Computational Tools and Resources for CRISPR/Cas Genome Editing

文献类型： 外文期刊

第一作者： Li, Chao

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

作者机构： Chinese Acad Agr Sci, Oil Crops Res Inst, Key Lab Biol & Genet Improvement Oil Crops, Minist Agr & Rural Affairs, Wuhan, Peoples R China;Chinese Acad Agr Sci, Grad Sch, Beijing 100081, Peoples R China;East Carolina Univ, Dept Biol, Greenville, NC 27858 USA

关键词： Genome editing; Efficiency and specificity; CRISPR; Cas9; sgRNA; Computational tool; Algorithm

期刊名称：GENOMICS PROTEOMICS & BIOINFORMATICS （ 2022影响因子：9.5； 五年影响因子：10.1 ）

ISSN： 1672-0229

年卷期： 2023 年 21 卷 1 期

页码：

收录情况： SCI

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) nucle-ases 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 RNA -guided platform for fundamental life science research and subsequent applications in diverse scenar-ios, 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 scor-ing algorithms and machine learning models have facilitated sgRNA design and off-target predic-tion. 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 limita-tions of available computational tools that would help researchers of this field for further optimiza-tion. Lastly, we suggest a simple but effective workflow for choosing and applying web-based resources and tools for CRISPR/Cas genome editing.

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