scholarly journals Experimental Assessment of PCR Specificity and Copy Number for Reliable Data Retrieval in DNA Storage

2019 ◽  
Author(s):  
Lee Organick ◽  
Yuan-Jyue Chen ◽  
Siena Dumas Ang ◽  
Randolph Lopez ◽  
Karin Strauss ◽  
...  
Keyword(s):  
Data Storage ◽  
Dna Sequences ◽  
Random Access ◽  
Data Retrieval ◽  
Drop Out ◽  
Prior Work ◽  
Synthetic Dna ◽  
File Recovery ◽  
Dna Strands ◽  
File Retrieval

ABSTRACTSynthetic DNA has been gaining momentum as a potential storage medium for archival data storage1–9. Digital information is translated into sequences of nucleotides and the resulting synthetic DNA strands are then stored for later individual file retrieval via PCR7–9(Fig. 1a). Using a previously presented encoding scheme9and new experiments, we demonstrate reliable file recovery when as few as 10 copies per sequence are stored, on average. This results in density of about 17 exabytes/g, nearly two orders of magnitude greater than prior work has shown6. Further, no prior work has experimentally demonstrated access to specific files in a pool more complex than approximately 106unique DNA sequences9, leaving the issue of accurate file retrieval at high data density and complexity unexamined. Here, we demonstrate successful PCR random access using three files of varying sizes in a complex pool of over 1010unique sequences, with no evidence that we have begun to approach complexity limits. We further investigate the role of file size on successful data recovery, the effect of increasing sequencing coverage to aid file recovery, and whether DNA strands drop out of solution in a systematic manner. These findings substantiate the robustness of PCR as a random access mechanism in complex settings, and that the number of copies needed for data retrieval does not compromise density significantly.

scholarly journals Low-Bias Amplification for Robust DNA Data Readout

2020 ◽  
Author(s):  
Yanmin Gao ◽  
Xin Chen ◽  
Jianye Hao ◽  
Chengwei Zhang ◽  
Hongyan Qiao ◽  
...  
Keyword(s):  
Data Storage ◽  
Dna Sequences ◽  
Magnetic Beads ◽  
Dna Amplification ◽  
Digital Data ◽  
Amplification Bias ◽  
Synthetic Dna ◽  
Sequence Complexity ◽  
Dna Strands ◽  
Efficient Information

AbstractIn DNA data storage, the massive sequence complexity creates challenges in repeatable and efficient information readout. Here, our study clearly demonstrated that canonical polymerase chain reaction (PCR) created significant DNA amplification biases, which greatly hinder fast and stable data retrieving from hundred-thousand synthetic DNA sequences encoding over 2.85 megabyte (MB) digital data. To mitigate the amplification bias, we adapted an isothermal DNA amplification for low-bias amplification of DNA pool with massive sequence complexity, and named the new method isothermal DNA reading (iDR). By using iDR, we were able to robustly and repeatedly retrieve the data stored in DNA strands attached on magnetic beads (MB) with significantly decreased sequencing reads, compared with the PCR method. Therefore, we believe that the low-bias iDR method provides an ideal platform for robust DNA data storage, and fast and reliable data readout.

scholarly journals DNA Punch Cards: Storing Data on Native DNA Sequences via Nicking

2019 ◽  
Author(s):  
S Kasra Tabatabaei ◽  
Boya Wang ◽  
Nagendra Bala Murali Athreya ◽  
Behnam Enghiad ◽  
Alvaro Gonzalo Hernandez ◽  
...  
Keyword(s):  
Data Storage ◽  
Dna Sequences ◽  
Genomic Dna ◽  
High Throughput Sequencing ◽  
Pyrococcus Furiosus ◽  
Random Access ◽  
Error Rates ◽  
Magnetic Storage ◽  
Synthetic Dna ◽  
Phosphate Backbone

AbstractSynthetic DNA-based data storage systems have received significant attention due to the promise of ultrahigh storage density and long-term stability. However, all platforms proposed so far suffer from high cost, read-write latency and error-rates that render them noncompetitive with modern optical and magnetic storage devices. One means to avoid synthesizing DNA and to reduce the system error-rates is to use readily available native DNA. As the symbol/nucleotide content of native DNA is fixed, one may adopt an alternative recording strategy that modifies the DNA topology to encode desired information. Here, we report the first macromolecular storage paradigm in which data is written in the form of “nicks (punches)” at predetermined positions on the sugar-phosphate backbone of native dsDNA. The platform accommodates parallel nicking on multiple “orthogonal” genomic DNA fragments and paired nicking and disassociation for creating “toehold” regions that enable single-bit random access and strand displacement in-memory computations. As a proof of concept, we used the programmable restriction enzyme Pyrococcus furiosus Argonaute to punch two files into the PCR products of Escherichia coli genomic DNA. The encoded data is accurately reconstructed through high-throughput sequencing and read alignment.

scholarly journals Scaling up DNA data storage and random access retrieval

2017 ◽  
Author(s):  
Lee Organick ◽  
Siena Dumas Ang ◽  
Yuan-Jyue Chen ◽  
Randolph Lopez ◽  
Sergey Yekhanin ◽  
...  
Keyword(s):  
Data Storage ◽  
Dna Sequences ◽  
Large Scale ◽  
Random Access ◽  
Attractive Alternative ◽  
Data Types ◽  
High Definition ◽  
Synthetic Dna ◽  
Dna Oligonucleotides ◽  
Order Of Magnitude

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 ~ 1018 B/mm3, 107 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 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.

Deoxyribonucleic Acid as a Tool for Digital Information Storage: An Overview

2019 ◽  
Vol 15 (01) ◽  
pp. 1-8
Author(s):  
Ashish C Patel ◽  
C G Joshi
Keyword(s):  
Data Storage ◽  
Dna Sequences ◽  
Consensus Sequence ◽  
Random Access ◽  
Information Storage ◽  
Digital Data ◽  
Digital Information ◽  
Multiple Sequence ◽  
Digital World ◽  
Digital File

Current data storage technologies cannot keep pace longer with exponentially growing amounts of data through the extensive use of social networking photos and media, etc. The "digital world” with 4.4 zettabytes in 2013 has predicted it to reach 44 zettabytes by 2020. From the past 30 years, scientists and researchers have been trying to develop a robust way of storing data on a medium which is dense and ever-lasting and found DNA as the most promising storage medium. Unlike existing storage devices, DNA requires no maintenance, except the need to store at a cool and dark place. DNA has a small size with high density; just 1 gram of dry DNA can store about 455 exabytes of data. DNA stores the informations using four bases, viz., A, T, G, and C, while CDs, hard disks and other devices stores the information using 0’s and 1’s on the spiral tracks. In the DNA based storage, after binarization of digital file into the binary codes, encoding and decoding are important steps in DNA based storage system. Once the digital file is encoded, the next step is to synthesize arbitrary single-strand DNA sequences and that can be stored in the deep freeze until use.When there is a need for information to be recovered, it can be done using DNA sequencing. New generation sequencing (NGS) capable of producing sequences with very high throughput at a much lower cost about less than 0.1 USD for one MB of data than the first sequencing technologies. Post-sequencing processing includes alignment of all reads using multiple sequence alignment (MSA) algorithms to obtain different consensus sequences. The consensus sequence is decoded as the reversal of the encoding process. Most prior DNA data storage efforts sequenced and decoded the entire amount of stored digital information with no random access, but nowadays it has become possible to extract selective files (e.g., retrieving only required image from a collection) from a DNA pool using PCR-based random access. Various scientists successfully stored up to 110 zettabytes data in one gram of DNA. In the future, with an efficient encoding, error corrections, cheaper DNA synthesis,and sequencing, DNA based storage will become a practical solution for storage of exponentially growing digital data.

scholarly journals Quantifying Molecular Bias in DNA Data Storage

2019 ◽  
Author(s):  
Yuan-Jyue Chen ◽  
Christopher N. Takahashi ◽  
Lee Organick ◽  
Kendall Stewart ◽  
Siena Dumas Ang ◽  
...  
Keyword(s):  
Data Storage ◽  
Data Retrieval ◽  
Drop Out ◽  
Digital Data ◽  
Synthesis Process ◽  
Molecular Processes ◽  
Sequencing Coverage ◽  
Trade Offs ◽  
Physical Density ◽  
Free Data

DNA has recently emerged as an attractive medium for future digital data storage because of its extremely high information density and potential longevity. Recent work has shown promising results in developing proof-of-principle prototype systems. However, very uneven (biased) sequencing coverage distributions have been reported, which indicates inefficiencies in the storage process and points to optimization opportunities. These deviations from the average coverage in oligonucleotide copy distribution result in sequence drop-out and make error-free data retrieval from DNA more challenging. The uneven copy distribution was believed to stem from the underlying molecular processes, but the interplay between these molecular processes and the copy number distribution has been poorly understood until now. In this paper, we use millions of unique sequences from a DNA-based digital data archival system to study the oligonucleotide copy unevenness problem and show that two important sources of bias are the synthesis process and the Polymerase Chain Reaction (PCR) process. By mapping the sequencing coverage of a large complex oligonucleotide pool back to its spatial distribution on the synthesis chip, we find that significant bias comes from array-based oligonucleotide synthesis. We also find that PCR stochasticity is another main driver of oligonucleotide copy variation. Based on these findings, we develop a statistical model for each molecular process as well as the overall process and compare the predicted bias with our experimental data. We further use our model to explore the trade-offs between synthesis bias, storage physical density and sequencing redundancy, providing insights for engineering efficient, robust DNA data storage systems.

scholarly journals Content-Based Similarity Search in Large-Scale DNA Data Storage Systems

2020 ◽  
Author(s):  
Callista Bee ◽  
Yuan-Jyue Chen ◽  
David Ward ◽  
Xiaomeng Liu ◽  
Georg Seelig ◽  
...  
Keyword(s):  
Data Storage ◽  
Dna Sequences ◽  
Similarity Search ◽  
Large Scale ◽  
Storage Systems ◽  
Unique Identifier ◽  
Query Image ◽  
Synthetic Dna ◽  
Dna Database ◽  
Similar Images

AbstractSynthetic DNA has the potential to store the world’s continuously growing amount of data in an extremely dense and durable medium. Current proposals for DNA-based digital storage systems include the ability to retrieve individual files by their unique identifier, but not by their content. Here, we demonstrate content-based retrieval from a DNA database by learning a mapping from images to DNA sequences such that an encoded query image will retrieve visually similar images from the database via DNA hybridization. We encoded and synthesized a database of 1.6 million images and queried it with a variety of images, showing that each query retrieves a sample of the database containing visually similar images are retrieved at a rate much greater than chance. We compare our results with several algorithms for similarity search in electronic systems, and demonstrate that our molecular approach is competitive with state-of-the-art electronics.One Sentence SummaryLearned encodings enable content-based image similarity search from a database of 1.6 million images encoded in synthetic DNA.

scholarly journals NOREC4DNA: using near-optimal rateless erasure codes for DNA storage

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Peter Michael Schwarz ◽  
Bernd Freisleben
Keyword(s):  
Data Storage ◽  
Dna Sequences ◽  
Storage Systems ◽  
High Capacity ◽  
Digital Data ◽  
Erasure Codes ◽  
Software Framework ◽  
Digital Information ◽  
Dna Storage ◽  
Dna Strands

Abstract Background DNA is a promising storage medium for high-density long-term digital data storage. Since DNA synthesis and sequencing are still relatively expensive tasks, the coding methods used to store digital data in DNA should correct errors and avoid unstable or error-prone DNA sequences. Near-optimal rateless erasure codes, also called fountain codes, are particularly interesting codes to realize high-capacity and low-error DNA storage systems, as shown by Erlich and Zielinski in their approach based on the Luby transform (LT) code. Since LT is the most basic fountain code, there is a large untapped potential for improvement in using near-optimal erasure codes for DNA storage. Results We present NOREC4DNA, a software framework to use, test, compare, and improve near-optimal rateless erasure codes (NORECs) for DNA storage systems. These codes can effectively be used to store digital information in DNA and cope with the restrictions of the DNA medium. Additionally, they can adapt to possible variable lengths of DNA strands and have nearly zero overhead. We describe the design and implementation of NOREC4DNA. Furthermore, we present experimental results demonstrating that NOREC4DNA can flexibly be used to evaluate the use of NORECs in DNA storage systems. In particular, we show that NORECs that apparently have not yet been used for DNA storage, such as Raptor and Online codes, can achieve significant improvements over LT codes that were used in previous work. NOREC4DNA is available on https://github.com/umr-ds/NOREC4DNA. Conclusion NOREC4DNA is a flexible and extensible software framework for using, evaluating, and comparing NORECs for DNA storage systems.

scholarly journals A empirical comparison of preservation methods for synthetic DNA data storage

2020 ◽  
Author(s):  
Lee Organick ◽  
Bichlien H. Nguyen ◽  
Rachel McAmis ◽  
Weida D. Chen ◽  
A. Xavier Kohll ◽  
...  
Keyword(s):  
Data Storage ◽  
Dna Sequences ◽  
Accelerated Aging ◽  
Digital Data ◽  
Synthetic Dna ◽  
Preservation Methods ◽  
Trade Offs ◽  
Physical Density ◽  
Data Files ◽  
Sequence Profiles

ABSTRACTSynthetic DNA has recently risen as a viable alternative for long-term digital data storage. To ensure that information is safely recovered after storage, it is essential to appropriately preserve the physical DNA molecules encoding the data. While preservation of biological DNA has been studied previously, synthetic DNA differs in that it is typically much shorter in length, it has different sequence profiles with fewer, if any, repeats (or homopolymers), and it has different contaminants. In this paper we evaluate nine different methods used to preserve data files encoded in synthetic DNA by accelerated aging of nearly 29,000 DNA sequences. In addition to a molecular count comparison, we also sequence and analyze the DNA after aging. Our findings show that errors and erasures are stochastic and show no practical distribution difference between preservation methods. Finally, we compare the physical density of these methods and provide a stability versus density trade-offs discussion.

Analysis of 6T SRAM Cell in Different Technologies

2017 ◽  
Vol MCSP2017 (01) ◽  
pp. 7-10 ◽  
Author(s):  
Subhashree Rath ◽  
Siba Kumar Panda
Keyword(s):  
Low Power ◽  
Data Storage ◽  
Low Voltage ◽  
Random Access ◽  
Storage Device ◽  
Cmos Process ◽  
Process Technology ◽  
Digital Devices ◽  
Noise Margin ◽  
Sram Cell

Static random access memory (SRAM) is an important component of embedded cache memory of handheld digital devices. SRAM has become major data storage device due to its large storage density and less time to access. Exponential growth of low power digital devices has raised the demand of low voltage low power SRAM. This paper presents design and implementation of 6T SRAM cell in 180 nm, 90 nm and 45 nm standard CMOS process technology. The simulation has been done in Cadence Virtuoso environment. The performance analysis of SRAM cell has been evaluated in terms of delay, power and static noise margin (SNM).

scholarly journals Promiscuous molecules for smarter file operations in DNA-based data storage

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Kyle J. Tomek ◽  
Kevin Volkel ◽  
Elaine W. Indermaur ◽  
James M. Tuck ◽  
Albert J. Keung
Keyword(s):  
Data Storage ◽  
Data Access ◽  
Molecular Architecture ◽  
Biomolecular Structure ◽  
Jpeg Images ◽  
Storage Media ◽  
Dna Storage ◽  
Dna Strands ◽  
Background Database ◽  
Organizational Features

AbstractDNA holds significant promise as a data storage medium due to its density, longevity, and resource and energy conservation. These advantages arise from the inherent biomolecular structure of DNA which differentiates it from conventional storage media. The unique molecular architecture of DNA storage also prompts important discussions on how data should be organized, accessed, and manipulated and what practical functionalities may be possible. Here we leverage thermodynamic tuning of biomolecular interactions to implement useful data access and organizational features. Specific sets of environmental conditions including distinct DNA concentrations and temperatures were screened for their ability to switchably access either all DNA strands encoding full image files from a GB-sized background database or subsets of those strands encoding low resolution, File Preview, versions. We demonstrate File Preview with four JPEG images and provide an argument for the substantial and practical economic benefit of this generalizable strategy to organize data.

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