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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.

Harrigan GG, Venkatesh TV, Leibman M, Blankenship J, Perez T, Halls S, Chassy AW, Fiehn O, Xu Y, Goodacre R - Metabolomics (2016)

Bottom Line: 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 demonstrated that the largest effects on metabolomic variation were associated with different growing locations and the female tester.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.

View Article: PubMed Central - PubMed

Affiliation: Compositional Biology Center, Monsanto Company, St. Louis, MO USA.

ABSTRACT

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.

No MeSH data available.


Related in: MedlinePlus

In plant breeding, selected individuals are crossed to introduce or combine desired trait characteristics into new offspring; this necessitates numerous generations of backcrossing to establish the desired trait characteristics fully. Each successive backcross increases the genetic similarity of the new offspring to the recurrent parent, e.g. 75 % similar at BC1 through to 99.2 % by BC6. These numbers are based on how much of the recurrent parent genome can be theoretically regained at each step; however slight variations can occur. Marker-assisted methodologies that utilize DNA markers to enable selection of plant individuals that contain the greatest number of favorable alleles can reduce the number of generations required to get close to 99 % similarity as adopted in the generation of the inbred variants of this study (Fig. S2)
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Fig1: In plant breeding, selected individuals are crossed to introduce or combine desired trait characteristics into new offspring; this necessitates numerous generations of backcrossing to establish the desired trait characteristics fully. Each successive backcross increases the genetic similarity of the new offspring to the recurrent parent, e.g. 75 % similar at BC1 through to 99.2 % by BC6. These numbers are based on how much of the recurrent parent genome can be theoretically regained at each step; however slight variations can occur. Marker-assisted methodologies that utilize DNA markers to enable selection of plant individuals that contain the greatest number of favorable alleles can reduce the number of generations required to get close to 99 % similarity as adopted in the generation of the inbred variants of this study (Fig. S2)

Mentions: Positive and negative inbred variants of NK603 were produced by standard marker-assisted backcrossing (MABC) methods (Eathington et al. 2007) and as described in Venkatesh et al. (2015b) (see Fig. 1 for an overview of backcrossing and Fig. S1 for a schematic of the procedure followed in this study). The variants were fingerprinted using the Illumina (San Diego, CA, USA) Infinium™ platform. The Infinium™ platform used for genotyping consisted of 35, 000 SNPs markers. The genotyping analysis is described in detail in Venkatesh et al. (2015a). Table S1 shows the genetic similarity of the inbred lines used in this study to the recurrent parent.Fig. 1


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.

Harrigan GG, Venkatesh TV, Leibman M, Blankenship J, Perez T, Halls S, Chassy AW, Fiehn O, Xu Y, Goodacre R - Metabolomics (2016)

In plant breeding, selected individuals are crossed to introduce or combine desired trait characteristics into new offspring; this necessitates numerous generations of backcrossing to establish the desired trait characteristics fully. Each successive backcross increases the genetic similarity of the new offspring to the recurrent parent, e.g. 75 % similar at BC1 through to 99.2 % by BC6. These numbers are based on how much of the recurrent parent genome can be theoretically regained at each step; however slight variations can occur. Marker-assisted methodologies that utilize DNA markers to enable selection of plant individuals that contain the greatest number of favorable alleles can reduce the number of generations required to get close to 99 % similarity as adopted in the generation of the inbred variants of this study (Fig. S2)
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4940444&req=5

Fig1: In plant breeding, selected individuals are crossed to introduce or combine desired trait characteristics into new offspring; this necessitates numerous generations of backcrossing to establish the desired trait characteristics fully. Each successive backcross increases the genetic similarity of the new offspring to the recurrent parent, e.g. 75 % similar at BC1 through to 99.2 % by BC6. These numbers are based on how much of the recurrent parent genome can be theoretically regained at each step; however slight variations can occur. Marker-assisted methodologies that utilize DNA markers to enable selection of plant individuals that contain the greatest number of favorable alleles can reduce the number of generations required to get close to 99 % similarity as adopted in the generation of the inbred variants of this study (Fig. S2)
Mentions: Positive and negative inbred variants of NK603 were produced by standard marker-assisted backcrossing (MABC) methods (Eathington et al. 2007) and as described in Venkatesh et al. (2015b) (see Fig. 1 for an overview of backcrossing and Fig. S1 for a schematic of the procedure followed in this study). The variants were fingerprinted using the Illumina (San Diego, CA, USA) Infinium™ platform. The Infinium™ platform used for genotyping consisted of 35, 000 SNPs markers. The genotyping analysis is described in detail in Venkatesh et al. (2015a). Table S1 shows the genetic similarity of the inbred lines used in this study to the recurrent parent.Fig. 1

Bottom Line: 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 demonstrated that the largest effects on metabolomic variation were associated with different growing locations and the female tester.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.

View Article: PubMed Central - PubMed

Affiliation: Compositional Biology Center, Monsanto Company, St. Louis, MO USA.

ABSTRACT

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.

No MeSH data available.


Related in: MedlinePlus