A statistical approach to quantification of genetically modified organisms (GMO) using frequency distributions

Detection of Soybean GMO Events Using Two Multiplex Droplet Digital PCR Assays

BACKGROUND

Detection methods for GMO events are required because of regulatory compliance requirements. Efficient detection and quantification of GMO events saves time and resources. Multiplex digital PCR (dPCR) allows detection and quantification of more than one GMO event at the same time.

OBJECTIVE

The study used two tetraplex droplet digital PCR (ddPCR) assays for the detection of 19 soybean GMO events.

METHODS

Two multiplex dPCR assays were developed and optimized for the detection of 19 soybean GMO events. The first tetraplex ddPCR assay contained four element-specific targets commonly found in GMO plants (P-35S, T-nos, tE9, and Pat). The second event-specific tetraplex ddPCR assay targeted four soybean GMO events that are not detected with the element-specific tetraplex ddPCR (CV127, DP305423, MON87701, and MON87751).

RESULTS

The element-specific tetraplex ddPCR assay detected all the expected 15 soybean GMO events. The element-specific tetraplex ddPCR assay also detected selected soybean GMO events at the 0.01% level. The event-specific tetraplex ddPCR assay was successfully used to quantify the four soybean GMO events at the 0.1, 1, 2, and 5% levels. The event-specific tetraplex ddPCR assay also detected the four soybean GMO events at the 0.01% level.

CONCLUSIONS

The two tetraplex ddPCR assays can be used for the detection of 19 soybean GMO events.

HIGHLIGHTS

An element-specific tetraplex ddPCR assay was used to detect 15 soybean GMO events, and an event-specific tetraplex ddPCR assay was used to detect and quantify four soybean GMO events that are not detected by the element-specific ddPCR assay.

Fast and accurate quantification of insertion-site specific transgene levels from raw seed samples using solid-state nanopore technology

Many modern crop varieties contain patented biotechnology traits, and an increasing number of these crops have multiple (stacked) traits. Fast and accurate determination of transgene levels is advantageous for a variety of use cases across the food, feed and fuel value chain. With the growing number of new transgenic crops, any technology used to quantify them should have robust assays that are simple to design and optimize, thereby facilitating the addition of new traits to an assay. Here we describe a PCR-based method that is simple to design, starts from whole seeds, and can be run to end-point in less than 5 minutes. Subsequent relative quantification (trait vs. non-trait) using capillary electrophoresis performed in 5% increments across the 0-100% range showed a mean absolute error of 1.9% (s.d. = 1.1%). We also show that the PCR assay can be coupled to non-optical solid-state nanopore sensors to give seed-to-trait quantification results with a mean absolute error of 2.3% (s.d. = 1.6%). In concert, the fast PCR and nanopore sensing stages demonstrated here can be fully integrated to produce seed-to-trait quantification results in less than 10 minutes, with high accuracy across the full dynamic range.

Transgene flow in Mexican maize revisited: Socio-biological analysis across two contrasting farmer communities and seed management systems

The flow of transgenes into landraces and wild relatives is an important biosafety concern. The case of transgene flow into local maize varieties in Mexico (the center of origin of maize) has been intensively debated over the past 15 years, including legal, political, and environmental disputes fanned by the existence of a significant scientific controversy over the methods used for the detection of transgenes. The use of diverse approaches and a lack of harmonized methods specific to the detection and monitoring of transgenes in landraces have generated both positive and negative results regarding contamination of Mexican maize with genetically modified material over the years. In this paper, we revisit the case of transgene contamination in Mexican maize and present a novel research approach based on socio‐biological analysis of contrasting communities and seed management systems. Two communities were used to investigate how different social and biological factors can affect transgene flow and impact transgene spread in Mexico. Our results show the presence of transgenes in one community and thus support the position that transgenes are highly likely to be present in Mexican maize landraces. However, our work also demonstrates that the extent and frequency with which transgenes can be found will significantly depend on the societal characteristics and seed management systems of the local communities. Therefore, we argue that future analysis of transgene presence should include social research on the seed management practices in the sampling area so that more robust and comprehensive understandings and conclusions can be drawn.