可追溯性
计算机科学
计算生物学
灵敏度(控制系统)
检出限
生物系统
极限(数学)
生物
多路复用
对偶(语法数字)
阿尔戈瑙特
数据挖掘
模式识别(心理学)
样品(材料)
人工智能
质量(理念)
DNA
假阳性悖论
相对标准差
实时计算
作者
Ruihong Pan,Yao Yang,Zhiwen Lu,Huimin Wu,Zini Zhang,Xiaoqing Yao,Shanshan Zhai,Chao Zhai,Gang Wu,Hongfei Gao
标识
DOI:10.1021/acs.jafc.5c13631
摘要
A dual-channel detection system using Pyrococcus furiosus Argonaute (PfAgo) was developed for the quantification of single-nucleotide variants (SNVs) in genome-edited rice. The proposed approach advanced PfAgo-based detection by introducing universal guide DNA (gDNA) that simplified the system through simultaneous recognition of both wild-type and SNV targets. It achieved precise dual quantification of single-base differences without cross-interference via a rationally designed mismatch in the molecular beacons. Under the optimal conditions, the developed method exhibited exceptional sensitivity with a detection limit of 0.1% for SNV mutant, while maintaining single-nucleotide discrimination capability across various genome-edited rice variants. In blinded sample tests at 5%-10%, the system exhibited robust performance with relative standard deviation below 6% and bias within ± 8%, confirming its quantitative reliability. The proposed approach integrates high sensitivity, excellent specificity, and precise quantification, thereby providing a powerful analytical platform for traceability and quality control of genome-edited products.
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