Parallel molecular data storage by printing epigenetic bits on DNA

Cheng Zhang (), Ranfeng Wu, Fajia Sun, Yisheng Lin, Yuan Liang, Jiongjiong Teng, Na Liu, Qi Ouyang (), Long Qian () and Hao Yan ()
Additional contact information
Cheng Zhang: Key Laboratory of High Confidence Software Technologies, Peking University
Ranfeng Wu: Key Laboratory of High Confidence Software Technologies, Peking University
Fajia Sun: Peking University
Yisheng Lin: Key Laboratory of High Confidence Software Technologies, Peking University
Yuan Liang: Key Laboratory of High Confidence Software Technologies, Peking University
Jiongjiong Teng: North China Electric Power University
Na Liu: University of Stuttgart
Qi Ouyang: Peking University
Long Qian: Peking University
Hao Yan: Biodesign Institute, Arizona State University

Nature, 2024, vol. 634, issue 8035, 824-832

Abstract: Abstract DNA storage has shown potential to transcend current silicon-based data storage technologies in storage density, longevity and energy consumption1–3. However, writing large-scale data directly into DNA sequences by de novo synthesis remains uneconomical in time and cost4. We present an alternative, parallel strategy that enables the writing of arbitrary data on DNA using premade nucleic acids. Through self-assembly guided enzymatic methylation, epigenetic modifications, as information bits, can be introduced precisely onto universal DNA templates to enact molecular movable-type printing. By programming with a finite set of 700 DNA movable types and five templates, we achieved the synthesis-free writing of approximately 275,000 bits on an automated platform with 350 bits written per reaction. The data encoded in complex epigenetic patterns were retrieved high-throughput by nanopore sequencing, and algorithms were developed to finely resolve 240 modification patterns per sequencing reaction. With the epigenetic information bits framework, distributed and bespoke DNA storage was implemented by 60 volunteers lacking professional biolab experience. Our framework presents a new modality of DNA data storage that is parallel, programmable, stable and scalable. Such an unconventional modality opens up avenues towards practical data storage and dual-mode data functions in biomolecular systems.

Date: 2024
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.nature.com/articles/s41586-024-08040-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:nature:v:634:y:2024:i:8035:d:10.1038_s41586-024-08040-5

Ordering information: This journal article can be ordered from
https://www.nature.com/

DOI: 10.1038/s41586-024-08040-5

Access Statistics for this article

Nature is currently edited by Magdalena Skipper

More articles in Nature from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().