Pragmatic soft-decision data readout of encoded large DNA
The encoded large DNA can be cloned and stored in vivo, capable of write-once and stable replication for multiple retrievals, offering potential in economic data archiving. Nanopore sequencing is advantageous in data access of large DNA due to its rapidity and long-read sequencing capability. However, the data readout is commonly limited by insertion and deletion (indel) errors and sequence assembly complexity. Here, a pragmatic soft-decision data readout is presented, achieving assembly-free sequence reconstruction, indel error correction, and ultra-low coverage data readout. Specifically, the watermark is cleverly embedded within large DNA fragments, allowing for the direct localization of raw reads via watermark alignment to avoid complex read assembly. A soft-decision forward-backward algorithm is proposed, which can identify indel errors and provide probability information to the error correction code, enabling error-free data recovery. Additionally, a minimum state transition is maintained, and a read segmentation is incorporated to achieve fast information reading. The readout assays for two circular plasmids (~51 kb) with different coding rates were demonstrated and achieved error-free recovery directly from noisy reads (error rate ~1%) at coverage of 1-4×. Simulations conducted on large-scale datasets across various error rates further confirm the scalability of the method and its robust performance under extreme conditions. This readout method enables nearly single-molecule recovery of large DNA, particularly suitable for rapid readout of DNA storage.
Authors
- Qi Ge
- Changcai Han (ORCID: https://orcid.org/0000-0003-4879-1748)
- Shuang Liu (ORCID: https://orcid.org/0000-0002-9027-0690)
- Quan Guo (ORCID: https://orcid.org/0000-0003-2858-5090)
- Rui Qin (ORCID: https://orcid.org/0009-0005-8609-0151)
- Weigang Chen (ORCID: https://orcid.org/0000-0002-4880-8186)
Institutions
- Tianjin University (CN)
Publication Details
- Journal
- Briefings in Bioinformatics
- Published
- 2025-03-01
- DOI
- https://doi.org/10.1093/bib/bbaf102
- Citations
- 5
- Primary Topic
- DNA and Biological Computing
- Type
- article
- Field-Weighted Citation Impact
- 4.03
Funders
- National Key Research and Development Program of China