Abstract

Synthetic DNA is becoming an attractive substrate for digital data storage due to its density, durability, and relevance in biological research. A major challenge in making DNA data storage a reality is that reading DNA back into data using sequencing by synthesis remains a laborious, slow and expensive process. Here, we demonstrate successful decoding of 1.67 megabytes of information stored in short fragments of synthetic DNA using a portable nanopore sequencing platform. We design and validate an assembly strategy for DNA storage that drastically increases the throughput of nanopore sequencing. Importantly, this assembly strategy is generalizable to any application that requires nanopore sequencing of small DNA amplicons.

Highlights

  • Synthetic DNA is becoming an attractive substrate for digital data storage due to its density, durability, and relevance in biological research

  • ONT MinION is a four-inch long USB-powered device containing an array of 512 sensors, each connected to four biological nanopores, capable of producing up to 15 gigabases of sequencing output per flowcell

  • Even though the overall error rate was similar to that of the non-homopolymer files, we found that nanopore sequencing tends to underestimate the length of homopolymer runs, leading to correlated deletion errors across payload sequences that cannot be corrected by the consensus algorithm. 26% of all original sequences corresponding to the Vitruvian Man file contained a homopolymer run of length 5 or more

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Summary

Introduction

Synthetic DNA is becoming an attractive substrate for digital data storage due to its density, durability, and relevance in biological research. Our group and others have demonstrated random access by selective PCR amplification of a given file without having to read all the data stored in a particular DNA pool[3,5,8,9]. Previous work by Yazdi et al demonstrated a DNA storage workflow where 17 unique large DNA fragments (~1000 bp.) encoding for a 3kB file were synthesized, and subsequently sequenced and decoded using ONT MinION platform[9].

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