<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Marie-Alice Fraiture</style></author><author><style face="normal" font="default" size="100%">Philippe Herman</style></author><author><style face="normal" font="default" size="100%">De Loose, Marc</style></author><author><style face="normal" font="default" size="100%">Debode, Frédéric</style></author><author><style face="normal" font="default" size="100%">Nancy Roosens</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">How can we better detect unauthorized GMO in the food and feed chain</style></title><secondary-title><style face="normal" font="default" size="100%">Trends in Biotechnology</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">detection</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA walking</style></keyword><keyword><style  face="normal" font="default" size="100%">Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">new workflow</style></keyword><keyword><style  face="normal" font="default" size="100%">next-generation-sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">qPCR</style></keyword><keyword><style  face="normal" font="default" size="100%">unauthorized GMO</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">24/03/2017</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">517</style></number><volume><style face="normal" font="default" size="100%">35</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Current GMO detection systems have limited abilities to detect unauthorized genetically modified organisms (GMOs). Here, we propose a new workflow, based on next-generation sequencing (NGS) technology, to overcome this problem. In providing information about DNA sequences, this high-throughput workflow can distinguish authorized and unauthorized GMOs by strengthening the tools commonly used by enforcement laboratories with the help of NGS technology. In addition, thanks to its massive sequencing capacity, this workflow could be used to monitor GMOs present in the food and feed chain. In view of its potential implementation by enforcement laboratories, we discuss this innovative approach, its current limitations, and its sustainability of use over time.&lt;/p&gt;
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