Monsanto Co. has developed two sweet corn hybrids, MON 88017 and MON 89034, that contain biotechnology-derived (biotech) traits designed to enhance sustainability and improve agronomic practices. MON 88017 confers benefits of glyphosate tolerance and protection against corn rootworm. MON 89034 provides protection against European corn borer and other lepidopteran insect pests. The purpose of this assessment was to compare the kernel compositions of MON 88017 and MON 89034 sweet corn with that of a conventional control that has a genetic background similar to the biotech sweet corn but does not express the biotechnology-derived traits. The sweet corn samples were grown at five replicated sites in the United States during the 2010 growing season and the conventional hybrid and 17 reference hybrids were grown concurrently to provide an estimate of natural variability for all assessed components. The compositional analysis included proximates, fibers, amino acids, sugars, vitamins, minerals, and selected metabolites. Results highlighted that MON 88017 and MON 89034 sweet corns were compositionally equivalent to the conventional control and that levels of the components essential to the desired properties of sweet corn, such as sugars and vitamins, were more affected by growing environment than the biotech traits. In summary, the benefits of biotech traits can be incorporated into sweet corn with no adverse effects on nutritional quality.

The selection of an appropriate seed source for a given geographic region is critical to ensuring prosperous southern pine plantations. The observed variation between eastern and western loblolly pine seed sources has shown differences in economically advantageous traits such as drought tolerance, growth rates, and disease resistance. Understanding what drives these local adaptations is of interest, given that current forecasted climate modeling suggests there will be increased temperatures and changes to precipitation by the year 2050. The objectives of this experiment were to 1) identify differentially expressed transcripts between eastern and western loblolly pine sources; 2) link these transcripts to Arabidopsis orthologs; 3) compare GO categories of differentially-expressed transcripts. The findings highlighted include interesting pathways and genes that are related to the known differences among eastern and western seed provenances. Additionally, they represent fundamental differences in the beginning of seedling development without any treatment or disease pressure applied, showing that there are detectable differences between these two provenances at a young age. Overall, this experiment contributes to the body of literature on fundamental differences between loblolly pine seed sources.

Phenotypic variation in forest trees can be partitioned into subsets controlled by genetic variation and by environmental factors, and heritability expressed as the proportion of total phenotypic variation attributed to genetic variation. Applied tree breeding programs can use matrices of relationships, based either on recorded pedigrees in structured breeding populations or on genotypes of molecular genetic markers, to model genetic covariation among related individuals and predict genetic values for individuals for whom no phenotypic measurements are available. This study tests the hypothesis that genetic covariation among individuals of similar genetic value will be reflected in shared patterns of gene expression. We collected gene expression data by high-throughput sequencing of RNA isolated from pooled seedlings from parents of known genetic value, and compared alternative approaches to data analysis to test this hypothesis. Selection of specific sets of transcripts increased the predictive power of models over that observed using all transcripts. Using information on presence of putative mutations in protein-coding sequences increased predictive accuracy for some traits but not for others. Known pedigree relationships are not required for this approach to modeling genetic variation, so it has potential to allow broader application of genetic covariance modeling to natural populations of forest trees.

Computer simulations of breeding strategies are an essential resource for tree breeders because they allow exploratory analyses into potential long-term impacts on genetic gain and inbreeding consequences without bearing the cost, time, or resource requirements of field experiments. Previous work has modeled the potential long-term implications on inbreeding and genetic gain using random mating and phenotypic selection. Reduction in sequencing costs has enabled the use of DNA marker-based relationship matrices in addition to or in place of pedigree-based allele sharing estimates; this has been shown to provide a significant increase in the accuracy of progeny breeding value prediction. A potential pitfall of genomic selection using genetic relationship matrices is increased coancestry among selections, leading to the accumulation of deleterious alleles and inbreeding depression. We used simulation to compare the relative genetic gain and risk of inbreeding depression within a breeding program similar to loblolly pine, utilizing pedigree-based or marker-based relationships over ten generations. We saw a faster rate of purging deleterious alleles when using a genomic relationship matrix based on markers that track identity-by-descent of segments of the genome. Additionally, we observed an increase in the rate of genetic gain when using a genomic relationship matrix instead of a pedigree-based relationship matrix. While the genetic variance of populations decreased more rapidly when using genomic-based relationship matrices as opposed to pedigree-based, there appeared to be no long-term consequences on the accumulation of deleterious alleles within the simulated breeding strategy.