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.

DNA-binding-domain fusions enhance the targeting range and precision of Cas9

Abstract

The CRISPR-Cas9 system is commonly used in biomedical research; however, the precision of Cas9 is suboptimal for applications that involve editing a large population of cells (for example, gene therapy). Variations on the standard Cas9 system have yielded improvements in the precision of targeted DNA cleavage, but they often restrict the range of targetable sequences. It remains unclear whether these variants can limit lesions to a single site in the human genome over a large cohort of treated cells. Here we show that by fusing a programmable DNA-binding domain (pDBD) to Cas9 and attenuating Cas9’s inherent DNA-binding affinity, we were able to produce a Cas9-pDBD chimera with dramatically improved precision and an increased targeting range. Because the specificity and affinity of this framework can be easily tuned, Cas9-pDBDs provide a flexible system that can be tailored to achieve extremely precise genome editing at nearly any genomic locus.

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

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

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

Figure 1: Development of an SpCas9-pDBD framework.
Figure 2: Attenuating the nuclease activity of SpCas9.
Figure 3: SpCas9MT-ZFP chimeras have improved precision.
Figure 4: Deep-sequencing analysis of SpCas9MT3-ZFP chimera precision.
Figure 5: Genome-wide off-target analysis of SpCas9MT3-ZFPs by GUIDE-seq17.

Accession codes

Primary accessions

Sequence Read Archive

References

  1. Doudna, J.A. & Charpentier, E. Genome editing. The new frontier of genome engineering with CRISPR-Cas9. Science 346, 1258096 (2014).

    PubMed  Google Scholar 

  2. Sander, J.D. & Joung, J.K. CRISPR-Cas systems for editing, regulating and targeting genomes. Nat. Biotechnol. 32, 347–355 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Hsu, P.D., Lander, E.S. & Zhang, F. Development and applications of CRISPR-Cas9 for genome engineering. Cell 157, 1262–1278 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Sternberg, S.H., Redding, S., Jinek, M., Greene, E.C. & Doudna, J.A. DNA interrogation by the CRISPR RNA-guided endonuclease Cas9. Nature 507, 62–67 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Szczelkun, M.D. et al. Direct observation of R-loop formation by single RNA-guided Cas9 and Cascade effector complexes. Proc. Natl. Acad. Sci. USA 111, 9798–9803 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Anders, C., Niewoehner, O., Duerst, A. & Jinek, M. Structural basis of PAM-dependent target DNA recognition by the Cas9 endonuclease. Nature 513, 569–573 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Jiang, F., Zhou, K., Ma, L., Gressel, S. & Doudna, J.A. A Cas9–guide RNA complex preorganized for target DNA recognition. Science 348, 1477–1481 (2015).

    CAS  PubMed  Google Scholar 

  9. Hsu, P.D. et al. DNA targeting specificity of RNA-guided Cas9 nucleases. Nat. Biotechnol. 31, 827–832 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Tsai, S.Q. et al. Dimeric CRISPR RNA-guided FokI nucleases for highly specific genome editing. Nat. Biotechnol. 32, 569–576 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Zhang, Y. et al. Comparison of non-canonical PAMs for CRISPR/Cas9-mediated DNA cleavage in human cells. Sci. Rep. 4, 5405 (2014).

    PubMed  PubMed Central  Google Scholar 

  12. Gabriel, R., von Kalle, C. & Schmidt, M. Mapping the precision of genome editing. Nat. Biotechnol. 33, 150–152 (2015).

    CAS  PubMed  Google Scholar 

  13. Ledford, H. CRISPR, the disruptor. Nature 522, 20–24 (2015).

    CAS  PubMed  Google Scholar 

  14. Fu, Y. et al. High-frequency off-target mutagenesis induced by CRISPR-Cas nucleases in human cells. Nat. Biotechnol. 31, 822–826 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Lin, Y. et al. CRISPR/Cas9 systems have off-target activity with insertions or deletions between target DNA and guide RNA sequences. Nucleic Acids Res. 42, 7473–7485 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Pattanayak, V. et al. High-throughput profiling of off-target DNA cleavage reveals RNA-programmed Cas9 nuclease specificity. Nat. Biotechnol. 31, 839–843 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. 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 

  18. 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 

  19. 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 

  20. Wang, X. 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 

  21. Zhu, L.J., Holmes, B.R., Aronin, N. & Brodsky, M.H. CRISPRseek: a bioconductor package to identify target-specific guide RNAs for CRISPR-Cas9 genome-editing systems. PLoS One 9, e108424 (2014).

    PubMed  PubMed Central  Google Scholar 

  22. Zhu, L.J. Overview of guide RNA design tools for CRISPR-Cas9 genome editing technology. Front. Biol. 10, 289–296 (2015).

    CAS  Google Scholar 

  23. Brunet, E. et al. Chromosomal translocations induced at specified loci in human stem cells. Proc. Natl. Acad. Sci. USA 106, 10620–10625 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Lee, H.J., Kim, E. & Kim, J.-S. Targeted chromosomal deletions in human cells using zinc finger nucleases. Genome Res. 20, 81–89 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Fu, Y., Sander, J.D., Reyon, D., Cascio, V.M. & Joung, J.K. Improving CRISPR-Cas nuclease specificity using truncated guide RNAs. Nat. Biotechnol. 32, 279–284 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Cho, S.W. et al. Analysis of off-target effects of CRISPR/Cas-derived RNA-guided endonucleases and nickases. Genome Res. 24, 132–141 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Ran, F.A. et al. Double nicking by RNA-guided CRISPR Cas9 for enhanced genome editing specificity. Cell 154, 1380–1389 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Mali, P. et al. CAS9 transcriptional activators for target specificity screening and paired nickases for cooperative genome engineering. Nat. Biotechnol. 31, 833–838 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Guilinger, J.P., Thompson, D.B. & Liu, D.R. Fusion of catalytically inactive Cas9 to FokI nuclease improves the specificity of genome modification. Nat. Biotechnol. 32, 577–582 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Zetsche, B., Volz, S.E. & Zhang, F. A split-Cas9 architecture for inducible genome editing and transcription modulation. Nat. Biotechnol. 33, 139–142 (2015).

    CAS  PubMed  Google Scholar 

  31. Nihongaki, Y., Kawano, F., Nakajima, T. & Sato, M. Photoactivatable CRISPR-Cas9 for optogenetic genome editing. Nat. Biotechnol. 33, 755–760 (2015).

    CAS  PubMed  Google Scholar 

  32. Wright, A.V. et al. Rational design of a split-Cas9 enzyme complex. Proc. Natl. Acad. Sci. USA 112, 2984–2989 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Davis, K.M., Pattanayak, V., Thompson, D.B., Zuris, J.A. & Liu, D.R. Small molecule-triggered Cas9 protein with improved genome-editing specificity. Nat. Chem. Biol. 11, 316–318 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Kleinstiver, B.P. et al. Engineered CRISPR-Cas9 nucleases with altered PAM specificities. Nature 523, 481–485 (2015).

    PubMed  PubMed Central  Google Scholar 

  35. Kim, S., Kim, D., Cho, S.W., Kim, J. & Kim, J.-S. Highly efficient RNA-guided genome editing in human cells via delivery of purified Cas9 ribonucleoproteins. Genome Res. 24, 1012–1019 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Ramakrishna, S. et al. Gene disruption by cell-penetrating peptide-mediated delivery of Cas9 protein and guide RNA. Genome Res. 24, 1020–1027 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Zuris, J.A. et al. Cationic lipid-mediated delivery of proteins enables efficient protein-based genome editing in vitro and in vivo. Nat. Biotechnol. 33, 73–80 (2015).

    CAS  PubMed  Google Scholar 

  38. Tsai, S.Q. & Joung, J.K. What's changed with genome editing? Cell Stem Cell 15, 3–4 (2014).

    CAS  PubMed  Google Scholar 

  39. Urnov, F.D., Rebar, E.J., Holmes, M.C., Zhang, H.S. & Gregory, P.D. Genome editing with engineered zinc finger nucleases. Nat. Rev. Genet. 11, 636–646 (2010).

    CAS  PubMed  Google Scholar 

  40. Joung, J.K. & Sander, J.D. TALENs: a widely applicable technology for targeted genome editing. Nat. Rev. Mol. Cell Biol. 14, 49–55 (2013).

    CAS  PubMed  Google Scholar 

  41. Persikov, A.V. et al. A systematic survey of the Cys2His2 zinc finger DNA-binding landscape. Nucleic Acids Res. 43, 1965–1984 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Hubbard, B.P. et al. Continuous directed evolution of DNA-binding proteins to improve TALEN specificity. Nat. Methods 12, 939–942 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Boissel, S. et al. megaTALs: a rare-cleaving nuclease architecture for therapeutic genome engineering. Nucleic Acids Res. 42, 2591–2601 (2014).

    CAS  PubMed  Google Scholar 

  44. Khalil, A.S. et al. A synthetic biology framework for programming eukaryotic transcription functions. Cell 150, 647–658 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Meckler, J.F. et al. Quantitative analysis of TALE-DNA interactions suggests polarity effects. Nucleic Acids Res. 41, 4118–4128 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Wilson, K.A., Chateau, M.L. & Porteus, M.H. Design and development of artificial zinc finger transcription factors and zinc finger nucleases to the hTERT locus. Mol. Ther. Nucleic Acids 2, e87 (2013).

    PubMed  PubMed Central  Google Scholar 

  47. Atkinson, H. & Chalmers, R. Delivering the goods: viral and non-viral gene therapy systems and the inherent limits on cargo DNA and internal sequences. Genetica 138, 485–498 (2010).

    CAS  PubMed  Google Scholar 

  48. Klemm, J.D. & Pabo, C.O. Oct-1 POU domain-DNA interactions: cooperative binding of isolated subdomains and effects of covalent linkage. Genes Dev. 10, 27–36 (1996).

    CAS  PubMed  Google Scholar 

  49. Hou, Z. et al. Efficient genome engineering in human pluripotent stem cells using Cas9 from Neisseria meningitidis. Proc. Natl. Acad. Sci. USA 110, 15644–15649 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Ran, F.A. et al. In vivo genome editing using Staphylococcus aureus Cas9. Nature 520, 186–191 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Kearns, N.A. et al. Cas9 effector-mediated regulation of transcription and differentiation in human pluripotent stem cells. Development 141, 219–223 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Villefranc, J.A., Amigo, J. & Lawson, N.D. Gateway compatible vectors for analysis of gene function in the zebrafish. Dev. Dyn. 236, 3077–3087 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Gupta, A. et al. An optimized two-finger archive for ZFN-mediated gene targeting. Nat. Methods 9, 588–590 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Zhu, C. et al. Using defined finger-finger interfaces as units of assembly for constructing zinc-finger nucleases. Nucleic Acids Res. 41, 2455–2465 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Cermak, T. et al. Efficient design and assembly of custom TALEN and other TAL effector-based constructs for DNA targeting. Nucleic Acids Res. 39, e82 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Kok, F.O., Gupta, A., Lawson, N.D. & Wolfe, S.A. Construction and application of site-specific artificial nucleases for targeted gene editing. Methods Mol. Biol. 1101, 267–303 (2014).

    CAS  PubMed  Google Scholar 

  57. Gupta, A. et al. Targeted chromosomal deletions and inversions in zebrafish. Genome Res. 23, 1008–1017 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Schneider, C.A., Rasband, W.S. & Eliceiri, K.W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  59. Gupta, A., Meng, X., Zhu, L.J., Lawson, N.D. & Wolfe, S.A. Zinc finger protein-dependent and -independent contributions to the in vivo off-target activity of zinc finger nucleases. Nucleic Acids Res. 39, 381–392 (2011).

    CAS  PubMed  Google Scholar 

  60. Ihaka, R. & Gentleman, R.R. A language for data analysis and graphics. J. Comput. Graph. Stat. 5, 299–314 (1996).

    Google Scholar 

  61. Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Series B Stat. Methodol. 57, 289–300 (1995).

    Google Scholar 

  62. Zhu, L.J. et al. ChIPpeakAnno: a Bioconductor package to annotate ChIP-seq and ChIP-chip data. BMC Bioinformatics 11, 237 (2010).

    PubMed  PubMed Central  Google Scholar 

  63. Zhu, L.J. Integrative analysis of ChIP-chip and ChIP-seq dataset. in Methods in Molecular Biology 1067 (eds. Lee, T.-L. & Shui Luk, A.C.) 105–124 (Humana Press, 2013).

Download references

Acknowledgements

We thank M. Porteus (Stanford Medicine, Stanford, California, USA) for GFP reporter vector M427, N. Rhind for the use of his FACS machine, E. Kittler and the UMass Medical School Deep Sequencing Core for their assistance with the Illumina sequencing, and E. Sontheimer for insightful discussions. All new reagents described in this work have been deposited with the nonprofit plasmid-distribution service Addgene. This work was supported by the US National Institutes of Health (grant R01AI117839 to S.A.W. and J. Luban, grant U01HG007910 to M.G. and J. Luban, and grant R01HL093766 to S.A.W. and N. Lawson).

Author information

Authors and Affiliations

Authors

Contributions

M.F.B. and A.G. performed all cell-based experiments. A.G.D., M.G. and L.J.Z. performed the bioinformatic analysis. S.O. and M.H.B. optimized the GFP reporter assay. M.F.B., A.G., L.J.Z. and S.A.W. directed the research and interpreted experiments. M.F.B., A.G. and S.A.W. wrote the manuscript with input from all the other authors.

Corresponding author

Correspondence to Scot A Wolfe.

Ethics declarations

Competing interests

The authors have filed patent applications related to genome engineering technologies. S.A.W. is a consultant for Editas Medicine.

Integrated supplementary information

Supplementary Figure 1 Overview of the distribution of potential SpCas9 off-target sites within the human genome.

a) Schematic of the SpCas9:sgRNA system and the two sequential stages of licensing required for cleavage: Stage 1 - PAM recognition (nGG is highly preferred) and Stage 2 - complementary R-loop formation between the 20 nucleotide guide RNA and the interrogated DNA sequence. b) Genome-wide analysis using CRISPRseek28 of the potential off target sites for a representative set of 124,793 guide RNAs targeting human exons sequences. Guides were binned based on the predicted off-target site with the smallest number of mismatches to the guide sequence. A perfect match indicates the presence of an off-target site with a perfect guide match (magenta wedge). Only 1.6% of these guide sequences do not have an off-target site with 3 or fewer mismatches to the guide sequence (teal wedge). This subset would be the best candidates for precise genome editing. The vast majority of guides typically have many potential off-target sequences with 3 or fewer mismatches. c) Genome-wide analysis of the minimum number of mismatches in off-target sites for a representative set of 55,687 guide RNAs targeting human promoter regions (binned as describe above). Only 1% of these guide sequences do not have an off-target site with 3 or fewer mismatches to the guide sequence (teal wedge). d,e) Guide RNAs targeting gene exons (d) or promoters (e) with no predicted off-targets with <= 3 mismatches (teal wedge from b,c) are analyzed for off-target sites with potential bulges in the sgRNA:DNA heteroduplex29. Magenta wedges indicate the fraction of guides that have one or more off-target sites that have perfect complementarity with the exception of a single bulge.

Supplementary Figure 2 Structural modeling of SpCas9-Zif268.

A hybrid model containing the structure of SpCas930 (grey, PAM recognition residues magenta) with an sgRNA (20 nucleotide guide region cyan, remaining nucleotides red) and complementary target DNA (black) with the structure of Zif26831 (orange) placed with a binding site 11 bp from the PAM recognition sequence (Watson strand), where the two structures were superimposed on a B-DNA model constructed using 3DNA32. In parallel with the spacing parameter analysis in Figure 1, the structural model suggests that there is ample room for a ZFP to dock proximally to SpCas9 downstream of the PAM element.

Supplementary Figure 3 Protein expression analysis of SpCas9 and SpCas9-Zif268 and SpCas9-TAL268 platforms.

HEK293T cells are transfected with the indicated Cas9 plasmid (see methods for details), which has triple HA-tag (Supplementary Note). (Top) Full length protein is probed with anti-HA antibody. (Bottom) Alpha-tubulin is used as loading control.

Supplementary Figure 4 Activity profile of SpCas9-Zif268 with truncated guide

Activity profile of SpCas9 (blue) and SpCas9-Zif268 (red) in the GFP reporter assay33 with sgRNAs of various lengths truncated from the 5’ end of the guide and an nGG PAM target site. Data are from three independent biological replicates performed on different days in HEK293T cells. Error bars indicate standard error of the mean.

Supplementary Figure 5 Activity profile of SpCas9-TAL268.

Activity profile of SpCas9 (blue) and SpCas9-TAL268 (brown) in the GFP reporter assay with sgRNAs of 20nt vs 16nt lengths on nGG, nAG, nGA, nGC PAM target sites. Data are from three independent biological replicates performed on different days in HEK293T cells. Error bars indicate standard error of the mean.

Supplementary Figure 6 Activity of PAM mutants on different sequences.

a) Local sequences of the PAM interacting domain mutants at positions 1333 or 1335 of SpCas9 examined in this study. b) Analysis of SpCas9 mutant activity on different nGn or nnG PAM-containing target sites in the GFP reporter assay. Mutations that alter the interaction of R1333 with its guanine contact (nGn, teal) reveal modest activity at nnG PAMs. Correspondingly, mutations that alter the interaction of R1335 with its guanine contact (nnG, magenta) reveal modest activity at nGn PAMs. Data are from three independent biological replicates performed on different days in HEK293T cells. Error bars indicate standard error of the mean.

Supplementary Figure 7 Genomic activity profile of SpCas9 mutants

Analysis of the genomic activity profile of SpCas9 mutants (MT1, MT2, MT3 & MT4) independently and as SpCas9-Zif268 fusions at the PLXNB2 locus at a target site with an nGG PAM and a Zif268 binding site 11 bp away on the Watson strand. T7EI assay data from PCR products spanning the target site in three independent biological replicates (Rep1, Rep2, Rep3) performed on different days in HEK293T cells. Cleaved products are indicated by magenta arrowheads.

Supplementary Figure 8 Analysis of the genomic activity profile of SpCas9MT1 at TS2, TS3 and TS4 sites.

T7EI assay data from PCR products spanning the target site in three independent biological replicates (Rep1, Rep2, Rep3) performed on different days in HEK293T cells. Cleaved products are indicated by magenta arrowheads.

Supplementary Figure 9 Analysis of the genomic activity profile of SpCas9MT3-ZFPDCLK2 and SpCas9MT3-ZFPF9

Activity of SpCas9MT3-ZFPDCLK2 and SpCas9MT3-ZFPF9 at DNAJC6 and PLXDC2 sites respectively. These sequences have compatible binding sites for the DCLK27 and Factor IX1 ZFPs. T7EI assay data from PCR products spanning the target site from single experiment done in HEK293T cells. Cleaved products are indicated by magenta arrowheads. Similar analysis of SpCas9MT3-ZFPHEBP2 (targeting a compatible binding site for the HEBP2 ZFP6) at GPRC5B did not detect any lesions for this SpCas9MT3-ZFP fusion (data not shown).

Supplementary Figure 10 T7EI activity profile of SpCas9MT3-ZFPTS3 at the TS3 genomic locus as a function of the number of incorporated fingers.

Both Cas9WT and SpCas9MT3-ZFPTS3 with four fingers (F1-4) achieve efficient target cleavage. Removing a single finger from either end of the zinc finger array (F1-3 or F2-4) dramatically reduces the activity of the SpCas9MT3-ZFP chimera. Cleaved products are indicated by magenta arrowheads. The bar graph displays the mean lesion rate in three independent biological replicates (Rep1, Rep2, Rep3) performed on different days in HEK293T cells. Error bars indicate standard error of the mean.

Supplementary Figure 11 Analysis of the genomic activity profile of SpCas9MT3-TALETS3 and SpCas9MT3-TALETS4 at the TS3 and TS4 sites.

An arrow indicates the strand (Watson) of the highlighted sequence that is bound by the TALE. Two different TALE repeat lengths (9.5 and 15.5) were examined at each target site. T7EI assay data from PCR products spanning the target site in three independent biological replicates (Rep1, Rep2, Rep3) performed on different days in HEK293T cells. Cleaved products are indicated by magenta arrowheads.

Supplementary Figure 12 Activity profile of SpCas9MT3-ZFPTS3/TS4 with tru-sgRNAs34.

a) Nuclease activity based on T7EI assay for SpCas9WT and SpCas9MT3-ZFPTS3 with a 17 nucleotide truncated guide at the TS3 target site. b) Nuclease activity based on T7EI assay for SpCas9WT and SpCas9MT3-ZFPTS4 with an 18 nucleotide truncated guide at the TS4 target site. Cleaved products are indicated by magenta arrowheads. c) Target sites for the TS3 and TS4 tru-sgRNAs and graph showing the average activity at each target site in three independent biological replicates performed on different days in HEK293T cells. Error bars indicate standard error of the mean. For both TS3 and TS4, the SpCas9MT3-ZFP chimera is more sensitive to the truncation of the guide sequence, which is consistent with the greater sensitivity of this system to guide mismatches.

Supplementary Figure 13 Genomic sequence of OT2-2.

The sequence complementary to the guide is underlined with the two mismatched positions in bold. The nGG PAM is red and the potential ZFPTS2 binding site highlighted in yellow. Below the genomic sequence is predicted consensus recognition motif and sequence logo for ZFPTS2 based on a Random Forest model of ZFP recognition35. The predicted recognition motif only differs substantially at one position in the finger 4 binding site (C versus A).

Supplementary Figure 14 T7EI activity profile of SpCas9MT3-ZFPTS2 at the TS2 genomic locus and OT2-2 as a function of the number of fingers.

a) Both Cas9WT and SpCas9MT3-ZFPTS2 with four fingers (F1-4) result in efficient cleavage at the TS2 target site (magenta arrowheads indicate cleaved products). Removing a single finger from either end of the zinc finger array (F1-3 or F2-4) at most modestly reduces activity of the SpCas9MT3-ZFP chimera. Removing a both terminal fingers from the zinc finger array (F2-3) dramatically reduces activity of the SpCas9MT3-ZFP chimera. Construction of an alternate ZFP (TS2*) that recognizes an overlapping target site can also promote target cleavage. b) Both Cas9WT and SpCas9MT3-ZFPTS2 with four fingers (F1-4) result in efficient cleavage at the OT2-2 off-target site (magenta arrowheads indicate cleaved products). Removing a single finger from either end of the zinc finger array (F1-3 or F2-4) dramatically reduces activity of the SpCas9MT3-ZFP chimera. As does the utilization of an alternate ZFP (TS2*) that recognizes a different target site. Data from three independent biological replicates (Rep1, Rep2, Rep3) performed on different days in HEK293T cells.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–14, Supplementary Tables 1–2, Supplementary Note and Supplementary Discussion (PDF 2557 kb)

Supplementary Table 3

Summary of lesion rates determined through targeted PCR-based deep-sequencing of potential off-target sites (XLSX 137 kb)

Supplementary Table 4

List of primers and on/off target sequences used in this study (XLSX 20 kb)

Supplementary Table 5

List of indexes used to identify genomic regions for targeted PCR deep-sequencing analysis (XLSX 67 kb)

Supplementary Table 6

Summary of peaks detected from GUIDE-seq off-target analysis (XLSX 12 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bolukbasi, M., Gupta, A., Oikemus, S. et al. DNA-binding-domain fusions enhance the targeting range and precision of Cas9. Nat Methods 12, 1150–1156 (2015). https://doi.org/10.1038/nmeth.3624

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nmeth.3624

This article is cited by

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