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Deep learning to decode sites of RNA translation in normal and cancerous tissues

Author

Listed:
  • Jim Clauwaert

    (University of Michigan
    University of Michigan
    University of Michigan)

  • Zahra McVey

    (Novo Nordisk Research Centre Oxford, Novo Nordisk Ltd)

  • Ramneek Gupta

    (Novo Nordisk Research Centre Oxford, Novo Nordisk Ltd)

  • Ian Yannuzzi

    (Broad Institute of MIT and Harvard)

  • Venkatesha Basrur

    (University of Michigan)

  • Alexey I. Nesvizhskii

    (University of Michigan
    University of Michigan)

  • Gerben Menschaert

    (Ghent University)

  • John R. Prensner

    (University of Michigan
    University of Michigan
    University of Michigan)

Abstract

The biological process of RNA translation is fundamental to cellular life and has wide-ranging implications for human disease. Accurate delineation of RNA translation variation represents a significant challenge due to the complexity of the process and technical limitations. Here, we introduce RiboTIE, a transformer model-based approach designed to enhance the analysis of ribosome profiling data. Unlike existing methods, RiboTIE leverages raw ribosome profiling counts directly to robustly detect translated open reading frames (ORFs) with high precision and sensitivity, evaluated on a diverse set of datasets. We demonstrate that RiboTIE successfully recapitulates known findings and provides novel insights into the regulation of RNA translation in both normal brain and medulloblastoma cancer samples. Our results suggest that RiboTIE is a versatile tool that can significantly improve the accuracy and depth of Ribo-Seq data analysis, thereby advancing our understanding of protein synthesis and its implications in disease.

Suggested Citation

  • Jim Clauwaert & Zahra McVey & Ramneek Gupta & Ian Yannuzzi & Venkatesha Basrur & Alexey I. Nesvizhskii & Gerben Menschaert & John R. Prensner, 2025. "Deep learning to decode sites of RNA translation in normal and cancerous tissues," Nature Communications, Nature, vol. 16(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-56543-0
    DOI: 10.1038/s41467-025-56543-0
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    References listed on IDEAS

    as
    1. Peng Zhang & Dandan He & Yi Xu & Jiakai Hou & Bih-Fang Pan & Yunfei Wang & Tao Liu & Christel M. Davis & Erik A. Ehli & Lin Tan & Feng Zhou & Jian Hu & Yonghao Yu & Xi Chen & Tuan M. Nguyen & Jeffrey , 2017. "Genome-wide identification and differential analysis of translational initiation," Nature Communications, Nature, vol. 8(1), pages 1-14, December.
    2. Alla D. Fedorova & Stephen J. Kiniry & Dmitry E. Andreev & Jonathan M. Mudge & Pavel V. Baranov, 2024. "Addendum: Thousands of human non-AUG extended proteoforms lack evidence of evolutionary selection among mammals," Nature Communications, Nature, vol. 15(1), pages 1-1, December.
    Full references (including those not matched with items on IDEAS)

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