Statistical framework for detection of genetically modified organisms based on Next Generation Sequencing

Abstract

Because the number and diversity of genetically modified (GM) crops has significantly increased, their analysis based on real-time PCR (qPCR) methods is becoming increasingly complex and laborious. While several pioneers already investigated Next Generation Sequencing (NGS) as an alternative to qPCR, its practical use has not been assessed for routine analysis. In this study a statistical framework was developed to predict the number of NGS reads needed to detect transgene sequences, to prove their integration into the host genome and to identify the specific transgene event in a sample with known composition. This framework was validated by applying it to experimental data from food matrices composed of pure GM rice, processed GM rice (noodles) or a 10% GM/non-GM rice mixture, revealing some influential factors. Finally, feasibility of NGS for routine analysis of GM crops was investigated by applying the framework to samples commonly encountered in routine analysis of GM crops.

Identification of Genomic Insertion and Flanking Sequence of G2-EPSPS and GAT Transgenes in Soybean Using Whole Genome Sequencing Method

“…In particular, since the downstream junction of GE-J16 on Chromosome 19 has not been identified, increasing the sequence coverage by deep sequencing is recommended. Nevertheless, the implementation of NGS in GMO routine analysis may be less affordable for some laboratories with modest budgets due to relatively high cost, the requirement of adequate computer infrastructures and qualified analysts in bioinformatics for dealing with enormous amount of sequencing data (Buermans and Dunnen, 2014; Liang et al, 2014; Willems et al, 2016). …”

Safety Assessment of Genetically Modified Feed: Is There Any Difference From Food?

“…In recent years, significant effort has been performed to replace the time-consuming and expensive qPCR screening procedure (Holst-Jensen et al, 2016;Salisu et al, 2017). As a result, other technologies are been evaluated including ddPCR (Dalmira et al, 2016;Dobnik et al, 2015;Köppel et al, 2015;Demeke et al, 2016;Dobnik et al, 2016;Gerdes et al, 2016;Głowacka et al, 2016;Iwobi et al, 2016;Grelewska-Nowotko et al, 2018;Niu et al, 2018;Corbisier and Emons, 2019;Giraldo et al, 2019), SGS (Willems et al, 2016;Fraiture et al, 2017;Arulandhu et al, 2018), DNA enrichment approaches (Arulandhu et al, 2016) and combined strategies of DNA walking and SGS (Fraiture et al, 2017).…”

Introductory Chapter: New Age Molecular Techniques in Plant Science

“…NGS technology is more sensitive than qPCR GMO detection to find out the existence of unknown GMOs. Integration of NGS to other new age molecular methods such as DNA walking opens a new window in GMO screening [30,[39][40][41][42].…”