Empowering low-crosstalk, dynamic-decision random access of DNA storage via 384-multiplexed nanopore signatures

Junyao Li, Xuyang Zhao, Qingyuan Fan, Yanping Long, Ronghui Liu, Jixian Zhai, Qing Pan and Yi Li ()
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Junyao Li: Southern University of Science and Technology
Xuyang Zhao: Southern University of Science and Technology
Qingyuan Fan: Southern University of Science and Technology
Yanping Long: Southern University of Science and Technology
Ronghui Liu: Southern University of Science and Technology
Jixian Zhai: Southern University of Science and Technology
Qing Pan: Zhejiang University of Technology
Yi Li: Southern University of Science and Technology

Nature Communications, 2025, vol. 16, issue 1, 1-12

Abstract: Abstract On-demand access to information encoded in nucleotides lies at the heart of DNA/RNA applications. However, contemporary methods for targeted retrieval using PCR amplification or bead-based extraction, rely on Watson-Crick base pairing and pre-defined primers, limiting dynamic decision-making whilst sequencing. We introduce SUSTag-ORCtrL, a nanopore-based system enables real-time, PCR-free random access to DNA-stored data by directly classifying raw ionic current signatures of 96 or 384-plex DNA molecular tags. Our framework combines SUSTag, a Bhattacharyya distance and incremental clustering enhanced molecular tag design (SUSTag) to minimize crosstalk, with an Optional-Reject Cnn-lstm deep learning model inspired by TRansfer-Learning (ORCtrL), designed to enhance adaptability to signal variability. SUSTag-ORCtrL achieves an intra-class weighted F1-score of 99.69% for 96-plex classification and 99.05% for 384-plex classification, surpassing existing molecular tagging systems. Domain adaptation using only120 minutes of new sequencing data ( ~ 200k reads) boosts the model performance from 87% to over 94%, achieving complete recovery of target data with minimal crosstalk in 10 min to 3 h. This system provides a scalable, low-latency solution for versatile DNA data access and holds promise for genomic and transcriptomic disease screening and the DNA-of-things.

Date: 2025
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DOI: 10.1038/s41467-025-64293-2

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