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Stacked GE trait products produced by conventional breeding reflect the compositional profiles of their component single trait products Erin Bell, Shuichi Nakai, and Luis Burzio J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b02317 • Publication Date (Web): 28 Jun 2018 Downloaded from http://pubs.acs.org on July 3, 2018

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Journal of Agricultural and Food Chemistry

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Stacked GE trait products produced by conventional breeding reflect the compositional profiles of their component single trait products

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Erin Bell*1, Shuichi Nakai2, and Luis A. Burzio1

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*To whom correspondence should be addressed. Email: [email protected]

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1

Monsanto Company, 700 Chesterfield Parkway West, Chesterfield, MO 63017, U.S.A.

11

2

Monsanto Japan Limited, 2-5-18 Kyobashi, Chuo-ku, Tokyo 104-0031, Japan.

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ACS Paragon Plus Environment


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Abstract

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An expanding trend for genetically engineered crops is to cultivate varieties in which two or

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more single trait products have been combined using conventional breeding to produce a

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stacked trait product that provides a useful grouping of traits. Here we report results from

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compositional analysis of several GE stacked trait products from maize and soybean. The

19

results demonstrate that these products are each compositionally equivalent to a relevant non-

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GE comparator variety, except for predictable shifts in the fatty acid profile in the case of

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stacked trait products that contain a trait, MON 87705, that confers a high-oleic acid phenotype

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in soybean. In each case, the conclusion on compositional equivalence for the stacked trait

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product reflects the conclusions obtained for the single trait products. These results provide

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strong support for conducting a reassessment of those regulatory guidelines that mandate

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explicit characterization of stacked trait products produced through conventional breeding.

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Key words: composition; stacked trait product; genetically engineered crops; conventional

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breeding

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Introduction

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Humans have been noticing and selecting for useful plant features since the beginning of

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agriculture, from the initial domestication of wild species to the incremental improvements of

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cultivated species. For example, the propagation of a variant with characteristics of reduced

35

seed shattering was important for the domestication of rice, and selection of other useful

36

features over time contributed to rice’s advancement as a primary food source for a large

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portion of the world population (1, 2). This process of selecting for desirable characteristics has

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continued, and, using more sophisticated tools, is still the basis of modern plant breeding. A

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key goal of plant breeding is to develop varieties that combine many useful characteristics, to

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increase the utility and value for farmers and/or consumers. Plant breeding has an established

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history of safety (3), in that thousands of new varieties have been introduced into food and/or

42

feed use without the emergence of safety concerns (4).

43

The introduction of desirable characteristics can also be achieved using the tools of

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biotechnology. Genetically engineered (GE; also referred to as GM) plants are developed

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through plant transformation to achieve the targeted introduction of a desirable characteristic,

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or “trait”, that may not be obtainable through traditional plant breeding processes. When GE

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techniques were first used for the introduction of desired traits into crops, intergovernmental

48

organizations and many governments established regulatory frameworks for pre-market

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assessments of the food/feed safety of new GE plants (5), such that each new GE crop is

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subjected to review by one or more regulatory authorities prior to release for commercial use.

51

For example, since the commercialization of the first GE crop in the U.S. in 1992, there have



52

been 126 GE crop products deregulated for cultivation in the United States (6) following

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regulatory evaluation of prescribed safety assessment approaches (7).

54

The utility of a crop variety can be increased by breeding to combine two or more desired

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characteristics found in parental lines. For example, conventional1 plant breeding practices,

56

including backcrossing, phenotypic selection, and marker-assisted selection, were used to

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introduce the native characteristic of bacterial blight resistance from one rice variety into a

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Basmati rice variety, resulting in a variety that displayed both bacterial blight resistance and

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Basmati quality characteristics (8). GE traits can also be combined by conventional breeding;

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such combined trait products are likewise developed to provide growers and/or consumers

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with more benefits in a single plant, for example traits to address the agronomic challenges of

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weeds and insect pests simultaneously.

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To produce a GE crop that addresses an agricultural challenge or provides a product with

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consumer benefit, developers typically use plant transformation to generate many independent

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lines containing the trait of interest, which are then extensively characterized and screened to

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select one that will be advanced for commercial use (9). The resulting trait-containing product

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(referred to here as a “single trait product” or “GE single”) is designated with a unique identifier

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(for example, MON 89788, a GE soybean that is tolerant to the herbicide glyphosate). A crop

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that contains the traits from two or more GE singles, that have been combined using

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conventional breeding, is referred to here as a “stacked trait product” (or “stack”).

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Designations for stacked trait products are differentiated from GE single trait products, typically

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through a naming convention that combines the names of each component GE single using the 1

“Conventional” breeding refers here to plant breeding techniques excluding GE.


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“×“ nomenclature typical for breeding crosses, for example MON 87705 × MON 89788 (a

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soybean stacked trait product with an improved fatty acid profile and glyphosate tolerance).

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Over the past 10-15 years there has been a notable increase in the number of stacked trait

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products developed and released, including those that contain three or more GE singles (10).

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The evaluation of a GE single trait product follows guidelines that have been established by

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Codex Alimentarius (5) as relevant and sufficient for food safety assessment of GE varieties.

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From a regulatory perspective, stacked trait products often differ in a key way from GE single

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trait products in that they contain traits that are not new to regulatory authorities, having

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already been fully evaluated in the component GE singles. Given that the safety concerns

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raised about GE crops revolve around the safety of the introduced trait and the potential for

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adverse unintended effects due to trait introduction, this distinction is important. Here we

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report the conclusions from compositional assessment of several GE stacked trait products,

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conducted by comparison of component values between the GE varieties and closely related

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non-GE comparators. The results indicate that a conclusion of compositional equivalence for a

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GE stacked trait product relative to its comparator aligns with compositional equivalence

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conclusions for the relevant GE single trait products. These results provide empirical support

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for a regulatory model in which explicit risk assessment of a GE stacked trait product is

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mandated only in limited circumstances (4).

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Materials and Methods

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Maize or soybean plants were cultivated in replicated field trials in the region and year(s) as

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indicated below and/or as cited. In each case, a closely related non-GE variety, indicated as



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“control” in Tables 2 and 3, was grown concurrently with the indicated GE (“test”) varieties,

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with each as entries in a randomized complete block design in the same field trial. In cases

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where the GE variety was treated as indicated with one or more trait-relevant herbicides, the

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treatment was applied to reflect conditions that could be typical of commercial cultivation for

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that crop. Information regarding the trait characteristics corresponding to the GE single trait

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products is provided in Table 1.

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Specific field trials:

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•

The maize products MON 87427 and MON 87427 x MON 89034 x MON 88017 were grown

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in the United States in 2008, at three locations (one each in Arkansas, Illinois, and Iowa),

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with three replications per location. Test plants were treated with glyphosate herbicide.

104

•

The maize product MON 89034 × TC1507 × MON 88017 × DAS-59122-7 was grown in the

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United States in2008, at four locations (one each in Illinois, Indiana, Iowa, and Nebraska),

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with three replications per location.

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glufosinate herbicides.

108

•

Test plants were treated with glyphosate and

The maize product MON 87427 × MON 89034 × TC1507 × MON 88017 × DAS-59122-7 was

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grown in the United States in 2010, at eight locations (one each in Arkansas, Indiana,

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Kansas and Nebraska, and two each in Illinois and Iowa), with four replications per location.

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Test plants were treated with glyphosate and glufosinate herbicides.

112

•

The soybean product MON 87705 was grown in Chile during the 2007/2008 season, at five

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locations (one each in the provinces of Cachapoal, Chacabuco, Colchagua, Maipo, and

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Melipilla), with three replications per location.


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•

The soybean product MON 87705 x MON 89788 was grown in the United States in 2009 at

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eight locations (one each in Iowa, Indiana, Kansas, Missouri, and Nebraska, and three in

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Illinois), with four replications per location. Test plants were treated with glyphosate

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herbicide.

119

•

The soybean product MON 87705 x MON 87708 x MON 89788 was grown in Argentina

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during the 2013/2014 season, at five locations (four in Buenos Aires province and one in

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Santa Fe province), with four replications per location. Test plants were treated with

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glyphosate and dicamba herbicides.

123 124

Key nutrients and anti-nutrients were analyzed from harvested maize grain and harvested

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soybean seed. Validated analytical methods, consistent with those described in (11), (12), or

126

(13), were used to assess analyte levels. Resulting data were combined by entry across all

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replicates and locations within a study, and combined site mean values for each component

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were calculated. For each component within each study, the combined site mean values for

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the test substance and the control substance were statistically compared using a mixed model

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analysis of variance, as described in Drury et al. (11). Statistical significance was defined at the

131

level of p < 0.05.

132 133

Results and Discussion

134

Assessment of stacked trait products from maize and soybean confirm the compositional

135

equivalence of these products to conventional crop varieties



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Whereas conventionally-bred crops are presumed to be safe, GE single trait products undergo

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an explicit comparative compositional assessment of important nutrients and relevant toxicants

138

to evaluate the substantial equivalence of the GE crop product to non-GE varieties (14). Since

139

its inception, the core objective of compositional assessment of a GE crop product has been to

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evaluate whether the composition of the GE product is as safe as that of conventional varieties

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of the same crop (15). It is known that both genetic factors (such as crop variety) and

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environmental factors (growing location, weather conditions, application of fertilizer, etc.) can

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impact the composition of a crop, and that the level of a particular component can vary

144

substantially without posing a nutritional or safety concern (16, 17). This natural variability

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provides important context, in that a value for a component in a GE product that is consistent

146

with previously-observed values for non-GE varieties provides assurance that the GE crop is as

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safe as conventional varieties with respect to the level of that given component. It is important

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to note that values outside of documented variation would not automatically indicate lack of

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safety.

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Monsanto Company has developed several stacked trait products that contain three or more

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single traits. Compositional data for two recently developed stacked trait products, MON

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87427 x MON 89034 × TC1507 × MON 88017 × DAS-59122-7 from maize, and MON 87705 x

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MON 89788 x MON 89788 from soybean, are reported here. A summary of the single trait

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products included in the maize or soybean stacked trait products is provided in Table 1.

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Table 2 presents composition data for the stacked trait product MON 87427 x MON 89034 ×

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TC1507 × MON 88017 × DAS-59122-7 from maize. For comparison purposes, data from related

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“lower order” stacked trait products, that contain a subset of the traits combined in the highest


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order stacked trait product, as well from selected single trait products, are also provided. For

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each GE crop, values were statistically compared to those from a closely-related, concurrently-

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grown non-GE, or “conventional”, variety; data for these comparators are also shown. As

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shown in Table 2, individual values for any given component could vary from analysis to analysis.

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Figure 1A represents one example of this, showing the range of maize grain protein values for

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each GE product and its conventional comparator.

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differences between the GE product and a relevant conventional comparator were observed,

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they represented a small difference in the level of the particular component. For example, the

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statistically significant difference in mean protein level in MON 87427 × MON 89034 × TC1507 ×

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MON 88017 × DAS-59122-7 represented a less than 10 % difference relative to the conventional

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comparator. In addition, the values for both the trait-containing variety and the conventional

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comparator were within the range of characterized natural variability for the crop, as defined

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by the International Life Sciences Institute Crop Composition Database (ILSI CCDB) ranges (Table

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2; Figure 1A). The ILSI CCDB, which includes data from the evaluation of conventional crop

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samples using validated analytical methods, provides a robust compilation of high quality non-

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GE composition data for several crops (18); these data provide valuable context for any

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statistical differences. Thus, despite variation in component levels, the conclusion for each of

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these products was that the neither the introduced trait(s), nor the process of developing the

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GE product, was a meaningful contributor to compositional variability, and that the product

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was compositionally equivalent to commercially available conventional maize varieties. [Table

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S1 presents additional component data for several of these maize products.]

While some statistically significant



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Table 3 presents composition data for the soybean stacked trait product MON 87705 x MON

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87708 x MON 89788, as well as data from some related GE single and stacked trait products. Of

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note is that one of the GE single trait products shown, MON 87705, was developed to confer a

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modified fatty acid profile, including an increase in oleic acid (19). These summarized data

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indicate that the modified fatty acid profile trait from MON 87705 functioned as intended when

184

combined with the other GE singles in the stacked trait products, and that otherwise the traits

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assessed were not meaningful contributors to compositional variability. Figure 1B, which

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shows ranges of protein values in these soybean varieties, provides a graphic representation of

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the compositional equivalence of protein levels for each GE variety with its conventional

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comparator. [Table S2 reports additional component data for some of these soybean products.]

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In Table 2, MON 87427 × MON 89034 × TC1507 × MON 88017 × DAS-59122-7 (generically, A × B

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× C × D × E) represents a higher order stacked trait product, and MON 87427 × MON 89034 ×

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MON 88017 (generically, A × B × D) represents a lower order stacked trait product. The

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commercialization of both higher order and lower order stacked trait products provides

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flexibility, allowing farmers to choose the combination of traits that are most useful for their

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cultivation conditions. As explicitly shown here for the high oleic acid phenotype for MON

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87705, the intended compositional differences in fatty acid levels manifested themselves as

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expected in stacks of varying orders, with both of the GE stacked trait products that include

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MON 87705 having an altered fatty acid profile relative to their respective control (see Table 3).

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In a hypothetical situation where a combination of traits from two previously evaluated and

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approved GE singles (e.g. traits F and G) resulted in a unique characteristic for the GE breeding

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stack, it is reasonable to expect that any stacked trait product that included that combination


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would also manifest its unique characteristic, whether a higher order, such as A x B x C x F x G,

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or a lower order stack, such as A x F x G, or F x G itself. Thus, the hypothetical unique

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characteristic conferred by the F x G combination could be adequately assessed in the context

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of safety in any one of the stacked trait products that contained the F × G combination. This

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suggests that, in cases where compositional assessment of stacked trait products is mandated,

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evaluation of a higher order stacked trait product would suffice to provide information

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regarding lower order stacked trait products as well.

208 209

Historic data also demonstrate a lack of compositional impact due to trait stacking

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Kok et al (20) summarized the outcomes for 22 stacked trait products that had been assessed

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(including compositional assessment) by the European Food Safety Authority. They concluded

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that there was no evidence that stacking GE traits through conventional breeding resulted in

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changes that would raise safety concerns. In addition, several publications have reported the

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consistency of compositional characteristics of a given stacked trait product with those of a

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conventional comparator (Table S3). Those reports, considered along with the regulatory

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approvals of more than 60 stacked trait products (10), provide empirical evidence that, as

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expected, notable unintended effects arising from the combination of traits in a stacked trait

218

product have not been observed.

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Risk assessment approaches for stacked trait products vary globally

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There are regulatory agencies that approach a stacked trait product as a unique GE crop that

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requires de novo assessment, despite their previously established safety conclusions for the



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individual GE singles and the safety of conventional breeding. One motivation for this approach

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could be a concern about possible interaction between traits that might lead to plant

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characteristics that are different from the expected sum of the combined traits. The overall

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potential for trait interactions in stacked trait products was extensively reviewed in a recent

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publication (4). The authors highlighted the fact that because the functional characteristics of

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introduced GE traits are known, it is possible to develop hypotheses on whether a specific

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combination of traits would interact to affect plant metabolism in a novel way, and on whether

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the hypothetical interaction would pose any risk. For example, many commercial stacked trait

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products combine herbicide tolerant (HT) traits. One widely available HT trait is tolerance to

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glyphosate, an herbicide that inhibits the plant’s 5-enolpyruvylshikimate-3-phosphate synthase

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(EPSPS) enzyme, that participates in the biosynthesis of aromatic amino acids. Tolerance to

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glyphosate can be achieved by the introduction of a gene encoding a glyphosate-tolerant EPSPS

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enzyme. Another HT trait is tolerance to the herbicide dicamba. Tolerance to dicamba can be

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achieved by introducing a gene encoding dicamba monooxygenase, an enzyme that catalyzes

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the demethylation of dicamba to a non-herbicidal form. In some stacked trait products,

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glyphosate tolerance has been combined with dicamba tolerance through conventional

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breeding. Given the distinct mechanisms by which these two enzymes confer their respective

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HT trait, and the chemical dissimilarity of their respective substrates, there is no plausible

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hypothesis that they would interact in a stacked trait product to warrant any novel safety

241

concerns by their combination. For this example, the compositional safety of a GE stacked trait

242

product that confers tolerance to glyphosate and dicamba has also been empirically

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demonstrated (21).

Specifically for the GE stacked trait products presented here, the maize


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products contain insect resistance and HT traits; similar to the example described, there is no

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plausible hypothesis for their combined presence to affect the metabolism of the plant and lead

246

to compositional differences. For the soybean products, that contain one or more HT traits and

247

a trait that impacts the fatty acid profile, there is also no plausible hypothesis for trait

248

interaction to affect the metabolism of the plant. As expected, the compositional profiles

249

observed for these GE stacked trait products are consistent with those that would be predicted

250

based on the characteristics of the relevant GE single trait products.

251

et al. concluded that if no plausible hypothesis for an interaction of concern can be developed,

252

further assessment of the stacked trait product is not scientifically justified, based on the

253

previously-determined safety of the constituent GE single trait products and the established

254

safety of conventional breeding (4).

255

Another factor that may motivate assessment of GE breeding stacks is concern regarding a

256

potential for the GE trait combination to affect the stability of one or more of the transgenes

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(22). As part of the characterization process for each GE single trait product, the stability and

258

inheritance pattern of the inserted transgene is explicitly demonstrated over multiple

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generations. Once a gene for a given trait is stably integrated into the genome, it behaves like

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the thousands of other genes in the plant’s genome. While there is a potential for genetic

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change in all plants and in all breeding processes, two recent publications (20, 23) have

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concluded that the process of combining traits in a GE breeding stack does not pose unique risk

263

relative to any other conventional breeding process. Thus, this concern does not justify safety

264

assessment of a stacked trait product.


More generally, Steiner


265

In considering the global landscape of GE regulations, there are currently three general

266

approaches to the food and feed safety assessment for a stacked trait product:

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Approach 1. As a product of a conventional breeding process, the stacked trait product is

268

not explicitly assessed

269

Under this approach, no data are required for a stacked trait product generated by

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conventional breeding of risk-assessed GE single trait products. For some regulatory

271

agencies, the potential for interaction of a new trait with previously approved traits is

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proactively considered at the time when a new GE single trait product is evaluated.

273

Regulatory agencies may require a written notification regarding the stacked trait

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product to be commercialized. Examples of agencies that follow this approach are

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United States Department of Agriculture, United States Food and Drug Administration,

276

Canadian Food Inspection Agency, Health Canada, and Food Standards Australia New

277

Zealand.

278

Approach 2. The requirement for GE breeding stack assessment is determined by the

279

characteristics of the traits being combined

280

Under this approach, stacked trait products that combine certain previously-assessed

281

traits are exempted from safety assessment, while combinations involving other traits

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(or trait categories) require additional characterization. For example, for Japan’s Food

283

Safety Commission and Ministry of Agriculture, Forestry and Fisheries Feed division, no

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data are required if the stack combines traits that do not alter metabolism of the host

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plant (Category 1), such as common herbicide tolerance or insect resistance traits (24).


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For other trait categories (Category 2 or Category 3, that impact plant metabolism or

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produce new substances, respectively), at least some direct characterization is required,

288

with the scope of the assessment dependent on the nature of the traits being combined.

289

It is interesting to note that this differential approach to stacked trait product safety

290

assessment is relatively new for regulatory agencies in Japan. The decision to no longer

291

require characterization data for stacks combining Category 1 traits was based on

292

scientific considerations and evaluation of the agencies’ historical experience from

293

evaluating many stack combinations without any evidence for safety concerns regarding

294

the stacked trait products. (24)

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Approach 3.

An explicit safety evaluation is required for any stacked trait product,

296

regardless of the nature of the traits combined

297

Under this approach, at least a subset of the data types previously generated and

298

evaluated for the GE single trait products, such as molecular characterization, protein

299

expression and compositional data, must be also generated and evaluated for a stacked

300

trait product (the exact nature of the data required for the assessment varies by agency).

301

Examples of some regulatory agencies that follow this approach are European Food

302

Safety Authority, Republic of Korea’s Ministry of Food and Drug Safety, Taiwan Food and

303

Drug Administration, and Mexico’s Federal Commission for the Protection Against

304

Sanitary Risk.

305

For stacked trait products, the formulation and evaluation of a product-specific risk hypothesis,

306

that evaluates the need, or lack thereof, for additional explicit safety assessment of a particular



307

stacked trait product, represents a rational, scientifically supportable, risk assessment approach

308

(3, 4, 25). However, as noted above, there are regulatory agencies that require explicit

309

characterization and safety assessments for every stacked trait product, independent of a risk

310

hypothesis. Overall, considering 1) the availability of safety conclusions for the relevant single

311

trait products, 2) the safe history of conventional breeding, and 3) the expanding body of

312

empirical data confirming the safety of GE trait stacking through conventional breeding, there is

313

a valid scientific justification to eliminate mandatory requirements to submit and evaluate

314

characterization data for each new stacked trait product. If, in practical terms, a step-wise

315

approach toward the elimination of generic data requirements for stacked trait products is

316

more realistic, refining the focus to a single targeted analysis of the stack could be the first step.

317

Such an approach would provide an empirical bridge to the previous assessments completed

318

for the component GE singles. For example, a streamlined assessment of the stack that focused

319

on composition, evaluating the levels of grain proximates and anti-nutrients in the context of

320

known natural variability, could be used to complement the safety conclusions previously

321

reached for the constituent single trait products.

322

In summary, based on the biological processes underlying conventional breeding and GE

323

breeding stacks, supported by the empirical assessment of more than 60 stacked trait products

324

(10) that show outcomes consistent with the expected impact of these processes, risk

325

assessment principles do not support a need for regulatory-focused characterization and

326

assessment of stacked trait products of previously assessed GE singles, except in cases

327

(currently unprecedented) where a plausible hypothesis of a trait interaction that could impact

328

product safety can be formulated.

Stacked trait products that provide useful GE trait


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combinations are a fast-growing segment of the GE portfolio; for that reason, it is important to

330

appropriately align their regulatory review with the principles of risk assessment.

331

requirement for pre-market evaluations that are not justified under these principles

332

contributes to a high barrier to development, may strain the resources of regulatory agencies

333

tasked with evaluating food and feed safety, and may preclude the use of GE by both public

334

and private developers interested in providing innovative new trait combinations to support

335

agricultural developments that help feed the world’s expanding population.

336 337 338

Abbreviations used

339

GE – genetically engineered

340

ILSI-CCDB – International Life Sciences Institute Crop Composition Database

341

HT – herbicide tolerant

342

EPSPS - 5-enolpyruvylshikimate-3-phosphate synthase

343

DMO – dicamba monooxygenase

344 345

Acknowledgements

346

The authors acknowledge Kevin Glenn for his critical review of the manuscript, and Tim

347

Klusmeyer and Mary Taylor for their assistance in preparing data tables.


A


348

Supporting Information

349

Data for additional compositional components for maize are reported in Table S1, and for

350

soybean are reported in Table S2. Citations for compositional equivalence for stacked trait

351

products are provided in Table S3.

352 353

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354

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Food Chemistry 2008, 56, 4623-4630.

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Zhu, E.; Ridley, W. P., Compositions of Seed, Forage, and Processed Fractions from Insect-Protected

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Chemistry 2009, 57, 11360-11369.

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Dharmasri, C.; Golbach, J.; Guo, R.; Maxwell, C.; Privalle, L.; Rogers, H.; Liu, K.; Shan, G. M.; Yarnall, M.;

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Cong, B.; Maxwell, C.; Luck, S.; Vespestad, D.; Richard, K.; Mickelson, J.; Zhong, C., Genotypic and

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and Analysis 2016, 51, 106-111.

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herbicide-tolerant, increased oleic acid genetically modified soybean MON 87705 for food and feed uses,

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import and processing under Regulation (EC) No 1829/2003 from Monsanto. EFSA Journal 2012, 10.

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20.

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stacked genetically modified events: To assess or not to assess? Trends in Biotechnology 2014, 32, 70-73.

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21.

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max L.) MON 87708 and MON 87708 x MON 89788 Are Compositionally Equivalent to Conventional

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genome plasticity and its relevance to food and feed safety of genetically engineered breeding stacks.

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87705, MON 87708, and MON 89788: Summary. Food Safety 2016, 4, 169-172.

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440

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441



442


Page 22 of 33

Page 23 of 33


443 444

Figure Captions

445

Figure 1. Protein levels in maize and soybean grain.

446

The range of total protein is shown, with protein expressed as percent dry weight. For each

447

pair, the dark grey bar represents the range of observed protein values for the indicated GE

448

substance, and the pale grey bar represents the range of observed protein values for a related

449

conventional variety (“control”) that was grown concurrently. The medium grey bar at the far

450

right of each panel represents the range of protein values reported for the respective crop in

451

the ILSI Crop Composition Database (ILSI CCBD).

452

A. Protein levels in maize grain. Stack 1 is MON 87427 x MON 89034 x MON 88017, Stack 2 is

453

MON 89034 × TC1507 × MON 88017 × DAS-59122-7, and Stack 3 is MON 87427 x MON 89034 ×

454

TC1507 × MON 88017 × DAS-59122-7.

455

B. Protein levels in harvested soybean seed. Stack 1 is MON 87705 x MON 89788, and Stack 2

456

is MON 87705 x MON 87708 x MON 89788.

457



Page 24 of 33

Table 1. Key traits of interest for the single trait products combined through conventional breeding in the assessed stacked trait products Citationsa

Crop

Product

Key Trait(s) of interest

Maize (Zea mays)

MON 89034

Protection against target aboveDrury et al, 2008(11) ground pests, through expression of Cry1A.105 and Cry2Ab2

MON 88017

Protection against target below ground pests, through expression of Cry3Bb1; tolerance to glyphosate herbicide through expression of CP4 EPSPS Tissue-selective tolerance to glyphosate herbicide (through expression of CP4 EPSPS), to facilitate production of viable hybrid maize seed Protection against target aboveground pests through expression of Cry1F

MON 87427

TC1507

DAS-59122-7

McCann et al., 2007(26)

Venkatesh et al, 2014(27); additional data provided in this publication

Baktavachalam 2015(28)

et

Protection against target below- Herman et al, 2007(29) ground pests, through expression of Cry34Ab1 and Cry 35Ab1); tolerance to glufosinate herbicide through expression of PAT Soybean MON 87705 Nutritionally-enhanced fatty acid This publication (Glycine profile, with increased level of max) oleic acid and decreased levels of palmitic, stearic, and linoleic acids MON 89788 Tolerance to glyphosate Lundry et al, 2008 (30) herbicide through expression of CP4 EPSPS MON 87708 Tolerance to dicamba herbicide Taylor et al, 2017(21) through expression of DMO a Reporting of compositional data for single trait product, where available


al.,

Page 25 of 33


Table 2. Compositional assessment of selected maize single trait and stacked trait products.

CONTROL

MON 87427 X MON 89034 × TC1507 × MON 88017 × DAS59122-7

9.69 0.42 11.10 8.52

c

9.13 0.41 10.35 6.77

3.69 0.13 3.98 3.47

4.16 0.085 4.49 3.88

4.13 0.084 4.29 4.00

1.62 0.036 1.82 1.42

1.56 0.038 1.67 1.48

1.47 0.052 1.66 1.25

c

84.96 0.42 86.22 83.58

84.70 0.56 85.62 83.63

84.51 0.57 85.76 82.96

84.68 0.42 86.16 83.43

9.12 0.060 9.34 8.91

11.08 0.26 11.69 10.65

10.54 0.26 11.08 10.15

11.05 0.12 11.39 10.52

CONTROL

MON 89034 × TC1507 × MON 88017 × DAS59122-7

MON 87427

CONTROL

MON a 88017

CONTROL

MON a 89034

CONTROL

MON 87427 X MON 89034 X MON 88017

10.05 0.63 11.35 8.46

10.26 0.63 11.92 8.62

12.51 0.35 13.00 11.63

12.28 0.35 13.82 11.22

10.43 0.42 11.98 8.54

10.36 0.42 11.52 9.22

10.03 0.63 11.08 8.85

10.26 0.63 11.92 8.62

3.50 0.13 3.83 3.13

3.69 0.13 3.98 3.47

3.64 0.13 3.96 3.44

3.79 0.13 4.36 3.53

3.32 0.069 3.89 3.05

3.29 0.069 3.75 3.05

3.67 0.13 3.93 3.19

1.58 0.036 1.81 1.43

1.56 0.038 1.67 1.48

1.54 0.077 1.68 1.31

1.59 0.077 1.97 1.23

1.41 0.036 1.56 1.25

1.39 0.036 1.51 1.28

84.88 0.56 86.33 83.60

84.51 0.57 85.76 82.96

82.32 0.40 83.39 81.61

82.33 0.40 83.62 80.67

84.85 0.42 86.52 83.29

10.54 0.26 11.08 10.15

10.24 0.43 10.52 10.07

11.27 0.43 14.57 10.14

9.19 0.060 9.46 8.98

CONTROL

ILSI b CCDB

10.06 0.20 11.27 8.78

9.21 0.20 10.51 7.44

17.26 5.72

3.74 0.089 4.37 3.19

c

3.33 0.089 3.78 2.74

7.83 1.36

1.34 0.051 1.55 1.06

1.34 0.040 1.81 1.02

1.33 0.040 1.86 0.96

6.28 0.62

85.39 0.41 87.85 84.08

84.86 0.23 86.58 83.95

c

86.13 0.23 88.12 84.93

89.7 77.4

10.63 0.12 11.28 10.40

11.05 0.11 11.69 10.40

c

11.67 0.11 13.26 10.87

26.55 6.81

Protein (% dw) MEAN S.E. MAX MIN Fat (% dw) MEAN S.E. MAX MIN Ash (% dw) MEAN S.E. MAX MIN Carbs (% dw) MEAN S.E. MAX MIN Palmitic Acid (% Total FA) MEAN S.E. MAX MIN

c

c

10.91 0.26 11.52 10.44

c


c

c


Page 26 of 33

Table 2, cont.

Stearic Acid (% Total FA) MEAN S.E. MAX MIN Oleic Acid (% Total FA) MEAN S.E. MAX MIN Linoleic Acid (% Total FA) MEAN S.E. MAX MIN Linolenic Acid (% Total FA) MEAN S.E. MAX MIN

1.82 0.021 1.87 1.76

2.01 0.091 2.19 1.83

1.90 0.091 2.07 1.77

2.10 0.080 2.40 1.90

2.01 0.079 2.19 1.81

2.13 0.049 2.59 1.85

22.87 0.23 23.51 21.43

24.96 0.34 25.75 23.38

24.84 0.34 26.66 23.62

23.55 0.92 25.41 21.94

23.52 0.92 25.71 21.74

32.20 0.78 34.02 30.43

32.24 0.78 33.66 30.74

62.85 0.39 63.72 61.86

61.52 0.39 63.18 59.10

61.82 0.40 63.61 60.85

62.07 0.40 63.41 60.51

61.33 1.28 63.20 58.62

62.06 1.28 64.09 59.18

52.81 0.75 54.37 51.10

1.21 0.062 1.26 1.15

1.32 0.062 1.77 1.19

1.19 0.027 1.23 1.12

1.22 0.027 1.43 1.15

1.23 0.014 1.28 1.20

c

1.20 0.014 1.22 1.18

1.01 0.016 1.04 0.98

CONTROL

MON a 89034

1.90 0.091 2.07 1.77

2.01 0.073 2.19 1.80

2.07 0.073 2.23 1.76

23.52 0.92 25.71 21.74

22.74 0.23 23.53 22.20

60.84 1.28 62.70 57.61

62.06 1.28 64.09 59.18

1.20 0.014 1.26 1.13

1.20 0.014 1.22 1.18

c

c

24.28 0.92 26.62 22.84

c

CONTROL

1.89 0.021 2.03 1.79

MON a 88017

1.97 0.091 2.17 1.81

CONTROL

CONTROL

MON 87427 X MON 89034 X MON 88017

CONTROL

MON 87427

MON 89034 × TC1507 × MON 88017 × DAS59122-7


c

c

c

c


CONTROL

ILSI b CCDB

2.00 0.049 2.40 1.76

3.83 1.02

23.02 0.32 25.05 19.86

22.50 0.32 24.01 20.22

42.81 16.38

53.29 0.75 54.98 51.95

61.65 0.26 64.12 59.86

61.69 0.26 63.59 60.58

67.68 34.27

1.01 0.015 1.10 0.92

1.21 0.024 1.40 1.10

c

1.25 0.024 1.53 1.15

2.33 0.55

c

c

Page 27 of 33


Table 2, cont.

CONTROL

CONTROL

MON a 88017

CONTROL

MON a 89034

CONTROL

MON 87427 X MON 89034 X MON 88017

0.96 0.031 1.04 0.87

1.02 0.031 1.12 0.94

0.95 0.043 1.05 0.83

0.89 0.043 1.03 0.72

0.75 0.050 0.87 0.53

0.73 0.050 0.88 0.56

1.03 0.031 1.07 0.93

1.02 0.031 1.12 0.94

1.00 0.055 1.08 0.89

0.92 0.054 1.10 0.71

0.94 0.020 1.10 0.76

0.14 0.028 0.21 0.098

0.15 0.029 0.21 0.11

0.17 0.013 0.20 0.14

0.17 0.013 0.23 0.14

-

-

0.15 0.028 0.21 0.093

0.15 0.029 0.21 0.11

0.086 0.019 0.14 0.028

0.10 0.019 0.13 0.028

0.26 0.0096 0.33 0.17

MON 87427

Phytic Acid (% dw) MEAN S.E. MAX MIN Raffinose (% dw) MEAN S.E. MAX MIN

CONTROL

MON 89034 × TC1507 × MON 88017 × DAS59122-7


c

a

c

c

CONTROL

ILSI b CCDB

0.90 0.020 1.01 0.66

1.94 0.11

0.24 0.0096 0.28 0.19

0.47 0.02

Composition data shown have been previously reported (MON 88017(26); MON 89034(11)); they are included here for comparison purposes. ILSI Crop Composition Database, Version 6.0; accessed 8/3/17 (www.crop.composition.com) c indicates statistical significance at p

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