Workflow for Genome-Wide Determination of Pre-mRNA Splicing Efficiency from Yeast RNA-seq Data

Pre-mRNA splicing represents an important regulatory layer of eukaryotic gene expression. In the simple budding yeast Saccharomyces cerevisiae, about one-third of all mRNA molecules undergo splicing, and splicing efficiency is tightly regulated, for example, during meiotic differentiation. S. cerevisiae features a streamlined, evolutionarily highly conserved splicing machinery and serves as a favourite model for studies of various aspects of splicing. RNA-seq represents a robust, versatile, and affordable technique for transcriptome interrogation, which can also be used to study splicing efficiency. However, convenient bioinformatics tools for the analysis of splicing efficiency from yeast RNA-seq data are lacking.

Researchers from Charles University present a complete workflow for the calculation of genome-wide splicing efficiency in S. cerevisiae using strand-specific RNA-seq data. Their pipeline takes sequencing reads in the FASTQ format and provides splicing efficiency values for the 5′ and 3′ splice junctions of each intron. The pipeline is based on up-to-date open-source software tools and requires very limited input from the user. They provide all relevant scripts in a ready-to-use form. The researchers demonstrate the functionality of the workflow using RNA-seq datasets from three spliceosome mutants. The workflow should prove useful for studies of yeast splicing mutants or of regulated splicing, for example, under specific growth conditions.

Workflow for calculating splicing efficiency from RNA-seq data

Files and datasets are represented by blue parallelograms (file formats given in parentheses), and processing steps are represented by orange rectangles (tool names given in parentheses). Some files/datasets are used repeatedly in several steps of the workflow as signified by multiple flow lines going from these files/datasets. The diagram was created using draw.io (https://www.draw.io/).