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IPScan: Detecting novel intronic PolyAdenylation events with RNA-seq data

  • Naima Ahmed Fahmi
  • , Sze Cheng
  • , Jeovani Overstreet
  • , Qianqian Song
  • , Jeongsik Yong
  • , Wei Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

Intronic PolyAdenylation (IPA) is an important post-transcriptional mechanism that can alter transcript coding potential by truncating translation regions, thereby increasing transcriptome and proteome diversity. This process generates novel protein isoforms with altered peptide sequences, some of which are implicated in disease progression, including cancer. Truncated proteins may lose tumor-suppressive functions, contributing to oncogenesis. Despite advancements in Alternative PolyAdenylation (APA) analysis using RNA-seq, detecting and quantifying novel IPA events remains challenging. To address this, we developed IPScan, a computational pipeline for precise IPA event identification, quantification, and visualization. IPScan has been benchmarked against existing methods using simulated data, different human and mouse cell lines, and TCGA (The Cancer Genome Atlas) breast cancer datasets. Differential IPA events under different biological conditions were quantified and validated via qPCR.

Original languageEnglish (US)
Pages (from-to)1-18
Number of pages18
JournalPLoS computational biology
Volume21
Issue number11
DOIs
StatePublished - Nov 11 2025

Bibliographical note

Publisher Copyright:
© (2025), (Public Library of Science). All rights reserved.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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