DPAC: a tool for Differential Poly(A) Site usage from poly(A)–targeted RNAseq data

Abstract

Poly(A)-tail targeted RNAseq approaches, such as 3'READS, PAS-seq and Poly(A)-ClickSeq, are becoming popular alternatives to random-primed RNAseq for simplified gene expression analyses as well as to measure changes in poly(A) site usage. We and others have recently demonstrated that these approaches perform similarly to other RNAseq strategies, while saving on the volume of sequencing data required and providing a simpler library synthesis strategy. Here, we present DPAC; a streamlined pipeline for the preprocessing of poly(A)-tail targeted RNAseq data, mapping of poly(A)-sites and poly(A) clustering, and determination of differential poly(A) site usage using DESeq2. Changes in poly(A) site usage is simultaneously used to report differential gene expression, differential terminal exon usage and alternative polyadenylation (APA).

RBFOX2 is Critical for Maintaining Alternative Polyadenylation Patterns and Mitochondrial Health in Rat Myoblasts

“…DPAC (Routh, 2019b) uses DESeq2 (Love et al, 2014) to measure changes in PAC usage between control and RBFOX2 KD cells. Data processing, read mapping and poly(A)-site detection were performed using the default parameters of the Differential-Poly(A)-Clustering ( DPAC) pipeline (Routh, 2019a).…”

“…PAC-seq libraries were submitted for 1x150 single end sequencing yielding between 14 and 25 million reads per sample. The output data was processed and mapped to the Rattus norvegicus genome (rn6) and poly(A)-clusters (PACs) were generated using the DPAC pipeline (Routh, 2019b), designed for automated analysis and annotation of poly(A)-targeted RNA-seq libraries such as PAC-seq.…”

“…DPAC (version 1.16) computational pipelines (Routh, 2019b) simultaneously compare mRNA levels and poly(A)-site cluster (PAC) usage preference. In the DPAC pipeline, PACs are defined as clusters of individual PASs that are found within 10nts of one another.…”