AS-Quant: Detection and Visualization of Alternative Splicing Events with RNA-seq Data

Area of Science:

• Genomics and Bioinformatics
• Molecular Biology
• Computational Biology

Background:

• The central dogma's simplicity doesn't explain the genome-proteome complexity.
• Alternative splicing is a key post-transcriptional mechanism driving proteome diversity.
• RNA-sequencing (RNA-seq) is vital for transcriptome analysis but lacks user-friendly tools for alternative splicing detection.

Purpose of the Study:

• To introduce AS-Quant, a robust bioinformatics program for genome-wide alternative splicing event identification and visualization.
• To provide a user-friendly tool for analyzing alternative splicing from RNA-seq data.
• To enhance the understanding of gene expression regulation through alternative splicing.

Main Methods:

• AS-Quant calculates exon and gene read coverage from RNA-seq data.
• It categorizes splicing events, assesses their significance between conditions, and generates visualization plots.
• The tool was evaluated using simulated and real RNA-seq datasets against existing methods.

Main Results:

• AS-Quant demonstrates superior performance in detecting alternative splicing events compared to SUPPA2, rMATS, and diffSplice.
• The tool successfully visualizes splicing events with short-read coverage plots and gene annotations.
• Key alternative splicing events identified by AS-Quant were validated using RT-PCR.

Conclusions:

• AS-Quant is an effective and user-friendly tool for alternative splicing analysis.
• The program aids in the genome-wide detection and visualization of alternative splicing events.
• AS-Quant contributes to a deeper understanding of gene expression regulation and proteome complexity.