生物
基因组编辑
计算生物学
基因组
遗传学
突变
基因
作者
Fuquan Li,Xiyu Tan,Shengting Li,Shaotong Chen,Lin Liu,Jingjing Huang,Gufeng Li,Zijun Lu,Jingwen Wu,Dongchang Zeng,Yanqiu Luo,Oliver Xiaoou Dong,Xingliang Ma,Qinlong Zhu,Letian Chen,Yao‐Guang Liu,Chengjie Chen,Xianrong Xie
标识
DOI:10.1016/j.molp.2025.03.002
摘要
Genome editing using CRISPR/Cas or other systems has become a cornerstone of numerous biological and applied research fields. However, detecting the resulting mutations by analysis of sequencing data remains time-consuming and inefficient. In response to this issue, we designed SuperDecode, an integrated software toolkit for analyzing editing outcomes using a range of sequencing strategies. SuperDecode comprises three modules, DSDecodeMS, HiDecode, and LaDecode, each designed to automatically decode mutations from Sanger, high-throughput short-read (next-generation sequencing), and long-read sequencing data (third-generation sequencing), respectively, from targeted PCR amplicons. By leveraging specific strategies for constructing sequencing libraries of pooled multiple amplicons, HiDecode and LaDecode facilitate large-scale identification of mutations induced by single or multiplex target-site editing in a cost-effective manner. We demonstrate the efficacy of SuperDecode by analyzing mutations produced using different genome editing tools (CRISPR/Cas, base editing, prime editing) in different materials (diploid and tetraploid rice, protoplasts), underscoring its versatility in decoding genome editing outcomes across different applications. Furthermore, this toolkit can be used to analyze other genetic variations, as exemplified by its ability to estimate the C-to-U editing rate of the cellular RNA of a mitochondrial gene. SuperDecode offers both a standalone software package and a web-based version, ensuring its easy access and broad compatibility across diverse computer systems. Thus, SuperDecode provides a comprehensive platform for analyzing a wide array of mutations, advancing the utility of genome editing for scientific research and genetic engineering.
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