Maize hybrids derived from GM positive and negative segregant inbreds are compositionally equivalent: any observed differences are associated with conventional backcrossing practices

Sex selection in layer chickens

The ability to detect and remove male chicks pre-hatch would be a big step forward to the egg-laying and related industries. The current practice of culling male chicks post-hatch creates a major ethical dilemma for many countries. Hatching out and growing male layer chicks is not a sustainable option for farmers. A genetic based in ovo sex selection application would effectively negate the need to cull or grow out male chickens and would contribute to a more sustainable industry with a view to future food security. Recent advancements in avian gene technology allow specific marking of the sex-determining chromosome in chickens so that the males can be identified before hatching and removed before incubation. This provides a simple solution to meet a pressing need for the industry and a leading opportunity for the adoption of biotechnology in animal agriculture.

Stacking transgenic event DAS-Ø15Ø7-1 alters maize composition less than traditional breeding

The impact of crossing ('stacking') genetically modified (GM) events on maize-grain biochemical composition was compared with the impact of generating nonGM hybrids. The compositional similarity of seven GM stacks containing event DAS-Ø15Ø7-1, and their matched nonGM near-isogenic hybrids (iso-hybrids) was compared with the compositional similarity of concurrently grown nonGM hybrids and these same iso-hybrids. Scatter plots were used to visualize comparisons among hybrids and a coefficient of identity (per cent of variation explained by line of identity) was calculated to quantify the relationships within analyte profiles. The composition of GM breeding stacks was more similar to the composition of iso-hybrids than was the composition of nonGM hybrids. NonGM breeding more strongly influenced crop composition than did transgenesis or stacking of GM events. These findings call into question the value of uniquely requiring composition studies for GM crops, especially for breeding stacks composed of GM events previously found to be compositionally normal.

Single-Event Transgene Product Levels Predict Levels in Genetically Modified Breeding Stacks

The concentration of transgene products (proteins and double-stranded RNA) in genetically modified (GM) crop tissues is measured to support food, feed, and environmental risk assessments. Measurement of transgene product concentrations in breeding stacks of previously assessed and approved GM events is required by many regulatory authorities to evaluate unexpected transgene interactions that might affect expression. Research was conducted to determine how well concentrations of transgene products in single GM events predict levels in breeding stacks composed of these events. The concentrations of transgene products were compared between GM maize, soybean, and cotton breeding stacks (MON-87427 × MON-89034 × DAS-Ø15Ø7-1 × MON-87411 × DAS-59122-7 × DAS-40278-9 corn, DAS-81419-2 × DAS-44406-6 soybean, and DAS-21023-5 × DAS-24236-5 × SYN-IR102-7 × MON-88913-8 × DAS-81910-7 cotton) and their component single events (MON-87427, MON-89034, DAS-Ø15Ø7-1, MON-87411, DAS-59122-7, and DAS-40278-9 corn, DAS-81419-2, and DAS-44406-6 soybean, and DAS-21023-5, DAS-24236-5, SYN-IR102-7, MON-88913-8, and DAS-81910-7 cotton). Comparisons were made within a crop and transgene product across plant tissue types and were also made across transgene products in each breeding stack for grain/seed. Scatter plots were generated comparing expression in the stacks to their component events, and the percent of variability accounted for by the line of identity (y = x) was calculated (coefficient of identity, I2). Results support transgene concentrations in single events predicting similar concentrations in breeding stacks containing the single events. Therefore, food, feed, and environmental risk assessments based on concentrations of transgene products in single GM events are generally applicable to breeding stacks composed of these events.

Evaluation of metabolomics profiles of grain from maize hybrids derived from near-isogenic GM positive and negative segregant inbreds demonstrates that observed differences cannot be attributed unequivocally to the GM trait

INTRODUCTION

Past studies on plant metabolomes have highlighted the influence of growing environments and varietal differences in variation of levels of metabolites yet there remains continued interest in evaluating the effect of genetic modification (GM).

OBJECTIVES

Here we test the hypothesis that metabolomics differences in grain from maize hybrids derived from a series of GM (NK603, herbicide tolerance) inbreds and corresponding negative segregants can arise from residual genetic variation associated with backcrossing and that the effect of insertion of the GM trait is negligible.

METHODS

Four NK603-positive and negative segregant inbred males were crossed with two different females (testers). The resultant hybrids, as well as conventional comparator hybrids, were then grown at three replicated field sites in Illinois, Minnesota, and Nebraska during the 2013 season. Metabolomics data acquisition using gas chromatography-time of flight-mass spectrometry (GC-TOF-MS) allowed the measurement of 367 unique metabolite features in harvested grain, of which 153 were identified with small molecule standards. Multivariate analyses of these data included multi-block principal component analysis and ANOVA-simultaneous component analysis. Univariate analyses of all 153 identified metabolites was conducted based on significance testing (α = 0.05), effect size evaluation (assessing magnitudes of differences), and variance component analysis.

RESULTS

Results demonstrated that the largest effects on metabolomic variation were associated with different growing locations and the female tester. They further demonstrated that differences observed between GM and non-GM comparators, even in stringent tests utilizing near-isogenic positive and negative segregants, can simply reflect minor genomic differences associated with conventional back-crossing practices.

CONCLUSION

The effect of GM on metabolomics variation was determined to be negligible and supports that there is no scientific rationale for prioritizing GM as a source of variation.