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A digital twin for DNA data storage based on comprehensive quantification of errors and biases

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  • Andreas L. Gimpel

    (ETH Zürich)

  • Wendelin J. Stark

    (ETH Zürich)

  • Reinhard Heckel

    (Technical University of Munich)

  • Robert N. Grass

    (ETH Zürich)

Abstract

Archiving data in synthetic DNA offers unprecedented storage density and longevity. Handling and storage introduce errors and biases into DNA-based storage systems, necessitating the use of Error Correction Coding (ECC) which comes at the cost of added redundancy. However, insufficient data on these errors and biases, as well as a lack of modeling tools, limit data-driven ECC development and experimental design. In this study, we present a comprehensive characterisation of the error sources and biases present in the most common DNA data storage workflows, including commercial DNA synthesis, PCR, decay by accelerated aging, and sequencing-by-synthesis. Using the data from 40 sequencing experiments, we build a digital twin of the DNA data storage process, capable of simulating state-of-the-art workflows and reproducing their experimental results. We showcase the digital twin’s ability to replace experiments and rationalize the design of redundancy in two case studies, highlighting opportunities for tangible cost savings and data-driven ECC development.

Suggested Citation

  • Andreas L. Gimpel & Wendelin J. Stark & Reinhard Heckel & Robert N. Grass, 2023. "A digital twin for DNA data storage based on comprehensive quantification of errors and biases," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41729-1
    DOI: 10.1038/s41467-023-41729-1
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    References listed on IDEAS

    as
    1. Randolph Lopez & Yuan-Jyue Chen & Siena Dumas Ang & Sergey Yekhanin & Konstantin Makarychev & Miklos Z Racz & Georg Seelig & Karin Strauss & Luis Ceze, 2019. "DNA assembly for nanopore data storage readout," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    2. Philipp L. Antkowiak & Jory Lietard & Mohammad Zalbagi Darestani & Mark M. Somoza & Wendelin J. Stark & Reinhard Heckel & Robert N. Grass, 2020. "Low cost DNA data storage using photolithographic synthesis and advanced information reconstruction and error correction," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    3. Yuan-Jyue Chen & Christopher N. Takahashi & Lee Organick & Callista Bee & Siena Dumas Ang & Patrick Weiss & Bill Peck & Georg Seelig & Luis Ceze & Karin Strauss, 2020. "Quantifying molecular bias in DNA data storage," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    Full references (including those not matched with items on IDEAS)

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