PASSpedia: A Polyadenylation Site Database Across Different Species at Single-cell Resolution

Polyadenylation site (PAS) selection plays important roles in gene expression regulation and function. RNA sequencing (RNA-seq) data derived from 3' tag sequencing contain intrinsic information about PAS usage and have been analyzed for alternative polyadenylation (APA) isoform expression in both bulk and single-cell samples. Here, we upgraded our previously developed deep learning-based PAS analysis pipeline SCAPTURE v2 to profile PASs from 1330 published 3' tag-based single-cell RNA-seq (scRNA-seq) datasets across seven species, resulting in a comprehensive PAS landscape across species. Validation with long-read sequencing data from matched human tissues showed high accuracy of single-cell PAS profiling by SCAPTURE, including previously unannotated ones. Further comparisons revealed distinct PAS usage preferences in different species, such as human versus mouse, independent of conservation of gene expression. Finally, we present PASSpedia, a comprehensive database for PAS analysis and comparison across seven species at single-cell resolution, which is freely accessible online at https://bits.fudan.edu.cn/PASSpedia/.