SpliceDecoder: A High-Throughput Tool for Guiding the Functional Interpretation of Differential Splicing Events

Area of Science:

• Molecular Biology
• Bioinformatics
• Genomics

Background:

• Alternative splicing generates diverse mRNA isoforms, crucial for protein diversity and cellular function.
• Splicing dysregulation is linked to various diseases, including cancer and neurodegeneration.
• The functional impact of most identified spliced isoforms remains largely unknown, hindering disease mechanism understanding and therapeutic development.

Purpose of the Study:

• To develop a computational workflow, SpliceDecoder, for prioritizing biologically meaningful alternative splicing events.
• To predict the impact of splicing events and isoforms on transcript productivity, protein sequence, and functional domains.
• To enable evidence-based prioritization of splicing events for biological and clinical relevance.

Main Methods:

• Developed SpliceDecoder, a computational workflow for analyzing alternative splicing.
• Implemented prediction of isoform impact on protein structure and function.
• Assigned functional effect scores to splicing events for prioritization.

Main Results:

• SpliceDecoder facilitates informed interpretation of splicing data.
• The workflow reduces reliance on prior knowledge for splicing event analysis.
• Validated known splicing alterations and identified novel disease-associated isoform switches in public datasets.

Conclusions:

• SpliceDecoder enhances the identification of functionally significant splicing events.
• The tool aids in uncovering splicing-driven disease mechanisms.
• SpliceDecoder supports the discovery of potential therapeutic targets related to alternative splicing.