dbSUPER: a database of super-enhancers in mouse and human genome

TFTG: A comprehensive database for human transcription factors and their targets

Transcription factors (TFs) are major contributors to gene transcription, especially in controlling cell-specific gene expression and disease occurrence and development. Uncovering the relationship between TFs and their target genes is critical to understanding the mechanism of action of TFs. With the development of high-throughput sequencing techniques, a large amount of TF-related data has accumulated, which can be used to identify their target genes. In this study, we developed TFTG (Transcription Factor and Target Genes) database (http://tf.liclab.net/TFTG), which aimed to provide a large number of available human TF-target gene resources by multiple strategies, besides performing a comprehensive functional and epigenetic annotations and regulatory analyses of TFs. We identified extensive available TF-target genes by collecting and processing TF-associated ChIP-seq datasets, perturbation RNA-seq datasets and motifs. We also obtained experimentally confirmed relationships between TF and target genes from available resources. Overall, the target genes of TFs were obtained through integrating the relevant data of various TFs as well as fourteen identification strategies. Meanwhile, TFTG was embedded with user-friendly search, analysis, browsing, downloading and visualization functions. TFTG is designed to be a convenient resource for exploring human TF-target gene regulations, which will be useful for most users in the TF and gene expression regulation research.

ImAge quantitates aging and rejuvenation

For efficient, cost-effective and personalized healthcare, biomarkers that capture aspects of functional, biological aging, thus predicting disease risk and lifespan more accurately and reliably than chronological age, are essential. We developed an imaging-based chromatin and epigenetic age (ImAge) that captures intrinsic age-related trajectories of the spatial organization of chromatin and epigenetic marks in single nuclei, in mice. We show that such trajectories readily emerge as principal changes in each individual dataset without regression on chronological age, and that ImAge can be computed using several epigenetic marks and DNA labeling. We find that interventions known to affect biological aging induce corresponding effects on ImAge, including increased ImAge upon chemotherapy treatment and decreased ImAge upon caloric restriction and partial reprogramming by transient OSKM expression in liver and skeletal muscle. Further, ImAge readouts from chronologically identical mice inversely correlated with their locomotor activity, suggesting that ImAge may capture elements of biological and functional age. In sum, we developed ImAge, an imaging-based biomarker of aging with single-cell resolution rooted in the analysis of spatial organization of epigenetic marks.

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.

Ageing-Related Changes to H3K4me3, H3K27ac, and H3K27me3 in Purified Mouse Neurons

Neurons are central to lifelong learning and memory, but ageing disrupts their morphology and function, leading to cognitive decline. Although epigenetic mechanisms are known to play crucial roles in learning and memory, neuron-specific genome-wide epigenetic maps into old age remain scarce, often being limited to whole-brain homogenates and confounded by glial cells. Here, we mapped H3K4me3, H3K27ac, and H3K27me3 in mouse neurons across their lifespan. This revealed stable H3K4me3 and global losses of H3K27ac and H3K27me3 into old age. We observed patterns of synaptic function gene deactivation, regulated through the loss of the active mark H3K27ac, but not H3K4me3. Alongside this, embryonic development loci lost repressive H3K27me3 in old age. This suggests a loss of a highly refined neuronal cellular identity linked to global chromatin reconfiguration. Collectively, these findings indicate a key role for epigenetic regulation in neurons that is inextricably linked with ageing.

Super-enhancer omics in stem cell

The hallmarks of stem cells, such as proliferation, self-renewal, development, differentiation, and regeneration, are critical to maintain stem cell identity which is sustained by genetic and epigenetic factors. Super-enhancers (SEs), which consist of clusters of active enhancers, play a central role in maintaining stemness hallmarks by specifically transcriptional model. The SE-navigated transcriptional complex, including SEs, non-coding RNAs, master transcriptional factors, Mediators and other co-activators, forms phase-separated condensates, which offers a toggle for directing diverse stem cell fate. With the burgeoning technologies of multiple-omics applied to examine different aspects of SE, we firstly raise the concept of "super-enhancer omics", inextricably linking to Pan-omics. In the review, we discuss the spatiotemporal organization and concepts of SEs, and describe links between SE-navigated transcriptional complex and stem cell features, such as stem cell identity, self-renewal, pluripotency, differentiation and development. We also elucidate the mechanism of stemness and oncogenic SEs modulating cancer stem cells via genomic and epigenetic alterations hijack in cancer stem cell. Additionally, we discuss the potential of targeting components of the SE complex using small molecule compounds, genome editing, and antisense oligonucleotides to treat SE-associated organ dysfunction and diseases, including cancer. This review also provides insights into the future of stem cell research through the paradigm of SEs.

Liver-specific deletion of de novo DNA methyltransferases protects against glucose intolerance in high-fat diet-fed male mice

Alterations to gene transcription and DNA methylation are a feature of many liver diseases including fatty liver disease and liver cancer. However, it is unclear whether the DNA methylation changes are a cause or a consequence of the transcriptional changes. It is even possible that the methylation changes are not required for the transcriptional changes. If DNA methylation is just a minor player in, or a consequence of liver transcriptional change, then future studies in this area should focus on other systems such as histone tail modifications. To interrogate the importance of de novo DNA methylation, we generated mice that are homozygous mutants for both Dnmt3a and Dnmt3b in post-natal liver. These mice are viable and fertile with normal sized livers. Males, but not females, showed increased adipose depots, yet paradoxically, improved glucose tolerance on both control diet and high-fat diets (HFD). Comparison of the transcriptome and methylome with RNA sequencing and whole-genome bisulfite sequencing in adult hepatocytes revealed that widespread loss of methylation in CpG-rich regions in the mutant did not induce loss of homeostatic transcriptional regulation. Similarly, extensive transcriptional changes induced by HFD did not require de novo DNA methylation. The improved metabolic phenotype of the Dnmt3a/3b mutant mice may be mediated through the dysregulation of a subset of glucose and fat metabolism genes which increase both glucose uptake and lipid export by the liver. However, further work is needed to confirm this.

RNA expression changes driven by altered epigenetics status related to NASH etiology

Non-alcoholic fatty liver disease (NAFLD) is a growing health problem due to the increased obesity rates, among other factors. In its more severe stage (NASH), inflammation, hepatocellular ballooning and fibrosis are present in the liver, which can further evolve to total liver dysfunction or even hepatocarcinoma. As a metabolic disease, is associated to environmental factors such as diet and lifestyle conditions, which in turn can influence the epigenetic landscape of the cells, affecting to the gene expression profile and chromatin organization. In this study we performed ATAC-sequencing and RNA-sequencing to interrogate the chromatin status of liver biopsies in subjects with and without NASH and its effects on RNA transcription and NASH etiology. NASH subjects showed transcriptional downregulation for lipid and glucose metabolic pathways (e.g., ABC transporters, AMPK, FoxO or insulin pathways). A total of 229 genes were differentially enriched (ATAC and mRNA) in NASH, which were mainly related to lipid transport activity, nuclear receptor-binding, dicarboxylic acid transporter, and PPARA lipid regulation. Interpolation of ATAC data with known liver enhancer regions showed differential openness at 8 enhancers, some linked to genes involved in lipid metabolism, (i.e., FASN) and glucose homeostasis (i.e., GCGR). In conclusion, the chromatin landscape is altered in NASH patients compared to patients without this liver condition. This alteration might cause mRNA changes explaining, at least partially, the etiology and pathophysiology of the disease.

Analysis of blood methylation quantitative trait loci in East Asians reveals ancestry-specific impacts on complex traits

Methylation quantitative trait loci (mQTLs) are essential for understanding the role of DNA methylation changes in genetic predisposition, yet they have not been fully characterized in East Asians (EAs). Here we identified mQTLs in whole blood from 3,523 Chinese individuals and replicated them in additional 1,858 Chinese individuals from two cohorts. Over 9% of mQTLs displayed specificity to EAs, facilitating the fine-mapping of EA-specific genetic associations, as shown for variants associated with height. Trans-mQTL hotspots revealed biological pathways contributing to EA-specific genetic associations, including an ERG-mediated 233 trans-mCpG network, implicated in hematopoietic cell differentiation, which likely reflects binding efficiency modulation of the ERG protein complex. More than 90% of mQTLs were shared between different blood cell lineages, with a smaller fraction of lineage-specific mQTLs displaying preferential hypomethylation in the respective lineages. Our study provides new insights into the mQTL landscape across genetic ancestries and their downstream effects on cellular processes and diseases/traits.

Pathogenic role of super-enhancers as potential therapeutic targets in lung cancer

Lung cancer is still one of the deadliest malignancies today, and most patients with advanced lung cancer pass away from disease progression that is uncontrollable by medications. Super-enhancers (SEs) are large clusters of enhancers in the genome's non-coding sequences that actively trigger transcription. Although SEs have just been identified over the past 10 years, their intricate structure and crucial role in determining cell identity and promoting tumorigenesis and progression are increasingly coming to light. Here, we review the structural composition of SEs, the auto-regulatory circuits, the control mechanisms of downstream genes and pathways, and the characterization of subgroups classified according to SEs in lung cancer. Additionally, we discuss the therapeutic targets, several small-molecule inhibitors, and available treatment options for SEs in lung cancer. Combination therapies have demonstrated considerable advantages in preclinical models, and we anticipate that these drugs will soon enter clinical studies and benefit patients.

Functional identification of cis-regulatory long noncoding RNAs at controlled false discovery rates

A key attribute of some long noncoding RNAs (lncRNAs) is their ability to regulate expression of neighbouring genes in cis. However, such 'cis-lncRNAs' are presently defined using ad hoc criteria that, we show, are prone to false-positive predictions. The resulting lack of cis-lncRNA catalogues hinders our understanding of their extent, characteristics and mechanisms. Here, we introduce TransCistor, a framework for defining and identifying cis-lncRNAs based on enrichment of targets amongst proximal genes. TransCistor's simple and conservative statistical models are compatible with functionally defined target gene maps generated by existing and future technologies. Using transcriptome-wide perturbation experiments for 268 human and 134 mouse lncRNAs, we provide the first large-scale survey of cis-lncRNAs. Known cis-lncRNAs are correctly identified, including XIST, LINC00240 and UMLILO, and predictions are consistent across analysis methods, perturbation types and independent experiments. We detect cis-activity in a minority of lncRNAs, primarily involving activators over repressors. Cis-lncRNAs are detected by both RNA interference and antisense oligonucleotide perturbations. Mechanistically, cis-lncRNA transcripts are observed to physically associate with their target genes and are weakly enriched with enhancer elements. In summary, TransCistor establishes a quantitative foundation for cis-lncRNAs, opening a path to elucidating their molecular mechanisms and biological significance.

Ancestry dynamics and trait selection in a designer cat breed

The Bengal cat breed was developed from intercrosses between the Asian leopard cat, Prionailurus bengalensis, and the domestic cat, Felis catus, with a last common ancestor approximately 6 million years ago. Predicted to derive ∼94% of their genome from domestic cats, regions of the leopard cat genome are thought to account for the unique pelage traits and ornate color patterns of the Bengal breed, which are similar to those of ocelots and jaguars. We explore ancestry distribution and selection signatures in the Bengal breed by using reduced representation and whole-genome sequencing from 947 cats. The mean proportion of leopard cat DNA in the Bengal breed is 3.48%, lower than predicted from breed history, and is broadly distributed, covering 93% of the Bengal genome. Overall, leopard cat introgressions do not show strong signatures of selection across the Bengal breed. However, two popular color traits in Bengal cats, charcoal and pheomelanin intensity, are explained by selection of leopard cat genes whose expression is reduced in a domestic cat background, consistent with genetic incompatibility resulting from hybridization. We characterize several selective sweeps in the Bengal genome that harbor candidate genes for pelage and color pattern and that are associated with domestic, rather than leopard, cat haplotypes. We identify the molecular and phenotypic basis of one selective sweep as reduced expression of the Fgfr2 gene, which underlies glitter, a trait desired by breeders that affects hair texture and light reflectivity.

TOP1 and R-loops facilitate transcriptional DSBs at hypertranscribed cancer driver genes

DNA double-stranded breaks (DSBs) pose a significant threat to genomic integrity, and their generation during essential cellular processes like transcription remains poorly understood. In this study, we employ several techniques to map DSBs, R-loops, and topoisomerase 1 cleavage complex (TOP1cc) to comprehensively investigate the interplay between transcription, DSBs, topoisomerase 1 (TOP1), and R-loops. Our findings reveal the presence of DSBs at highly expressed genes enriched with TOP1 and R-loops. Remarkably, transcription-associated DSBs at these loci are significantly reduced upon depletion of R-loops and TOP1, uncovering the pivotal roles of TOP1 and R-loops in transcriptional DSB formation. By elucidating the intricate interplay between TOP1cc trapping, R-loops, and DSBs, our study provides insights into the mechanisms underlying transcription-associated genomic instability. Moreover, we establish a link between transcriptional DSBs and early molecular changes driving cancer development, highlighting the distinct etiology and molecular characteristics of driver mutations compared to passenger mutations.

TSCRE: a comprehensive database for tumor-specific cis-regulatory elements

Cis-regulatory elements (CREs) and super cis-regulatory elements (SCREs) are non-coding DNA regions which influence the transcription of nearby genes and play critical roles in development. Dysregulated CRE and SCRE activities have been reported to alter the expression of oncogenes and tumor suppressors, thereby regulating cancer hallmarks. To address the strong need for a comprehensive catalogue of dysregulated CREs and SCREs in human cancers, we present TSCRE (http://tscre.zsqylab.com/), an open resource providing tumor-specific and cell type-specific CREs and SCREs derived from the re-analysis of publicly available histone modification profiles. Currently, TSCRE contains 1 864 941 dysregulated CREs and 68 253 dysregulated SCREs identified from 1366 human patient samples spanning 17 different cancer types and 9 histone marks. Over 95% of these elements have been validated in public resources. TSCRE offers comprehensive annotations for each element, including associated genes, expression patterns, clinical prognosis, somatic mutations, transcript factor binding sites, cancer-type specificity, and drug response. Additionally, TSCRE integrates pathway and transcript factor enrichment analyses for each study, enabling in-depth functional and mechanistic investigations. Furthermore, TSCRE provides an interactive interface for users to explore any CRE and SCRE of interest. We believe TSCRE will be a highly valuable platform for the community to discover candidate cancer biomarkers.

NCAD v1.0: a database for non-coding variant annotation and interpretation

The application of whole genome sequencing is expanding in clinical diagnostics across various genetic disorders, and the significance of non-coding variants in penetrant diseases is increasingly being demonstrated. Therefore, it is urgent to improve the diagnostic yield by exploring the pathogenic mechanisms of variants in non-coding regions. However, the interpretation of non-coding variants remains a significant challenge, due to the complex functional regulatory mechanisms of non-coding regions and the current limitations of available databases and tools. Hence, we develop the non-coding variant annotation database (NCAD, http://www.ncawdb.net/), encompassing comprehensive insights into 665,679,194 variants, regulatory elements, and element interaction details. Integrating data from 96 sources, spanning both GRCh37 and GRCh38 versions, NCAD v1.0 provides vital information to support the genetic diagnosis of non-coding variants, including allele frequencies of 12 diverse populations, with a particular focus on the population frequency information for 230,235,698 variants in 20,964 Chinese individuals. Moreover, it offers prediction scores for variant functionality, five categories of regulatory elements, and four types of non-coding RNAs. With its rich data and comprehensive coverage, NCAD serves as a valuable platform, empowering researchers and clinicians with profound insights into non-coding regulatory mechanisms while facilitating the interpretation of non-coding variants.

eRNAbase: a comprehensive database for decoding the regulatory eRNAs in human and mouse

Enhancer RNAs (eRNAs) transcribed from distal active enhancers serve as key regulators in gene transcriptional regulation. The accumulation of eRNAs from multiple sequencing assays has led to an urgent need to comprehensively collect and process these data to illustrate the regulatory landscape of eRNAs. To address this need, we developed the eRNAbase (http://bio.liclab.net/eRNAbase/index.php) to store the massive available resources of human and mouse eRNAs and provide comprehensive annotation and analyses for eRNAs. The current version of eRNAbase cataloged 10 399 928 eRNAs from 1012 samples, including 858 human samples and 154 mouse samples. These eRNAs were first identified and uniformly processed from 14 eRNA-related experiment types manually collected from GEO/SRA and ENCODE. Importantly, the eRNAbase provides detailed and abundant (epi)genetic annotations in eRNA regions, such as super enhancers, enhancers, common single nucleotide polymorphisms, expression quantitative trait loci, transcription factor binding sites, CRISPR/Cas9 target sites, DNase I hypersensitivity sites, chromatin accessibility regions, methylation sites, chromatin interactions regions, topologically associating domains and RNA spatial interactions. Furthermore, the eRNAbase provides users with three novel analyses including eRNA-mediated pathway regulatory analysis, eRNA-based variation interpretation analysis and eRNA-mediated TF-target gene analysis. Hence, eRNAbase is a powerful platform to query, browse and visualize regulatory cues associated with eRNAs.

MethMarkerDB: a comprehensive cancer DNA methylation biomarker database

DNA methylation plays a crucial role in tumorigenesis and tumor progression, sparking substantial interest in the clinical applications of cancer DNA methylation biomarkers. Cancer-related whole-genome bisulfite sequencing (WGBS) data offers a promising approach to precisely identify these biomarkers with differentially methylated regions (DMRs). However, currently there is no dedicated resource for cancer DNA methylation biomarkers with WGBS data. Here, we developed a comprehensive cancer DNA methylation biomarker database (MethMarkerDB, https://methmarkerdb.hzau.edu.cn/), which integrated 658 WGBS datasets, incorporating 724 curated DNA methylation biomarker genes from 1425 PubMed published articles. Based on WGBS data, we documented 5.4 million DMRs from 13 common types of cancer as candidate DNA methylation biomarkers. We provided search and annotation functions for these DMRs with different resources, such as enhancers and SNPs, and developed diagnostic and prognostic models for further biomarker evaluation. With the database, we not only identified known DNA methylation biomarkers, but also identified 781 hypermethylated and 5245 hypomethylated pan-cancer DMRs, corresponding to 693 and 2172 genes, respectively. These novel potential pan-cancer DNA methylation biomarkers hold significant clinical translational value. We hope that MethMarkerDB will help identify novel cancer DNA methylation biomarkers and propel the clinical application of these biomarkers.

A distant global control region is essential for normal expression of anterior HOXA genes during mouse and human craniofacial development

Craniofacial abnormalities account for approximately one third of birth defects. The regulatory programs that build the face require precisely controlled spatiotemporal gene expression, achieved through tissue-specific enhancers. Clusters of coactivated enhancers and their target genes, known as superenhancers, are important in determining cell identity but have been largely unexplored in development. In this study we identified superenhancer regions unique to human embryonic craniofacial tissue. To demonstrate the importance of such regions in craniofacial development and disease, we focused on an ~600 kb noncoding region located between NPVF and NFE2L3. We identified long range interactions with this region in both human and mouse embryonic craniofacial tissue with the anterior portion of the HOXA gene cluster. Mice lacking this superenhancer exhibit perinatal lethality, and present with highly penetrant skull defects and orofacial clefts phenocopying Hoxa2-/- mice. Moreover, we identified two cases of de novo copy number changes of the superenhancer in humans both with severe craniofacial abnormalities. This evidence suggests we have identified a critical noncoding locus control region that specifically regulates anterior HOXA genes and copy number changes are pathogenic in human patients.

A High-Throughput PIXUL-Matrix-Based Toolbox to Profile Frozen and Formalin-Fixed Paraffin-Embedded Tissues Multiomes

Large-scale high-dimensional multiomics studies are essential to unravel molecular complexity in health and disease. We developed an integrated system for tissue sampling (CryoGrid), analytes preparation (PIXUL), and downstream multiomic analysis in a 96-well plate format (Matrix), MultiomicsTracks96, which we used to interrogate matched frozen and formalin-fixed paraffin-embedded (FFPE) mouse organs. Using this system, we generated 8-dimensional omics data sets encompassing 4 molecular layers of intracellular organization: epigenome (H3K27Ac, H3K4m3, RNA polymerase II, and 5mC levels), transcriptome (messenger RNA levels), epitranscriptome (m6A levels), and proteome (protein levels) in brain, heart, kidney, and liver. There was a high correlation between data from matched frozen and FFPE organs. The Segway genome segmentation algorithm applied to epigenomic profiles confirmed known organ-specific superenhancers in both FFPE and frozen samples. Linear regression analysis showed that proteomic profiles, known to be poorly correlated with transcriptomic data, can be more accurately predicted by the full suite of multiomics data, compared with using epigenomic, transcriptomic, or epitranscriptomic measurements individually.

The counterpart congenital overgrowth syndromes Beckwith-Wiedemann Syndrome in human and large offspring syndrome in bovine involve alterations in DNA methylation, transcription, and chromatin configuration

Beckwith-Wiedemann Syndrome (BWS, OMIM #130650) is a congenital epigenetic disorder in humans which affects approximately 1 in 10,340 children. The incidence is likely an underestimation as the condition is usually recognized based on observable phenotypes at birth. BWS children have up to a 28% risk of developing tumors and currently, only 80% of patients can be corroborated molecularly (epimutations/variants). It is unknown how the subtypes of this condition are molecularly similar/dissimilar globally, therefore there is a need to deeply characterize the syndrome at the molecular level. Here we characterize the methylome, transcriptome and chromatin configuration of 18 BWS individuals together with the animal model of the condition, the bovine large offspring syndrome (LOS). Sex specific comparisons are performed for a subset of the BWS patients and LOS. Given that this epigenetic overgrowth syndrome has been characterized as a loss-of-imprinting condition, parental allele-specific comparisons were performed using the bovine animal model. In general, the differentially methylated regions (DMRs) detected in BWS and LOS showed significant enrichment for CTCF binding sites. Altered chromosome compartments in BWS and LOS were positively correlated with gene expression changes, and the promoters of differentially expressed genes showed significant enrichment for DMRs, differential topologically associating domains, and differential A/B compartments in some comparisons of BWS subtypes and LOS. We show shared regions of dysregulation between BWS and LOS, including several HOX gene clusters, and also demonstrate that altered DNA methylation differs between the clinically epigenetically identified BWS patients and those identified as having DNA variants (i.e. CDKN1C microdeletion). Lastly, we highlight additional genes and genomic regions that have the potential to serve as targets for biomarker development to improve current molecular methodologies. In summary, our results suggest that genome-wide alternation of chromosome architecture, which is partially caused by DNA methylation changes, also contribute to the development of BWS and LOS.

Molecular basis for SOX2-dependent regulation of super-enhancer activity

Pioneer transcription factors (TFs) like SOX2 are vital for stemness and cancer through enhancing gene expression within transcriptional condensates formed with coactivators, RNAs and mediators on super-enhancers (SEs). Despite their importance, how these factors work together for transcriptional condensation and activation remains unclear. SOX2, a pioneer TF found in SEs of pluripotent and cancer stem cells, initiates SE-mediated transcription by binding to nucleosomes, though the mechanism isn't fully understood. To address SOX2's role in SEs, we identified mSE078 as a model SOX2-enriched SE and p300 as a coactivator through bioinformatic analysis. In vitro and cell assays showed SOX2 forms condensates with p300 and SOX2-binding motifs in mSE078. We further proved that SOX2 condensation is highly correlated with mSE078's enhancer activity in cells. Moreover, we successfully demonstrated that p300 not only elevated transcriptional activity but also triggered chromatin acetylation via its direct interaction with SOX2 within these transcriptional condensates. Finally, our validation of SOX2-enriched SEs showcased their contribution to target gene expression in both stem cells and cancer cells. In its entirety, this study imparts valuable mechanistic insights into the collaborative interplay of SOX2 and its coactivator p300, shedding light on the regulation of transcriptional condensation and activation within SOX2-enriched SEs.

Noncoding function of super enhancer derived mRNA in modulating neighboring gene expression and TAD interaction

Super enhancers are important regulators of gene expression that often overlap with protein-coding genes. However, it is unclear whether the overlapping protein-coding genes and the mRNA derived from them contribute to enhancer activity. Using an erythroid-specific super enhancer that overlaps the Cpox gene as a model, we found that Cpox mRNA has a non-coding function in regulating neighboring protein-coding genes, eRNA expression and TAD interactions. Depletion of Cpox mRNA leads to accumulation of H3K27me3 and release of p300 from the Cpox locus, activating an intra-TAD enhancer and gene expression. Additionally, we identified a head-to-tail interaction between the TAD boundary genes Cpox and Dcbld2 that is facilitated by a novel type of repressive loop anchored by p300 and PRC2/H3K27me3. Our results uncover a regulatory role for mRNA transcribed within a super enhancer context and provide insight into head-to-tail inter-gene interaction in the regulation of gene expression and oncogene activation.

Identifying quantitatively differential chromosomal compartmentalization changes and their biological significance from Hi-C data using DARIC

BACKGROUND

Chromosomal compartmentalization plays a critical role in maintaining proper transcriptional programs in cell differentiation and oncogenesis. However, currently the prevalent method for comparative analysis of compartmentalization landscapes between different cell types is limited to the qualitative switched compartments.

RESULTS

To identify genomic regions with quantitatively differential compartmentalization changes from genome-wide chromatin conformation data like Hi-C, we developed a computational framework named DARIC. DARIC includes three modules: compartmentalization quantification, normalization, and differential analysis. Comparing DARIC with the conventional compartment switching analysis reveals substantial regions characterized by quantitatively significant compartmentalization changes without switching. These changes are accompanied by changes in gene expression, chromatin accessibility, H3K27ac intensity, as well as the interactions with nuclear lamina proteins and nuclear positioning, highlighting the functional importance of such quantitative changes in gene regulation. We applied DARIC to dissect the quantitative compartmentalization changes during human cardiomyocyte differentiation and identified two distinct mechanisms for gene activation based on the association with compartmentalization changes. Using the quantitative compartmentalization measurement module from DARIC, we further dissected the compartment variability landscape in the human genome by analyzing a compendium of 32 Hi-C datasets from 4DN. We discovered an interesting correlation between compartmentalization variability and sub-compartments.

CONCLUSIONS

DARIC is a useful tool for analyzing quantitative compartmentalization changes and mining novel biological insights from increasing Hi-C data. Our results demonstrate the functional significance of quantitative compartmentalization changes in gene regulation, and provide new insights into the relationship between compartmentalization variability and sub-compartments in the human genome.

Integrome signatures of lentiviral gene therapy for SCID-X1 patients

Lentiviral vector (LV)-based gene therapy holds promise for a broad range of diseases. Analyzing more than 280,000 vector integration sites (VISs) in 273 samples from 10 patients with X-linked severe combined immunodeficiency (SCID-X1), we discovered shared LV integrome signatures in 9 of 10 patients in relation to the genomics, epigenomics, and 3D structure of the human genome. VISs were enriched in the nuclear subcompartment A1 and integrated into super-enhancers close to nuclear pore complexes. These signatures were validated in T cells transduced with an LV encoding a CD19-specific chimeric antigen receptor. Intriguingly, the one patient whose VISs deviated from the identified integrome signatures had a distinct clinical course. Comparison of LV and gamma retrovirus integromes regarding their 3D genome signatures identified differences that might explain the lower risk of insertional mutagenesis in LV-based gene therapy. Our findings suggest that LV integrome signatures, shaped by common features such as genome organization, may affect the efficacy of LV-based cellular therapies.

Metformin Promotes Proliferation of Mouse Female Germline Stem Cells by Histone Acetylation Modification of Traf2

Female germline stem cells (FGSCs) are adult stem cells that can both self-renew and differentiate into mature oocytes. Although small-molecule compounds are capable of regulating the development of FGSCs, the effects and mechanisms of action of metformin, a commonly used drug for diabetes, on FGSCs are largely unknown. Here, we found that metformin promoted the viability and proliferation of FGSCs through H3K27ac modification. To elucidate the mechanism by which metformin promoted FGSCs proliferation, Chromatin Immunoprecipitation Sequencing of histone 3 lysine 27 acetylation (H3K27ac) in FGSCs was performed with or without metformin-treatment. The results indicate that metformin modulates FGSCs via the mitogen-activated protein kinase (MAPK) signaling pathway, and tumor necrosis factor receptor associated factor 2 (Traf2) was identified as an important target gene for H3K27ac modification during FGSCs proliferation. Subsequent experiments showed metformin promoted FGSCs proliferation by H3K27ac modification of Traf2 to regulate MAPK signaling. Our findings deepen understanding of how H3K27ac modifications regulate FGSCs development and provide a theoretical basis for the prevention and treatment of premature ovarian failure, polycystic ovary syndrome, infertility, and related diseases.

Cis-Cardio: A comprehensive analysis platform for cardiovascular-relavant cis-regulation in human and mouse

Cis-regulatory elements are important molecular switches in controlling gene expression and are regarded as determinant hubs in the transcriptional regulatory network. Collection and processing of large-scale cis-regulatory data are urgent to decipher the potential mechanisms of cardiovascular diseases from a cis-regulatory element aspect. Here, we developed a novel web server, Cis-Cardio, which aims to document a large number of available cardiovascular-related cis-regulatory data and to provide analysis for unveiling the comprehensive mechanisms at a cis-regulation level. The current version of Cis-Cardio catalogs a total of 45,382,361 genomic regions from 1,013 human and mouse epigenetic datasets, including ATAC-seq, DNase-seq, Histone ChIP-seq, TF/TcoF ChIP-seq, RNA polymerase ChIP-seq, and Cohesin ChIP-seq. Importantly, Cis-Cardio provides six analysis tools, including region overlap analysis, element upstream/downstream analysis, transcription regulator enrichment analysis, variant interpretation, and protein-protein interaction-based co-regulatory analysis. Additionally, Cis-Cardio provides detailed and abundant (epi-) genetic annotations in cis-regulatory regions, such as super-enhancers, enhancers, transcription factor binding sites (TFBSs), methylation sites, common SNPs, risk SNPs, expression quantitative trait loci (eQTLs), motifs, DNase I hypersensitive sites (DHSs), and 3D chromatin interactions. In summary, Cis-Cardio is a valuable resource for elucidating and analyzing regulatory cues of cardiovascular-specific cis-regulatory elements. The platform is freely available at http://www.licpathway.net/Cis-Cardio/index.html.

The genetic variant rs55986091 HLA-DQB1 is associated with a protective effect against cervical cancer

Introduction

Cervical cancer (CC) is a prevalent malignancy affecting women globally. The primary causative factor of CC is the high-risk oncogenic human papillomavirus (HR-HPV). However, it is noteworthy that not all women infected with HR-HPV develop cancer, indicating the potential involvement of genetic predisposition in the development of CC. This study aims to identify genetic risks and their distribution in groups of women with different epidemiological features of HR-HPV.

Materials and methods

A comparison was conducted among four groups of women, comprising 218 HPV-negative women, 120 HPV-positive women, 191 women diagnosed with cervical intraepithelial neoplasia (CIN) grade 2 or 3, and 124 women diagnosed with CC. The analysis focused on four single nucleotide polymorphisms (SNPs): rs55986091 in HLA-DQB1, rs138446575 in TTC34, rs1048943 in CYP1A1, and rs2910164 in miRNA-146a.

Results

The rs55986091-A allele exhibited a protective effect within the "CC" group when compared to the "HPV-Negative" group (OR = 0.4, 95% CI= 0.25-0.65) using a log-additive model. Additionally, similar protective effects were observed in the "CIN 2/3" group compared to the "HPV-Negative" group (OR = 0.47, 95% CI = 0.28-0.79).

Conclusion

The data obtained emphasize the importance of developing PCR-based diagnostic kits for the identification of SNP alleles, particularly for rs55986091, among HR-HPV-positive women within the Russian population.

Super-enhancers complexes zoom in transcription in cancer

Super-enhancers (SEs) consist of multiple typical enhancers enriched at high density with transcription factors, histone-modifying enzymes and cofactors. Oncogenic SEs promote tumorigenesis and malignancy by altering protein-coding gene expression and noncoding regulatory element function. Therefore, they play central roles in the treatment of cancer. Here, we review the structural characteristics, organization, identification, and functions of SEs and the underlying molecular mechanism by which SEs drive oncogenic transcription in tumor cells. We then summarize abnormal SE complexes, SE-driven coding genes, and noncoding RNAs involved in tumor development. In summary, we believe that SEs show great potential as biomarkers and therapeutic targets.

Low RNA stability signifies increased post-transcriptional regulation of cell identity genes

Cell identity genes are distinct from other genes with respect to the epigenetic mechanisms to activate their transcription, e.g. by super-enhancers and broad H3K4me3 domains. However, it remains unclear whether their post-transcriptional regulation is also unique. We performed a systematic analysis of transcriptome-wide RNA stability in nine cell types and found that unstable transcripts were enriched in cell identity-related pathways while stable transcripts were enriched in housekeeping pathways. Joint analyses of RNA stability and chromatin state revealed significant enrichment of super-enhancers and broad H3K4me3 domains at the gene loci of unstable transcripts. Intriguingly, the RNA m6A methyltransferase, METTL3, preferentially binds to chromatin at super-enhancers, broad H3K4me3 domains and their associated genes. METTL3 binding intensity is positively correlated with RNA m6A methylation and negatively correlated with RNA stability of cell identity genes, probably due to co-transcriptional m6A modifications promoting RNA decay. Nanopore direct RNA-sequencing showed that METTL3 knockdown has a stronger effect on RNA m6A and mRNA stability for cell identity genes. Our data suggest a run-and-brake model, where cell identity genes undergo both frequent transcription and fast RNA decay to achieve precise regulation of RNA expression.

Integrative mapping of the dog epigenome: Reference annotation for comparative intertissue and cross-species studies

Dogs have become a valuable model in exploring multifaceted diseases and biology relevant to human health. Despite large-scale dog genome projects producing high-quality draft references, a comprehensive annotation of functional elements is still lacking. We addressed this through integrative next-generation sequencing of transcriptomes paired with five histone marks and DNA methylome profiling across 11 tissue types, deciphering the dog's epigenetic code by defining distinct chromatin states, super-enhancer, and methylome landscapes, and thus showed that these regions are associated with a wide range of biological functions and cell/tissue identity. In addition, we confirmed that the phenotype-associated variants are enriched in tissue-specific regulatory regions and, therefore, the tissue of origin of the variants can be traced. Ultimately, we delineated conserved and dynamic epigenomic changes at the tissue- and species-specific resolutions. Our study provides an epigenomic blueprint of the dog that can be used for comparative biology and medical research.

Hi-TrAC detects active sub-TADs and reveals internal organizations of super-enhancers

The spatial folding of eukaryotic genome plays a key role in genome function. We report here that our recently developed method, Hi-TrAC, which specializes in detecting chromatin loops among accessible genomic regions, can detect active sub-TADs with a median size of 100 kb, most of which harbor one or two cell specifically expressed genes and regulatory elements such as super-enhancers organized into nested interaction domains. These active sub-TADs are characterized by highly enriched histone mark H3K4me1 and chromatin-binding proteins, including Cohesin complex. Deletion of selected sub-TAD boundaries have different impacts, such as decreased chromatin interaction and gene expression within the sub-TADs or compromised insulation between the sub-TADs, depending on the specific chromatin environment. We show that knocking down core subunit of the Cohesin complex using shRNAs in human cells or decreasing the H3K4me1 modification by deleting the H3K4 methyltransferase Mll4 gene in mouse Th17 cells disrupted the sub-TADs structure. Our data also suggest that super-enhancers exist as an equilibrium globule structure, while inaccessible chromatin regions exist as a fractal globule structure. In summary, Hi-TrAC serves as a highly sensitive and inexpensive approach to study dynamic changes of active sub-TADs, providing more explicit insights into delicate genome structures and functions.

Disruption of CDK7 signaling leads to catastrophic chromosomal instability coupled with a loss of condensin-mediated chromatin compaction

Chromatin organization is highly dynamic and modulates DNA replication, transcription, and chromosome segregation. Condensin is essential for chromosome assembly during mitosis and meiosis, as well as maintenance of chromosome structure during interphase. While it is well established that sustained condensin expression is necessary to ensure chromosome stability, the mechanisms that control its expression are not yet known. Herein, we report that disruption of cyclin-dependent kinase 7 (CDK7), the core catalytic subunit of CDK-activating kinase, leads to reduced transcription of several condensin subunits, including structural maintenance of chromosomes 2 (SMC2). Live and static microscopy revealed that inhibiting CDK7 signaling prolongs mitosis and induces chromatin bridge formation, DNA double-strand breaks, and abnormal nuclear features, all of which are indicative of mitotic catastrophe and chromosome instability. Affirming the importance of condensin regulation by CDK7, genetic suppression of the expression of SMC2, a core subunit of this complex, phenocopies CDK7 inhibition. Moreover, analysis of genome-wide chromatin conformation using Hi-C revealed that sustained activity of CDK7 is necessary to maintain chromatin sublooping, a function that is ascribed to condensin. Notably, the regulation of condensin subunit gene expression is independent of superenhancers. Together, these studies reveal a new role for CDK7 in sustaining chromatin configuration by ensuring the expression of condensin genes, including SMC2.

A restrictor complex of ZC3H4, WDR82, and ARS2 integrates with PNUTS to control unproductive transcription

The transcriptional termination of unstable non-coding RNAs (ncRNAs) is poorly understood compared to coding transcripts. We recently identified ZC3H4-WDR82 ("restrictor") as restricting human ncRNA transcription, but how it does this is unknown. Here, we show that ZC3H4 additionally associates with ARS2 and the nuclear exosome targeting complex. The domains of ZC3H4 that contact ARS2 and WDR82 are required for ncRNA restriction, suggesting their presence in a functional complex. Consistently, ZC3H4, WDR82, and ARS2 co-transcriptionally control an overlapping population of ncRNAs. ZC3H4 is proximal to the negative elongation factor, PNUTS, which we show enables restrictor function and is required to terminate the transcription of all major RNA polymerase II transcript classes. In contrast to short ncRNAs, longer protein-coding transcription is supported by U1 snRNA, which shields transcripts from restrictor and PNUTS at hundreds of genes. These data provide important insights into the mechanism and control of transcription by restrictor and PNUTS.

SENet: A deep learning framework for discriminating super- and typical enhancers by sequence information

Super-enhancers are large domains on the genome where multiple short typical enhancers within a specific genomic distance are stitched together. Typically, they are cell type-specific and responsible for defining cell identity and regulating gene transcription. Numerous studies have demonstrated that super-enhancers are enriched for trait-associated variants, and mutations in super-enhancers are possibly related to known diseases. Recently, several machine learning-based methods have been used to distinguish super-enhancers from typical enhancers by using high-throughput data from various experimental methods. The acquisition of such experimental data is usually costly and time-consuming. In this paper, we innovatively proposed SENet, a groundbreaking method based on a deep neural network model, for discriminating between the two categories solely utilizing sequence information. SENet employs dna2vec feature embedding, convolution for local feature extraction, attention pooling for refined feature retention, and Transformer for contextual information extraction. Experiments demonstrate that SENet outperforms all current state-of-the-art computational methods and shows satisfactory performance in cross-species validation. Our method pioneers the distinction between super-enhancers and typical ones using only sequence information. The source code and datasets are stored in https://github.com/lhy0322/SENet.

The Interplay between Dysregulated Metabolism and Epigenetics in Cancer

Cellular metabolism (or energetics) and epigenetics are tightly coupled cellular processes. It is arguable that of all the described cancer hallmarks, dysregulated cellular energetics and epigenetics are the most tightly coregulated. Cellular metabolic states regulate and drive epigenetic changes while also being capable of influencing, if not driving, epigenetic reprogramming. Conversely, epigenetic changes can drive altered and compensatory metabolic states. Cancer cells meticulously modify and control each of these two linked cellular processes in order to maintain their tumorigenic potential and capacity. This review aims to explore the interplay between these two processes and discuss how each affects the other, driving and enhancing tumorigenic states in certain contexts.

Pou4f1-Tbr1 transcriptional cascade controls the formation of Jam2-expressing retinal ganglion cells

More than 40 retinal ganglion cell (RGC) subtypes have been categorized in mouse based on their morphologies, functions, and molecular features. Among these diverse subtypes, orientation-selective Jam2-expressing RGCs (J-RGCs) has two unique morphologic characteristics: the ventral-facing dendritic arbor and the OFF-sublaminae stratified terminal dendrites in the inner plexiform layer. Previously, we have discovered that T-box transcription factor T-brain 1 (Tbr1) is expressed in J-RGCs. We further found that Tbr1 is essential for the expression of Jam2, and Tbr1 regulates the formation and the dendritic morphogenesis of J-RGCs. However, Tbr1 begins to express in terminally differentiated RGCs around perinatal stage, suggesting that it is unlikely involved in the initial fate determination for J-RGC and other upstream transcription factors must control Tbr1 expression and J-RGC formation. Using the Cleavage Under Targets and Tagmentation technique, we discovered that Pou4f1 binds to Tbr1 on the evolutionary conserved exon 6 and an intergenic region downstream of the 3'UTR, and on a region flanking the promoter and the first exon of Jam2. We showed that Pou4f1 is required for the expression of Tbr1 and Jam2, indicating Pou4f1 as a direct upstream regulator of Tbr1 and Jam2. Most interestingly, the Pou4f1-bound element in exon 6 of Tbr1 possesses high-level enhancer activity, capable of directing reporter gene expression in J-RGCs. Together, these data revealed a Pou4f1-Tbr1-Jam2 genetic hierarchy as a critical pathway in the formation of J-RGC subtype.

Identifying Quantitatively Differential Chromosomal Compartmentalization Changes and Their Biological Significance from Hi-C data using DARIC

Background

Chromosomal compartmentalization plays a critical role in maintaining proper transcriptional programs in cell differentiation and oncogenesis. However, currently the prevalent method for comparative analysis of compartmentalization landscapes between different cell types is limited to the qualitative switched compartments.

Results

To identify genomic regions with quantitatively differential compartmentalization changes from genome-wide chromatin conformation data like Hi-C, we developed a computational framework named DARIC. DARIC includes three modules: compartmentalization quantification, normalization, and differential analysis. Comparing DARIC with the conventional compartment switching analysis reveals substantial regions characterized by quantitatively significant compartmentalization changes without switching. These changes are accompanied by changes in gene expression, chromatin accessibility, H3K27ac intensity, as well as the interactions with nuclear lamina proteins and nuclear positioning, highlighting the functional importance of such quantitative changes in gene regulation. We applied DARIC to dissect the quantitative compartmentalization changes during human cardiomyocyte differentiation and identified two distinct mechanisms for gene activation based on the association with compartmentalization changes. Using the quantitative compartmentalization measurement module from DARIC, we further dissected the compartment variability landscape in the human genome by analyzing a compendium of 32 Hi-C datasets from 4DN. We discovered an interesting correlation between compartmentalization variability and sub-compartments.

Conclusions

DARIC is a useful tool for analyzing quantitative compartmentalization changes and mining novel biological insights from increasing Hi-C data. Our results demonstrate the functional significance of quantitative compartmentalization changes in gene regulation, and provide new insights into the relationship between compartmentalization variability and sub-compartments in the human genome.

Experimental Validation and Prediction of Super-Enhancers: Advances and Challenges

Super-enhancers (SEs) are cis-regulatory elements of the human genome that have been widely discussed since the discovery and origin of the term. Super-enhancers have been shown to be strongly associated with the expression of genes crucial for cell differentiation, cell stability maintenance, and tumorigenesis. Our goal was to systematize research studies dedicated to the investigation of structure and functions of super-enhancers as well as to define further perspectives of the field in various applications, such as drug development and clinical use. We overviewed the fundamental studies which provided experimental data on various pathologies and their associations with particular super-enhancers. The analysis of mainstream approaches for SE search and prediction allowed us to accumulate existing data and propose directions for further algorithmic improvements of SEs' reliability levels and efficiency. Thus, here we provide the description of the most robust algorithms such as ROSE, imPROSE, and DEEPSEN and suggest their further use for various research and development tasks. The most promising research direction, which is based on topic and number of published studies, are cancer-associated super-enhancers and prospective SE-targeted therapy strategies, most of which are discussed in this review.

Super-enhancer landscape rewiring in cancer: The epigenetic control at distal sites

Super-enhancers evolve as elements at the top of the hierarchical control of gene expression. They are important end-gatherers of signaling pathways that control stemness, differentiation or adaptive responses. Many epigenetic regulations focus on these regions, and not surprisingly, during the process of tumorigenesis, various alterations can account for their dysfunction. Super-enhancers are emerging as key drivers of the aberrant gene expression landscape that sustain the aggressiveness of cancer cells. In this review, we will describe and discuss about the structure of super-enhancers, their epigenetic regulation, and the major changes affecting their functionality in cancer.

Acetylation of histone H2B marks active enhancers and predicts CBP/p300 target genes

Chromatin features are widely used for genome-scale mapping of enhancers. However, discriminating active enhancers from other cis-regulatory elements, predicting enhancer strength and identifying their target genes is challenging. Here we establish histone H2B N-terminus multisite lysine acetylation (H2BNTac) as a signature of active enhancers. H2BNTac prominently marks candidate active enhancers and a subset of promoters and discriminates them from ubiquitously active promoters. Two mechanisms underlie the distinct H2BNTac specificity: (1) unlike H3K27ac, H2BNTac is specifically catalyzed by CBP/p300; (2) H2A-H2B, but not H3-H4, are rapidly exchanged through transcription-induced nucleosome remodeling. H2BNTac-positive candidate enhancers show a high validation rate in orthogonal enhancer activity assays and a vast majority of endogenously active enhancers are marked by H2BNTac and H3K27ac. Notably, H2BNTac intensity predicts enhancer strength and outperforms current state-of-the-art models in predicting CBP/p300 target genes. These findings have broad implications for generating fine-grained enhancer maps and modeling CBP/p300-dependent gene regulation.

Blocking Genomic Instability Prevents Acquired Resistance to MAPK Inhibitor Therapy in Melanoma

Blocking cancer genomic instability may prevent tumor diversification and escape from therapies. We show that, after MAPK inhibitor (MAPKi) therapy in patients and mice bearing patient-derived xenografts (PDX), acquired resistant genomes of metastatic cutaneous melanoma specifically amplify resistance-driver, nonhomologous end-joining (NHEJ), and homologous recombination repair (HRR) genes via complex genomic rearrangements (CGR) and extrachromosomal DNAs (ecDNA). Almost all sensitive and acquired-resistant genomes harbor pervasive chromothriptic regions with disproportionately high mutational burdens and significant overlaps with ecDNA and CGR spans. Recurrently, somatic mutations within ecDNA and CGR amplicons enrich for HRR signatures, particularly within acquired resistant tumors. Regardless of sensitivity or resistance, breakpoint-junctional sequence analysis suggests NHEJ as critical to double-stranded DNA break repair underlying CGR and ecDNA formation. In human melanoma cell lines and PDXs, NHEJ targeting by a DNA-PKCS inhibitor prevents/delays acquired MAPKi resistance by reducing the size of ecDNAs and CGRs early on combination treatment. Thus, targeting the causes of genomic instability prevents acquired resistance.

SIGNIFICANCE

Acquired resistance often results in heterogeneous, redundant survival mechanisms, which challenge strategies aimed at reversing resistance. Acquired-resistant melanomas recurrently evolve resistance-driving and resistance-specific amplicons via ecDNAs and CGRs, thereby nominating chromothripsis-ecDNA-CGR biogenesis as a resistance-preventive target. Specifically, targeting DNA-PKCS/NHEJ prevents resistance by suppressing ecDNA/CGR rearrangements in MAPKi-treated melanomas. This article is highlighted in the In This Issue feature, p. 799.

MultiomicsTracks96: A high throughput PIXUL-Matrix-based toolbox to profile frozen and FFPE tissues multiomes

Background

The multiome is an integrated assembly of distinct classes of molecules and molecular properties, or "omes," measured in the same biospecimen. Freezing and formalin-fixed paraffin-embedding (FFPE) are two common ways to store tissues, and these practices have generated vast biospecimen repositories. However, these biospecimens have been underutilized for multi-omic analysis due to the low throughput of current analytical technologies that impede large-scale studies.

Methods

Tissue sampling, preparation, and downstream analysis were integrated into a 96-well format multi-omics workflow, MultiomicsTracks96. Frozen mouse organs were sampled using the CryoGrid system, and matched FFPE samples were processed using a microtome. The 96-well format sonicator, PIXUL, was adapted to extract DNA, RNA, chromatin, and protein from tissues. The 96-well format analytical platform, Matrix, was used for chromatin immunoprecipitation (ChIP), methylated DNA immunoprecipitation (MeDIP), methylated RNA immunoprecipitation (MeRIP), and RNA reverse transcription (RT) assays followed by qPCR and sequencing. LC-MS/MS was used for protein analysis. The Segway genome segmentation algorithm was used to identify functional genomic regions, and linear regressors based on the multi-omics data were trained to predict protein expression.

Results

MultiomicsTracks96 was used to generate 8-dimensional datasets including RNA-seq measurements of mRNA expression; MeRIP-seq measurements of m6A and m5C; ChIP-seq measurements of H3K27Ac, H3K4m3, and Pol II; MeDIP-seq measurements of 5mC; and LC-MS/MS measurements of proteins. We observed high correlation between data from matched frozen and FFPE organs. The Segway genome segmentation algorithm applied to epigenomic profiles (ChIP-seq: H3K27Ac, H3K4m3, Pol II; MeDIP-seq: 5mC) was able to recapitulate and predict organ-specific super-enhancers in both FFPE and frozen samples. Linear regression analysis showed that proteomic expression profiles can be more accurately predicted by the full suite of multi-omics data, compared to using epigenomic, transcriptomic, or epitranscriptomic measurements individually.

Conclusions

The MultiomicsTracks96 workflow is well suited for high dimensional multi-omics studies - for instance, multiorgan animal models of disease, drug toxicities, environmental exposure, and aging as well as large-scale clinical investigations involving the use of biospecimens from existing tissue repositories.

eccDNA Atlas: a comprehensive resource of eccDNA catalog

Extrachromosomal circular DNA (eccDNA) represents a large category of non-mitochondrial and non-plasmid circular extrachromosomal DNA, playing an indispensable role in various aspects such as tumorigenesis, immune responses. However, the information of characteristics and functions about eccDNA is fragmented, hiding behind abundant literatures and massive whole-genome sequencing (WGS) data, which has not been sufficiently used for the identification of eccDNAs. Therefore, establishing an integrated repository portal is essential for identifying and analyzing eccDNAs. Here, we developed eccDNA Atlas (http://lcbb.swjtu.edu.cn/eccDNAatlas), a user-friendly database of eccDNAs that aims to provide a high-quality and integrated resource for browsing, searching and analyzing eccDNAs from multiple species. eccDNA Atlas currently contains 629 987 eccDNAs and 8221 ecDNAs manually curated from literatures and 1105 ecDNAs predicted by AmpliconArchitect based on WGS data involved in 66 diseases, 57 tissues and 319 cell lines. The content of each eccDNA entry includes multiple aspects such as sequence, disease, function, characteristic, validation strategies. Furthermore, abundant annotations and analyzing utilities were provided to explore existing eccDNAs in eccDNA Atlas or user-defined eccDNAs including oncogenes, typical enhancers, super enhancers, CTCF-binding sites, SNPs, chromatin accessibility, eQTLs, gene expression, survival and genome visualization. Overall, eccDNA Atlas provides an integrated eccDNA data warehouse and serves as an important tool for future research.

Comprehensive characterization of the embryonic factor LEUTX

The paired-like homeobox transcription factor LEUTX is expressed in human preimplantation embryos between the 4- and 8-cell stages, and then silenced in somatic tissues. To characterize the function of LEUTX, we performed a multiomic characterization of LEUTX using two proteomics methods and three genome-wide sequencing approaches. Our results show that LEUTX stably interacts with the EP300 and CBP histone acetyltransferases through its 9 amino acid transactivation domain (9aaTAD), as mutation of this domain abolishes the interactions. LEUTX targets genomic cis-regulatory sequences that overlap with repetitive elements, and through these elements it is suggested to regulate the expression of its downstream genes. We find LEUTX to be a transcriptional activator, upregulating several genes linked to preimplantation development as well as 8-cell-like markers, such as DPPA3 and ZNF280A. Our results support a role for LEUTX in preimplantation development as an enhancer binding protein and as a potent transcriptional activator.

Effect of mechanical unloading on genome-wide DNA methylation profile of the failing human heart

Heart failure (HF) is characterized by global alterations in myocardial DNA methylation, yet little is known about the epigenetic regulation of the noncoding genome and potential reversibility of DNA methylation with left ventricular assist device (LVAD) therapy. Genome-wide mapping of myocardial DNA methylation in 36 patients with HF at LVAD implantation, 8 patients at LVAD explantation, and 7 nonfailing (NF) donors using a high-density bead array platform identified 2,079 differentially methylated positions (DMPs) in ischemic cardiomyopathy (ICM) and 261 DMPs in nonischemic cardiomyopathy (NICM). LVAD support resulted in normalization of 3.2% of HF-associated DMPs. Methylation-expression correlation analysis yielded several protein-coding genes that are hypomethylated and upregulated (HTRA1, FBXO16, EFCAB13, and AKAP13) or hypermethylated and downregulated (TBX3) in HF. A potentially novel cardiac-specific super-enhancer long noncoding RNA (lncRNA) (LINC00881) is hypermethylated and downregulated in human HF. LINC00881 is an upstream regulator of sarcomere and calcium channel gene expression including MYH6, CACNA1C, and RYR2. LINC00881 knockdown reduces peak calcium amplitude in the beating human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). These data suggest that HF-associated changes in myocardial DNA methylation within coding and noncoding genomes are minimally reversible with mechanical unloading. Epigenetic reprogramming strategies may be necessary to achieve sustained clinical recovery from heart failure.

Superenhancers as master gene regulators and novel therapeutic targets in brain tumors

Transcriptional deregulation, a cancer cell hallmark, is driven by epigenetic abnormalities in the majority of brain tumors, including adult glioblastoma and pediatric brain tumors. Epigenetic abnormalities can activate epigenetic regulatory elements to regulate the expression of oncogenes. Superenhancers (SEs), identified as novel epigenetic regulatory elements, are clusters of enhancers with cell-type specificity that can drive the aberrant transcription of oncogenes and promote tumor initiation and progression. As gene regulators, SEs are involved in tumorigenesis in a variety of tumors, including brain tumors. SEs are susceptible to inhibition by their key components, such as bromodomain protein 4 and cyclin-dependent kinase 7, providing new opportunities for antitumor therapy. In this review, we summarized the characteristics and identification, unique organizational structures, and activation mechanisms of SEs in tumors, as well as the clinical applications related to SEs in tumor therapy and prognostication. Based on a review of the literature, we discussed the relationship between SEs and different brain tumors and potential therapeutic targets, focusing on glioblastoma.

Complexity of enhancer networks predicts cell identity and disease genes revealed by single-cell multi-omics analysis

Many enhancers exist as clusters in the genome and control cell identity and disease genes; however, the underlying mechanism remains largely unknown. Here, we introduce an algorithm, eNet, to build enhancer networks by integrating single-cell chromatin accessibility and gene expression profiles. The complexity of enhancer networks is assessed by two metrics: the number of enhancers and the frequency of predicted enhancer interactions (PEIs) based on chromatin co-accessibility. We apply eNet algorithm to a human blood dataset and find cell identity and disease genes tend to be regulated by complex enhancer networks. The network hub enhancers (enhancers with frequent PEIs) are the most functionally important. Compared with super-enhancers, enhancer networks show better performance in predicting cell identity and disease genes. eNet is robust and widely applicable in various human or mouse tissues datasets. Thus, we propose a model of enhancer networks containing three modes: Simple, Multiple and Complex, which are distinguished by their complexity in regulating gene expression. Taken together, our work provides an unsupervised approach to simultaneously identify key cell identity and disease genes and explore the underlying regulatory relationships among enhancers in single cells.

ChromLoops: a comprehensive database for specific protein-mediated chromatin loops in diverse organisms

Chromatin loops (or chromatin interactions) are important elements of chromatin structures. Disruption of chromatin loops is associated with many diseases, such as cancer and polydactyly. A few methods, including ChIA-PET, HiChIP and PLAC-Seq, have been proposed to detect high-resolution, specific protein-mediated chromatin loops. With rapid progress in 3D genomic research, ChIA-PET, HiChIP and PLAC-Seq datasets continue to accumulate, and effective collection and processing for these datasets are urgently needed. Here, we developed a comprehensive, multispecies and specific protein-mediated chromatin loop database (ChromLoops, https://3dgenomics.hzau.edu.cn/chromloops), which integrated 1030 ChIA-PET, HiChIP and PLAC-Seq datasets from 13 species, and documented 1 491 416 813 high-quality chromatin loops. We annotated genes and regions overlapping with chromatin loop anchors with rich functional annotations, such as regulatory elements (enhancers, super-enhancers and silencers), variations (common SNPs, somatic SNPs and eQTLs), and transcription factor binding sites. Moreover, we identified genes with high-frequency chromatin interactions in the collected species. In particular, we identified genes with high-frequency interactions in cancer samples. We hope that ChromLoops will provide a new platform for studying chromatin interaction regulation in relation to biological processes and disease.

SEdb 2.0: a comprehensive super-enhancer database of human and mouse

Super-enhancers (SEs) are cell-specific DNA cis-regulatory elements that can supervise the transcriptional regulation processes of downstream genes. SEdb 2.0 (http://www.licpathway.net/sedb) aims to provide a comprehensive SE resource and annotate their potential roles in gene transcriptions. Compared with SEdb 1.0, we have made the following improvements: (i) Newly added the mouse SEs and expanded the scale of human SEs. SEdb 2.0 contained 1 167 518 SEs from 1739 human H3K27ac chromatin immunoprecipitation sequencing (ChIP-seq) samples and 550 226 SEs from 931 mouse H3K27ac ChIP-seq samples, which was five times that of SEdb 1.0. (ii) Newly added transcription factor binding sites (TFBSs) in SEs identified by TF motifs and TF ChIP-seq data. (iii) Added comprehensive (epi)genetic annotations of SEs, including chromatin accessibility regions, methylation sites, chromatin interaction regions and topologically associating domains (TADs). (iv) Newly embedded and updated search and analysis tools, including 'Search SE by TF-based', 'Differential-Overlapping-SE analysis' and 'SE-based TF-Gene analysis'. (v) Newly provided quality control (QC) metrics for ChIP-seq processing. In summary, SEdb 2.0 is a comprehensive update of SEdb 1.0, which curates more SEs and annotation information than SEdb 1.0. SEdb 2.0 provides a friendly platform for researchers to more comprehensively clarify the important role of SEs in the biological process.

An atlas of transcribed human cardiac promoters and enhancers reveals an important role of regulatory elements in heart failure

A deeper knowledge of the dynamic transcriptional activity of promoters and enhancers is needed to improve mechanistic understanding of the pathogenesis of heart failure and heart diseases. In this study, we used cap analysis of gene expression (CAGE) to identify and quantify the activity of transcribed regulatory elements (TREs) in the four cardiac chambers of 21 healthy and ten failing adult human hearts. We identified 17,668 promoters and 14,920 enhancers associated with the expression of 14,519 genes. We showed how these regulatory elements are alternatively transcribed in different heart regions, in healthy versus failing hearts and in ischemic versus non-ischemic heart failure samples. Cardiac-disease-related single-nucleotide polymorphisms (SNPs) appeared to be enriched in TREs, potentially affecting the allele-specific transcription factor binding. To conclude, our open-source heart CAGE atlas will serve the cardiovascular community in improving the understanding of the role of the cardiac gene regulatory networks in cardiovascular disease and therapy.

Activation of HIV-1 proviruses increases downstream chromatin accessibility

It is unclear how the activation of HIV-1 transcription affects chromatin structure. We interrogated chromatin organization both genome-wide and nearby HIV-1 integration sites using Hi-C and ATAC-seq. In conjunction, we analyzed the transcription of the HIV-1 genome and neighboring genes. We found that long-range chromatin contacts did not differ significantly between uninfected cells and those harboring an integrated HIV-1 genome, whether the HIV-1 genome was actively transcribed or inactive. Instead, the activation of HIV-1 transcription changes chromatin accessibility immediately downstream of the provirus, demonstrating that HIV-1 can alter local cellular chromatin structure. Finally, we examined HIV-1 and neighboring host gene transcripts with long-read sequencing and found populations of chimeric RNAs both virus-to-host and host-to-virus. Thus, multiomics profiling revealed that the activation of HIV-1 transcription led to local changes in chromatin organization and altered the expression of neighboring host genes.