[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
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.

  • Brief Communication
  • Published:

GuideScan software for improved single and paired CRISPR guide RNA design

Abstract

We present GuideScan software for the design of CRISPR guide RNA libraries that can be used to edit coding and noncoding genomic regions. GuideScan produces high-density sets of guide RNAs (gRNAs) for single- and paired-gRNA genome-wide screens. We also show that the trie data structure of GuideScan enables the design of gRNAs that are more specific than those designed by existing tools.

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

Figure 1: The GuideScan gRNA design tool.
Figure 2: GuideScan correctly enumerates off-target sequences and filters out promiscuous gRNAs.

Similar content being viewed by others

References

  1. Doudna, J.A. & Charpentier, E. Science 346, 1258096 (2014).

    PubMed  Google Scholar 

  2. Hsu, P.D., Lander, E.S. & Zhang, F. Cell 157, 1262–1278 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Shalem, O. et al. Science 343, 84–87 (2014).

    Article  CAS  PubMed  Google Scholar 

  4. Koike-Yusa, H., Li, Y., Tan, E.P., Velasco-Herrera, Mdel C. & Yusa, K. Nat. Biotechnol. 32, 267–273 (2014).

    Article  CAS  PubMed  Google Scholar 

  5. Wang, T., Wei, J.J., Sabatini, D.M. & Lander, E.S. Science 343, 80–84 (2014).

    Article  CAS  PubMed  Google Scholar 

  6. Korkmaz, G. et al. Nat. Biotechnol. 34, 192–198 (2016).

    Article  CAS  PubMed  Google Scholar 

  7. Rajagopal, N. et al. Nat. Biotechnol. 34, 167–174 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Zhu, S. et al. Nat. Biotechnol. 34, 1279–1286 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Canver, M.C. et al. Nature 527, 192–197 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Moreno-Mateos, M.A. et al. Nat. Methods 12, 982–988 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Vidigal, J.A. & Ventura, A. Nat. Commun. 6, 8083 (2015).

    Article  CAS  PubMed  Google Scholar 

  12. Fu, Y., Sander, J.D., Reyon, D., Cascio, V.M. & Joung, J.K. Nat. Biotechnol. 32, 279–284 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Doench, J.G. et al. Nat. Biotechnol. 34, 184–191 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Hsu, P.D. et al. Nat. Biotechnol. 31, 827–832 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Tsai, S.Q. et al. Nat. Biotechnol. 33, 187–197 (2015).

    Article  CAS  PubMed  Google Scholar 

  16. Heigwer, F., Kerr, G. & Boutros, M. Nat. Methods 11, 122–123 (2014).

    Article  CAS  PubMed  Google Scholar 

  17. Aguirre, A.J. et al. Cancer Discov. 6, 914–929 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Maddalo, D. et al. Nature 516, 423–427 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Pliatsika, V. & Rigoutsos, I. Biol. Direct 10, 4 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Li, H. et al. Bioinformatics 25, 2078–2079 (2009).

    PubMed  PubMed Central  Google Scholar 

  21. ENCODE Project Consortium. Nature 489, 57–74 (2012).

  22. Whyte, W.A. et al. Cell 153, 307–319 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Kozomara, A. & Griffiths-Jones, S. Nucleic Acids Res. 39, D152–D157 (2011).

    Article  CAS  PubMed  Google Scholar 

  24. Harrow, J. et al. Genome Res. 22, 1760–1774 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Lin, S., Staahl, B.T., Alla, R.K. & Doudna, J.A. eLife 3, e04766 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank members of the Ventura and the Leslie laboratories for comments and suggestions. We thank L. Fairchild and R. Pelossof for providing source code for the SplashRNA web server to serve as the backbone for the GuideScan website. This work was supported in part by NIH: grants P30-CA008748 (MSK Core), U01-HG007033 (C.S.L.), U01-HG007893 (C.S.L.), and by grants from the Geoffrey Beene Cancer Research Foundation (A.V.), the Uniting Against Lung Cancer Foundation (A.V.), the Cycle for Survival Foundation (A.V.), the Pershing Square Sohn Cancer Research Alliance (A.V.), and the Lung Cancer Research Foundation (J.A.V.). The GuideScan source code and all associated documentation are deposited at guidescan.com.

Author information

Authors and Affiliations

Authors

Contributions

J.A.V., C.S.L., and A.V. conceived and supervised the project. Y.P. and A.R.P. developed the GuideScan algorithm with input from C.S.L.; A.R.P. and Y.P. implemented the GuideScan software package; A.R.P. performed the computational experiments; J.A.V. performed the wet-lab experiments; A.R.P. and S.C. implemented the web-server; L.Z. provided expertise in software development and helped improve the website user experience; J.A.V. drafted the manuscript with contributions from all authors.

Corresponding authors

Correspondence to Joana A Vidigal, Christina S Leslie or Andrea Ventura.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Output of GuideScan and competitor tools.

(a) Genome-wide density of guides in GuideScan’s murine Cas9 database (blue), compared to the UCSC genome track from mit.edu (red). (b) Dot plot showing specificity scores and number of perfect off-target sites for promiscuous guides designed by the mit.edu gRNA web design tool. Data points are color-coded based on the specificity scores of the corresponding gRNAs following the guidelines of mit.edu web portal (red = low specificity, score 1-19; yellow = medium specificity, score 20-49; green = high specificity, score 50-100).

Supplementary Figure 2 Uncropped gel images.

(a) Uncropped gel of T7 cleavage assay shown in Figure 2d. First lane shows the separations of the 1kb+ (Invitrogen) molecular size ladder. The size of selected bands of the ladder is shown on the left. Numbers above gel refer to gel lanes on which T7 assays were run. Red and Blue bars below gel highlight assays unrelated to this work (red; lanes 1—4), and those shown in Fig. 2 (blue; lanes 5—10); (b) Uncropped gel of PCR shown on Figure 2f; (c) Uncropped gel of PCRs shown in Fig. 2e. Bars below gels in panels b—c highlight the chromosomal region amplified.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1,2 and Supplementary Note 1 (PDF 673 kb)

Supplementary Table 1

Off-target reporting by competitor tools for a subset of promiscuous gRNAs. (XLSX 66 kb)

Supplementary Table 2

Number of gRNAs with off-targets with 0 or 1 mismatches. (XLSX 78 kb)

Supplementary Table 3

Genomic Coordinates used for tool comparison experiment. (XLSX 50 kb)

Supplementary Table 4

sequence of gRNAs and primers used in Fig. 2 (XLSX 44 kb)

Supplementary Code

Supplementary Code (ZIP 27314 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Perez, A., Pritykin, Y., Vidigal, J. et al. GuideScan software for improved single and paired CRISPR guide RNA design. Nat Biotechnol 35, 347–349 (2017). https://doi.org/10.1038/nbt.3804

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nbt.3804

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