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

Journal: Genomics, proteomics & bioinformatics
Published Date: Jun 26, 2026

Abstract

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/.

Authors

  • Pei-Hong Zhang
    Center for Molecular Medicine, Children's Hospital of Fudan University and Shanghai Key Laboratory of Medical Epigenetics, International Laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China.
  • Hua Feng
    Clinical Epidemiology and Comparative Effectiveness Program, Center for Innovations in Quality, Effectiveness and Safety, Michael E. Debakey VA Medical Center, John P. McGovern Campus, 2450 Holcombe Blvd., Suite 01Y, Houston, TX, 77021, USA.
  • Xu-Kai Ma
    Center for Molecular Medicine, Children's Hospital of Fudan University and Shanghai Key Laboratory of Medical Epigenetics, International Laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China.
  • Fang Nan
    CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
  • Li Yang
    Department of Pharmacy, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.

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