Random access in large-scale DNA data storage.

Area of Science:

• Biotechnology
• Bioinformatics
• Data Storage

Background:

• Synthetic DNA offers high-density, durable data storage potential.
• Current DNA data retrieval methods necessitate sequencing the entire DNA pool, limiting scalability.

Purpose of the Study:

• To demonstrate a scalable, random-access method for retrieving individual files from large-scale DNA data storage.
• To develop enabling technologies for efficient and error-free data extraction from DNA.

Main Methods:

• Encoding 35 distinct files (over 200 MB) into more than 13 million DNA oligonucleotides.
• Designing and validating a comprehensive primer library for targeted DNA sequence recovery.
• Implementing a novel algorithm to minimize sequencing read coverage for accurate data decoding.

Main Results:

• Successful individual and error-free recovery of all 35 stored files.
• Demonstrated feasibility of random access for DNA data retrieval.
• Significant reduction in required sequencing depth for data decoding.

Conclusions:

• The developed system provides a viable, large-scale solution for DNA data storage and retrieval.
• Random access and algorithmic improvements overcome key limitations of previous DNA data storage methods.
• This work paves the way for practical applications of DNA as a high-capacity data storage medium.