Capitalizing on genebank core collections for rare and novel disease resistance loci to enhance barley resilience.

In the realm of agricultural sustainability, the utilization of plant genetic resources for enhanced disease resistance is paramount. Preservation efforts in genebanks are justified by their potential contributions to future crop improvement. To capitalize on the potential of plant genetic resources, we focused on a barley core collection from the German ex situ genebank and contrasted it with a European elite collection. The phenotypic assessment included 812 plant genetic resources and 298 elites, with a particular emphasis on four disease traits (Puccinia hordei, Blumeria graminis hordei, Ramularia collo-cygni, and Rhynchosporium commune). An integrated genome-wide association study, employing both Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK) and a linear mixed model, was performed to unravel the genetic underpinnings of disease resistance. A total of 932 marker-trait associations were identified and assigned to 49 quantitative trait loci. The accumulation of novel and rare resistance alleles significantly bolstered the overall resistance level in plant genetic resources. Three plant genetic resources donors with high counts of novel/rare alleles and exhibiting exceptional resistance to leaf rust and powdery mildew were identified, offering promise for targeted pre-breeding goals and enhanced resilience in future varieties. Our findings underscore the critical contribution of plant genetic resources to strengthening crop resilience and advancing sustainable agricultural practices.

Genomic predictions to leverage phenotypic data across genebanks.

Genome-wide prediction is a powerful tool in breeding. Initial results suggest that genome-wide approaches are also promising for enhancing the use of the genebank material: predicting the performance of plant genetic resources can unlock their hidden potential and fill the information gap in genebanks across the world and, hence, underpin prebreeding programs. As a proof of concept, we evaluated the power of across-genebank prediction for extensive germplasm collections relying on historical data on flowering/heading date, plant height, and thousand kernel weight of 9,344 barley (Hordeum vulgare L.) plant genetic resources from the German Federal Ex situ Genebank for Agricultural and Horticultural Crops (IPK) and of 1,089 accessions from the International Center for Agriculture Research in the Dry Areas (ICARDA) genebank. Based on prediction abilities for each trait, three scenarios for predictive characterization were compared: 1) a benchmark scenario, where test and training sets only contain ICARDA accessions, 2) across-genebank predictions using IPK as training and ICARDA as test set, and 3) integrated genebank predictions that include IPK with 30% of ICARDA accessions as a training set to predict the rest of ICARDA accessions. Within the population of ICARDA accessions, prediction abilities were low to moderate, which was presumably caused by a limited number of accessions used to train the model. Interestingly, ICARDA prediction abilities were boosted up to ninefold by using training sets composed of IPK plus 30% of ICARDA accessions. Pervasive genotype × environment interactions (GEIs) can become a potential obstacle to train robust genome-wide prediction models across genebanks. This suggests that the potential adverse effect of GEI on prediction ability was counterbalanced by the augmented training set with certain connectivity to the test set. Therefore, across-genebank predictions hold the promise to improve the curation of the world's genebank collections and contribute significantly to the long-term development of traditional genebanks toward biodigital resource centers.

Hybrid Seed Set in Relation with Male Floral Traits, Estimation of Heterosis and Combining Abilities for Yield and Its Components in Wheat (Triticum aestivum L.).

Breeding hybrids with maximum heterosis requires efficient cross-pollination and an improved male sterility system. Renewed efforts have been made to dissect the phenotypic variation and genetic basis of hybrid floral traits, although the potential of tailoring the appropriate flower design on seed setting is less known. To this end, elite wheat genotypes were crossed using a chemical hybridizing agent at different doses. A total of 23 hybrids were developed from a partial diallel design; and planted in an alpha lattice design with their parents at two locations in Morocco, for two years, to evaluate for yield components, heterosis and combining abilities. The 13.5 L ha-1 dose induced a maximum level of sterility (95%) and seed set showed large phenotypic variation and high heritability. In parallel, seed set showed tight correlation with pollen mass (0.97), visual anther extrusion (0.94) and pollen shedding (0.91) (p < 0.001), allowing direct selection of the associated traits. Using the combined data, mid-parent heterosis ranges were -7.64-14.55% for biomass (BM), -8.34-12.51% for thousand kernel weight (TKW) and -5.29-26.65% for grain yield (YLD); while best-parent heterosis showed ranges of -11.18-7.20%, -11.35-11.26% and -8.27-24.04% for BM, TKW and YLD, respectively. The magnitude of general combining ability (GCA) variance was greater than the specific combining ability (SCA) variance suggesting a greater additive gene action for BM, TKW and YLD. The favorable GCA estimates showed a simple method to predict additive effects contributing to high heterosis and thus could be an effective approach for the selection of promising parents in early generations.

Identification of Resistance Sources and Genome-Wide Association Mapping of Septoria Tritici Blotch Resistance in Spring Bread Wheat Germplasm of ICARDA.

Septoria tritici blotch (STB) of wheat, caused by the ascomycete Zymoseptoria tritici (formerly Mycosphaerella graminicola), is one of the most important foliar diseases of wheat. In Morocco, STB is a devastating disease in temperate wheat-growing regions, and the yield losses can exceed up to 50% under favorable conditions. The aims of this study were to identify sources of resistance to STB in Septoria Association Mapping Panel (SAMP), which is composed of 377 advanced breeding lines (ABLs) from spring bread wheat breeding program of ICARDA, and to identify loci associated with resistance to STB at seedling (SRT) as well as at the adult plant (APS) stages using genome-wide association mapping (GWAM). Seedling resistance was evaluated under controlled conditions with two virulent isolates of STB (SAT-2 and 71-R3) from Morocco, whereas adult plant resistance was assessed at two hot spot locations in Morocco (Sidi Allal Tazi, Marchouch) under artificial inoculation with a mixture of STB isolates. At seedling stage, 45 and 32 ABLs were found to be resistant to 71-R3 and SAT-2 isolates of STB, respectively. At adult plant stage, 50 ABLs were found to be resistant at hot spot locations in Morocco. Furthermore, 10 genotypes showed resistance in both locations during two cropping seasons. GWAM was conducted with 9,988 SNP markers using phenotypic data for seedling and the adult plant stage. MLM model was employed in TASSEL 5 (v 5.2.53) using principal component analysis and Kinship Matrix as covariates. The GWAM analysis indicated 14 quantitative trait loci (QTL) at the seedling stage (8 for isolate SAT-2 and 6 for isolate 71-R3), while 23 QTL were detected at the adult plant stage resistance (4 at MCH-17, 16 at SAT-17, and 3 at SAT-18). SRT QTL explained together 33.3% of the phenotypic variance for seedling resistance to STB isolate SAT-2 and 28.3% for 71-R3, respectively. QTL for adult plant stage resistance explained together 13.1, 68.6, and 11.9% of the phenotypic variance for MCH-17, SAT-17, and SAT-18, respectively. Identification of STB-resistant spring bread wheat germplasm in combination with QTL detected both at SRT and APS stage will serve as an important resource in STB resistance breeding efforts.

Genome-Wide Association and Prediction of Male and Female Floral Hybrid Potential Traits in Elite Spring Bread Wheat Genotypes.

Hybrid wheat breeding is one of the most promising technologies for further sustainable yield increases. However, the cleistogamous nature of wheat displays a major bottleneck for a successful hybrid breeding program. Thus, an optimized breeding strategy by developing appropriate parental lines with favorable floral trait combinations is the best way to enhance the outcrossing ability. This study, therefore, aimed to dissect the genetic basis of various floral traits using genome-wide association study (GWAS) and to assess the potential of genome-wide prediction (GP) for anther extrusion (AE), visual anther extrusion (VAE), pollen mass (PM), pollen shedding (PSH), pollen viability (PV), anther length (AL), openness of the flower (OPF), duration of floret opening (DFO) and stigma length. To this end, we employed 196 ICARDA spring bread wheat lines evaluated for three years and genotyped with 10,477 polymorphic SNP. In total, 70 significant markers were identified associated to the various assessed traits at FDR ≤ 0.05 contributing a minor to large proportion of the phenotypic variance (8-26.9%), affecting the traits either positively or negatively. GWAS revealed multi-marker-based associations among AE, VAE, PM, OPF and DFO, most likely linked markers, suggesting a potential genomic region controlling the genetic association of these complex traits. Of these markers, Kukri_rep_c103359_233 and wsnp_Ex_rep_c107911_91350930 deserve particular attention. The consistently significant markers with large effect could be useful for marker-assisted selection. Genomic selection revealed medium to high prediction accuracy ranging between 52% and 92% for the assessed traits with the least and maximum value observed for stigma length and visual anther extrusion, respectively. This indicates the feasibility to implement genomic selection to predict the performance of hybrid floral traits with high reliability.