Literature DB >> 30810790

Performance assessment of digital PCR for the quantification of GM-maize and GM-soya events.

Geoffrey Cottenet1, Carine Blancpain2, Poh Fong Chuah3.   

Abstract

Accurate quantitative methods are needed to determine the amount of transgenic material in ingredients and comply with labelling GMO thresholds. Quantitative real-time PCR methods are usually applied for GMO quantification, but since a few years, digital PCR (dPCR) has been described as a potential alternative by quantifying DNA molecules directly without any standard curves. In this study, the performance of dPCR to quantify 9 GM-soya events and 15 GM-maize events was assessed. Following GMO validation guidelines, the trueness and precision were determined on high, medium and low levels of transgenic content. Results showed biases below ± 25% and satisfactory precision data. Limits of quantification were determined for each GM-event and were between 12 and 31 target copies. The reliability of GMO quantification by dPCR was further confirmed by analysing several proficiency test samples. Overall, dPCR showed accurate and precise GMO quantification on all the tested GM-events, from high to low transgenic amount. With its ease-of-use, dPCR was found to be an appealing alternative technology for routine GMO testing laboratories. Graphical abstract.

Entities:  

Keywords:  Digital PCR; GMO; Quantification; Transgenic

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Substances:

Year:  2019        PMID: 30810790     DOI: 10.1007/s00216-019-01692-7

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  4 in total

1.  Development and assessment of a duplex droplet digital PCR method for quantification of GM rice Kemingdao.

Authors:  Jun Li; Shanshan Zhai; Hongfei Gao; Fang Xiao; Yunjing Li; Gang Wu; Yuhua Wu
Journal:  Anal Bioanal Chem       Date:  2021-05-22       Impact factor: 4.142

2.  A quantitative detection of mung bean in chestnut paste using duplex digital PCR.

Authors:  Yingjie Liang; Dongwei Gao; Jie Dong; Lijun Guan; Zhiyong Li; Jin Liu
Journal:  Curr Res Food Sci       Date:  2021-12-18

3.  Establishment and Validation of Reference Genes of Brassica napus L. for Digital PCR Detection of Genetically Modified Canola.

Authors:  Likun Long; Zhenjuan Xing; Yuxuan He; Wei Yan; Congcong Li; Wei Xia; Liming Dong; Ning Zhao; Yue Ma; Yanbo Xie; Na Liu; Feiwu Li
Journal:  Foods       Date:  2022-08-22

4.  An Editing-Site-Specific PCR Method for Detection and Quantification of CAO1-Edited Rice.

Authors:  Hongwen Zhang; Jun Li; Shengbo Zhao; Xiaohong Yan; Nengwu Si; Hongfei Gao; Yunjing Li; Shanshan Zhai; Fang Xiao; Gang Wu; Yuhua Wu
Journal:  Foods       Date:  2021-05-27
  4 in total

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