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Dynamic analyses of alternative polyadenylation from RNA-seq reveal a 3′-UTR landscape across seven tumour types

Author

Listed:
  • Zheng Xia

    (Dan L Duncan Cancer Center, Baylor College of Medicine
    Baylor College of Medicine)

  • Lawrence A. Donehower

    (Baylor College of Medicine
    Human Genome Sequencing Center, Baylor College of Medicine)

  • Thomas A. Cooper

    (Baylor College of Medicine
    Baylor College of Medicine
    Baylor College of Medicine)

  • Joel R. Neilson

    (Baylor College of Medicine)

  • David A. Wheeler

    (Human Genome Sequencing Center, Baylor College of Medicine
    Baylor College of Medicine)

  • Eric J. Wagner

    (The University of Texas Medical School at Houston)

  • Wei Li

    (Dan L Duncan Cancer Center, Baylor College of Medicine
    Baylor College of Medicine)

Abstract

Alternative polyadenylation (APA) is a pervasive mechanism in the regulation of most human genes, and its implication in diseases including cancer is only beginning to be appreciated. Since conventional APA profiling has not been widely adopted, global cancer APA studies are very limited. Here we develop a novel bioinformatics algorithm (DaPars) for the de novo identification of dynamic APAs from standard RNA-seq. When applied to 358 TCGA Pan-Cancer tumour/normal pairs across seven tumour types, DaPars reveals 1,346 genes with recurrent and tumour-specific APAs. Most APA genes (91%) have shorter 3′-untranslated regions (3′ UTRs) in tumours that can avoid microRNA-mediated repression, including glutaminase (GLS), a key metabolic enzyme for tumour proliferation. Interestingly, selected APA events add strong prognostic power beyond common clinical and molecular variables, suggesting their potential as novel prognostic biomarkers. Finally, our results implicate CstF64, an essential polyadenylation factor, as a master regulator of 3′-UTR shortening across multiple tumour types.

Suggested Citation

  • Zheng Xia & Lawrence A. Donehower & Thomas A. Cooper & Joel R. Neilson & David A. Wheeler & Eric J. Wagner & Wei Li, 2014. "Dynamic analyses of alternative polyadenylation from RNA-seq reveal a 3′-UTR landscape across seven tumour types," Nature Communications, Nature, vol. 5(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms6274
    DOI: 10.1038/ncomms6274
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    1. Hui Chen & Zeyang Wang & Lihai Gong & Qixuan Wang & Wenyan Chen & Jia Wang & Xuelian Ma & Ruofan Ding & Xing Li & Xudong Zou & Mireya Plass & Cheng Lian & Ting Ni & Gong-Hong Wei & Wei Li & Lin Deng &, 2024. "A distinct class of pan-cancer susceptibility genes revealed by an alternative polyadenylation transcriptome-wide association study," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    2. Siddharth Sethi & David Zhang & Sebastian Guelfi & Zhongbo Chen & Sonia Garcia-Ruiz & Emmanuel O. Olagbaju & Mina Ryten & Harpreet Saini & Juan A. Botia, 2022. "Leveraging omic features with F3UTER enables identification of unannotated 3’UTRs for synaptic genes," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    3. Timofey A. Karginov & Antoine Ménoret & Anthony T. Vella, 2022. "Optimal CD8+ T cell effector function requires costimulation-induced RNA-binding proteins that reprogram the transcript isoform landscape," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    4. Austin M. Gabel & Andrea E. Belleville & James D. Thomas & Siegen A. McKellar & Taylor R. Nicholas & Toshihiro Banjo & Edie I. Crosse & Robert K. Bradley, 2024. "Multiplexed screening reveals how cancer-specific alternative polyadenylation shapes tumor growth in vivo," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    5. Xiaochuan Liu & Hao Chen & Zekun Li & Xiaoxiao Yang & Wen Jin & Yuting Wang & Jian Zheng & Long Li & Chenghao Xuan & Jiapei Yuan & Yang Yang, 2024. "InPACT: a computational method for accurate characterization of intronic polyadenylation from RNA sequencing data," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    6. Seungjae Lee & Yen-Chung Chen & Austin E. Gillen & J. Matthew Taliaferro & Bart Deplancke & Hongjie Li & Eric C. Lai, 2022. "Diverse cell-specific patterns of alternative polyadenylation in Drosophila," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    7. Yange Cui & Luyang Wang & Qingbao Ding & Jihae Shin & Joel Cassel & Qin Liu & Joseph M. Salvino & Bin Tian, 2023. "Elevated pre-mRNA 3′ end processing activity in cancer cells renders vulnerability to inhibition of cleavage and polyadenylation," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
    8. Valter Bergant & Daniel Schnepf & Niklas Andrade Krätzig & Philipp Hubel & Christian Urban & Thomas Engleitner & Ronald Dijkman & Bernhard Ryffel & Katja Steiger & Percy A. Knolle & Georg Kochs & Rola, 2023. "mRNA 3’UTR lengthening by alternative polyadenylation attenuates inflammatory responses and correlates with virulence of Influenza A virus," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    9. Jie Ping & Guochong Jia & Qiuyin Cai & Xingyi Guo & Ran Tao & Christine Ambrosone & Dezheng Huo & Stefan Ambs & Mollie E. Barnard & Yu Chen & Montserrat Garcia-Closas & Jian Gu & Jennifer J. Hu & Esth, 2024. "Using genome and transcriptome data from African-ancestry female participants to identify putative breast cancer susceptibility genes," Nature Communications, Nature, vol. 15(1), pages 1-8, December.

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