An alternative approach to nucleic acid memory
Open accessAbstract
DNA is a compelling alternative to non-volatile information storage technologies due to its information density, stability, and energy efficiency. Previous studies have used artificially synthesized DNA to store data and automated next-generation sequencing to read it back. Here, we report digital Nucleic Acid Memory (dNAM) for applications that require a limited amount of data to have high information density, redundancy, and copy number. In dNAM, data is encoded by selecting combinations of single-stranded DNA with (1) or without (0) docking-site domains. When self-assembled with scaffold DNA, staple strands form DNA origami breadboards. Information encoded into the breadboards is read by monitoring the binding of fluorescent imager probes using DNA-PAINT super-resolution microscopy. To enhance data retention, a multi-layer error correction scheme that combines fountain and bi-level parity codes is used. As a prototype, fifteen origami encoded with ‘Data is in our DNA!\n’ are analyzed. Each origami encodes unique data-droplet, index, orientation, and error-correction information. The error-correction algorithms fully recover the message when individual docking sites, or entire origami, are missing. Unlike other approaches to DNA-based data storage, reading dNAM does not require sequencing. As such, it offers an additional path to explore the advantages and disadvantages of DNA as an emerging memory material.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Information can be stored in the 3D structures of DNA assemblies instead of in the sequence, with readout relying on imaging techniques or single-molecule nanopore measurements.
“Information can thus be stored in the 3D structures of these assemblies instead of in the sequence, with readout relying on imaging techniques, such as super resolution imaging,22 or using single-molecule nanopore measurements.23,25”
From Emerging Approaches to DNA Data Storage: Challenges and Prospects (2022) · cites this paper as [22]
A DNA origami breadboard divided into a grid of pixels or an indexed matrix can encode binary information by the presence ("1") or absence ("0") of a docking site for a fluorophore at each location.
“Another tactic used a DNA origami “breadboard,” which was divided into a grid of pixels or an “indexed matrix of digital information.” Each specific location on the origami represents a bit, with the presence (“1”) or absence (“0”) of a docking site for a fluorophore encoding binary information.22”
From Emerging Approaches to DNA Data Storage: Challenges and Prospects (2022) · cites this paper as [22]
The DNA origami breadboard tactic requires only femtomoles of material.
“Unlike DNA sequencing, which requires multiple reads to reach a consensus, this tactic can read 750 origami to reach a 100% probability of full data retrieval, which means that only femtomoles of material are needed.”
From Emerging Approaches to DNA Data Storage: Challenges and Prospects (2022) · cites this paper as [22]
In the DNA origami breadboard approach, unique data patterns are created by selecting which staple strands within the origami possess data domains.
“In this example, unique data patterns are created by selecting which staple strands within the origami possess data domains.”
From Emerging Approaches to DNA Data Storage: Challenges and Prospects (2022) · cites this paper as [22]
The DNA origami breadboard approach uses error-correction algorithms that enable message recovery even when individual docking sites are missing.
“This approach also uses error-correction algorithms that enable message recovery even when individual docking sites are missing.”
From Emerging Approaches to DNA Data Storage: Challenges and Prospects (2022) · cites this paper as [22]
Unlike DNA sequencing, which requires multiple reads to reach a consensus, the DNA origami breadboard tactic can read 750 origami to reach a 100% probability of full data retrieval.
“Unlike DNA sequencing, which requires multiple reads to reach a consensus, this tactic can read 750 origami to reach a 100% probability of full data retrieval, which means that only femtomoles of material are needed.”
From Emerging Approaches to DNA Data Storage: Challenges and Prospects (2022) · cites this paper as [22]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Ror2 signaling regulates Golgi structure and transport through IFT20 for tumor invasiveness
Nishita, M., Park, S.-Y., Nishio, T., Kamizaki, K., Wang, Z., Tamada, K., Takumi, T., Hashimoto, R., Otani, H., Pazour, G. J., et al. (2017) · Scientific Reports · doi:10.1038/s41598-016-0028-x · Cited by 15,947 · see citing works
Folding DNA to create nanoscale shapes and patterns
Rothemund, P. W. K. (2006) · Nature · doi:10.1038/nature04586 · Cited by 7,320 · see citing works
Python for scientific computing
Oliphant, T. E. (2007) · Computing in Science & Engineering · doi:10.1109/mcse.2007.58 · Cited by 3,303 · see citing works
Luby, M. G. (2003) · doi:10.1109/sfcs.2002.1181950 · Cited by 2,786 · see citing works
Ovesný, M., Křížek, P., Borkovec, J., Švindrych, Z., & Hagen, G. M. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu202 · Cited by 1,515 · see citing works
Towards Practical, High-Capacity, Low-Maintenance Information Storage in Synthesized DNA
Goldman, N., Bertone, P., Chen, S., Dessimoz, C., LeProust, E. M., Sipos, B., & Birney, E. (2013) · Nature · doi:10.1038/nature11875 · Cited by 1,220 · see citing works
Super-resolution microscopy with DNA-PAINT
Schnitzbauer, J., Strauss, M. T., Schlichthaerle, T., Schueder, F., & Jungmann, R. (2017) · Nature Protocols · doi:10.1038/nprot.2017.024 · Cited by 1,047 · see citing works
Being Sensitive to Uncertainty
Arriola, L. M., & Hyman, J. M. (2007) · Computing in Science & Engineering · doi:10.1109/mcse.2007.27 · Cited by 975 · see citing works
Jungmann, R., Steinhauer, C., Scheible, M. B., Kuzyk, A., Tinnefeld, P., & Simmel, F. C. (2010) · Nano Letters · doi:10.1021/nl103427w · Cited by 907 · see citing works
Mackay, D. (2005) · IEE Proceedings - Communications · doi:10.1049/ip-com:20050237 · Cited by 900 · see citing works
DNA Fountain enables a robust and efficient storage architecture
Erlich, Y., & Zielinski, D. (2017) · Science · doi:10.1126/science.aaj2038 · Cited by 898 · see citing works
Random access in large-scale DNA data storage
Organick, L., Ang, S. D., Chen, Y.-J., Lopez, R., Yekhanin, S., Makarychev, K., Racz, M. Z., Kamath, G., Gopalan, P., Nguyen, B., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4079 · Cited by 775 · see citing works
Robust Chemical Preservation of Digital Information on DNA in Silica with Error-Correcting Codes
Grass, R. N., Heckel, R., Puddu, M., Paunescu, D., & Stark, W. J. (2015) · Angewandte Chemie International Edition · doi:10.1002/anie.201411378 · Cited by 754 · see citing works
Deep-STORM: super-resolution single-molecule microscopy by deep learning
Nehme, E., Weiss, L. E., Michaeli, T., & Shechtman, Y. (2018) · Optica · doi:10.1364/optica.5.000458 · Cited by 589 · see citing works
MINFLUX nanoscopy delivers 3D multicolor nanometer resolution in cells
Gwosch, K. C., Pape, J. K., Balzarotti, F., Hoess, P., Ellenberg, J., Ries, J., & Hell, S. W. (2020) · Nature Methods · doi:10.1038/s41592-019-0688-0 · Cited by 570 · see citing works
Hassani, S. A., Oemisch, M., Balcarras, M., Westendorff, S., Ardid, S., van der Meer, M. A. A., Tiesinga, P. H. E., & Womelsdorf, T. (2017) · Scientific Reports · doi:10.1038/srep40606 · Cited by 363 · see citing works
Portable and Error-Free DNA-Based Data Storage
Yazdi, S. M. H. T., Gabrys, R., & Milenkovic, O. (2017) · Scientific Reports · doi:10.1038/s41598-017-05188-1 · Cited by 361 · see citing works
A DNA-Based Archival Storage System
Bornholt, J., Lopez, R. M., Carmean, D. M., Ceze, L., Seelig, G., & Strauß, K. (2016) · International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) · doi:10.1145/2872362.2872397 · Cited by 346 · see citing works
The Beauty and Utility of DNA Origami
Wang, P., Meyer, T. A., Pan, V., Dutta, P. K., & Ke, Y. (2017) · Chem · doi:10.1016/j.chempr.2017.02.009 · Cited by 345 · see citing works
Forward Error Correction for DNA Data Storage
Blawat, M., Gaedke, K., Hütter, I., Chen, X.-M., Turczyk, B., Inverso, S., Pruitt, B. W., & Church, G. M. (2016) · Procedia Computer Science · doi:10.1016/j.procs.2016.05.398 · Cited by 333 · see citing works
Zhirnov, V., Zadegan, R. M., Sandhu, G. S., Church, G. M., & Hughes, W. L. (2016) · Nature Materials · doi:10.1038/nmat4594 · Cited by 307 · see citing works
Self-citationEnzymatic DNA synthesis for digital information storage.
Lee, H. H., Kalhor, R., Goela, N., Bolot, J., & Church, G. M. (2018) · doi:10.1101/348987 · Cited by 265 · see citing works
Optical imaging of individual biomolecules in densely packed clusters
Dai, M., Jungmann, R., & Yin, P. (2016) · Nature Nanotechnology · doi:10.1038/nnano.2016.95 · Cited by 248 · see citing works
Molecular recordings by directed CRISPR spacer acquisition
Shipman, S. L., Nivala, J., Macklis, J. D., & Church, G. M. (2016) · Science · doi:10.1126/science.aaf1175 · Cited by 243 · see citing works
Up to 100-fold speed-up and multiplexing in optimized DNA-PAINT
Strauss, S., & Jungmann, R. (2020) · Nature Methods · doi:10.1038/s41592-020-0869-x · Cited by 198 · see citing works
Surface‐Assisted Large‐Scale Ordering of DNA Origami Tiles
Rafat, A. A., Pirzer, T., Scheible, M. B., Kostina, A., & Simmel, F. C. (2014) · Angewandte Chemie International Edition · doi:10.1002/anie.201403965 · Cited by 183 · see citing works
DNA origami cryptography for secure communication
Zhang, Y., Wang, F., Chao, J., Xie, M., Liu, H., Pan, M., Kopperger, E., Liu, X., Li, Q., Shi, J., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-13517-3 · Cited by 163 · see citing works
Jiménez‐Guerrero, I., Acosta‐Jurado, S., del Cerro, P., Navarro‐Gómez, P., López‐Baena, F. J., Ollero, F. J., Vinardell, J., & Pérez‐Montaño, F. (2017) · Genes · doi:10.3390/genes9010001 · Cited by 135 · see citing works
124-Color Super-resolution Imaging by Engineering DNA-PAINT Blinking Kinetics
Wade, O. K., Woehrstein, J. B., Nickels, P. C., Strauss, S., Stehr, F., Stein, J., Schueder, F., Strauss, M. T., Ganji, M., Schnitzbauer, J., et al. (2019) · Nano Letters · doi:10.1021/acs.nanolett.9b00508 · Cited by 120 · see citing works
DNA-Based Super-Resolution Microscopy: DNA-PAINT
Nieves, D. J., Gaus, K., & Baker, M. A. B. (2018) · Genes · doi:10.3390/genes9120621 · Cited by 83 · see citing works
A DNA-Based Archival Storage System
Bornholt, J., Lopez, R. M., Carmean, D. M., Ceze, L., Seelig, G., & Strauß, K. (2016) · ACM SIGARCH Computer Architecture News · doi:10.1145/2980024.2872397 · Cited by 55 · see citing works
Influence of thermodynamically unfavorable secondary structures on DNA hybridization kinetics
Hata, H., Kitajima, T., & Suyama, A. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx1171 · Cited by 29 · see citing works
Boron-Implanted Silicon Substrates for Physical Adsorption of DNA Origami
Takabayashi, S., Kotani, S., Flores-Estrada, J., Spears, E., Padilla, J. E., Godwin, L., Graugnard, E., Kuang, W., Sills, S. E., & Hughes, W. L. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19092513 · Cited by 13 · see citing works
Self-citationGreengard, S. (2019) · Communications of the ACM · doi:10.1145/3311723 · Cited by 3 · see citing works
Fountain-code Aided File Transfer in Vehicular Delay Tolerant Networks
Langari, S. M. M., YOUSEFI, S., & Jabbehdari, S. (2013) · Advances in Electrical and Computer Engineering · doi:10.4316/aece.2013.04020 · Cited by 2 · see citing works
Green, C. M. (2019) · doi:10.18122/td/1639/boisestate · Cited by 2 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 3
- [1]Victor, Z. 2018 Semiconductor Synthetic Biology Roadmap. 1–36 10.13140/RG.2.2.34352.40960. (2018). · DOI
- [2]ITRS. International Technology Roadmap for Semiconductors, 2015 Results. ITRPV vol. 0 1–37 https://www.semiconductors.org/wp-content/uploads/2018/06/0_2015-ITRS-2.0-Executive-Report-1.pdf. Accessed 1st March 2021. (2016).
- [18]Luby, M. LT codes. In Proceedings of the 43rd Annual IEEE Symposium on Foundations of Computer Science (IEEE, 2002) 271–280 (IEEE, 2002).
Cited by
Sorted by citations
Emerging Approaches to DNA Data Storage: Challenges and Prospects
Doricchi, A., Platnich, C. M., Gimpel, A., Horn, F., Earle, M., Lanzavecchia, G., Cortajarena, A. L., Liz-Marzán, L. M., Liu, N., Heckel, R., et al. (2022) · ACS Nano · doi:10.1021/acsnano.2c06748 · Cited by 235 · see citing works
Preservation and Encryption in DNA Digital Data Storage
Zhang, Y., Ren, Y., Liu, Y., Wang, F., Zhang, H., & Liu, K. (2022) · ChemPlusChem · doi:10.1002/cplu.202200183 · Cited by 28 · see citing works
Project Silica: Towards Sustainable Cloud Archival Storage in Glass
Anderson, P., Aranas, E., Assaf, Y., Behrendt, R., Black, R., Caballero, M., Cameron, P., Canakci, B., Chatzieleftheriou, A., Clarke, R., et al. (2025) · ACM Transactions on Storage · doi:10.1145/3708996 · Cited by 13 · see citing works
- Authors
- Dickinson, G. D., Mortuza, G. M., Clay, W., Piantanida, L., Green, C. M., Watson, C., Hayden, E. J., Andersen, T., Kuang, W., Graugnard, E., Zadegan, R., & Hughes, W. L.
- Affiliations
- Boise State University (US)
- Corresponding author
- Hughes, William L.
- ORCID
- Venue
- Nature Communications
- Published
- 2021-04-22
- Volume
- 12
- Issue
- 1
- Pages
- 2371-2371
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC8062470
- OpenAlex
- W3157019608
- Cited by
- 82
- References
- 36
- Citations by year
- 2026: 12 · 2025: 19 · 2024: 17 · 2023: 16 · 2022: 13 · 2021: 5
- FWCI
- 4.00
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- ScholarWorks (Boise State University) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Science Foundation (ECCS 1807809)
- Semiconductor Research Corporation
- Idaho Global Entrepreneurial Mission and Higher Education Research Council
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › DNA and Biological Computing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced biosensing and bioanalysis techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Algorithms and Data Compression
- Keywords
- DNA data storage, DNA origami, DNA-PAINT, fluorescent probe binding, error correction, fountain codes, non-volatile memory, data retention
- MeSH terms
- Proof of Concept Study, Algorithms, DNA, Single-Stranded, Nucleic Acid Conformation, Information Storage and Retrieval, Nanotechnology, Nanostructures
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review