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Design of Guide RNA for CRISPR/Cas Plant Genome Editing

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Abstract

CRISPR/Cas technology of genome editing is a powerful tool for making targeted changes in the DNA of various organisms, including plants. The choice of the precise nucleotide sequence (protospacer) in the gene to be edited is important in the design of guide RNA, which can be carried out by specialized software. We review and compare all the known on-line and off-line resources for guide RNA design, with special attention paid to tools capable of searching for off-target edits sites in plant genomes. The use of Cas12a may be preferable to Cas9. Techniques allowing C→T and G→A base editing without DNA cleavage are discussed along with the basic requirements for the design of effective and highly specific guide RNAs. Ways for improving guide RNA design software are presented. We also discuss the lesser risks of off-target editing in plant genomes as opposed to animal genomes. Examples of edited plant genomes including those that do not lead to the creation of transgenic plants are reviewed.

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REFERENCES

  1. Kuluev B.R., Gumerova G.R., Mikhaylova E.V., Gerashchenkov G.A., Rozhnova N.A., Vershinina Z.R., Knyazev A.V., Matniyazov R.T., Baymiev An.Kh., Baymiev Al.Kh., Chemeris A.V. 2019. Delivery of CRISPR/Cas components into higher plant cells for genome editing. Russ. J. Plant Physiol.66 (5), 694–706. https://doi.org/10.1134/S0015330319050117

    Article  CAS  Google Scholar 

  2. Graham D.B., Root D.E. 2015. Resources for the design of CRISPR gene editing experiments. Genome Biol.16, 260. https://doi.org/10.1186/s13059-015-0823-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Kanchiswamy C.N., Maffei M., Malnoy M., Velasco R., Kim J.S. 2016. Fine-tuning next-generation genome editing tools. Trends Biotechnol.34, 562‒574. https://doi.org/10.1016/j.tibtech.2016.03.007

    Article  CAS  PubMed  Google Scholar 

  4. Chuai G.H., Wang Q.L., Liu Q. 2017. In silico meets in vivo: Towards computational CRISPR-based sgRNA design. Trends Biotechnol.35, 12‒21. https://doi.org/10.1016/j.tibtech.2016.06.008

    Article  CAS  PubMed  Google Scholar 

  5. Periwal V. 2017. A comprehensive overview of computational resources to aid in precision genome editing with engineered nucleases. Brief Bioinform.18, 698‒711. https://doi.org/10.1093/bib/bbw052

    Article  CAS  PubMed  Google Scholar 

  6. Yennmalli R.M., Kalra S., Srivastava P.A., Garlapati V.K. 2017. Computational tools and resources for CRISPR/Cas 9 genome editing method. MOJ Proteomics Bioinform.5, 00164.

    Google Scholar 

  7. Cui Y., Xu J., Cheng M., Liao X., Peng S. 2018. Review of CRISPR/Cas9 sgRNA design tools. Interdiscip. Sci.10, 455‒465. https://doi.org/10.1007/s12539-018-0298-z

    Article  CAS  PubMed  Google Scholar 

  8. Demirci Y., Zhang B., Unver T. 2018. CRISPR/Cas9: An RNA-guided highly precise synthetic tool for plant genome editing. J. Cell Physiol.233, 1844‒1859. https://doi.org/10.1002/jcp.25970

    Article  CAS  PubMed  Google Scholar 

  9. Yan J., Chuai G., Zhou C., Zhu C., Yang J., Zhang C., Gu F., Xu H., Wei J., Liu Q. 2018. Benchmarking CRISPR on-target sgRNA design. Brief Bioinform.19, 721‒724. https://doi.org/10.1093/bib/bbx001

    Article  CAS  PubMed  Google Scholar 

  10. Chemeris D.A., Kir’yanova O.Yu., Gerashchenkov G.A., Kuluev B.R., Rozhnova N.A., Matniyazov R.T., Baymiev An.Kh., Baymiev Al.Kh., Gubaidullin I.M., Chemeris A.V. 2017. Bioinformatic resources for CRISPR/Cas genome editing. Biomika.9, 203‒208.

    Google Scholar 

  11. Chugunova A.A., Dontsova O.A., Sergiev P.V. 2016. Methods of genome engineering: A new era of molecular biology. Biochemistry (Moscow). 81 (7), 662‒677.

    CAS  PubMed  Google Scholar 

  12. Jiang F., Doudna J.A. 2017. CRISPR-Cas9 structures and mechanisms. Annu. Rev. Biophys.46, 505‒529. https://doi.org/10.1146/annurev-biophys-062215-010822

    Article  CAS  PubMed  Google Scholar 

  13. Bannikov A.V., Lavrov A.V. 2017. CRISPR/CAS9, the king of genome editing tools. Mol. Biol. (Moscow). 51 (4), 514–525. https://doi.org/10.7868/S0026898417040036

    Article  CAS  Google Scholar 

  14. Kuluev B.R., Gerashchenkov G.A., Rozhnova N.A., Baymiev An.Kh., Vershinina Z.R., Knyazev A.V., Matniyazov R.T., Gumerova G.R., Mikhailova E.V., Nikonorov Yu.M., Chemeris D.A., Baymiev Al.Kh., Che-meris A.V. 2017. CRISPR/Cas editing of plant genomes. Biomika.9, 155‒182.

    Google Scholar 

  15. Karagyaur M.N., Rubtsov Yu.P., Vasiliev P.A., Tkachuk V.A. 2018. Practical recommendations for improving efficiency and accuracy of the CRISPR/Cas9 genome editing system. Biochemistry (Moscow). 83 (6), 629‒642.

    CAS  PubMed  Google Scholar 

  16. Ahmad H.I., Ahmad M.J., Asif A.R., Adnan M., Iqbal M.K., Mehmood K., Muhammad S.A., Bhuiyan A.A., Elokil A., Du X., Zhao C., Liu X., Xie S. 2018. A review of CRISPR-based genome editing: Survival, evolution and challenges. Curr. Issues Mol. Biol.28, 47‒68. https://doi.org/10.21775/cimb.028.047

    Article  PubMed  Google Scholar 

  17. Makarova S.S., Khromov A.V., Spechenkova N.A., Taliansky M.E., Kalinina N.O. 2018. Application of the CRISPR/Cas system for generation of pathogen-resistant plants. Biochemistry (Moscow). 83, 1552‒1562. https://doi.org/10.1134/S0006297918120131

    Article  CAS  PubMed  Google Scholar 

  18. Redaktirovanie genov i genomov (Gene and Genome Editing), 2nd ed. Zakiyan S.M., Medvedev S.P., Dement’ev E.V., Pokushalov E.A., Vlasov V.V., Eds. Novosibirsk: Ross. Akad. Nauk, 2018.

  19. Zlobin N.E., Lebedeva M.V., Taranov V.V., Kharchenko P.N., Babakov A.V. 2018. Plant genome editing by targeted nitrogenous base replacement. Biotekhnologiya.34, 59–68. https://doi.org/10.21519/0234-2758-2018-34-6-59-68

    Article  Google Scholar 

  20. Korotkova A.M., Gerasimova S.V., Khlestkina E.K. 2019. Current achievements in modifying crop genes using CRISPR/Cas system. Vavilov. Zh. Genet. Selekts.23, 29‒37. https://doi.org/10.18699/VJ19.458

    Article  Google Scholar 

  21. Molla K.A., Yang Y. 2019. CRISPR/Cas-mediated base editing: Technical considerations and practical applications. Trends Biotechnol. pii: S0167-7799(19)30053-8. https://doi.org/10.1016/j.tibtech.2019.03.008

  22. Wolter F., Schindele P., Puchta H. 2019. Plant breeding at the speed of light: the power of CRISPR/Cas to generate directed genetic diversity at multiple sites. BMC Plant Biol.19, 176. https://doi.org/10.1186/s12870-019-1775-1

    Article  PubMed  PubMed Central  Google Scholar 

  23. Swarts D.C., Jinek M. 2018. Cas9 versus Cas12a/Cpf1: Structure–function comparisons and implications for genome editing. Wiley Interdiscip. Rev. RNA. e1481. https://doi.org/10.1002/wrna.1481

  24. Kelley M.L., Strezoska Z., He K., Vermeulen A., Smith A. 2016. Versatility of chemically synthesized guide RNAs for CRISPR-Cas9 genome editing. J. Biotechnol.233, 74–83. https://doi.org/10.1016/j.jbiotec.2016.06.011

    Article  CAS  PubMed  Google Scholar 

  25. Andersson M., Turesson H., Olsson N., Fält A.S., Ohlsson P., Gonzalez M.N., Samuelsson M., Hofvander P. 2018. Genome editing in potato via CRISPR-Cas9 ribonucleoprotein delivery. Physiol. Plant.164, 378‒384. https://doi.org/10.1111/ppl.12731

    Article  CAS  PubMed  Google Scholar 

  26. Strohkendl I., Saifuddin F.A., Rybarski J.R., Finkelstein I.J., Russell R. 2018. Kinetic basis for DNA target specificity of CRISPR-Cas12a. Mol. Cell.71, 816‒824.e3. https://doi.org/10.1016/j.molcel.2018.06.043

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Hsu P.D., Scott D.A., Weinstein J.A., Ran F.A., Konermann S., Agarwala V., Li Y., Fine E.J., Wu X., Shalem O., Cradick T.J., Marraffini L.A., Bao G., Zhang F. 2013. DNA targeting specificity of RNA-guided Cas9 nucleases. Nat. Biotechnol.31, 827‒832. https://doi.org/10.1038/nbt.2647

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Doench J.G., Hartenian E., Graham D.B., Tothova Z., Hegde M., Smith I., Sullender M., Ebert B.L., Xavier R.J., Root D.E. 2014. Rational design of highly active sgRNAs for CRISPR-Cas9-mediated gene inactivation. Nat. Biotechnol. 2014. 32, 1262‒1267. https://doi.org/10.1038/nbt.3026

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Doench J.G., Fusi N., Sullender M., Hegde M., Vaimberg E.W., Donovan K.F., Smith I., Tothova Z., Wilen C., Orchard R., Virgin H.W., Listgarten J., Root D.E. 2016. Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nat. Biotechnol.34, 184‒191. https://doi.org/10.1038/nbt.3437

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Abadi S., Yan W.X., Amar D., Mayrose I. 2017. A machine learning approach for predicting CRISPR-Cas9 cleavage efficiencies and patterns underlying its mechanism of action. PLoS Comput. Biol.13, e1005807. https://doi.org/10.1371/journal.pcbi.1005807

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Kim H.K., Min S., Song M., Jung S., Choi J.W., Kim Y., Lee S., Yoon S., Kim H.H. 2018. Deep learning improves prediction of CRISPR-Cpf1 guide RNA activity. Nat. Biotechnol.36, 239‒241. https://doi.org/10.1038/nbt.4061

    Article  CAS  PubMed  Google Scholar 

  32. Labuhn M., Adams F.F., Ng M., Knoess S., Schambach A., Charpentier E.M., Schwarzer A., Mateo J.L., Klusmann J.H., Heckl D. 2018. Refined sgRNA efficacy prediction improves large- and small-scale CRISPR-Cas9 applications. Nucleic Acids Res.46, 1375‒1385. https://doi.org/10.1093/nar/gkx1268

    Article  CAS  PubMed  Google Scholar 

  33. Listgarten J., Weinstein M., Kleinstiver B.P., Sousa A.A., Joung J.K., Crawford J., Gao K., Hoang L., Elibol M., Doench J.G., Fusi N. 2018. Prediction of off-target activities for the end-to-end design of CRISPR guide RNAs. Nat. Biomed. Eng.2, 38‒47. https://doi.org/10.1038/s41551-017-0178-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Xue L., Tang B., Chen W., Luo J. 2019. Prediction of CRISPR sgRNA activity using a deep convolutional neural network. J. Chem. Inf. Model.59, 615‒624. https://doi.org/10.1021/acs.jcim.8b00368

    Article  CAS  PubMed  Google Scholar 

  35. Minkenberg B., Zhang J., Xie K., Yang Y. 2019. CRISPR-PLANT v2: An online resource for highly specific guide RNA spacers based on improved off-target analysis. Plant Biotechnol. J.17, 5‒8. https://doi.org/10.1111/pbi.13025

    Article  PubMed  Google Scholar 

  36. Zhu H., Liang C. 2019. CRISPR-DT: designing gRNAs for the CRISPR-Cpf1 system with improved target efficiency and specificity. Bioinformatics.35, 2783–2789. https://doi.org/10.1093/bioinformatics/bty1061

    Article  PubMed  Google Scholar 

  37. Graf R., Li X., Chu V.T., Rajewsky K. 2019. sgRNA sequence motifs blocking efficient CRISPR/Cas9-mediated gene editing. Cell Rep.26, 1098‒1103.e3. https://doi.org/10.1016/j.celrep.2019.01.024

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Wong N., Liu W., Wang X. 2015. WU-CRISPR: characteristics of functional guide RNAs for the CRISPR/ Cas9 system. Genome Biol.16, 218. https://doi.org/10.1186/s13059-015-0784-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Garafutdinov R.R., Baimiev An.Kh., Maleev G.V., Alekseev Ya.I., Zubov V.V., Chemeris D.A., Kir’yanova O.Yu., Gubaidullin I.M., Matniyazov R.T., Sakhabutdinova A.R., Nikonorov Yu.M., Kuluev B.R., Baymiev Al.Kh., Chemeris A.V. 2019. Diversity of primers for PCR and principles of their selection. Biomika. 11, 23–70. https://doi.org/10.31301/2221-6197.bmcs.2019-04

    Article  Google Scholar 

  40. Hahn F., Nekrasov V. 2019. CRISPR/Cas precision: Do we need to worry about off-targeting in plants? Plant Cell Rep.38, 437‒441. https://doi.org/10.1007/s00299-018-2355-9

    Article  CAS  PubMed  Google Scholar 

  41. Tang X., Liu G., Zhou J., Ren Q., You Q., Tian L., Xin X., Zhong Z., Liu B., Zheng X., Zhang D., Malzahn A., Gong Z., Qi Y., Zhang T., Zhang Y. 2018. 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. https://doi.org/10.1186/s13059-018-1458-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Ossowski S., Schneeberger K., Lucas-Lledó J.I., Warthmann N., Clark R.M., Shaw R.G., Weigel D., Lynch M. 2010. The rate and molecular spectrum of spontaneous mutations in Arabidopsis thaliana.Science.327, 92‒94. https://doi.org/10.1126/science.1180677

    Article  CAS  PubMed  Google Scholar 

  43. Wolt J.D., Wang K., Sashital D., Lawrence-Dill C.J. 2016. Achieving plant CRISPR targeting that limits off-target effects. Plant Genome.9 (3). https://doi.org/10.3835/plantgenome2016.05.0047

  44. Svitashev S., Schwartz C., Lenderts B., Young J.K., Mark Cigan A. 2016. Genome editing in maize directed by CRISPR-Cas9 ribonucleoprotein complexes. Nat. Commun.7, 13274. https://doi.org/10.1038/ncomms13274

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Liang Z., Chen K., Li T., Zhang Y., Wang Y., Zhao Q., Liu J., Zhang H., Liu C., Ran Y., Gao C. 2017. Efficient DNA-free genome editing of bread wheat using CRISPR/Cas9 ribonucleoprotein complexes. Nat. Commun.8, 14261. https://doi.org/10.1038/ncomms14261

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Khromov A.V., Makhotenko A.V., Snigir’ E.V., Makarova S.S., Makarov V.V., Suprunova T.P., Miroshnichenko D.N., Kalinina N.O., Dolgov S.V., Tal’yanskii M.E. 2018. Delivery of CRISPR/Cas9 ribonucleoprotein complex to apical meristem cells for DNA-free editing of potato Solanum tuberosum genome. Biotekhmologiya.34, 51‒58.

    Article  Google Scholar 

  47. Miroshnichenko D.N., Shul’ga O.A., Timerbaev V.R., Dolgov S.V. 2019. Production of nontransgenic plants with an edited genome: Achievements, problems, and prospects. Biotekhnologiya.35, 3‒26. https://doi.org/10.21519/0234-2758-2019-35-1-3-26

    Article  Google Scholar 

  48. Oliveros J.C., Franch M., Tabas-Madrid D., San-León D., Montoliu L., Cubas P., Pazos F. 2016. Breaking-Cas-interactive design of guide RNAs for CRISPR-Cas experiments for ENSEMBL genomes. Nucleic Acids Res.44, 267‒271. https://doi.org/10.1093/nar/gkw407

    Article  CAS  Google Scholar 

  49. Stemmer M., Thumberger T., Del Sol Keyer M., Wittbrodt J., Mateo J.L. 2015. CCTop: An intuitive, flexible and reliable CRISPR/Cas9 target prediction tool. PLoS One.24, e0124633.

    Article  Google Scholar 

  50. Brazelton V.A. Jr., Zarecor S., Wright D.A., Wang Y., Liu J., Chen K., Yang B., Lawrence-Dill C.J. 2015. A quick guide to CRISPR sgRNA design tools. GM Crops Food.6, 266–276. https://doi.org/10.1080/21645698.2015.1137690

    Article  PubMed  Google Scholar 

  51. Montague T.G., Cruz J.M., Gagnon J.A., Church G.M., Valen E. 2014. CHOPCHOP: A CRISPR/Cas9 and TALEN web tool for genome editing. Nucleic Acids Res.42, 401–407. https://doi.org/10.1093/nar/gku410

    Article  CAS  Google Scholar 

  52. Labun K., Montague T.G., Gagnon J.A., Thyme S.B., Valen E. 2016. CHOPCHOP v2: A web tool for the next generation of CRISPR genome engineering. Nucleic Acids Res.44, 272‒276. https://doi.org/10.1093/nar/gkw398

    Article  CAS  Google Scholar 

  53. Heigwer F., Zhan T., Breinig M., Winter J., Brugemann D., Leible S., Boutros M. 2016. CRISPR library designer (CLD): Software for multispecies design of single guide RNA libraries. Genome Biol.17, 55. https://doi.org/10.1186/s13059-016-0915-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Haeussler M., Schönig K., Eckert H., Eschstruth A., Mianné J., Renaud J.B., Schneider-Maunoury S., Shkumatava A., Teboul L., Kent J., Joly J.S.,Concordet J.P. 2016. Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR. Genome Biol.17, 148. https://doi.org/10.1186/s13059-016-1012-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Concordet J.P., Haeussler M. 2018. CRISPOR: intuitive guide selection for CRISPR/Cas9 genome editing experiments and screens. Nucleic Acids Res.46, 242‒245. https://doi.org/10.1093/nar/gky354

    Article  CAS  Google Scholar 

  56. Naito Y., Hino K., Bono H., Ui-Tei K. 2015. CRISPRdirect: Software for designing CRISPR/Cas guide RNA with reduced off-target sites. Bioinformatics.31, 1120–1123. https://doi.org/10.1093/bioinformatics/btu743

    Article  CAS  PubMed  Google Scholar 

  57. Xie X., Ma X., Zhu Q., Zeng D., Li G., Liu Y.-G. 2017. CRISPR-GE: A convenient software toolkit for CRISPR-based genome editing. Mol. Plant.10, 1246‒1249. https://doi.org/10.1016/j.molp.2017.06.004

    Article  CAS  PubMed  Google Scholar 

  58. Prykhozhij S.V., Rajan V., Gaston D., Berman J.N. 2015. CRISPR Multitargeter: A web tool to find common and unique CRISPR single guide RNA targets in a set of similar sequences. PLoS One.10, e0119372. https://doi.org/10.1371/journal.pone.0119372

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Prykhozhij S.V., Rajan V., Gaston D., Berman J.N. 2015. Correction: CRISPR MultiTargeter: A Web Tool to find common and unique CRISPR single guide RNA targets in a set of similar sequences. PLoS One.10, e0138634. https://doi.org/10.1371/journal.pone.0138634

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Lei Y., Lu L., Liu H.Y., Li S., Xing F., Chen L.L. 2014. CRISPR-P: A web tool for synthetic single-guide RNA design of CRISPR-system in plants. Mol. Plant.7, 1494–1496. https://doi.org/10.1093/mp/ssu044

    Article  CAS  PubMed  Google Scholar 

  61. Liu H., Ding Y., Zhou Y., Jin W., Xie K., Chen L.L. 2017. CRISPR-P 2.0: An improved CRISPR-Cas9 tool for genome editing in plants. Mol. Plant.10, 530–532. https://doi.org/10.1016/j.molp.2017.01.003

    Article  CAS  PubMed  Google Scholar 

  62. Sun J., Liu H., Liu J., Cheng S., Peng Y., Zhang Q., Yan J., Liu H.J., Chen L.L. 2019. CRISPR-Local: A local single-guide RNA (sgRNA) design tool for non-reference plant genomes. Bioinformatics.35, 2501–2503. https://doi.org/10.1093/bioinformatics/bty970

    Article  PubMed  Google Scholar 

  63. Xie K., Zhang J., Yang Y. 2014. Genome-wide prediction of highly specific guide RNA spacers for the CRISPR-Cas9 mediated genome editing in model plants and major crops. Mol. Plant.7, 923‒926. https://doi.org/10.1093/mp/ssu009

    Article  CAS  PubMed  Google Scholar 

  64. Yan M., Zhou S.R., Xue H.W. 2015. CRISPR Primer Designer: Design primers for knockout and chromosome imaging CRISPR-Cas system. J. Integr. Plant Biol.57, 613‒617. https://doi.org/10.1111/jipb.12295

    Article  CAS  PubMed  Google Scholar 

  65. Bae S., Park J., Kim J.S. 2014. Cas-OFFinder: A fast and versatile algorithm that searches for potential off-target sites of Cas9 RNA-guided endonucleases. Bioinformatics.30, 1473–1475. https://doi.org/10.1093/bioinformatics/btu048

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Bae S., Kweon J., Kim H.S., Kim J.S. 2014. Microhomology-based choice of Cas9 nuclease target sites. Nat. Methods.11, 705–706. https://doi.org/10.1038/nmeth.3015

    Article  CAS  PubMed  Google Scholar 

  67. Park J., Bae S., Kim J.S. 2015. Cas-Designer: A web-based tool for choice of CRISPR-Cas9 target sites. Bioinformatics.31, 4014–4016. https://doi.org/10.1093/bioinformatics/btv537

    Article  CAS  PubMed  Google Scholar 

  68. Park J., Kim J.S., Bae S. 2016. Cas-Database: Web-based genome-wide guide RNA library design for gene knockout screens using CRISPR-Cas9. Bioinformatics.32, 2017–2023. https://doi.org/10.1093/bioinformatics/btw103

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Hwang G.H., Park J., Lim K., Kim S., Yu J., Yu E., Kim S.T., Eils R., Kim J.S., Bae S. 2018. Web-based design and analysis tools for CRISPR base editing. BMC Bioinformatics.19, 542. https://doi.org/10.1186/s12859-018-2585-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Park J., Bae S. 2018. Cpf1-Database: Web-based genome-wide guide RNA library design for gene knockout screens using CRISPR-Cpf1. Bioinformatics.34, 1077‒1079. https://doi.org/10.1093/bioinformatics/btx695

    Article  CAS  PubMed  Google Scholar 

  71. Zhu H., Misel L., Graham M., Robinson M.L., Liang C. 2016. CT-Finder: A web service for CRISPR optimal target prediction and visualization. Sci. Rep.23, 25516. https://doi.org/10.1038/srep25516

    Article  CAS  Google Scholar 

  72. Zhu H., Richmond E., Liang C. 2018. CRISPR-RT: A web service for designing CRISPR-C2c2 crRNA with improved target specificity. Bioinformatics.34, 117‒119. https://doi.org/10.1093/bioinformatics/btx580

    Article  CAS  PubMed  Google Scholar 

  73. Hough S.H., Kancleris K., Brody L., Humphryes-Kirilov N., Wolanski J., Dunaway K., Ajetunmobi A., Dillard V. 2017. Guide Picker is a comprehensive design tool for visualizing and selecting guides for CRISPR experiments. BMC Bioinformatics.18, 167. https://doi.org/10.1186/s12859-017-1581-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Heigwer F., Kerr G., Boutros M. 2014. E-CRISP: Fast CRISPR target site identification. Nat. Methods.11, 122–123. https://doi.org/10.1038/nmeth.2812

    Article  CAS  PubMed  Google Scholar 

  75. O’Brien A., Bailey T.L. 2014. GT-Scan: Identifying unique genomic targets. Bioinformatics.30, 2673–2675. https://doi.org/10.1093/bioinformatics/btu354

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Rastogi A., Murik O., Bowler C., Tirichine L. 2016. PhytoCRISP-Ex: A web-based and stand-alone application to find specific target sequences for CRISPR/CAS editing. BMC Bioinformatics.17, 261. https://doi.org/10.1186/s12859-016-1143-1

    Article  PubMed  PubMed Central  Google Scholar 

  77. Liu H., Wei Z., Dominguez A., Li Y., Wang X., Qi L.S. 2015. CRISPR-ERA: A comprehensive design tool for CRISPR-mediated gene editing, repression and activation. Bioinformatics.31, 3676–3678. https://doi.org/10.1093/bioinformatics/btv423

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. O’Brien A.R., Wilson L.O.W., Burgio G., Bauer D.C. 2019. Unlocking HDR-mediated nucleotide editing by identifying high-efficiency target sites using machine learning. Sci. Rep.9, 2788. https://doi.org/10.1038/s41598-019-39142-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Merritt B.B., Cheung L.C. 2019. GRIBCG: A software for selection of sgRNAs in the design of balancer chromosomes. BMC Bioinformatics.20, 122. https://doi.org/10.1186/s12859-019-2712-x

    Article  PubMed  PubMed Central  Google Scholar 

  80. Moreno-Mateos M.A., Vejnar C.E., Beaudoin J.D., Fernandez J.P., Mis E.K., Khokha M.K., Giraldez A.J. 2015. CRISPRscan: Designing highly efficient sgRNAs for CRISPR-Cas9 targeting in vivo. Nat. Methods.12, 982‒988. https://doi.org/10.1038/nmeth.3543

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Dandage R., Després P.C., Yachie N., Landry C.R. 2019. beditor: A computational workflow for designing libraries of guide RNAs for CRISPR-mediated base editing. Genetics.212, 377‒385, https://doi.org/10.1534/genetics.119.302089

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Chari R., Mali P., Moosburner M., Church G.M. 2015. Unraveling CRISPR-Cas9 genome engineering parameters via a library-on-library approach. Nat. Methods.12, 823‒826. https://doi.org/10.1038/nmeth.3473

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Horlbeck M.A., Witkowsky L.B., Guglielmi B., Replogle J.M., Gilbert L.A., Villalta J.E., Torigoe S.E., Tjian R., Weissman J.S. 2016. Nucleosomes impede Cas9 access to DNA in vivo and in vitro.eLife.5, pii: e12677. https://doi.org/10.7554/eLife.12677

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Jensen K.T., Fløe L., Petersen T.S., Huang J., Xu F., Bolund L., Luo Y., Lin L. 2017. Chromatin accessibility and guide sequence secondary structure affect CRISPR-Cas9 gene editing efficiency. FEBS Lett.591, 1892‒1901. https://doi.org/10.1002/1873-3468.12707

    Article  CAS  PubMed  Google Scholar 

  85. Yarrington R.M., Verma S., Schwartz S., Trautman J.K., Carroll D. 2018. Nucleosomes inhibit target cleavage by CRISPR-Cas9 in vivo.Proc. Natl. Acad. Sci. U. S. A.115, 9351‒9358. https://doi.org/10.1073/pnas.1810062115

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Feng C., Yuan J., Wang R., Liu Y., Birchler J.A., Han F. 2016. Efficient targeted genome modification in maize using CRISPR/Cas9 system. J. Genet. Genomics.43, 37‒43. https://doi.org/10.1016/j.jgg.2015.10.002

    Article  PubMed  Google Scholar 

  87. Singh R., Kuscu C., Quinlan A., Qi Y., Adli M. 2015. Cas9-chromatin binding information enables more accurate CRISPR off-target prediction. Nucleic Acids Res.43, e118. https://doi.org/10.1093/nar/gkv575

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Zhang S., Li X., Lin Q., Wong K.C. 2019. Synergizing CRISPR/Cas9 off-target predictions for ensemble insights and practical applications. Bioinformatics.35, 1108‒1115. https://doi.org/10.1093/bioinformatics/bty748

    Article  CAS  PubMed  Google Scholar 

  89. Zhang D., Hurst T., Duan D., Chen S.J. 2019. Unified energetics analysis unravels SpCas9 cleavage activity for optimal gRNA design. Proc. Natl. Acad. Sci. U. S. A.116, 8693‒8698. https://doi.org/10.1073/pnas.1820523116

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Funding

This work was supported by the Russian Foundation for Basic Research, project nos. 18-04-00118 А, 19-016-00117 А, 19-016-00139 А, and by the governmental grants, nos. АААА-А16-116020350028-4, AAAA-A19-119021190011-0.

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Correspondence to G. A. Gerashchenkov.

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The present article does not contain any studies with human or animals as objects.

Conflict of interest. The authors declare no conflict of interests.

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Translated by M. Bibov

Abbreviations: gRNA, guide RNA; Cas9, CRISPR associated protein 9; Cpf1, CRISPR from Prevotella and Francisella 1; CRISPR, Clustered Regularly Interspaced Short Palindromic Repeats; PAM, Protospacer Adjacent Motif.

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Gerashchenkov, G.A., Rozhnova, N.A., Kuluev, B.R. et al. Design of Guide RNA for CRISPR/Cas Plant Genome Editing. Mol Biol 54, 24–42 (2020). https://doi.org/10.1134/S0026893320010069

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  • DOI: https://doi.org/10.1134/S0026893320010069

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