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High-coverage allele-resolved single-cell DNA methylation profiling reveals cell lineage, X-inactivation state, and replication dynamics

Author

Listed:
  • Nathan J. Spix

    (Van Andel Institute)

  • Walid Abi Habib

    (Van Andel Institute
    Takara Bio Europe)

  • Zhouwei Zhang

    (Van Andel Institute
    McKinsey & Company)

  • Emily Eugster

    (Van Andel Institute)

  • Hsiao-yun Milliron

    (Van Andel Institute)

  • David Sokol

    (Van Andel Institute)

  • KwangHo Lee

    (Van Andel Institute)

  • Paula A. Nolte

    (Van Andel Institute)

  • Jamie L. Endicott

    (Van Andel Institute
    Altos Labs)

  • Kelly F. Krzyzanowski

    (Van Andel Institute)

  • Toshinori Hinoue

    (Van Andel Institute)

  • Jacob Morrison

    (Van Andel Institute)

  • Benjamin K. Johnson

    (Van Andel Institute)

  • Wanding Zhou

    (Van Andel Institute
    University of Pennsylvania)

  • Hui Shen

    (Van Andel Institute)

  • Peter W. Laird

    (Van Andel Institute)

Abstract

DNA methylation patterns at crucial short sequence features, such as enhancers and promoters, may convey key information about cell lineage and state. The need for high-resolution single-cell DNA methylation profiling has therefore become increasingly apparent. Existing single-cell whole-genome bisulfite sequencing (scWGBS) studies have both methodological and analytical shortcomings. Inefficient library generation and low CpG coverage mostly preclude direct cell-to-cell comparisons and necessitate the use of cluster-based analyses, imputation of methylation states, or averaging of DNA methylation measurements across large genomic bins. Such summarization methods obscure the interpretation of methylation states at individual regulatory elements and limit our ability to discern important cell-to-cell differences. We report an improved scWGBS method, single-cell Deep and Efficient Epigenomic Profiling of methyl-C (scDEEP-mC), which offers efficient generation of high-coverage libraries. scDEEP-mC allows for cell type identification, genome-wide profiling of hemi-methylation, and allele-resolved analysis of X-inactivation epigenetics in single cells. Furthermore, we combine methylation and copy-number data from scDEEP-mC to identify single, actively replicating cells and profile DNA methylation maintenance dynamics during and after DNA replication. These analyses unlock further avenues for exploring DNA methylation regulation and dynamics and illustrate the power of high-complexity, highly efficient scWGBS library construction as facilitated by scDEEP-mC.

Suggested Citation

  • Nathan J. Spix & Walid Abi Habib & Zhouwei Zhang & Emily Eugster & Hsiao-yun Milliron & David Sokol & KwangHo Lee & Paula A. Nolte & Jamie L. Endicott & Kelly F. Krzyzanowski & Toshinori Hinoue & Jaco, 2025. "High-coverage allele-resolved single-cell DNA methylation profiling reveals cell lineage, X-inactivation state, and replication dynamics," Nature Communications, Nature, vol. 16(1), pages 1-17, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-61589-1
    DOI: 10.1038/s41467-025-61589-1
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    References listed on IDEAS

    as
    1. Vishnu Dileep & David M. Gilbert, 2018. "Single-cell replication profiling to measure stochastic variation in mammalian replication timing," Nature Communications, Nature, vol. 9(1), pages 1-8, December.
    2. Netanel Loyfer & Judith Magenheim & Ayelet Peretz & Gordon Cann & Joerg Bredno & Agnes Klochendler & Ilana Fox-Fisher & Sapir Shabi-Porat & Merav Hecht & Tsuria Pelet & Joshua Moss & Zeina Drawshy & H, 2023. "A DNA methylation atlas of normal human cell types," Nature, Nature, vol. 613(7943), pages 355-364, January.
    3. Jamie L. Endicott & Paula A. Nolte & Hui Shen & Peter W. Laird, 2022. "Cell division drives DNA methylation loss in late-replicating domains in primary human cells," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    4. Ludovica Vanzan & Hadrien Soldati & Victor Ythier & Santosh Anand & Simon M. G. Braun & Nicole Francis & Rabih Murr, 2021. "High throughput screening identifies SOX2 as a super pioneer factor that inhibits DNA methylation maintenance at its binding sites," Nature Communications, Nature, vol. 12(1), pages 1-18, December.
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