Title: Methods for Optimizing CRISPR-Cas9 Genome Editing Specificity
Abstract: Advances in the development of delivery, repair, and specificity strategies for the CRISPR-Cas9 genome engineering toolbox are helping researchers understand gene function with unprecedented precision and sensitivity. CRISPR-Cas9 also holds enormous therapeutic potential for the treatment of genetic disorders by directly correcting disease-causing mutations. Although the Cas9 protein has been shown to bind and cleave DNA at off-target sites, the field of Cas9 specificity is rapidly progressing, with marked improvements in guide RNA selection, protein and guide engineering, novel enzymes, and off-target detection methods. We review important challenges and breakthroughs in the field as a comprehensive practical guide to interested users of genome editing technologies, highlighting key tools and strategies for optimizing specificity. The genome editing community should now strive to standardize such methods for measuring and reporting off-target activity, while keeping in mind that the goal for specificity should be continued improvement and vigilance. Advances in the development of delivery, repair, and specificity strategies for the CRISPR-Cas9 genome engineering toolbox are helping researchers understand gene function with unprecedented precision and sensitivity. CRISPR-Cas9 also holds enormous therapeutic potential for the treatment of genetic disorders by directly correcting disease-causing mutations. Although the Cas9 protein has been shown to bind and cleave DNA at off-target sites, the field of Cas9 specificity is rapidly progressing, with marked improvements in guide RNA selection, protein and guide engineering, novel enzymes, and off-target detection methods. We review important challenges and breakthroughs in the field as a comprehensive practical guide to interested users of genome editing technologies, highlighting key tools and strategies for optimizing specificity. The genome editing community should now strive to standardize such methods for measuring and reporting off-target activity, while keeping in mind that the goal for specificity should be continued improvement and vigilance. The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 genome engineering technology has been established as a powerful molecular tool for numerous areas of biological study in which it is useful to target or modify specific DNA sequences (Hsu et al., 2014Hsu P.D. Lander E.S. Zhang F. Development and applications of CRISPR-Cas9 for genome engineering.Cell. 2014; 157: 1262-1278Abstract Full Text Full Text PDF PubMed Scopus (793) Google Scholar, Sander and Joung, 2014Sander J.D. Joung J.K. 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However, in the context of large eukaryotic genomes, Cas9 is known to bind and cleave at off-target sites (Cong et al., 2013Cong L. Ran F.A. Cox D. Lin S. Barretto R. Habib N. Hsu P.D. Wu X. Jiang W. Marraffini L.A. Zhang F. Multiplex genome engineering using CRISPR/Cas systems.Science. 2013; 339: 819-823Crossref PubMed Scopus (2540) Google Scholar, Fu et al., 2013Fu Y. Foden J.A. Khayter C. Maeder M.L. Reyon D. Joung J.K. Sander J.D. High-frequency off-target mutagenesis induced by CRISPR-Cas nucleases in human cells.Nat. Biotechnol. 2013; 31: 822-826Crossref PubMed Scopus (322) Google Scholar, Hsu et al., 2013Hsu P.D. Scott D.A. Weinstein J.A. Ran F.A. Konermann S. Agarwala V. Li Y. Fine E.J. Wu X. Shalem O. et al.DNA targeting specificity of RNA-guided Cas9 nucleases.Nat. Biotechnol. 2013; 31: 827-832Crossref PubMed Scopus (816) Google Scholar) like its genome editing predecessors zinc finger nucleases (Bibikova et al., 2001Bibikova M. Carroll D. Segal D.J. Trautman J.K. Smith J. 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While prior review articles should be referred to for foundational background and insight into Cas9 genome editing development (Makarova and Koonin, 2015Makarova K.S. Koonin E.V. Annotation and classification of CRISPR-Cas systems.Methods Mol. Biol. 2015; 1311: 47-75Crossref PubMed Google Scholar) and applications (Mali et al., 2013bMali P. Esvelt K.M. Church G.M. Cas9 as a versatile tool for engineering biology.Nat. Methods. 2013; 10: 957-963Crossref PubMed Scopus (385) Google Scholar, Hsu et al., 2014Hsu P.D. Lander E.S. Zhang F. Development and applications of CRISPR-Cas9 for genome engineering.Cell. 2014; 157: 1262-1278Abstract Full Text Full Text PDF PubMed Scopus (793) Google Scholar, Sander and Joung, 2014Sander J.D. Joung J.K. CRISPR-Cas systems for editing, regulating and targeting genomes.Nat. Biotechnol. 2014; 32: 347-355Crossref PubMed Scopus (567) Google Scholar, Porteus, 2016Porteus M. Genome editing: a new approach to human therapeutics.Annu. Rev. Pharmacol. Toxicol. 2016; 56: 163-190Crossref PubMed Scopus (0) Google Scholar, Wright et al., 2016Wright A.V. Nuñez J.K. Doudna J.A. Biology and applications of CRISPR systems: harnessing nature’s toolbox for genome engineering.Cell. 2016; 164: 29-44Abstract Full Text Full Text PDF PubMed Scopus (67) Google Scholar), in this article we focus on the sub-field of Cas9 specificity by comparing relevant methods for off-target improvement and detection, highlighting useful experimental and computational tools, and emphasizing further research directions for continued improvement. Recently, several improvements have been devised for the wild-type Cas9 enzyme derived from Streptococcus pyogenes, currently the nuclease most widely used for genome editing applications. Initially, bioinformatic solutions for guide RNA selection recommended guide sequences that recognized cognate genomic DNA targets with minimal sequence homology across that given genome. Although such approaches proved reasonably effective, subsequent systematic profiles of Cas9 off-target activity both in vitro (Pattanayak et al., 2013Pattanayak V. Lin S. Guilinger J.P. Ma E. Doudna J.A. Liu D.R. High-throughput profiling of off-target DNA cleavage reveals RNA-programmed Cas9 nuclease specificity.Nat. Biotechnol. 2013; 31: 839-843Crossref PubMed Scopus (392) Google Scholar) and in vivo (Fu et al., 2013Fu Y. Foden J.A. Khayter C. Maeder M.L. Reyon D. Joung J.K. Sander J.D. High-frequency off-target mutagenesis induced by CRISPR-Cas nucleases in human cells.Nat. Biotechnol. 2013; 31: 822-826Crossref PubMed Scopus (322) Google Scholar, Hsu et al., 2013Hsu P.D. Scott D.A. Weinstein J.A. Ran F.A. Konermann S. Agarwala V. Li Y. Fine E.J. Wu X. Shalem O. et al.DNA targeting specificity of RNA-guided Cas9 nucleases.Nat. Biotechnol. 2013; 31: 827-832Crossref PubMed Scopus (816) Google Scholar, Mali et al., 2013aMali P. Aach J. Stranges P.B. Esvelt K.M. Moosburner M. Kosuri S. Yang L. Church G.M. CAS9 transcriptional activators for target specificity screening and paired nickases for cooperative genome engineering.Nat. Biotechnol. 2013; 31: 833-838Crossref PubMed Scopus (534) Google Scholar) led to the first set of data-driven guidelines for target site selection. Given a particular locus and species of interest, computational models and associated web tools typically rank guide RNAs by predicted specificity and suggest likely off-target sites that can be checked for undesired mutagenesis via targeted sequencing or enzymatic assays (see Biased Off-Target Detection). However, the appropriate number of potential off-target sites to experimentally assay remains unclear, as the accuracy of in silico prediction can vary. Thus, improving methods of off-target detection and quantification has become a focus of a number of research groups in the CRISPR-Cas9 field. Several protocols for the unbiased detection of genome-wide Cas9 off-target activity in cells have been recently described (Frock et al., 2015Frock R.L. Hu J. Meyers R.M. Ho Y.J. Kii E. Alt F.W. Genome-wide detection of DNA double-stranded breaks induced by engineered nucleases.Nat. Biotechnol. 2015; 33: 179-186Crossref PubMed Scopus (122) Google Scholar, Kim et al., 2015Kim D. Bae S. Park J. Kim E. Kim S. Yu H.R. Hwang J. Kim J.I. Kim J.S. Digenome-seq: genome-wide profiling of CRISPR-Cas9 off-target effects in human cells.Nat. Methods. 2015; 12: 237-243, 1, 243Crossref PubMed Scopus (120) Google Scholar, Ran et al., 2015Ran F.A. Cong L. Yan W.X. Scott D.A. Gootenberg J.S. Kriz A.J. Zetsche B. Shalem O. Wu X. Makarova K.S. et al.In vivo genome editing using Staphylococcus aureus Cas9.Nature. 2015; 520: 186-191Crossref PubMed Scopus (283) Google Scholar, Tsai et al., 2015Tsai S.Q. Zheng Z. Nguyen N.T. Liebers M. Topkar V.V. Thapar V. Wyvekens N. Khayter C. Iafrate A.J. Le L.P. et al.GUIDE-seq enables genome-wide profiling of off-target cleavage by CRISPR-Cas nucleases.Nat. Biotechnol. 2015; 33: 187-197Crossref PubMed Scopus (225) Google Scholar, Wang et al., 2015Wang X. Wang Y. Wu X. Wang J. Wang Y. Qiu Z. Chang T. Huang H. Lin R.J. Yee J.K. Unbiased detection of off-target cleavage by CRISPR-Cas9 and TALENs using integrase-defective lentiviral vectors.Nat. Biotechnol. 2015; 33: 175-178Crossref PubMed Scopus (301) Google Scholar) and are important complements to biased off-target detection methods based on in silico prediction and targeted sequencing (Fu et al., 2013Fu Y. Foden J.A. Khayter C. Maeder M.L. Reyon D. Joung J.K. Sander J.D. High-frequency off-target mutagenesis induced by CRISPR-Cas nucleases in human cells.Nat. Biotechnol. 2013; 31: 822-826Crossref PubMed Scopus (322) Google Scholar, Hsu et al., 2013Hsu P.D. Scott D.A. Weinstein J.A. Ran F.A. Konermann S. Agarwala V. Li Y. Fine E.J. Wu X. Shalem O. et al.DNA targeting specificity of RNA-guided Cas9 nucleases.Nat. Biotechnol. 2013; 31: 827-832Crossref PubMed Scopus (816) Google Scholar, Mali et al., 2013aMali P. Aach J. Stranges P.B. Esvelt K.M. Moosburner M. Kosuri S. Yang L. Church G.M. CAS9 transcriptional activators for target specificity screening and paired nickases for cooperative genome engineering.Nat. Biotechnol. 2013; 31: 833-838Crossref PubMed Scopus (534) Google Scholar, Pattanayak et al., 2013Pattanayak V. Lin S. Guilinger J.P. Ma E. Doudna J.A. Liu D.R. High-throughput profiling of off-target DNA cleavage reveals RNA-programmed Cas9 nuclease specificity.Nat. Biotechnol. 2013; 31: 839-843Crossref PubMed Scopus (392) Google Scholar) (see Unbiased Genome-wide Off-Target Detection). The adoption of these protocols marks an important departure from methods for measuring an inherently biased subset of potential off-target sites. In addition to these protocols, the computational tools used for guide RNA design and off-target prediction are expanding to account for a deepening understanding of specificity-governing parameters in the cell, including detailed features of the off-target sequence and the Cas9 orthologs (see Computational Guide RNA Selection and Predictive Models). Furthermore, multiple methods have been developed to improve specificity by using natural or engineered orthologous Cas9s (see Cas9 Orthologs and New CRISPR Proteins), engineering the Cas9 protein or guide RNA (see Protein Engineering and Bespoke PAMs and Modified Guides), or modulating the kinetics and regulation of the CRISPR components in the cell (see Kinetics and Regulation). Meanwhile, use of nuclease-dead Cas9, or dCas9, for targeted binding applications such as transcriptional regulation have particular considerations given the distinctions between the Cas9 target search and nucleolytic mechanisms (see dCas9 Specificity). CRISPR specificity must also be considered in a broader sense to include cell type and temporal and spatial specificity. Last, the standardization of off-target analysis methods and data reporting in research publications would benefit the field by enabling comparison across studies and better algorithms for guide RNA design (see Broader Implications of Specificity and The Need for Standardization). To date, the predominant approach for identifying Cas9 nuclease off-target activity has been to (1) computationally predict likely off-target sites on the basis of sequence homology and then (2) assess any potential editing activity by enzymatic assays on the basis of mismatch-sensitive endonucleases (Guschin et al., 2010Guschin D.Y. Waite A.J. Katibah G.E. Miller J.C. Holmes M.C. Rebar E.J. A rapid and general assay for monitoring endogenous gene modification.Methods Mol. Biol. 2010; 649: 247-256Crossref PubMed Scopus (167) Google Scholar, Ran et al., 2013bRan F.A. Hsu P.D. Wright J. Agarwala V. Scott D.A. Zhang F. Genome engineering using the CRISPR-Cas9 system.Nat. Protoc. 2013; 8: 2281-2308Crossref PubMed Scopus (751) Google Scholar), Sanger sequencing, or targeted deep sequencing (see The Need for Standardization). These a priori predictions are critical, as ∼98% of Streptococcus pyogenes Cas9 (SpCas9) guide RNAs in human exons and promoters have at least one off-target site with three or fewer mismatches (Bolukbasi et al., 2016Bolukbasi M.F. Gupta A. Wolfe S.A. Creating and evaluating accurate CRISPR-Cas9 scalpels for genomic surgery.Nat. Methods. 2016; 13: 41-50Crossref PubMed Scopus (23) Google Scholar), and foundational Cas9 specificity studies collectively demonstrated that off-target sites with three or fewer mismatches are significantly more likely to be cleaved than more dissimilar sites (Fu et al., 2013Fu Y. Foden J.A. Khayter C. Maeder M.L. Reyon D. Joung J.K. Sander J.D. High-frequency off-target mutagenesis induced by CRISPR-Cas nucleases in human cells.Nat. Biotechnol. 2013; 31: 822-826Crossref PubMed Scopus (322) Google Scholar, Hsu et al., 2013Hsu P.D. Scott D.A. Weinstein J.A. Ran F.A. Konermann S. Agarwala V. Li Y. Fine E.J. Wu X. Shalem O. et al.DNA targeting specificity of RNA-guided Cas9 nucleases.Nat. Biotechnol. 2013; 31: 827-832Crossref PubMed Scopus (816) Google Scholar, Mali et al., 2013aMali P. Aach J. Stranges P.B. Esvelt K.M. Moosburner M. Kosuri S. Yang L. Church G.M. CAS9 transcriptional activators for target specificity screening and paired nickases for cooperative genome engineering.Nat. Biotechnol. 2013; 31: 833-838Crossref PubMed Scopus (534) Google Scholar, Pattanayak et al., 2013Pattanayak V. Lin S. Guilinger J.P. Ma E. Doudna J.A. Liu D.R. High-throughput profiling of off-target DNA cleavage reveals RNA-programmed Cas9 nuclease specificity.Nat. Biotechnol. 2013; 31: 839-843Crossref PubMed Scopus (392) Google Scholar). Selecting the most unique target site possible is thus a valuable strategy for improving specificity, because many gene editing applications have several possible guide RNAs capable of accomplishing the same experimental outcome (i.e., knocking out a gene by introducing indels in an exon of interest). Sequence uniqueness is thus an important initial filter for selecting guide RNAs with minimal potential off-target sites with high sequence homology. However, as the number of mismatches considered relative to the on-target site increases, the total number of potential off-target sites dramatically increases as well. For example, a benchmark guide RNA designed to target the EMX1 locus (Ran et al., 2015Ran F.A. Cong L. Yan W.X. Scott D.A. Gootenberg J.S. Kriz A.J. Zetsche B. Shalem O. Wu X. Makarova K.S. et al.In vivo genome editing using Staphylococcus aureus Cas9.Nature. 2015; 520: 186-191Crossref PubMed Scopus (283) Google Scholar), with no “off-by-one” mismatched off-target sites in the hg38 reference genome, has 10 “off-by-two” sites, 69 “off-by-three” sites, and 27,480 “off-by-six” sites. As a result, even targeted sequencing, likely the most scalable of the aforementioned approaches, is biased toward a small number of sites that can reasonably be assayed. However, Cas9-mediated cleavage has been reported at off-target sites with as many as six mismatches to the guide sequence (Tsai et al., 2015Tsai S.Q. Zheng Z. Nguyen N.T. Liebers M. Topkar V.V. Thapar V. Wyvekens N. Khayter C. Iafrate A.J. Le L.P. et al.GUIDE-seq enables genome-wide profiling of off-target cleavage by CRISPR-Cas nucleases.Nat. Biotechnol. 2015; 33: 187-197Crossref PubMed Scopus (225) Google Scholar), demonstrating the risk of missing detectable events by setting low “off-by” thresholds for the sake of practical, biased off-target screening. Furthermore, most computational off-target prediction tools do not adequately consider off-target sites with gaps, bulges, or alternative protospacer adjacent motif (PAM) sequences (sequence motifs recognized by Cas9 directly 3′ of the matching guide sequence in the target DNA; typically 5′-NGG for SpCas9 but also 5′-NAG with lower efficiency) (Table 1).Table 1Improvements to CRISPR-Cas9 SpecificityImprovementDescriptionAdvantageDisadvantageMeasurementTargeted deep sequencing (Ran et al., 2013bRan F.A. Hsu P.D. Wright J. Agarwala V. Scott D.A. Zhang F. Genome engineering using the CRISPR-Cas9 system.Nat. Protoc. 2013; 8: 2281-2308Crossref PubMed Scopus (751) Google Scholar)targeted amplicon NGS of putative or known off-target sites, followed by computational analysis to quantify the proportion of reads with indels near the PAM sitemore quantitative, sensitive, and scalable than alternative assays such as Surveyorbiased toward a subset of off-target sites that can reasonably be assessed; best used as complement to unbiased, genome-wide off-target detection methodsGUIDE-seq (Tsai et al., 2015Tsai S.Q. Zheng Z. Nguyen N.T. Liebers M. Topkar V.V. Thapar V. Wyvekens N. Khayter C. Iafrate A.J. Le L.P. et al.GUIDE-seq enables genome-wide profiling of off-target cleavage by CRISPR-Cas nucleases.Nat. Biotechnol. 2015; 33: 187-197Crossref PubMed Scopus (225) Google Scholar)captures DSBs with a dsODN, which is then used as a priming site for sequencingstraightforward wet-lab protocol with computational pipelines available online for data processingrequires efficient delivery of the dsODN, which may be toxic to some cell types at some doses, and has not been demonstrated for in vivo modelsBLESS (Ran et al., 2015Ran F.A. Cong L. Yan W.X. Scott D.A. Gootenberg J.S. Kriz A.J. Zetsche B. Shalem O. Wu X. Makarova K.S. et al.In vivo genome editing using Staphylococcus aureus Cas9.Nature. 2015; 520: 186-191Crossref PubMed Scopus (283) Google Scholar, Slaymaker et al., 2016Slaymaker I.M. Gao L. Zetsche B. Scott D.A. Yan W.X. Zhang F. Rationally engineered Cas9 nucleases with improved specificity.Science. 2016; 351: 84-88Crossref PubMed Scopus (160) Google Scholar)biochemical ligation of NGS sequencing adapters to exposed gDNA ends; computational filtering separates Cas9-mediated DSBs (aligned near PAM) from naturally occurring DSBs (more randomly distributed)no exogenous bait is introduced to cells; can be applied to tissue samples from in vivo modelssensitive to time of cell fixation; current configuration requires relatively large number of cellsDigenome-seq (Kim et al., 2015Kim D. Bae S. Park J. Kim E. Kim S. Yu H.R. Hwang J. Kim J.I. Kim J.S. Digenome-seq: genome-wide profiling of CRISPR-Cas9 off-target effects in human cells.Nat. Methods. 2015; 12: 237-243, 1, 243Crossref PubMed Scopus (120) Google Scholar, Kim et al., 2016bKim 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. 2016; 26: 406-415Crossref PubMed Scopus (18) Google Scholar)cell-free gDNA samples are digested in vitro by Cas9 RNP with multiplexed guide RNAs before WGS; cut sites are identified on the basis of read alignmentcan be applied to any cell type as digestion performed on extracted gDNA; more sensitive than GUIDE-seq in a head-to-headWGS may be costly; must be paired with one of the other methods to validate the sites discovered in vitro are truly mutagenized in the cellComputational Guide SelectionSpecificity score (Hsu et al., 2013Hsu P.D. Scott D.A. Weinstein J.A. Ran F.A. Konermann S. Agarwala V. Li Y. Fine E.J. Wu X. Shalem O. et al.DNA targeting specificity of RNA-guided Cas9 nucleases.Nat. Biotechnol. 2013; 31: 827-832Crossref PubMed Scopus (816) Google Scholar) and CFD (Doench et al., 2016Doench J.G. Fusi N. Sullender M. Hegde M. Vaimberg E.W. Donovan K.F. Smith I. Tothova Z. Wilen C. Orchard R. et al.Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9.Nat. Biotechnol. 2016; 34: 184-191Crossref PubMed Scopus (0) Google Scholar)an experimentally derived function to score the likelihood of an off-target site being edited, on the basis of the position and nature of its mismatchesa continuous variable to distinguish guide RNAs during design and to rank off-target sites for targeted sequencing follow-upscore is derived from SpCas9 data with 20-mer guides, so it may not generalize to other contextsWGS of reference genome (Yang et al., 2014Yang L. Grishin D. Wang G. Aach J. Zhang C.Z. Chari R. Homsy J. Cai X. Zhao Y. Fan J.B. et al.Targeted and genome-wide sequencing reveal single nucleotide variations impacting specificity of Cas9 in human stem cells.Nat. Commun. 2014; 5: 5507Crossref PubMed Scopus (0) Google Scholar)WGS of the relevant cell line, animal model, patient, etc. (Box 1)identify new off-target sites created by genetic variation, which are not present in the reference genomes (i.e., hg38)remains costly; custom reference genomes only available with some guide design tools (Table 2)Protein EngineeringSingle/paired nickases (Cong et al., 2013Cong L. Ran F.A. Cox D. Lin S. Barretto R. Habib N. Hsu P.D. Wu X. Jiang W. Marraffini L.A. Zhang F. Multiplex genome engineering using CRISPR/Cas systems.Science. 2013; 339: 819-823Crossref PubMed Scopus (2540) Google Scholar, Mali et al., 2013aMali P. Aach J. Stranges P.B. Esvelt K.M. Moosburner M. Kosuri S. Yang L. Church G.M. CAS9 transcriptional activators for target specificity screening and paired nickases for cooperative genome engineering.Nat. Biotechnol. 2013; 31: 833-838Crossref PubMed Scopus (534) Google Scholar, Ran et al., 2013aRan F.A. Hsu P.D. Lin C.Y. Gootenberg J.S. Konermann S. Trevino A.E. Scott D.A. Inoue A. Matoba S. Zhang Y. Zhang F. Double nicking by RNA-guided CRISPR Cas9 for enhanced genome editing specificity.Cell. 2013; 154: 1380-1389Abstract Full Text Full Text PDF PubMed Scopus (742) Google Scholar)a point mutation at the active site of one of the Cas9 nuclease domains yields a targeted nickase; paired nickases targeting complementary strands create a deletionnicks are repaired with higher fidelity than DSBs, so off-target edits are less frequent; nickases can also mediate efficient homology directed repairless efficient on-target editing with some guide RNAsSpCas9 PAM Variant D1135E (Kleinstiver et al., 2015bKleinstiver B.P. Prew M.S. Tsai S.Q. Topkar V.V. Nguyen N.T. Zheng Z. Gonzales A.P. Li Z. Peterson R.T. Yeh J.R. et al.Engineered CRISPR-Cas9 nucleases with altered PAM specificities.Nature. 2015; 523: 481-485Crossref PubMed Scopus (163) Google Scholar)a single point mutation increases specificity for the 5′-NGG PAMsignificant decrease in editing at 5′-NAG and 5′-NGA PAMs; improved genome-wide specificity for several guides as assessed by GUIDE-seqon-target efficiency may be affected; it was comparable with wtCas9 for six guides by T7E1 but somewhat lower for three guides by deep sequencingeSpCas9 (Slaymaker et al., 2016Slaymaker I.M. Gao L. Zetsche B. Scott D.A. Yan W.X. Zhang F. Rationally engineered Cas9 nucleases with improved specificity.Science. 2016; 351: 84-88Crossref PubMed Scopus (160) Google Scholar)three mutations within the nt-groove weaken Cas9’s non-target DNA strand stabilization and therefore increase stringency of guide RNA-DNA complementation for nuclease activationoff-target editing was nearly entirely avoided, as assessed by both BLESS and targeted deep sequencingon-target efficiency may be affected, although it was comparable with wtCas9 for most of the guide RNAs reportedSpCas9-HF (Kleinstiver et al., 2016aKleinstiver B.P. Pattanayak V. Prew M.S. Tsai S.Q. Nguyen N.T. Zheng Z. Joung J.K. 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