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Integrated analysis of genomic and transcriptomic data for the discovery of splice-associated variants in cancer

Author

Listed:
  • Kelsy C. Cotto

    (Washington University School of Medicine
    Washington University School of Medicine)

  • Yang-Yang Feng

    (Washington University School of Medicine)

  • Avinash Ramu

    (Washington University School of Medicine)

  • Megan Richters

    (Washington University School of Medicine
    Washington University School of Medicine)

  • Sharon L. Freshour

    (Washington University School of Medicine
    Washington University School of Medicine)

  • Zachary L. Skidmore

    (Washington University School of Medicine
    Washington University School of Medicine)

  • Huiming Xia

    (Washington University School of Medicine
    Washington University School of Medicine)

  • Joshua F. McMichael

    (Washington University School of Medicine)

  • Jason Kunisaki

    (Washington University School of Medicine)

  • Katie M. Campbell

    (Washington University School of Medicine)

  • Timothy Hung-Po Chen

    (Washington University School of Medicine)

  • Emily B. Rozycki

    (Washington University School of Medicine)

  • Douglas Adkins

    (Washington University School of Medicine)

  • Siddhartha Devarakonda

    (Washington University School of Medicine)

  • Sumithra Sankararaman

    (Washington University School of Medicine)

  • Yiing Lin

    (Washington University School of Medicine)

  • William C. Chapman

    (Washington University School of Medicine)

  • Christopher A. Maher

    (Washington University School of Medicine)

  • Vivek Arora

    (Washington University School of Medicine)

  • Gavin P. Dunn

    (Mass General Hospital
    Mass General Hospital)

  • Ravindra Uppaluri

    (Brigham and Women’s Hospital
    Dana-Farber Cancer Institute)

  • Ramaswamy Govindan

    (Washington University School of Medicine
    Washington University School of Medicine)

  • Obi L. Griffith

    (Washington University School of Medicine
    Washington University School of Medicine
    Washington University School of Medicine
    Washington University School of Medicine)

  • Malachi Griffith

    (Washington University School of Medicine
    Washington University School of Medicine
    Washington University School of Medicine
    Washington University School of Medicine)

Abstract

Somatic mutations within non-coding regions and even exons may have unidentified regulatory consequences that are often overlooked in analysis workflows. Here we present RegTools ( www.regtools.org ), a computationally efficient, free, and open-source software package designed to integrate somatic variants from genomic data with splice junctions from bulk or single cell transcriptomic data to identify variants that may cause aberrant splicing. We apply RegTools to over 9000 tumor samples with both tumor DNA and RNA sequence data. RegTools discovers 235,778 events where a splice-associated variant significantly increases the splicing of a particular junction, across 158,200 unique variants and 131,212 unique junctions. To characterize these somatic variants and their associated splice isoforms, we annotate them with the Variant Effect Predictor, SpliceAI, and Genotype-Tissue Expression junction counts and compare our results to other tools that integrate genomic and transcriptomic data. While many events are corroborated by the aforementioned tools, the flexibility of RegTools also allows us to identify splice-associated variants in known cancer drivers, such as TP53, CDKN2A, and B2M, and other genes.

Suggested Citation

  • Kelsy C. Cotto & Yang-Yang Feng & Avinash Ramu & Megan Richters & Sharon L. Freshour & Zachary L. Skidmore & Huiming Xia & Joshua F. McMichael & Jason Kunisaki & Katie M. Campbell & Timothy Hung-Po Ch, 2023. "Integrated analysis of genomic and transcriptomic data for the discovery of splice-associated variants in cancer," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-37266-6
    DOI: 10.1038/s41467-023-37266-6
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    References listed on IDEAS

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    2. Xena Marie Mapel & Naveen Kumar Kadri & Alexander S. Leonard & Qiongyu He & Audald Lloret-Villas & Meenu Bhati & Maya Hiltpold & Hubert Pausch, 2024. "Molecular quantitative trait loci in reproductive tissues impact male fertility in cattle," Nature Communications, Nature, vol. 15(1), pages 1-15, December.

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