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| Quantitative Detection of Genetically Modified Maize (Zea mays) Bt11 Strain Based on Duplex Droplet Digital PCR |
| LIANG Mei-Dan, SONG An-Hua, ZHANG Ming-Ming, LEI Yan, HUANG Zhi-Shen, XIAO Jian* |
| Guangzhou Institute for Food Inspection, Guangzhou 510410, China |
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Abstract Maize (Zea mays) Bt11 is a genetically modified (GM) maize strain that has the feature of insect-resistant and herbicide-tolerant. At present, there was no accurate quantitative detection methods for Bt11. Droplet digital PCR (ddPCR) is the third generation of PCR technology emerged in recent years, and has great application prospect in quantitative field of genetically modified products. In order to solve the implementation problems of current genetically modified food standards and improve the inspection and supervision of genetically modified foods in China, the application of ddPCR in the screening detection of genetically modified organisms was established. A quantitative detection method for exogenous and endogenous gene of Bt11 was established based on duplex ddPCR. The maize endogenous gene Zein and the specific gene Cry1A(b) of Bt11 were selected as quantitative target sequences. The method of duplex ddPCR for quantitative detection of GM maize Bt11 was evaluated by stability, specificity, quantitative linear range, quantitative detection low limit and accuracy analysis. The results showed that both Bt11 event-specific sequence and endogenous gene could be amplified specifically with good stability. It had an excellent linearity when the DNA concentration is in the range of 0.05~10 ng/μL, and the correlation coefficient R2 was 0.999. The limit of quantitation (LOQ) of endogenous and exogenous genes were 11.14 and 3.96 copies, respectively. The results of quantitative accuracy test showed that the relative standard deviation (RSD) was between 5.68% and 10.31%, meeting the requirement of less than 25%. In conclusion, the quantitative detection method for exogenous and endogenous genes in genetically modified maize Bt11 was established in this study and had strong specificity, good stability, high accuracy and wide quantitative range, which could be used for quantitative detection of the components of GM maize in food.
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Received: 06 August 2019
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Corresponding Authors:
* xjhq521@163.com
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