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

Optimum allocation of resources for QTL detection using a nested association mapping strategy in maize

In quantitative trait locus (QTL) mapping studies, it is mandatory that the available financial resources are spent in such a way that the power for detection of QTL is maximized. The objective of this study was to optimize for three different fixed budgets the power of QTL detection 1 − β* in recombinant inbred line (RIL) populations derived from a nested design by varying (1) the genetic complexity of the trait, (2) the costs for developing, genotyping, and phenotyping RILs, (3) the total number of RILs, and (4) the number of environments and replications per environment used for phenotyping. Our computer simulations were based on empirical data of 653 single nucleotide polymorphism markers of 26 diverse maize inbred lines which were selected on the basis of 100 simple sequence repeat markers out of a worldwide sample of 260 maize inbreds to capture the maximum genetic diversity. For the standard scenario of costs, the optimum number of test environments (Eopt) ranged across the examined total budgets from 7 to 19 in the scenarios with 25 QTL. In comparison, the Eopt values observed for the scenarios with 50 and 100 QTL were slightly higher. Our finding of differences in 1 − β* estimates between experiments with optimally and sub-optimally allocated resources illustrated the potential to improve the power for QTL detection without increasing the total resources necessary for a QTL mapping experiment. Furthermore, the results of our study indicated that also in studies using the latest genomics tools to dissect quantitative traits, it is required to evaluate the individuals of the mapping population in a high number of environments with a high number of replications per environment

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

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