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Parallel molecular data storage by printing epigenetic bits on DNA

Author

Listed:
  • Cheng Zhang

    (Key Laboratory of High Confidence Software Technologies, Peking University)

  • Ranfeng Wu

    (Key Laboratory of High Confidence Software Technologies, Peking University)

  • Fajia Sun

    (Peking University)

  • Yisheng Lin

    (Key Laboratory of High Confidence Software Technologies, Peking University)

  • Yuan Liang

    (Key Laboratory of High Confidence Software Technologies, Peking University
    North China Electric Power University)

  • Jiongjiong Teng

    (North China Electric Power University)

  • Na Liu

    (University of Stuttgart
    Max Planck Institute for Solid State Research)

  • Qi Ouyang

    (Peking University)

  • Long Qian

    (Peking University)

  • Hao Yan

    (Biodesign Institute, Arizona State University
    Arizona State University)

Abstract

DNA storage has shown potential to transcend current silicon-based data storage technologies in storage density, longevity and energy consumption1–3. However, writing large-scale data directly into DNA sequences by de novo synthesis remains uneconomical in time and cost4. We present an alternative, parallel strategy that enables the writing of arbitrary data on DNA using premade nucleic acids. Through self-assembly guided enzymatic methylation, epigenetic modifications, as information bits, can be introduced precisely onto universal DNA templates to enact molecular movable-type printing. By programming with a finite set of 700 DNA movable types and five templates, we achieved the synthesis-free writing of approximately 275,000 bits on an automated platform with 350 bits written per reaction. The data encoded in complex epigenetic patterns were retrieved high-throughput by nanopore sequencing, and algorithms were developed to finely resolve 240 modification patterns per sequencing reaction. With the epigenetic information bits framework, distributed and bespoke DNA storage was implemented by 60 volunteers lacking professional biolab experience. Our framework presents a new modality of DNA data storage that is parallel, programmable, stable and scalable. Such an unconventional modality opens up avenues towards practical data storage and dual-mode data functions in biomolecular systems.

Suggested Citation

  • Cheng Zhang & Ranfeng Wu & Fajia Sun & Yisheng Lin & Yuan Liang & Jiongjiong Teng & Na Liu & Qi Ouyang & Long Qian & Hao Yan, 2024. "Parallel molecular data storage by printing epigenetic bits on DNA," Nature, Nature, vol. 634(8035), pages 824-832, October.
  • Handle: RePEc:nat:nature:v:634:y:2024:i:8035:d:10.1038_s41586-024-08040-5
    DOI: 10.1038/s41586-024-08040-5
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