Synthetic DNA is durable and can encode digital data with high density, making it an attractive medium for data storage. However, recovering stored data on a large-scale currently requires all the DNA in a pool to be sequenced, even if only a subset of the information needs to be extracted. Here, we encode and store 35 distinct files (over 200 MB of data), in more than 13 million DNA oligonucleotides, and show that we can recover each file individually and with no errors, using a random access approach. We design and validate a large library of primers that enable individual recovery of all files stored within the DNA. We also develop an algorithm that greatly reduces the sequencing read coverage required for error-free decoding by maximizing information from all sequence reads. These advances demonstrate a viable, large-scale system for DNA data storage and retrieval.
We would like to thank B. Peck, P. Finn, S. Chen, A. Stewart, B. Arias, and E. Leproust from Twist Bioscience for supplying the DNA, suggesting protocol refinements, and offering input to our data analysis. We also thank J. Bornholt, K. D'Silva, and A. Levskaya for their help in the early stages of this project, and Y. Chou for her help in preparing samples for distribution. This work was supported in part by a sponsored research agreement by Microsoft, NSF award CCF-1409831 to L.C. and G.S. and by NSF award CCF-1317653 to G.S.
Integrated supplementary information
Supplementary Figures 1–5