Robust data storage in DNA by de Bruijn graph-based de novo strand assembly

© 2022. The Author(s)..

DNA data storage is a rapidly developing technology with great potential due to its high density, long-term durability, and low maintenance cost. The major technical challenges include various errors, such as strand breaks, rearrangements, and indels that frequently arise during DNA synthesis, amplification, sequencing, and preservation. In this study, a de novo strand assembly algorithm (DBGPS) is developed using de Bruijn graph and greedy path search to meet these challenges. DBGPS shows substantial advantages in handling DNA breaks, rearrangements, and indels. The robustness of DBGPS is demonstrated by accelerated aging, multiple independent data retrievals, deep error-prone PCR, and large-scale simulations. Remarkably, 6.8 MB of data is accurately recovered from a severely corrupted sample that has been treated at 70 °C for 70 days. With DBGPS, we are able to achieve a logical density of 1.30 bits/cycle and a physical density of 295 PB/g.

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:13

Enthalten in:

Nature communications - 13(2022), 1 vom: 12. Sept., Seite 5361

Sprache:

Englisch

Beteiligte Personen:

Song, Lifu [VerfasserIn]
Geng, Feng [VerfasserIn]
Gong, Zi-Yi [VerfasserIn]
Chen, Xin [VerfasserIn]
Tang, Jijun [VerfasserIn]
Gong, Chunye [VerfasserIn]
Zhou, Libang [VerfasserIn]
Xia, Rui [VerfasserIn]
Han, Ming-Zhe [VerfasserIn]
Xu, Jing-Yi [VerfasserIn]
Li, Bing-Zhi [VerfasserIn]
Yuan, Ying-Jin [VerfasserIn]

Links:

Volltext

Themen:

9007-49-2
DNA
Journal Article
Research Support, Non-U.S. Gov't

Anmerkungen:

Date Completed 14.09.2022

Date Revised 02.11.2022

published: Electronic

figshare: 10.6084/m9.figshare.17193170.v2, 10.6084/m9.figshare.17192639.v1, 10.6084/m9.figshare.18515078.v1, 10.6084/m9.figshare.16727122.v2, 10.6084/m9.figshare.17193128.v1, 10.6084/m9.figshare.18515045.v1, 10.6084/m9.figshare.17183081.v1

Citation Status MEDLINE

doi:

10.1038/s41467-022-33046-w

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM346139376