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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, Mingzhe Han, Jing-Yi Xu, Bing‐Zhi Li, Ying‐Jin Yuan

2022Nature Communications91 citationsDOIOpen Access PDF

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.

Topics & Concepts

De Bruijn graphDe Bruijn sequenceSequence assemblyComputer scienceDNAComputational biologyBiologyGraphGeneticsCombinatoricsGeneTheoretical computer scienceMathematicsGene expressionTranscriptomeDNA and Biological ComputingAdvanced biosensing and bioanalysis techniquesAlgorithms and Data Compression
Robust data storage in DNA by de Bruijn graph-based de novo strand assembly | Litcius