Skip to main content

Thank you for visiting nature.com. 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.

  • Protocol
  • Published:

An unbiased method for evaluating the genome-wide specificity of base editors in rice

Abstract

Base editors can achieve targeted genomic base conversion. However, the off-target issue is one of the major concerns in their application. Whole-genome sequencing (WGS) at the individual level can provide direct information on genome-wide specificity, but it is difficult to distinguish true off-target single-nucleotide variants (SNVs) induced by base editors from background variation. Here we describe an unbiased WGS method for evaluating the specificity of base editors in rice. In this protocol, we describe the experimental design and provide details of vector construction, rice transformation and tissue culture, as well as a comprehensive WGS data analysis pipeline for overcoming two related core problems in various plant species: high background mutation rates and the heterogeneity of examined populations. Using this protocol, researchers can straightforwardly and accurately assess the genome-wide specificity of base editors and other genome editing tools in 12–15 weeks.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Overview of WGS for evaluating the genome-wide specificity of base editors.
Fig. 2: Agrobacterium tumefaciens-mediated transformation of rice calluses and plant regeneration.
Fig. 3: Typical results.
Fig. 4: Saturation analysis of WGS depth and numbers of sequenced wild-type plants.

Similar content being viewed by others

Data availability

All the sequence data have been deposited in NCBI BioProject under accession code PRJNA522656, in which CBE refers to BE3 and HF1-CBE to HF1-BE3.

Code availability

All the code used in this protocol is available on GitHub at: https://github.com/ReiGao/GWSBE. The code in this protocol has been peer-reviewed.

References

  1. Komor, A. C., Kim, Y. B., Packer, M. S., Zuris, J. A. & Liu, D. R. Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage. Nature 533, 420–424 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. Gaudelli, N. M. et al. Programmable base editing of A•T to G•C in genomic DNA without DNA cleavage. Nature 551, 464–471 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Nishida, K. et al. Targeted nucleotide editing using hybrid prokaryotic and vertebrate adaptive immune systems. Science 353, 6305 (2016).

    Google Scholar 

  4. Kim, K. et al. Highly efficient RNA-guided base editing in mouse embryos. Nat. Biotechnol. 35, 435–437 (2017).

    CAS  PubMed  Google Scholar 

  5. Liang, P. et al. Effective gene editing by high-fidelity base editor 2 in mouse zygotes. Protein Cell 8, 601–611 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Liu, Z. Q. et al. Highly efficient RNA-guided base editing in rabbit. Nat. Commun. 9, 2717 (2018).

    PubMed  PubMed Central  Google Scholar 

  7. Tanaka, S. et al. In vivo targeted single-nucleotide editing in zebrafish. Sci. Rep. 8, 11423 (2018).

    PubMed  PubMed Central  Google Scholar 

  8. Zhang, Y. H. et al. Programmable base editing of zebrafish genome using a modified CRISPR-Cas9 system. Nat. Commun. 8, 118 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Zong, Y. et al. Precise base editing in rice, wheat and maize with a Cas9-cytidine deaminase fusion. Nat. Biotechnol. 35, 438–440 (2017).

    CAS  PubMed  Google Scholar 

  10. Li, C. et al. Expanded base editing in rice and wheat using a Cas9-adenosine deaminase fusion. Genome. Biol. 19, 59 (2018).

    PubMed  PubMed Central  Google Scholar 

  11. Zong, Y. et al. Efficient C-to-T base editing in plants using a fusion of nCas9 and human APOBEC3A. Nat. Biotechnol. 36, 950–953 (2018).

    CAS  Google Scholar 

  12. Komor, A. C., Badran, A. H. & Liu, D. R. CRISPR-based technologies for the manipulation of eukaryotic genomes. Cell 168, 20–36 (2017).

    CAS  PubMed  Google Scholar 

  13. Rees, H. A. & Liu, D. R. Base editing: precision chemistry on the genome and transcriptome of living cells. Nat. Rev. Genet. 19, 770–788 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Jiao, R. & Gao, C. Anything impossible with CRISPR/Cas9? Sci. China Life. Sci. 60, 445–446 (2017).

    PubMed  Google Scholar 

  15. Jinek, M. et al. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337, 816–821 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Tsai, S. Q. & Joung, J. K. Defining and improving the genome-wide specificities of CRISPR-Cas9 nucleases. Nat. Rev. Genet. 17, 300–312 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Tycko, J., Myer, V. E. & Hsu, P. D. Methods for optimizing CRISPR-Cas9 genome editing specificity. Mol. Cell. 63, 355–370 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Zhang, F. Development of CRISPR-Cas systems for genome editing and beyond. Q. Rev. Biophys. 52, E6 (2019).

  19. Jin, S. et al. Cytosine, but not adenine, base editors induce genome-wide off-target mutations in rice. Science 364, 292–295 (2019).

    CAS  PubMed  Google Scholar 

  20. Zuo, E. W. et al. Cytosine base editor generates substantial off-target single-nucleotide variants in mouse embryos. Science 364, 289–292 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Lee, H. K., Smith, H. E., Liu, C., Willi, M. & Hennighausen, L. Cytosine base editor 4 but not adenine base editor generates off-target mutations in mouse embryos. Commun. Biol. 3, 19 (2020).

    PubMed  PubMed Central  Google Scholar 

  22. Doman, J. L., Raguram, A., Newby, G. A. & Liu, D. R. Evaluation and minimization of Cas9-independent off-target DNA editing by cytosine base editors. Nat. Biotechnol. 3, 620-628 (2020).

  23. Gabriel, R. et al. An unbiased genome-wide analysis of zinc-finger nuclease specificity. Nat. Biotechnol. 29, 816–823 (2011).

    CAS  PubMed  Google Scholar 

  24. Wang, X. L. et al. Unbiased detection of off-target cleavage by CRISPR-Cas9 and TALENs using integrase-defective lentiviral vectors. Nat. Biotechnol. 33, 175–178 (2015).

    CAS  PubMed  Google Scholar 

  25. Frock, R. L. et al. Genome-wide detection of DNA double-stranded breaks induced by engineered nucleases. Nat. Biotechnol. 33, 179–186 (2015).

    CAS  PubMed  Google Scholar 

  26. Kim, D. et al. Digenome-seq: genome-wide profiling of CRISPR-Cas9 off-target effects in human cells. Nat. Methods 12, 237–243 (2015).

    CAS  PubMed  Google Scholar 

  27. Kim, D., Kim, S., Kim, S., Park, J. & Kim, J. S. Genome-wide target specificities of CRISPR-Cas9 nucleases revealed by multiplex Digenome-seq. Genome Res. 26, 406–415 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Cameron, P. et al. Mapping the genomic landscape of CRISPR-Cas9 cleavage. Nat. Methods 14, 600–606 (2017).

    CAS  PubMed  Google Scholar 

  29. Tsai, S. Q. et al. CIRCLE-seq: a highly sensitive in vitro screen for genome-wide CRISPR-Cas9 nuclease off-targets. Nat. Methods 14, 607–614 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Crosetto, N. et al. Nucleotide-resolution DNA double-strand break mapping by next-generation sequencing. Nat. Methods 10, 361–365 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Tsai, S. Q. et al. GUIDE-seq enables genome-wide profiling of off-target cleavage by CRISPR-Cas nucleases. Nat. Biotechnol. 33, 187–197 (2015).

    CAS  PubMed  Google Scholar 

  32. Wienert, B. et al. Unbiased detection of CRISPR off-targets in vivo using DISCOVER-Seq. Science 364, 286–289 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Li, J. et al. Whole genome sequencing reveals rare off-target mutations and considerable inherent genetic or/and somaclonal variations in CRISPR/Cas9-edited cotton plants. Plant Biotechnol. J. 17, 858–868 (2019).

    CAS  PubMed  Google Scholar 

  34. Willi, M., Smith, H. E., Wang, C., Liu, C. & Hennighausen, L. Mutation frequency is not increased in CRISPR-Cas9-edited mice. Nat. Methods 15, 756–758 (2018).

    CAS  PubMed  Google Scholar 

  35. Iyer, V. et al. No unexpected CRISPR-Cas9 off-target activity revealed by trio sequencing of gene-edited mice. PLoS Genet 14, e1007503 (2018).

    PubMed  PubMed Central  Google Scholar 

  36. Tang, X. et al. A large-scale whole-genome sequencing analysis reveals highly specific genome editing by both Cas9 and Cpf1 (Cas12a) nucleases in rice. Genome. Biol. 19, 84 (2018).

    PubMed  PubMed Central  Google Scholar 

  37. Landrum, M. J. et al. ClinVar: public archive of interpretations of clinically relevant variants. Nucleic Acids Res. 44, D862–D868 (2016).

    CAS  PubMed  Google Scholar 

  38. Jackson, S. A. Rice: The first crop genome. Rice 9, 14 (2016).

    PubMed  PubMed Central  Google Scholar 

  39. Shukla, V. K. et al. Precise genome modification in the crop species Zea mays using zinc-finger nucleases. Nature 459, 437–441 (2009).

    CAS  PubMed  Google Scholar 

  40. Townsend, J. A. et al. High-frequency modification of plant genes using engineered zinc-finger nucleases. Nature 459, 442–445 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Li, T., Liu, B., Spalding, M. H., Weeks, D. P. & Yang, B. High-efficiency TALEN-based gene editing produces disease-resistant rice. Nat. Biotechnol. 30, 390–392 (2012).

    CAS  PubMed  Google Scholar 

  42. Wang, Y. P. et al. Simultaneous editing of three homoeoalleles in hexaploid bread wheat confers heritable resistance to powdery mildew. Nat. Biotechnol. 32, 947–951 (2014).

    CAS  PubMed  Google Scholar 

  43. Wood, A. J. et al. Targeted genome editing across species using ZFNs and TALENs. Science 333, 307–307 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Anzalone, A. V. et al. Search-and-replace genome editing without double-strand breaks or donor DNA. Nature 576, 149–157 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Cong, L. et al. Multiplex genome engineering using CRISPR/Cas systems. Science 339, 819–823 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Yang, L. H. et al. Targeted and genome-wide sequencing reveal single nucleotide variations impacting specificity of Cas9 in human stem cells. Nat. Commun. 5, 5507 (2014).

    CAS  PubMed  Google Scholar 

  47. Feng, Z. Y. et al. Multigeneration analysis reveals the inheritance, specificity, and patterns of CRISPR/Cas-induced gene modifications in Arabidopsis. Proc. Natl Acad. Sci. USA 111, 4632–4637 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Feng, C. et al. High-efficiency genome editing using a dmc1 promoter-controlled CRISPR/Cas9 system in maize. Plant Biotechnol. J. 16, 1848–1857 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Nekrasov, V. et al. Rapid generation of a transgene-free powdery mildew resistant tomato by genome deletion. Sci. Rep. 7, 482 (2017).

    PubMed  PubMed Central  Google Scholar 

  50. Liang, P. et al. Genome-wide profiling of adenine base editor specificity by EndoV-seq. Nat. Commun. 10, 67 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Kim, D., Kim, D. E., Lee, G., Cho, S. I. & Kim, J. S. Genome-wide target specificity of CRISPR RNA-guided adenine base editors. Nat. Biotechnol 37, 430–435 (2019).

    CAS  PubMed  Google Scholar 

  52. Kim, D. et al. Genome-wide analysis reveals specificities of Cpf1 endonucleases in human cells. Nat. Biotechnol. 34, 863–868 (2016).

    CAS  PubMed  Google Scholar 

  53. Kim, D. & Kim, J. S. DIG-seq: a genome-wide CRISPR off-target profiling method using chromatin DNA. Genome Res. 28, 1894–1900 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Crosetto, N. et al. Nucleotide-resolution DNA double-strand break mapping by next-generation sequencing. Nat. Methods 10, 361–365 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Goodstein, D. M. et al. Phytozome: a comparative platform for green plant genomics. Nucleic Acids Res. 40, D1178–D1186 (2012).

    CAS  PubMed  Google Scholar 

  56. Bae, S., Park, J. & Kim, J. S. Cas-OFFinder: a fast and versatile algorithm that searches for potential off-target sites of Cas9 RNA-guided endonucleases. Bioinformatics 30, 1473–1475 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Zhang, Y., Li, J. & Gao, C. Generation of stable transgenic rice (Oryza sativa L.) by Agrobacterium-mediated transformation. Curr. Protoc. Plant Biol. 1, 235–246 (2016).

    CAS  PubMed  Google Scholar 

  58. Wei, F. J. et al. Somaclonal variation does not preclude the use of rice transformants for genetic screening. Plant J. 85, 648–659 (2016).

    CAS  PubMed  Google Scholar 

  59. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Li, H. & Durbin, R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 26, 589–595 (2010).

    PubMed  PubMed Central  Google Scholar 

  61. Genomes Project Consortium . et al. A global reference for human genetic variation. Nature 526, 68–74 (2015).

    Google Scholar 

  62. McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Wilm, A. et al. LoFreq: a sequence-quality aware, ultra-sensitive variant caller for uncovering cell-population heterogeneity from high-throughput sequencing datasets. Nucleic Acids Res. 40, 11189–11201 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Kim, S. et al. Strelka2: fast and accurate calling of germline and somatic variants. Nat. Methods 15, 591–594 (2018).

    CAS  PubMed  Google Scholar 

  65. Shan, Q., Wang, Y., Li, J. & Gao, C. Genome editing in rice and wheat using the CRISPR/Cas system. Nat. Protoc. 9, 2395–2410 (2014).

    CAS  PubMed  Google Scholar 

  66. Shan, Q. et al. Rapid and efficient gene modification in rice and Brachypodium using TALENs. Mol. Plant 6, 1365–1368 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. Hiei, Y. & Komari, T. Agrobacterium-mediated transformation of rice using immature embryos or calli induced from mature seed. Nat. Protoc. 3, 824–834 (2008).

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank Y. Zhang (Department of Plant and Environmental Sciences, University of Copenhagen) for critical revision of the manuscript. This work was supported by grants from the National Natural Science Foundation of China (31788103), the Strategic Priority Research Program of the Chinese Academy of Sciences (Precision Seed Design and Breeding, XDA24020102), the National Key Research and Development Program of China (2016YFD0101804) and the R&D Program in Key Areas of Guangdong Province (2018B020202005).

Author information

Authors and Affiliations

Authors

Contributions

S.J. performed the experiments; S.J. designed figures; C.G. supervised the project; S.J., Q.G. and C.G. wrote the manuscript.

Corresponding author

Correspondence to Caixia Gao.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Protocols thanks Keiji Nishida, Pengcheng Wei and Huanbin Zhou for their contribution to the peer review of this work.

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

Related links

Key reference using this protocol

Jin, S. et al. Science 364, 292–295 (2019): https://doi.org/10.1126/science.aaw7166

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2, Supplementary Notes 1–3 and Supplementary Tables 1–4.

Reporting Summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jin, S., Gao, Q. & Gao, C. An unbiased method for evaluating the genome-wide specificity of base editors in rice. Nat Protoc 16, 431–457 (2021). https://doi.org/10.1038/s41596-020-00423-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41596-020-00423-y

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research