3t-seq: automatic gene expression analysis of single-copy genes, transposable elements, and tRNAs from RNA-seq data

RNA sequencing is the gold-standard method to quantify transcriptomic changes between two conditions. The overwhelming majority of data analysis methods available are focused on polyadenylated RNA transcribed from single-copy genes and overlook transcripts from repeated sequences such as transposable elements (TEs). These self-autonomous genetic elements are increasingly studied, and specialized tools designed to handle multimapping sequencing reads are available. Transfer RNAs are transcribed by RNA polymerase III and are essential for protein translation. There is a need for integrated software that is able to analyze multiple types of RNA. Here, we present 3t-seq, a Snakemake pipeline for integrated differential expression analysis of transcripts from single-copy genes, TEs, and tRNA. 3t-seq produces an accessible report and easy-to-use results for downstream analysis starting from raw sequencing data and performing quality control, genome mapping, gene expression quantification, and statistical testing. It implements three methods to quantify TEs expression and one for tRNA genes. It provides an easy-to-configure method to manage software dependencies that lets the user focus on results. 3t-seq is released under MIT license and is available at https://github.com/boulardlab/3t-seq.

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Publication Details

Journal
Briefings in Bioinformatics
Published
2024-09-23
DOI
https://doi.org/10.1093/bib/bbae467
Citations
1
Primary Topic
RNA modifications and cancer
Type
article
Field-Weighted Citation Impact
0.23

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article

3t-seq: automatic gene expression analysis of single-copy genes, transposable elements, and tRNAs from RNA-seq data

Francesco Tabaro, Matthieu Boulard
1 citations
Briefings in Bioinformatics
RNA modifications and cancer
0.23
article

3t-seq: automatic gene expression analysis of single-copy genes, transposable elements, and tRNAs from RNA-seq data

Francesco Tabaro, Matthieu Boulard
article en
1 citations

Abstract

RNA sequencing is the gold-standard method to quantify transcriptomic changes between two conditions. The overwhelming majority of data analysis methods available are focused on polyadenylated RNA transcribed from single-copy genes and overlook transcripts from repeated sequences such as transposable elements (TEs). These self-autonomous genetic elements are increasingly studied, and specialized tools designed to handle multimapping sequencing reads are available. Transfer RNAs are transcribed by RNA polymerase III and are essential for protein translation. There is a need for integrated software that is able to analyze multiple types of RNA. Here, we present 3t-seq, a Snakemake pipeline for integrated differential expression analysis of transcripts from single-copy genes, TEs, and tRNA. 3t-seq produces an accessible report and easy-to-use results for downstream analysis starting from raw sequencing data and performing quality control, genome mapping, gene expression quantification, and statistical testing. It implements three methods to quantify TEs expression and one for tRNA genes. It provides an easy-to-configure method to manage software dependencies that lets the user focus on results. 3t-seq is released under MIT license and is available at https://github.com/boulardlab/3t-seq.

Briefings in BioinformaticsVol. 25(6)
European Molecular Biology Laboratory (IT)
European Molecular Biology Laboratory
Openalex Percentile: Top 42%
RNA modifications and cancer
0.23
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