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Utility of long-read sequencing for All of Us

Author

Listed:
  • M. Mahmoud

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

  • Y. Huang

    (Broad Institute of MIT and Harvard)

  • K. Garimella

    (Broad Institute of MIT and Harvard)

  • P. A. Audano

    (The Jackson Laboratory for Genomic Medicine)

  • W. Wan

    (Broad Institute of MIT and Harvard)

  • N. Prasad

    (Discovery Life Sciences)

  • R. E. Handsaker

    (Harvard Medical School
    Broad Institute of MIT and Harvard)

  • S. Hall

    (Discovery Life Sciences)

  • A. Pionzio

    (Discovery Life Sciences)

  • M. C. Schatz

    (Johns Hopkins University)

  • M. E. Talkowski

    (Broad Institute of MIT and Harvard
    Massachusetts General Hospital)

  • E. E. Eichler

    (University of Washington School of Medicine
    University of Washington)

  • S. E. Levy

    (HudsonAlpha Institute for Biotechnology)

  • F. J. Sedlazeck

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

Abstract

The All of Us (AoU) initiative aims to sequence the genomes of over one million Americans from diverse ethnic backgrounds to improve personalized medical care. In a recent technical pilot, we compare the performance of traditional short-read sequencing with long-read sequencing in a small cohort of samples from the HapMap project and two AoU control samples representing eight datasets. Our analysis reveals substantial differences in the ability of these technologies to accurately sequence complex medically relevant genes, particularly in terms of gene coverage and pathogenic variant identification. We also consider the advantages and challenges of using low coverage sequencing to increase sample numbers in large cohort analysis. Our results show that HiFi reads produce the most accurate results for both small and large variants. Further, we present a cloud-based pipeline to optimize SNV, indel and SV calling at scale for long-reads analysis. These results lead to widespread improvements across AoU.

Suggested Citation

  • M. Mahmoud & Y. Huang & K. Garimella & P. A. Audano & W. Wan & N. Prasad & R. E. Handsaker & S. Hall & A. Pionzio & M. C. Schatz & M. E. Talkowski & E. E. Eichler & S. E. Levy & F. J. Sedlazeck, 2024. "Utility of long-read sequencing for All of Us," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-44804-3
    DOI: 10.1038/s41467-024-44804-3
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    References listed on IDEAS

    as
    1. Peter Edge & Vikas Bansal, 2019. "Longshot enables accurate variant calling in diploid genomes from single-molecule long read sequencing," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    2. Daniel C. Jeffares & Clemency Jolly & Mimoza Hoti & Doug Speed & Liam Shaw & Charalampos Rallis & Francois Balloux & Christophe Dessimoz & Jürg Bähler & Fritz J. Sedlazeck, 2017. "Transient structural variations have strong effects on quantitative traits and reproductive isolation in fission yeast," Nature Communications, Nature, vol. 8(1), pages 1-11, April.
    3. Sara Reardon, 2015. "Giant study poses DNA data-sharing dilemma," Nature, Nature, vol. 525(7567), pages 16-17, September.
    4. Yunxi Liu & Joshua Kearney & Medhat Mahmoud & Bryce Kille & Fritz J. Sedlazeck & Todd J. Treangen, 2022. "Rescuing low frequency variants within intra-host viral populations directly from Oxford Nanopore sequencing data," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    Full references (including those not matched with items on IDEAS)

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