanisms underlying the failure of iris development and the origin of associated features remain elusive. Here, we present a 3D architecture model of the 13q32.1 region, demonstrating that MCOR-related deletions consistently disrupt the boundary between two topologically associating domains (TADs). Deleting the critical MCOR-causing region in mice reveals ectopic Sox21 expression precisely aligning with Dct, each located in one of the two neighbor TADs. This observation is consistent with the TADs' boundary alteration and adoption of Dct regulatory elements by the Sox21 promoter. Additionally, we identify Tgfb2 as a target gene of SOX21 and show TGFΒ2 accumulation in the aqueous humor of an MCOR-affected subject. Accumulation of TGFB2 is recognized for its role in glaucoma and potential impact on axial myopia. Our results highlight the importance of SOX21-TGFB2 signaling in iris development and control of eye growth and IOP. Insights from MCOR studies may provide therapeutic avenues for this condition but also for glaucoma and high myopia conditions, affecting millions of people.

FAS gene expression, prognostic significance and molecular interactions in lung cancer

Introduction

FAS has been implicated in the development of various cancers, but its involvement in lung cancer has not been systematically characterized. In this study, we performed data mining in online tumor databases to investigate the expression, methylation, alterations, protein interactions, co-expression and prognostic significance of FAS in lung cancer.

Method

The expression, prognostic significance and molecular interactions of FAS in lung cancer was mined and analyzed using GENT2, GEPIA2, UALCAN, cBioPortal, STRING, GeneMANIA, UCSC Xena, Enrichr, and OSluca databases. FAS expression was subsequently investigated at the protein level in samples from 578 lung cancer patients to understand its protein-level expression. In vitro validation of FAS gene expression was performed on H1299, H1993, A549 and HBE cell lines.

Result

We found that the expression of FAS was significantly downregulated in both lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) compared to normal lung tissue. In addition, we observed a higher level of FAS promoter methylation in LUSC tissue than in normal tissue. FAS alterations were rare (1.9%) in lung cancer samples, with deep deletions being more common than missense mutations, which occurred mainly in the TNFR-like cysteine-rich domain and the death domain. We also identified a list of proteins interacting with FAS and genes co-expressed with FAS, with LUAD having 11 co-expressed genes and LUSC having 90 co-expressed genes. Our results also showed that FAS expression has limited prognostic significance (HR=1.302, 95% CI=0.935-1.139, P=0.530). Protein level investigation revealed that FAS expression varied among individuals, with nTPM values ranging from 5.2 to 67.2.

Conclusion

This study provides valuable insights into the involvements and characteristics of FAS in lung cancer. Further studies are needed to investigate the clinical significance of FAS alterations in lung cancer and to explore the potential of targeting FAS for therapeutic intervention.

EnhancerNet: a predictive model of cell identity dynamics through enhancer selection

Understanding how cell identity is encoded by the genome and acquired during differentiation is a central challenge in cell biology. I have developed a theoretical framework called EnhancerNet, which models the regulation of cell identity through the lens of transcription factor-enhancer interactions. I demonstrate that autoregulation in these interactions imposes a constraint on the model, resulting in simplified dynamics that can be parameterized from observed cell identities. Despite its simplicity, EnhancerNet recapitulates a broad range of experimental observations on cell identity dynamics, including enhancer selection, cell fate induction, hierarchical differentiation through multipotent progenitor states and direct reprogramming by transcription factor overexpression. The model makes specific quantitative predictions, reproducing known reprogramming recipes and the complex haematopoietic differentiation hierarchy without fitting unobserved parameters. EnhancerNet provides insights into how new cell types could evolve and highlights the functional importance of distal regulatory elements with dynamic chromatin in multicellular evolution.

Multiple promoter and enhancer differences likely contribute to augmented G6PC2 expression in human versus mouse pancreatic islet alpha cells

G6PC2 encodes a glucose-6-phosphatase catalytic subunit that opposes the action of glucokinase in pancreatic islets, thereby modulating the sensitivity of insulin and glucagon secretion to glucose. In mice, G6pc2 is expressed at ~20-fold higher levels in β-cells than in α-cells, whereas in humans G6PC2 is expressed at only ~5-fold higher levels in β-cells. We therefore hypothesize that G6PC2 likely influences glucagon secretion to a greater degree in humans. With a view to generating a humanized mouse that recapitulates augmented G6PC2 expression levels in α-cells, we sought to identify the genomic regions that confer differential mouse G6pc2 expression in α-cells versus β-cells as well as the evolutionary changes that have altered this ratio in humans. Studies in islet-derived cell lines suggest that the elevated G6pc2 expression in mouse β-cells versus α-cells is mainly due to a difference in the relative activity of the proximal G6pc2 promoter in these cell types. Similarly, the smaller difference in G6PC2 expression between α-cells and β-cells in humans is potentially explained by a change in relative proximal G6PC2 promoter activity. However, we show that both glucocorticoid levels and multiple differences in the relative activity of eight transcriptional enhancers between mice and humans likely contribute to differential G6PC2 expression. Finally, we show that a mouse-specific non-coding RNA, Gm13613, whose expression is controlled by G6pc2 enhancer I, does not regulate G6pc2 expression, indicating that altered expression of Gm13613 in a humanized mouse that contains both the human promoter and enhancers should not affect G6PC2 function.

Nucleosome placement and polymer mechanics explain genomic contacts on 100kbp scales

The 3d organization of the genome - in particular, which two regions of DNA are in contact with each other - plays a role in regulating gene expression. Several factors influence genome 3d organization. Nucleosomes (where ~ 100 basepairs of DNA wrap around histone proteins) also bend, twist and compactify chromosomal DNA, altering its polymer mechanics. How much does the positioning of nucleosomes between gene loci influence contacts between those gene loci? And, to what extent is polymer mechanics responsible for this? To address this question, we combine a stochastic polymer mechanics model of chromosomal DNA including twists and wrapping induced by nucleosomes with two data-driven pipelines. The first estimates nucleosome positioning from ATACseq data in regions of high accessibility. Most of the genome is low-accessibility, so we combine this with a novel image analysis method that estimates the distribution of nucleosome spacing from electron microscopy data. There are no free parameters in the biophysical model. We apply this method to IL6, IL15, CXCL9, and CXCL10, inflammatory marker genes in macrophages, before and after immune stimulation, and compare the predictions with contacts measured by conformation capture experiments (4C-seq). We find that within a 500 kilo-basepairs genomic region, polymer mechanics with nucleosomes can explain 71% of close contacts. These results suggest that, while genome contacts on 100kbp-scales are multifactorial, they may be amenable to mechanistic, physical explanation. Our work also highlights the role of nucleosomes, not just at the loci of interest, but between them, and not just the total number of nucleosomes, but their specific placement. The method generalizes to other genes, and can be used to address whether a contact is under active regulation by the cell (e.g., a macrophage during inflammatory stimulation). Importantly, our findings suggest that gene function may have evolved through selective pressures that co-opted contact-mediated regulatory mechanisms reliant largely on polymer mechanics.

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.

Transcriptional silencing in Saccharomyces cerevisiae: known unknowns

Transcriptional silencing in Saccharomyces cerevisiae is a persistent and highly stable form of gene repression. It involves DNA silencers and repressor proteins that bind nucleosomes. The silenced state is influenced by numerous factors including the concentration of repressors, nature of activators, architecture of regulatory elements, modifying enzymes and the dynamics of chromatin.Silencers function to increase the residence time of repressor Sir proteins at silenced domains while clustering of silenced domains enables increased concentrations of repressors and helps facilitate long-range interactions. The presence of an accessible NDR at the regulatory regions of silenced genes, the cycling of chromatin configurations at regulatory sites, the mobility of Sir proteins, and the non-uniform distribution of the Sir proteins across the silenced domain, all result in silenced chromatin that only stably silences weak promoters and enhancers via changes in transcription burst duration and frequency.These data collectively suggest that silencing is probabilistic and the robustness of silencing is achieved through sub-optimization of many different nodes of action such that a stable expression state is generated and maintained even though individual constituents are in constant flux.

Intrinsic Epigenetic State of Primary Osteosarcoma Drives Metastasis

Osteosarcoma is the most common primary malignant bone tumor affecting the pediatric population with a high potential to metastasize. However, insights into the molecular features enabling its metastatic potential are limited. We mapped the active chromatin landscapes of osteosarcoma tumors by integrating histone H3 lysine-acetylated chromatin state (n = 13), chromatin accessibility profiles (n = 11), and gene expression (n = 13) to understand the differences in their active chromatin profiles and their impact on molecular mechanisms driving the malignant phenotypes. Primary osteosarcoma tumors from patients with metastasis (primary met) have a distinct active chromatin landscape compared with those without metastasis (localized). This difference shapes the transcriptional profile of osteosarcoma. We identified novel candidate genes, including PPP1R1B, PREX1, and IGF2BP1, that exhibit increased chromatin activity in primary met. Loss of PREX1 in primary met osteosarcoma cells significantly diminishes osteosarcoma proliferation, invasion, migration, and colony formation capacity. Differential chromatin activity in primary met is associated with genes regulating cytoskeleton organization, cellular adhesion, and extracellular matrix, suggesting their role in facilitating osteosarcoma metastasis. Chromatin profiling of tumors from metastatic lung lesions shows increased chromatin activity in genes involved in cell migration and Wnt pathway. These data demonstrate that metastatic potential is intrinsically present in primary met tumors, with cellular chromatin profiles further adapting for successful dissemination, migration, and colonization at the distal site. Implications: Our study demonstrates that metastatic potential is intrinsic to primary metastatic osteosarcoma tumors, with chromatin profiles further adapting for successful dissemination, migration, and colonization at the distal metastatic site.

An integrated transcription factor framework for Treg identity and diversity

Vertebrate cell identity depends on the combined activity of scores of transcription factors (TF). While TFs have often been studied in isolation, a systematic perspective on their integration has been missing. Focusing on FoxP3+ regulatory T cells (Tregs), key guardians of immune tolerance, we combined single-cell chromatin accessibility, machine learning, and high-density genetic variation, to resolve a validated framework of diverse Treg chromatin programs, each shaped by multi-TF inputs. This framework identified previously unrecognized Treg controllers (Smarcc1) and illuminated the mechanism of action of FoxP3, which amplified a pre-existing Treg identity, diversely activating or repressing distinct programs, dependent on different regulatory partners. Treg subpopulations in the colon relied variably on FoxP3, Helios+ Tregs being completely dependent, but RORγ+ Tregs largely independent. These differences were rooted in intrinsic biases decoded by the integrated framework. Moving beyond master regulators, this work unravels how overlapping TF activities coalesce into Treg identity and diversity.

Genome binding properties of Zic transcription factors underlie their changing functions during neuronal maturation

BACKGROUND

The Zic family of transcription factors (TFs) promote both proliferation and maturation of cerebellar granule neurons (CGNs), raising the question of how a single, constitutively expressed TF family can support distinct developmental processes. Here we use an integrative experimental and bioinformatic approach to discover the regulatory relationship between Zic TF binding and changing programs of gene transcription during postnatal CGN differentiation.

RESULTS

We first established a bioinformatic pipeline to integrate Zic ChIP-seq data from the developing mouse cerebellum with other genomic datasets from the same tissue. In newborn CGNs, Zic TF binding predominates at active enhancers that are co-bound by developmentally regulated TFs including Atoh1, whereas in mature CGNs, Zic TF binding consolidates toward promoters where it co-localizes with activity-regulated TFs. We then performed CUT&RUN-seq in differentiating CGNs to define both the time course of developmental shifts in Zic TF binding and their relationship to gene expression. Mapping Zic TF binding sites to genes using chromatin looping, we identified the set of Zic target genes that have altered expression in RNA-seq from Zic1 or Zic2 knockdown CGNs.

CONCLUSIONS

Our data show that Zic TFs are required for both induction and repression of distinct, developmentally regulated target genes through a mechanism that is largely independent of changes in Zic TF binding. We suggest that the differential collaboration of Zic TFs with other TF families underlies the shift in their biological functions across CGN development.

Efficient and multiplex gene upregulation in plants through CRISPR-Cas-mediated knockin of enhancers

Gene upregulation through genome editing is important for plant research and breeding. Targeted insertion of short transcriptional enhancers (STEs) into gene promoters may offer a universal solution akin to transgene-mediated overexpression while avoiding the drawbacks associated with transgenesis. Here, we introduce an "in locus activation" technique in rice that leverages well-characterized STEs for refined, heritable, and multiplexed gene upregulation. To address the scarcity of potent enhancers, we developed a large-scale mining approach and discovered a suite of STEs that are capable of enhancing gene expression in rice protoplasts. The in locus integration of these STEs into eight rice genes resulted in substantial transcriptional upregulation in the edited plants, with up to 869.1-fold increases in their transcript levels. Employing a variety of STEs, we achieved delicate control of gene expression, enabling the fine-tuning of key phenotypic traits such as plant height. Our approach also enabled efficient multiplexed gene upregulation, with up to four genes activated simultaneously, significantly enhancing the nicotinamide mononucleotide metabolic pathway. Importantly, heritability studies from the T0 to T3 generations confirmed the stable and heritable nature of STE-driven gene activation. Collectively, our work demonstrates that coupled with STE mining, leveraging genome editing for in locus activation and gene upregulation holds great promise to be widely adopted in fundamental plant research and crop breeding.

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.

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.

Transcriptional bursting: from fundamentals to novel insights

Transcription occurs as irregular bursts in a very wide range of systems, including numerous different species and many genes within these. In this review, we examine the underlying theories, discuss how these relate to experimental measurements, and explore some of the discrepancies that have emerged among various studies. Finally, we consider more recent works that integrate novel concepts, such as the involvement of biomolecular condensates in enhancer-promoter interactions and their effects on the dynamics of transcriptional bursting.

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.

LDB1 establishes multi-enhancer networks to regulate gene expression

How specific enhancer-promoter pairing is established is still mostly unclear. Besides the CTCF/cohesin machinery, only a few nuclear factors have been studied for a direct role in physically connecting regulatory elements. Here, we show via acute degradation experiments that LDB1 directly and broadly promotes enhancer-promoter loops. Most LDB1-mediated contacts, even those spanning hundreds of kb, can form in the absence of CTCF, cohesin, or YY1 as determined via the use of multiple degron systems. Moreover, an engineered LDB1-driven chromatin loop is cohesin independent. Cohesin-driven loop extrusion does not stall at LDB1 occupied sites but may aid the formation of a subset of LDB1 anchored loops. Leveraging the dynamic reorganization of nuclear architecture during the transition from mitosis to G1-phase, we establish a relationship between LDB1-dependent interactions in the context of TAD organization and gene activation. Lastly, Tri-C and Region Capture Micro-C reveal that LDB1 organizes multi-enhancer networks to activate transcription. This establishes LDB1 as a direct driver of regulatory network inter-connectivity.

IVEA: an integrative variational Bayesian inference method for predicting enhancer-gene regulatory interactions

Motivation

Enhancers play critical roles in cell-type-specific transcriptional control. Despite the identification of thousands of candidate enhancers, unravelling their regulatory relationships with their target genes remains challenging. Therefore, computational approaches are needed to accurately infer enhancer-gene regulatory relationships.

Results

In this study, we propose a new method, IVEA, that predicts enhancer-gene regulatory interactions by estimating promoter and enhancer activities. Its statistical model is based on the gene regulatory mechanism of transcriptional bursting, which is characterized by burst size and frequency controlled by promoters and enhancers, respectively. Using transcriptional readouts, chromatin accessibility, and chromatin contact data as inputs, promoter and enhancer activities were estimated using variational Bayesian inference, and the contribution of each enhancer-promoter pair to target gene transcription was calculated. Our analysis demonstrates that the proposed method can achieve high prediction accuracy and provide biologically relevant enhancer-gene regulatory interactions.

Availability and implementation

The IVEA code is available on GitHub at https://github.com/yasumasak/ivea. The publicly available datasets used in this study are described in Supplementary Table S4.

Comprehensive network modeling approaches unravel dynamic enhancer-promoter interactions across neural differentiation

BACKGROUND

Increasing evidence suggests that a substantial proportion of disease-associated mutations occur in enhancers, regions of non-coding DNA essential to gene regulation. Understanding the structures and mechanisms of the regulatory programs this variation affects can shed light on the apparatuses of human diseases.

RESULTS

We collect epigenetic and gene expression datasets from seven early time points during neural differentiation. Focusing on this model system, we construct networks of enhancer-promoter interactions, each at an individual stage of neural induction. These networks serve as the base for a rich series of analyses, through which we demonstrate their temporal dynamics and enrichment for various disease-associated variants. We apply the Girvan-Newman clustering algorithm to these networks to reveal biologically relevant substructures of regulation. Additionally, we demonstrate methods to validate predicted enhancer-promoter interactions using transcription factor overexpression and massively parallel reporter assays.

CONCLUSIONS

Our findings suggest a generalizable framework for exploring gene regulatory programs and their dynamics across developmental processes; this includes a comprehensive approach to studying the effects of disease-associated variation on transcriptional networks. The techniques applied to our networks have been published alongside our findings as a computational tool, E-P-INAnalyzer. Our procedure can be utilized across different cellular contexts and disorders.

Integrative analysis reveals novel insights into juvenile idiopathic arthritis pathogenesis and shared molecular pathways with associated traits

Background

Juvenile idiopathic arthritis (JIA) is an autoimmune joint disease that frequently co-occurs with other complex phenotypes, including cancers and other autoimmune diseases. Despite the identification of numerous risk variants through genome-wide association studies (GWAS), the affected genes, their connection to JIA pathogenesis, and their role in the development of associated traits remain unclear. This study aims to address these gaps by elucidating the gene-regulatory mechanisms underlying JIA pathogenesis and exploring its potential role in the emergence of associated traits.

Methods

A two-sample Mendelian Randomization (MR) analysis was conducted to identify blood-expressed genes causally linked to JIA. A curated protein interaction network was subsequently used to identify sets of single-nucleotide polymorphisms (i.e., spatial eQTL SNPs) that regulate the expression of JIA causal genes and their protein interaction partners. These SNPs were cross-referenced against the GWAS catalog to identify statistically enriched traits associated with JIA.

Results

The two-sample MR analysis identified 52 genes whose expression changes in the blood are putatively causal for JIA. These genes (e.g., HLA, LTA, LTB, IL6ST) participate in a range of immune-related pathways (e.g., antigen presentation, cytokine signalling) and demonstrate cell type-specific regulatory patterns across different immune cell types (e.g., PPP1R11 in CD4+ T cells). The spatial eQTLs that regulate JIA causal genes and their interaction partners were statistically enriched for GWAS SNPs linked with 95 other traits, including both known and novel JIA-associated traits. This integrative analysis identified genes whose dysregulation may explain the links between JIA and associated traits, such as autoimmune/inflammatory diseases (genes at 6p22.1 locus), Hodgkin lymphoma (genes at 6p21.3 [FKBPL, PBX2, AGER]), and chronic lymphocytic leukemia (BAK1).

Conclusion

Our approach provides a significant advance in understanding the genetic architecture of JIA and associated traits. The results suggest that the burden of associated traits may differ among JIA patients, influenced by their combined genetic risk across different clusters of traits. Future experimental validation of the identified connections could pave the way for refined patient stratification, the discovery of new biomarkers, and shared therapeutic targets.

Long-term exposure to diesel exhaust particles induces concordant changes in DNA methylation and transcriptome in human adenocarcinoma alveolar basal epithelial cells

BACKGROUND

Diesel exhaust particles (DEP), which contain hazardous compounds, are emitted during the combustion of diesel. As approximately one-third of the vehicles worldwide use diesel, there are growing concerns about the risks posed by DEP to human health. Long-term exposure to DEP is associated with airway hyperresponsiveness, pulmonary fibrosis, and inflammation; however, the molecular mechanisms behind the effects of DEP on the respiratory tract are poorly understood. Such mechanisms can be addressed by examining transcriptional and DNA methylation changes. Although several studies have focused on the effects of short-term DEP exposure on gene expression, research on the transcriptional effects and genome-wide DNA methylation changes caused by long-term DEP exposure is lacking. Hence, in this study, we investigated transcriptional and DNA methylation changes in human adenocarcinoma alveolar basal epithelial A549 cells caused by prolonged exposure to DEP and determined whether these changes are concordant.

RESULTS

DNA methylation analysis using the Illumina Infinium MethylationEPIC BeadChips showed that the methylation levels of DEP-affected CpG sites in A549 cells changed in a dose-dependent manner; the extent of change increased with increasing dose reaching the statistical significance only in samples exposed to 30 µg/ml DEP. Four-week exposure to 30 µg/ml of DEP significantly induced DNA hypomethylation at 24,464 CpG sites, which were significantly enriched for DNase hypersensitive sites, genomic regions marked by H3K4me1 and H3K27ac, and several transcription factor binding sites. In contrast, 9,436 CpG sites with increased DNA methylation levels were significantly overrepresented in genomic regions marked by H3K27me3 as well as H3K4me1 and H3K27ac. In parallel, gene expression profiling by RNA sequencing demonstrated that long-term exposure to DEP altered the expression levels of 2,410 genes, enriching 16 gene sets including Xenobiotic metabolism, Inflammatory response, and Senescence. In silico analysis revealed that the expression levels of 854 genes correlated with the methylation levels of the DEP-affected cis-CpG sites.

CONCLUSIONS

To our knowledge, this is the first report of genome-wide transcriptional and DNA methylation changes and their associations in A549 cells following long-term exposure to DEP.

Predicting regulatory mutations and their target genes by new computational integrative analysis: A study of follicular lymphoma

Mutations in DNA regulatory regions are increasingly being recognized as important drivers of cancer and other complex diseases. These mutations can regulate gene expression by affecting DNA-protein binding and epigenetic profiles, such as DNA methylation in genome regulatory elements. However, identifying mutation hotspots associated with expression regulation and disease progression in non-coding DNA remains a challenge. Unlike most existing approaches that assign a mutation score to individual single nucleotide polymorphisms (SNP), a mutation block (MB)-based approach was introduced in this study to assess the collective impact of a cluster of SNPs on transcription factor-DNA binding affinity, differential gene expression (DEG), and nearby DNA methylation. Moreover, the long-distance target genes of functional MBs were identified using a new permutation-based algorithm that assessed the significance of correlations between DNA methylation at regulatory regions and target gene expression. Two new Python packages were developed. The Differential Methylation Region (DMR-analysis) analysis tool was used to detect DMR and map them to regulatory elements. The second tool, an integrated DMR, DEG, and SNP analysis tool (DDS-analysis), was used to combine the omics data to identify functional MBs and long-distance target genes. Both tools were validated in follicular lymphoma (FL) cohorts, where not only known functional MBs and their target genes (BCL2 and BCL6) were recovered, but also novel genes were found, including CDCA4 and JAG2, which may be associated with FL development. These genes are linked to target gene expression and are significantly correlated with the methylation of nearby DNA sequences in FL. The proposed computational integrative analysis of multiomics data holds promise for identifying regulatory mutations in cancer and other complex diseases.

Enhancers associated with unstable RNAs are rare in plants

Unstable transcripts have emerged as markers of active enhancers in vertebrates and shown to be involved in many cellular processes and medical disorders. However, their prevalence and role in plants is largely unexplored. Here, we comprehensively captured all actively initiating (nascent) transcripts across diverse crops and other plants using capped small (cs)RNA sequencing. We discovered that unstable transcripts are rare in plants, unlike in vertebrates, and when present, often originate from promoters. In addition, many 'distal' elements in plants initiate tissue-specific stable transcripts and are likely bona fide promoters of as-yet-unannotated genes or non-coding RNAs, cautioning against using reference genome annotations to infer putative enhancer sites. To investigate enhancer function, we integrated data from self-transcribing active regulatory region (STARR) sequencing. We found that annotated promoters and other regions that initiate stable transcripts, but not those marked by unstable or bidirectional unstable transcripts, showed stronger enhancer activity in this assay. Our findings underscore the blurred line between promoters and enhancers and suggest that cis-regulatory elements can encompass diverse structures and mechanisms in eukaryotes, including humans.

A single-cell multimodal view on gene regulatory network inference from transcriptomics and chromatin accessibility data

Eukaryotic gene regulation is a combinatorial, dynamic, and quantitative process that plays a vital role in development and disease and can be modeled at a systems level in gene regulatory networks (GRNs). The wealth of multi-omics data measured on the same samples and even on the same cells has lifted the field of GRN inference to the next stage. Combinations of (single-cell) transcriptomics and chromatin accessibility allow the prediction of fine-grained regulatory programs that go beyond mere correlation of transcription factor and target gene expression, with enhancer GRNs (eGRNs) modeling molecular interactions between transcription factors, regulatory elements, and target genes. In this review, we highlight the key components for successful (e)GRN inference from (sc)RNA-seq and (sc)ATAC-seq data exemplified by state-of-the-art methods as well as open challenges and future developments. Moreover, we address preprocessing strategies, metacell generation and computational omics pairing, transcription factor binding site detection, and linear and three-dimensional approaches to identify chromatin interactions as well as dynamic and causal eGRN inference. We believe that the integration of transcriptomics together with epigenomics data at a single-cell level is the new standard for mechanistic network inference, and that it can be further advanced with integrating additional omics layers and spatiotemporal data, as well as with shifting the focus towards more quantitative and causal modeling strategies.

An enhancer RNA recruits KMT2A to regulate transcription of Myb

The Myb proto-oncogene encodes the transcription factor c-MYB, which is critical for hematopoiesis. Distant enhancers of Myb form a hub of interactions with the Myb promoter. We identified a long non-coding RNA (Myrlin) originating from the -81-kb murine Myb enhancer. Myrlin and Myb are coordinately regulated during erythroid differentiation. Myrlin TSS deletion using CRISPR-Cas9 reduced Myrlin and Myb expression and LDB1 complex occupancy at the Myb enhancers, compromising enhancer contacts and reducing RNA Pol II occupancy in the locus. In contrast, CRISPRi silencing of Myrlin left LDB1 and the Myb enhancer hub unperturbed, although Myrlin and Myb expressions were downregulated, decoupling transcription and chromatin looping. Myrlin interacts with the KMT2A/MLL1 complex. Myrlin CRISPRi compromised KMT2A occupancy in the Myb locus, decreasing CDK9 and RNA Pol II binding and resulting in Pol II pausing in the Myb first exon/intron. Thus, Myrlin directly participates in activating Myb transcription by recruiting KMT2A.

MYC Binding Near Transcriptional End Sites Regulates Basal Gene Expression, Read-Through Transcription and Intragenic Contacts

The MYC oncoprotein regulates numerous genes involved in cellular processes such as cell cycle and mitochondrial and ribosomal structure and function. This requires heterodimerization with its partner, MAX, and binding to specific promoter and enhancer elements. Here, we show that MYC and MAX also bind near transcriptional end sites (TESs) of over one-sixth of all annotated genes. These interactions are dose-dependent, evolutionarily conserved, stabilize the normally short-lived MYC protein and regulate expression both in concert with and independent of MYC's binding elsewhere. MYC's TES binding occurs in association with other transcription factors, alters the chromatin landscape, increases nuclease susceptibility and can alter transcriptional read-through, particularly in response to certain stresses. MYC-bound TESs can directly contact promoters and may fine-tune gene expression in response to both physiologic and pathologic stimuli. Collectively, these findings support a previously unrecognized role for MYC in regulating transcription and its read-through via direct intragenic contacts between TESs and promoters.

Primary osteoarthritis chondrocyte map of chromatin conformation reveals novel candidate effector genes

OBJECTIVES

Osteoarthritis is a complex disease with a huge public health burden. Genome-wide association studies (GWAS) have identified hundreds of osteoarthritis-associated sequence variants, but the effector genes underpinning these signals remain largely elusive. Understanding chromosome organisation in three-dimensional (3D) space is essential for identifying long-range contacts between distant genomic features (e.g., between genes and regulatory elements), in a tissue-specific manner. Here, we generate the first whole genome chromosome conformation analysis (Hi-C) map of primary osteoarthritis chondrocytes and identify novel candidate effector genes for the disease.

METHODS

Primary chondrocytes collected from 8 patients with knee osteoarthritis underwent Hi-C analysis to link chromosomal structure to genomic sequence. The identified loops were then combined with osteoarthritis GWAS results and epigenomic data from primary knee osteoarthritis chondrocytes to identify variants involved in gene regulation via enhancer-promoter interactions.

RESULTS

We identified 345 genetic variants residing within chromatin loop anchors that are associated with 77 osteoarthritis GWAS signals. Ten of these variants reside directly in enhancer regions of 10 newly described active enhancer-promoter loops, identified with multiomics analysis of publicly available chromatin immunoprecipitation sequencing (ChIP-seq) and assay for transposase-accessible chromatin using sequencing (ATAC-seq) data from primary knee chondrocyte cells, pointing to two new candidate effector genes SPRY4 and PAPPA (pregnancy-associated plasma protein A) as well as further support for the gene SLC44A2 known to be involved in osteoarthritis. For example, PAPPA is directly associated with the turnover of insulin-like growth factor 1 (IGF-1) proteins, and IGF-1 is an important factor in the repair of damaged chondrocytes.

CONCLUSIONS

We have constructed the first Hi-C map of primary human chondrocytes and have made it available as a resource for the scientific community. By integrating 3D genomics with large-scale genetic association and epigenetic data, we identify novel candidate effector genes for osteoarthritis, which enhance our understanding of disease and can serve as putative high-value novel drug targets.

Characterization of activating cis-regulatory elements from the histone genes of Chlamydomonas reinhardtii

Regulation of gene expression in eukaryotes is controlled by cis-regulatory modules (CRMs). A major class of CRMs are enhancers which are composed of activating cis-regulatory elements (CREs) responsible for upregulating transcription. To date, most enhancers and activating CREs have been studied in angiosperms; in contrast, our knowledge about these key regulators of gene expression in green algae is limited. In this study, we aimed at characterizing putative activating CREs/CRMs from the histone genes of the unicellular model alga Chlamydomonas reinhardtii. To test the activity of four candidates, reporter constructs consisting of a tetramerized CRE, an established promoter, and a gene for the mCerulean3 fluorescent protein were incorporated into the nuclear genome of C. reinhardtii, and their activity was quantified by flow cytometry. Two tested candidates, Eupstr and Ehist cons, significantly upregulated gene expression and were characterized in detail. Eupstr, which originates from highly expressed genes of C. reinhardtii, is an orientation-independent CRE capable of activating both the RBCS2 and β2-tubulin promoters. Ehist cons, which is a CRM from histone genes of angiosperms, upregulates the β2-tubulin promoter in C. reinhardtii over a distance of at least 1.5 kb. The octamer motif present in Ehist cons was identified in C. reinhardtii and the related green algae Chlamydomonas incerta, Chlamydomonas schloesseri, and Edaphochlamys debaryana, demonstrating its high evolutionary conservation. The results of this investigation expand our knowledge about the regulation of gene expression in green algae. Furthermore, the characterized activating CREs/CRMs can be applied as valuable genetic tools.

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.

HDI-STARR-seq: Condition-specific enhancer discovery in mouse liver in vivo

Background

STARR-seq and other massively-parallel reporter assays are widely used to discover functional enhancers in transfected cell models, which can be confounded by plasmid vector-induced type-I interferon immune responses and lack the multicellular environment and endogenous chromatin state of complex mammalian tissues.

Results

Here, we describe HDI-STARR-seq, which combines STARR-seq plasmid library delivery to the liver, by hydrodynamic tail vein injection (HDI), with reporter RNA transcriptional initiation driven by a minimal Albumin promoter, which we show is essential for mouse liver STARR-seq enhancer activity assayed 7 days after HDI. Importantly, little or no vector-induced innate type-I interferon responses were observed. Comparisons of HDI-STARR-seq activity between male and female mouse livers and in livers from males treated with an activating ligand of the transcription factor CAR (Nr1i3) identified many condition-dependent enhancers linked to condition-specific gene expression. Further, thousands of active liver enhancers were identified using a high complexity STARR-seq library comprised of ~ 50,000 genomic regions released by DNase-I digestion of mouse liver nuclei. When compared to stringently inactive library sequences, the active enhancer sequences identified were highly enriched for liver open chromatin regions with activating histone marks (H3K27ac, H3K4me1, H3K4me3), were significantly closer to gene transcriptional start sites, and were significantly depleted of repressive (H3K27me3, H3K9me3) and transcribed region histone marks (H3K36me3).

Conclusions

HDI-STARR-seq offers substantial improvements over current methodologies for large scale, functional profiling of enhancers, including condition-dependent enhancers, in liver tissue in vivo, and can be adapted to characterize enhancer activities in a variety of species and tissues by selecting suitable tissue- and species-specific promoter sequences.

Transcriptional response to an alternative diet on liver, muscle, and rumen of beef cattle

Feed cost represents a major economic determinant within cattle production, amounting to an estimated 75% of the total variable costs. Consequently, comprehensive approaches such as optimizing feed utilization through alternative feed sources, alongside the selection of feed-efficient animals, are of great significance. Here, we investigate the effect of two diets, traditional corn-grain fed and alternative by-product based, on 14 phenotypes related to feed, methane emission and production efficiency and on multi-tissue transcriptomics data from liver, muscle, and rumen wall, derived from 52 Nellore bulls, 26 on each diet. To this end, diets were contrasted at the level of phenotype, gene expression, and gene-phenotype network connectivity. As regards the phenotypic level, at a P value < 0.05, significant differences were found in favour of the alternative diet for average daily weight gain at finishing, dry matter intake at finishing, methane emission, carcass yield and subcutaneous fat thickness at the rib-eye muscle area. In terms of the transcriptional level of the 14,776 genes expressed across the examined tissues, we found 487, 484, and 499 genes differentially expressed due to diet in liver, muscle, and rumen, respectively (P value < 0.01). To explore differentially connected phenotypes across both diet-based networks, we focused on the phenotypes with the largest change in average number of connections within diets and tissues, namely methane emission and carcass yield, highlighting, in particular, gene expression changes involving SREBF2, and revealing the largest differential connectivity in rumen and muscle, respectively. Similarly, from examination of differentially connected genes across diets, the top-ranked most differentially connected regulators within each tissue were MEOX1, PTTG1, and BASP1 in liver, muscle, and rumen, respectively. Changes in gene co-expression patterns suggest activation or suppression of specific biological processes and pathways in response to dietary interventions, consequently impacting the phenotype. The identification of genes that respond differently to diets and their associated phenotypic effects serves as a crucial stepping stone for further investigations, aiming to build upon our discoveries. Ultimately, such advancements hold the promise of improving animal welfare, productivity, and sustainability in livestock farming.

HDI-STARR-seq: Condition-specific enhancer discovery in mouse liver in vivo

STARR-seq and other massively-parallel reporter assays are widely used to discover functional enhancers in transfected cell models, which can be confounded by plasmid vector-induced type-I interferon immune responses and lack the multicellular environment and endogenous chromatin state of complex mammalian tissues. Here, we describe HDI-STARR-seq, which combines STARR-seq plasmid library delivery to the liver, by hydrodynamic tail vein injection (HDI), with reporter RNA transcriptional initiation driven by a minimal Albumin promoter, which we show is essential for mouse liver STARR-seq enhancer activity assayed 7 days after HDI. Importantly, little or no vector-induced innate type-I interferon responses were observed. Comparisons of HDI-STARR-seq activity between male and female mouse livers and in livers from males treated with an activating ligand of the transcription factor CAR (Nr1i3) identified many condition-dependent enhancers linked to condition-specific gene expression. Further, thousands of active liver enhancers were identified using a high complexity STARR-seq library comprised of ~50,000 genomic regions released by DNase-I digestion of mouse liver nuclei. When compared to stringently inactive library sequences, the active enhancer sequences identified were highly enriched for liver open chromatin regions with activating histone marks (H3K27ac, H3K4me1, H3K4me3), were significantly closer to gene transcriptional start sites, and were significantly depleted of repressive (H3K27me3, H3K9me3) and transcribed region histone marks (H3K36me3). HDI-STARR-seq offers substantial improvements over current methodologies for large scale, functional profiling of enhancers, including condition-dependent enhancers, in liver tissue in vivo, and can be adapted to characterize enhancer activities in a variety of species and tissues by selecting suitable tissue- and species-specific promoter sequences.

Three-dimensional chromatin mapping of sensory neurons reveals that cohesin-dependent genomic domains are 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 programme at homeostasis and after sciatic nerve injury in wild-type and cohesin-deficient mouse sensory dorsal root ganglia neurons via combinatorial Hi-C and RNA-seq. We find that cohesin is required for the full induction of the regenerative transcriptional program, by organising 3D genomic domains required for the activation of regenerative genes. Importantly, loss of cohesin results in disruption of chromatin architecture at regenerative genes and severely impaired nerve regeneration. Together, these data provide an original three-dimensional chromatin map of adult sensory neurons in vivo and demonstrate a role for cohesin-dependent chromatin interactions in neuronal regeneration.

Placental co-transcriptional activator Vestigial-like 1 (VGLL1) drives tumorigenesis via increasing transcription of proliferation and invasion genes

Introduction

Vestigial-like 1 (VGLL1) is a co-transcriptional activator that binds to TEA domain-containing transcription factors (TEADs). Its expression is upregulated in a variety of aggressive cancer types, including pancreatic and basal-like breast cancer, and increased transcription of VGLL1 is strongly correlated with poor prognosis and decreased overall patient survival. In normal tissues, VGLL1 is most highly expressed within placental trophoblast cells, which share the common attributes of rapid cellular proliferation and invasion with tumor cells. The impact of VGLL1 in cancer has not been fully elucidated and no VGLL1-targeted therapy currently exists.

Methods

The aim of this study was to evaluate the cellular function and downstream genomic targets of VGLL1 in placental, pancreatic, and breast cancer cells. Functional assays were employed to assess the role of VGLL1 in cellular invasion and proliferation, and ChIP-seq and RNAseq assays were performed to identify VGLL1 target genes and potential impact using pathway analysis.

Results

ChIP-seq analysis identified eight transcription factors with a VGLL1-binding motif that were common between all three cell types, including TEAD1-4, AP-1, and GATA6, and revealed ~3,000 shared genes with which VGLL1 interacts. Furthermore, increased VGLL1 expression led to an enhancement of cell invasion and proliferation, which was supported by RNAseq analysis showing transcriptional changes in several genes known to be involved in these processes.

Discussion

This work expands our mechanistic understanding of VGLL1 function in tumor cells and provides a strong rationale for developing VGLL1-targeted therapies for treating cancer patients.

Multiscale Bayesian simulations reveal functional chromatin condensation of gene loci

Chromatin, the complex assembly of DNA and associated proteins, plays a pivotal role in orchestrating various genomic functions. To aid our understanding of the principles underlying chromatin organization, we introduce Hi-C metainference, a Bayesian approach that integrates Hi-C contact frequencies into multiscale prior models of chromatin. This approach combines both bottom-up (the physics-based prior) and top-down (the data-driven posterior) strategies to characterize the 3D organization of a target genomic locus. We first demonstrate the capability of this method to accurately reconstruct the structural ensemble and the dynamics of a system from contact information. We then apply the approach to investigate the Sox2, Pou5f1, and Nanog loci of mouse embryonic stem cells using a bottom-up chromatin model at 1 kb resolution. We observe that the studied loci are conformationally heterogeneous and organized as crumpled globules, favoring contacts between distant enhancers and promoters. Using nucleosome-resolution simulations, we then reveal how the Nanog gene is functionally organized across the multiple scales of chromatin. At the local level, we identify diverse tetranucleosome folding motifs with a characteristic distribution along the genome, predominantly open at cis-regulatory elements and compact in between. At the larger scale, we find that enhancer-promoter contacts are driven by the transient condensation of chromatin into compact domains stabilized by extensive internucleosome interactions. Overall, this work highlights the condensed, but dynamic nature of chromatin in vivo, contributing to a deeper understanding of gene structure-function relationships.