No correlation between amylase/trypsin-inhibitor content and amylase inhibitory activity in hexaploid and tetraploid wheat species

Wheat amylase/trypsin-inhibitors (ATI) are known triggers for wheat-related disorders. The aims of our study were to determine (1) the inhibitory activity against different α-amylases, (2) the content of albumins and globulins (ALGL) and total ATI and (3) to correlate these parameters in wholegrain flour of hexaploid, tetraploid and diploid wheat species. The amount of ATI within the ALGL fraction varied from 0.8% in einkorn to 20% in spelt. ATI contents measured with reversed-phase high-performance liquid chromatography (RP-HPLC) revealed similar contents (1.2–4.2 mg/g) compared to the results determined by LC-MS/MS (0.2–5.2 mg/g) for all wheat species except einkorn. No correlation was found between ALGL content and inhibitory activity. In general, hexaploid cultivars of spelt and common wheat had the highest inhibitory activities, showing values between 897 and 3564 AIU/g against human salivary α-amylase. Tetraploid wheat species durum and emmer had lower activities (170–1461 AIU/g), although a few emmer cultivars showed similar activities at one location. In einkorn, no inhibitory activity was found. No correlation was observed between the ATI content and the inhibitory activity against the used α-amylases, highlighting that it is very important to look at the parameters separately

Association of progeny variance and genetic distances among parents and implications for the design of elite maize breeding programs

Choice of crosses is crucial for a successful and sustainable management of breeding programs. Our objectives were to (1) investigate the association between the Rogers’ distances among parents and the genetic variance within their crosses (σ2 within) in elite maize breeding germplasm, (2) study whether this association can be improved selecting trait-specific markers, and (3) evaluate the consequences to implement the usefulness criterion based on Rogers’ distances on the optimum choice of crosses. Testcross performance of eleven segregating crosses with a total of 930 progenies was evaluated in six environments for grain yield (GY) and grain moisture content (GMC). Moreover, the 930 genotypes were fingerprinted with 425 polymorphic SNP markers. Our findings revealed that working within a heterotic group, σ2 within increased with increasing Rogers’ distances among the parents. This was more pronounced for GY (rP = 0.55 P < 0.1) compared to GMC (rP = 0.17). Selecting trait specific markers, which were associated with putative QTL affecting these traits, led for GY to a decrease in the association between σ2 within and Rogers’ distances among the parents. Consequently, using for GY a regression model based on Rogers’ distances estimated with an unselected set of markers allows a rough implementation of the usefulness criterion in maize breeding programs. Our model calculations suggested that implementing the usefulness criterion will facilitate a broadening of the diversity of elite maize breeding pools by counterbalancing a reduction in parental performance with an increase in σ2 within

Estimation of quantitative genetic and stability parameters in maize under high and low N levels

AB It is important to breed maize (Zea mays L) cultivars with high performance under variable N levels. We studied the effect of N levels and estimated quantitative genetic parameters for grain yield, quality, and other traits, and examined stability of performance for grain yield in diverse Chinese maize germplasm. From 2006 to 2008, each year 20 and in total 30 maize hybrids, including commercial hybrids currently grown in this region and other ex¬perimental hybrids as well as high-oil hybrids, were tested using nine environments (location-year combinations) in North China Plain. In each environment, two replicated trials were grown: one under high N application rate (HN, 225 kg N ha-1) and the other under low N application rate (LN, no N fertilization). Compared to HN, grain yield was significantly reduced (35.6%) under LN level, as well as kernel number per ear, 1000-kernel weight, plant and ear heights, and protein concentration. In the analysis over environments under each N level, genotypic variance was significant and heritability was high for all traits. In the analyses across N levels and environments, genotypic variance was significant for all traits and larger than the genotype × N and/or environment interaction variance components except for protein concentration. In stability analyses across N levels, hybrids differed for their linear response to environments, and some showed dissimilar response under HN and LN levels. Our results indicated that breeding maize adapted to variable N levels is feasible with the Chinese germplasm available in the summer breeding programs in North China Plain. Multi-environment tests are required to identify hybrids with high grain yield under variable N conditions, and examining yield stability separately under HN and LN would be useful

The Global Durum Wheat Panel (GDP): An International Platform to Identify and Exchange Beneficial Alleles

Representative, broad and diverse collections are a primary resource to dissect genetic diversity and meet pre-breeding and breeding goals through the identification of beneficial alleles for target traits. From 2,500 tetraploid wheat accessions obtained through an international collaborative effort, a Global Durum wheat Panel (GDP) of 1,011 genotypes was assembled that captured 94-97% of the original diversity. The GDP consists of a wide representation of Triticum turgidum ssp. durum modern germplasm and landraces, along with a selection of emmer and primitive tetraploid wheats to maximize diversity. GDP accessions were genotyped using the wheat iSelect 90K SNP array. Among modern durum accessions, breeding programs from Italy, France and Central Asia provided the highest level of genetic diversity, with only a moderate decrease in genetic diversity observed across nearly 50 years of breeding (1970-2018). Further, the breeding programs from Europe had the largest sets of unique alleles. LD was lower in the landraces (0.4 Mbp) than in modern germplasm (1.8 Mbp) at r 2 = 0.5. ADMIXTURE analysis of modern germplasm defined a minimum of 13 distinct genetic clusters (k), which could be traced to the breeding program of origin. Chromosome regions putatively subjected to strong selection pressure were identified from fixation index (F st ) and diversity reduction index (DRI) metrics in pairwise comparisons among decades of release and breeding programs. Clusters of putative selection sweeps (PSW) were identified as co-localized with major loci controlling phenology (Ppd and Vrn), plant height (Rht) and quality (gliadins and glutenins), underlining the role of the corresponding genes as driving elements in modern breeding. Public seed availability and deep genetic characterization of the GDP make this collection a unique and ideal resource to identify and map useful genetic diversity at loci of interest to any breeding program

Euphytica / Genomic predictions for Fusarium head blight resistance in a diverse durum wheat panel: an effective incorporation of plant height and heading date as covariates

Selection for multiple traits is a highly challenging task for breeders due to potential unfavorable associations between characters. Fusarium head blight FHB, being one of the most relevant diseases affecting durum wheat frequently shows in this respect an unfavorable correlation with morpho-agronomical traits like plant height (PH) and heading date (HD). In this study, we used a cross-validation scheme to assess the prediction ability of the genomic predictions (GP) for FHB severity relying on genomic best linear unbiased prediction models in a diverse panel of 178 durum wheat lines evaluated across five environments. Additionally, we compared three types of approaches to include HD and PH as covariates into the analysis: (1) correcting FHB severity values before training GP models, (2) tuning the GP model parameters that included multi-trait alternatives, and (3) adjusting the genomic-based predictions by restriction indexes. Models that weighted genomic estimated breeding values (GEBV) by restriction indexes as well as models that predicted FHBms values corrected by regression-based methods were efficient alternatives in diminishing the HD trade-off, nonetheless they were also associated with large reductions in prediction ability for FHB severity. After a simulated round of genomic selection, considering HD as fixed effect in the GP model were the most suitable alternative to select a higher proportion of genotypes moderately resistant with lower-than-average HD and PH estimations. Hence, an appropriate GP model given unfavorable association between characters should combine high predictabilities and adequate reduction of undesired trade-offs.European Union\u2019s Horizon 2020 research and innovation program under the Marie S\u142odowska-Curie Grant Agreement No. 674964 and Deutsche Forschungsgemeinschaft, Grant ID: LO 1816/2-1. Open access funding was provided by University of Natural Resources and Life Sciences Vienna (BOKU

Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat.

Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population