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We proposed a data cleaning pipeline for single cell (SC) RNA-seq data, where we first screen genes (gene-wise screening) followed by screening cell libraries (library-wise screening). Gene-wise screening is based on the expectation that for a gene with a low technical noise, a gene's count in a library will tend to increase with the increase of library size, which was tested using negative binomial regression of gene count (as dependent variable) against library size (as independent variable). Library-wise screening is based on the expectation that across-library correlations for housekeeping (HK) genes is expected to be higher than the correlations for non-housekeeping (NHK) genes in those libraries with low technical noise. We removed those libraries, whose mean pairwise correlation for HK genes is NOT significantly higher than that for NHK genes. We successfully applied the pipeline to two large SC RNA-seq datasets. The pipeline was also developed into an R package. • Single cell RNA sequencing measures gene expression at level of individual cells. • Single cell RNA sequencing data normally contain a lot of technical noise. • A pipeline is proposed to clean the technical noise based on housekeeping genes. • The pipeline is based on rigorous statistical analyses that avoid arbitrary cut off. • A software program is available to implement the pipeline. [ABSTRACT FROM AUTHOR]

The relationship between Epstein Barr Virus (EBV) and miR-155 is well established. EBV infection induces miR-155 expression, which is expressed at higher levels in EBV latency type III cells compared to EBV latency type I cells. However, the mechanism by which EBV latency genes activate miR-155 expression is still unclear. Here we present data showing that DNA methylation regulates miR-155 expression. We also provide evidence that the AP1 signaling pathway is involved in EBV-mediated miR-155 activation, and that Bay11 influences signaling of the miR-155 promoter AP1 element. Lastly, we show that LMP2A, LMP1 and EBNAs cannot activate miR-155 expression alone, indicating that the regulation of miR-155 by EBV is dependent on more than one EBV gene or cell signaling pathway. We conclude that the regulation of miR-155 in EBV-positive cells occurs through multiple cell signaling processes involving EBV-mediated chromatin remodeling, cell signaling regulation and transcription factor activation. [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]