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

Common nonmutational NOTCH1 activation in chronic lymphocytic leukemia

Activating mutations of NOTCH1 (a well-known oncogene in T-cell acute lymphoblastic leukemia) are present in ∼4-13% of chronic lymphocytic leukemia (CLL) cases, where they are associated with disease progression and chemorefractoriness. However, the specific role of NOTCH1 in leukemogenesis remains to be established. Here, we report that the active intracellular portion of NOTCH1 (ICN1) is detectable in ∼50% of peripheral blood CLL cases lacking gene mutations. We identify a "NOTCH1 gene-expression signature" in CLL cells, and show that this signature is significantly enriched in primary CLL cases expressing ICN1, independent of NOTCH1 mutation. NOTCH1 target genes include key regulators of B-cell proliferation, survival, and signal transduction. In particular, we show that NOTCH1 transactivates MYC via binding to B-cell-specific regulatory elements, thus implicating this oncogene in CLL development. These results significantly extend the role of NOTCH1 in CLL pathogenesis, and have direct implications for specific therapeutic targeting.

Systematic analysis of telomere length and somatic alterations in 31 cancer types

Cancer cells survive cellular crisis through telomere maintenance mechanisms. We report telomere lengths in 18,430 samples, including tumors and non-neoplastic samples, across 31 cancer types. Telomeres were shorter in tumors than in normal tissues and longer in sarcomas and gliomas than in other cancers. Among 6,835 cancers, 73% expressed telomerase reverse transcriptase (TERT), which was associated with TERT point mutations, rearrangements, DNA amplifications and transcript fusions and predictive of telomerase activity. TERT promoter methylation provided an additional deregulatory TERT expression mechanism. Five percent of cases, characterized by undetectable TERT expression and alterations in ATRX or DAXX, demonstrated elongated telomeres and increased telomeric repeat-containing RNA (TERRA). The remaining 22% of tumors neither expressed TERT nor harbored alterations in ATRX or DAXX. In this group, telomere length positively correlated with TP53 and RB1 mutations. Our analysis integrates TERT abnormalities, telomerase activity and genomic alterations with telomere length in cancer.

Roles of RUNX in B Cell Immortalisation

RUNX1 and RUNX3 are the main RUNX genes expressed in B lymphocytes. Both are expressed throughout B-cell development and play key roles at certain key developmental transitions. The tumour-associated Epstein-Barr virus (EBV) has potent B-cell transforming ability and manipulates RUNX3 and RUNX1 transcription through novel mechanisms to control B cell growth. In contrast to resting mature B cells where RUNX1 expression is high, in EBV-infected cells RUNX1 levels are low and RUNX3 levels are high. Downregulation of RUNX1 in these cells results from cross-regulation by RUNX3 and serves to relieve RUNX1-mediated growth repression. RUNX3 is upregulated by the EBV transcription factor (TF) EBNA2 and represses RUNX1 transcription through RUNX sites in the RUNX1 P1 promoter. Recent analysis revealed that EBNA2 activates RUNX3 transcription through an 18 kb upstream super-enhancer in a manner dependent on the EBNA2 and Notch DNA-binding partner RBP-J. This super-enhancer also directs RUNX3 activation by two further RBP-J-associated EBV TFs, EBNA3B and 3C. Counter-intuitively, EBNA2 also hijacks RBP-J to target a super-enhancer region upstream of RUNX1 to maintain some RUNX1 expression in certain cell backgrounds, although the dual functioning EBNA3B and 3C proteins limit this activation. Interestingly, the B-cell genome binding sites of EBV TFs overlap extensively with RUNX3 binding sites and show enrichment for RUNX motifs. Therefore in addition to B-cell growth manipulation through the long-range control of RUNX transcription, EBV may also use RUNX proteins as co-factors to deregulate the transcription of many B cell genes during immortalisation.

Roles of the RUNX1 Enhancer in Normal Hematopoiesis and Leukemogenesis

Enhancers are regulatory elements in genomic DNA that contain specific sequence motifs that are bound by DNA-binding transcription factors. The activity of enhancers is tightly regulated in an integrated and combinatorial manner, thus yielding complex patterns of transcription in different tissues. Identifying enhancers is crucial to understanding the physiological and pathogenic roles of their target genes. The RUNX1 intronic enhancer, eR1, acts in cis to regulate RUNX1 gene expression in hematopoietic stem cells (HSCs) and hemogenic endothelial cells. RUNX1 and other hematopoietic transcription factors TAL1/SCL, GATA2, PU.1, LMO2 and LDB1 bind at this region. Interestingly, recent studies have revealed that this region is involved in a large cluster of enhancers termed a super-enhancer. The RUNX1 super-enhancer is observed in normal HSCs and T-cell acute lymphoblastic leukemia cells. In this review, we describe the discovery of eR1 and its roles in normal development and leukemogenesis, as well as its potential applications in stem cell research.

DNA Hypomethylation in Intragenic and Intergenic Enhancer Chromatin of Muscle-Specific Genes Usually Correlates with their Expression

Tissue-specific enhancers are critical for gene regulation. In this study, we help elucidate the contribution of muscle-associated differential DNA methylation to the enhancer activity of highly muscle-specific genes. By bioinformatic analysis of 44 muscle-associated genes, we show that preferential gene expression in skeletal muscle (SkM) correlates with SkM-specific intragenic and intergenic enhancer chromatin and overlapping foci of DNA hypomethylation. Some genes, e.g., CASQ1 and FBXO32, displayed broad regions of both SkM- and heart-specific enhancer chromatin but exhibited focal SkM-specific DNA hypomethylation. Half of the genes had SkM-specific super-enhancers. In contrast to simple enhancer/gene-expression correlations, a super-enhancer was associated with the myogenic MYOD1 gene in both SkM and myoblasts even though SkM has < 1 percent as much MYOD1 expression. Local chromatin differences in this super-enhancer probably contribute to the SkM/myoblast differential expression. Transfection assays confirmed the tissue-specificity of the 0.3-kb core enhancer within MYOD1's super-enhancer and demonstrated its repression by methylation of its three CG dinucleotides. Our study suggests that DNA hypomethylation increases enhancer tissue-specificity and that SkM super-enhancers sometimes are poised for physiologically important, rapid up-regulation.

Impact of the gut microbiota on enhancer accessibility in gut intraepithelial lymphocytes

The gut microbiota impacts many aspects of host biology including immune function. One hypothesis is that microbial communities induce epigenetic changes with accompanying alterations in chromatin accessibility, providing a mechanism that allows a community to have sustained host effects even in the face of its structural or functional variation. We used Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) to define chromatin accessibility in predicted enhancer regions of intestinal αβ⁺ and γδ⁺ intraepithelial lymphocytes purified from germ-free mice, their conventionally raised (CONV-R) counterparts, and mice reared germ free and then colonized with CONV-R gut microbiota at the end of the suckling-weaning transition. Characterizing genes adjacent to traditional enhancers and super-enhancers revealed signaling networks, metabolic pathways, and enhancer-associated transcription factors affected by the microbiota. Our results support the notion that epigenetic modifications help define microbial community-affiliated functional features of host immune cell lineages.

Enhancers and super-enhancers have an equivalent regulatory role in embryonic stem cells through regulation of single or multiple genes

Transcriptional enhancers are critical for maintaining cell-type-specific gene expression and driving cell fate changes during development. Highly transcribed genes are often associated with a cluster of individual enhancers such as those found in locus control regions. Recently, these have been termed stretch enhancers or super-enhancers, which have been predicted to regulate critical cell identity genes. We employed a CRISPR/Cas9-mediated deletion approach to study the function of several enhancer clusters (ECs) and isolated enhancers in mouse embryonic stem (ES) cells. Our results reveal that the effect of deleting ECs, also classified as ES cell super-enhancers, is highly variable, resulting in target gene expression reductions ranging from 12% to as much as 92%. Partial deletions of these ECs which removed only one enhancer or a subcluster of enhancers revealed partially redundant control of the regulated gene by multiple enhancers within the larger cluster. Many highly transcribed genes in ES cells are not associated with a super-enhancer; furthermore, super-enhancer predictions ignore 81% of the potentially active regulatory elements predicted by cobinding of five or more pluripotency-associated transcription factors. Deletion of these additional enhancer regions revealed their robust regulatory role in gene transcription. In addition, select super-enhancers and enhancers were identified that regulated clusters of paralogous genes. We conclude that, whereas robust transcriptional output can be achieved by an isolated enhancer, clusters of enhancers acting on a common target gene act in a partially redundant manner to fine tune transcriptional output of their target genes.

Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps

Large-scale whole-genome sequence data sets offer novel opportunities to identify genetic variation underlying human traits. Here we apply genotype imputation based on whole-genome sequence data from the UK10K and 1000 Genomes Project into 35,981 study participants of European ancestry, followed by association analysis with 20 quantitative cardiometabolic and hematological traits. We describe 17 new associations, including 6 rare (minor allele frequency (MAF) < 1%) or low-frequency (1% < MAF < 5%) variants with platelet count (PLT), red blood cell indices (MCH and MCV) and HDL cholesterol. Applying fine-mapping analysis to 233 known and new loci associated with the 20 traits, we resolve the associations of 59 loci to credible sets of 20 or fewer variants and describe trait enrichments within regions of predicted regulatory function. These findings improve understanding of the allelic architecture of risk factors for cardiometabolic and hematological diseases and provide additional functional insights with the identification of potentially novel biological targets.

A generative model for the behavior of RNA polymerase

MOTIVATION

Transcription by RNA polymerase is a highly dynamic process involving multiple distinct points of regulation. Nascent transcription assays are a relatively new set of high throughput techniques that measure the location of actively engaged RNA polymerase genome wide. Hence, nascent transcription is a rich source of information on the regulation of RNA polymerase activity. To fully dissect this data requires the development of stochastic models that can both deconvolve the stages of polymerase activity and identify significant changes in activity between experiments.

RESULTS

We present a generative, probabilistic model of RNA polymerase that fully describes loading, initiation, elongation and termination. We fit this model genome wide and profile the enzymatic activity of RNA polymerase across various loci and following experimental perturbation. We observe striking correlation of predicted loading events and regulatory chromatin marks. We provide principled statistics that compute probabilities reminiscent of traveler's and divergent ratios. We finish with a systematic comparison of RNA Polymerase activity at promoter versus non-promoter associated loci.

AVAILABILITY AND IMPLEMENTATION

Transcription Fit (Tfit) is a freely available, open source software package written in C/C ++ that requires GNU compilers 4.7.3 or greater. Tfit is available from GitHub (https://github.com/azofeifa/Tfit).

CONTACT

robin.dowell@colorado.eduSupplementary information: Supplementary data are available at Bioinformatics online.

LMethyR-SVM: Predict Human Enhancers Using Low Methylated Regions based on Weighted Support Vector Machines

BACKGROUND

The identification of enhancers is a challenging task. Various types of epigenetic information including histone modification have been utilized in the construction of enhancer prediction models based on a diverse panel of machine learning schemes. However, DNA methylation profiles generated from the whole genome bisulfite sequencing (WGBS) have not been fully explored for their potential in enhancer prediction despite the fact that low methylated regions (LMRs) have been implied to be distal active regulatory regions.

METHOD

In this work, we propose a prediction framework, LMethyR-SVM, using LMRs identified from cell-type-specific WGBS DNA methylation profiles and a weighted support vector machine learning framework. In LMethyR-SVM, the set of cell-type-specific LMRs is further divided into three sets: reliable positive, like positive and likely negative, according to their resemblance to a small set of experimentally validated enhancers in the VISTA database based on an estimated non-parametric density distribution. Then, the prediction model is obtained by solving a weighted support vector machine.

RESULTS

We demonstrate the performance of LMethyR-SVM by using the WGBS DNA methylation profiles derived from the human embryonic stem cell type (H1) and the fetal lung fibroblast cell type (IMR90). The predicted enhancers are highly conserved with a reasonable validation rate based on a set of commonly used positive markers including transcription factors, p300 binding and DNase-I hypersensitive sites. In addition, we show evidence that the large fraction of the LMethyR-SVM predicted enhancers are not predicted by ChromHMM in H1 cell type and they are more enriched for the FANTOM5 enhancers.

CONCLUSION

Our work suggests that low methylated regions detected from the WGBS data are useful as complementary resources to histone modification marks in developing models for the prediction of cell-type-specific enhancers.

MYC activation and BCL2L11 silencing by a tumour virus through the large-scale reconfiguration of enhancer-promoter hubs

Lymphomagenesis in the presence of deregulated MYC requires suppression of MYC-driven apoptosis, often through downregulation of the pro-apoptotic BCL2L11 gene (Bim). Transcription factors (EBNAs) encoded by the lymphoma-associated Epstein-Barr virus (EBV) activate MYC and silence BCL2L11. We show that the EBNA2 transactivator activates multiple MYC enhancers and reconfigures the MYC locus to increase upstream and decrease downstream enhancer-promoter interactions. EBNA2 recruits the BRG1 ATPase of the SWI/SNF remodeller to MYC enhancers and BRG1 is required for enhancer-promoter interactions in EBV-infected cells. At BCL2L11, we identify a haematopoietic enhancer hub that is inactivated by the EBV repressors EBNA3A and EBNA3C through recruitment of the H3K27 methyltransferase EZH2. Reversal of enhancer inactivation using an EZH2 inhibitor upregulates BCL2L11 and induces apoptosis. EBV therefore drives lymphomagenesis by hijacking long-range enhancer hubs and specific cellular co-factors. EBV-driven MYC enhancer activation may contribute to the genesis and localisation of MYC-Immunoglobulin translocation breakpoints in Burkitt's lymphoma.

Characterisation of non-coding genetic variation in histamine receptors using AnNCR-SNP

Almost 90 % of disease-associated genetic variants found using genome wide association studies (GWAS) are located in non-coding regions of the genome. Such variants can affect phenotype by altering important regulatory elements such as promoters, enhancers or repressors, leading to changes in gene expression and consequently disease, such as thyroid cancer and allergic diseases. A number of allergy and atopy related diseases such as asthma and atopic dermatitis are related to histamine receptors; however, these diseases are not fully characterized at the molecular level. Moreover, candidate gene based studies of common variants known as single nucleotide polymorphism (SNPs) located in the coding regions of these receptors have given mixed results. It is important to complement these approaches by identifying and characterising non-coding variants in order to further elucidate the role of these receptors in disease. Here we present an analysis of histamine receptor genes using the tool AnNCR-SNP to characterise variants in non-coding genomic regions. AnNCR-SNP combines bioinformatics and experimental data sets from various sources to predict the effects of genetic variation on gene expression regulation. We find many SNPs located in areas of open chromatin, overlapping with transcription factor binding sites and associated with changes in gene expression in expression quantitative trait loci (eQTL) experiments. Here we present the results as a catalogue of non-coding variation in histamine receptor genes to aid histamine researchers in identifying putative functional SNPs found in GWAS for further validation, and to help select variants for candidate gene studies.

Gamma-Retrovirus Integration Marks Cell Type-Specific Cancer Genes: A Novel Profiling Tool in Cancer Genomics

Retroviruses have been foundational in cancer research since early studies identified proto-oncogenes as targets for insertional mutagenesis. Integration of murine gamma-retroviruses into the host genome favours promoters and enhancers and entails interaction of viral integrase with host BET/bromodomain factors. We report that this integration pattern is conserved in feline leukaemia virus (FeLV), a gamma-retrovirus that infects many human cell types. Analysis of FeLV insertion sites in the MCF-7 mammary carcinoma cell line revealed strong bias towards active chromatin marks with no evidence of significant post-integration growth selection. The most prominent FeLV integration targets had little overlap with the most abundantly expressed transcripts, but were strongly enriched for annotated cancer genes. A meta-analysis based on several gamma-retrovirus integration profiling (GRIP) studies in human cells (CD34+, K562, HepG2) revealed a similar cancer gene bias but also remarkable cell-type specificity, with prominent exceptions including a universal integration hotspot at the long non-coding RNA MALAT1. Comparison of GRIP targets with databases of super-enhancers from the same cell lines showed that these have only limited overlap and that GRIP provides unique insights into the upstream drivers of cell growth. These observations elucidate the oncogenic potency of the gamma-retroviruses and support the wider application of GRIP to identify the genes and growth regulatory circuits that drive distinct cancer types.

BET Inhibition Attenuates Helicobacter pylori-Induced Inflammatory Response by Suppressing Inflammatory Gene Transcription and Enhancer Activation

Helicobacter pylori infection causes chronic gastritis and peptic ulceration. H. pylori-initiated chronic gastritis is characterized by enhanced expression of many NF-κB-regulated inflammatory cytokines. Brd4 has emerged as an important NF-κB regulator and regulates the expression of many NF-κB-dependent inflammatory genes. In this study, we demonstrated that Brd4 was not only actively involved in H. pylori-induced inflammatory gene mRNA transcription but also H. pylori-induced inflammatory gene enhancer RNA (eRNA) synthesis. Suppression of H. pylori-induced eRNA synthesis impaired H. pylori-induced mRNA synthesis. Furthermore, H. pylori stimulated NF-κB-dependent recruitment of Brd4 to the promoters and enhancers of inflammatory genes to facilitate the RNA polymerase II-mediated eRNA and mRNA synthesis. Inhibition of Brd4 by JQ1 attenuated H. pylori-induced eRNA and mRNA synthesis for a subset of NF-κB-dependent inflammatory genes. JQ1 also inhibited H. pylori-induced interaction between Brd4 and RelA and the recruitment of Brd4 and RNA polymerase II to the promoters and enhancers of inflammatory genes. Finally, we demonstrated that JQ1 suppressed inflammatory gene expression, inflammation, and cell proliferation in H. pylori-infected mice. These studies highlight the importance of Brd4 in H. pylori-induced inflammatory gene expression and suggest that Brd4 could be a potential therapeutic target for the treatment of H. pylori-triggered inflammatory diseases and cancer.

RUNX super-enhancer control through the Notch pathway by Epstein-Barr virus transcription factors regulates B cell growth

In B cells infected by the cancer-associated Epstein-Barr virus (EBV), RUNX3 and RUNX1 transcription is manipulated to control cell growth. The EBV-encoded EBNA2 transcription factor (TF) activates RUNX3 transcription leading to RUNX3-mediated repression of the RUNX1 promoter and the relief of RUNX1-directed growth repression. We show that EBNA2 activates RUNX3 through a specific element within a −97 kb super-enhancer in a manner dependent on the expression of the Notch DNA-binding partner RBP-J. We also reveal that the EBV TFs EBNA3B and EBNA3C contribute to RUNX3 activation in EBV-infected cells by targeting the same element. Uncovering a counter-regulatory feed-forward step, we demonstrate EBNA2 activation of a RUNX1 super-enhancer (−139 to −250 kb) that results in low-level RUNX1 expression in cells refractory to RUNX1-mediated growth inhibition. EBNA2 activation of the RUNX1 super-enhancer is also dependent on RBP-J. Consistent with the context-dependent roles of EBNA3B and EBNA3C as activators or repressors, we find that these proteins negatively regulate the RUNX1 super-enhancer, curbing EBNA2 activation. Taken together our results reveal cell-type-specific exploitation of RUNX gene super-enhancers by multiple EBV TFs via the Notch pathway to fine tune RUNX3 and RUNX1 expression and manipulate B-cell growth.

The 2016 database issue of Nucleic Acids Research and an updated molecular biology database collection

The 2016 Database Issue of Nucleic Acids Research starts with overviews of the resources provided by three major bioinformatics centers, the U.S. National Center for Biotechnology Information (NCBI), the European Bioinformatics Institute (EMBL-EBI) and Swiss Institute for Bioinformatics (SIB). Also included are descriptions of 62 new databases and updates on 95 databases that have been previously featured in NAR plus 17 previously described elsewhere. A number of papers in this issue deal with resources on nucleic acids, including various kinds of non-coding RNAs and their interactions, molecular dynamics simulations of nucleic acid structure, and two databases of super-enhancers. The protein database section features important updates on the EBI's Pfam, PDBe and PRIDE databases, as well as a variety of resources on pathways, metabolomics and metabolic modeling. This issue also includes updates on popular metagenomics resources, such as MG-RAST, EBI Metagenomics, and probeBASE, as well as a newly compiled Human Pan-Microbe Communities database. A significant fraction of the new and updated databases are dedicated to the genetic basis of disease, primarily cancer, and various aspects of drug research, including resources for patented drugs, their side effects, withdrawn drugs, and potential drug targets. A further six papers present updated databases of various antimicrobial and anticancer peptides. The entire Database Issue is freely available online on the Nucleic Acids Research website (http://nar.oxfordjournals.org/). The NAR online Molecular Biology Database Collection, http://www.oxfordjournals.org/nar/database/c/, has been updated with the addition of 88 new resources and removal of 23 obsolete websites, which brought the current listing to 1685 databases.

SEA: a super-enhancer archive

Super-enhancers are large clusters of transcriptional enhancers regarded as having essential roles in driving the expression of genes that control cell identity during development and tumorigenesis. The construction of a genome-wide super-enhancer database is urgently needed to better understand super-enhancer-directed gene expression regulation for a given biology process. Here, we present a specifically designed web-accessible database, Super-Enhancer Archive (SEA, http://sea.edbc.org). SEA focuses on integrating super-enhancers in multiple species and annotating their potential roles in the regulation of cell identity gene expression. The current release of SEA incorporates 83 996 super-enhancers computationally or experimentally identified in 134 cell types/tissues/diseases, including human (75 439, three of which were experimentally identified), mouse (5879, five of which were experimentally identified), Drosophila melanogaster (1774) and Caenorhabditis elegans (904). To facilitate data extraction, SEA supports multiple search options, including species, genome location, gene name, cell type/tissue and super-enhancer name. The response provides detailed (epi)genetic information, incorporating cell type specificity, nearby genes, transcriptional factor binding sites, CRISPR/Cas9 target sites, evolutionary conservation, SNPs, H3K27ac, DNA methylation, gene expression and TF ChIP-seq data. Moreover, analytical tools and a genome browser were developed for users to explore super-enhancers and their roles in defining cell identity and disease processes in depth.