Genome-wide association studies dissect the G × E interaction for agronomic traits in a worldwide collection of safflowers (Carthamus tinctorius L.).

Genome-wide association studies were conducted using a globally diverse safflower (Carthamus tinctorius L.) Genebank collection for grain yield (YP), days to flowering (DF), plant height (PH), 500 seed weight (SW), seed oil content (OL), and crude protein content (PR) in four environments (sites) that differed in water availability. Phenotypic variation was observed for all traits. YP exhibited low overall genetic correlations (rGoverall) across sites, while SW and OL had high rGoverall and high pairwise genetic correlations (rGij) across all pairwise sites. In total, 92 marker-trait associations (MTAs) were identified using three methods, single locus genome-wide association studies (GWAS) using a mixed linear model (MLM), the Bayesian multi-locus method (BayesR), and meta-GWAS. MTAs with large effects across all sites were detected for OL, SW, and PR, and MTAs specific for the different water stress sites were identified for all traits. Five MTAs were associated with multiple traits; 4 of 5 MTAs were variously associated with the three traits of SW, OL, and PR. This study provided insights into the phenotypic variability and genetic architecture of important safflower agronomic traits under different environments. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-022-01295-8.

Mining the Wheat Grain Proteome.

Bread wheat is the most widely cultivated crop worldwide, used in the production of food products and a feed source for animals. Selection tools that can be applied early in the breeding cycle are needed to accelerate genetic gain for increased wheat production while maintaining or improving grain quality if demand from human population growth is to be fulfilled. Proteomics screening assays of wheat flour can assist breeders to select the best performing breeding lines and discard the worst lines. In this study, we optimised a robust LC-MS shotgun quantitative proteomics method to screen thousands of wheat genotypes. Using 6 cultivars and 4 replicates, we tested 3 resuspension ratios (50, 25, and 17 µL/mg), 2 extraction buffers (with urea or guanidine-hydrochloride), 3 sets of proteases (chymotrypsin, Glu-C, and trypsin/Lys-C), and multiple LC settings. Protein identifications by LC-MS/MS were used to select the best parameters. A total 8738 wheat proteins were identified. The best method was validated on an independent set of 96 cultivars and peptides quantities were normalised using sample weights, an internal standard, and quality controls. Data mining tools found particularly useful to explore the flour proteome are presented (UniProt Retrieve/ID mapping tool, KEGG, AgriGO, REVIGO, and Pathway Tools).

A Simple High-Throughput Method for the Analysis of Vicine and Convicine in Faba Bean.

The faba bean is one of the earliest domesticated crops, with both economic and environmental benefits. Like most legumes, faba beans are high in protein, and can be used to contribute to a balanced diet, or as a meat substitute. However, they also produce the anti-nutritional compounds, vicine and convicine (v-c), that when enzymatically degraded into reactive aglycones can potentially lead to hemolytic anemia or favism. Current methods of analysis use LC-UV, but are only suitable at high concentrations, and thus lack the selectivity and sensitivity to accurately quantitate the low-v-c genotypes currently being developed. We have developed and fully validated a rapid high-throughput LC-MS method for the analysis of v-c in faba beans by optimizing the extraction protocol and assessing the method of linearity, limit of detection, limit of quantitation, accuracy, precision and matrix effects. This method uses 10-times less starting material; removes the use of buffers, acids and organic chemicals; and improves precision and accuracy when compared to current methods.

Genotype and environment effects on the chemical composition and rheological properties of field peas.

BACKGROUND: The inclusion of pulses in traditional wheat-based food products such as bread, cakes, and pasta is increasing as the food industry and consumers are recognizing the nutritional benefits due to high protein, antioxidant activity, and good sources of dietary fiber of pulses. In all crops, including cereals, oilseeds, and pulses, variability in chemical composition is known to exist due to genetic differences and environmental effects. This study reports the effect of genotype and environment on seed composition and the rheological properties of field-pea genotypes for both field-pea flour and isolated starch. RESULTS: Genotype had a significant effect on the chemical composition (protein, total starch, water-soluble carbohydrates, and phenolic compounds), the mean starch granule size, and rheological properties (peak viscosity, breakdown viscosity, final viscosity, peak time, and pasting temperature) of the field peas. The growing environment also had a significant effect on starch granule size, phytic acid, water-soluble carbohydrates, some phenolic compounds, and pasting characteristics of field peas. Genotype × environment (G × E) interactions were observed for protein, some phenolic compounds, and some pasting characteristics. CONCLUSION: Genotype and the growing environment had a significant effect on the chemical composition and rheological properties of the field pea. The variability in composition and quality traits could be exploited through plant breeding and optimized agronomic practices to increase production of field peas with the desired quality traits. © 2019 Society of Chemical Industry.

Genomic Prediction and Genetic Correlation of Agronomic, Blackleg Disease, and Seed Quality Traits in Canola (Brassica napus L.).

Genomic selection accelerates genetic progress in crop breeding through the prediction of future phenotypes of selection candidates based on only their genomic information. Here we report genetic correlations and genomic prediction accuracies in 22 agronomic, disease, and seed quality traits measured across multiple years (2015-2017) in replicated trials under rain-fed and irrigated conditions in Victoria, Australia. Two hundred and two spring canola lines were genotyped for 62,082 Single Nucleotide Polymorphisms (SNPs) using transcriptomic genotype-by-sequencing (GBSt). Traits were evaluated in single trait and bivariate genomic best linear unbiased prediction (GBLUP) models and cross-validation. GBLUP were also expanded to include genotype-by-environment G × E interactions. Genomic heritability varied from 0.31to 0.66. Genetic correlations were highly positive within traits across locations and years. Oil content was positively correlated with most agronomic traits. Strong, not previously documented, negative correlations were observed between average internal infection (a measure of blackleg disease) and arachidic and stearic acids. The genetic correlations between fatty acid traits followed the expected patterns based on oil biosynthesis pathways. Genomic prediction accuracy ranged from 0.29 for emergence count to 0.69 for seed yield. The incorporation of G × E translates into improved prediction accuracy by up to 6%. The genomic prediction accuracies achieved indicate that genomic selection is ready for application in canola breeding.

NMR Based Metabolomic Analysis of Health Promoting Phytochemicals in Lentils.

Lentils are a high-protein plant food and a valuable source of human nutrition, particularly in the Indian subcontinent. However, beyond sustenance, there is evidence that the consumption of lentils (and legumes in general) is associated with decreased risk of diseases, such as diabetes and cardiovascular disease. Lentils contain health-promoting phytochemicals, such as trigonelline and various polyphenolics. Fourteen lentil genotypes were grown at three locations to explore the variation in phytochemical composition in hulls and cotyledons. Significant differences were measured between genotypes and environments, with some genotypes more affected by environment than others. However, there was a strong genetic effect which indicated that future breeding programs could breed for lentils that product more of these health-promoting phytochemicals.

A Robust Automated Image-Based Phenotyping Method for Rapid Vegetative Screening of Wheat Germplasm for Nitrogen Use Efficiency.

Nitrogen use efficiency (NUE) in crops is generally low, with more than 60% of applied nitrogen (N) being lost to the environment, which increases production costs and affects ecosystems and human habitats. To overcome these issues, the breeding of crop varieties with improved NUE is needed, requiring efficient phenotyping methods along with molecular and genetic approaches. To develop an effective phenotypic screening method, experiments on wheat varieties under various N levels were conducted in the automated phenotyping platform at Plant Phenomics Victoria, Horsham. The results from the initial experiment showed that two relative N levels-5 mM and 20 mM, designated as low and optimum N, respectively-were ideal to screen a diverse range of wheat germplasm for NUE on the automated imaging phenotyping platform. In the second experiment, estimated plant parameters such as shoot biomass and top-view area, derived from digital images, showed high correlations with phenotypic traits such as shoot biomass and leaf area seven weeks after sowing, indicating that they could be used as surrogate measures of the latter. Plant growth analysis confirmed that the estimated plant parameters from the vegetative linear growth phase determined by the "broken-stick" model could effectively differentiate the performance of wheat varieties for NUE. Based on this study, vegetative phenotypic screens should focus on selecting wheat varieties under low N conditions, which were highly correlated with biomass and grain yield at harvest. Analysis indicated a relationship between controlled and field conditions for the same varieties, suggesting that greenhouse screens could be used to prioritise a higher value germplasm for subsequent field studies. Overall, our results showed that this phenotypic screening method is highly applicable and can be applied for the identification of N-efficient wheat germplasm at the vegetative growth phase.

Studies on the application of temperature-responsive ion exchange polymers with whey proteins.

Several new types of temperature-responsive ion exchange resins of different polymer composition have been prepared by grafting the products from the co-polymerisation of N-phenylacrylamide, N-iso-propylacrylamide and acrylic acid derivatives onto cross-linked agarose. Analysis of the binding isotherms for these different resins obtained under batch adsorption conditions indicated that the resin based on N-iso-propylacrylamide containing 5% (w/w) N-phenylacrylamide and 5% (w/w) acrylic acid resulted in the highest adsorption capacity, Bmax, for the whey protein, bovine lactoferrin, e.g. 14 mg bovine lactoferrin/mL resin at 4 °C and 62 mg bovine lactoferrin/mL resin at 40 °C, respectively. Under dynamic loading conditions at 40 °C, 94% of the loaded bovine lactoferrin on a normalised mg protein per mL resin basis was adsorbed by this new temperature-responsive ion-exchanger, and 76% was eluted by a single cycle temperature shift to 4 °C without varying the composition of the 10mM sodium dihydrogen phosphate buffer, pH 6.5, or the flow rate. The binding characteristics of these different ion exchange resins with bovine lactoferrin were also compared to results obtained using other resins based on N-isopropylacrylamide but contained N-tert-butylacrylamide rather than N-phenylacrylamide, where the corresponding dynamic capture and release properties for bovine lactoferrin required different temperature conditions of 20 °C and 50 °C, respectively for optimal desorption/adsorption. The cationic protein, bovine lactoperoxidase, was also adsorbed and desorbed with these temperature-responsive resins under similar conditions of changing temperature, whereas the anionic protein, bovine ß-lactoglobulin, was not adsorbed under this regime of temperature conditions but instead eluted in the flow-through.

Development of a temperature-responsive agarose-based ion-exchange chromatographic resin.

A temperature-responsive ion-exchange resin (ItBA) has been prepared by grafting poly(N-isopropylacrylamide-co-acrylic acid-co-tert-butylacrylamide; ItBA) onto cross-linked agarose. A carboxymethylated ion exchanger (CM) of similar charge density was also prepared. Maximum adsorption capacities (B(max)) for lactoferrin at 20 degrees C and 50 degrees C were determined for both resins by batch adsorption procedures. Dynamic adsorption and desorption characteristics of the CM and ItBA with lactoferrin were established, as well as the ability of ItBA to selectively adsorb and desorb lactoferrin in the presence of other proteins. With the CM-agarose resin there was no significant difference between the B(max) values obtained at 20 degrees C and 50 degrees C. However, for the agarose-based ItBA resin the B(max) value at 50 degrees C was almost three times higher than the B(max) value at 20 degrees C. Dynamically, lactoferrin adsorbed to the ItBA packed column at 50 degrees C with a significant proportion of the adsorbed lactoferrin desorbed by reducing the temperature to 20 degrees C. In addition, anionic proteins did not adsorb to the ItBA packed column, and did not interfere with the dynamic adsorption/desorption behaviour of lactoferrin. These results indicate that this new temperature-responsive agarose-based ItBA resin has potential for the fractionation of whey proteins, with good selectivity for cationic proteins.