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.

Next-generation sequencing and read mapping. All libraries were sequenced to a 54-nucleotide (nt) read length on individual lanes of a Genome Analyzer IIx (Illumina, San Diego, CA). Small RNA sequences were submitted to Geospiza (PerkinElmer, Seattle, WA) for initial analysis. Raw reads were trimmed to remove adapter sequence. Trimmed reads were aligned using Burrows-Wheeler Aligner (BWA) software against a filter reference containing rRNA, tRNA, snRNA, and mtRNA sequences (36) . The remaining reads were aligned to NCBI build 37.2 of the human genome using BWA and subsequently quantified using genomic annotations for microRNAs (miRBase 17) (7), piRNAs, and known genes (Ref-Seq gene, build 37.2) or classified as unmapped. MicroRNA read count data were obtained from Geospiza (available at http://viromics .washington.edu). By read count, we refer to the number of cDNA fragments that are sequenced and map to a particular genomic feature. Filtering was performed by requiring Õ†10 reads in all the samples of at least one condition for a given microRNA. Normalization was applied to the remaining read count data using DESeq, an R software package for testing differential expression, using R version 2.14.1 (13) . Briefly, normalization comprised calculating a size factor for each sample (as the median ratio of read counts for each feature and sample to the geometric mean of read counts for each feature across samples) and dividing all of the read counts in a particular sample by the sample size factor (13) . DE microRNAs were determined using negative binomial tests implemented in DESeq, where dispersion was estimated using a fitted, parametric curve. For comparison, data from HCMV-infected fibroblasts was obtained through the Short-Read Archive (study identifier [ID] SRP009246) (17) .