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Random access in large-scale DNA data storage

delete2018-02-19
delete488
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OA
AI
L
Lee Organick
S
Siena Dumas Ang
Y
Yuan-Jyue Chen
R
Randolph Lopez
S
Sergey Yekhanin
K
Konstantin Makarychev
M
Miklós Z. Rácz
G
Govinda M. Kamath
P
Parikshit Gopalan
B
Bichlien H. Nguyen
C
Christopher N. Takahashi
S
Sharon Newman
H
Hsing-Yeh Parker
C
Cyrus Rashtchian
K
Kendall Stewart
G
Gagan D. Gupta
R
Robert H. Carlson
J
John Mulligan
D
Douglas M. Carmean
G
Georg Seelig
L
Luís Ceze *
K
Karin Strauß *
DOI:10.1038/nbt.4079delete
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摘要

摘要

En 中文
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.
Keyword:
DIGITAL INFORMATION
DESIGN
ROBUST
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期刊

Nature Biotechnology 封面图
Nature Biotechnology
IF:
41.7
论文数:
1.2W
被引数:
10.1W

机构

U
University of Washington
学者数:
8.0W
论文数: 7.0W
被引数: 12.5W
M
Microsoft
学者数:
3.0K
论文数: 2.7K
被引数: 7
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