Abstract
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.
Highlights
Over the last two decades, farmers around the globe have increasingly adopted the use of crops with genetic modifications that introduce novel traits, such as resistance to herbicides or pests
While quantitative PCR (qPCR) methods in the literature produce up to 20% error within the upper register of the range, being optimized to discriminate 1.25-fold differences in trait abundance, we report a maximum of 5% for across the entire dynamic range
Across the entire dynamic range, the absolute error with 3rd degree calibration equation has the mean value 1.87% and standard deviation 1.05% across 19 error values, which corresponds to 0.24% standard error of and a 95% confidence interval of 1.39% to 2.34%
Summary
Over the last two decades, farmers around the globe have increasingly adopted the use of crops with genetic modifications that introduce novel traits, such as resistance to herbicides or pests. To address public concern around food safety, different countries have defined regulations that restrict these technologies and their use in food products, for example, which requires reliable detection and quantitative analytical methods for the implementation of labeling requirements [1]. Such methods are based either on DNA detection or protein detection. DNA detection and quantification most often uses.
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