Scaling logical density of DNA storage with enzymatically-ligated composite motifs

Yan, Yiqing; Pinnamaneni, Nimesh; Chalapati, Sachin; Crosbie, Conor; Appuswamy, Raja
Nature Scientific Reports, 25 September 2023

DNA is a promising candidate for long-term data storage due to its high density and endurance. The key challenge in DNA storage today is the cost of synthesis. In this work, we propose composite motifs, a framework that uses a mixture of prefabricated motifs as building blocks to reduce synthesis cost by scaling logical density. To write data, we introduce Bridge Oligonucleotide Assembly, an enzymatic ligation technique for synthesizing oligos based on composite motifs. To sequence data, we introduce Direct Oligonucleotide Sequencing, a nanopore-based technique to sequence oligos without assembly and amplification. To decode data, we introduce Motif-Search, a novel consensus caller that provides accurate reconstruction despite synthesis and sequencing errors. Using the proposed methods, we present an end-to-end experiment where we store the text 'HelloWorld' at a logical density of 84 bits/cycle (14-42x improvement over state-of-the-art.)


DOI
Type:
Journal
Date:
2023-09-25
Department:
Data Science
Eurecom Ref:
7200
Copyright:
© Springer. Personal use of this material is permitted. The definitive version of this paper was published in Nature Scientific Reports, 25 September 2023 and is available at : https://doi.org/10.1101/2023.02.02.526799

PERMALINK : https://www.eurecom.fr/publication/7200