← 研踪 PaperTrailarXiv:2603.14527 · v3
DNA-MGC+: A versatile codec for reliable and resource-efficient data storage on synthetic DNA
首次提交 2026-03-16 02:10
版本更新 2026-11-09 14:24
雷达观测 2026-11-10 13:18
摘要
The biochemical processes underlying DNA data storage, including synthesis, amplification, and sequencing, are inherently noisy, leading to insertion, deletion, and substitution errors as well as sequence dropouts that challenge reliable data retrieval. Here we introduce DNA-MGC+, a DNA storage codec designed for reliable and resource-efficient retrieval under diverse operating conditions. We evaluate DNA-MGC+ across various in silico and in vitro settings. In comparison with selected representative codecs, the results show that DNA-MGC+ consistently improves key performance metrics under explicit reliability constraints, including required sequencing depth, read cost, decoding time, storage density, and error-correction capability. In silico experiments show that DNA-MGC+ supports reliable decoding at error rates up to 24% for a 15-KB file, while separate scalability experiments demonstrate reliable decoding of files up to 200 MB at a 5% error rate. In vitro experiments involving a 24-KB file and electrochemical synthesis show that different DNA-MGC+ configurations achieve minimum sequencing depths below 3x and read costs below 3.5 nts/bit under both Illumina and Nanopore sequencing.
作者备注：Accepted in Communications Engineering (Nature Portfolio)
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v3 · 2026-11-09 14:24 · 最新观测版本
DNA-MGC+: A versatile codec for reliable and resource-efficient data storage on synthetic DNA
The biochemical processes underlying DNA data storage, including synthesis, amplification, and sequencing, are inherently noisy, leading to insertion, deletion, and substitution errors as well as sequence dropouts that challenge reliable data retrieval. Here we introduce DNA-MGC+, a DNA storage codec designed for reliable and resource-efficient retrieval under diverse operating conditions. We evaluate DNA-MGC+ across various in silico and in vitro settings. In comparison with selected representative codecs, the results show that DNA-MGC+ consistently improves key performance metrics under explicit reliability constraints, including required sequencing depth, read cost, decoding time, storage density, and error-correction capability. In silico experiments show that DNA-MGC+ supports reliable decoding at error rates up to 24% for a 15-KB file, while separate scalability experiments demonstrate reliable decoding of files up to 200 MB at a 5% error rate. In vitro experiments involving a 24-KB file and electrochemical synthesis show that different DNA-MGC+ configurations achieve minimum sequencing depths below 3x and read costs below 3.5 nts/bit under both Illumina and Nanopore sequencing.
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