Jiangsu Key Laboratory of Crop Genetics and Physiology, Co-Innovation Centre for Modern Production Technology of Grain Crops, Key Laboratory of Plant Functional Genomics of the Ministry of Education, Yangzhou University, Yangzhou 225009, China.
Joint International Research Laboratory of Agriculture and Agri-Product Safety, the Ministry of Education of China, Yangzhou University, Yangzhou 225009, China.
Int J Biol Sci. 2018 May 22;14(8):858-862. doi: 10.7150/ijbs.24581. eCollection 2018.
Custom-designed nucleases, including CRISPR-Cas9 and CRISPR-Cpf1, are widely used to realize the precise genome editing. The high-coverage, low-cost and quantifiability make high-throughput sequencing (NGS) to be an effective method to assess the efficiency of custom-designed nucleases. However, contrast to standardized transcriptome protocol, the NGS data lacks a user-friendly pipeline connecting different tools that can automatically calculate mutation, evaluate editing efficiency and realize in a more comprehensive dataset that can be visualized. Here, we have developed an automatic stand-alone toolkit based on python script, namely CRISPRMatch, to process the high-throughput genome-editing data of CRISPR nuclease transformed protoplasts by integrating analysis steps like mapping reads and normalizing reads count, calculating mutation frequency (deletion and insertion), evaluating efficiency and accuracy of genome-editing, and visualizing the results (tables and figures). Both of CRISPR-Cas9 and CRISPR-Cpf1 nucleases are supported by CRISPRMatch toolkit and the integrated code has been released on GitHub (https://github.com/zhangtaolab/CRISPRMatch).
定制设计的核酸酶，包括 CRISPR-Cas9 和 CRISPR-Cpf1，被广泛用于实现精确的基因组编辑。高通量测序 (NGS) 具有高覆盖率、低成本和可量化性，使其成为评估定制设计核酸酶效率的有效方法。然而，与标准化转录组协议相比，NGS 数据缺乏连接不同工具的用户友好型管道，这些工具可以自动计算突变、评估编辑效率，并在更全面的可可视化数据集上实现。在这里，我们基于 python 脚本开发了一个自动独立的工具包，即 CRISPRMatch，用于通过整合分析步骤（如读取映射和读取计数标准化、计算突变频率（缺失和插入）、评估基因组编辑的效率和准确性以及可视化结果（表格和图形））来处理 CRISPR 核酸酶转化原生质体的高通量基因组编辑数据。CRISPRMatch 工具包支持 CRISPR-Cas9 和 CRISPR-Cpf1 核酸酶，集成代码已在 GitHub 上发布（https://github.com/zhangtaolab/CRISPRMatch）。
