Explore the vast range of titles available.

The great efforts spent in the maintenance of past diversity in genebanks are rationalized by the potential role of plant genetic resources (PGR) in future crop improvement—a concept whose practical implementation has fallen short of expectations. Here, we implement a genomics-informed prebreeding strategy for wheat improvement that does not discriminate against nonadapted germplasm. We collect and analyze dense genetic profiles for a large winter wheat collection and evaluate grain yield and resistance to yellow rust (YR) in bespoke core sets. Breeders already profit from wild introgressions but PGR still offer useful, yet unused, diversity. Potential donors of resistance sources not yet deployed in breeding were detected, while the prebreeding contribution of PGR to yield was estimated through ‘Elite × PGR’ F 1 crosses. Genomic prediction within and across genebanks identified the best parents to be used in crosses with elite cultivars whose advanced progenies can outyield current wheat varieties in multiple field trials. Implementation of a genomics-informed prebreeding strategy in a global winter wheat collection enhances the use of genebank accessions and uncovers the value of genetic resources for wheat improvement.

Hybrid breeding promises to boost yield and stability. The single most important element in implementing hybrid breeding is the recognition of a high-yielding heterotic pattern.We have developed a three-step strategy for identifying heterotic patterns for hybrid breeding comprising the following elements. First, the full hybrid performance matrix is compiled using genomic prediction. Second, a high-yielding heterotic pattern is searched based on a developed simulated annealing algorithm. Third, the long-term success of the identified heterotic pattern is assessed by estimating the usefulness, selection limit, and representativeness of the heterotic pattern with respect to a defined base population. This three-step approach was successfully implemented and evaluated using a phenotypic and genomic wheat dataset comprising 1,604 hybrids and their 135 parents. Integration of metabolomic-based prediction was not as powerful as genomic prediction. We show that hybrid wheat breeding based on the identified heterotic pattern can boost grain yield through the exploitation of heterosis and enhance recurrent selection gain. Our strategy represents a key step forward in hybrid breeding and is relevant for self-pollinating crops, which are currently shifting from pure-line to high-yielding and resilient hybrid varieties.

KEY MESSAGE : Commercial heterosis for grain yield is present in hybrid wheat but long-term competiveness of hybrid versus line breeding depends on the development of heterotic groups to improve hybrid prediction. Detailed knowledge of the amount of heterosis and quantitative genetic parameters are of paramount importance to assess the potential of hybrid breeding. Our objectives were to (1) examine the extent of midparent, better-parent and commercial heterosis in a vast population of 1,604 wheat (Triticum aestivum L.) hybrids and their parental elite inbred lines and (2) discuss the consequences of relevant quantitative parameters for the design of hybrid wheat breeding programs. Fifteen male lines were crossed in a factorial mating design with 120 female lines, resulting in 1,604 of the 1,800 potential single-cross hybrid combinations. The hybrids, their parents, and ten commercial wheat varieties were evaluated in multi-location field experiments for grain yield, plant height, heading time and susceptibility to frost, lodging, septoria tritici blotch, yellow rust, leaf rust, and powdery mildew at up to five locations. We observed that hybrids were superior to the mean of their parents for grain yield (10.7 %) and susceptibility to frost (−7.2 %), leaf rust (−8.4 %) and septoria tritici blotch (−9.3 %). Moreover, 69 hybrids significantly (P < 0.05) outyielded the best commercial inbred line variety underlining the potential of hybrid wheat breeding. The estimated quantitative genetic parameters suggest that the establishment of reciprocal recurrent selection programs is pivotal for a successful long-term hybrid wheat breeding.

Key messageAdditive and dominance effect QTL for grain yield and protein content display antagonistic pleiotropic effects, making genomic selection based on the index grain protein deviation a promising method to alleviate the negative correlation between these traits in wheat breeding.Grain yield and quality-related traits such as protein content and sedimentation volume are key traits in wheat breeding. In this study, we used a large population of 1604 hybrids and their 135 parental components to investigate the genetics and metabolomics underlying the negative relationship of grain yield and quality, and evaluated approaches for their joint improvement. We identified a total of nine trait-associated metabolites and show that prediction using genomic data alone resulted in the highest prediction ability for all traits. We dissected the genetic architecture of grain yield and quality-determining traits and show results of the first mapping of the derived trait grain protein deviation. Further, we provide a genetic analysis of the antagonistic relation of grain yield and protein content and dissect the mode of gene action (pleiotropy vs linkage) of identified QTL. Lastly, we demonstrate that the composition of the training set for genomic prediction is crucial when considering different quality classes in wheat breeding.

Wheat is one of the most important staple crops worldwide. Wheat breeding mainly focused on improving agronomy and techno-functionality for bread or pasta production, but nutrient content is becoming more important to fight malnutrition. We therefore investigated 282 bread wheat cultivars from seven decades of wheat breeding in Central Europe on 63 different traits related to agronomy, quality and nutrients in multiple field environments. Our results showed that wheat breeding has tremendously increased grain yield, resistance against diseases and lodging as well as baking quality across last decades. By contrast, mineral content slightly decreased without selection on it, probably due to its negative correlation with grain yield. The significant genetic variances determined for almost all traits show the potential for further improvement but significant negative correlations among grain yield and baking quality as well as grain yield and mineral content complicate their combined improvement. Thus, compromises in improvement of these traits are necessary to feed a growing global population.

Plant genetic resources (PGR) stored at genebanks are humanity’s crop diversity savings for the future. Information on PGR contrasted with modern cultivars is key to select PGR parents for pre-breeding. Genotyping-by-sequencing was performed for 7,745 winter wheat PGR samples from the German Federal ex situ genebank at IPK Gatersleben and for 325 modern cultivars. Whole-genome shotgun sequencing was carried out for 446 diverse PGR samples and 322 modern cultivars and lines. In 19 field trials, 7,683 PGR and 232 elite cultivars were characterized for resistance to yellow rust - one of the major threats to wheat worldwide. Yield breeding values of 707 PGR were estimated using hybrid crosses with 36 cultivars - an approach that reduces the lack of agronomic adaptation of PGR and provides better estimates of their contribution to yield breeding. Cross-validations support the interoperability between genomic and phenotypic data. The here presented data are a stepping stone to unlock the functional variation of PGR for European pre-breeding and are the basis for future breeding and research activities.Measurement(s)genome sequence • wheat stripe rust disease resistance • grain yield traitTechnology Type(s)genotyping-by-sequencing • whole genome shotgun sequencing • Manual scoring in natural and artificially infected fields • Combine harvesterFactor Type(s)genotype • locationSample Characteristic - OrganismTriticum aestivumSample Characteristic - Environmentagricultural fieldSample Characteristic - LocationGermany

Reciprocal recurrent genomic selection is a breeding strategy aimed at improving the hybrid performance of two base populations. It promises to significantly advance hybrid breeding in wheat. Against this backdrop, the main objective of this study was to empirically investigate the potential and limitations of reciprocal recurrent genomic selection. Genome-wide predictive equations were developed using genomic and phenotypic data from a comprehensive population of 1,604 single crosses between 120 female and 15 male wheat lines. Twenty superior female lines were selected for initiation of the reciprocal recurrent genomic selection program. Focusing on the female pool, one cycle was performed with genomic selection steps at the F 2 (60 out of 629 plants) and the F 5 stage (49 out of 382 plants). Selection gain for grain yield was evaluated at six locations. Analyses of the phenotypic data showed pronounced genotype-by-environment interactions with two environments that formed an outgroup compared to the environments used for the genome-wide prediction equations. Removing these two environments for further analysis resulted in a selection gain of 1.0 dt ha −1 compared to the hybrids of the original 20 parental lines. This underscores the potential of reciprocal recurrent genomic selection to promote hybrid wheat breeding, but also highlights the need to develop robust genome-wide predictive equations.

Key message Stem rust resistance was mainly based on a few, already known resistance genes; for yellow rust resistance there was a combination of designated genes and minor QTLs. Yellow rust (YR) caused by Puccinia striiformis f. sp. tritici ( Pst ) and stem rust (SR) caused by Puccinia graminis f. sp. tritici ( Pgt ) are among the most damaging wheat diseases. Although, yellow rust has occurred regularly in Europe since the advent of the Warrior race in 2011, damaging stem rust epidemics are still unusual. We analyzed the resistance of seven segregating populations at the adult growth stage with the parents being selected for YR and SR resistances across three to six environments (location–year combinations) following inoculation with defined Pst and Pgt races. In total, 600 progenies were phenotyped and 563 were genotyped with a 25k SNP array. For SR resistance, three major resistance genes ( Sr24 , Sr31 , Sr38/Yr17 ) were detected in different combinations. Additional QTLs provided much smaller effects except for a gene on chromosome 4B that explained much of the genetic variance. For YR resistance, ten loci with highly varying percentages of explained genetic variance (pG, 6–99%) were mapped. Our results imply that introgression of new SR resistances will be necessary for breeding future rust resistant cultivars, whereas YR resistance can be achieved by genomic selection of many of the detected QTLs.

Summary A resistance gene atlas is an integral component of the breeder’s arsenal in the fight against evolving pathogens. Thanks to high‐throughput sequencing, catalogues of resistance genes can be assembled even in crop species with large and polyploid genomes. Here, we report on capture sequencing and assembly of resistance gene homologs in a diversity panel of 907 winter wheat genotypes comprising ex situ genebank accessions and current elite cultivars. In addition, we use accurate long‐read sequencing and chromosome conformation capture sequencing to construct a chromosome‐scale genome sequence assembly of cv. Attraktion, an elite variety representative of European winter wheat. We illustrate the value of our resource for breeders and geneticists by (i) comparing the resistance gene complements in plant genetic resources and elite varieties and (ii) conducting genome‐wide associations scans (GWAS) for the fungal diseases yellow rust and leaf rust using reference‐based and reference‐free GWAS approaches. The gene content under GWAS peaks was scrutinized in the assembly of cv. Attraktion.

Modern genomics approaches rely on the availability of high-throughput and high-density genotyping platforms. A major breakthrough in wheat genotyping was the development of an SNP array. In this study, we used a diverse panel of 172 elite European winter wheat lines to evaluate the utility of the SNP array for genomic analyses in wheat germplasm derived from breeding programs. We investigated population structure and genetic relatedness and found that the results obtained with SNP and SSR markers differ. This suggests that additional research is required to determine the optimum approach for the investigation of population structure and kinship. Our analysis of linkage disequilibrium (LD) showed that LD decays within approximately 5–10 cM. Moreover, we found that LD is variable along chromosomes. Our results suggest that the number of SNPs needs to be increased further to obtain a higher coverage of the chromosomes. Taken together, SNPs can be a valuable tool for genomics approaches and for a knowledge-based improvement of wheat.