| 计算机辅助CRISPR向导RNA设计 |
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| 引用本文： | 王远立,啜国晖,闫继芳,石雷,刘琦.计算机辅助CRISPR向导RNA设计[J].生物工程学报,2017,33(10):1744-1756. |
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| 作者姓名： | 王远立 啜国晖 闫继芳 石雷 刘琦 |
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| 作者单位： | 2 合肥工业大学 计算机与信息学院，安徽 合肥 230009,1 同济附属第十人民医院 同济大学生命科学与技术学院生物信息学系，上海 200092,1 同济附属第十人民医院 同济大学生命科学与技术学院生物信息学系，上海 200092,2 合肥工业大学 计算机与信息学院，安徽 合肥 230009,1 同济附属第十人民医院 同济大学生命科学与技术学院生物信息学系，上海 200092 |
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| 摘 要： | 基于CRISPR/Cas9系统的基因编辑已被成功应用于多种细胞类型中。计算机辅助的向导RNA(Guide RNA)设计是使用CRISPR系统成功进行基因编辑的关键步骤之一。目前的计算工作主要致力于利用计算模型来提高sgRNA的打靶效率并降低其脱靶。文中对于目前存在的sgRNA设计工具进行综述,并且说明可以通过建立高效的计算模型,对当前的异质基因编辑数据进行整合挖掘,以获得无偏差的sgRNA设计规则,并预测影响sgRNA设计的关键特征。笔者认为,对于sgRNA打靶和脱靶效果的系统总结和评价,将有助于使用CRISPR系统进行更加精准的基因编辑和基因治疗。
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| 关 键 词： | CRISPR，基因编辑，计算机辅助向导RNA设计，脱靶 |
| 收稿时间： | 2017/5/5 0:00:00 |
In silico CRISPR-based sgRNA design |
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| Yuanli Wang,Guohui Chuai,Jifang Yan,Lei Shi and Qi Liu.In silico CRISPR-based sgRNA design[J].Chinese Journal of Biotechnology,2017,33(10):1744-1756. |
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| Authors: | Yuanli Wang Guohui Chuai Jifang Yan Lei Shi and Qi Liu |
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| Institution: | 2 School of Computer and Information, Hefei University of Technology, Hefei 230009, Anhui, China,1 Shanghai Tenth People''s Hospital, Department of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China,1 Shanghai Tenth People''s Hospital, Department of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China,2 School of Computer and Information, Hefei University of Technology, Hefei 230009, Anhui, China and 1 Shanghai Tenth People''s Hospital, Department of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China |
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| Abstract: | CRISPR-based genome editing has been widely implemented in various cell types. In-silico single guide RNA (sgRNA) design is a key step for successful gene editing using CRISPR system. Continuing efforts are made to refine in-silico sgRNA design with high on-target efficacy and reduced off-target effects. In this paper, we summarize the present sgRNA design tools, and show that efficient in-silico models can be built that integrate current heterogeneous genome-editing data to derive unbiased sgRNA design rules and identify key features for improving sgRNA design. Our review shows that systematic comparisons and evaluation of on-target and off-target effects of sgRNA will allow more precise genome editing and gene therapies using the CRISPR system. |
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| Keywords: | CRISPR genome editing in-silico sgRNA design off-target |
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