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.
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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.
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Integrated supplementary information
(a) Method for primer design. A random 20-mer continues to mutate until it satisfies the design criteria explained above. After satisfying these criteria, the primer is filtered by secondary structure and melting temperature. After generating a library of primers, the library is screened using BLAST to further improve sequence orthogonality. (b) Example of scoring for a primer. If the primer violates a design criterion, all bases related to the violation receive a +1 score.
(a) The total number of primer pairs that pass the selection criteria described in Supplementary Fig. 1 (y-axis) increases with the log of the number of starting random 20-mers (x-axis, logarithmic scale). The six blue dots are primer libraries generated from different numbers of starting random 20-mers. (b) The ratio of primers passing the primer-payload collision detection algorithm described in Supplementary Fig. 4 (y-axis) decreases as the log of the amount of information to be stored increases (x-axis, logarithmic scale). Blue points represent the average passing ratio of the six different primer libraries generated in a. Error bars indicate standard deviation calculated from these six primer libraries. The measures of the centre indicate mean calculated from these six primer libraries.
Digital data are iteratively randomized to reduce collisions between primers and payloads.
Supplementary Figure 4 Comparing amplification of files with and without collision detection and our primer design method.
All 15 bp traces are size markers used by the Qiagen QIAxcel system. The same instrument and profile was used for each trace. Each trace is a representative of three independent trials with virtually identical results. (a) “Simple conditions” indicates single-file pools. i. Trace of an amplified file designed with collision detection. ii. Trace of an amplified file designed without collision detection. (b) “Complex conditions” indicates multi-file pools. i. Trace of an amplified file designed with collision detection (9-file pool; amplified file is 17.4% of the pool). ii. Trace of an amplified file designed without using collision detection (6-file pool; amplified file is 18.0% of the pool).
First, random access regions are used to select files for sequencing. Through ePCR, a 25N region is added to the oligos to improve nucleotide diversity. Then, samples are ligated to Illumina sequencing adaptors with modified Illumina TruSeq Nano kit protocol. Finally, prepared samples are sequenced on an Illumina NextSeq instrument with a 10%-20% PhiX spike-in.
Supplementary Figures 1–5 (PDF 565 kb)
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Organick, L., Ang, S., Chen, Y. et al. Random access in large-scale DNA data storage. Nat Biotechnol 36, 242–248 (2018). https://doi.org/10.1038/nbt.4079
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