Generalizable sgRNA design for improved CRISPR/Cas9 editing efficiency

MOTIVATION The development of CRISPR/Cas9 technology has provided a simple yet powerful system for targeted genome editing. In recent years, this system has been widely used for various gene editing applications. The CRISPR editing efficacy is mainly dependent on the sgRNA, which guides Cas9 for genome cleavage. While there have been multiple attempts at improving sgRNA design, there is a pressing need for greater sgRNA potency and generalizability across various experimental conditions. RESULTS We employed a unique plasmid library expressed in human cells to quantify the potency of thousands of CRISPR/Cas9 sgRNAs. Differential sequence and structural features among the most and least potent sgRNAs were then used to train a machine learning algorithm for assay design. Comparative analysis indicates that our new algorithm outperforms existing CRISPR/Cas9 sgRNA design tools. AVAILABILITY The new sgRNA design tool is freely accessible as a web application via http://crispr.wustl.edu. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

[1]  Scott Bailey,et al.  Cut Site Selection by the Two Nuclease Domains of the Cas9 RNA-guided Endonuclease* , 2014, The Journal of Biological Chemistry.

[2]  Eli J. Fine,et al.  DNA targeting specificity of RNA-guided Cas9 nucleases , 2013, Nature Biotechnology.

[3]  Yi Zheng,et al.  CRISPR/Cas9 cleavage efficiency regression through boosting algorithms and Markov sequence profiling , 2018, Bioinform..

[4]  J. Vogel,et al.  CRISPR RNA maturation by trans-encoded small RNA and host factor RNase III , 2011, Nature.

[5]  Yilong Li,et al.  Genome-wide recessive genetic screening in mammalian cells with a lentiviral CRISPR-guide RNA library , 2013, Nature Biotechnology.

[6]  Charles A Gersbach,et al.  Increasing the specificity of CRISPR systems with engineered RNA secondary structures , 2019, Nature Biotechnology.

[7]  Ivo L. Hofacker,et al.  Vienna RNA secondary structure server , 2003, Nucleic Acids Res..

[8]  Xiaowei Wang,et al.  WU-CRISPR: characteristics of functional guide RNAs for the CRISPR/Cas9 system , 2015, Genome Biology.

[9]  G. Church,et al.  Unraveling CRISPR-Cas9 genome engineering parameters via a library-on-library approach , 2015, Nature Methods.

[10]  Jennifer Doudna,et al.  RNA-programmed genome editing in human cells , 2013, eLife.

[11]  Meagan E. Sullender,et al.  Rational design of highly active sgRNAs for CRISPR-Cas9–mediated gene inactivation , 2014, Nature Biotechnology.

[12]  Guohui Chuai,et al.  DeepCRISPR: optimized CRISPR guide RNA design by deep learning , 2018, Genome Biology.

[13]  Clifford A. Meyer,et al.  Sequence determinants of improved CRISPR sgRNA design , 2015, Genome research.

[14]  David A. Scott,et al.  Double Nicking by RNA-Guided CRISPR Cas9 for Enhanced Genome Editing Specificity , 2013, Cell.

[15]  J. L. Mateo,et al.  Refined sgRNA efficacy prediction improves large- and small-scale CRISPR–Cas9 applications , 2017, Nucleic acids research.

[16]  Neville E Sanjana,et al.  Genome-scale CRISPR-Cas9 knockout and transcriptional activation screening , 2016, Nature Protocols.

[17]  David K. Gifford,et al.  Predictable and precise template-free CRISPR editing of pathogenic variants , 2018, Nature.

[18]  James E. DiCarlo,et al.  RNA-Guided Human Genome Engineering via Cas9 , 2013, Science.

[19]  Meagan E. Sullender,et al.  Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9 , 2015, Nature Biotechnology.

[20]  David A. Scott,et al.  Rationally engineered Cas9 nucleases with improved specificity , 2015, Science.

[21]  Andrew R. Bassett,et al.  Predicting the mutations generated by repair of Cas9-induced double-strand breaks , 2018, Nature Biotechnology.

[22]  Jin-Wu Nam,et al.  In vivo high-throughput profiling of CRISPR–Cpf1 activity , 2016, Nature Methods.

[23]  P. Hsu,et al.  Methods for Optimizing CRISPR-Cas9 Genome Editing Specificity. , 2016, Molecular cell.

[24]  Neville E. Sanjana,et al.  Genome-Scale CRISPR-Cas9 Knockout Screening in Human Cells , 2014, Science.

[25]  J. Joung,et al.  High-fidelity CRISPR-Cas9 variants with undetectable genome-wide off-targets , 2015, Nature.

[26]  J. Doudna,et al.  A Programmable Dual-RNA–Guided DNA Endonuclease in Adaptive Bacterial Immunity , 2012, Science.

[27]  R. Barrangou,et al.  CRISPR Provides Acquired Resistance Against Viruses in Prokaryotes , 2007, Science.

[28]  O. Abudayyeh,et al.  Pairwise library screen systematically interrogates Staphylococcus aureus Cas9 specificity in human cells , 2018, Nature Communications.

[29]  David H. Wolpert,et al.  Stacked generalization , 1992, Neural Networks.

[30]  J. Doudna,et al.  The new frontier of genome engineering with CRISPR-Cas9 , 2014, Science.

[31]  Yulia Yuzenkova,et al.  Mechanism of Eukaryotic RNA Polymerase III Transcription Termination , 2013, Science.

[32]  E. Lander,et al.  Genetic Screens in Human Cells Using the CRISPR-Cas9 System , 2013, Science.