CelFiE-ISH: a probabilistic model for multi-cell type deconvolution from single-molecule DNA methylation haplotypes.

Deconvolution methods infer quantitative cell type estimates from bulk measurement of mixed samples including blood and tissue. DNA methylation sequencing measures multiple CpGs per read, but few existing deconvolution methods leverage this within-read information. We develop CelFiE-ISH, which extends an existing method (CelFiE) to use within-read haplotype information. CelFiE-ISH outperforms CelFiE and other existing methods, achieving 30% better accuracy and more sensitive detection of rare cell types. We also demonstrate the importance of marker selection and of tailoring markers for haplotype-aware methods. While here we use gold-standard short-read sequencing data, haplotype-aware methods will be well-suited for long-read sequencing.

BISCUIT: an efficient, standards-compliant tool suite for simultaneous genetic and epigenetic inference in bulk and single-cell studies.

Data from both bulk and single-cell whole-genome DNA methylation experiments are under-utilized in many ways. This is attributable to inefficient mapping of methylation sequencing reads, routinely discarded genetic information, and neglected read-level epigenetic and genetic linkage information. We introduce the BISulfite-seq Command line User Interface Toolkit (BISCUIT) and its companion R/Bioconductor package, biscuiteer, for simultaneous extraction of genetic and epigenetic information from bulk and single-cell DNA methylation sequencing. BISCUIT's performance, flexibility and standards-compliant output allow large, complex experimental designs to be characterized on clinical timescales. BISCUIT is particularly suited for processing data from single-cell DNA methylation assays, with its excellent scalability, efficiency, and ability to greatly enhance mappability, a key challenge for single-cell studies. We also introduce the epiBED format for single-molecule analysis of coupled epigenetic and genetic information, facilitating the study of cellular and tissue heterogeneity from DNA methylation sequencing.

Comprehensive analyses of partially methylated domains and differentially methylated regions in esophageal cancer reveal both cell-type- and cancer-specific epigenetic regulation.

BACKGROUND: As one of the most common malignancies, esophageal cancer has two subtypes, squamous cell carcinoma and adenocarcinoma, arising from distinct cells-of-origin. Distinguishing cell-type-specific molecular features from cancer-specific characteristics is challenging. RESULTS: We analyze whole-genome bisulfite sequencing data on 45 esophageal tumor and nonmalignant samples from both subtypes. We develop a novel sequence-aware method to identify large partially methylated domains (PMDs), revealing profound heterogeneity at both methylation level and genomic distribution of PMDs across tumor samples. We identify subtype-specific PMDs that are associated with repressive transcription, chromatin B compartments and high somatic mutation rate. While genomic locations of these PMDs are pre-established in normal cells, the degree of loss is significantly higher in tumors. We find that cell-type-specific deposition of H3K36me2 may underlie genomic distribution of PMDs. At a smaller genomic scale, both cell-type- and cancer-specific differentially methylated regions (DMRs) are identified for each subtype. Using binding motif analysis within these DMRs, we show that a cell-type-specific transcription factor HNF4A maintains the binding sites that it generates in normal cells, while establishing new binding sites cooperatively with novel partners such as FOSL1 in esophageal adenocarcinoma. Finally, leveraging pan-tissue single-cell and pan-cancer epigenomic datasets, we demonstrate that a substantial fraction of cell-type-specific PMDs and DMRs identified here in esophageal cancer are actually markers that co-occur in other cancers originating from related cell types. CONCLUSIONS: These findings advance our understanding of DNA methylation dynamics at various genomic scales in normal and malignant states, providing novel mechanistic insights into cell-type- and cancer-specific epigenetic regulations.

Muscle injury causes long-term changes in stem-cell DNA methylation.

Injury to muscle brings about the activation of stem cells, which then generate new myocytes to replace damaged tissue. We demonstrate that this activation is accompanied by a dramatic change in the stem-cell methylation pattern that prepares them epigenetically for terminal myocyte differentiation. These de- and de novo methylation events occur at regulatory elements associated with genes involved in myogenesis and are necessary for activation and regeneration. Local injury of one muscle elicits an almost identical epigenetic change in satellite cells from other muscles in the body, in a process mediated by circulating factors. Furthermore, this same methylation state is also generated in muscle stem cells (MuSCs) of female animals following pregnancy, even in the absence of any injury. Unlike the activation-induced expression changes, which are transient, the induced methylation profile is stably maintained in resident MuSCs and thus represents a molecular memory of previous physiological events that is probably programmed to provide a mechanism for long-term adaptation.

DNA methylation and transcriptomic features are preserved throughout disease recurrence and chemoresistance in high grade serous ovarian cancers.

BACKGROUND: Little is known about the role of global DNA methylation in recurrence and chemoresistance of high grade serous ovarian cancer (HGSOC). METHODS: We performed whole genome bisulfite sequencing and transcriptome sequencing in 62 primary and recurrent tumors from 28 patients with stage III/IV HGSOC, of which 11 patients carried germline, pathogenic BRCA1 and/or BRCA2 mutations. RESULTS: Landscapes of genome-wide methylation (on average 24.2 million CpGs per tumor) and transcriptomes in primary and recurrent tumors showed extensive heterogeneity between patients but were highly preserved in tumors from the same patient. We identified significant differences in the burden of differentially methylated regions (DMRs) in tumors from BRCA1/2 compared to non-BRCA1/2 carriers (mean 659 DMRs and 388 DMRs in paired comparisons respectively). We identified overexpression of immune pathways in BRCA1/2 carriers compared to non-carriers, implicating an increased immune response in improved survival (P = 0.006) in these BRCA1/2 carriers. CONCLUSION: These findings indicate methylome and gene expression programs established in the primary tumor are conserved throughout disease progression, even after extensive chemotherapy treatment, and that changes in methylation and gene expression are unlikely to serve as drivers for chemoresistance in HGSOC.

Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing.

The Oxford Nanopore (ONT) platform provides portable and rapid genome sequencing, and its ability to natively profile DNA methylation without complex sample processing is attractive for point-of-care real-time sequencing. We recently demonstrated ONT shallow whole-genome sequencing to detect copy number alterations (CNAs) from the circulating tumor DNA (ctDNA) of cancer patients. Here, we show that cell type and cancer-specific methylation changes can also be detected, as well as cancer-associated fragmentation signatures. This feasibility study suggests that ONT shallow WGS could be a powerful tool for liquid biopsy.

Expanding the MECP2 network using comparative genomics reveals potential therapeutic targets for Rett syndrome.

Inactivating mutations in the Methyl-CpG Binding Protein 2 (MECP2) gene are the main cause of Rett syndrome (RTT). Despite extensive research into MECP2 function, no treatments for RTT are currently available. Here, we used an evolutionary genomics approach to construct an unbiased MECP2 gene network, using 1028 eukaryotic genomes to prioritize proteins with strong co-evolutionary signatures with MECP2. Focusing on proteins targeted by FDA-approved drugs led to three promising targets, two of which were previously linked to MECP2 function (IRAK, KEAP1) and one that was not (EPOR). The drugs targeting these three proteins (Pacritinib, DMF, and EPO) were able to rescue different phenotypes of MECP2 inactivation in cultured human neural cell types, and appeared to converge on Nuclear Factor Kappa B (NF-κB) signaling in inflammation. This study highlights the potential of comparative genomics to accelerate drug discovery, and yields potential new avenues for the treatment of RTT.

Activation of bivalent factor DLX5 cooperates with master regulator TP63 to promote squamous cell carcinoma.

To reconstruct systematically hyperactive transcription factor (TF)-dependent transcription networks in squamous cell carcinomas (SCCs), a computational method (ELMER) was applied to 1293 pan-SCC patient samples, and 44 hyperactive SCC TFs were identified. As a top candidate, DLX5 exhibits a notable bifurcate re-configuration of its bivalent promoter in cancer. Specifically, DLX5 maintains a bivalent state in normal tissues; its promoter is hypermethylation, leading to DLX5 transcriptional silencing in esophageal adenocarcinoma (EAC). In stark contrast, DLX5 promoter gains active histone marks and becomes transcriptionally activated in ESCC, which is directly mediated by SOX2. Functionally, silencing of DLX5 substantially inhibits SCC viability both in vitro and in vivo. Mechanistically, DLX5 cooperates with TP63 in regulating ∼2000 enhancers and promoters, which converge on activating cancer-promoting pathways. Together, our data establish a novel and strong SCC-promoting factor and elucidate a new epigenomic mechanism - bifurcate chromatin re-configuration - during cancer development.

A pan-cancer analysis of CpG Island gene regulation reveals extensive plasticity within Polycomb target genes.

CpG Island promoter genes make up more than half of human genes, and a subset regulated by Polycomb-Repressive Complex 2 (PRC2+-CGI) become DNA hypermethylated and silenced in cancer. Here, we perform a systematic analysis of CGI genes across TCGA cancer types, finding that PRC2+-CGI genes are frequently prone to transcriptional upregulation as well. These upregulated PRC2+-CGI genes control important pathways such as Epithelial-Mesenchymal Transition (EMT) and TNFα-associated inflammatory response, and have greater cancer-type specificity than other CGI genes. Using publicly available chromatin datasets and genetic perturbations, we show that transcription factor binding sites (TFBSs) within distal enhancers underlie transcriptional activation of PRC2+-CGI genes, coinciding with loss of the PRC2-associated mark H3K27me3 at the linked promoter. In contrast, PRC2-free CGI genes are predominantly regulated by promoter TFBSs which are common to most cancer types. Surprisingly, a large subset of PRC2+-CGI genes that are upregulated in one cancer type are also hypermethylated/silenced in at least one other cancer type, underscoring the high degree of regulatory plasticity of these genes, likely derived from their complex regulatory control during normal development.

Mechanistic and therapeutic distinctions between cardiosphere-derived cell and mesenchymal stem cell extracellular vesicle non-coding RNA.

Cell therapy limits ischemic injury following myocardial infarction (MI) by preventing cell death, modulating the immune response, and promoting tissue regeneration. The therapeutic efficacy of cardiosphere-derived cells (CDCs) and mesenchymal stem cells (MSCs) is associated with extracellular vesicle (EV) release. Prior head-to-head comparisons have shown CDCs to be more effective than MSCs in MI models. Despite differences in cell origin, it is unclear why EVs from different adult stem cell populations elicit differences in therapeutic efficacy. Here, we compare EVs derived from multiple human MSC and CDC donors using diverse in vitro and in vivo assays. EV membrane protein and non-coding RNA composition are highly specific to the parent cell type; for example, miR-10b is enriched in MSC-EVs relative to CDC-EVs, while Y RNA fragments follow the opposite pattern. CDC-EVs enhance the Arg1/Nos2 ratio in macrophages in vitro and reduce MI size more than MSC-EVs and suppress inflammation during acute peritonitis in vivo. Thus, CDC-EVs are distinct from MSC-EVs, confer immunomodulation, and protect the host against ischemic myocardial injury and acute inflammation.

Ovarian Cancer Risk Variants Are Enriched in Histotype-Specific Enhancers and Disrupt Transcription Factor Binding Sites.

Quantifying the functional effects of complex disease risk variants can provide insights into mechanisms underlying disease biology. Genome-wide association studies have identified 39 regions associated with risk of epithelial ovarian cancer (EOC). The vast majority of these variants lie in the non-coding genome, where they likely function through interaction with gene regulatory elements. In this study we first estimated the heritability explained by known common low penetrance risk alleles for EOC. The narrow sense heritability (hg2) of EOC overall and high-grade serous ovarian cancer (HGSOCs) were estimated to be 5%-6%. Partitioned SNP heritability across broad functional categories indicated a significant contribution of regulatory elements to EOC heritability. We collated epigenomic profiling data for 77 cell and tissue types from Roadmap Epigenomics and ENCODE, and from H3K27Ac ChIP-seq data generated in 26 ovarian cancer and precursor-related cell and tissue types. We identified significant enrichment of risk single-nucleotide polymorphisms (SNPs) in active regulatory elements marked by H3K27Ac in HGSOCs. To further investigate how risk SNPs in active regulatory elements influence predisposition to ovarian cancer, we used motifbreakR to predict the disruption of transcription factor binding sites. We identified 469 candidate causal risk variants in H3K27Ac peaks that are predicted to significantly break transcription factor (TF) motifs. The most frequently broken motif was REST (p value = 0.0028), which has been reported as both a tumor suppressor and an oncogene. Overall, these systematic functional annotations with epigenomic data improve interpretation of EOC risk variants and shed light on likely cells of origin.

Lineage-Specific Epigenomic and Genomic Activation of Oncogene HNF4A Promotes Gastrointestinal Adenocarcinomas.

Gastrointestinal adenocarcinomas (GIAC) of the tubular gastrointestinal (GI) tract including esophagus, stomach, colon, and rectum comprise most GI cancers and share a spectrum of genomic features. However, the unified epigenomic changes specific to GIAC are poorly characterized. Using 907 GIAC samples from The Cancer Genome Atlas, we applied mathematical algorithms to large-scale DNA methylome and transcriptome profiles to reconstruct transcription factor (TF) networks and identify a list of functionally hyperactive master regulator (MR) TF shared across different GIAC. The top candidate HNF4A exhibited prominent genomic and epigenomic activation in a GIAC-specific manner. A complex interplay between the HNF4A promoter and three distal enhancer elements was coordinated by GIAC-specific MRTF including ELF3, GATA4, GATA6, and KLF5. HNF4A also self-regulated its own promoter and enhancers. Functionally, HNF4A promoted cancer proliferation and survival by transcriptional activation of many downstream targets, including HNF1A and factors of interleukin signaling, in a lineage-specific manner. Overall, our study provides new insights into the GIAC-specific gene regulatory networks and identifies potential therapeutic strategies against these common cancers. SIGNIFICANCE: These findings show that GIAC-specific master regulatory transcription factors control HNF4A via three distal enhancers to promote GIAC cell proliferation and survival. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/13/2722/F1.large.jpg.

Non-coding somatic mutations converge on the PAX8 pathway in ovarian cancer.

The functional consequences of somatic non-coding mutations in ovarian cancer (OC) are unknown. To identify regulatory elements (RE) and genes perturbed by acquired non-coding variants, here we establish epigenomic and transcriptomic landscapes of primary OCs using H3K27ac ChIP-seq and RNA-seq, and then integrate these with whole genome sequencing data from 232 OCs. We identify 25 frequently mutated regulatory elements, including an enhancer at 6p22.1 which associates with differential expression of ZSCAN16 (P = 6.6 × 10-4) and ZSCAN12 (P = 0.02). CRISPR/Cas9 knockout of this enhancer induces downregulation of both genes. Globally, there is an enrichment of single nucleotide variants in active binding sites for TEAD4 (P = 6 × 10-11) and its binding partner PAX8 (P = 2×10-10), a known lineage-specific transcription factor in OC. In addition, the collection of cis REs associated with PAX8 comprise the most frequently mutated set of enhancers in OC (P = 0.003). These data indicate that non-coding somatic mutations disrupt the PAX8 transcriptional network during OC development.

RNA-Binding Protein ZFP36L1 Suppresses Hypoxia and Cell-Cycle Signaling.

ZFP36L1 is a tandem zinc-finger RNA-binding protein that recognizes conserved adenylate-uridylate-rich elements (ARE) located in 3'untranslated regions (UTR) to mediate mRNA decay. We hypothesized that ZFP36L1 is a negative regulator of a posttranscriptional hub involved in mRNA half-life regulation of cancer-related transcripts. Analysis of in silico data revealed that ZFP36L1 was significantly mutated, epigenetically silenced, and downregulated in a variety of cancers. Forced expression of ZFP36L1 in cancer cells markedly reduced cell proliferation in vitro and in vivo, whereas silencing of ZFP36L1 enhanced tumor cell growth. To identify direct downstream targets of ZFP36L1, systematic screening using RNA pull-down of wild-type and mutant ZFP36L1 as well as whole transcriptome sequencing of bladder cancer cells {plus minus} tet-on ZFP36L1 was performed. A network of 1,410 genes was identified as potential direct targets of ZFP36L1. These targets included a number of key oncogenic transcripts such as HIF1A, CCND1, and E2F1. ZFP36L1 specifically bound to the 3'UTRs of these targets for mRNA degradation, thus suppressing their expression. Dual luciferase reporter assays and RNA electrophoretic mobility shift assays showed that wild-type, but not zinc-finger mutant ZFP36L1, bound to HIF1A 3'UTR and mediated HIF1A mRNA degradation, leading to reduced expression of HIF1A and its downstream targets. Collectively, our findings reveal an indispensable role of ZFP36L1 as a posttranscriptional safeguard against aberrant hypoxic signaling and abnormal cell-cycle progression. SIGNIFICANCE: RNA-binding protein ZFP36L1 functions as a tumor suppressor by regulating the mRNA stability of a number of mRNAs involved in hypoxia and cell-cycle signaling.

Master transcription factors form interconnected circuitry and orchestrate transcriptional networks in oesophageal adenocarcinoma.

OBJECTIVE: While oesophageal squamous cell carcinoma remains infrequent in Western populations, the incidence of oesophageal adenocarcinoma (EAC) has increased sixfold to eightfold over the past four decades. We aimed to characterise oesophageal cancer-specific and subtypes-specific gene regulation patterns and their upstream transcription factors (TFs). DESIGN: To identify regulatory elements, we profiled fresh-frozen oesophageal normal samples, tumours and cell lines with chromatin immunoprecipitation sequencing (ChIP-Seq). Mathematical modelling was performed to establish (super)-enhancers landscapes and interconnected transcriptional circuitry formed by master TFs. Coregulation and cooperation between master TFs were investigated by ChIP-Seq, circularised chromosome conformation capture sequencing and luciferase assay. Biological functions of candidate factors were evaluated both in vitro and in vivo. RESULTS: We found widespread and pervasive alterations of the (super)-enhancer reservoir in both subtypes of oesophageal cancer, leading to transcriptional activation of a myriad of novel oncogenes and signalling pathways, some of which may be exploited pharmacologically (eg, leukemia inhibitory factor (LIF) pathway). Focusing on EAC, we bioinformatically reconstructed and functionally validated an interconnected circuitry formed by four master TFs-ELF3, KLF5, GATA6 and EHF-which promoted each other's expression by interacting with each super-enhancer. Downstream, these master TFs occupied almost all EAC super-enhancers and cooperatively orchestrated EAC transcriptome. Each TF within the transcriptional circuitry was highly and specifically expressed in EAC and functionally promoted EAC cell proliferation and survival. CONCLUSIONS: By establishing cancer-specific and subtype-specific features of the EAC epigenome, our findings promise to transform understanding of the transcriptional dysregulation and addiction of EAC, while providing molecular clues to develop novel therapeutic modalities against this malignancy.

GENAVi: a shiny web application for gene expression normalization, analysis and visualization.

BACKGROUND: The development of next generation sequencing (NGS) methods led to a rapid rise in the generation of large genomic datasets, but the development of user-friendly tools to analyze and visualize these datasets has not developed at the same pace. This presents a two-fold challenge to biologists; the expertise to select an appropriate data analysis pipeline, and the need for bioinformatics or programming skills to apply this pipeline. The development of graphical user interface (GUI) applications hosted on web-based servers such as Shiny can make complex workflows accessible across operating systems and internet browsers to those without programming knowledge. RESULTS: We have developed GENAVi (Gene Expression Normalization Analysis and Visualization) to provide a user-friendly interface for normalization and differential expression analysis (DEA) of human or mouse feature count level RNA-Seq data. GENAVi is a GUI based tool that combines Bioconductor packages in a format for scientists without bioinformatics expertise. We provide a panel of 20 cell lines commonly used for the study of breast and ovarian cancer within GENAVi as a foundation for users to bring their own data to the application. Users can visualize expression across samples, cluster samples based on gene expression or correlation, calculate and plot the results of principal components analysis, perform DEA and gene set enrichment and produce plots for each of these analyses. To allow scalability for large datasets we have provided local install via three methods. We improve on available tools by offering a range of normalization methods and a simple to use interface that provides clear and complete session reporting and for reproducible analysis. CONCLUSION: The development of tools using a GUI makes them practical and accessible to scientists without bioinformatics expertise, or access to a data analyst with relevant skills. While several GUI based tools are currently available for RNA-Seq analysis we improve on these existing tools. This user-friendly application provides a convenient platform for the normalization, analysis and visualization of gene expression data for scientists without bioinformatics expertise.

Before and After: Comparison of Legacy and Harmonized TCGA Genomic Data Commons' Data.

We present a systematic analysis of the effects of synchronizing a large-scale, deeply characterized, multi-omic dataset to the current human reference genome, using updated software, pipelines, and annotations. For each of 5 molecular data platforms in The Cancer Genome Atlas (TCGA)-mRNA and miRNA expression, single nucleotide variants, DNA methylation and copy number alterations-comprehensive sample, gene, and probe-level studies were performed, towards quantifying the degree of similarity between the 'legacy' GRCh37 (hg19) TCGA data and its GRCh38 (hg38) version as 'harmonized' by the Genomic Data Commons. We offer gene lists to elucidate differences that remained after controlling for confounders, and strategies to mitigate their impact on biological interpretation. Our results demonstrate that the hg19 and hg38 TCGA datasets are very highly concordant, promote informed use of either legacy or harmonized omics data, and provide a rubric that encourages similar comparisons as new data emerge and reference data evolve.

Mapping Citrullinated Sites in Multiple Organs of Mice Using Hypercitrullinated Library.

Protein citrullination (or deimination), an irreversible post-translational modification, has been implicated in several physiological and pathological processes, including gene expression regulation, apoptosis, rheumatoid arthritis, and Alzheimer's disease. Several research studies have been carried out on citrullination under many conditions. However, until now, challenges in sample preparation and data analysis have made it difficult to confidently identify a citrullinated protein and assign the citrullinated site. To overcome these limitations, we generated a mouse hyper-citrullinated spectral library and set up coordinates to confidently identify and validate citrullinated sites. Using this workflow, we detect a four-fold increase in citrullinated proteome coverage across six mouse organs compared with the current state-of-the art techniques. Our data reveal that the subcellular distribution of citrullinated proteins is tissue-type-dependent and that citrullinated targets are involved in fundamental physiological processes, including the metabolic process. These data represent the first report of a hyper-citrullinated library for the mouse and serve as a central resource for exploring the role of citrullination in this organism.