Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Data storage in DNA with fewer synthesis cycles using composite DNA letters

An Author Correction to this article was published on 16 September 2019

This article has been updated


The density and long-term stability of DNA make it an appealing storage medium, particularly for long-term data archiving. Existing DNA storage technologies involve the synthesis and sequencing of multiple nominally identical molecules in parallel, resulting in information redundancy. We report the development of encoding and decoding methods that exploit this redundancy using composite DNA letters. A composite DNA letter is a representation of a position in a sequence that consists of a mixture of all four DNA nucleotides in a predetermined ratio. Our methods encode data using fewer synthesis cycles. We encode 6.4 MB into composite DNA, with distinguishable composition medians, using 20% fewer synthesis cycles per unit of data, as compared to previous reports. We also simulate encoding with larger composite alphabets, with distinguishable composition deciles, to show that 75% fewer synthesis cycles are potentially sufficient. We describe applicable error-correcting codes and inference methods, and investigate error patterns in the context of composite DNA letters.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Encoding a binary message using standard and composite DNA.
Fig. 2: Encoding pipeline of a large-scale composite DNA-based data storage.
Fig. 3: Performance of a large-scale composite DNA-based storage system.
Fig. 4: Analysis of higher-resolution composite alphabets using large-scale experiments.
Fig. 5: Data storage systems based on large composite alphabets.

Data availability

All raw sequencing data are available from the European Nucleotide Archive (ENA) under accession PRJEB32427. This includes sequencing of the large-scale experiment described in Figs. 24, sequencing of the experiment with large alphabets described in Fig. 5 and sequencing of the error analysis experiment described in Fig. 5. All other data are available within the article or its supplementary information.

Code availability

All original software code included in this study is available online. Alteration of the previously published DNA fountain code to support composite DNA is available from Code used for Reed–Solomon error correction (altered from previously published code) is available from Custom code used for the analyses presented in this study is available from

Change history

  • 16 September 2019

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.


  1. 1.

    Cox, J. P. Long-term data storage in DNA. Trends Biotechnol. 19, 247–250 (2001).

    CAS  Article  Google Scholar 

  2. 2.

    Zhirnov, V., Zadegan, R. M., Sandhu, G. S., Church, G. M. & Hughes, W. L. Nucleic acid memory. Nat. Mater. 15, 366–370 (2016).

    CAS  Article  Google Scholar 

  3. 3.

    Church, G. M., Gao, Y. & Kosuri, S. Next-generation digital information storage in DNA. Science 337, 1628 (2012).

    CAS  Article  Google Scholar 

  4. 4.

    Goldman, N. et al. Towards practical, high-capacity, low-maintenance information storage in synthesized DNA. Nature 494, 77–80 (2013).

    CAS  Article  Google Scholar 

  5. 5.

    Bornholt, J. et al. Toward a DNA-based archival storage system. IEEE Micro 37, 98–104 (2017).

    Article  Google Scholar 

  6. 6.

    Tabatabaei Yazdi, S. M. H. et al. A rewritable, random-access DNA-based storage system. Sci. Rep. 5, 14138 (2015).

    CAS  Article  Google Scholar 

  7. 7.

    Erlich, Y. & Zielinski, D. DNA Fountain enables a robust and efficient storage architecture. Science 355, 950–954 (2017).

    CAS  Article  Google Scholar 

  8. 8.

    Organick, L. et al. Random access in large-scale DNA data storage. Nat. Biotechnol. 36, 242–248 (2018).

    CAS  Article  Google Scholar 

  9. 9.

    Gabrys, R., Kiah, H. M. & Milenkovic, O. Asymmetric lee distance codes for DNA-based storage. In Proc. 2015 IEEE International Symposium on Information Theory (ISIT) 909–913 (IEEE, 2015)..

  10. 10.

    Levy, M. & Yaakobi, E. Mutually uncorrelated codes for DNA storage. In Proc. 2017 IEEE International Symposium on Information Theory (ISIT) 3115–3119 (IEEE, 2017).

  11. 11.

    Lee, H. H., Kalhor, R., Goela, N., Bolot, J. & Church, G. M. Terminator-free template-independent enzymatic DNA synthesis for digital information storage. Nat. Commun. 10, 2383 (2019).

    Article  Google Scholar 

  12. 12.

    Palluk, S. et al. De novo DNA synthesis using polymerase–nucleotide conjugates. Nat. Biotechnol. 36, 645–650 (2018).

    CAS  Article  Google Scholar 

  13. 13.

    Roquet, N., Park, H. & Bhatia, S. P. Nucleic acid-based data storage. US patent 20180137418 (2017).

  14. 14.

    LeProust, E. M. et al. Synthesis of high-quality libraries of long (150mer) oligonucleotides by a novel depurination controlled process. Nucleic Acids Res. 38, 2522–2540 (2010).

    CAS  Article  Google Scholar 

  15. 15.

    Barrett, M. T. et al. Comparative genomic hybridization using oligonucleotide microarrays and total genomic DNA. Proc. Natl Acad. Sci. USA 101, 17765–17770 (2004).

    CAS  Article  Google Scholar 

  16. 16.

    Kosuri, S. & Church, G. M. Large-scale de novo DNA synthesis: technologies and applications. Nat. Methods 11, 499–507 (2014).

    CAS  Article  Google Scholar 

  17. 17.

    Choi, Y. et al. High information capacity DNA-based data storage with augmented encoding characters using degenerate bases. Sci. Rep. 9, 6582 (2019).

    Article  Google Scholar 

  18. 18.

    Grass, R. N., Heckel, R., Puddu, M., Paunescu, D. & Stark, W. J. Robust chemical preservation of digital information on DNA in silica with error-correcting codes. Angew. Chem. Int. Ed. Engl. 54, 2552–2555 (2015).

    CAS  Article  Google Scholar 

  19. 19.

    Reed, I. S. & Solomon, G. Polynomial codes over certain finite fields. J. Soc. Ind. Appl. Math. 8, 300–304 (1960).

    Article  Google Scholar 

  20. 20.

    MacKay, D. J. C. Fountain codes. IEE Proc. Comm. 152, 1062 (2005).

    Article  Google Scholar 

  21. 21.

    Jiménez-Sánchez, A. DNA computer code based on expanded genetic alphabet. Eur. J. Comput. Sci. Inf. Technol. 2, 8–20 (2014).

    Google Scholar 

  22. 22.

    Tabatabaei Yazdi, S. M. H. et al. DNA-based storage: trends and methods. IEEE Trans. Mol. Biol. Multiscale Commun. 1, 230–248 (2015).

    Article  Google Scholar 

  23. 23.

    Raviv, N., Schwartz, M. & Yaakobi, E. Rank modulation codes for DNA storage. In Proc. 2017 IEEE International Symposium on Information Theory (ISIT) 3125–3129 (IEEE, 2017).

  24. 24.

    Yazdi, S. M. H. T., Kiah, H. M., Gabrys, R. & Milenkovic, O. Mutually uncorrelated primers for DNA-based data storage. Preprint at (2017).

  25. 25.

    Takahashi, C. N., Nguyen, B. H., Strauss, K. & Ceze, L. Demonstration of end-to-end automation of DNA data storage. Sci. Rep. 9, 4998 (2019).

    Article  Google Scholar 

  26. 26.

    Hoshika, S. et al. Hachimoji DNA and RNA: a genetic system with eight building blocks. Science 363, 884–887 (2019).

    CAS  Article  Google Scholar 

  27. 27.

    Bains, W. Hybridization methods for DNA sequencing. Genomics 11, 94–301 (1991).

    Article  Google Scholar 

  28. 28.

    Pevzner, P. A. Rearrangements of DNA sequences and SBH. Comput. Chem. 18, 221–223 (1994).

    CAS  Article  Google Scholar 

  29. 29.

    Preparata, F. P. & Oliver, J. S. DNA sequencing by hybridization using semi-degenerate bases. J. Comput. Biol. 11, 753–765 (2004).

    CAS  Article  Google Scholar 

  30. 30.

    Snir, S., Yeger-Lotem, E., Chor, B., and Yakhini, Z. Using restriction enzymes to improve sequencing by hybridization. Technical report CS-2002-14 (Technion, 2002).

  31. 31.

    Chen, Z. et al. Highly accurate fluorogenic DNA sequencing with information theory-based error correction. Nat. Biotechnol. 35, 1170–1178 (2017).

    CAS  Article  Google Scholar 

  32. 32.

    Davidson, E. H. The Regulatory Genome: Gene Regulatory Networks in Development and Evolution (Academic, 2006).

  33. 33.

    Sandelin, A., Alkema, W., Engström, P., Wasserman, W. W. & Lenhard, B. JASPAR: an open-access database for eukaryotic transcription factor binding profiles. Nucleic Acids Res. 32, D91–D94 (2004).

    CAS  Article  Google Scholar 

  34. 34.

    Levy, L. et al. A synthetic oligo library and sequencing approach reveals an insulation mechanism encoded within bacterial σ54 promoters. Cell Rep. 21, 845–858 (2017).

    CAS  Article  Google Scholar 

  35. 35.

    Sharon, E. et al. Inferring gene regulatory logic from high-throughput measurements of thousands of systematically designed promoters. Nat. Biotechnol. 30, 521–530 (2012).

    CAS  Article  Google Scholar 

  36. 36.

    Gilbert, L. A. et al. CRISPR-mediated modular RNA-guided regulation of transcription in eukaryotes. Cell 154, 442–451 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Mikutis, G. et al. Silica-encapsulated DNA-based tracers for aquifer characterization. Environ. Sci. Technol. 52, 12142–12152 (2018).

    CAS  Article  Google Scholar 

  38. 38.

    Zhang, J., Kobert, K., Flouri, T. & Stamatakis, A. PEAR: a fast and accurate Illumina paired-end read merger. Bioinformatics 30, 614–620 (2014).

    CAS  Article  Google Scholar 

  39. 39.

    Shakespeare, W. The Complete Works of William Shakespeare (1994)

  40. 40.

    Huffman, D. A. A method for the construction of minimum-redundancy codes. Proc. IRE 40, 1098–1101 (1952).

    Article  Google Scholar 

Download references


We thank T. Katz-Ezov and T. Hashimshony from the Technion Genome Center for advice and assistance with oligonucleotide design and sequencing experiments. We also thank P. Weiss from Twist Bioscience for technical support and assistance with DNA synthesis. Finally, we thank the Yakhini and Amit research groups for valuable comments and discussions. L. Anavy is supported by the Adams Fellowships Program of the Israel Academy of Sciences and Humanities. This project received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement 664918 (MRG-Grammar).

Author information




L.A. and Z.Y. initiated and designed the coding and algorithmic approach. L.A. developed the software and performed data analysis. I.V. and O.A. performed the experiments. L.A., R.A. and Z.Y. wrote the manuscript. R.A. and Z.Y. supervised the study.

Corresponding authors

Correspondence to Leon Anavy or Zohar Yakhini.

Ethics declarations

Competing interests

L.A, Z.Y and R.A are the inventors of a patent application for the method described in this article. The initial filing was assigned United States Provisional Patent Application No. 62/674,114. The remaining authors declare no competing financial interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–17 and Supplementary Note

Reporting Summary

Supplementary Table 1

Physical density calculations of composite DNA storage. This includes the large-scale experiment and the dilution experiment.

Supplementary Table 2

Logical density calculations of composite DNA storage. This includes all the experiments, theoretical encodings and simulation experiments.

Supplementary Table 3

Oligonucleotide design for large-alphabet experiments and error analysis.

Supplementary Table 4

Oligonucleotide design for the large-scale composite DNA storage.

Supplementary Table 5

Oligonucleotide design for the simulations of large composite alphabet DNA storage.

Supplementary Table 6

Simulation results of large composite alphabet DNA storage

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Anavy, L., Vaknin, I., Atar, O. et al. Data storage in DNA with fewer synthesis cycles using composite DNA letters. Nat Biotechnol 37, 1229–1236 (2019).

Download citation

Further reading


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing