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Our appreciation for the extent of Epstein Barr virus (EBV) transcriptome complexity continues to grow through findings of EBV encoded microRNAs, new long non-coding RNAs as well as the more recent discovery of over a hundred new polyadenylated lytic transcripts. Here we report an additional layer to the EBV transcriptome through the identification of a repertoire of latent and lytic viral circular RNAs. Utilizing RNase R-sequencing with cell models representing latency types I, II, and III, we identified EBV encoded circular RNAs expressed from the latency Cp promoter involving backsplicing from the W1 and W2 exons to the C1 exon, from the EBNA BamHI U fragment exon, and from the latency long non-coding RPMS1 locus. In addition, we identified circular RNAs expressed during reactivation including backsplicing from exon 8 to exon 2 of the LMP2 gene and a highly expressed circular RNA derived from intra-exonic backsplicing within the BHLF1 gene. While expression of most of these circular RNAs was found to depend on the EBV transcriptional program utilized and the transcription levels of the associated loci, expression of LMP2 exon 8 to exon 2 circular RNA was found to be cell model specific. Altogether we identified over 30 unique EBV circRNAs candidates and we validated and determined the structural features, expression profiles and nuclear/cytoplasmic distributions of several predominant and notable viral circRNAs. Further, we show that two of the EBV circular RNAs derived from the RPMS1 locus are detected in EBV positive clinical stomach cancer specimens. This study increases the known EBV latency and lytic transcriptome repertoires to include viral circular RNAs and it provides an essential foundation and resource for investigations into the functions and roles of this new class of EBV transcripts in EBV biology and diseases. [ABSTRACT FROM AUTHOR]

High-throughput RNA sequencing (RNA-seq) has become an instrumental assay for the analysis of multiple aspects of an organism's transcriptome. Further, the analysis of a biological specimen's associated microbiome can also be performed using RNA-seq data and this application is gaining interest in the scientific community. There are many existing bioinformatics tools designed for analysis and visualization of transcriptome data. Despite the availability of an array of next generation sequencing (NGS) analysis tools, the analysis of RNA-seq data sets poses a challenge for many biomedical researchers who are not familiar with command-line tools. Here we present RNA CoMPASS, a comprehensive RNA-seq analysis pipeline for the simultaneous analysis of transcriptomes and metatranscriptomes from diverse biological specimens. RNA CoMPASS leverages existing tools and parallel computing technology to facilitate the analysis of even very large datasets. RNA CoMPASS has a web-based graphical user interface with intrinsic queuing to control a distributed computational pipeline. RNA CoMPASS was evaluated by analyzing RNA-seq data sets from 45 B-cell samples. Twenty-two of these samples were derived from lymphoblastoid cell lines (LCLs) generated by the infection of naïve B-cells with the Epstein Barr virus (EBV), while another 23 samples were derived from Burkitt's lymphomas (BL), some of which arose in part through infection with EBV. Appropriately, RNA CoMPASS identified EBV in all LCLs and in a fraction of the BLs. Cluster analysis of the human transcriptome component of the RNA CoMPASS output clearly separated the BLs (which have a germinal center-like phenotype) from the LCLs (which have a blast-like phenotype) with evidence of activated MYC signaling and lower interferon and NF-kB signaling in the BLs. Together, this analysis illustrates the utility of RNA CoMPASS in the simultaneous analysis of transcriptome and metatranscriptome data. RNA CoMPASS is freely available at http://rnacompass.sourceforge.net/. [ABSTRACT FROM AUTHOR]

Single-nucleotide polymorphisms (SNPs) contribute to the between-individual expression variation of many genes. A regulatory (trait-associated) SNP is usually located near or within a (host) gene, possibly influencing the gene’s transcription or/and post-transcriptional modification. But its targets may also include genes that are physically farther away from it. A heuristic explanation of such multiple-target interferences is that the host gene transfers the SNP genotypic effects to the distant gene(s) by a transcriptional or signaling cascade. These connections between the host genes (regulators) and the distant genes (targets) make the genetic analysis of gene expression traits a promising approach for identifying unknown regulatory relationships. In this study, through a mixed model analysis of multi-source digital expression profiling for 140 human lymphocyte cell lines (LCLs) and the genotypes distributed by the international HapMap project, we identified 45 thousands of potential SNP-induced regulatory relationships among genes (the significance level for the underlying associations between expression traits and SNP genotypes was set at FDR < 0.01). We grouped the identified relationships into four classes (paradigms) according to the two different mechanisms by which the regulatory SNPs affect their cis- and trans- regulated genes, modifying mRNA level or altering transcript splicing patterns. We further organized the relationships in each class into a set of network modules with the cis- regulated genes as hubs. We found that the target genes in a network module were often characterized by significant functional similarity, and the distributions of the target genes in three out of the four networks roughly resemble a power-law, a typical pattern of gene networks obtained from mutation experiments. By two case studies, we also demonstrated that significant biological insights can be inferred from the identified network modules. [ABSTRACT FROM AUTHOR]

Epstein-Barr virus (EBV) is associated with roughly 10% of gastric carcinomas worldwide (EBVaGC). Although previous investigations provide a strong link between EBV and gastric carcinomas, these studies were performed using selected EBV gene probes. Using a cohort of gastric carcinoma RNA-seq data sets from The Cancer Genome Atlas (TCGA), we performed a quantitative and global assessment of EBV gene expression in gastric carcinomas and assessed EBV associated cellular pathway alterations. EBV transcripts were detected in 17% of samples but these samples varied significantly in EBV coverage depth. In four samples with the highest EBV coverage (hiEBVaGC – high EBV associated gastric carcinoma), transcripts from the BamHI A region comprised the majority of EBV reads. Expression of LMP2, and to a lesser extent, LMP1 were also observed as was evidence of abortive lytic replication. Analysis of cellular gene expression indicated significant immune cell infiltration and a predominant IFNG response in samples expressing high levels of EBV transcripts relative to samples expressing low or no EBV transcripts. Despite the apparent immune cell infiltration, high levels of the cytotoxic T-cell (CTL) and natural killer (NK) cell inhibitor, IDO1, was observed in the hiEBVaGCs samples suggesting an active tolerance inducing pathway in this subgroup. These results were confirmed in a separate cohort of 21 Vietnamese gastric carcinoma samples using qRT-PCR and on tissue samples using in situ hybridization and immunohistochemistry. Lastly, a panel of tumor suppressors and candidate oncogenes were expressed at lower levels in hiEBVaGC versus EBV-low and EBV-negative gastric cancers suggesting the direct regulation of tumor pathways by EBV. [ABSTRACT FROM AUTHOR]

Recent studies have shown the contribution of miRNAs to cancer pathogenesis. Prostate cancer is the most commonly diagnosed cancer in men. Unlike other major types of cancer, no single gene has been identified as being mutated in the majority of prostate tumors. This implies that the expression profiling of genes, including the non-coding miRNAs, may substantially vary across individual cases of this cancer. The within-class variability makes it possible to reconstruct or infer disease-specific miRNA-mRNA correlation and regulatory modular networks using high-dimensional microarray data of prostate tumor samples. Furthermore, since miRNAs and tumor suppressor genes are usually tissue specific, miRNA-mRNA modules could potentially differ between primary prostate cancer (PPC) and metastatic prostate cancer (MPC). We herein performed an in silico analysis to explore the miRNA-mRNA correlation network modules in the two tumor subtypes. Our analysis identified 5 miRNA-mRNA module pairs (MPs) for PPC and MPC, respectively. Each MP includes one positiveconnection (correlation) module and one negative-connection (correlation) module. The number of miRNAs or mRNAs (genes) in each module varies from 2 to 8 or from 6 to 622. The modules discovered for PPC are more informative than those for MPC in terms of the implicated biological insights. In particular, one negative-connection module in PPC fits well with the popularly recognized miRNA-mediated post-transcriptional regulation theory. That is, the 3'UTR sequences of the involved mRNAs (∼620) are enriched with the target site motifs of the 7 modular miRNAs, has-miR-106b, -191, -19b, -92a, - 92b, -93, and -141. About 330 GO terms and KEGG pathways, including TGF-beta signaling pathway that maintains tissue homeostasis and plays a crucial role in the suppression of the proliferation of cancer cells, are over-represented (adj.p<0.05) in the modular gene list. These computationally identified modules provide remarkable biological evidence for the interference of miRNAs in the development of prostate cancers and warrant additional follow-up in independent laboratory studies. [ABSTRACT FROM AUTHOR]

In metazoans, miRNAs regulate gene expression primarily through binding to target sites in the 39 UTRs (untranslated regions) of messenger RNAs (mRNAs). Cis-acting variants within, or close to, a gene are crucial in explaining the variability of gene expression measures. Single nucleotide polymorphisms (SNPs) in the 39 UTRs of genes can affect the base-pairing between miRNAs and mRNAs, and hence disrupt existing target sites (in the reference sequence) or create novel target sites, suggesting a possible mechanism for cis regulation of gene expression. Moreover, because the alleles of different SNPs within a DNA sequence of limited length tend to be in strong linkage disequilibrium (LD), we hypothesize the variants of miRNA target sites caused by SNPs potentially function as bridges linking the documented cis-SNP markers to the expression of the associated genes. A large-scale analysis was herein performed to test this hypothesis. By systematically integrating multiple latest information sources, we found 21 significant gene-level SNP-involved miRNA-mediated posttranscriptional regulation modules (SNP-MPRMs) in the form of SNP-miRNA-mRNA triplets in lymphocyte cell lines for the CEU and YRI populations. Among the cognate genes, six including ALG8, DGKE, GNA12, KLF11, LRPAP1, and MMAB are related to multiple genetic diseases such as depressive disorder and Type-II diabetes. Furthermore, we found that ∼35% of the documented transcript intensity-related cis-SNPs (∼950) in a recent publication are identical to, or in significant linkage disequilibrium (LD) (p<0.01) with, one or multiple SNPs located in miRNA target sites. Based on these associations (or identities), 69 significant exon-level SNP-MPRMs and 12 disease genes were further determined for two populations. These results provide concrete in silico evidence for the proposed hypothesis. The discovered modules warrant additional followup in independent laboratory studies. [ABSTRACT FROM AUTHOR]