Computational Tools and Resources for CRISPR/Cas Genome Editing  

作　　者：Chao Li Wen Chu Rafaqat Ali Gill Shifei Sang Yuqin Shi Xuezhi Hu Yuting Yang Qamar U.Zaman Baohong Zhang 

机构地区：[1]Oil Crops Research Institute,Chinese Academy of Agricultural Sciences,Key Laboratory for Biology and Genetic Improvement of Oil Crops,Ministry of Agriculture and Rural Affairs,Wuhan 430062,China [2]Graduate School of Chinese Academy of Agricultural Sciences,Beijing 100081,China [3]Department of Biology,East Carolina University,Greenville,NC 27858,USA

出　　处：《Genomics, Proteomics & Bioinformatics》2023年第1期108-126,共19页基因组蛋白质组与生物信息学报（英文版）

基　　金：We greatly appreciate Dr.Jeffrey McKinnon for his thoughtful proofreading and wonderful suggestion on this manuscript.We also greatly appreciate the scientific community for making huge progress in this field.We have tried to cite as many references as possible.However,due to the page limitation,there may be some important works not cited here;we apologize for this.The work in Dr.Baohong Zhang’s Laboratory is supported in part by Cotton Incorporated and the National Science Foundation,the United States(Grant No.1658709);This work was also supported by the National Natural Science Foundation of China(Grant No.31700316);the Fundamental Research Funds for the Central Nonprofit Scientific Institution(Grant No.1610172018009);the Natural Science Foundation of Hubei Province,China(Grant No.2018CFB543).

摘　　要：The past decade has witnessed a rapid evolution in identifying more versatile clustered regularly interspaced short palindromic repeats(CRISPR)/CRISPR-associated protein(Cas)nucleases and their functional variants,as well as in developing precise CRISPR/Cas-derived genome editors.The programmable and robust features of the genome editors provide an effective RNAguided platform for fundamental life science research and subsequent applications in diverse scenarios,including biomedical innovation and targeted crop improvement.One of the most essential principles is to guide alterations in genomic sequences or genes in the intended manner without undesired off-target impacts,which strongly depends on the efficiency and specificity of single guide RNA(sgRNA)-directed recognition of targeted DNA sequences.Recent advances in empirical scoring algorithms and machine learning models have facilitated sgRNA design and off-target prediction.In this review,we first briefly introduce the different features of CRISPR/Cas tools that should be taken into consideration to achieve specific purposes.Secondly,we focus on the computer-assisted tools and resources that are widely used in designing sgRNAs and analyzing CRISPR/Cas-induced on-and off-target mutations.Thirdly,we provide insights into the limitations of available computational tools that would help researchers of this field for further optimization.Lastly,we suggest a simple but effective workflow for choosing and applying web-based resources and tools for CRISPR/Cas genome editing.

关 键 词：Genome editing Efficiency and specificity CRISPR/Cas9 sgRNA Computational tool Algorithm 

分 类 号：Q78[生物学—分子生物学]