ENCODE Consortium Research Articles

Leveraging multi-omics data to infer regulators of mRNA 3' end processing in glioblastoma.

Alterations in mRNA 3' end processing and polyadenylation are widely implicated in the biology of many cancer types, including glioblastoma (GBM), one the most aggressive tumor types. Although several RNA-binding proteins (RBPs) responsible for alternative polyadenylation (APA) were identified from functional studies in cell lines, their contribution to the APA landscape in tumors in vivo was not thoroughly addressed. In this study we analyzed a large RNA-seq data set of glioblastoma (GBM) samples from The Cancer Genome Atlas (TCGA) to identify APA patterns differentiating the main molecular subtypes of GBM. We superimposed these to RBP footprinting data and to APA events occurring upon depletion of individual RBPs from a large panel tested by the ENCODE Consortium. Our analysis revealed 22 highly concordant and statistically significant RBP-APA associations, whereby changes in RBP expression were accompanied by APA in both TCGA and ENCODE datasets. Among these, we found a previously unknown PTBP1-regulated APA event in the PRRC2B gene and an HNRNPU-regulated event in the SC5D gene. Both of these were further supported by RNA-sequencing data of paired tumor center-periphery GBM samples obtained at the University Hospital of Basel. In addition, we validated the regulation of APA in PRRC2B by PTBP1 in siRNA-knockdown and overexpression experiments followed by RNA-sequencing in two glioblastoma cell lines. The transcriptome analysis workflow that we present here enables the identification of concordant RBP-APA associations in cancers.

Multicenter integrated analysis of noncoding CRISPRi screens

The ENCODE Consortium’s efforts to annotate noncoding cis-regulatory elements (CREs) have advanced our understanding of gene regulatory landscapes. Pooled, noncoding CRISPR screens offer a systematic approach to investigate cis-regulatory mechanisms. The ENCODE4 Functional Characterization Centers conducted 108 screens in human cell lines, comprising >540,000 perturbations across 24.85 megabases of the genome. Using 332 functionally confirmed CRE–gene links in K562 cells, we established guidelines for screening endogenous noncoding elements with CRISPR interference (CRISPRi), including accurate detection of CREs that exhibit variable, often low, transcriptional effects. Benchmarking five screen analysis tools, we find that CASA produces the most conservative CRE calls and is robust to artifacts of low-specificity single guide RNAs. We uncover a subtle DNA strand bias for CRISPRi in transcribed regions with implications for screen design and analysis. Together, we provide an accessible data resource, predesigned single guide RNAs for targeting 3,275,697 ENCODE SCREEN candidate CREs with CRISPRi and screening guidelines to accelerate functional characterization of the noncoding genome.

Machine Learning Sequence Modeling Identifies Gene Regulatory Responses to Bone Marrow Stromal Interactions in Multiple Myeloma

Introduction Multiple myeloma (MM) is a hematological malignancy of plasma cells which affects different organs including the bone marrow. The interaction between MM and the bone marrow stromal cells (BMSC) has been shown to affect the disease progression and response to treatment (Kumar et al. Multiple myeloma. Nat. Rev. Dis. Primers, 2017). An in vitro system to isolate the signaling mechanisms between BMSC and MM cells has been developed by (Dziadowicz et al., Cancers, 2022), who co-cultured MM cell lines in transwell media (TSW) exposed to BMSC secreted factors and compared their ATAC-seq profiles to MM cell lines (MONO) in isolation without the exposure to BMSC. While some of the gene expression changes induced by the BMSC-MM crosstalk were reported in (Dziadowicz et al., Cancers, 2022), here we model the entire chromatin accessibility profiles with a DNA-sequence based machine learning model to detect the altered Transcription Factor (TF) and enhancer activity responsible for driving the gene expression changes. We used sequence-based machine learning models (Beer et al., 2020, Annu. Rev. Genom. Hum. Genet.) and applied a systematic approach to model the chromatin accessibility changes induced by the interaction of BMSC and MM cells (MM-TSW) vs. MM cell lines cultured in isolation (MM-MONO). Methods We trained gapped-kmer SVM (gkm-SVM) machine learning models on MM1S and RPMI8226 MM cell line ATAC-seq data generated by Dziadowicz et al. as well as 1270 DNase-seq chromatin accessibility profiles of various human primary tissues and cell lines (including MM1S and RPMI8226) from the ENCODE consortium. We trained gkm-SVM on the top 2000 differentially-accessible distal ATAC peaks (>2000bp from transcription start site, e.g. enhancers) to find the differential TF activity between MM-TSW and MM-MONO (Figure 1) and found the TF binding site motifs explaining the gkmSVM output kmer weight distribution (Figure 2). We also identified the set of differentially-expressed TFs and performed gene set enrichment using MSigDB. Results We found that RUNX and Ebox-binding (5‘-CACCTG-3‘) TF family members are the most active TFs in MM1S-MONO and RPMI8226-MONO enhancers (gkmSVM AUROCs~0.92). The contribution of the Ebox TFs to distal chromatin accessibility in the MM cell lines is greater than in any other ENCODE sample (n=1270). Principal Component Analysis (PCA) on distal ATAC peaks compared to promoters showed that the MM transcriptional response to BMSC is more clearly explained by the differences in enhancer activity rather than promoters. This response is driven by dysregulated activity of a set of enhancer regions in MM-TSW compared to MM-MONO (Figure 1) and our machine learning method can identify these regulatory changes (AUROC~0.90). In addition to the altered AP1 and JAK/STAT activity reported by Dziadowicz et al., we discovered that RUNX and Ebox-binding transcriptional activity are downregulated in MM cells following the interaction with BMSC (Figure 2). Although our RNA-seq analysis found differential expression of some Ebox-binding TFs such as TCF3 and ZEB1 and RUNX members, the identification of the exact TF member(s) driving these RUNX and Ebox/E2A downregulation in MM-TSW is still challenging. Furthermore, PCA analysis of the gene expression profiles of MM1S and RPMI8226 cells showed that the targets of Bone Morphogenetic Protein 2 (BMP2) are upregulated in MM-TSW (FDR < 10 -28). Conclusion While some of the gene expression changes induced by the BMSC-MM interaction were reported in (Dziadowicz et al., Cancers, 2022), our modeling of the entire chromatin landscape discovered the previously unreported downregulation of RUNX and Ebox/E2A TFs in MM as the dominant response of MM interacting with BMSCs, accompanied by an upregulation of AP1 and JAK/STAT. RUNX and E2A-binding families of TFs include RUNX1/2/3, ZEB1/2, SNAI1/2 and TCF3, some of which we previously found to be strongly involved in epithelial to mesenchymal transition in gastric cancer and its invasiveness (Razavi-Mohseni et al., submitted, 2023). Bone marrow microenvironment interactions with MM are known to affect the disease progression and treatment, therefore, identifying the set of TFs driving the MM response to stroma may provide better understanding of the disease and better therapeutic opportunities.

DsRID: in silico identification of dsRNA regions using long-read RNA-seq data.

Double-stranded RNAs (dsRNAs) are potent triggers of innate immune responses upon recognition by cytosolic dsRNA sensor proteins. Identification of endogenous dsRNAs helps to better understand the dsRNAome and its relevance to innate immunity related to human diseases. Here, we report dsRID (double-stranded RNA identifier), a machine-learning-based method to predict dsRNA regions in silico, leveraging the power of long-read RNA-sequencing (RNA-seq) and molecular traits of dsRNAs. Using models trained with PacBio long-read RNA-seq data derived from Alzheimer's disease (AD) brain, we show that our approach is highly accurate in predicting dsRNA regions in multiple datasets. Applied to an AD cohort sequenced by the ENCODE consortium, we characterize the global dsRNA profile with potentially distinct expression patterns between AD and controls. Together, we show that dsRID provides an effective approach to capture global dsRNA profiles using long-read RNA-seq data. Software implementation of dsRID, and genomic coordinates of regions predicted by dsRID in all samples are available at the GitHub repository: https://github.com/gxiaolab/dsRID.

Ensemble learning based assessment of the role of transcription factors in gene expression

Cancer cells are formed when the associated, active genes fail to function the way they are meant to function. Multiple genes collectively control cell growth by activating a proper set of genes. Regulation of gene expression is controlled through the combined effort of multiple regulatory elements. Transcription of each gene is affected differently according to the combinatorial patterns of regulatory elements bound in the nearby regions. Identifying and analysing such patterns will give a better insight into the cell function. The main focus of this study is on developing a computational model to predict the functional role of transcriptional factors residing between divergent gene pairs. Acute Myeloid Leukaemia (AML) gene expression data from GEO and the two TFs EP300 and CTCF binding data calibrated in k562 cell line from ENCODE consortium are taken as a case study.

Pleiotropic Enhancers are Ubiquitous Regulatory Elements in the Human Genome.

Enhancers are regulatory elements of genomes that determine spatio-temporal patterns of gene expression. The human genome contains a vast number of enhancers, which largely outnumber protein-coding genes. Historically, enhancers have been regarded as highly tissue-specific. However, recent evidence has demonstrated that many enhancers are pleiotropic, with activity in multiple developmental contexts. Yet, the extent and impact of pleiotropy remain largely unexplored. In this study we analyzed active enhancers across human organs based on the analysis of both eRNA transcription (FANTOM5 consortium data sets) and chromatin architecture (ENCODE consortium data sets). We show that pleiotropic enhancers are pervasive in the human genome and that most enhancers active in a particular organ are also active in other organs. In addition, our analysis suggests that the proportion of context-specific enhancers of a given organ is explained, at least in part, by the proportion of context-specific genes in that same organ. The notion that such a high proportion of human enhancers can be pleiotropic suggests that small regions of regulatory DNA contain abundant regulatory information and that these regions evolve under important evolutionary constraints.

Controlling Hematopoietic Stem Cell Quiescence By Ablating the TGFβ-Responsive, Hematopoietic-Hpecific Enhancer of CDKN1C (p57)

Introduction: The cyclin-dependent kinase inhibitor (CDKI) CDKN1C (p57) is a putative tumor suppressor gene with strong differential expression in both human and murine hematopoietic stem cells (HSCs). The most immature, quiescent HSCs are marked by p57 expression and p57 is rapidly downregulated as HSCs enter cell cycle and differentiate. Genetic deletion of p57 leads to abnormal HSC cell cycle entry and, in murine models, a propensity for HSC exhaustion indicating that p57 is an essential gatekeeper of HSC function. TGFβ signaling is an important mediator of HSC quiescence and mandates the withdrawal of HSCs from cell cycle following hematopoietic stress. We have found that p57 is a direct transcriptional target of TGFβ in HSCs where it serves as an essential downstream mediator of TGFβ signaling. In HSCs, genetic deletion of p57 phenocopies the effects of TGFβ blockade in vivo. The regulation of p57 is complex and interesting. In almost all epithelial cell types, p57 is poorly expressed and is not a transcriptional target of TGFβ. This is also true for most differentiated hematopoietic lineages. The mechanism for the tissue-type and differentiation stage-specific expression of p57 and its control by TGFβ in HSCs is not known. We hypothesized that a hematopoietic enhancer for p57 must be responsible for TGFβ induction in HSCs.Methods: We performed chromatin immunoprecipitation (ChIP/ChIP-chip/ChIP-seq) in human, AML-derived M091 cells that faithfully upregulate p57 in response to TGFβ signaling in a manner indistinguishable from human cord blood derived CD34+ cells. Cultured cells were studied while proliferating and following treatment with TGFβ for various times. ChIP was performed for histone modifications that mark enhancer elements (histone H3 lysine 4 mono-methylation, H3K4me1, and H3K27-acetlylation, H3K27ac) and promoters (histone H3 lysine 4 tri-methylation, H3K4me2, and H3K27-acetlylation, H3K27ac). Genomic localization of receptor activated phospho-Smad2 was also identified before and after TGFβ stimulation. Putative enhancers were cloned into reporter constructs that were then studied after stable incorporation into the genome of M091 and K562 cells.Results: We identified putative enhancer elements more than 100 KB from the p57 gene body (Fig. A). A cluster of three small elements fulfilled our biochemical criterion for a hematopoietic-specific enhancer: enhancer histone marks (H3K4me1/H3K27ac); hyper-acetylation and phospho-Smad2 binding in response to TGFβ (Fig. B, D). When subcloned and tested in reporter assays, the elements had enhancer function and two of the three were induced by TGFβ (Fig. C). Interestingly, the ENCODE consortium identified the genomic region of our putative enhancers as overlapping with a DNAseI hypersensitive site and harboring the chromatin signature of a “Strong Enhancer” only in hematopoietic cells (K562) but not in other cell type tested. Nonetheless, unequivocal classification of this element as a p57 enhancer required in vivo analysis of HSCs with targeted deletion of the enhancer element.We designed and cloned, ten guide-RNAs (gRNAs) targeting regions upstream and downstream of this putative enhancer cluster. These gRNAs were then tested in HeLa cells by transient transfection with wild-type Cas9 nuclease. Using this approach, we selected a pair of gRNAs with the highest efficiency in deleting the entire enhancer cluster as assessed by ddPCR (~30% alleles). These gRNAs or non-targeting control gRNAs and Cas9 were then transfected into M091 cells along with a GFP reporter. Transfected GFP+ cells were then sorted 36 hrs later. A second lot of unsorted cells were grown in bulk cultures. Allelic ratios of this enhancer element were tracked by ddPCR to assess the relative outgrowth of genomically unmodified cells compared to those that had this putative p57 enhancer deleted. The targeted MO91 population has exhibited resistance to TGFβ as assessed using a growth curve assay.Conclusions: A hematopoietic-specific enhancer lying ~100 kb from the p57 gene body is important for TGFβ-mediated upregulation of p57 and consequent cell cycle withdrawal in immature hematopoietic cells. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Genetic and epigenetic features of promoters with ubiquitous chromatin accessibility support ubiquitous transcription of cell-essential genes.

Gene expression is controlled by regulatory elements within accessible chromatin. Although most regulatory elements are cell type-specific, a subset is accessible in nearly all the 517 human and 94 mouse cell and tissue types assayed by the ENCODE consortium. We systematically analyzed 9000 human and 8000 mouse ubiquitously-accessible candidate cis-regulatory elements (cCREs) with promoter-like signatures (PLSs) from ENCODE, which we denote ubi-PLSs. These are more CpG-rich than non-ubi-PLSs and correspond to genes with ubiquitously high transcription, including a majority of cell-essential genes. ubi-PLSs are enriched with motifs of ubiquitously-expressed transcription factors and preferentially bound by transcriptional cofactors regulating ubiquitously-expressed genes. They are highly conserved between human and mouse at the synteny level but exhibit frequent turnover of motif sites; accordingly, ubi-PLSs show increased variation at their centers compared with flanking regions among the ∼186 thousand human genomes sequenced by the TOPMed project. Finally, ubi-PLSs are enriched in genes implicated in Mendelian diseases, especially diseases broadly impacting most cell types, such as deficiencies in mitochondrial functions. Thus, a set of roughly 9000 mammalian promoters are actively maintained in an accessible state across cell types by a distinct set of transcription factors and cofactors to ensure the transcriptional programs of cell-essential genes.

Efficient detection and classification of epigenomic changes under multiple conditions.

Epigenomics, the study of the human genome and its interactions with proteins and other cellular elements, has become of significant interest in recent years. Such interactions have been shown to regulate essential cellular functions and are associated with multiple complex diseases. Therefore, understanding how these interactions may change across conditions is central in biomedical research. Chromatin immunoprecipitation followed by massively parallel sequencing (ChIP-seq) is one of several techniques to detect local changes in epigenomic activity (peaks). However, existing methods for differential peak calling are not optimized for the diversity in ChIP-seq signal profiles, are limited to the analysis of two conditions, or cannot classify specific patterns of differential change when multiple patterns exist. To address these limitations, we present a flexible and efficient method for the detection of differential epigenomic activity across multiple conditions. We utilize data from the ENCODE Consortium and show that the presented method, epigraHMM, exhibits superior performance to current tools and it is among the fastest algorithms available, while allowing the classification of combinatorial patterns of differential epigenomic activity and the characterization of chromatin regulatorystates.

F-Seq2: improving the feature density based peak caller with dynamic statistics.

Genomic and epigenomic features are captured at a genome-wide level by using high-throughput sequencing (HTS) technologies. Peak calling delineates features identified in HTS experiments, such as open chromatin regions and transcription factor binding sites, by comparing the observed read distributions to a random expectation. Since its introduction, F-Seq has been widely used and shown to be the most sensitive and accurate peak caller for DNase I hypersensitive site (DNase-seq) data. However, the first release (F-Seq1) has two key limitations: lack of support for user-input control datasets, and poor test statistic reporting. These constrain its ability to capture systematic and experimental biases inherent to the background distributions in peak prediction, and to subsequently rank predicted peaks by confidence. To address these limitations, we present F-Seq2, which combines kernel density estimation and a dynamic ‘continuous’ Poisson test to account for local biases and accurately rank candidate peaks. The output of F-Seq2 is suitable for irreproducible discovery rate analysis as test statistics are calculated for individual candidate summits, allowing direct comparison of predictions across replicates. These improvements significantly boost the performance of F-Seq2 for ATAC-seq and ChIP-seq datasets, outperforming competing peak callers used by the ENCODE Consortium in terms of precision and recall.

Genome-wide analysis of primary microRNA expression using H3K36me3 ChIP-seq data

MicroRNAs are key players in gene regulatory networks controlling cell homeostasis. Their altered expression has been previously linked to disease outcomes and microRNAs thus serve as biomarkers for disease diagnostics. However, their synthesis and its transcriptional regulation have been challenging to investigate. In this study, we validated the use of H3K36me3 histone modification for the quantification of microRNA transcription levels using data from the ENCODE Consortium and then applied this approach to provide new insight into the cell-type-specific regulationin tissues, cell line models and cardiac disease. In cardiomyocytes derived from patients suffering from septal defects, carrying a G296S mutation in the transcription factor GATA4, we show that microRNA gene transcription is altered in cardiomyocytes carrying this mutation and coincides with novel super-enhancers formed within regulatory domains defined using chromatin interaction profiles. The most prominently elevated primary transcript encodes for let-7a and miR-100 that may target genes in the Hippo signaling pathway. Collectively, our work presents a methodology to quantify microRNA gene expression using histone marker data and paves the way for functional studies of cell-type-specific transcriptional regulation occurring in disease pathology.

Analysis of splice variants of the human protein disulfide isomerase (P4HB) gene

BackgroundProtein Disulfide Isomerases are thiol oxidoreductase chaperones from thioredoxin superfamily with crucial roles in endoplasmic reticulum proteostasis, implicated in many diseases. The family prototype PDIA1 is also involved in vascular redox cell signaling. PDIA1 is coded by the P4HB gene. While forced changes in P4HB gene expression promote physiological effects, little is known about endogenous P4HB gene regulation and, in particular, gene modulation by alternative splicing. This study addressed the P4HB splice variant landscape.ResultsTen protein coding sequences (Ensembl) of the P4HB gene originating from alternative splicing were characterized. Structural features suggest that except for P4HB-021, other splice variants are unlikely to exert thiol isomerase activity at the endoplasmic reticulum. Extensive analyses using FANTOM5, ENCODE Consortium and GTEx project databases as RNA-seq data sources were performed. These indicated widespread expression but significant variability in the degree of isoform expression among distinct tissues and even among distinct locations of the same cell, e.g., vascular smooth muscle cells from different origins. P4HB-02, P4HB-027 and P4HB-021 were relatively more expressed across each database, the latter particularly in vascular smooth muscle. Expression of such variants was validated by qRT-PCR in some cell types. The most consistently expressed splice variant was P4HB-021 in human mammary artery vascular smooth muscle which, together with canonical P4HB gene, had its expression enhanced by serum starvation.ConclusionsOur study details the splice variant landscape of the P4HB gene, indicating their potential role to diversify the functional reach of this crucial gene. P4HB-021 splice variant deserves further investigation in vascular smooth muscle cells.

Berberine chloride suppresses non-small cell lung cancer by deregulating Sin3A/TOP2B pathway in vitro and in vivo.

Berberine chloride (BBC) is a well-known plant isoquinoline alkaloid derived from Berberis aristata. In this study, we aim to explore the effect of BBC on non-small cell lung cancer (NSCLC), and further expound the underlying mechanism of BBC induces NSCLC cell death in vitro and in vivo. CCK-8 assay and colony formation assay were used to test the viability and colony formation ability of NSCLC cells. Apoptosis analysis was used to analyze the apoptotic cells. siRNAs were utilized to disturb the expression of Sin3A. qPCR and Western blot analysis were employed to determine mRNA and protein levels of related genes and proteins. Tumor xenografts model was used for in vivo detection. BBC inhibited the proliferation and colony formation of human NSCLC cells in a dose- and time-dependent manner. In addition, BBC induced DNA double-stranded breaks (DSBs) through downregulating TOP2B level, leading to apoptosis in human NSCLC cells. The Chip-seq data of A549 cells obtained from the ENCODE consortium indicate that Sin3A binds on the promoters of TOP2B. Knockdown of Sin3A led to downregulation of TOP2B in human NSCLC cells. Furthermore, BBC decreased Sin3A expression and shortened the half-life of Sin3A, results in downregulation of TOP2B in human NSCLC cells. In this study, we demonstrated a new mechanism that BBC suppresses human NSCLC by deregulating Sin3A/TOP2B pathway, leading to DNA damage and apoptosis in human NSCLC in vitro and in vivo.

Abstract 3122: A functional POT1 variant and risk of thyroid subsequent malignant neoplasm: A report from the Childhood Cancer Survivor Study

Abstract Purpose: Reduced telomere content has been associated with an increased risk for subsequent malignant neoplasms of the thyroid (thyroid SMN) in survivors of childhood cancer (PMID 24277454). However, variation in nine common single nucleotide polymorphisms (SNPs) that influence leukocyte telomere length was not associated with thyroid SMN (PMID 30377209). Here, we report results of a candidate gene approach investigating associations between thyroid SMN and genes functionally related to telomere maintenance. Methods: Genome-wide SNP data were generated using the Illumina HumanOmni5Exome array in 5,324 5-year survivors of childhood cancer enrolled to the Childhood Cancer Survivor Study (CCSS), and imputed to the 1000 Genomes reference haplotypes. Of these 5,324 survivors, 117 developed thyroid SMN. We mapped 4,290 variants to 18 genes involved in telomere maintenance (TERC, TERT, RAD50, NHP2, POT1, TERF1, NBN, TPP1, MRE11A, TINF2, NOP10, PARN, ACD, TERF2, RAP1 (TERF2IP), WRAP53, CTC1, and RTEL1) and used RegulomeDB to annotate each variant by its projected functional impact. Time-to-event Cox regression was used for thyroid SMN, censored by date of any SMN, death, or last follow-up. For each functional SNP, hazard ratios (HR) were estimated, adjusting for sex, primary cancer diagnosis, neck radiation exposure (yes/no), alkylating agent exposure (yes/no), and thyroid nodules. Results: Our analysis included 103 SNPs with a RegulomeDB score ≤ 2, signifying high likelihood for affecting transcriptional regulation. After Bonferroni correction (α=0.000485), an imputed variant in an intronic region of POT1 (Protection of Telomeres 1), rs58722976 (CCSS minor allele frequency = 0.2%), was associated with risk for thyroid SMN (adjusted HR=6.1, 95% CI: 2.4, 15.5, p=0.0001) and was present in 3 cases and 14 controls. Conclusions: Using a candidate gene approach, we observed an association between an intronic regulatory POT1 variant and risk for thyroid SMN in survivors. POT1 is a highly conserved gene encoding a key component of the shelterin complex, which protects telomere ends against DNA damage recognition and facilitates telomerase-mediated telomere elongation. The ENCODE Consortium identifies rs58722976 as a strong enhancer and DNase in multiple tissues, including the hematopoietic compartment. ENCODE ChIP-Seq data suggest that rs58722976 genotypes also affect protein binding of RAD21, SMC3, and CTCF, components of cohesin and a co-localizing protein that play key roles in maintaining genomic integrity. Germline variants in POT1 have been described in familial glioma, melanoma, colorectal cancer, chronic lymphocytic leukemia, and non-TP53 familial cancer syndromes. The results of this study suggest that intronic variation in POT1 may affect key protein binding interactions related to defects in telomere maintenance and affecting genomic integrity. Citation Format: Melissa A. Richard, Philip J. Lupo, Lindsay M. Morton, Yutaka Yasui, Michael A. Arnold, Joseph P. Neglia, Lucie M. Turcotte, Wendy M. Leisenring, Stephen J. Chanock, Joshua N. Sampson, Gregory T. Armstrong, Leslie L. Robison, Smita Bhatia, Maria M. Gramatges. A functional POT1 variant and risk of thyroid subsequent malignant neoplasm: A report from the Childhood Cancer Survivor Study [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 3122.

EpiAlignment: alignment with both DNA sequence and epigenomic data.

Comparative epigenomics, which subjects both epigenome and genome to interspecies comparison, has become a powerful approach to reveal regulatory features of the genome. Thus elucidated regulatory features surpass the information derived from comparison of genomic sequences alone. Here, we present EpiAlignment, a web-based tool to align genomic regions with both DNA sequence and epigenomic data. EpiAlignment takes DNA sequence and epigenomic profiles derived by ChIP-seq from two species as input data, and outputs the best semi-global alignments. These alignments are based on EpiAlignment scores, computed by a dynamic programming algorithm that accounts for both sequence alignment and epigenome similarity. For timely response, the EpiAlignment web server automatically initiates up to 140 computing threads depending on the size of user input data. For users’ convenience, we have pre-compiled the comparable human and mouse epigenome datasets in matched cell types and tissues from the Roadmap Epigenomics and ENCODE consortia. Users can either upload their own data or select pre-compiled datasets as inputs for EpiAlignment analyses. Results are presented in graphical and tabular formats where the entries can be interactively expanded to visualize additional features of these aligned regions. EpiAlignment is available at https://epialign.ucsd.edu/.

Noncoding AUG circRNAs constitute an abundant and conserved subclass of circles.

Circular RNAs (circRNAs) are a subset of noncoding RNAs previously considered as products of missplicing. Now, circRNAs are considered functional molecules, although to date, only few functions have been experimentally validated. Here, based on RNA sequencing from the ENCODE consortium, we identify and characterize a subset of circRNAs, coined AUG circRNAs, encompassing the annotated translational start codon from the protein-coding host genes. AUG circRNAs are more abundantly expressed and conserved than other groups of circRNAs, and they display flanking sequences that suggest an Alu-independent mechanism of biogenesis. The AUG circRNAs contain part of bona fide open reading frame, and in the recent years, several studies have reported cases of circRNA translation. However, using thorough cross-species analysis, extensive ribosome profiling, proteomics analyses, and experimental data on a selected panel of AUG circRNAs, we observe no indications of translation of AUG circRNAs or any other circRNAs. Our data provide a comprehensive classification of circRNAs and, collectively, the data suggest that the AUG circRNAs constitute an abundant subclass of circRNAs produced independently of primate-specific Alu elements.

Epigenomic analysis reveals DNA motifs regulating histone modifications in human and mouse

Histones are modified by enzymes that act in a locus, cell-type, and developmental stage-specific manner. The recruitment of enzymes to chromatin is regulated at multiple levels, including interaction with sequence-specific DNA-binding factors. However, the DNA-binding specificity of the regulatory factors that orchestrate specific histone modifications has not been broadly mapped. We have analyzed 6 histone marks (H3K4me1, H3K4me3, H3K27ac, H3K27me3, K3H9me3, H3K36me3) across 121 human cell types and tissues from the NIH Roadmap Epigenomics Project as well as 8 histone marks (with addition of H3K4me2 and H3K9ac) from the mouse ENCODE Consortium. We have identified 361 and 369 DNA motifs in human and mouse, respectively, that are the most predictive of each histone mark. Interestingly, 107 human motifs are conserved between the two species. In human embryonic cell line H1, we mutated only the found DNA motifs at particular loci and the significant reduction of H3K27ac levels validated the regulatory roles of the perturbed motifs. The functionality of these motifs was also supported by the evidence that histone-associated motifs, especially H3K4me3 motifs, significantly overlap with the expression of quantitative trait loci SNPs in cancer patients more than the known and random motifs. Furthermore, we observed possible feedbacks to control chromatin dynamics as the found motifs appear in the promoters or enhancers associated with various histone modification enzymes. These results pave the way toward revealing the molecular mechanisms of epigenetic events, such as histone modification dynamics and epigenetic priming.

Regular expression based pattern extraction from a cell - Specific gene expression data

Abstract Cancer cells are formed when active genes stop functioning properly. Timely activation of a gene is governed through the combined effort of multiple Transcription Factors (TFs). TFs are proteins that bind on DNA in a sequence-specific manner. It is difficult to trace the target and role of TFs in the gene regulation process. The same element acts differently in different places, similar to the way the same word has a different meaning in a different context. This approach treats the cell line in a language context, whereas the genes and TFs are the symbols or letters of the language. Different combination of symbols forms a sequence with repetitive patterns. Identifying and analysing such frequently occurring patterns will give a better insight into the cell. This work mainly aims to identify such patterns found in the cell line using regular expression technique. The patterns generated in this work can be chosen as a feature for identifying the effect of regulatory elements in the genomic region. For improving readability identity of each character present in the pattern is documented in the form of a text file. Acute Myeloid Leukaemia (AML) data from GEO repository and the related two TFs binding narrow peak data, calibrated in K562 cell line from ENCODE consortium are taken as a case study.

From the human genome to the epigenome of cancer: the use of high technology in molecular oncology

Fifteen years after the publication of the full sequence of the human genome which revolutionized medicine and biotechnology, profound elucidation of the molecular mechanisms of genetic disorders remains a challenge. National and international institutions conduct a number of research projects in genomics. Some of them are focused on the characterization of functional elements of the genome (e.g., the Genome Browser database by the ENCODE consortium), some gather information on polymorphisms (HapMap, The 1000 Genomes Project) and mutations (The Human Gene Mutation Database), while other are specifically dedicated to the genomic characterization of cancer (The Cancer Genome Atlas, The Pediatric Cancer Genome Project). Even though the projects are conducted independently, juxtapositions of the constantly updated project data may be performed, leading to interesting results. The genome-wide association studies (GWAS) allowed the identification of millions of SNPs and short insertions/deletions, as well as thousands of structural variants of polymorphic gene products. Further data-mining studies allowed the distinction between synonymous and nonsynonymous SNPs, which became the basis for the epidemiological studies of various types of genetic disorders. The results of the sequencing of entire genomes and transcriptomes may be useful in the identification of novel prognostic and predictive markers. High-throughput technologies are emerging methods in molecular diagnostics, furthermore the correlation of DNA methylation patterns and gene expression profiles may also provide useful results in cancer diagnostics.

RBP-Maps enables robust generation of splicing regulatory maps.

Alternative splicing of pre-messenger RNA transcripts enables the generation of multiple protein isoforms from the same gene locus, providing a major source of protein diversity in mammalian genomes. RNA binding proteins (RBPs) bind to RNA to control splice site choice and define which exons are included in the resulting mature RNA transcript. However, depending on where the RBPs bind relative to splice sites, they can activate or repress splice site usage. To explore this position-specific regulation, in vivo binding sites identified by methods such as cross-linking and immunoprecipitation (CLIP) are integrated with alternative splicing events identified by RNA-seq or microarray. Merging these data sets enables the generation of a “splicing map,” where CLIP signal relative to a merged meta-exon provides a simple summary of the position-specific effect of binding on splicing regulation. Here, we provide RBP-Maps, a software tool to simplify generation of these maps and enable researchers to rapidly query regulatory patterns of an RBP of interest. Further, we discuss various alternative approaches to generate such splicing maps, focusing on how decisions in construction (such as the use of peak versus read density, or whole-reads versus only single-nucleotide candidate crosslink positions) can affect the interpretation of these maps using example eCLIP data from the 150 RBPs profiled by the ENCODE consortium.