Author: Chang, Stewart T.; Thomas, Matthew J.; Sova, Pavel; Green, Richard R.; Palermo, Robert E.; Katze, Michael G.
Title: Next-Generation Sequencing of Small RNAs from HIV-Infected Cells Identifies Phased microRNA Expression Patterns and Candidate Novel microRNAs Differentially Expressed upon Infection Document date: 2013_2_5
ID: t98g8z7i_29
Snippet: During the course of infection, HIV is known to affect cellular functions at several levels. In this study, we investigated the effect of HIV infection on small RNA expression in CD4-expressing T lymphoblastoid cells. Other studies have previously used NGS to examine small RNAs in the context of HIV infection, e.g., Yeung et al. and Schopman et al. (8, 10) . However, the focus in these studies has largely been on virally encoded microRNAs rather .....
Document: During the course of infection, HIV is known to affect cellular functions at several levels. In this study, we investigated the effect of HIV infection on small RNA expression in CD4-expressing T lymphoblastoid cells. Other studies have previously used NGS to examine small RNAs in the context of HIV infection, e.g., Yeung et al. and Schopman et al. (8, 10) . However, the focus in these studies has largely been on virally encoded microRNAs rather than on cellular microRNAs. These studies typically also examine only a single time point after infection, e.g., two days postinfection in Yeung et al. and Schopman et al. (8, 10) . Other studies have profiled microRNA expression in infected patient populations, e.g., Bignami et al. (19) , but in these cases, heterogeneous mixtures of cell types served as the source material, complicating data analysis. In contrast, we have focused on the host response at the level of a single infected cell type and profiled this system over time using small RNA-Seq and other NGS-based approaches (1). To our knowledge, this study offers the first unbiased glimpse into the dynamic changes underlying the small RNA population of HIVinfected cells. The specific goals of the study were to (i) identify patterns of DE microRNA expression starting early in infection, (ii) identify anticorrelated targets of DE microRNAs, including those with low evolutionary conservation, and (iii) detect other classes of small RNA altered during infection, including candidate novel microRNAs.
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