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Nat Biotechnol. 2018 Mar;36(3):242-248. doi: 10.1038/nbt.4079. Epub 2018 Feb 19.

Random access in large-scale DNA data storage.

Author information

1
Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington, USA.
2
Microsoft Research, Redmond, Washington, USA.
3
Department of Bioengineering Department, University of Washington, Seattle, Washington, USA.
4
Department of Electrical Engineering, University of Washington, Seattle, Washington, USA.

Abstract

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.

PMID:
29457795
DOI:
10.1038/nbt.4079

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