Next-Generation Sequencing of Small RNAs from HIV-Infected Cells Identifies Phased microRNA Expression Patterns and Candidate Novel microRNAs Differentially Expressed upon Infection

Chang, Stewart T.; Thomas, Matthew J.; Sova, Pavel; Green, Richard R.; Palermo, Robert E.; Katze, Michael G.

Integrative analysis of small RNA-Seq and mRNA-Seq data. To integrate microRNA and mRNA data, we generated target predictions from three prediction algorithms-TargetScan (37), PITA (38) , and Miranda (39)-accessed through the MAGIA website (40) . We obtained mRNA data from previous mRNA-Seq analysis of the same 12-and 24-hpi HIVand mock-infected samples used to derive the small RNA-Seq data set 1. mRNA data were represented as log 2 fragments per kilobase of exon per million mapped fragments (FPKM) in each replicate and identified by Entrez gene IDs as accessed via Biomart in Bioconductor (41) . MicroRNA data were represented as log 2 DESeq-normalized counts with miRBase 17 IDs. For each predicted microRNA-mRNA pairing, we calculated a Pearson correlation coefficient as well as a Benjamini-Hochberg-adjusted P value. Significant interactions were identified by negative correlation coefficients associated with adjusted P values of Ͻ0.05. These interactions were used to generate networks in Cytoscape (42) .