scPASU: A computational protocol for quantifying polyadenylation site usage and alternative polyadenylation from 3'...

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• 3' single-cell RNA sequencing (scRNA-seq) provides polyadenylation (poly(A)) site information.
• Quantifying poly(A) site usage and alternative polyadenylation (APA) is crucial for understanding gene regulation.
• Existing methods may lack comprehensive analysis for scRNA-seq data.

Purpose of the Study:

• To present scPASU, a Snakemake workflow for analyzing poly(A) site usage and APA from 3' scRNA-seq data.
• To enable quantification of poly(A) site usage per gene and cell.
• To facilitate the discovery of novel poly(A) sites and APA events.

Main Methods:

• Development of the scPASU Snakemake workflow.
• Building a poly(A) site reference database.
• Generating a site-by-cell matrix for quantitative analysis.
• Implementing statistical tests for APA detection between cell groups.

Main Results:

• The scPASU workflow enables accurate quantification of poly(A) site usage from 3' scRNA-seq data.
• It facilitates the identification of alternative polyadenylation (APA) events across different cell populations.
• The protocol is adaptable to various organisms and sample types.

Conclusions:

• scPASU provides a robust and configurable solution for analyzing poly(A) site dynamics in single cells.
• This workflow enhances the utility of 3' scRNA-seq data for studying gene expression regulation.
• It supports the discovery of novel biological insights through poly(A) site analysis.