Improving error-correcting capability in DNA digital storage via soft-decision decoding

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外文摘要：Error-correcting codes(ECCs)employed in the state-of-the-art DNA digital storage(DDS)systems suffer from a trade-offbetween error-correcting capability and the proportion of redundancy.To address this issue,in this study,we introduce soft-decision decoding approach into DDS by proposing a DNA-specific error prediction model and a series of novel strategies.We demonstrate the effectiveness of our approach through a proof-of-concept DDS system based on Reed-Solomon(RS)code,named as Derrick.Derrick shows significant improvement in error-correcting capability without involving additional redundancy in both in vitro and in silico experiments,using various sequencing technologies such as Illumina,PacBio and Oxford Nanopore Technology(ONT).Notably,in vitro experiments using ONT sequencing at a depth of 7 x reveal that Derrick,compared with the traditional hard-decision decoding strategy,doubles the error-correcting capability of RS code,decreases the proportion of matrices with decoding-failure by 229-fold,and amplifies the potential maximum storage volume by impressive 32 388-fold.Also,Derrick surpasses'state-of-the-art'DDS systems by comprehensively considering the information density and the minimum sequencing depth required for complete information recovery.Crucially,the soft-decision decoding strategy and key steps of Derrick are generalizable to other ECCs'decoding algorithms.

外文关键词：

DNA digital storage(DDS)error-correcting code(ECC)soft-decision decodingerror-correcting capabilitystorage volume

作者：

丁璐璐、伍世刚、侯志浩、李阿伦、许亚苹、冯虎、潘玮华、阮珏

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作者单位：

Shenzhen Branch,Guangdong Laboratory of Lingnan Modern Agriculture,Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs,Agricultural Genomics Institute at Shenzhen,Chinese Academy of Agricultural Sciences,Shenzhen 518120,China

Guangdong Provincial Key Laboratory of Plant Molecular Breeding,State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources,South China Agricultural University,Guangzhou 510642,China

基金：

National Key R&D Program of ChinaNational Key R&D Program of ChinaNational Natural Science Foundation of ChinaShenzhen Science and Technology ProgramInnovation Program of Chinese Academy of Agricultural Sciences

项目编号：

2019YFA07070032022YFC340030032100501RCBS20210609103819020

出版年：

2024

DOI：

10.1093/nsr/nwad229

国家科学评论(英文版)

CSTPCD

ISSN：

年,卷(期)：2024.11(2)

参考文献量39