ScanExitronLR: characterization and quantification of exitron splicing events in long-read RNA-seq data

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Exitron splicing, where coding sequences are removed, increases proteome diversity and is implicated in cancer.
• Long-read RNA sequencing is ideal for studying alternative splicing, but lacks specific tools for exitron analysis.

Purpose of the Study:

• To develop and present ScanExitronLR, a novel application for characterizing and quantifying exitron splicing events in long-read RNA-seq data.
• To provide a tool for downstream analysis of differential exitron splicing and annotation of exitron features.

Main Methods:

• ScanExitronLR processes BAM alignment files, reference genomes, and gene annotations.
• It outputs exitron events at the transcript level and can report annotations like truncation, frameshift, and NMD status.

Main Results:

• ScanExitronLR effectively characterizes and quantifies exitron splicing events from long-read RNA-seq data.
• The tool demonstrates superior performance on noisy long-reads compared to existing short-read exitron detection algorithms.

Conclusions:

• ScanExitronLR is a valuable new resource for the comprehensive analysis of exitron splicing using long-read RNA-seq.
• This tool will advance research into the role of exitrons in proteome plasticity and diseases like cancer.