PROTAC-DB 3.0: an updated database of PROTACs with extended pharmacokinetic parameters.

Proteolysis-targeting chimera (PROTAC) is an emerging therapeutic technology that leverages the ubiquitin-proteasome system to target protein degradation. Due to its event-driven mechanistic characteristics, PROTAC has the potential to regulate traditionally non-druggable targets. Recently, AI-aided drug design has accelerated the development of PROTAC drugs. However, the rational design of PROTACs remains a considerable challenge. Here, we present an updated online database, PROTAC-DB 3.0. In this third version, we have expanded the database to include 6111 PROTACs (87% increase compared to the 2.0 version). Additionally, the database now contains 569 warheads (small molecules targeting the protein), 2753 linkers, and 107 E3 ligands (small molecules recruiting E3 ligases). The number of target-PROTAC-E3 ternary complex structures has also increased to 959. Recognizing the importance of druggability in PROTAC design, we have incorporated pharmacokinetic data to PROTAC-DB 3.0. To enhance user experience, we have added features for sorting based on molecular similarity and literature publication date. PROTAC-DB 3.0 is accessible at http://cadd.zju.edu.cn/protacdb/.

Occlusion enhanced pan-cancer classification via deep learning.

Quantitative measurement of RNA expression levels through RNA-Seq is an ideal replacement for conventional cancer diagnosis via microscope examination. Currently, cancer-related RNA-Seq studies focus on two aspects: classifying the status and tissue of origin of a sample and discovering marker genes. Existing studies typically identify marker genes by statistically comparing healthy and cancer samples. However, this approach overlooks marker genes with low expression level differences and may be influenced by experimental results. This paper introduces "GENESO," a novel framework for pan-cancer classification and marker gene discovery using the occlusion method in conjunction with deep learning. we first trained a baseline deep LSTM neural network capable of distinguishing the origins and statuses of samples utilizing RNA-Seq data. Then, we propose a novel marker gene discovery method called "Symmetrical Occlusion (SO)". It collaborates with the baseline LSTM network, mimicking the "gain of function" and "loss of function" of genes to evaluate their importance in pan-cancer classification quantitatively. By identifying the genes of utmost importance, we then isolate them to train new neural networks, resulting in higher-performance LSTM models that utilize only a reduced set of highly relevant genes. The baseline neural network achieves an impressive validation accuracy of 96.59% in pan-cancer classification. With the help of SO, the accuracy of the second network reaches 98.30%, while using 67% fewer genes. Notably, our method excels in identifying marker genes that are not differentially expressed. Moreover, we assessed the feasibility of our method using single-cell RNA-Seq data, employing known marker genes as a validation test.

Unlocking cardioprotection: iPSC exosomes deliver Nec-1 to target PARP1/AIFM1 axis, alleviating HF oxidative stress and mitochondrial dysfunction.

BACKGROUND: Heart failure (HF) is characterized by oxidative stress and mitochondrial dysfunction. This study investigates the therapeutic potential of Necrostatin-1 (Nec-1) delivered through exosomes derived from induced pluripotent stem cells (iPSCs) to address these pathologies in HF. METHODS: An HF rat model was established, and comprehensive assessments were performed using echocardiography, hemodynamics, and ventricular mass index measurements. iPSCs were used to isolate exosomes, loaded with Nec-1, and characterized for efficient delivery into cardiomyocytes. The interaction between Nec-1-loaded exosomes (Nec-1-Exos), poly (ADP-ribose) polymerase 1 (PARP1), and apoptosis-inducing factor mitochondria-associated 1 (AIFM1) was explored. Gain-of-function experiments assessed changes in cardiomyocyte parameters, and histological analyses were conducted on myocardial tissues. RESULTS: Cardiomyocytes successfully internalized Nec-1-loaded exosomes, leading to downregulation of PARP1, inhibition of AIFM1 nuclear translocation, increased ATP and superoxide dismutase levels, reduced reactive oxygen species and malonaldehyde levels, and restored mitochondrial membrane potential. Histological examinations confirmed the modulation of the PARP1/AIFM1 axis by Nec-1, mitigating HF. CONCLUSIONS: iPSC-derived exosomes carrying Nec-1 attenuate oxidative stress and mitochondrial dysfunction in HF by targeting the PARP1/AIFM1 axis. This study proposes a promising therapeutic strategy for HF management and highlights the potential of exosome-mediated drug delivery.

The design, synthesis and bioactivity evaluation of novel androgen receptor degraders based on hydrophobic tagging.

Prostate Cancer (PCa) easily progress to metastatic Castration-Resistant Prostate Cancer (mCRPC) that remains a significant cause of cancer-related death. Androgen receptor (AR)-dependent transcription is a major driver of prostate tumor cell proliferation. Proteolysis-targeting chimaera (PROTAC) technology based on Hydrophobic Tagging (HyT) represents an intriguing strategy to regulate the function of therapeutically androgen receptor proteins. In the present study, we have designed, synthesized, and evaluated a series of PROTAC-HyT AR degraders using AR antagonists, RU59063, which were connected with adamantane-based hydrophobic moieties by different alkyl chains. Compound D-4-6 exhibited significant AR protein degradation activity, with a degradation rate of 57 % at 5 µM and nearly 90 % at 20 µM in 24 h, and inhibited the proliferation of LNCaP cells significantly with an IC50 value of 4.77 ± 0.26 µM in a time-concentration-dependent manner. In conclusion, the present study lays the foundation for the development of a completely new class of therapeutic agents for the treatment of mCRPC, and further design and synthesis of AR-targeting degraders are currently in progress for better degradation rate.

BMAL1 moonlighting as a gatekeeper for LINE1 repression and cellular senescence in primates.

Aging in humans is intricately linked with alterations in circadian rhythms concomitant with physiological decline and stem cell exhaustion. However, whether the circadian machinery directly regulates stem cell aging, especially in primates, remains poorly understood. In this study, we found that deficiency of BMAL1, the only non-redundant circadian clock component, results in an accelerated aging phenotype in both human and cynomolgus monkey mesenchymal progenitor cells (MPCs). Unexpectedly, this phenotype was mainly attributed to a transcription-independent role of BMAL1 in stabilizing heterochromatin and thus preventing activation of the LINE1-cGAS-STING pathway. In senescent primate MPCs, we observed decreased capacity of BMAL1 to bind to LINE1 and synergistic activation of LINE1 expression. Likewise, in the skin and muscle tissues from the BMAL1-deficient cynomolgus monkey, we observed destabilized heterochromatin and aberrant LINE1 transcription. Altogether, these findings uncovered a noncanonical role of BMAL1 in stabilizing heterochromatin to inactivate LINE1 that drives aging in primate cells.

YY1 regulates skeletal muscle regeneration through controlling metabolic reprogramming of satellite cells.

Skeletal muscle satellite cells (SCs) are adult muscle stem cells responsible for muscle regeneration after acute or chronic injuries. The lineage progression of quiescent SC toward activation, proliferation, and differentiation during the regeneration is orchestrated by cascades of transcription factors (TFs). Here, we elucidate the function of TF Yin Yang1 (YY1) in muscle regeneration. Muscle-specific deletion of YY1 in embryonic muscle progenitors leads to severe deformity of diaphragm muscle formation, thus neonatal death. Inducible deletion of YY1 in SC almost completely blocks the acute damage-induced muscle repair and exacerbates the chronic injury-induced dystrophic phenotype. Examination of SC revealed that YY1 loss results in cell-autonomous defect in activation and proliferation. Mechanistic search revealed that YY1 binds and represses mitochondrial gene expression. Simultaneously, it also stabilizes Hif1α protein and activates Hif1α-mediated glycolytic genes to facilitate a metabolic reprogramming toward glycolysis which is needed for SC proliferation. Altogether, our findings have identified YY1 as a key regulator of SC metabolic reprogramming through its dual roles in modulating both mitochondrial and glycolytic pathways.

NAMS webserver: coding potential assessment and functional annotation of plant transcripts.

Recent advances in transcriptomics have uncovered lots of novel transcripts in plants. To annotate such transcripts, dissecting their coding potential is a critical step. Computational approaches have been proven fruitful in this task; however, most current tools are designed/optimized for mammals and only a few of them have been tested on a limited number of plant species. In this work, we present NAMS webserver, which contains a novel coding potential classifier, NAMS, specifically optimized for plants. We have evaluated the performance of NAMS using a comprehensive dataset containing more than 3 million transcripts from various plant species, where NAMS demonstrates high accuracy and remarkable performance improvements over state-of-the-art software. Moreover, our webserver also furnishes functional annotations, aiming to provide users informative clues to the functions of their transcripts. Considering that most plant species are poorly characterized, our NAMS webserver could serve as a valuable resource to facilitate the transcriptomic studies. The webserver with testing dataset is freely available at http://sunlab.cpy.cuhk.edu.hk/NAMS/.

Large scale RNA-binding proteins/LncRNAs interaction analysis to uncover lncRNA nuclear localization mechanisms.

Long non-coding RNAs (lncRNAs) are key regulators of major biological processes and their functional modes are dictated by their subcellular localization. Relative nuclear enrichment of lncRNAs compared to mRNAs is a prevalent phenomenon but the molecular mechanisms governing their nuclear retention in cells remain largely unknown. Here in this study, we harness the recently released eCLIP data for a large number of RNA-binding proteins (RBPs) in K562 and HepG2 cells and utilize multiple bioinformatics methods to comprehensively survey the roles of RBPs in lncRNA nuclear retention. We identify an array of splicing RBPs that bind to nuclear-enriched lincRNAs (large intergenic non-coding RNAs) thus may act as trans-factors regulating their nuclear retention. Further analyses reveal that these RBPs may bind with distinct core motifs, flanking sequence compositions, or secondary structures to drive lincRNA nuclear retention. Moreover, network analyses uncover potential co-regulatory RBP clusters and the physical interaction between HNRNPU and SAFB2 proteins in K562 cells is further experimentally verified. Altogether, our analyses reveal previously unknown factors and mechanisms that govern lincRNA nuclear localization in cells.

Computationally guided discovery of novel non-steroidal AR-GR dual antagonists demonstrating potency against antiandrogen resistance.

As a major class of medicine for treating the lethal type of castration-resistant prostate cancer (PCa), long-term use of androgen receptor (AR) antagonists commonly leads to antiandrogen resistance. When AR signaling pathway is blocked by AR-targeted therapy, glucocorticoid receptor (GR) could compensate for AR function especially at the late stage of PCa. AR-GR dual antagonist is expected to be a good solution for this situation. Nevertheless, no effective non-steroidal AR-GR dual antagonist has been reported so far. In this study, an AR-GR dual binder H18 was first discovered by combining structure-based virtual screening and biological evaluation. Then with the aid of computationally guided design, the AR-GR dual antagonist HD57 was finally identified with antagonistic activity towards both AR (IC50 = 0.394 µM) and GR (IC50 = 17.81 µM). Moreover, HD57 could effectively antagonize various clinically relevant AR mutants. Further molecular dynamics simulation provided more atomic insights into the mode of action of HD57. Our research presents an efficient and rational strategy for discovering novel AR-GR dual antagonists, and the new scaffold provides important clues for the development of novel therapeutics for castration-resistant PCa.

Role of hsa_circ_0000280 in regulating vascular smooth muscle cell function and attenuating neointimal hyperplasia via ELAVL1.

The pathological proliferation of cells in vascular smooth muscle underlies neointimal hyperplasia (NIH) development during atherosclerosis. Circular RNAs (circRNAs), which represent novel functional biomarkers and RNA-binding proteins, contribute to multiple cardiovascular diseases; however, their roles in regulating the vascular smooth muscle cell cycle remain unknown. Thus, we aimed to identify the roles of circRNAs in vascular smooth muscle during coronary heart disease (CHD). Through circRNA sequencing of CHD samples and human antigen R (ELAVL1) immunoprecipitation, we identified circRNAs that are associated with CHD and interact with ELAVL1. Our results suggested that the hsa_circ_0000280 associated with CHD inhibits cell proliferation and induces ELAVL1-dependent cell cycle arrest. Gain/loss-of-function experiments and assays in vivo indicated that hsa_circ_0000280 facilitates interactions between ELAVL1 and cyclin-dependent kinase suppressor 1 (CDKN1A) mRNA and stabilization of this complex and leads to cell cycle arrest at the G1/S checkpoint, inhibiting cell proliferation of vascular smooth muscle cells in vitro and NIH in vivo. Importantly, hsa_circ_0000280 reduced neointimal thickness and smooth muscle cell proliferation in vivo. Taken together, these findings reveal a novel pathway in which hsa_circ_0000280 facilitates the regulation of ELAVL1 on CDKN1A mRNA to inhibit NIH. Therefore, measuring and modulating their expression might represent a potential diagnostic or therapeutic strategy for CHD.

Concurrent binding to DNA and RNA facilitates the pluripotency reprogramming activity of Sox2.

Some transcription factors that specifically bind double-stranded DNA appear to also function as RNA-binding proteins. Here, we demonstrate that the transcription factor Sox2 is able to directly bind RNA in vitro as well as in mouse and human cells. Sox2 targets RNA via a 60-amino-acid RNA binding motif (RBM) positioned C-terminally of the DNA binding high mobility group (HMG) box. Sox2 can associate with RNA and DNA simultaneously to form ternary RNA/Sox2/DNA complexes. Deletion of the RBM does not affect selection of target genes but mitigates binding to pluripotency related transcripts, switches exon usage and impairs the reprogramming of somatic cells to a pluripotent state. Our findings designate Sox2 as a multi-functional factor that associates with RNA whilst binding to cognate DNA sequences, suggesting that it may co-transcriptionally regulate RNA metabolism during somatic cell reprogramming.

Single-cell RNA sequencing analysis to characterize cells and gene expression landscapes in atrial septal defect.

This study aimed to characterize the cells and gene expression landscape in atrial septal defect (ASD). We performed single-cell RNA sequencing of cells derived from cardiac tissue of an ASD patient. Unsupervised clustering analysis was performed to identify different cell populations, followed by the investigation of the cellular crosstalk by analysing ligand-receptor interactions across cell types. Finally, differences between ASD and normal samples for all cell types were further investigated. An expression matrix of 18,411 genes in 6487 cells was obtained and used in this analysis. Five cell types, including cardiomyocytes, endothelial cells, smooth muscle cells, fibroblasts and macrophages were identified. ASD showed a decreased proportion of cardiomyocytes and an increased proportion of fibroblasts. There was more cellular crosstalk among cardiomyocytes, fibroblasts and macrophages, especially between fibroblast and macrophage. For all cell types, the majority of the DEGs were downregulated in ASD samples. For cardiomyocytes, there were 199 DEGs (42 upregulated and 157 downregulated) between ASD and normal samples. PPI analysis showed that cardiomyocyte marker gene FABP4 interacted with FOS, while FOS showed interaction with NPPA. Cell trajectory analysis showed that FABP4, FOS, and NPPA showed different expression changes along the pseudotime trajectory. Our results showed that single-cell RNA sequencing provides a powerful tool to study DEG profiles in the cell subpopulations of interest at the single-cell level. These findings enhance the understanding of the underlying mechanisms of ASD at both the cellular and molecular level and highlight potential targets for the treatment of ASD.

Capturing the interactome of newly transcribed RNA.

We combine the labeling of newly transcribed RNAs with 5-ethynyluridine with the characterization of bound proteins. This approach, named capture of the newly transcribed RNA interactome using click chemistry (RICK), systematically captures proteins bound to a wide range of RNAs, including nascent RNAs and traditionally neglected nonpolyadenylated RNAs. RICK has identified mitotic regulators amongst other novel RNA-binding proteins with preferential affinity for nonpolyadenylated RNAs, revealed a link between metabolic enzymes/factors and nascent RNAs, and expanded the known RNA-bound proteome of mouse embryonic stem cells. RICK will facilitate an in-depth interrogation of the total RNA-bound proteome in different cells and systems.

SKmDB: an integrated database of next generation sequencing information in skeletal muscle.

MOTIVATION: Skeletal muscles have indispensable functions and also possess prominent regenerative ability. The rapid emergence of Next Generation Sequencing (NGS) data in recent years offers us an unprecedented perspective to understand gene regulatory networks governing skeletal muscle development and regeneration. However, the data from public NGS database are often in raw data format or processed with different procedures, causing obstacles to make full use of them. RESULTS: We provide SKmDB, an integrated database of NGS information in skeletal muscle. SKmDB not only includes all NGS datasets available in the human and mouse skeletal muscle tissues and cells, but also provide preliminary data analyses including gene/isoform expression levels, gene co-expression subnetworks, as well as assembly of putative lincRNAs, typical and super enhancers and transcription factor hotspots. Users can efficiently search, browse and visualize the information with the well-designed user interface and server side. SKmDB thus will offer wet lab biologists useful information to study gene regulatory mechanisms in the field of skeletal muscle development and regeneration. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://sunlab.cpy.cuhk.edu.hk/SKmDB. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Therapeutic potential of a novel prodrug of green tea extract in induction of apoptosis via ERK/JNK and Akt signaling pathway in human endometrial cancer.

BACKGROUND: Previous studies have shown a major green tea polyphenol (-)-epigallocatechin-3-gallate ((-)-EGCG) as a powerful anti-cancer agent. However, its poor bioavailability and requirement of a high dosage to manifest activity have restricted its clinical application. Recently, our team synthesized a peracetate-protected derivative of EGCG, which can act as a prodrug of (-)-EGCG (ProEGCG) with enhanced stability and improved bioavailability in vitro and in vivo. Herein, we tested the therapeutic efficacy of this novel ProEGCG, in comparison to EGCG, toward human endometrial cancer (EC). METHODS: In this study, the effects of ProEGCG and EGCG treatments on cell growth, cell survival and modulation of intracellular signaling pathways in RL95-2 and AN3 CA EC cells were compared. The antiproliferative effect was evaluated by cell viability assay. Apoptosis was measured by annexin/propidium iodide staining. Expression of mitogen-activated protein kinases, markers of proliferation and apoptosis were measured by immunoblot analysis. In addition, the effects of ProEGCG and EGCG on tumor growth, vessel formation and gene expression profiles on xenograft models of the EC cells were investigated. RESULTS: We found that treatment with ProEGCG, but not EGCG, inhibited, in a time- and dose-dependent manner, the proliferation and increased apoptosis of EC cells. Treatment with low-dose ProEGCG significantly enhanced phosphorylation of JNK and p38 MAPK and inhibited phosphorylation of Akt and ERK which are critical mediators of apoptosis. ProEGCG, but not EGCG, elicited a significant decrease in the growth of the EC xenografts, promoted apoptotic activity of tumour cells in the EC xenografts, and decreased microvessel formation, by differentially suppressing anti-apoptotic molecules, NOD1 and NAIP. Notably, no obvious adverse effects were detected. CONCLUSIONS: Taken together, ProEGCG at a low dose exhibited anticancer activity in EC cells through its anti-proliferative, pro-apoptotic and anti-tumor actions on endometrial cancer in vitro and in vivo. In contrast, a low dose of EGCG did not bring about similar effects. Importantly, our data demonstrated the efficacy and safety of ProEGCG which manifests the potential of a novel anticancer agent for the management of endometrial cancer.

IL-33 induces production of autoantibody against autologous respiratory epithelial cells: a potential mechanism for the pathogenesis of COPD.

The mechanisms underlying the chronic, progressive airways inflammation, remodelling and alveolar structural damage characteristic of human chronic obstructive pulmonary disease (COPD) remain unclear. In the present study, we address the hypothesis that these changes are at least in part mediated by respiratory epithelial alarmin (IL-33)-induced production of autoantibodies against airways epithelial cells. Mice immunized with homologous, syngeneic lung tissue lysate along with IL-33 administered directly to the respiratory tract or systemically produced IgG autoantibodies binding predominantly to their own alveolar type II epithelial cells, along with increased percentages of Tfh cells and B2 B-cells in their local, mediastinal lymph nodes. Consistent with its specificity for respiratory epithelial cells, this autoimmune inflammation was confined principally to the lung and not other organs such as the liver and kidney. Furthermore, the serum autoantibodies produced by the mice bound not only to murine, but also to human alveolar type II epithelial cells, suggesting specificity for common, cross-species determinants. Finally, concentrations of antibodies against both human and murine alveolar epithelial cells were significantly elevated in the serum of patients with COPD compared with those of control subjects. These data are consistent with the hypothesis that IL-33 contributes to the chronic, progressive airways obstruction, inflammation and alveolar destruction characteristic of phenotypes of COPD/emphysema through induction of autoantibodies against lung tissue, and particularly alveolar type II epithelial cells.

lncFunTK: a toolkit for functional annotation of long noncoding RNAs.

Motivation: Thousands of long noncoding RNAs (lncRNAs) were newly identified from high throughput RNA-seq data. Functional annotation and prioritization of these lncRNAs for further experimental validation as well as the functional investigation is the bottleneck step for many noncoding RNA studies. Results: Here we describe lncFunTK that can run either as standard application or webserver for this purpose. It integrates high throughput sequencing data (i.e. ChIP-seq, CLIP-seq and RNA-seq) to construct the regulatory network associated with lncRNAs. Through the network, it calculates the Functional Information Score (FIS) of each individual lncRNA for prioritizing and inferring its functions through Gene Ontology (GO) terms of neighboring genes. In addition, it also provides utility scripts to support the input data preprocessing and the parameter optimizing. We further demonstrate that lncFunTK can be widely used in various biological systems for lncRNA prioritization and functional annotation. Availability and implementation: The lncFunTK standalone version is an open source package and freely available at http://sunlab.cpy.cuhk.edu.hk/lncfuntk under the MIT license. A webserver implementation is also available at http://sunlab.cpy.cuhk.edu.hk/lncfuntk/runlncfuntk.html. Supplementary information: Supplementary data are available at Bioinformatics online.

GeneCT: a generalizable cancerous status and tissue origin classifier for pan-cancer biopsies.

Motivation: Tissue biopsy is commonly used in cancer diagnosis and molecular studies. However, advanced skills are required for determining cancerous status of biopsies and tissue origin of tumor for cancerous ones. Correct classification is essential for downstream experiment design and result interpretation, especially in molecular cancer studies. Methods for accurate classification of cancerous status and tissue origin for pan-cancer biopsies are thus urgently needed. Results: We developed a deep learning-based classifier, named GeneCT, for predicting cancerous status and tissue origin of pan-cancer biopsies. GeneCT showed high performance on pan-cancer datasets from various sources and outperformed existing tools. We believe that GeneCT can potentially facilitate cancer diagnosis, tumor origin determination and molecular cancer studies. Availability and implementation: GeneCT is implemented in Perl/R and supported on GNU/Linux platforms. Source code, testing data and webserver are freely available at http://sunlab.cpy.cuhk.edu.hk/GeneCT/. Supplementary information: Supplementary data are available at Bioinformatics online.

LncFunNet: an integrated computational framework for identification of functional long noncoding RNAs in mouse skeletal muscle cells.

Long noncoding RNAs (lncRNAs) are key regulators of diverse cellular processes. Recent advances in high-throughput sequencing have allowed for an unprecedented discovery of novel lncRNAs. To identify functional lncRNAs from thousands of candidates for further functional validation is still a challenging task. Here, we present a novel computational framework, lncFunNet (lncRNA Functional inference through integrated Network) that integrates ChIP-seq, CLIP-seq and RNA-seq data to predict, prioritize and annotate lncRNA functions. In mouse embryonic stem cells (mESCs), using lncFunNet we not only recovered most of the functional lncRNAs known to maintain mESC pluripotency but also predicted a plethora of novel functional lncRNAs. Similarly, in mouse myoblast C2C12 cells, applying lncFunNet led to prediction of reservoirs of functional lncRNAs in both proliferating myoblasts (MBs) and differentiating myotubes (MTs). Further analyses demonstrated that these lncRNAs are frequently bound by key transcription factors, interact with miRNAs and constitute key nodes in biological network motifs. Further experimentations validated their dynamic expression profiles and functionality during myoblast differentiation. Collectively, our studies demonstrate the use of lncFunNet to annotate and identify functional lncRNAs in a given biological system.

MyoD- and FoxO3-mediated hotspot interaction orchestrates super-enhancer activity during myogenic differentiation.

Super-enhancers (SEs) are cis-regulatory elements enriching lineage specific key transcription factors (TFs) to form hotspots. A paucity of identification and functional dissection promoted us to investigate SEs during myoblast differentiation. ChIP-seq analysis of histone marks leads to the uncovering of SEs which remodel progressively during the course of differentiation. Further analyses of TF ChIP-seq enable the definition of SE hotspots co-bound by the master TF, MyoD and other TFs, among which we perform in-depth dissection for MyoD/FoxO3 interaction in driving the hotspots formation and SE activation. Furthermore, using Myogenin as a model locus, we elucidate the hierarchical and complex interactions among hotspots during the differentiation, demonstrating SE function is propelled by the physical and functional cooperation among hotspots. Finally, we show MyoD and FoxO3 are key in orchestrating the Myogenin hotspots interaction and activation. Altogether our results identify muscle-specific SEs and provide mechanistic insights into the functionality of SE.