A computational workflow for the analysis of 3' Tag-Seq data

RNA-sequencing (RNA-seq) is a ubiquitous tool to profile genome-wide changes in gene expression. RNA-seq uses high-throughput sequencing technology to quantify the amount of RNA in a biological sample. With the increasing popularity of RNA-seq, many variations on the protocol have been proposed to extract unique and relevant information from biological samples. 3' Tag-Seq (also called TagSeq, 3' Tag-RNA-Seq, and Quant-Seq 3' mRNA-Seq) is one RNA-seq variation, where the 3' end of the transcript is selected and amplified to yield one copy of cDNA from each transcript in the biological sample.We present a simple, easy to use, and publicly available computational workflow to analyze 3' Tag-Seq data. The workflow begins by trimming sequence adapters from raw FASTQ files. The trimmed sequence reads are checked for quality using FastQC, aligned to the reference genome, and read counts are obtained using STAR. Differential gene expression analysis is performed using DESeq2, based on differential analysis of gene count data. The outputs of this workflow are MA plots, tables of differentially expressed genes, and UpSet plots.This protocol is intended for users specifically interested in analyzing 3' Tag-Seq data. As such, transcript length-based normalizations are not performed within the workflow. Future updates to this workflow could include custom analyses based on the gene counts table as well as data visualization enhancements. Overall design: Comparative gene expression profiling of Candida albicans transcription factor TF028 mutant samples with wildtype samples.