GRO-seq Data Research Articles

Using Functional Genomic Data in Monocytes/Macrophages and Genotyping to Nominate Disease-Driving Single Nucleotide Polymorphisms and Target Genes in Juvenile Idiopathic Arthritis.

GWAS have identified multiple regions that confer risk for juvenile idiopathic arthritis (JIA). However, identifying the single nucleotide polymorphisms (SNPs) that drive disease risk is impeded by the SNPs' that identify risk loci being in linkage disequilibrium (LD) with hundreds of other SNPs. Since the causal SNPs remain unknown, it is difficult to identify target genes and use genetic information to inform patient care. We used genotyping and functional data in primary human monocytes/macrophages to nominate disease-driving SNPs on JIA risk haplotypes and identify their likely target genes. We identified JIA risk haplotypes using Immunochip data from Hinks et al (Nature Gen 2013) and the meta-analysis from McIntosh et al (Arthritis Rheum 2017). We used genotyping data from 3,939 children with JIA and 14,412 healthy controls to identify SNPs that: (1) were situated within open chromatin in multiple immune cell types and (2) were more common in children with JIA than the controls (p< 0.05). We intersected the chosen SNPs (n=846) with regions of bi-directional transcription initiation characteristic of non-coding regulatory regions detected using dREG to analyze GRO-seq data. Finally, we used MicroC data to identify gene promoters interacting with the regulatory regions harboring the candidate causal SNPs. We identified 190 SNPs that overlap with dREG peaks in monocytes and126 SNPs that overlap with dREG peaks in macrophages. Of these SNPs, 101 were situated within dREG peaks in both monocytes and macrophages, suggesting that these SNPs exert their effects independent of the cellular activation state. MicroC data in monocytes identified 20 genes/transcripts whose promoters interact with the enhancers harboring the SNPs of interest. SNPs in JIA risk regions that are candidate causal variants can be further screened using functional data such as GRO-seq. This process identifies a finite number of candidate causal SNPs, the majority of which are likely to exert their biological effects independent of cellular activation state in monocytes. Three-dimensional chromatin data generated with MicroC identifies genes likely to be influenced by these SNPs. These studies demonstrate the importance of investigations into the role of innate immunity in JIA.

Abstract 6284: Multimoics reveal aberrant pathways and regulation of castration resistant and metastatic prostate cancer

Abstract Prostate cancer is a highly heterogeneous disease and in the end, 30% of patients will experience metastatic and fatal castration resistant prostate cancer (mCRPC). In spite of the vigorous efforts to search the causes of metastatic CRPC (mCRPC), the mechanisms are still largely unresolved. To understand the progression of mCRPC, we utilized scRNA-seq to profile global expression patterns in LNCaP, LNCaP-Abl and PC3 representing castration sensitive and resistant states. ScRNA-seq revealed 335 and 2393 differentially expressed (DE) genes in early and advanced castration resistant states enriched in 43 and 163 aberrant pathways. These included focal adhesion, adherens junction, leukocyte transendothelial migration, ECM-receptor interaction, regulation of actins, gap junction, TGFb, WNT, Hippo, Ephrin and other pathways. Upregulation of these pathways predicted worst disease free/overall survival of The Cancer Genomes Atlas (TCGA) PC cohort using Kaplan-Meir estimation. Further scRNA-seq also indicated most of the pathways were also enriched in ex vivo circulating tumor cells derived from biochemical recurrent or mCRPC patients. Small molecule perturbation verified function of 9 pathways involved in cell proliferation, migration, invasion, and organoid formation of mCRPC cell lines and CTCs. We then delved into how these genes are regulated by the global chromatin landscape through Assay for Transposase-Accessible Chromatin and high throughput DNA-seq (ATAC-seq). In castration sensitive LNCaP, active chromatins are associated with genes but most of them are located in distal intergenic regions. Conversely, the majority (51.9-57.6%) of open chromatins in castration resistant PC cells are situated in promoters that lie within 1kb of transcription start sites. KEGG pathway enrichment analysis uncovered Hippo, Wnt, tight junction, adherens junction, circadian and other pathways that corroborate the scRNA-seq findings. GRO-seq data indicated that nascent transcription supports gene body transcription in castration resistant cells but leads to massive pausing in castration sensitive cells. Citation Format: Aaron M. Horning, Chia-Nung Hung, Brandon Liebermann, Chih-Wei Chou, Che-Kuang Lin, Yao Vickie Wang, Victor X. Jin, Michael A. Liss, Chiou-Miin Wang, Chun- Lin, Meizhen Chen, Tim H-M Huang, Chun-Liang Chen. Multimoics reveal aberrant pathways and regulation of castration resistant and metastatic prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6284.

Herpes simplex virus 1 immediate early transcription initiation, pause-release, elongation, and termination in the presence and absence of ICP4.

Infection with herpes simplex virus 1 (HSV-1) leads to lifelong infection due to the virus's remarkable ability to control transcription of its own genome, resulting in two transcriptional programs: lytic (highly active) and latent (restricted). The lytic program requires immediate early (IE) proteins to first repress transcription of late viral genes, which then undergo sequential de-repression, leading to a specific sequence of gene expression. Here, we show that the IE ICP4 functions to regulate the cascade by limiting RNA polymerase initiation at immediate early times. However, late viral genes that initiate too early in the absence of ICP4 do not yield mRNA as transcription stalls within gene bodies. It follows that other regulatory steps intercede to prevent elongation of genes at the incorrect time, demonstrating the precise control HSV-1 exerts over its own transcription.

Temporal regulation of head-on transcription at replication initiation sites

Head-on (HO) collisions between the DNA replication machinery and RNA polymerase over R-loop forming sequences (RLFS) are genotoxic, leading to replication fork blockage and DNA breaks. Current models suggest that HO collisions are avoided through replication initiation site (RIS) positioning upstream of active genes, ensuring co-orientation of replication fork movement and genic transcription. However, this model does not account for pervasive transcription, or intragenic RIS. Moreover, pervasive transcription initiation and CG-rich DNA is a feature of RIS, suggesting that HO transcription units (HO TUs) capable of forming R-loops might occur. Through mining phased GRO-seq data, and developing an informatics strategy to stringently identify RIS, we demonstrate that HO TUs containing RLFS occur at RIS in MCF-7 cells, and are downregulated at the G1/S phase boundary. Our analysis reveals a novel spatiotemporal relationship between transcription and replication, and supports the idea that HO collisions are avoided through transcriptional regulatory mechanisms.

Analysis of chromatin data supports a role for CD14+ monocytes/macrophages in mediating genetic risk for juvenile idiopathic arthritis.

IntroductionGenome wide association studies (GWAS) have identified multiple regions that confer genetic risk for the polyarticular/oligoarticular forms of juvenile idiopathic arthritis (JIA). However, genome-wide scans do not identify the cells impacted by genetic polymorphisms on the risk haplotypes or the genes impacted by those variants. We have shown that genetic variants driving JIA risk are likely to affect both innate and adaptive immune functions. We provide additional evidence that JIA risk variants impact innate immunity.Materials and methodsWe queried publicly available H3K4me1/H3K27ac ChIP-seq data in CD14+ monocytes to determine whether the linkage disequilibrium (LD) blocks incorporating the SNPs that tag JIA risk loci showed enrichment for these epigenetic marks. We also queried monocyte/macrophage GROseq data, a functional readout of active enhancers. We defined the topologically associated domains (TADs) encompassing enhancers on the risk haplotypes and identified genes within those TADs expressed in monocytes. We performed ontology analyses of these genes to identify cellular processes that may be impacted by these variants. We also used whole blood RNAseq data from the Genotype-Tissue Expression (GTEx) data base to determine whether SNPs lying within monocyte GROseq peaks influence plausible target genes within the TADs encompassing the JIA risk haplotypes.ResultsThe LD blocks encompassing the JIA genetic risk regions were enriched for H3K4me1/H3K27ac ChIPseq peaks (p=0.00021 and p=0.022) when compared to genome background. Eleven and sixteen JIA were enriched for resting and activated macrophage GROseq peaks, respectively risk regions (p=0.04385 and p=0.00004). We identified 321 expressed genes within the TADs encompassing the JIA haplotypes in human monocytes. Ontological analysis of these genes showed enrichment for multiple immune functions. Finally, we found that SNPs lying within the GROseq peaks are strongly associated with expression levels of plausible target genes in human whole blood.ConclusionsThese findings support the idea that both innate and adaptive immunity are impacted by JIA genetic risk variants.

Master lineage transcription factors anchor trans mega transcriptional complexes at highly accessible enhancer sites to promote long-range chromatin clustering and transcription of distal target genes.

The term ‘super enhancers’ (SE) has been widely used to describe stretches of closely localized enhancers that are occupied collectively by large numbers of transcription factors (TFs) and co-factors, and control the transcription of highly-expressed genes. Through integrated analysis of >600 DNase-seq, ChIP-seq, GRO-seq, STARR-seq, RNA-seq, Hi-C and ChIA-PET data in five human cancer cell lines, we identified a new class of autonomous SEs (aSEs) that are excluded from classic SE calls by the widely used Rank Ordering of Super-Enhancers (ROSE) method. TF footprint analysis revealed that compared to classic SEs and regular enhancers, aSEs are tightly bound by a dense array of master lineage TFs, which serve as anchors to recruit additional TFs and co-factors in trans. In addition, aSEs are preferentially enriched for Cohesins, which likely involve in stabilizing long-distance interactions between aSEs and their distal target genes. Finally, we showed that aSEs can be reliably predicted using a single DNase-seq data or combined with Mediator and/or P300 ChIP-seq. Overall, our study demonstrates that aSEs represent a unique class of functionally important enhancer elements that distally regulate the transcription of highly expressed genes.

RNA polymerase mapping in plants identifies intergenic regulatory elements enriched in causal variants.

Control of gene expression is fundamental at every level of cell function. Promoter-proximal pausing and divergent transcription at promoters and enhancers, which are prominent features in animals, have only been studied in a handful of research experiments in plants. PRO-Seq analysis in cassava (Manihot esculenta) identified peaks of transcriptionally engaged RNA polymerase at both the 5′ and 3′ end of genes, consistent with paused or slowly moving Polymerase. In addition, we identified divergent transcription at intergenic sites. A full genome search for bi-directional transcription using an algorithm for enhancer detection developed in mammals (dREG) identified many intergenic regulatory element (IRE) candidates. These sites showed distinct patterns of methylation and nucleotide conservation based on genomic evolutionary rate profiling (GERP). SNPs within these IRE candidates explained significantly more variation in fitness and root composition than SNPs in chromosomal segments randomly ascertained from the same intergenic distribution, strongly suggesting a functional importance of these sites. Maize GRO-Seq data showed RNA polymerase occupancy at IREs consistent with patterns in cassava. Furthermore, these IREs in maize significantly overlapped with sites previously identified on the basis of open chromatin, histone marks, and methylation, and were enriched for reported eQTL. Our results suggest that bidirectional transcription can identify intergenic genomic regions in plants that play an important role in transcription regulation and whose identification has the potential to aid crop improvement.

PEPPRO: quality control and processing of nascent RNA profiling data

Nascent RNA profiling is growing in popularity; however, there is no standard analysis pipeline to uniformly process the data and assess quality. Here, we introduce PEPPRO, a comprehensive, scalable workflow for GRO-seq, PRO-seq, and ChRO-seq data. PEPPRO produces uniformly processed output files for downstream analysis and assesses adapter abundance, RNA integrity, library complexity, nascent RNA purity, and run-on efficiency. PEPPRO is restartable and fault-tolerant, records copious logs, and provides a web-based project report. PEPPRO can be run locally or using a cluster, providing a portable first step for genomic nascent RNA analysis.

An Enhancer-Based Analysis Revealed a New Function of Androgen Receptor in Tumor Cell Immune Evasion.

Cancer is characterized by dysregulation at multiple levels, such as gene transcription. Enhancers are well-studied transcription regulators that can enhance target transcripts through DNA loop formation mediated by chromosome folding. The gain or loss of the interaction between an enhancer and its target gene has a critical effect on gene expression. In this study, we analyzed GRO-seq data to identify active enhancers from seven common cancer cell lines and studied the function of these enhancers across multiple cancer types. By constructing an “enhancer effect score” (EES), we found a significant correlation between EES and tumor-infiltrating lymphocytes (TILs) in prostate cancer. Further analysis revealed that androgen receptor (AR) plays an important role in regulating the immune checkpoint gene PVR via its enhancer. These results suggest that AR contributes to prostate cancer aggressiveness by promoting cancer cell immune evasion.

SUN-743 Understanding the Role of Pancreas and Testis Specific lncRNA86 in Estrogen-Dependent Signaling in Breast Cancer

Long noncoding RNAs (lncRNAs) are emerging as key regulators of diverse cellular processes, but their roles in breast cancer biology are just beginning to be elucidated. In this study, integration of powerful techniques, RNA-seq data from subcellular fractionated RNA with GRO-seq data has yielded a comprehensive catalog of estrogen-regulated lncRNAs in MCF-7 cells. Analysis of RNA-seq data from samples representing molecular subtypes of breast cancer and normal tissue types, revealed that many lncRNAs (such as lincRNA86) show distinct expression patterns. LincRNA86 shows highest normal expression in pancreas followed by testis in normal human tissues. The hypothesis is lincRNA86 regulate estrogen-dependent signaling in breast cancer. In functional assays, knockdown of lncRNA86 inhibits the growth of ER-positive breast cancer cells. Amplified expression of lncRNA86 in breast cancer correlates with clinical outcome. LncRNA86 have now been fully annotated (transcription start and stop site, 5’ cap, polyA tail, and exon/intron structure), and cloned. We are now performing detailed molecular analyses to better understand the underlying mechanisms of action of the lncRNA. We are also currently have experiments underway to view cancer phenotypes: estrogen-dependent tumor growth. Collectively, our preliminary results suggest that lincRNA86 plays a critical role in ERα-dependent pathways.

Enhancer occlusion transcripts regulate the activity of human enhancer domains via transcriptional interference: a computational perspective.

Analysis of ENCODE long RNA-Seq and ChIP-seq (Chromatin Immunoprecipitation Sequencing) datasets for HepG2 and HeLa cell lines uncovered 1647 and 1958 transcripts that interfere with transcription factor binding to human enhancer domains. TFBSs (Transcription Factor Binding Sites) intersected by these ‘Enhancer Occlusion Transcripts’ (EOTrs) displayed significantly lower relative transcription factor (TF) binding affinities compared to TFBSs for the same TF devoid of EOTrs. Expression of most EOTrs was regulated in a cell line specific manner; analysis for the same TFBSs across cell lines, i.e. in the absence or presence of EOTrs, yielded consistently higher relative TF/DNA-binding affinities for TFBSs devoid of EOTrs. Lower activities of EOTr-associated enhancer domains coincided with reduced occupancy levels for histone tail modifications H3K27ac and H3K9ac. Similarly, the analysis of EOTrs with allele-specific expression identified lower activities for alleles associated with EOTrs. ChIA-PET (Chromatin Interaction Analysis by Paired-End Tag Sequencing) and 5C (Carbon Copy Chromosome Conformation Capture) uncovered that enhancer domains associated with EOTrs preferentially interacted with poised gene promoters. Analysis of EOTr regions with GRO-seq (Global run-on) data established the correlation of RNA polymerase pausing and occlusion of TF-binding. Our results implied that EOTr expression regulates human enhancer domains via transcriptional interference.

Abstract 2882: Mithramycin impedes EWS-FLI1 driven transcription by preventing target promoter clearance

Abstract Background: Ewing sarcoma (ES) is a primary bone tumor of adolescence with poor prognosis. ES is characterized by the presence of EWS-FLI1 which acts as an oncogenic transcription factor to promote and maintain a tumorigenic phenotype. All ES cells express EWS-FLI1, however, other actionable mutations are exceedingly rare. We previously identified mithramycin (MMA) as a potent and specific EWS-FLI1 inhibitor. MMA effectively decreases ES tumor cell viability and tumor volume in vivo by reversing the EWS-FLI1 transcriptional signature. Structural and biochemical data suggest that sub-micromolar MMA increases the stability of the DNA binding domain of EWS-FLI1 at GGAA repeats. These data suggest that MMA may prevent EWS-FLI1 from successfully promoting Pol II transcriptional elongation. Methods: We used ChIP-qPCR to detect EWS-FLI1 binding at the promoter of well characterized targets. We used a Pol II processivity assay to measure the efficiency of transcriptional elongation at EWS-FLI1 targets. We use RT-qPCR, western blotting, and RNAseq to confirm that MMA sensitizes ES cells to elongation inhibitors. Finally, we use GROseq to identify the changes to Pol II dynamics at EWS-FLI1 targets following MMA treatment. Results: Our ChIP-qPCR data demonstrate an increased fraction of EWS-FLI1 DNA binding at the promoters of target genes with GGAA microsatellite regions. MMA significantly inhibits the processivity of Pol II at EWS-FLI1 targets when added both into a run-on reaction or following ES cell pretreatment. Combining MMA with elongation inhibitors induces strong synergy as measured by Bliss-Independence, renders multiple ES cell lines unviable by inhibiting the effects of EWS-FLI1 at the mRNA and protein level, and is effective in vivo. MMA biases GROseq reads toward the 5’ end of genes, a result consistent with a promoter trapping mechanism. We are currently correlating GROseq data to global EWS-FLI1 DNA binding using ChIPseq. Conclusions: We characterized a mechanism of MMA-induced EWS-FLI1 inhibition that involves increased stabilization of the fusion protein at target promoter regions. This mechanism is supported by changes to EWS-FLI1 DNA-binding, EWS-FLI1 target transcriptional processivity, and a reversal of the EWS-FLI1 transcriptional signature by combining MMA with downstream elongation inhibition. We hope that this work will inform future endeavors to develop a targeted therapy for ES that inhibits the main driver of disease, EWS-FLI1. Citation Format: Guillermo Flores, Susan Kitchen-Goosen, Brandon Oswald, Elissa Boguslawski, Marie Adams, Ian Beddows, Zachary Madaj, Patrick Grohar. Mithramycin impedes EWS-FLI1 driven transcription by preventing target promoter clearance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2882.

AlleleHMM: a data-driven method to identify allele specific differences in distributed functional genomic marks.

How DNA sequence variation influences gene expression remains poorly understood. Diploid organisms have two homologous copies of their DNA sequence in the same nucleus, providing a rich source of information about how genetic variation affects a wealth of biochemical processes. However, few computational methods have been developed to discover allele specific differences in functional genomic data. Existing methods either treat each SNP independently, limiting statistical power, or combine SNPs across gene annotations, preventing the discovery of allele specific differences in unexpected genomic regions. Here we introduce AlleleHMM, a new computational method to identify blocks of neighboring SNPs that share similar allele specific differences in mark abundance. AlleleHMM uses a hidden Markov model to divide the genome into three hidden states based on allele frequencies in genomic data: a symmetric state (state S) which shows no difference between alleles, and regions with a higher signal on the maternal (state M) or paternal (state P) allele. AlleleHMM substantially outperformed naive methods using both simulated and real genomic data, particularly when input data had realistic levels of overdispersion. Using global run-on sequencing (GRO-seq) data, AlleleHMM identified thousands of allele specific blocks of transcription in both coding and non-coding genomic regions. AlleleHMM is a powerful tool for discovering allele specific regions in functional genomic datasets.

Abstract P2-03-12: Role of nucleus-specific intergenic long noncoding RNA-1476 in estrogen-dependent transcription in cancer

Abstract Long noncoding RNAs (lncRNAs) are emerging as key regulators of diverse cellular processes, but their roles in cancer biology are just beginning to be elucidated. Previous work using Global Run-On sequencing (GRO-seq) to study the transcriptome of MCF-7 breast cancer cells identified a large number of unannotated noncoding RNAs. Integration of RNA-seq data from subcellular fractionated RNA (i.e., cytoplasm, nucleoplasm, and chromatin-associated) with GRO-seq data using a novel bioinformatics pipeline has yielded a comprehensive catalog of &amp;gt;1900 polyadenylated lncRNAs in MCF-7 cells, about half of which have not been annotated previously and about a quarter of which are estrogen-regulated. Analysis of RNA-seq data from hundreds of samples representing 13 different cancer and normal tissue types, revealed that many lncRNAs are differentially expressed in various cancers. Furthermore, a large number of lncRNAs show distinct expression patterns across molecular subtypes of cancer. In functional assays, Kaplan Meier analysis of selected lncRNA, such as lncRNA 1476, predicts clinical outcome in ER-positive cancer and is transcriptionally upregulated in MCF-7 cells upon estrogen treatment. LncRNA1476 has now been fully annotated (transcription start and stop site, 5' cap, polyA tail, and exon/intron structure), and cloned. Molecular analyses indicate that lncRNA1476 plays a critical role in ER-dependent pathway. Collectively, our results suggest that lncRNAs are essential in controlling biological processes. Supported by a grant from the Cancer Prevention and Research Institute of Texas to S.S.G Citation Format: Choudhari R, Harrison AL, Carrillo CN, Gadad SS. Role of nucleus-specific intergenic long noncoding RNA-1476 in estrogen-dependent transcription in cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P2-03-12.

Global transcriptional activity dynamics reveal functional enhancer RNAs.

Active enhancers of the human genome generate long noncoding transcripts known as enhancer RNAs (eRNAs). How dynamic transcriptional changes of eRNAs are physically and functionally linked with target gene transcription remains unclear. To investigate the dynamic functional relationships among eRNAs and target promoters, we obtained a dense time series of GRO-seq and ChIP-seq data to generate a time-resolved enhancer activity map of a cell undergoing an innate antiviral immune response. Dynamic changes in eRNA and pre-mRNA transcription activities suggest distinct regulatory roles of enhancers. Using a criterion based on proximity and transcriptional inducibility, we identified 123 highly confident pairs of virus-inducible enhancers and their target genes. These enhancers interact with their target promoters transiently and concurrently at the peak of gene activation. Accordingly, their physical disassociation from the promoters is likely involved in post-induction repression. Functional assessments further establish that these eRNAs are necessary for full induction of the target genes and that a complement of inducible eRNAs functions together to achieve full activation. Lastly, we demonstrate the potential for eRNA-targeted transcriptional reprogramming through targeted reduction of eRNAs for a clinically relevant gene, TNFSF10, resulting in a selective control of interferon-induced apoptosis.

Alternative DNA secondary structure formation affects RNA polymerase II promoter-proximal pausing in human

BackgroundAlternative DNA secondary structures can arise from single-stranded DNA when duplex DNA is unwound during DNA processes such as transcription, resulting in the regulation or perturbation of these processes. We identify sites of high propensity to form stable DNA secondary structure across the human genome using Mfold and ViennaRNA programs with parameters for analyzing DNA.ResultsThe promoter-proximal regions of genes with paused transcription are significantly and energetically more favorable to form DNA secondary structure than non-paused genes or genes without RNA polymerase II (Pol II) binding. Using Pol II ChIP-seq, GRO-seq, NET-seq, and mNET-seq data, we arrive at a robust set of criteria for Pol II pausing, independent of annotation, and find that a highly stable secondary structure is likely to form about 10–50 nucleotides upstream of a Pol II pausing site. Structure probing data confirm the existence of DNA secondary structures enriched at the promoter-proximal regions of paused genes in human cells. Using an in vitro transcription assay, we demonstrate that Pol II pausing at HSPA1B, a human heat shock gene, is affected by manipulating DNA secondary structure upstream of the pausing site.ConclusionsOur results indicate alternative DNA secondary structure formation as a mechanism for how GC-rich sequences regulate RNA Pol II promoter-proximal pausing genome-wide.

Predicting stimulation-dependent enhancer-promoter interactions from ChIP-Seq time course data.

We have developed a machine learning approach to predict stimulation-dependent enhancer-promoter interactions using evidence from changes in genomic protein occupancy over time. The occupancy of estrogen receptor alpha (ERα), RNA polymerase (Pol II) and histone marks H2AZ and H3K4me3 were measured over time using ChIP-Seq experiments in MCF7 cells stimulated with estrogen. A Bayesian classifier was developed which uses the correlation of temporal binding patterns at enhancers and promoters and genomic proximity as features to predict interactions. This method was trained using experimentally determined interactions from the same system and was shown to achieve much higher precision than predictions based on the genomic proximity of nearest ERα binding. We use the method to identify a genome-wide confident set of ERα target genes and their regulatory enhancers genome-wide. Validation with publicly available GRO-Seq data demonstrates that our predicted targets are much more likely to show early nascent transcription than predictions based on genomic ERα binding proximity alone.

CIPHER: a flexible and extensive workflow platform for integrative next-generation sequencing data analysis and genomic regulatory element prediction

BackgroundNext-generation sequencing (NGS) approaches are commonly used to identify key regulatory networks that drive transcriptional programs. Although these technologies are frequently used in biological studies, NGS data analysis remains a challenging, time-consuming, and often irreproducible process. Therefore, there is a need for a comprehensive and flexible workflow platform that can accelerate data processing and analysis so more time can be spent on functional studies.ResultsWe have developed an integrative, stand-alone workflow platform, named CIPHER, for the systematic analysis of several commonly used NGS datasets including ChIP-seq, RNA-seq, MNase-seq, DNase-seq, GRO-seq, and ATAC-seq data. CIPHER implements various open source software packages, in-house scripts, and Docker containers to analyze and process single-ended and pair-ended datasets. CIPHER’s pipelines conduct extensive quality and contamination control checks, as well as comprehensive downstream analysis. A typical CIPHER workflow includes: (1) raw sequence evaluation, (2) read trimming and adapter removal, (3) read mapping and quality filtering, (4) visualization track generation, and (5) extensive quality control assessment. Furthermore, CIPHER conducts downstream analysis such as: narrow and broad peak calling, peak annotation, and motif identification for ChIP-seq, differential gene expression analysis for RNA-seq, nucleosome positioning for MNase-seq, DNase hypersensitive site mapping, site annotation and motif identification for DNase-seq, analysis of nascent transcription from Global-Run On (GRO-seq) data, and characterization of chromatin accessibility from ATAC-seq datasets. In addition, CIPHER contains an “analysis” mode that completes complex bioinformatics tasks such as enhancer discovery and provides functions to integrate various datasets together.ConclusionsUsing public and simulated data, we demonstrate that CIPHER is an efficient and comprehensive workflow platform that can analyze several NGS datasets commonly used in genome biology studies. Additionally, CIPHER’s integrative “analysis” mode allows researchers to elicit important biological information from the combined dataset analysis.

Epstein–Barr virus super-enhancer eRNAs are essential for MYC oncogene expression and lymphoblast proliferation

Epstein-Barr virus (EBV) super-enhancers (ESEs) are essential for lymphoblastoid cell (LCL) growth and survival. Reanalyses of LCL global run-on sequencing (Gro-seq) data found abundant enhancer RNAs (eRNAs) being transcribed at ESEs. Inactivation of ESE components, EBV nuclear antigen 2 (EBNA2) and bromodomain-containing protein 4 (BRD4), significantly decreased eRNAs at ESEs -428 and -525 kb upstream of the MYC oncogene transcription start site (TSS). shRNA knockdown of the MYC -428 and -525 ESE eRNA caused LCL growth arrest and reduced cell growth. Furthermore, MYC ESE eRNA knockdown also significantly reduced MYC expression, ESE H3K27ac signals, and MYC ESEs looping to MYC TSS. These data indicate that ESE eRNAs strongly affect cell gene expression and enable LCL growth.

Computational Approaches for Mining GRO-Seq Data to Identify and Characterize Active Enhancers.

Transcriptional enhancers are DNA regulatory elements that are bound by transcription factors and act to positively regulate the expression of nearby or distally located target genes. Enhancers have many features that have been discovered using genomic analyses. Recent studies have shown that active enhancers recruit RNA polymerase II (Pol II) and are transcribed, producing enhancer RNAs (eRNAs). GRO-seq, a method for identifying the location and orientation of all actively transcribing RNA polymerases across the genome, is a powerful approach for monitoring nascent enhancer transcription. Furthermore, the unique pattern of enhancer transcription can be used to identify enhancers in the absence of any information about the underlying transcription factors. Here, we describe the computational approaches required to identify and analyze active enhancers using GRO-seq data, including data pre-processing, alignment, and transcript calling. In addition, we describe protocols and computational pipelines for mining GRO-seq data to identify active enhancers, as well as known transcription factor binding sites that are transcribed. Furthermore, we discuss approaches for integrating GRO-seq-based enhancer data with other genomic data, including target gene expression and function. Finally, we describe molecular biology assays that can be used to confirm and explore further the function of enhancers that have been identified using genomic assays. Together, these approaches should allow the user to identify and explore the features and biological functions of new cell type-specific enhancers.