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