No. 26 (2007)
Articles

Qualitative detection of genetically modified organisms in plant samples

Published July 16, 2007
Csilla Uri
Debreceni Egyetem Agrártudományi Centrum, Mezőgazdaságtudományi Kar, Élelmiszertudományi, Minőségbiztosítási és Mikrobiológiai Intézet, Debrecen
József Prokisch
Debreceni Egyetem Agrártudományi Centrum, Mezőgazdaságtudományi Kar, Élelmiszertudományi, Minőségbiztosítási és Mikrobiológiai Intézet, Debrecen
Erzsébet Sándor
Debreceni Egyetem Agrártudományi Centrum, Mezőgazdaságtudományi Kar, Növényvédelmi Tanszék, Debrecen
Zoltán Győri
Debreceni Egyetem Agrártudományi Centrum, Mezőgazdaságtudományi Kar, Élelmiszertudományi, Minőségbiztosítási és Mikrobiológiai Intézet, Debrecen
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APA

Uri, C., Prokisch, J., Sándor, E., & Győri, Z. (2007). Qualitative detection of genetically modified organisms in plant samples. Acta Agraria Debreceniensis, (26), 309-313. https://doi.org/10.34101/actaagrar/26/3091

We analysed the GMO content of corn samples by polymerase chain reaction following the appropriate optimization of the reaction. The analysis included two main steps: extraction of DNA from the sample, and detection of the GMO content by polymerase chain reaction. The polymerase chain reaction is an in vitro method to multiply chromosomatic or cloned DNA (cDNA) sequences through the enzymatic pathway. The reaction is sensitive enough to produce DNA in sufficient amount for the analysis from a single DNA. We identified the PCR products by agarose gel electrophoresis. When optimizing the reaction, the MgCl2 concentration, reaction time and temperature have to be taken into consideration. The temperature of the anellation has to be increased until the highest specificity and yield is reached. If the temperature of the anellation is too high, the primer is linked to non-specific sites as well; in the gel visualization, more lines can be seen at one sample. If the temperature of the anellation is too high, the primer is insufficiently linked or is not linked at all (too few lines in the gel visualization). After optimization, the GMO content in the unknown sample can be determined along with the appropriate positive and negative controls.

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