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From deep archival to real-time applications: Challenges and opportunities in DNA data storage
Qian Liu1, Qiu-Jun Liu2, Shaohua Kang3
1College of Food Science and Engineering, Tianjin University of Science & Technology, Tianjin 300457, China; School of Synthetic Biology and Biomanufacturing, Tianjin University, Tianjin 300350, China.; State Key Laboratory of Synthetic Biology, Tianjin University, Tianjin 300350, China..
Biotechnology Advances
|February 5, 2026
Summary
DNA data storage offers high density and durability but faces challenges across different access speeds. Innovations are needed for long-term archival, periodic retrieval, and real-time processing to realize DNA
Area of Science:
- Biotechnology
- Data Storage
- Molecular Engineering
Background:
- DNA offers superior data storage density, durability, and energy efficiency over conventional methods.
- Current DNA storage technologies face challenges in diverse data access scenarios, from archival to real-time processing.
Purpose of the Study:
- To review the state-of-the-art in DNA data storage across various scenarios.
- To identify key challenges and outline future research directions for practical DNA data storage implementation.
Main Methods:
- Exploration of preservation strategies for deep cold archival storage (e.g., silica encapsulation, microbial chassis).
- Review of techniques for cold data retrieval (e.g., molecular indexing, microfluidic partitioning, isothermal amplification).
- Analysis of barriers in warm and hot data storage (e.g., throughput, latency, dynamic operations).
Main Results:
- Deep cold storage strategies show potential for millennial lifespans.
- Cold data access is improved by molecular indexing and cellular systems.
- Warm and hot data storage requires advancements in speed, reusability, and automation.
Conclusions:
- Sustained interdisciplinary efforts are crucial for advancing DNA data storage.
- Integration of molecular design, media engineering, and retrieval strategies is key.
- System-level integration is necessary to meet diverse data storage demands.
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