Background: One theoretical explanation for the relatively poor performance ofBrassica rapa(weed) ×Brassica napus(crop) transgenic hybrids suggests that hybridization imparts a negative genetic load. Consequently, in hybrids genetic load could overshadow any benefits of fitness enhancing transgenes and become the limiting factor in transgenic hybrid persistence. Two types of genetic load were analyzed in this study: random/linkage-derived genetic load, and directly incorporated genetic load using a transgenic mitigation (TM) strategy. In order to measure the effects of random genetic load, hybrid productivity (seed yield and biomass) was correlated with crop- and weed-specific AFLP genomic markers. This portion of the study was designed to answer whether or not weed × transgenic crop hybrids possessing more crop genes were less competitive than hybrids containing fewer crop genes. The effects of directly incorporated genetic load (TM) were analyzed through transgene persistence data. TM strategies are proposed to decrease transgene persistence if gene flow and subsequent transgene introgression to a wild host were to occur.Results: In the absence of interspecific competition, transgenic weed × crop hybrids benefited from having more crop-specific alleles. There was a positive correlation between performance and number ofB. napuscrop-specific AFLP markers [seed yield vs. marker number (r = 0.54, P = 0.0003) and vegetative dry biomass vs. marker number (r = 0.44, P = 0.005)]. However under interspecific competition with wheat or more weed-like conditions (i.e. representing a situation where hybrid plants emerge as volunteer weeds in subsequent cropping systems), there was a positive correlation between the number ofB. rapaweed-specific AFLP markers and seed yield (r = 0.70, P = 0.0001), although no such correlation was detected for vegetative biomass. When genetic load was directly incorporated into the hybrid genome, by inserting a fitness-mitigating dwarfing gene that that is beneficial for crops but deleterious for weeds (a transgene mitigation measure), there was a dramatic decrease in the number of transgenic hybrid progeny persisting in the population.Conclusion: The effects of genetic load of crop and in some situations, weed alleles might be beneficial under certain environmental conditions. However, when genetic load was directly incorporated into transgenic events, e.g., using a TM construct, the number of transgenic hybrids and persistence in weedy genomic backgrounds was significantly decreased.

Conyza bonariensis (hairy fleabane) is one of the most problematic and widespread glyphosate-resistant weeds in the world. This highly competitive weed species significantly interferes with crop growth and substantially decreases crop yield. Despite its agricultural importance, the molecular mechanisms of glyphosate resistance are still unknown. The present RNA-Seq study was performed with the goal of identifying differentially expressed candidate transcripts (genes) related to metabolism-based non-target site glyphosate resistance in C. bonariensis. The whole-transcriptome was de novo assembled from glyphosate-resistant and -sensitive biotypes of C. bonariensis from Southern Brazil. The RNA was extracted from untreated and glyphosate-treated plants at several timepoints up to 288 h after treatment in both biotypes. The transcriptome assembly produced 90,124 contigs with an average length of 777 bp and N50 of 1118 bp. In response to glyphosate treatment, differential gene expression analysis was performed on glyphosate-resistant and -sensitive biotypes. A total of 9622 genes were differentially expressed as a response to glyphosate treatment in both biotypes, 4297 (44.6%) being up- and 5325 (55.4%) down-regulated. The resistant biotype presented 1770 up- and 2333 down-regulated genes while the sensitive biotype had 2335 and 2800 up- and down-regulated genes, respectively. Among them, 974 up- and 1290 down-regulated genes were co-expressed in both biotypes. In the present work, we identified 41 new candidate target genes from five families related to herbicide transport and metabolism: 19 ABC transporters, 10 CYP450s, one glutathione S-transferase (GST), five glycosyltransferases (GT), and six genes related to antioxidant enzyme catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD). The candidate genes may participate in metabolic-based glyphosate resistance via oxidation, conjugation, transport, and degradation, plus antioxidation. One or more of these genes might ‘rescue’ resistant plants from irreversible damage after glyphosate treatment. The 41 target genes we report in the present study may inform further functional genomics studies, including gene editing approaches to elucidate glyphosate-resistance mechanisms in C. bonariensis.

Background: The expression of fluorescent protein (FP) genes as real-time visual markers, both transiently and stably, has revolutionized plant biotechnology. A palette of colors of FPs is now available for use, but the diversity has generally been underutilized in plant biotechnology. Because of the green and far-red autofluorescent properties of many plant tissues and the FPs themselves, red and orange FPs (RFPs, and OFPs, respectfully) appear to be the colors with maximum utility in plant biotechnology. Within the color palette OFPs have emerged as the brightest FP markers in the visible spectra. This study compares several native, near-native and modified OFPs for their “brightness” and fluorescence, therefore, their usability as marker genes in transgenic plant tissues. Results: The OFPs DsRed2, tdTomato, mOrange and pporRFP were all expressed under the control of the CaMV 35S promoter in agroinfiltration-mediated transient assays in Nicotiana benthamiana. Each of these, as well as endoplasmic reticulum (ER)-targeted versions, were stably expressed in transgenic Nicotiana tabacum and Arabidopsis thaliana. Congruent results were observed between transient and stable assays. Our results demonstrated that there are several adequate OFP genes available for plant transformation, including the new pporRFP, an unaltered tetramer from the hard coral Porites porites. When the tandem dimer tdTomato and the monomeric mOrange were targeted to the ER, dramatic, ca. 3-fold, increase in plant fluorescence was observed. Conclusions: From our empirical data, and a search of the literature, it appears that tdTomato-ER and mOrange-ER are the two highest fluorescing FPs available as reporters for transgenic plants. The pporRFP is a brightly fluorescing tetramer, but all tetramer FPs are far less bright than the ER-targeted monomers we report here.

Trypsin inhibitors (TIs) are widely distributed in plants and are known to play a protective role against herbivores. TIs reduce the biological activity of trypsin, an enzyme involved in the breakdown of many different proteins, by inhibiting the activation and catalytic reactions of proteins. Soybean (Glycine max) contains two major TI classes: Kunitz trypsin inhibitor (KTI) and Bowman-Birk inhibitor (BBI). Both genes encoding TI inactivate trypsin and chymotrypsin enzymes, which are the main digestive enzymes in the gut fluids of Lepidopteran larvae feeding on soybean. In this study, the possible role of soybean TIs in plant defense against insects and nematodes was investigated. A total of six TIs were tested, including three known soybean trypsin inhibitors (KTI1, KTI2 and KTI3) and three genes encoding novel inhibitors identified in soybean (KTI5, KTI7, and BBI5). Their functional role was further examined by overexpression of the individual TI genes in soybean and Arabidopsis. The endogenous expression patterns of these TI genes varied among soybean tissues, including leaf, stem, seed, and root.In vitroenzyme inhibitory assays showed significant increase in trypsin and chymotrypsin inhibitory activities in both transgenic soybean and Arabidopsis. Detached leaf-punch feeding bioassays detected significant reduction in corn earworm (Helicoverpa zea) larval weight when larvae fed on transgenic soybean and Arabidopsis lines, with the greatest reduction observed in KTI7 and BBI5 overexpressing lines. Whole soybean plant greenhouse feeding bioassays withH. zeaon KTI7 and BBI5 overexpressing lines resulted in significantly reduced leaf defoliation compared to non-transgenic plants. However, bioassays of KTI7 and BBI5 overexpressing lines with soybean cyst nematode (SCN,Heterodera glycines) showed no differences in SCN female index between transgenic and non-transgenic control plants. There were no significant differences in growth and productivity between transgenic and non-transgenic plants grown in the absence of herbivores to full maturity under greenhouse conditions. The present study provides further insight into the potential applications of TI genes for insect resistance improvement in plants.

Unmanned aerial vehicles (UAVs) provide an intermediate scale of spatial and spectral data collection that yields increased accuracy and consistency in data collection for morphological and physiological traits than satellites and expanded flexibility and high-throughput compared to ground-based data collection. In this study, we used UAV-based remote sensing for automated phenotyping of field-grown switchgrass (Panicum virgatum), a leading bioenergy feedstock. Using vegetation indices calculated from a UAV-based multispectral camera, statistical models were developed for rust disease caused by Puccinia novopanici, leaf chlorophyll, nitrogen, and lignin contents. For the first time, UAV remote sensing technology was used to explore the potentials for multiple traits associated with sustainable production of switchgrass, and one statistical model was developed for each individual trait based on the statistical correlation between vegetation indices and the corresponding trait. Also, for the first time, lignin content was estimated in switchgrass shoots via UAV-based multispectral image analysis and statistical analysis. The UAV-based models were verified by ground-truthing via correlation analysis between the traits measured manually on the ground-based with UAV-based data. The normalized difference red edge (NDRE) vegetation index outperformed the normalized difference vegetation index (NDVI) for rust disease and nitrogen content, while NDVI performed better than NDRE for chlorophyll and lignin content. Overall, linear models were sufficient for rust disease and chlorophyll analysis, but for nitrogen and lignin contents, nonlinear models achieved better results. As the first comprehensive study to model switchgrass sustainability traits from UAV-based remote sensing, these results suggest that this methodology can be utilized for switchgrass high-throughput phenotyping in the field.