Scaling up DNA data storage and random access retrieval

Abstract

Current storage technologies can no longer keep pace with exponentially growing amounts of data.1 Synthetic DNA offers an attractive alternative due to its potential information density of ~ 10 18 B/mm 3 , 10 7 times denser than magnetic tape, and potential durability of thousands of years.2 Recent advances in DNA data storage have highlighted technical challenges, in particular, coding and random access, but have stored only modest amounts of data in synthetic DNA. 3,4,5 This paper demonstrates an end-to-end approach toward the viability of DNA data storage with large-scale random access. We encoded and stored 35 distinct files, totaling 200MB of data, in more than 13 million DNA oligonucleotides (about 2 billion nucleotides in total) and fully recovered the data with no bit errors, representing an advance of almost an order of magnitude compared to prior work. 6 Our data curation focused on technologically advanced data types and historical relevance, including the Universal Declaration of Human Rights in over 100 languages, 7 a high-definition music video of the band OK Go, 8 and a CropTrust database of the seeds stored in the Svalbard Global Seed Vault. 9 We developed a random access methodology based on selective amplification, for which we designed and validated a large library of primers, and successfully retrieved arbitrarily chosen items from a subset of our pool containing 10.3 million DNA sequences. Moreover, we developed a novel coding scheme that dramatically reduces the physical redundancy (sequencing read coverage) required for error-free decoding to a median of 5x, while maintaining levels of logical redundancy comparable to the best prior codes. We further stress-tested our coding approach by successfully decoding a file using the more error-prone nanopore-based sequencing. We provide a detailed analysis of errors in the process of writing, storing, and reading data from synthetic DNA at a large scale, which helps peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/114553 doi: bioRxiv preprint first posted online Mar. 7, 2017; 2 characterize DNA as a storage medium and justify our coding approach. Thus, we have demonstrated a significant improvement in data volume, random access, and encoding/decoding schemes that contribute to a whole-system vision for DNA data storage.Storing digital data using synthetic DNA encompasses mapping bits into nucleotide sequences, synthesizing the corresponding molecules, and storing them in an appropriate environment.Reading the information requires sequencing and converting the stored DNA back into digital data. Our project explores this DNA data storage workflow end-to-end (Figure 1a). We focus on scaling up data volumes and solving associated key challenges. Specifically, we address the need to access data selectively rather than in bulk and the need to minimize the amount of sequencing required to completely recover stored data.Most pr...

Coding Over Sets for DNA Storage

“…We denote by s the maximum number of sequences that are never drawn (or their clusters are not identified), by t the maximum number of sequences, which have been reconstructed with errors with a maximum of ǫ errors of type E each. Typical error types E after the reconstruction step are insertions, deletions and substitutions, where the latter two are the most prominent ones in DNA storage systems [5]. To be more precise, we define the error balls associated with the channel model.…”

“…One way to address this problem is using block addresses, also called indices, that are stored as part of the strand. Errors in DNA are typically substitutions, insertions, and deletions, where most published studies report that either substitutions or deletions are the most prominent ones, depending upon the specific technology for synthesis and sequencing [2], [3], [4], [5], [6], [7]. For example, in column-based DNA oligo synthesis the dominant errors are deletions that result from either failure to remove the dimethoxytrityl (DMT) or combined inefficiencies in the coupling and capping steps [4].…”

Speckle-interferometry and speckle-correlometry of GB-speckles

“…However, as mentioned, such a problem can be easily resolved using data storage on DNA-carriers. Using synthetic DNA for the storage of numerical information makes it possible to achieve potential information density of 10 9 Gb/mm 3 at the potential durability of thousands of years (6). Thus, the researchers of Microsoft Corporation (Microsoft Research) in co-operation with scientists from University of Washington have stored more than 200 Mb numerical data in the form of DNA (4,6,7,8,9).…”

“…Using synthetic DNA for the storage of numerical information makes it possible to achieve potential information density of 10 9 Gb/mm 3 at the potential durability of thousands of years (6). Thus, the researchers of Microsoft Corporation (Microsoft Research) in co-operation with scientists from University of Washington have stored more than 200 Mb numerical data in the form of DNA (4,6,7,8,9). In particular, these data contain the encoding of high definition video (10), copies of the Universal Declaration of Human Rights in different languages, the top 100 books from Project Gutenberg, and the Crop Trust seed database (6).…”

Clustering-Correcting Codes

“…Since then, several more groups have demonstrated the ability to successfully store data of large scale using DNA molecules; see e.g. [1], [2], [5], [13], [18]. Other works developed coding solutions which are specifically targeted to correct the special types of errors inside DNA-based storage systems [10]- [12], [14], [16]- [18].…”