Gungnir codec enabling high error-tolerance and low-redundancy DNA storage through substantial computing power

DNA has emerged as a compelling archival storage medium, offering unprecedented information density and millennia-scale durability. Despite its promise, DNA-based data storage faces critical challenges due to error-prone processes during DNA synthesis, storage, and sequencing. In this study, we introduce Gungnir, a codec system using the proof-of-work idea to address substitution, insertion, and deletion errors in a sequence. With a hash signature for each data fragment, Gungnir corrects the errors by testing the educated guesses until the hash signature is matched. For practicality, especially when sequenced with nanopore long-read, Gungnir also considers biochemical constraints, including GC-content, homopolymers, and error-prone motifs during encoding. In silico benchmarking demonstrates its outperforming error resilience capacity against the state-of-the-art methods and achieving complete binary data recovery from a single sequence copy containing 20% erroneous bases. Gungnir requires neither keeping many redundant sequence copies to address molecular decay in archival storage, nor high-coverage sequencing to address sequencing error, reducing the overall cost of using DNA for storage. DNA can store vast amounts of data, but current systems rely on many redundant copies and deep sequencing to correct synthetic, storage and readout errors. Here, authors present Gungnir, a DNA storage codec that recovers data from a single, highly error-prone sequence, reducing cost and improving reliability.