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Barcoded multiple displacement amplification for high coverage sequencing in spatial genomics

Author

Listed:
  • Jinhyun Kim

    (Seoul National University)

  • Sungsik Kim

    (Seoul National University)

  • Huiran Yeom

    (The University of Suwon)

  • Seo Woo Song

    (Children’s Heart Center, Stanford University)

  • Kyoungseob Shin

    (Seoul National University)

  • Sangwook Bae

    (Harvard Medical School)

  • Han Suk Ryu

    (Seoul National University
    Seoul National University College of Medicine)

  • Ji Young Kim

    (Seoul National University Hospital)

  • Ahyoun Choi

    (Seoul National University)

  • Sumin Lee

    (Seoul National University
    Meteor Biotech, Co. Ltd.)

  • Taehoon Ryu

    (ATG Lifetech Inc.)

  • Yeongjae Choi

    (Gwangju Institute of Science and Technology (GIST))

  • Hamin Kim

    (Seoul National University)

  • Okju Kim

    (ATG Lifetech Inc.)

  • Yushin Jung

    (ATG Lifetech Inc.)

  • Namphil Kim

    (Seoul National University)

  • Wonshik Han

    (Seoul National University
    Seoul National University Hospital
    Seoul National University College of Medicine)

  • Han-Byoel Lee

    (Seoul National University
    Seoul National University Hospital
    Seoul National University College of Medicine)

  • Amos C. Lee

    (Seoul National University
    Meteor Biotech, Co. Ltd.)

  • Sunghoon Kwon

    (Seoul National University
    Seoul National University
    Seoul National University Hospital
    Seoul National University)

Abstract

Determining mutational landscapes in a spatial context is essential for understanding genetically heterogeneous cell microniches. Current approaches, such as Multiple Displacement Amplification (MDA), offer high genome coverage but limited multiplexing, which hinders large-scale spatial genomic studies. Here, we introduce barcoded MDA (bMDA), a technique that achieves high-coverage genomic analysis of low-input DNA while enhancing the multiplexing capabilities. By incorporating cell barcodes during MDA, bMDA streamlines library preparation in one pot, thereby overcoming a key bottleneck in spatial genomics. We apply bMDA to the integrative spatial analysis of triple-negative breast cancer tissues by examining copy number alterations, single nucleotide variations, structural variations, and kataegis signatures for each spatial microniche. This enables the assessment of subclonal evolutionary relationships within a spatial context. Therefore, bMDA has emerged as a scalable technology with the potential to advance the field of spatial genomics significantly.

Suggested Citation

  • Jinhyun Kim & Sungsik Kim & Huiran Yeom & Seo Woo Song & Kyoungseob Shin & Sangwook Bae & Han Suk Ryu & Ji Young Kim & Ahyoun Choi & Sumin Lee & Taehoon Ryu & Yeongjae Choi & Hamin Kim & Okju Kim & Yu, 2023. "Barcoded multiple displacement amplification for high coverage sequencing in spatial genomics," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41019-w
    DOI: 10.1038/s41467-023-41019-w
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    References listed on IDEAS

    as
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