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Computational Approaches for Designing Highly Specific and Efficient sgRNAs

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Microbial Systems Biology

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2349))

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Abstract

The easily programmable CRISPR/Cas9 system has found applications in biomedical research as well as microbial and crop applications, due to its ability to create site-specific edits. This powerful and flexible system has also been modified to enable inducible gene regulation, epigenome modifications and high-throughput screens. Designing efficient and specific guides for the nuclease is a key step and also a major challenge in effective application. This chapter describes rules for sgRNA design and important features to consider while touching upon bioinformatics advances in predicting efficient guides. Computational tools that suggest improved guides, depending on application, or predict off-targets have also been mentioned and compared.

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References

  1. Cong L, Ran FA, Cox D, Lin S, Barretto R, Habib N et al (2013) Multiplex genome engineering using CRISPR/Cas systems. Science 339(6121):819–823

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Mali P, Yang L, Esvelt KM, Aach J, Guell M, DiCarlo JE et al (2013) RNA-guided human genome engineering via Cas9. Science 339(6121):823–826

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Malina A, Mills JR, Cencic R, Yan Y, Fraser J, Schippers LM et al (2013) Repurposing CRISPR/Cas9 for in situ functional assays. Genes Dev 27(23):2602–2614

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Zhou Y, Zhu S, Cai C, Yuan P, Li C, Huang Y et al (2014) High-throughput screening of a CRISPR/Cas9 library for functional genomics in human cells. Nature 509(7501):487–491

    Article  CAS  PubMed  Google Scholar 

  5. Dhanjal JK, Radhakrishnan N, Sundar D (2017) Identifying synthetic lethal targets using CRISPR/Cas9 system. Methods 131:66–73

    Article  CAS  PubMed  Google Scholar 

  6. Qiu XY, Zhu LY, Zhu CS, Ma JX, Hou T, Wu XM et al (2018) High-effective and low-cost microRNA detection with CRISPR-Cas9. ACS Synth Biol 7(3):807–813

    Article  CAS  PubMed  Google Scholar 

  7. Sergiu C, Diana G, Amin H, Ioana BN (2018) Restoring the p53 ‘guardian’ phenotype in p53-deficient tumor cells with CRISPR/Cas9. Trends Biotechnol 36(7):653–660

    Article  CAS  Google Scholar 

  8. Rauscher B, Heigwer F, Henkel L, Hielscher T, Voloshanenko O, Boutros M (2018) Toward an integrated map of genetic interactions in cancer cells. Mol Syst Biol 14(2):e7656

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Pham HT, Mesplede T (2018) The latest evidence for possible HIV-1 curative strategies. Drugs Context 7:212522

    Article  PubMed  PubMed Central  Google Scholar 

  10. Uppada V, Gokara M, Rasineni GK (2018) Diagnosis and therapy with CRISPR advanced CRISPR based tools for point of care diagnostics and early therapies. Gene 656:22–22

    Article  CAS  PubMed  Google Scholar 

  11. Shi J, Wang E, Milazzo JP, Wang Z, Kinney JB, Vakoc CR (2015) Discovery of cancer drug targets by CRISPR-Cas9 screening of protein domains. Nat Biotechnol 33(6):661–667

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Chen Y, Cao J, Xiong M, Petersen AJ, Dong Y, Tao Y et al (2015) Engineering human stem cell lines with inducible gene knockout using CRISPR/Cas9. Cell Stem Cell 17(2):233–244

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. Belhaj K, Chaparro-Garcia A, Kamoun S, Patron NJ, Nekrasov V (2015) Editing plant genomes with CRISPR/Cas9. Curr Opin Biotechnol 32:76–84

    Article  CAS  PubMed  Google Scholar 

  14. Lowder LG, Zhang D, Baltes NJ, Paul JW III, Tang X, Zheng X et al (2015) A CRISPR/Cas9 toolbox for multiplexed plant genome editing and transcriptional regulation. Plant Physiol 169(2):971–985

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Khatodia S, Bhatotia K, Passricha N, Khurana SM, Tuteja N (2016) The CRISPR/Cas genome-editing tool: application in improvement of crops. Front Plant Sci 7:506

    Article  PubMed  PubMed Central  Google Scholar 

  16. Choi KR, Lee SY (2016) CRISPR technologies for bacterial systems: current achievements and future directions. Biotechnol Adv 34(7):1180–1209

    Article  CAS  PubMed  Google Scholar 

  17. Estrela R, Cate JH (2016) Energy biotechnology in the CRISPR-Cas9 era. Curr Opin Biotechnol 38:79–84

    Article  CAS  PubMed  Google Scholar 

  18. Donohoue PD, Barrangou R, May AP (2018) Advances in industrial biotechnology using CRISPR-Cas systems. Trends Biotechnol 36(2):134–146

    Article  CAS  PubMed  Google Scholar 

  19. Deltcheva E, Chylinski K, Sharma CM, Gonzales K, Chao Y, Pirzada ZA et al (2011) CRISPR RNA maturation by trans-encoded small RNA and host factor RNase III. Nature 471(7340):602–607

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Hawkins JS, Wong S, Peters JM, Almeida R, Qi LS (2015) Targeted transcriptional repression in bacteria using CRISPR interference (CRISPRi). Methods Mol Biol 1311:349–362

    Article  PubMed  PubMed Central  Google Scholar 

  21. Ran FA, Hsu PD, Wright J, Agarwala V, Scott DA, Zhang F (2013) Genome engineering using the CRISPR-Cas9 system. Nat Protoc 8(11):2281–2308

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Shalem O, Sanjana NE, Hartenian E, Shi X, Scott DA, Mikkelson T et al (2014) Genome-scale CRISPR-Cas9 knockout screening in human cells. Science 343(6166):84–87

    Article  CAS  PubMed  Google Scholar 

  23. Chu HW, Rios C, Huang C, Wesolowska-Andersen A, Burchard EG, O'Connor BP et al (2015) CRISPR-Cas9-mediated gene knockout in primary human airway epithelial cells reveals a proinflammatory role for MUC18. Gene Ther 22(10):822–829

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Feng X, Zhao D, Zhang X, Ding X, Bi C (2018) CRISPR/Cas9 assisted multiplex genome editing technique in Escherichia coli. Biotechnol J 13(9):1700604

    Article  CAS  Google Scholar 

  25. de Vries ARG, de Groot PA, van den Broek M, Daran J-MG (2017) CRISPR-Cas9 mediated gene deletions in lager yeast Saccharomyces pastorianus. Microb Cell Fact 16(1):222

    Article  PubMed Central  CAS  Google Scholar 

  26. Serif M, Dubois G, Finoux A-L, Teste M-A, Jallet D, Daboussi F (2018) One-step generation of multiple gene knock-outs in the diatom Phaeodactylum tricornutum by DNA-free genome editing. Nat Commun 9(1):3924

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. Hegde S, Nilyanimit P, Kozlova E, Narra HP, Sahni SK, Hughes GL (2018) CRISPR/Cas9-mediated gene deletion of the ompA gene in an enterobacter gut symbiont impairs biofilm formation and reduces gut colonization of Aedes aegypti mosquitoes. bioRxiv 13(12):e0007883

    Google Scholar 

  28. Shen Z, Zhang X, Chai Y, Zhu Z, Yi P, Feng G et al (2014) Conditional knockouts generated by engineered CRISPR-Cas9 endonuclease reveal the roles of coronin in C. elegans neural development. Dev Cell 30(5):625–636

    Article  CAS  PubMed  Google Scholar 

  29. Bae S, Kweon J, Kim HS, Kim JS (2014) Microhomology-based choice of Cas9 nuclease target sites. Nat Methods 11(7):705–706

    Article  CAS  PubMed  Google Scholar 

  30. Doench JG, Hartenian E, Graham DB, Tothova Z, Hegde M, Smith I et al (2014) Rational design of highly active sgRNAs for CRISPR-Cas9-mediated gene inactivation. Nat Biotechnol 32(12):1262–1267

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Maruyama T, Dougan SK, Truttmann MC, Bilate AM, Ingram JR, Ploegh HL (2015) Increasing the efficiency of precise genome editing with CRISPR-Cas9 by inhibition of nonhomologous end joining. Nat Biotechnol 33(5):538–542

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Li HL, Fujimoto N, Sasakawa N, Shirai S, Ohkame T, Sakuma T et al (2015) Precise correction of the dystrophin gene in duchenne muscular dystrophy patient induced pluripotent stem cells by TALEN and CRISPR-Cas9. Stem Cell Rep 4(1):143–154

    Article  CAS  Google Scholar 

  33. Peng J, Wang Y, Jiang J, Zhou X, Song L, Wang L et al (2015) Production of human albumin in pigs through CRISPR/Cas9-mediated knockin of human cDNA into swine albumin locus in the zygotes. Sci Rep 5:16705

    Article  PubMed  PubMed Central  Google Scholar 

  34. Platt RJ, Chen S, Zhou Y, Yim MJ, Swiech L, Kempton HR et al (2014) CRISPR-Cas9 knockin mice for genome editing and cancer modeling. Cell 159(2):440–455

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Dow LE (2015) Modeling disease in vivo with CRISPR/Cas9. Trends Mol Med 21(10):609–621

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Zhang MM, Wong FT, Wang Y, Luo S, Lim YH, Heng E et al (2017) CRISPR–Cas9 strategy for activation of silent Streptomyces biosynthetic gene clusters. Nat Chem Biol 13(6):607

    Article  CAS  Google Scholar 

  37. Behler J, Vijay D, Hess WR, Akhtar MK (2018) CRISPR-based technologies for metabolic engineering in cyanobacteria. Trends Biotechnol 36(10):996–1010

    Article  CAS  PubMed  Google Scholar 

  38. Qi LS, Larson MH, Gilbert LA, Doudna JA, Weissman JS, Arkin AP et al (2013) Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression. Cell 152(5):1173–1183

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Cheng AW, Wang H, Yang H, Shi L, Katz Y, Theunissen TW et al (2013) Multiplexed activation of endogenous genes by CRISPR-on, an RNA-guided transcriptional activator system. Cell Res 23(10):1163–1171

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Chuai GH, Wang QL, Liu Q (2017) In silico meets in vivo: towards computational CRISPR-based sgRNA design. Trends Biotechnol 35(1):12–21

    Article  CAS  PubMed  Google Scholar 

  41. Cong L, Ran FA, Cox D, Lin S, Barretto R, Habib N et al (2013) Multiplex genome engineering using CRISPR/Cas systems. Science 339(6121):819–823

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Xu H, Xiao T, Chen CH, Li W, Meyer CA, Wu Q et al (2015) Sequence determinants of improved CRISPR sgRNA design. Genome Res 25(8):1147–1157

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Jinek M, Chylinski K, Fonfara I, Hauer M, Doudna JA, Charpentier E (2012) A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337(6096):816–821

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Mekler V, Minakhin L, Severinov K (2017) Mechanism of duplex DNA destabilization by RNA-guided Cas9 nuclease during target interrogation. Proc Natl Acad Sci U S A 114(21):5443–5448

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Tim Wang JJW, Sabatini DM, Lander ES (2014) Genetic screens in human cells using the CRISPR-Cas9 system. Science 343(6166):80–84

    Article  PubMed  CAS  Google Scholar 

  46. Wang X, Wang X, Varma RK, Beauchamp L, Magdaleno S, Sendera TJ (2009) Selection of hyperfunctional siRNAs with improved potency and specificity. Nucleic Acids Res 37(22):e152

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  47. Long D, Lee R, Williams P, Chan CY, Ambros V, Ding Y (2007) Potent effect of target structure on microRNA function. Nat Struct Mol Biol 14(4):287–294

    Article  CAS  PubMed  Google Scholar 

  48. Robins H, Li Y, Padgett RW (2005) Incorporating structure to predict microRNA targets. Proc Natl Acad Sci U S A 102(11):4006–4009

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Wong N, Liu W, Wang X (2015) WU-CRISPR: characteristics of functional guide RNAs for the CRISPR/Cas9 system. Genome Biol 16:218

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  50. Wu X, Scott DA, Kriz AJ, Chiu AC, Hsu PD, Dadon DB et al (2014) Genome-wide binding of the CRISPR endonuclease Cas9 in mammalian cells. Nat Biotechnol 32(7):670–676

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Fu Y, Foden JA, Khayter C, Maeder ML, Reyon D, Joung JK et al (2013) High-frequency off-target mutagenesis induced by CRISPR-Cas nucleases in human cells. Nat Biotechnol 31(9):822–826

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Hsu PD, Scott DA, Weinstein JA, Ran FA, Konermann S, Agarwala V et al (2013) DNA targeting specificity of RNA-guided Cas9 nucleases. Nat Biotechnol 31(9):827–832

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Yu C, Liu Y, Ma T, Liu K, Xu S, Zhang Y et al (2015) Small molecules enhance CRISPR genome editing in pluripotent stem cells. Cell Stem Cell 16(2):142–147

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. G-h C, Wang Q-L, Liu Q (2017) In silico meets in vivo: towards computational CRISPR-based sgRNA design. Trends Biotechnol 35(1):12–21

    Article  CAS  Google Scholar 

  55. Fu Y, Sander JD, Reyon D, Cascio VM, Joung JK (2014) Improving CRISPR-Cas nuclease specificity using truncated guide RNAs. Nat Biotechnol 32(3):279–284

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Daesik Kim SB, Park J, Kim E, Kim S, Yu HR, Hwang J, Kim J-I, Kim J-S (2015) Digenome-seq: genome-wide profiling of CRISPR-Cas9 off-target effects in human cells. Nat Methods 12:237–242

    Article  PubMed  CAS  Google Scholar 

  57. Ran FA, Hsu PD, Lin CY, Gootenberg JS, Konermann S, Trevino AE et al (2013) Double nicking by RNA-guided CRISPR Cas9 for enhanced genome editing specificity. Cell 154(6):1380–1389

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Tsai SQ, Wyvekens N, Khayter C, Foden JA, Thapar V, Reyon D et al (2014) Dimeric CRISPR RNA-guided FokI nucleases for highly specific genome editing. Nat Biotechnol 32(6):569–576

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Guilinger JP, Thompson DB, Liu DR (2014) Fusion of catalytically inactive Cas9 to FokI nuclease improves the specificity of genome modification. Nat Biotechnol 32(6):577–582

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Kleinstiver BP, Pattanayak V, Prew MS, Tsai SQ, Nguyen NT, Zheng Z et al (2016) High-fidelity CRISPR-Cas9 nucleases with no detectable genome-wide off-target effects. Nature 529(7587):490–495

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Slaymaker IM, Gao L, Zetsche B, Scott DA, Yan WX, Zhang F (2016) Rationally engineered Cas9 nucleases with improved specificity. Science 351(6268):84–88

    Article  CAS  PubMed  Google Scholar 

  62. Chen JS, Dagdas YS, Kleinstiver BP, Welch MM, Sousa AA, Harrington LB et al (2017) Enhanced proofreading governs CRISPR-Cas9 targeting accuracy. Nature 550(7676):407–410

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Zuris JA, Thompson DB, Shu Y, Guilinger JP, Bessen JL, Hu JH et al (2015) Cationic lipid-mediated delivery of proteins enables efficient protein-based genome editing in vitro and in vivo. Nat Biotechnol 33(1):73–80

    Article  CAS  PubMed  Google Scholar 

  64. Kim S, Kim D, Cho SW, Kim J, Kim JS (2014) Highly efficient RNA-guided genome editing in human cells via delivery of purified Cas9 ribonucleoproteins. Genome Res 24(6):1012–1019

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Zetsche B, Volz SE, Zhang F (2015) A split-Cas9 architecture for inducible genome editing and transcription modulation. Nat Biotechnol 33(2):139–142

    Article  CAS  PubMed  Google Scholar 

  66. Petris G, Casini A, Montagna C, Lorenzin F, Prandi D, Romanel A et al (2017) Hit and go CAS9 delivered through a lentiviral based self-limiting circuit. Nat Commun 8:15334

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Shin J, Jiang F, Liu J-J, Bray NL, Rauch BJ, Baik SH, Nogales E, Bondy-Denomy J, Corn JE, Doudna JA (2017) Disabling Cas9 by an anti-CRISPR DNA mimic. Sci Adv 3(7):e1701620

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  68. Ryan DE, Taussig D, Steinfeld I, Phadnis SM, Lunstad BD, Singh M et al (2017) Improving CRISPR-Cas specificity with chemical modifications in single-guide RNAs. Nucleic Acids Res 46(2):792–803

    Article  PubMed Central  CAS  Google Scholar 

  69. Cameron P, Fuller CK, Donohoue PD, Jones BN, Thompson MS, Carter MM et al (2017) Mapping the genomic landscape of CRISPR-Cas9 cleavage. Nat Methods 14(6):600–606

    Article  CAS  PubMed  Google Scholar 

  70. Liu H, Wei Z, Dominguez A, Li Y, Wang X, Qi LS (2015) CRISPR-ERA: a comprehensive design tool for CRISPR-mediated gene editing, repression and activation. Bioinformatics 31(22):3676–3678

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Xu H, Xiao T, Chen C-H, Li W, Meyer CA, Wu Q et al (2015) Sequence determinants of improved CRISPR sgRNA design. Genome Res 25(8):1147–1157

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Ma M, Ye AY, Zheng W, Kong L (2013) A guide RNA sequence design platform for the CRISPR/Cas9 system for model organism genomes. Biomed Res Int 2013:270805

    PubMed  PubMed Central  Google Scholar 

  73. Montague TG, Cruz JM, Gagnon JA, Church GM, Valen E (2014) CHOPCHOP: a CRISPR/Cas9 and TALEN web tool for genome editing. Nucleic Acids Res 42(Web Server issue):W401–W407

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. O'Brien A, Bailey TL (2014) GT-scan: identifying unique genomic targets. Bioinformatics 30(18):2673–2675

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Heigwer F, Kerr G, Boutros M (2014) E-CRISP: fast CRISPR target site identification. Nat Methods 11(2):122

    Article  CAS  PubMed  Google Scholar 

  76. Lei Y, Lu L, Liu HY, Li S, Xing F, Chen LL (2014) CRISPR-P: a web tool for synthetic single-guide RNA design of CRISPR-system in plants. Mol Plant 7(9):1494–1496

    Article  CAS  PubMed  Google Scholar 

  77. Bae S, Park J, Kim JS (2014) Cas-OFFinder: a fast and versatile algorithm that searches for potential off-target sites of Cas9 RNA-guided endonucleases. Bioinformatics 30(10):1473–1475

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Cradick TJ, Qiu P, Lee CM, Fine EJ, Bao G (2014) COSMID: a web-based tool for identifying and validating CRISPR/Cas off-target sites. Mol Ther Nucl Acids 3(12):e214

    Article  CAS  Google Scholar 

  79. Lin Y, Cradick TJ, Brown MT, Deshmukh H, Ranjan P, Sarode N et al (2014) CRISPR/Cas9 systems have off-target activity with insertions or deletions between target DNA and guide RNA sequences. Nucleic Acids Res 42(11):7473–7485

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Doench JG, Fusi N, Sullender M, Hegde M, Vaimberg EW, Donovan KF et al (2016) Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nat Biotechnol 34(2):184

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Tsai SQ, Zheng Z, Nguyen NT, Liebers M, Topkar VV, Thapar V et al (2015) GUIDE-seq enables genome-wide profiling of off-target cleavage by CRISPR-Cas nucleases. Nat Biotechnol 33(2):187–197

    Article  CAS  PubMed  Google Scholar 

  82. Lee CM, Cradick TJ, Fine EJ, Bao G (2016) Nuclease target site selection for maximizing on-target activity and minimizing off-target effects in genome editing. Mol Ther 24(3):475–487

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. 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(18):e118

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  84. Dhanjal JK, Radhakrishnan N, Sundar D (2018) CRISPcut: a novel tool for designing optimal sgRNAs for CRISPR/Cas9 based experiments in human cells. Genomics 111(4):560–566

    Article  PubMed  CAS  Google Scholar 

  85. Lei Y, Lu L, Liu HY, Li S, Xing F, Chen LL (2014) CRISPR-P: a web tool for synthetic single-guide RNA design of CRISPR-system in plants. Mol Plant 7(9):1494-1496

    Google Scholar 

  86. Gratz SJ, Ukken FP, Rubinstein CD, Thiede G, Donohue LK, Cummings AM et al (2014) Highly specific and efficient CRISPR/Cas9-catalyzed homology-directed repair in Drosophila. Genetics 196(4):961–971

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Peng D, Tarleton R (2015) EuPaGDT: a web tool tailored to design CRISPR guide RNAs for eukaryotic pathogens. Microb Genomics 1(4):e000033

    Article  Google Scholar 

  88. MacPherson CR, Scherf A (2015) Flexible guide-RNA design for CRISPR applications using protospacer workbench. Nat Biotechnol 33(8):805

    Article  CAS  PubMed  Google Scholar 

  89. Li W, Xu H, Xiao T, Cong L, Love MI, Zhang F et al (2014) MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens. Genome Biol 15(12):554

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  90. Winter J, Breinig M, Heigwer F, Brügemann D, Leible S, Pelz O et al (2015) caRpools: an R package for exploratory data analysis and documentation of pooled CRISPR/Cas9 screens. Bioinformatics 32(4):632–634

    Article  PubMed  CAS  Google Scholar 

  91. Güell M, Yang L, Church GM (2014) Genome editing assessment using CRISPR genome analyzer (CRISPR-GA). Bioinformatics 30(20):2968–2970

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  92. Pinello L, Canver M, Hoban M (2015) Crispresso: sequencing analysis toolbox for crispr-cas9 genome editing. bioRxiv. https://doi.org/10.1101/031203

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Authors and Affiliations

  1. Department of Biochemical Engineering and Biotechnology, DBT-AIST International Laboratory for Advanced Biomedicine (DAILAB), Indian Institute of Technology Delhi, Hauz Khas, New Delhi, India

    Jaspreet Kaur Dhanjal, Dhvani Vora, Navaneethan Radhakrishnan & Durai Sundar

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  1. Jaspreet Kaur Dhanjal
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  2. Dhvani Vora
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  3. Navaneethan Radhakrishnan
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  4. Durai Sundar
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Correspondence to Durai Sundar .

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  1. Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, CA, USA

    Ali Navid

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Dhanjal, J.K., Vora, D., Radhakrishnan, N., Sundar, D. (2022). Computational Approaches for Designing Highly Specific and Efficient sgRNAs. In: Navid, A. (eds) Microbial Systems Biology. Methods in Molecular Biology, vol 2349. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1585-0_8

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  • DOI: https://doi.org/10.1007/978-1-0716-1585-0_8

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