A Computational Workflow for Analysis of 3′ Tag‐Seq Data

Abstract

RNA‐sequencing (RNA‐seq) is a gold‐standard method 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 and aligned to the reference genome, and then 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, and thus normalizations based on transcript length 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. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Running the 3′ Tag‐Seq workflow Support Protocol: Generating genome indices

Comparative genomics points to tandem duplications of SAD gene clusters as drivers of increased α‐linolenic (ω‐3) content in S. hispanica seeds

“…The reference genome sequences and annotations for these species were retrieved from NCBI (Sayers et al, 2021). The comparative genome analysis in this study was conducted using the compare_genomes analysis pipeline (Paril et al, 2022(Paril et al, , 2023. Protein sequences from S. hispanica and the species compared were used to define gene families or orthogroups as clusters of homologous genes using OrthoFinder v2.5.4 (Emms & Kelly, 2019).…”