SnakeAltPromoter Facilitates Differential Alternative Promoter Analysis

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Alternative promoter usage drives mammalian isoform diversity and gene regulation.
• Current methods like Cap Analysis of Gene Expression are costly for large-scale studies.
• RNA sequencing (RNA-seq) data offers an alternative but lacks automated, reproducible analysis frameworks.

Purpose of the Study:

• To develop a scalable, end-to-end workflow for automating alternative promoter analysis using RNA-seq data.
• To integrate and standardize multiple RNA-seq-based promoter analysis methods for reproducible results.
• To provide a framework for comparing RNA-seq-inferred promoter activity with experimental data.

Main Methods:

• Developed SnakeAltPromoter, a Snakemake workflow for automated RNA-seq data processing.
• Integrated junction-based, transcript-based, and first-exon-based quantification methods.
• Implemented quality control, alignment, promoter classification, and differential analysis modules.
• Included a benchmarking module to compare RNA-seq results with Cap Analysis of Gene Expression data.

Main Results:

• SnakeAltPromoter successfully automates alternative promoter analysis from raw RNA-seq data.
• The workflow demonstrated robust and complementary performance across different methods, tissues, and cell types.
• Benchmarking confirmed the reliability of RNA-seq-based promoter activity inference.

Conclusions:

• SnakeAltPromoter is the first unified, reproducible framework for scalable RNA-seq-based promoter analysis.
• It standardizes and integrates existing tools, offering a robust platform for studying promoter-level regulation.
• This framework enhances the utility of public RNA-seq data for alternative promoter research.