FLAME: long-read bioinformatics tool for comprehensive spliceome characterization.

Area of Science:

• Bioinformatics
• Genomics
• Molecular Biology

Background:

• Current bioinformatics tools for analyzing RNA splicing with nanopore sequencing often depend heavily on existing gene annotations, limiting their effectiveness.
• Accurate characterization of differentially spliced RNA transcripts is crucial for understanding gene regulation and disease mechanisms.

Purpose of the Study:

• To develop and present FLAME, a novel bioinformatics pipeline for comprehensive alternative splicing analysis using long-read sequencing data.
• To overcome limitations of annotation-dependent tools and enable de novo discovery of splice variants.

Main Methods:

• FLAME, a Python-based pipeline, was developed for gene-specific or transcriptome-wide analysis of long-read sequencing data.
• The pipeline quantifies full-length splice variants, identifies splice sites and exons de novo, and represents exon connectivity.
• It integrates short-read sequencing data to enhance the confidence of nanopore sequencing results.

Main Results:

• FLAME successfully characterized the spliceome of the Epstein-Barr virus long noncoding RNA RPMS1.
• All previously known splice variants of RPMS1 were detected, along with 32 novel exons.
• The novel findings included two intron retentions and a cassette exon within the RPMS1 gene.

Conclusions:

• FLAME provides a robust solution for alternative splicing analysis, particularly when reference annotations are incomplete.
• The pipeline facilitates the discovery of novel RNA splice variants and regulatory elements.
• FLAME enhances the utility of nanopore sequencing for comprehensive transcriptome analysis.