QuantSeq FWD and QuantSeq REV using RNA samples from mouse NIH3T3 cells

Most eukaryotic genes harbor multiple cleavage and polyadenylation sites (PASs), leading to expression of alternative polyadenylation (APA) isoforms. APA regulation has been implicated in a diverse array of physiological and pathological conditions. While RNA sequencing tools that generate reads containing the PAS, named onSite reads, have been instrumental in identifying PASs, they have not been widely used. By contrast, a growing number of methods generate reads that are close to the PAS, named nearSite reads, including the 3' end counting strategy commonly used in single cell analysis. How these nearSite reads can be used for APA analysis, however, is poorly studied. Here, we present a computational method, named model-based analysis of alternative polyadenylation using 3' end-linked reads (MAAPER), to examine APA using nearSite reads. MAAPER uses a probabilistic model to predict PASs for nearSite reads with high accuracy and sensitivity, and examines different types of APA events, including those in 3'UTRs and introns, with robust statistics. We show usability of MAAPER with data from bulk RNA and single cell samples. Our result also highlights the importance of using well annotated PASs for nearSite read analysis. Overall design: QuantSeq FWD and QuantSeq REV libraries using RNA samples from nontreated mouse NIH3T3 cells (NT), NIH3T3 cells treated with arsenite stress for 1 hour (AS), and NIH3T3 cells that have recovered from AS treatment for 4 or 8 hours (RC4 or RC8).