Robust data storage in DNA by de Bruijn graph-based de novo strand assembly

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 () and Ying-Jin Yuan ()
Additional contact information
Lifu Song: Tianjin University
Feng Geng: Binzhou Medical University
Zi-Yi Gong: Tianjin University
Xin Chen: Tianjin University
Jijun Tang: Tianjin University
Chunye Gong: National SuperComputer Center in Tianjin
Libang Zhou: Nanjing Agricultural University
Rui Xia: National SuperComputer Center in Tianjin
Ming-Zhe Han: Tianjin University
Jing-Yi Xu: Tianjin University
Bing-Zhi Li: Tianjin University
Ying-Jin Yuan: Tianjin University

Nature Communications, 2022, vol. 13, issue 1, 1-9

Abstract: Abstract DNA data storage is a rapidly developing technology with great potential due to its high density, long-term durability, and low maintenance cost. The major technical challenges include various errors, such as strand breaks, rearrangements, and indels that frequently arise during DNA synthesis, amplification, sequencing, and preservation. In this study, a de novo strand assembly algorithm (DBGPS) is developed using de Bruijn graph and greedy path search to meet these challenges. DBGPS shows substantial advantages in handling DNA breaks, rearrangements, and indels. The robustness of DBGPS is demonstrated by accelerated aging, multiple independent data retrievals, deep error-prone PCR, and large-scale simulations. Remarkably, 6.8 MB of data is accurately recovered from a severely corrupted sample that has been treated at 70 °C for 70 days. With DBGPS, we are able to achieve a logical density of 1.30 bits/cycle and a physical density of 295 PB/g.

Date: 2022
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DOI: 10.1038/s41467-022-33046-w

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