Low cost DNA data storage using photolithographic synthesis and advanced information reconstruction and error correction

Due to its longevity and enormous information density, DNA is an attractive medium for archival storage. The current hamstring of DNA data storage systems—both in cost and speed—is synthesis. The key idea for breaking this bottleneck pursued in this work is to move beyond the low-error and expensive...

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Veröffentlicht in:Nature communications Jg. 11; H. 1; S. 5345 - 10
Hauptverfasser: Antkowiak, Philipp L., Lietard, Jory, Darestani, Mohammad Zalbagi, Somoza, Mark M., Stark, Wendelin J., Heckel, Reinhard, Grass, Robert N.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Nature Publishing Group UK 22.10.2020
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ISSN:2041-1723, 2041-1723
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Zusammenfassung:Due to its longevity and enormous information density, DNA is an attractive medium for archival storage. The current hamstring of DNA data storage systems—both in cost and speed—is synthesis. The key idea for breaking this bottleneck pursued in this work is to move beyond the low-error and expensive synthesis employed almost exclusively in today’s systems, towards cheaper, potentially faster, but high-error synthesis technologies. Here, we demonstrate a DNA storage system that relies on massively parallel light-directed synthesis, which is considerably cheaper than conventional solid-phase synthesis. However, this technology has a high sequence error rate when optimized for speed. We demonstrate that even in this high-error regime, reliable storage of information is possible, by developing a pipeline of algorithms for encoding and reconstruction of the information. In our experiments, we store a file containing sheet music of Mozart, and show perfect data recovery from low synthesis fidelity DNA. The current bottleneck for DNA data storage systems is the cost and speed of synthesis. Here, the authors use inexpensive, massively parallel light-directed synthesis and correct for a high error rate with a pipeline of encoding and reconstruction algorithms.
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ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-020-19148-3