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DNA punch cards for storing data on native DNA sequences via enzymatic nicking

Author

Listed:
  • S. Kasra Tabatabaei

    (University of Illinois at Urbana-Champaign)

  • Boya Wang

    (University of Texas at Austin)

  • Nagendra Bala Murali Athreya

    (University of Illinois at Urbana-Champaign)

  • Behnam Enghiad

    (University of Illinois at Urbana-Champaign)

  • Alvaro Gonzalo Hernandez

    (University of Illinois at Urbana-Champaign)

  • Christopher J. Fields

    (University of Illinois at Urbana-Champaign)

  • Jean-Pierre Leburton

    (University of Illinois at Urbana-Champaign)

  • David Soloveichik

    (University of Texas at Austin)

  • Huimin Zhao

    (University of Illinois at Urbana-Champaign
    University of Illinois at Urbana-Champaign
    University of Illinois at Urbana-Champaign)

  • Olgica Milenkovic

    (University of Illinois at Urbana-Champaign)

Abstract

Synthetic DNA-based data storage systems have received significant attention due to the promise of ultrahigh storage density and long-term stability. However, all known platforms suffer from high cost, read-write latency and error-rates that render them noncompetitive with modern storage devices. One means to avoid the above problems is using readily available native DNA. As the sequence content of native DNA is fixed, one can modify the topology instead to encode information. Here, we introduce DNA punch cards, a macromolecular storage mechanism in which data is written in the form of nicks at predetermined positions on the backbone of native double-stranded DNA. The platform accommodates parallel nicking on orthogonal DNA fragments and enzymatic toehold creation that enables single-bit random-access and in-memory computations. We use Pyrococcus furiosus Argonaute to punch files into the PCR products of Escherichia coli genomic DNA and accurately reconstruct the encoded data through high-throughput sequencing and read alignment.

Suggested Citation

  • S. Kasra Tabatabaei & Boya Wang & Nagendra Bala Murali Athreya & Behnam Enghiad & Alvaro Gonzalo Hernandez & Christopher J. Fields & Jean-Pierre Leburton & David Soloveichik & Huimin Zhao & Olgica Mil, 2020. "DNA punch cards for storing data on native DNA sequences via enzymatic nicking," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-15588-z
    DOI: 10.1038/s41467-020-15588-z
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    Cited by:

    1. Lifu Song & Feng Geng & Zi-Yi Gong & Xin Chen & Jijun Tang & Chunye Gong & Libang Zhou & Rui Xia & Ming-Zhe Han & Jing-Yi Xu & Bing-Zhi Li & Ying-Jin Yuan, 2022. "Robust data storage in DNA by de Bruijn graph-based de novo strand assembly," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    2. Afsaneh Sadremomtaz & Robert F. Glass & Jorge Eduardo Guerrero & Dennis R. LaJeunesse & Eric A. Josephs & Reza Zadegan, 2023. "Digital data storage on DNA tape using CRISPR base editors," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    3. Chao Pan & S. Kasra Tabatabaei & S. M. Hossein Tabatabaei Yazdi & Alvaro G. Hernandez & Charles M. Schroeder & Olgica Milenkovic, 2022. "Rewritable two-dimensional DNA-based data storage with machine learning reconstruction," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    4. Cheng Kai Lim & Jing Wui Yeoh & Aurelius Andrew Kunartama & Wen Shan Yew & Chueh Loo Poh, 2023. "A biological camera that captures and stores images directly into DNA," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

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