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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]

Cancer develops and progresses often by inactivating p53. Here, we unveil nerve growth factor receptor (NGFR, p75NTR or CD271) as a novel p53 inactivator. p53 activates NGFR transcription, whereas NGFR inactivates p53 by promoting its MDM2-mediated ubiquitindependent proteolysis and by directly binding to its central DNA binding domain and preventing its DNA-binding activity. Inversely, NGFR ablation activates p53, consequently inducing apoptosis, attenuating survival, and reducing clonogenic capability of cancer cells, as well as sensitizing human cancer cells to chemotherapeutic agents that induce p53 and suppressing mouse xenograft tumor growth. NGFR is highly expressed in human glioblastomas, and its gene is often amplified in breast cancers with wild type p53. Altogether, our results demonstrate that cancers hijack NGFR as an oncogenic inhibitor of p53. [ABSTRACT FROM AUTHOR]

Summary Dysregulation of MLL complex-mediated histone methylation plays a pivotal role in gene expression associated with diseases, but little is known about cellular factors modulating MLL complex activity. Here, we report that SON, previously known as an RNA splicing factor, controls MLL complex-mediated transcriptional initiation. SON binds to DNA near transcription start sites, interacts with menin, and inhibits MLL complex assembly, resulting in decreased H3K4me3 and transcriptional repression. Importantly, alternatively spliced short isoforms of SON are markedly upregulated in acute myeloid leukemia. The short isoforms compete with full-length SON for chromatin occupancy but lack the menin-binding ability, thereby antagonizing full-length SON function in transcriptional repression while not impairing full-length SON-mediated RNA splicing. Furthermore, overexpression of a short isoform of SON enhances replating potential of hematopoietic progenitors. Our findings define SON as a fine-tuner of the MLL-menin interaction and reveal short SON overexpression as a marker indicating aberrant transcriptional initiation in leukemia. [ABSTRACT FROM AUTHOR]

Abstract: The Epstein–Barr virus (EBV) is associated with lymphoid and epithelial cancers. Initial EBV infection alters lymphocyte gene expression, inducing cellular proliferation and differentiation as the virus transitions through consecutive latency transcription programs. Cellular microRNAs (miRNAs) are important regulators of signaling pathways and are implicated in carcinogenesis. The extent to which EBV exploits cellular miRNAs is unknown. Using micro-array analysis and quantitative PCR, we demonstrate differential expression of cellular miRNAs in type III versus type I EBV latency including elevated expression of miR-21, miR-23a, miR-24, miR-27a, miR-34a, miR-146a and b, and miR-155. In contrast, miR-28 expression was found to be lower in type III latency. The EBV-mediated regulation of cellular miRNAs may contribute to EBV signaling and associated cancers. [Copyright &y& Elsevier]