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DNA 5-methylcytosine detection and methylation phasing using PacBio circular consensus sequencing

Author

Listed:
  • Peng Ni

    (Central South University
    Xiangjiang Laboratory
    Central South University)

  • Fan Nie

    (Central South University
    Xiangjiang Laboratory
    Central South University)

  • Zeyu Zhong

    (Central South University
    Central South University)

  • Jinrui Xu

    (Central South University
    Central South University)

  • Neng Huang

    (Central South University
    Central South University)

  • Jun Zhang

    (Central South University
    Central South University)

  • Haochen Zhao

    (Central South University
    Central South University)

  • You Zou

    (Central South University
    Central South University)

  • Yuanfeng Huang

    (Xiangya Hospital, Central South University)

  • Jinchen Li

    (Xiangya Hospital, Central South University
    Central South University)

  • Chuan-Le Xiao

    (Sun Yat-sen University)

  • Feng Luo

    (Clemson University)

  • Jianxin Wang

    (Central South University
    Xiangjiang Laboratory
    Central South University)

Abstract

Long single-molecular sequencing technologies, such as PacBio circular consensus sequencing (CCS) and nanopore sequencing, are advantageous in detecting DNA 5-methylcytosine in CpGs (5mCpGs), especially in repetitive genomic regions. However, existing methods for detecting 5mCpGs using PacBio CCS are less accurate and robust. Here, we present ccsmeth, a deep-learning method to detect DNA 5mCpGs using CCS reads. We sequence polymerase-chain-reaction treated and M.SssI-methyltransferase treated DNA of one human sample using PacBio CCS for training ccsmeth. Using long (≥10 Kb) CCS reads, ccsmeth achieves 0.90 accuracy and 0.97 Area Under the Curve on 5mCpG detection at single-molecule resolution. At the genome-wide site level, ccsmeth achieves >0.90 correlations with bisulfite sequencing and nanopore sequencing using only 10× reads. Furthermore, we develop a Nextflow pipeline, ccsmethphase, to detect haplotype-aware methylation using CCS reads, and then sequence a Chinese family trio to validate it. ccsmeth and ccsmethphase can be robust and accurate tools for detecting DNA 5-methylcytosines.

Suggested Citation

  • Peng Ni & Fan Nie & Zeyu Zhong & Jinrui Xu & Neng Huang & Jun Zhang & Haochen Zhao & You Zou & Yuanfeng Huang & Jinchen Li & Chuan-Le Xiao & Feng Luo & Jianxin Wang, 2023. "DNA 5-methylcytosine detection and methylation phasing using PacBio circular consensus sequencing," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39784-9
    DOI: 10.1038/s41467-023-39784-9
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    References listed on IDEAS

    as
    1. Zaka Wing-Sze Yuen & Akanksha Srivastava & Runa Daniel & Dennis McNevin & Cameron Jack & Eduardo Eyras, 2021. "Systematic benchmarking of tools for CpG methylation detection from nanopore sequencing," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    2. Warren A. Cheung & Adam F. Johnson & William J. Rowell & Emily Farrow & Richard Hall & Ana S. A. Cohen & John C. Means & Tricia N. Zion & Daniel M. Portik & Christopher T. Saunders & Boryana Koseva & , 2023. "Direct haplotype-resolved 5-base HiFi sequencing for genome-wide profiling of hypermethylation outliers in a rare disease cohort," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
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    Cited by:

    1. Yilei Fu & Sergey Aganezov & Medhat Mahmoud & John Beaulaurier & Sissel Juul & Todd J. Treangen & Fritz J. Sedlazeck, 2024. "MethPhaser: methylation-based long-read haplotype phasing of human genomes," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

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