SEA: a super-enhancer archive

SEgene identifies links between super enhancers and gene expression across cell types

Enhancers are non-coding DNA regions that facilitate gene transcription, with a specialized subset, super-enhancers, known to exert exceptionally strong transcriptional activation effects. Super-enhancers have been implicated in oncogenesis, and their identification is achievable through histone mark chromatin immunoprecipitation followed by sequencing data using existing analytical tools. However, conventional super-enhancer detection methodologies often do not accurately reflect actual gene expression levels, and the large volume of identified super-enhancers complicates comprehensive analysis. To address these limitations, we developed the super-enhancer to gene links (SE-to-gene Links) analysis, a platform named "SEgene" which incorporates the peak-to-gene links approach-a statistical method designed to reveal correlations between genes and peak regions ( https://github.com/hamamoto-lab/SEgene ). This platform enables a targeted evaluation of super-enhancer regions in relation to gene expression, facilitating the identification of super-enhancers that are functionally linked to transcriptional activity. Here, we demonstrate the application of SE-to-gene Links analysis to public datasets, confirming its efficacy in accurately detecting super-enhancers and identifying functionally associated genes. Additionally, SE-to-gene Links analysis identified ERBB2 as a significant gene of interest in the lung adenocarcinoma dataset from the National Cancer Center Japan cohort, suggesting a potential impact across multiple patient samples. Thus, the SE-to-gene Links analysis provides an analytical tool for evaluating super-enhancers as potential therapeutic targets, supporting the identification of clinically significant super-enhancer regions and their functionally associated genes.

LncPepAtlas: a comprehensive resource for exploring the translational landscape of long non-coding RNAs

Long non-coding RNAs were commonly viewed as non-coding elements. However, they are increasingly recognized for their ability to be translated into proteins, thereby playing a significant role in various cellular processes and diseases. With developments in biotechnology and computational algorithms, a range of novel approaches are being applied to investigate the translation of long non-coding RNA (lncRNAs). Herein, we developed the LncPepAtlas database (http://www.cnitbiotool.net/LncPepAtlas/), which aims to compile multiple evidences for the translation of lncRNAs and annotations for the upstream regulation of lncRNAs across various species. LncPepAtlas integrated compelling evidence from nine distinct sources for the translation of lncRNAs. These include a dataset comprising 2631 publicly available Ribo-seq samples from nine species, which has been collected and analysed. LncPepAtlas offers extensive annotation for lncRNA upstream regulation and expression profiles across various cancers, tissues or cell lines at transcriptional and translational levels. Importantly, it enables novel antigen predictions for lncRNA-encoded peptides. By identifying numerous peptide candidates that could potentially bind to major histocompatibility complex class I and II molecules, this work may provide new insights into cancer immunotherapy. The function of peptides were inferred by aligning them with experimentally detected proteins. LncPepAtlas aims to become a convenient resource for exploring translatable lncRNAs.

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.

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.

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.

Spinal-Specific Super Enhancer in Neuropathic Pain

Dysfunctional gene expression in nociceptive pathways plays a critical role in the development and maintenance of neuropathic pain. Super enhancers (SEs), composed of a large cluster of transcriptional enhancers, are emerging as new players in the regulation of gene expression. However, whether SEs participate in nociceptive responses remains unknown. Here, we report a spinal-specific SE (SS-SE) that regulates chronic constriction injury (CCI)-induced neuropathic pain by driving Ntmt1 and Prrx2 transcription in dorsal horn neurons. Peripheral nerve injury significantly enhanced the activity of SS-SE and increased the expression of NTMT1 and PRRX2 in the dorsal horn of male mice in a bromodomain-containing protein 4 (BRD4)-dependent manner. Both intrathecal administration of a pharmacological BRD4 inhibitor JQ1 and CRISPR-Cas9-mediated SE deletion abolished the increased NTMT1 and PRRX2 in CCI mice and attenuated their nociceptive hypersensitivities. Furthermore, knocking down Ntmt1 or Prrx2 with siRNA suppressed the injury-induced elevation of phosphorylated extracellular-signal-regulated kinase (p-ERK) and glial fibrillary acidic protein (GFAP) expression in the dorsal horn and alleviated neuropathic pain behaviors. Mimicking the increase in spinal Ntmt1 or Prrx2 in naive mice increased p-ERK and GFAP expression and led to the genesis of neuropathic pain-like behavior. These results redefine our understanding of the regulation of pain-related genes and demonstrate that BRD4-driven increases in SS-SE activity is responsible for the genesis of neuropathic pain through the governance of NTMT1 and PRRX2 expression in dorsal horn neurons. Our findings highlight the therapeutic potential of BRD4 inhibitors for the treatment of neuropathic pain.SIGNIFICANCE STATEMENT SEs drive gene expression by recruiting master transcription factors, cofactors, and RNA polymerase, but their role in the development of neuropathic pain remains unknown. Here, we report that the activity of an SS-SE, located upstream of the genes Ntmt1 and Prrx2, was elevated in the dorsal horn of mice with neuropathic pain. SS-SE contributes to the genesis of neuropathic pain by driving expression of Ntmt1 and Prrx2 Both inhibition of SS-SE with a pharmacological BRD4 inhibitor and genetic deletion of SS-SE attenuated pain hypersensitivities. This study suggests an effective and novel therapeutic strategy for neuropathic pain.

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.

Analysis of super-enhancer using machine learning and its application to medical biology

The analysis of super-enhancers (SEs) has recently attracted attention in elucidating the molecular mechanisms of cancer and other diseases. SEs are genomic structures that strongly induce gene expression and have been reported to contribute to the overexpression of oncogenes. Because the analysis of SEs and integrated analysis with other data are performed using large amounts of genome-wide data, artificial intelligence technology, with machine learning at its core, has recently begun to be utilized. In promoting precision medicine, it is important to consider information from SEs in addition to genomic data; therefore, machine learning technology is expected to be introduced appropriately in terms of building a robust analysis platform with a high generalization performance. In this review, we explain the history and principles of SE, and the results of SE analysis using state-of-the-art machine learning and integrated analysis with other data are presented to provide a comprehensive understanding of the current status of SE analysis in the field of medical biology. Additionally, we compared the accuracy between existing machine learning methods on the benchmark dataset and attempted to explore the kind of data preprocessing and integration work needed to make the existing algorithms work on the benchmark dataset. Furthermore, we discuss the issues and future directions of current SE analysis.

Integrative analysis of a novel super-enhancer-associated lncRNA prognostic signature and identifying LINC00945 in aggravating glioma progression

BACKGROUND

Super-enhancers (SEs), driving high-level expression of genes with tumor-promoting functions, have been investigated recently. However, the roles of super-enhancer-associated lncRNAs (SE-lncRNAs) in tumors remain undetermined, especially in gliomas. We here established a SE-lncRNAs expression-based prognostic signature to choose the effective treatment of glioma and identify a novel therapeutic target.

METHODS

Combined analysis of RNA sequencing (RNA-seq) data and ChIP sequencing (ChIP-seq) data of glioma patient-derived glioma stem cells (GSCs) screened SE-lncRNAs. Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets served to construct and validate SE-lncRNA prognostic signature. The immune profiles and potential immuno- and chemotherapies response prediction value of the signature were also explored. Moreover, we verified the epigenetic activation mechanism of LINC00945 via the ChIP assay, and its effect on glioma was determined by performing the functional assay and a mouse xenograft model.

RESULTS

6 SE-lncRNAs were obtained and identified three subgroups of glioma patients with different prognostic and clinical features. A risk signature was further constructed and demonstrated to be an independent prognostic factor. The high-risk group exhibited an immunosuppressive microenvironment and was higher enrichment of M2 macrophage, regulatory T cells (Tregs), and Cancer-associated fibroblasts (CAFs). Patients in the high-risk group were better candidates for immunotherapy and chemotherapeutics. The SE of LINC00945 was further verified via ChIP assay. Mechanistically, BRD4 may mediate epigenetic activation of LINC00945. Additionally, overexpression of LINC00945 promoted glioma cell proliferation, EMT, migration, and invasion in vitro and xenograft tumor formation in vivo.

CONCLUSION

Our study constructed the first prognostic SE-lncRNA signature with the ability to optimize the choice of patients receiving immuno- and chemotherapies and provided a potential therapeutic target for glioma.

Efficient Selection of Enhancers and Promoters from MIA PaCa-2 Pancreatic Cancer Cells by ChIP-lentiMPRA

A library of active genome regulatory elements (putative promoters and enhancers) from MIA PaCa-2 pancreatic adenocarcinoma cells was constructed using a specially designed lentiviral vector and a massive parallel reporter assay (ChIP-lentiMPRA). Chromatin immunoprecipitation of the cell genomic DNA by H3K27ac antibodies was used for primary enrichment of the library for regulatory elements. Totally, 11,264 unique genome regions, many of which are capable of enhancing the expression of the CopGFP reporter gene from the minimal CMV promoter, were identified. The regions tend to be located near promoters. Based on the proximity assay, we found an enrichment of highly expressed genes among those associated with three or more mapped distal regions (2 kb distant from the 5'-ends of genes). It was shown significant enrichment of genes related to carcinogenesis or Mia PaCa-2 cell identity genes in this group. In contrast, genes associated with 1-2 distal regions or only with proximal regions (within 2 kbp of the 5'-ends of genes) are more often related to housekeeping functions. Thus, ChIP-lentiMPRA is a useful strategy for creating libraries of regulatory elements for the study of tumor-specific gene transcription.

Emerging Role of Enhancer RNAs as Potential Diagnostic and Prognostic Biomarkers in Cancer

Enhancers are distal cis-acting elements that are commonly recognized to regulate gene expression via cooperation with promoters. Along with regulating gene expression, enhancers can be transcribed and generate a class of non-coding RNAs called enhancer RNAs (eRNAs). The current discovery of abundant tissue-specific transcription of enhancers in various diseases such as cancers raises questions about the potential role of eRNAs in disease diagnosis and therapy. This review aimed to demonstrate the current understanding of eRNAs in cancer research with a focus on the potential roles of eRNAs as prognostic and diagnostic biomarkers in cancers.

Analysis of the landscape of human enhancer sequences in biological databases

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

Whole exome sequencing identifies novel germline variants of SLC15A4 gene as potentially cancer predisposing in familial colorectal cancer

About 15% of colorectal cancer (CRC) patients have first-degree relatives affected by the same malignancy. However, for most families the cause of familial aggregation of CRC is unknown. To identify novel high-to-moderate-penetrance germline variants underlying CRC susceptibility, we performed whole exome sequencing (WES) on four CRC cases and two unaffected members of a Polish family without any mutation in known CRC predisposition genes. After WES, we used our in-house developed Familial Cancer Variant Prioritization Pipeline and identified two novel variants in the solute carrier family 15 member 4 (SLC15A4) gene. The heterozygous missense variant, p. Y444C, was predicted to affect the phylogenetically conserved PTR2/POT domain and to have a deleterious effect on the function of the encoded peptide/histidine transporter. The other variant was located in the upstream region of the same gene (GRCh37.p13, 12_129308531_C_T; 43 bp upstream of transcription start site, ENST00000266771.5) and it was annotated to affect the promoter region of SLC15A4 as well as binding sites of 17 different transcription factors. Our findings of two distinct variants in the same gene may indicate a synergistic up-regulation of SLC15A4 as the underlying genetic cause and implicate this gene for the first time in genetic inheritance of familial CRC.

The molecular understanding of super-enhancer dysregulation in cancer

Abnormalities in the regulation of gene expression are associated with various pathological conditions. Among the distal regulatory elements in the genome, the activation of target genes by enhancers plays a central role in the formation of cell type-specific gene expression patterns. Super-enhancers are a subclass of enhancers that frequently contain multiple enhancer-like elements and are characterized by dense binding of master transcription factors and Mediator complexes and high signals of active histone marks. Super-enhancers have been studied in detail as important regulatory regions that control cell identity and contribute to the pathogenesis of diverse diseases. In cancer, super-enhancers have multifaceted roles by activating various oncogenes and other cancer-related genes and shaping characteristic gene expression patterns in cancer cells. Alterations in super-enhancer activities in cancer involve multiple mechanisms, including the dysregulation of transcription factors and the super-enhancer-associated genomic abnormalities. The study of super-enhancers could contribute to the identification of effective biomarkers and the development of cancer therapeutics targeting transcriptional addiction. In this review, we summarize the roles of super-enhancers in cancer biology, with a particular focus on hematopoietic malignancies, in which multiple super-enhancer alteration mechanisms have been reported.

PCRMS: a database of predicted cis-regulatory modules and constituent transcription factor binding sites in genomes

More accurate and more complete predictions of cis-regulatory modules (CRMs) and constituent transcription factor (TF) binding sites (TFBSs) in genomes can facilitate characterizing functions of regulatory sequences. Here, we developed a database predicted cis-regulatory modules (PCRMS) (https://cci-bioinfo.uncc.edu) that stores highly accurate and unprecedentedly complete maps of predicted CRMs and TFBSs in the human and mouse genomes. The web interface allows the user to browse CRMs and TFBSs in an organism, find the closest CRMs to a gene, search CRMs around a gene and find all TFBSs of a TF. PCRMS can be a useful resource for the research community to characterize regulatory genomes. Database URL: https://cci-bioinfo.uncc.edu/.

A Comparative Analysis of Super-Enhancers and Broad H3K4me3 Domains in Pig, Human, and Mouse Tissues

Super-enhancers (SEs) and broad H3K4me3 domains (BDs) are crucial regulators in the control of tissue identity in human and mouse. However, their features in pig remain largely unknown. In this study, by integrative computational analyses of epigenomic and transcriptomic data, we have characterized SEs and BDs in six pig tissues and analyzed their conservation in comparison with human and mouse tissues. Similar to human and mouse, pig SEs and BDs display higher tissue specificity than their typical counterparts. Genes proximal to SEs and BDs are associated with tissue identity in most tissues. About 55-182 SEs (5-17% in total) and 99-309 BDs (8-16% in total) across pig tissues are considered as functionally conserved elements because they have orthologous SEs and BDs in human and mouse. However, these elements do not necessarily exhibit sequence conservation. The functionally conserved SEs are correlated to tissue identity in majority of pig tissues, while those conserved BDs are linked to tissue identity in a few tissues. Our study provides resources for future gene regulatory studies in pig. It highlights that SEs are more effective in defining tissue identity than BDs, which is contrasting to a previous study. It also provides novel insights on understanding the sequence features of functionally conserved elements.

Seeing the forest through the trees: prioritising potentially functional interactions from Hi-C

Eukaryotic genomes are highly organised within the nucleus of a cell, allowing widely dispersed regulatory elements such as enhancers to interact with gene promoters through physical contacts in three-dimensional space. Recent chromosome conformation capture methodologies such as Hi-C have enabled the analysis of interacting regions of the genome providing a valuable insight into the three-dimensional organisation of the chromatin in the nucleus, including chromosome compartmentalisation and gene expression. Complicating the analysis of Hi-C data, however, is the massive amount of identified interactions, many of which do not directly drive gene function, thus hindering the identification of potentially biologically functional 3D interactions. In this review, we collate and examine the downstream analysis of Hi-C data with particular focus on methods that prioritise potentially functional interactions. We classify three groups of approaches: structural-based discovery methods, e.g. A/B compartments and topologically associated domains, detection of statistically significant chromatin interactions, and the use of epigenomic data integration to narrow down useful interaction information. Careful use of these three approaches is crucial to successfully identifying potentially functional interactions within the genome.

Whole Exome Sequencing Identifies APCDD1 and HDAC5 Genes as Potentially Cancer Predisposing in Familial Colorectal Cancer

Germline mutations in predisposition genes account for only 20% of all familial colorectal cancers (CRC) and the remaining genetic burden may be due to rare high- to moderate-penetrance germline variants that are not explored. With the aim of identifying such potential cancer-predisposing variants, we performed whole exome sequencing on three CRC cases and three unaffected members of a Polish family and identified two novel heterozygous variants: a coding variant in APC downregulated 1 gene (APCDD1, p.R299H) and a non-coding variant in the 5′ untranslated region (UTR) of histone deacetylase 5 gene (HDAC5). Sanger sequencing confirmed the variants segregating with the disease and Taqman assays revealed 8 additional APCDD1 variants in a cohort of 1705 familial CRC patients and no further HDAC5 variants. Proliferation assays indicated an insignificant proliferative impact for the APCDD1 variant. Luciferase reporter assays using the HDAC5 variant resulted in an enhanced promoter activity. Targeting of transcription factor binding sites of SNAI-2 and TCF4 interrupted by the HDAC5 variant showed a significant impact of TCF4 on promoter activity of mutated HDAC5. Our findings contribute not only to the identification of unrecognized genetic causes of familial CRC but also underline the importance of 5’UTR variants affecting transcriptional regulation and the pathogenesis of complex disorders.

Super enhancers-Functional cores under the 3D genome

Complex biochemical reactions take place in the nucleus all the time. Transcription machines must follow the rules. The chromatin state, especially the three-dimensional structure of the genome, plays an important role in gene regulation and expression. The super enhancers are important for defining cell identity in mammalian developmental processes and human diseases. It has been shown that the major components of transcriptional activation complexes are recruited by super enhancer to form phase-separated condensates. We summarize the current knowledge about super enhancer in the 3D genome. Furthermore, a new related transcriptional regulation model from super enhancer is outlined to explain its role in the mammalian cell progress.

Genetic Dissection of a Super Enhancer Controlling the Nppa-Nppb Cluster in the Heart

RATIONALE

ANP (atrial natriuretic peptide) and BNP (B-type natriuretic peptide), encoded by the clustered genes Nppa and Nppb, are important prognostic, diagnostic, and therapeutic proteins in cardiac disease. The spatiotemporal expression pattern and stress-induction of the Nppa and Nppb are tightly regulated, possibly involving their coregulation by an evolutionary conserved enhancer cluster.

OBJECTIVE

To explore the physiological functions of the enhancer cluster and elucidate the genomic mechanism underlying Nppa-Nppb coregulation in vivo.

METHODS AND RESULTS

By analyzing epigenetic data we uncovered an enhancer cluster with super enhancer characteristics upstream of Nppb. Using CRISPR/Cas9 genome editing, the enhancer cluster or parts thereof, Nppb and flanking regions or the entire genomic block spanning Nppa-Nppb, respectively, were deleted from the mouse genome. The impact on gene regulation and phenotype of the respective mouse lines was investigated by transcriptomic, epigenomic, and phenotypic analyses. The enhancer cluster was essential for prenatal and postnatal ventricular expression of Nppa and Nppb but not of any other gene. Enhancer cluster-deficient mice showed enlarged hearts before and after birth, similar to Nppa-Nppb compound knockout mice we generated. Analysis of the other deletion alleles indicated the enhancer cluster engages the promoters of Nppa and Nppb in a competitive rather than a cooperative mode, resulting in increased Nppa expression when Nppb and flanking sequences were deleted. The enhancer cluster maintained its active epigenetic state and selectivity when its target genes are absent. In enhancer cluster-deficient animals, Nppa was induced but remained low in the postmyocardial infarction border zone and in the hypertrophic ventricle, involving regulatory sequences proximal to Nppa.

CONCLUSIONS

Coordinated ventricular expression of Nppa and Nppb is controlled in a competitive manner by a shared super enhancer, which is also required to augment stress-induced expression and to prevent premature hypertrophy.

Shikonin induces tumor apoptosis in glioma cells via endoplasmic reticulum stress, and Bax/Bak mediated mitochondrial outer membrane permeability

ETHNOPHARMACOLOGICAL RELEVANCE

Shikonin, one of the main active ingredients of Chinese herbal medicine Lithospermum erythrorhizon, has been widely used to treat various disease including virus infection and inflammation in clinical. Its anti-tumor activity has been recorded in "Chinese herbal medicine". Recently, some studies about its anti-glioma effects have been reported. However, little is known about the molecular pharmacological activity of Shikonin in glioma.

AIM

This study aimed to systematically uncover and validate the pharmacological mechanism of Shikonin against glioma.

MATERIAL AND METHODS

Network pharmacology approach, survival analysis, and Pearson co-expression analysis were performed to uncover and test the pharmacological mechanisms of Shikonin in glioma. Apoptosis assay, Caspase-3 activity assay and immunoblot analysis were practiced to validate the mechanisms.

RESULTS

Network pharmacology results suggested, anti-glioma effect of Shikonin by interfering endoplasmic reticulum (ER) stress-mediated tumor apoptosis targeting Caspase-3, and Bax/Bak-induced mitochondrial outer membrane permeabilization (MOMP) triggering cancer cell apoptosis. Survival analysis suggested the association of CASP3 with glioma (P < 0.05). Pearson correlation analysis indicated possible interaction of CASP3 with PERK through positive feedback regulation. Shikonin or in combination with 14G2a induced cell apoptosis in oligodendroglioma Hs683 cells in a dose-dependent manner with at a maximum apoptosis rate of 33%-37.5%, and 73%-77% respectively. Immunoblot analysis showed that Shikonin increased Caspase-3 activity to about 4.29 times, and increased 9 times when it combined with 14G2a. Shikonin increased also the expression levels of the proteins PERK and CHOP by about 4.4 and 5.6 folds, respectively, when it combined with 14G2a.

CONCLUSIONS

This study highlights the pharmacological mechanisms of Shikonin in the induction of tumor apoptosis in glioma cells.

Super-enhancer in prostate cancer: transcriptional disorders and therapeutic targets

Abnormal activity of oncogenic and tumor-suppressor signaling pathways contributes to cancer and cancer risk in humans. Transcriptional dysregulation of these pathways is commonly associated with tumorigenesis and the development of cancer. Genetic and epigenetic alterations may mediate dysregulated transcriptional activity. One of the most important epigenetic alternations is the non-coding regulatory element, which includes both enhancers and super-enhancers (SEs). SEs, characterized as large clusters of enhancers with aberrant high levels of transcription factor binding, have been considered as key drivers of gene expression in controlling and maintaining cancer cell identity. In cancer cells, oncogenes acquire SEs and the cancer phenotype relies on these abnormal transcription programs driven by SEs, which leads to cancer cells often becoming addicted to the SEs-related transcription programs, including prostate cancer. Here, we summarize recent findings of SEs and SEs-related gene regulation in prostate cancer and review the potential pharmacological inhibitors in basic research and clinical trials.

The emerging role of super enhancer-derived noncoding RNAs in human cancer

Super enhancers (SEs) are large clusters of adjacent enhancers that drive the expression of genes which regulate cellular identity; SE regions can be enriched with a high density of transcription factors, co-factors, and enhancer-associated epigenetic modifications. Through enhanced activation of their target genes, SEs play an important role in various diseases and conditions, including cancer. Recent studies have shown that SEs not only activate the transcriptional expression of coding genes to directly regulate biological functions, but also drive the transcriptional expression of non-coding RNAs (ncRNAs) to indirectly regulate biological functions. SE-derived ncRNAs play critical roles in tumorigenesis, including malignant proliferation, metastasis, drug resistance, and inflammatory response. Moreover, the abnormal expression of SE-derived ncRNAs is closely related to the clinical and pathological characterization of tumors. In this review, we summarize the functions and roles of SE-derived ncRNAs in tumorigenesis and discuss their prospective applications in tumor therapy. A deeper understanding of the potential mechanism underlying the action of SE-derived ncRNAs in tumorigenesis may provide new strategies for the early diagnosis of tumors and targeted therapy.

Characterization of super-enhancer-associated functional lncRNAs acting as ceRNAs in ESCC

Long noncoding RNAs (lncRNAs) have important regulatory roles in cancer biology. Although some lncRNAs have well-characterized functions, the vast majority of this class of molecules remains functionally uncharacterized. To systematically pinpoint functional lncRNAs, a computational approach was proposed for identification of lncRNA-mediated competing endogenous RNAs (ceRNAs) through combining global and local regulatory direction consistency of expression. Using esophageal squamous cell carcinoma (ESCC) as model, we further identified many known and novel functional lncRNAs acting as ceRNAs (ce-lncRNAs). We found that most of them significantly regulated the expression of cancer-related hallmark genes. These ce-lncRNAs were significantly regulated by enhancers, especially super-enhancers (SEs). Landscape analyses for lncRNAs further identified SE-associated functional ce-lncRNAs in ESCC, such as HOTAIR, XIST, SNHG5, and LINC00094. THZ1, a specific CDK7 inhibitor, can result in global transcriptional downregulation of SE-associated ce-lncRNAs. We further demonstrate that a SE-associated ce-lncRNA, LINC00094 can be activated by transcription factors TCF3 and KLF5 through binding to SE regions and promoted ESCC cancer cell growth. THZ1 downregulated expression of LINC00094 through inhibiting TCF3 and KLF5. Our data demonstrated the important roles of SE-associated ce-lncRNAs in ESCC oncogenesis and might serve as targets for ESCC diagnosis and therapy.

SEanalysis: a web tool for super-enhancer associated regulatory analysis

Super-enhancers (SEs) have prominent roles in biological and pathological processes through their unique transcriptional regulatory capability. To date, several SE databases have been developed by us and others. However, these existing databases do not provide downstream or upstream regulatory analyses of SEs. Pathways, transcription factors (TFs), SEs, and SE-associated genes form complex regulatory networks. Therefore, we designed a novel web server, SEanalysis, which provides comprehensive SE-associated regulatory network analyses. SEanalysis characterizes SE-associated genes, TFs binding to target SEs, and their upstream pathways. The current version of SEanalysis contains more than 330 000 SEs from more than 540 types of cells/tissues, 5042 TF ChIP-seq data generated from these cells/tissues, DNA-binding sequence motifs for ∼700 human TFs and 2880 pathways from 10 databases. SEanalysis supports searching by either SEs, samples, TFs, pathways or genes. The complex regulatory networks formed by these factors can be interactively visualized. In addition, we developed a customizable genome browser containing >6000 customizable tracks for visualization. The server is freely available at http://licpathway.net/SEanalysis.

SEA version 3.0: a comprehensive extension and update of the Super-Enhancer archive

Super-enhancers (SEs) are critical for the transcriptional regulation of gene expression. We developed the super-enhancer archive version 3.0 (SEA v. 3.0, http://sea.edbc.org) to extend SE research. SEA v. 3.0 provides the most comprehensive archive to date, consisting of 164 545 super-enhancers. Of these, 80 549 are newly identified from 266 cell types/tissues/diseases using an optimized computational strategy, and 52 have been experimentally confirmed with manually curated references. We now support super-enhancers in 11 species including 7 new species (zebrafish, chicken, chimp, rhesus, sheep, Xenopus tropicalis and stickleback). To facilitate super-enhancer functional analysis, we added several new regulatory datasets including 3 361 785 typical enhancers, chromatin interactions, SNPs, transcription factor binding sites and SpCas9 target sites. We also updated or developed new criteria query, genome visualization and analysis tools for the archive. This includes a tool based on Shannon Entropy to evaluate SE cell type specificity, a new genome browser that enables the visualization of SE spatial interactions based on Hi-C data, and an enhanced enrichment analysis interface that provides online enrichment analyses of SE related genes. SEA v. 3.0 provides a comprehensive database of all available SE information across multiple species, and will facilitate super-enhancer research, especially as related to development and disease.

EnhancerAtlas 2.0: an updated resource with enhancer annotation in 586 tissue/cell types across nine species

Enhancers are distal cis-regulatory elements that activate the transcription of their target genes. They regulate a wide range of important biological functions and processes, including embryogenesis, development, and homeostasis. As more and more large-scale technologies were developed for enhancer identification, a comprehensive database is highly desirable for enhancer annotation based on various genome-wide profiling datasets across different species. Here, we present an updated database EnhancerAtlas 2.0 (http://www.enhanceratlas.org/indexv2.php), covering 586 tissue/cell types that include a large number of normal tissues, cancer cell lines, and cells at different development stages across nine species. Overall, the database contains 13 494 603 enhancers, which were obtained from 16 055 datasets using 12 high-throughput experiment methods (e.g. H3K4me1/H3K27ac, DNase-seq/ATAC-seq, P300, POLR2A, CAGE, ChIA-PET, GRO-seq, STARR-seq and MPRA). The updated version is a huge expansion of the first version, which only contains the enhancers in human cells. In addition, we predicted enhancer–target gene relationships in human, mouse and fly. Finally, the users can search enhancers and enhancer–target gene relationships through five user-friendly, interactive modules. We believe the new annotation of enhancers in EnhancerAtlas 2.0 will facilitate users to perform useful functional analysis of enhancers in various genomes.

OncoBase: a platform for decoding regulatory somatic mutations in human cancers

Whole-exome and whole-genome sequencing have revealed millions of somatic mutations associated with different human cancers, and the vast majority of them are located outside of coding sequences, making it challenging to directly interpret their functional effects. With the rapid advances in high-throughput sequencing technologies, genome-scale long-range chromatin interactions were detected, and distal target genes of regulatory elements were determined using three-dimensional (3D) chromatin looping. Herein, we present OncoBase (http://www.oncobase.biols.ac.cn/), an integrated database for annotating 81 385 242 somatic mutations in 68 cancer types from more than 120 cancer projects by exploring their roles in distal interactions between target genes and regulatory elements. OncoBase integrates local chromatin signatures, 3D chromatin interactions in different cell types and reconstruction of enhancer-target networks using state-of-the-art algorithms. It employs informative visualization tools to display the integrated local and 3D chromatin signatures and effects of somatic mutations on regulatory elements. Enhancer-promoter interactions estimated from chromatin interactions are integrated into a network diffusion system that quantitatively prioritizes somatic mutations and target genes from a large pool. Thus, OncoBase is a useful resource for the functional annotation of regulatory noncoding regions and systematically benchmarking the regulatory effects of embedded noncoding somatic mutations in human carcinogenesis.

ENdb: a manually curated database of experimentally supported enhancers for human and mouse

Enhancers are a class of cis-regulatory elements that can increase gene transcription by forming loops in intergenic regions, introns and exons. Enhancers, as well as their associated target genes, and transcription factors (TFs) that bind to them, are highly associated with human disease and biological processes. Although some enhancer databases have been published, most only focus on enhancers identified by high-throughput experimental techniques. Therefore, it is highly desirable to construct a comprehensive resource of manually curated enhancers and their related information based on low-throughput experimental evidences. Here, we established a comprehensive manually-curated enhancer database for human and mouse, which provides a resource for experimentally supported enhancers, and to annotate the detailed information of enhancers. The current release of ENdb documents 737 experimentally validated enhancers and their related information, including 384 target genes, 263 TFs, 110 diseases and 153 functions in human and mouse. Moreover, the enhancer-related information was supported by experimental evidences, such as RNAi, in vitro knockdown, western blotting, qRT-PCR, luciferase reporter assay, chromatin conformation capture (3C) and chromosome conformation capture-on-chip (4C) assays. ENdb provides a user-friendly interface to query, browse and visualize the detailed information of enhancers. The database is available at http://www.licpathway.net/ENdb.

Super-enhancers in transcriptional regulation and genome organization

Gene expression is precisely controlled in a stage and cell-type-specific manner, largely through the interaction between cis-regulatory elements and their associated trans-acting factors. Where these components aggregate in promoters and enhancers, they are able to cooperate to modulate chromatin structure and support the engagement in long-range 3D superstructures that shape the dynamics of a cell's genomic architecture. Recently, the term 'super-enhancer' has been introduced to describe a hyper-active regulatory domain comprising a complex array of sequence elements that work together to control the key gene networks involved in cell identity. Here, we survey the unique characteristics of super-enhancers compared to other enhancer types and summarize the recent advances in our understanding of their biological role in gene regulation. In particular, we discuss their capacity to attract the formation of phase-separated condensates, and capacity to generate three-dimensional genome structures that precisely activate their target genes. We also propose a multi-stage transition model to explain the evolutionary pressure driving the development of super-enhancers in complex organisms, and highlight the potential for involvement in tumorigenesis. Finally, we discuss more broadly the role of super-enhancers in human health disorders and related potential in therapeutic interventions.

Super-enhancers: A new frontier for glioma treatment

Glioma is the most common primary malignant tumor in the human brain. Although there are a variety of treatments, such as surgery, radiation and chemotherapy, glioma is still an incurable disease. Super-enhancers (SEs) are implicated in the control of tumor cell identity, and they promote oncogenic transcription, which supports tumor cells. Inhibition of the SE complex, which is required for the assembly and maintenance of SEs, may repress oncogenic transcription and impede tumor growth. In this review, we discuss the unique characteristics of SEs compared to typical enhancers, and we summarize the recent advances in the understanding of their properties and biological role in gene regulation. Additionally, we highlight that SE-driven lncRNAs, miRNAs and genes are involved in the malignant phenotype of glioma. Most importantly, the application of SE inhibitors in different cancer subtypes has introduced new directions in glioma treatment.

Integrated Epigenome, Exome, and Transcriptome Analyses Reveal Molecular Subtypes and Homeotic Transformation in Uterine Fibroids

Uterine fibroids are benign myometrial smooth muscle tumors of unknown etiology that, when symptomatic, are the most common indication for hysterectomy in the United States. Unsupervised clustering of results from DNA methylation analyses segregates normal myometrium from fibroids and further segregates the fibroids into subtypes characterized by MED12 mutation or activation of either HMGA2 or HMGA1 expression. Upregulation of HMGA2 expression does not always appear to be dependent on translocation but is associated with hypomethylation in the HMGA2 gene body. HOXA13 expression is upregulated in fibroids and correlates with expression of typical uterine fibroid genes. Significant overlap of differentially expressed genes is observed between cervical stroma and uterine fibroids compared with normal myometrium. These analyses show a possible role of DNA methylation in fibroid biology and suggest that homeotic transformation of myometrial cells to a more cervical stroma phenotype could be an important mechanism for etiology of the disease.

Identification of gene specific cis-regulatory elements during differentiation of mouse embryonic stem cells: An integrative approach using high-throughput datasets

Gene expression governs cell fate, and is regulated via a complex interplay of transcription factors and molecules that change chromatin structure. Advances in sequencing-based assays have enabled investigation of these processes genome-wide, leading to large datasets that combine information on the dynamics of gene expression, transcription factor binding and chromatin structure as cells differentiate. While numerous studies focus on the effects of these features on broader gene regulation, less work has been done on the mechanisms of gene-specific transcriptional control. In this study, we have focussed on the latter by integrating gene expression data for the in vitro differentiation of murine ES cells to macrophages and cardiomyocytes, with dynamic data on chromatin structure, epigenetics and transcription factor binding. Combining a novel strategy to identify communities of related control elements with a penalized regression approach, we developed individual models to identify the potential control elements predictive of the expression of each gene. Our models were compared to an existing method and evaluated using the existing literature and new experimental data from embryonic stem cell differentiation reporter assays. Our method is able to identify transcriptional control elements in a gene specific manner that reflect known regulatory relationships and to generate useful hypotheses for further testing.

An enhancer cluster controls gene activity and topology of the SCN5A-SCN10A locus in vivo

Mutations and variations in and around SCN5A, encoding the major cardiac sodium channel, influence impulse conduction and are associated with a broad spectrum of arrhythmia disorders. Here, we identify an evolutionary conserved regulatory cluster with super enhancer characteristics downstream of SCN5A, which drives localized cardiac expression and contains conduction velocity-associated variants. We use genome editing to create a series of deletions in the mouse genome and show that the enhancer cluster controls the conformation of a >0.5 Mb genomic region harboring multiple interacting gene promoters and enhancers. We find that this cluster and its individual components are selectively required for cardiac Scn5a expression, normal cardiac conduction and normal embryonic development. Our studies reveal physiological roles of an enhancer cluster in the SCN5A-SCN10A locus, show that it controls the chromatin architecture of the locus and Scn5a expression, and suggest that genetic variants affecting its activity may influence cardiac function.

Whole Genome Sequencing of Familial Non-Medullary Thyroid Cancer Identifies Germline Alterations in MAPK/ERK and PI3K/AKT Signaling Pathways

Evidence of familial inheritance in non-medullary thyroid cancer (NMTC) has accumulated over the last few decades. However, known variants account for a very small percentage of the genetic burden. Here, we focused on the identification of common pathways and networks enriched in NMTC families to better understand its pathogenesis with the final aim of identifying one novel high/moderate-penetrance germline predisposition variant segregating with the disease in each studied family. We performed whole genome sequencing on 23 affected and 3 unaffected family members from five NMTC-prone families and prioritized the identified variants using our Familial Cancer Variant Prioritization Pipeline (FCVPPv2). In total, 31 coding variants and 39 variants located in upstream, downstream, 5′ or 3′ untranslated regions passed FCVPPv2 filtering. Altogether, 210 genes affected by variants that passed the first three steps of the FCVPPv2 were analyzed using Ingenuity Pathway Analysis software. These genes were enriched in tumorigenic signaling pathways mediated by receptor tyrosine kinases and G-protein coupled receptors, implicating a central role of PI3K/AKT and MAPK/ERK signaling in familial NMTC. Our approach can facilitate the identification and functional validation of causal variants in each family as well as the screening and genetic counseling of other individuals at risk of developing NMTC.

Isolation and genome-wide characterization of cellular DNA:RNA triplex structures

RNA can directly bind to purine-rich DNA via Hoogsteen base pairing, forming a DNA:RNA triple helical structure that anchors the RNA to specific sequences and allows guiding of transcription regulators to distinct genomic loci. To unravel the prevalence of DNA:RNA triplexes in living cells, we have established a fast and cost-effective method that allows genome-wide mapping of DNA:RNA triplex interactions. In contrast to previous approaches applied for the identification of chromatin-associated RNAs, this method uses protein-free nucleic acids isolated from chromatin. High-throughput sequencing and computational analysis of DNA-associated RNA revealed a large set of RNAs which originate from non-coding and coding loci, including super-enhancers and repeat elements. Combined analysis of DNA-associated RNA and RNA-associated DNA identified genomic DNA:RNA triplex structures. The results suggest that triplex formation is a general mechanism of RNA-mediated target-site recognition, which has major impact on biological functions.

DiseaseEnhancer: a resource of human disease-associated enhancer catalog

Large-scale sequencing studies discovered substantial genetic variants occurring in enhancers which regulate genes via long range chromatin interactions. Importantly, such variants could affect enhancer regulation by changing transcription factor bindings or enhancer hijacking, and in turn, make an essential contribution to disease progression. To facilitate better usage of published data and exploring enhancer deregulation in various human diseases, we created DiseaseEnhancer (http://biocc.hrbmu.edu.cn/DiseaseEnhancer/), a manually curated database for disease-associated enhancers. As of July 2017, DiseaseEnhancer includes 847 disease-associated enhancers in 143 human diseases. Database features include basic enhancer information (i.e. genomic location and target genes); disease types; associated variants on the enhancer and their mediated phenotypes (i.e. gain/loss of enhancer and the alterations of transcription factor bindings). We also include a feature on our website to export any query results into a file and download the full database. DiseaseEnhancer provides a promising avenue for researchers to facilitate the understanding of enhancer deregulation in disease pathogenesis, and identify new biomarkers for disease diagnosis and therapy.

Beyond the Exome: The Non-coding Genome and Enhancers in Neurodevelopmental Disorders and Malformations of Cortical Development

The development of the human cerebral cortex is a complex and dynamic process, in which neural stem cell proliferation, neuronal migration, and post-migratory neuronal organization need to occur in a well-organized fashion. Alterations at any of these crucial stages can result in malformations of cortical development (MCDs), a group of genetically heterogeneous neurodevelopmental disorders that present with developmental delay, intellectual disability and epilepsy. Recent progress in genetic technologies, such as next generation sequencing, most often focusing on all protein-coding exons (e.g., whole exome sequencing), allowed the discovery of more than a 100 genes associated with various types of MCDs. Although this has considerably increased the diagnostic yield, most MCD cases remain unexplained. As Whole Exome Sequencing investigates only a minor part of the human genome (1-2%), it is likely that patients, in which no disease-causing mutation has been identified, could harbor mutations in genomic regions beyond the exome. Even though functional annotation of non-coding regions is still lagging behind that of protein-coding genes, tremendous progress has been made in the field of gene regulation. One group of non-coding regulatory regions are enhancers, which can be distantly located upstream or downstream of genes and which can mediate temporal and tissue-specific transcriptional control via long-distance interactions with promoter regions. Although some examples exist in literature that link alterations of enhancers to genetic disorders, a widespread appreciation of the putative roles of these sequences in MCDs is still lacking. Here, we summarize the current state of knowledge on cis-regulatory regions and discuss novel technologies such as massively-parallel reporter assay systems, CRISPR-Cas9-based screens and computational approaches that help to further elucidate the emerging role of the non-coding genome in disease. Moreover, we discuss existing literature on mutations or copy number alterations of regulatory regions involved in brain development. We foresee that the future implementation of the knowledge obtained through ongoing gene regulation studies will benefit patients and will provide an explanation to part of the missing heritability of MCDs and other genetic disorders.

The SNP of rs6854845 suppresses transcription via the DNA looping structure alteration of super-enhancer in colon cells

Single-nucleotide polymorphisms (SNPs) identified by Genome-Wide Association Studies (GWASs) have been determined to closely connect with multiple diseases. Previous studies revealed one underlying mechanism that SNPs located within the regulatory elements could affect the encoding gene expression through long-range regulation. SNP rs6854845 was suggested to be a risk of colon cancer in human population. Nevertheless, the underlying molecular mechanism for colon carcinogenesis remains largely unknown. In present study, rs6854845 with G > T mutation in situ in FHC, HCT-116 and SW-480 cells were generated by Crispr/Cas9. The nearby chromatin organization was investigated by chromatin conformation capture (3C). And the expression of coding gene regulated by super-enhancer (SE) was detected by real-time PCR. We observed a significantly different pattern of the genome organization upon rs6854845 generation in colon epithelial cells but not in colon cancer cells. Moreover, we observed the shifted enrichment of H3K4me1 and H3K27ac at the SE (chr4:75.7M-76.0 M) where rs6854845 located. Furthermore, we observed that the transcription of the gene clusters regulated by SE were affected by rs6854845 in colon cells. Overall, our results demonstrated that SNP rs6854845 located in SE could destroy the long-range chromosomal interaction between SE and target gene clusters thereby affecting the transcription of these genes.

PLAIDOH: a novel method for functional prediction of long non-coding RNAs identifies cancer-specific LncRNA activities

BACKGROUND

Long non-coding RNAs (lncRNAs) exhibit remarkable cell-type specificity and disease association. LncRNA's functional versatility includes epigenetic modification, nuclear domain organization, transcriptional control, regulation of RNA splicing and translation, and modulation of protein activity. However, most lncRNAs remain uncharacterized due to a shortage of predictive tools available to guide functional experiments.

RESULTS

To address this gap for lymphoma-associated lncRNAs identified in our studies, we developed a new computational method, Predicting LncRNA Activity through Integrative Data-driven 'Omics and Heuristics (PLAIDOH), which has several unique features not found in other methods. PLAIDOH integrates transcriptome, subcellular localization, enhancer landscape, genome architecture, chromatin interaction, and RNA-binding (eCLIP) data and generates statistically defined output scores. PLAIDOH's approach identifies and ranks functional connections between individual lncRNA, coding gene, and protein pairs using enhancer, transcript cis-regulatory, and RNA-binding protein interactome scores that predict the relative likelihood of these different lncRNA functions. When applied to 'omics datasets that we collected from lymphoma patients, or to publicly available cancer (TCGA) or ENCODE datasets, PLAIDOH identified and prioritized well-known lncRNA-target gene regulatory pairs (e.g., HOTAIR and HOX genes, PVT1 and MYC), validated hits in multiple lncRNA-targeted CRISPR screens, and lncRNA-protein binding partners (e.g., NEAT1 and NONO). Importantly, PLAIDOH also identified novel putative functional interactions, including one lymphoma-associated lncRNA based on analysis of data from our human lymphoma study. We validated PLAIDOH's predictions for this lncRNA using knock-down and knock-out experiments in lymphoma cell models.

CONCLUSIONS

Our study demonstrates that we have developed a new method for the prediction and ranking of functional connections between individual lncRNA, coding gene, and protein pairs, which were validated by genetic experiments and comparison to published CRISPR screens. PLAIDOH expedites validation and follow-on mechanistic studies of lncRNAs in any biological system. It is available at https://github.com/sarahpyfrom/PLAIDOH .

Modeling double strand break susceptibility to interrogate structural variation in cancer

BACKGROUND

Structural variants (SVs) are known to play important roles in a variety of cancers, but their origins and functional consequences are still poorly understood. Many SVs are thought to emerge from errors in the repair processes following DNA double strand breaks (DSBs).

RESULTS

We used experimentally quantified DSB frequencies in cell lines with matched chromatin and sequence features to derive the first quantitative genome-wide models of DSB susceptibility. These models are accurate and provide novel insights into the mutational mechanisms generating DSBs. Models trained in one cell type can be successfully applied to others, but a substantial proportion of DSBs appear to reflect cell type-specific processes. Using model predictions as a proxy for susceptibility to DSBs in tumors, many SV-enriched regions appear to be poorly explained by selectively neutral mutational bias alone. A substantial number of these regions show unexpectedly high SV breakpoint frequencies given their predicted susceptibility to mutation and are therefore credible targets of positive selection in tumors. These putatively positively selected SV hotspots are enriched for genes previously shown to be oncogenic. In contrast, several hundred regions across the genome show unexpectedly low levels of SVs, given their relatively high susceptibility to mutation. These novel coldspot regions appear to be subject to purifying selection in tumors and are enriched for active promoters and enhancers.

CONCLUSIONS

We conclude that models of DSB susceptibility offer a rigorous approach to the inference of SVs putatively subject to selection in tumors.

Differentiated super-enhancers in lung cancer cells

Super-enhancers (SEs) are regulatory elements with enriched accumulation of key transcription factors. Few studies were done investigating SEs in lung cancers. Here we analyzed epigenetic profiling data to identify SEs in lung cancer cell lines. Enhancers were classified as SEs and typical enhancers (TEs). Most of the TEs were overlapped between normal cell and cancer cells. A great portion of SEs were differentiated comparing these cells. Analysis of GO terms associated with SEs revealed SE remodeling (lost on some sites while gain on others) between normal and lung cancer cells. By comparing the average number of SEs in each GO term in cancer cells with the number in control cells, surprisingly, no GO terms with significantly increased SE number in cancer condition were observed. On the contrary, in aspects such as "cell-cell adhesion", "receptor activity" and "negative regulation of canonical Wnt signaling pathway", the related SEs were significantly reduced in cancer cells. These findings suggest that in lung cancer, cells may not gain decisive gene expression in the related aspect, instead, they may have lost control of the fateful genes. Taken together, our work with the usability of omics data identified SEs in lung cancer cells and further showed cancer-specific features of SE-related terms.

HACER: an atlas of human active enhancers to interpret regulatory variants

Recent studies have shown that disease-susceptibility variants frequently lie in cell-type-specific enhancer elements. To identify, interpret, and prioritize such risk variants, we must identify the enhancers active in disease-relevant cell types, their upstream transcription factor (TF) binding, and their downstream target genes. To address this need, we built HACER (http://bioinfo.vanderbilt.edu/AE/HACER/), an atlas of Human ACtive Enhancers to interpret Regulatory variants. The HACER atlas catalogues and annotates in-vivo transcribed cell-type-specific enhancers, as well as placing enhancers within transcriptional regulatory networks by integrating ENCODE TF ChIP-Seq and predicted/validated chromatin interaction data. We demonstrate the utility of HACER in (i) offering a mechanistic hypothesis to explain the association of SNP rs614367 with ER-positive breast cancer risk, (ii) exploring tumor-specific enhancers in selective MYC dysregulation and (iii) prioritizing/annotating non-coding regulatory regions targeting CCND1. HACER provides a valuable resource for studies of GWAS, non-coding variants, and enhancer-mediated regulation.

SEdb: a comprehensive human super-enhancer database

Super-enhancers are important for controlling and defining the expression of cell-specific genes. With research on human disease and biological processes, human H3K27ac ChIP-seq datasets are accumulating rapidly, creating the urgent need to collect and process these data comprehensively and efficiently. More importantly, many studies showed that super-enhancer-associated single nucleotide polymorphisms (SNPs) and transcription factors (TFs) strongly influence human disease and biological processes. Here, we developed a comprehensive human super-enhancer database (SEdb, http://www.licpathway.net/sedb) that aimed to provide a large number of available resources on human super-enhancers. The database was annotated with potential functions of super-enhancers in the gene regulation. The current version of SEdb documented a total of 331 601 super-enhancers from 542 samples. Especially, unlike existing super-enhancer databases, we manually curated and classified 410 available H3K27ac samples from >2000 ChIP-seq samples from NCBI GEO/SRA. Furthermore, SEdb provides detailed genetic and epigenetic annotation information on super-enhancers. Information includes common SNPs, motif changes, expression quantitative trait locus (eQTL), risk SNPs, transcription factor binding sites (TFBSs), CRISPR/Cas9 target sites and Dnase I hypersensitivity sites (DHSs) for in-depth analyses of super-enhancers. SEdb will help elucidate super-enhancer-related functions and find potential biological effects.

EnhancerDB: a resource of transcriptional regulation in the context of enhancers

Enhancers can act as cis-regulatory elements to control transcriptional regulation by recruiting DNA-binding transcription factors (TFs) in a tissue-specific manner. Recent studies show that enhancers regulate not only protein-coding genes but also microRNAs (miRNAs), and mutations within the TF binding sites (TFBSs) located on enhancers will cause a variety of diseases such as cancer. However, a comprehensive resource to integrate these regulation elements for revealing transcriptional regulations in the context of enhancers is not currently available. Here, we introduce EnhancerDB, a web-accessible database to provide a resource to browse and search regulatory relationships identified in this study, including 131 054 581 TF–enhancer, 17 059 enhancer–miRNAs, 318 993 enhancer–genes, 4 639 558 TF–miRNAs, 1 059 695 TF–genes, 11 439 394 enhancer–single-nucleotide polymorphisms (SNPs) and 23 334 genes associated with expression quantitative trait loci (eQTL) SNP and expression profile of TF/gene/miRNA across multiple human tissues/cell lines. We also developed a tool that further allows users to define tissue-specific enhancers by setting the threshold score of tissue specificity of enhancers. In addition, links to external resources are also available at EnhancerDB.

RAEdb: a database of enhancers identified by high-throughput reporter assays

High-throughput reporter assays have been recently developed to directly and quantitatively assess enhancer activity for thousands of regulatory elements. However, there is still no database to collect these enhancers. We developed RAEdb, the first database to collect enhancers identified by high-throughput reporter assays. RAEdb includes 538 320 enhancers derived from eight studies, most of which were from six human cell lines. An activity score was assigned to each enhancer based on reporter assays. Based on these enhancers, 7658 epromoters (promoters with enhancer activity) were identified and stored in the database. RAEdb provides two ways of searches: the first is to search studies by species and cell line; the other is to search enhancers or epromoters by position, activity score, sequence and gene. RAEdb also provides a genome browser to query, visualize and compare enhancers. All data in RAEdb is freely available for download.

Interpreting Non-coding Genetic Variation in Multiple Sclerosis Genome-Wide Associated Regions

Multiple sclerosis (MS) is the most common neurological disorder in young adults. Despite extensive studies, only a fraction of MS heritability has been explained, with association studies focusing primarily on protein-coding genes, essentially for the difficulty of interpreting non-coding features. However, non-coding RNAs (ncRNAs) and functional elements, such as super-enhancers (SE), are crucial regulators of many pathways and cellular mechanisms, and they have been implicated in a growing number of diseases. In this work, we searched for possible enrichments in non-coding elements at MS genome-wide associated loci, with the aim to highlight their possible involvement in the susceptibility to the disease. We first reconstructed the linkage disequilibrium (LD) structure of the Italian population using data of 727,478 single-nucleotide polymorphisms (SNPs) from 1,668 healthy individuals. The genomic coordinates of the obtained LD blocks were intersected with those of the top hits identified in previously published MS genome-wide association studies (GWAS). By a bootstrapping approach, we hence demonstrated a striking enrichment of non-coding elements, especially of circular RNAs (circRNAs) mapping in the 73 LD blocks harboring MS-associated SNPs. In particular, we found a total of 482 circRNAs (annotated in publicly available databases) vs. a mean of 194 ± 65 in the random sets of LD blocks, using 1,000 iterations. As a proof of concept of a possible functional relevance of this observation, we experimentally verified that the expression levels of a circRNA derived from an MS-associated locus, i.e., hsa_circ_0043813 from the STAT3 gene, can be modulated by the three genotypes at the disease-associated SNP. Finally, by evaluating RNA-seq data of two cell lines, SH-SY5Y and Jurkat cells, representing tissues relevant for MS, we identified 18 (two novel) circRNAs derived from MS-associated genes. In conclusion, this work showed for the first time that MS-GWAS top hits map in LD blocks enriched in circRNAs, suggesting circRNAs as possible novel contributors to the disease pathogenesis.

Super-enhancers maintain renin-expressing cell identity and memory to preserve multi-system homeostasis

Renin cells are crucial for survival - they control fluid-electrolyte and blood pressure homeostasis, vascular development, regeneration, and oxygen delivery to tissues. During embryonic development, renin cells are progenitors for multiple cell types that retain the memory of the renin phenotype. When there is a threat to survival, those descendants are transformed and reenact the renin phenotype to restore homeostasis. We tested the hypothesis that the molecular memory of the renin phenotype resides in unique regions and states of these cells' chromatin. Using renin cells at various stages of stimulation, we identified regions in the genome where the chromatin is open for transcription, mapped histone modifications characteristic of active enhancers such as H3K27ac, and tracked deposition of transcriptional activators such as Med1, whose deletion results in ablation of renin expression and low blood pressure. Using the rank ordering of super-enhancers, epigenetic rewriting, and enhancer deletion analysis, we found that renin cells harbor a unique set of super-enhancers that determine their identity. The most prominent renin super-enhancer may act as a chromatin sensor of signals that convey the physiologic status of the organism, and is responsible for the transformation of renin cell descendants to the renin phenotype, a fundamental process to ensure homeostasis.

SUMO Safeguards Somatic and Pluripotent Cell Identities by Enforcing Distinct Chromatin States

Understanding general principles that safeguard cellular identity should reveal critical insights into common mechanisms underlying specification of varied cell types. Here, we show that SUMO modification acts to stabilize cell fate in a variety of contexts. Hyposumoylation enhances pluripotency reprogramming in vitro and in vivo, increases lineage transdifferentiation, and facilitates leukemic cell differentiation. Suppressing sumoylation in embryonic stem cells (ESCs) promotes their conversion into 2-cell-embryo-like (2C-like) cells. During reprogramming to pluripotency, SUMO functions on fibroblastic enhancers to retain somatic transcription factors together with Oct4, Sox2, and Klf4, thus impeding somatic enhancer inactivation. In contrast, in ESCs, SUMO functions on heterochromatin to silence the 2C program, maintaining both proper H3K9me3 levels genome-wide and repression of the Dux locus by triggering recruitment of the sumoylated PRC1.6 and Kap/Setdb1 repressive complexes. Together, these studies show that SUMO acts on chromatin as a glue to stabilize key determinants of somatic and pluripotent states.