Literature DB >> 16076097

Identification and quantification of three genetically modified insect resistant cotton lines using conventional and TaqMan real-time polymerase chain reaction methods.

Litao Yang1, Aihu Pan, Kewei Zhang, Jinchao Guo, Changsong Yin, Jianxiu Chen, Cheng Huang, Dabing Zhang.   

Abstract

As the genetically modified organisms (GMOs) labeling policies are issued in many countries, qualitative and quantitative polymerase chain reaction (PCR) techniques are increasingly used for the detection of genetically modified (GM) crops in foods. Qualitative PCR and TaqMan real-time quantitative PCR methods to detect and identify three varieties of insect resistant cotton, i.e., Mon531 cotton (Monsanto Co.) and GK19 and SGK321 cottons (Chinese Academy of Agricultural Sciences), which were approved for commercialization in China, were developed in this paper. Primer pairs specific to inserted DNAs, such as Cowpea trypsin inhibitor (CpTI) gene of SGK321 cotton and the specific junction DNA sequences containing partial Cry1A(c) gene and NOS terminator of Mon531, GK19, and SGK321 cotton varieties were designed to conduct the identified PCR assays. In conventional specific identified PCR assays, the limit of detection (LOD) was 0.05% for Mon531, GK19, or SGK321 in 100 ng of cotton genomic DNA for one reaction. Also, the multiplex PCR method for screening the three GM cottons was also established, which could save time and cost in practical detection. Furthermore, a real-time quantitative PCR assay based on TaqMan chemistry for detection of insect resistant gene, Cry1A(c), was developed. This assay also featured the use of a standard plasmid as a reference molecule, which contained both a specific region of the transgene Cry1A(c) and an endogenous stearoyl-acyl carrier protein desaturase (Sad1) gene of the cotton. In quantitative PCR assay, the quantification range was from 0.01 to 100% in 100 ng of the genome DNA template, and in the detection of 1.0, 3.0, and 5.0% levels of three insect resistant cotton lines, respectively, all of the relative standard deviations (RSDs) were less than 8.2% except for the GM cotton samples with 1.0% Mon531 or GK19, which meant that our real-time PCR assays involving the use of reference molecule were reliable and practical for GM insect resistant cottons quantification. All of these results indicated that our established conventional and TaqMan real-time PCR assays were applicable to detect the three insect resistant cottons qualitatively and quantitatively.

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Year:  2005        PMID: 16076097     DOI: 10.1021/jf050095u

Source DB:  PubMed          Journal:  J Agric Food Chem        ISSN: 0021-8561            Impact factor:   5.279


  5 in total

1.  Sensitivity of a real-time PCR method for the detection of transgenes in a mixture of transgenic and non-transgenic seeds of papaya (Carica papaya L.).

Authors:  Madhugiri Nageswara-Rao; Charles Kwit; Sujata Agarwal; Mariah T Patton; Jordan A Skeen; Joshua S Yuan; Richard M Manshardt; C Neal Stewart
Journal:  BMC Biotechnol       Date:  2013-09-01       Impact factor: 2.563

2.  Endpoint visual detection of three genetically modified rice events by loop-mediated isothermal amplification.

Authors:  Xiaoyun Chen; Xiaofu Wang; Nuo Jin; Yu Zhou; Sainan Huang; Qingmei Miao; Qing Zhu; Junfeng Xu
Journal:  Int J Mol Sci       Date:  2012-11-07       Impact factor: 5.923

3.  A novel universal real-time PCR system using the attached universal duplex probes for quantitative analysis of nucleic acids.

Authors:  Litao Yang; Wanqi Liang; Lingxi Jiang; Wenquan Li; Wei Cao; Zoe A Wilson; Dabing Zhang
Journal:  BMC Mol Biol       Date:  2008-06-04       Impact factor: 2.946

4.  Establishment of quantitative analysis method for genetically modified maize using a reference plasmid and novel primers.

Authors:  Gi-Seong Moon; Weon-Sun Shin
Journal:  Prev Nutr Food Sci       Date:  2012-12

5.  Structure of Exogenous Gene Integration and Event-Specific Detection in the Glyphosate-Tolerant Transgenic Cotton Line BG2-7.

Authors:  Xiaobing Zhang; Qiaoling Tang; Xujing Wang; Zhixing Wang
Journal:  PLoS One       Date:  2016-07-05       Impact factor: 3.240

  5 in total

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