scAPAdb: a comprehensive database of alternative polyadenylation at single-cell resolution

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Alternative polyadenylation (APA) is a key mechanism for transcript diversification in eukaryotes.
• APA plays a crucial role in regulating gene expression.
• Previous APA databases lacked single-cell resolution, limiting the study of cell-to-cell heterogeneity.

Purpose of the Study:

• To develop and present scAPAdb, a user-friendly database providing APA information at the single-cell level.
• To create a comprehensive atlas of poly(A) sites, APA events, and poly(A) signals from single-cell RNA sequencing data.
• To facilitate the study of cell-to-cell heterogeneity in APA usage and APA-mediated gene regulation.

Main Methods:

• Collected and curated APA information from over 360 single-cell RNA sequencing (scRNA-seq) experiments.
• Integrated data from multiple species, including human, mouse, and plants.
• Developed a web-based platform (http://www.bmibig.cn/scAPAdb) for data querying and download.

Main Results:

• scAPAdb provides a manually curated atlas of poly(A) sites, APA events, and poly(A) signals at single-cell resolution.
• The database covers a wide range of scRNA-seq experiments across six species.
• Users can query the database using gene identifiers, functions, or accession numbers and perform batch downloads.

Conclusions:

• scAPAdb is a valuable and extendable resource for investigating cell-to-cell heterogeneity in APA isoform usage.
• The database enables the study of APA-mediated gene regulation at the single-cell level.
• It supports research across diverse cell types, tissues, and species, advancing the understanding of eukaryotic gene expression.