Adaptive coding for DNA storage with high storage density and low coverage

• Published in: NPJ systems biology and applications Vol. 8; no. 1; pp. 23 - 12
• Main Authors: Cao, Ben, Zhang, Xiaokang, Cui, Shuang, Zhang, Qiang
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 04.07.2022; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114; 631/553/2720; 631/553/552; 631/61/350; Algorithms; Bioinformatics; Biology; Biomedical and Life Sciences; Codes; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Data compression; Deoxyribonucleic acid; DNA; Error correction & detection; Life Sciences; Methods; Nucleotide sequence; Systems Biology
• ISSN: 2056-7189; 2056-7189
• DOI: 10.1038/s41540-022-00233-w

The rapid development of information technology has generated substantial data, which urgently requires new storage media and storage methods. DNA, as a storage medium with high density, high durability, and ultra-long storage time characteristics, is promising as a potential solution. However, DNA storage is still in its infancy and suffers from low space utilization of DNA strands, high read coverage, and poor coding coupling. Therefore, in this work, an adaptive coding DNA storage system is proposed to use different coding schemes for different coding region locations, and the method of adaptively generating coding constraint thresholds is used to optimize at the system level to ensure the efficient operation of each link. Images, videos, and PDF files of size 698 KB were stored in DNA using adaptive coding algorithms. The data were sequenced and losslessly decoded into raw data. Compared with previous work, the DNA storage system implemented by adaptive coding proposed in this paper has high storage density and low read coverage, which promotes the development of carbon-based storage systems.