Hybrid breeding in autogamous cereals has a long history of attempts with moderate success. There is a vast amount of literature investigating the potential problems and solutions, but until now, market share of hybrids is still a niche compared to line varieties. Our aim was to summarize the status quo of hybrid breeding efforts for the autogamous cereals wheat, rice, barley, and triticale. Furthermore, the research needs for a successful hybrid breeding in autogamous cereals are intensively discussed. To our opinion, the basic requirements for a successful hybrid breeding in autogamous cereals are fulfilled. Nevertheless, optimization of the existing hybridization systems is urgently required and should be coupled with the development of clear male and female pool concepts. We present a quantitative genetic framework as a first step to compare selection gain of hybrid versus line breeding. The lack of precise empirical estimates of relevant quantitative genetic parameters, however, is currently the major bottleneck for a robust evaluation of the potential of hybrid breeding in autogamous cereals.

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.hybrid breeding | genomic prediction | heterotic pattern

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.

Increases in the yield of wheat during the Green Revolution of the late 20 century were achieved through the introduction of Reduced height (Rht) dwarfing genes. The Rht-B1 and Rht-D1 loci ensured short stature by limiting the response to the growth-promoting hormone gibberellin, and are now widespread through international breeding programs. Despite this advantage, interference with the plant's response to gibberellin also triggers adverse effects for a range of important agronomic traits, and consequently modern Green Revolution genes are urgently required. In this study, we revisited the genetic control of wheat height using an association mapping approach and a large panel of 1110 worldwide winter wheat cultivars. This led to the identification of a major Rht locus on chromosome 6A, Rht24, which substantially reduces plant height alone as well as in combination with Rht-1b alleles. Remarkably, behind Rht-D1, Rht24 was the second most important locus for reduced height, explaining 15.0% of the genotypic variance and exerting an allele substitution effect of -8.8 cm. Unlike the two Rht-1b alleles, plants carrying Rht24 remain sensitive to gibberellic acid treatment. Rht24 appears in breeding programs from all countries of origin investigated, with increased frequency over the last decades, indicating that wheat breeders have actively selected for this locus. Taken together, this study reveals Rht24 as an important Rht gene of commercial relevance in worldwide wheat breeding.

Flowering time is an important trait in wheat breeding as it affects adaptation and yield potential. The aim of this study was to investigate the genetic architecture of flowering time in European winter bread wheat cultivars. To this end a population of 410 winter wheat varieties was evaluated in multi-location field trials and genotyped by a genotyping-by-sequencing approach and candidate gene markers. Our analyses revealed that the photoperiod regulator Ppd-D1 is the major factor affecting flowering time in this germplasm set, explaining 58% of the genotypic variance. Copy number variation at the Ppd-B1 locus was present but explains only 3.2% and thus a comparably small proportion of genotypic variance. By contrast, the plant height loci Rht-B1 and Rht-D1 had no effect on flowering time. The genome-wide scan identified six QTL which each explain only a small proportion of genotypic variance and in addition we identified a number of epistatic QTL, also with small effects. Taken together, our results show that flowering time in European winter bread wheat cultivars is mainly controlled by Ppd-D1 while the fine tuning to local climatic conditions is achieved through Ppd-B1 copy number variation and a larger number of QTL with small effects.

Based on data from field trials with a large collection of 135 elite winter wheat inbred lines and 1604 F 1 hybrids derived from them, we compared the accuracy of prediction of marker-assisted selection and current genomic selection approaches for the model traits heading time and plant height in a cross-validation approach. For heading time, the high accuracy seen with marker-assisted selection severely dropped with genomic selection approaches RR-BLUP (ridge regression best linear unbiased prediction) and BayesCp, whereas for plant height, accuracy was low with marker-assisted selection as well as RR-BLUP and BayesCp. Differences in the linkage disequilibrium structure of the functional and single-nucleotide polymorphism markers relevant for the two traits were identified in a simulation study as a likely explanation for the different trends in accuracies of prediction. A new genomic selection approach, weighted best linear unbiased prediction (W-BLUP), designed to treat the effects of known functional markers more appropriately, proved to increase the accuracy of prediction for both traits and thus closes the gap between marker-assisted and genomic selection.

This study revealed a complex genetic architecture of male floral traits in wheat, and Rht-D1 was identified as the only major QTL. Genome-wide prediction approaches but also phenotypic recurrent selection appear promising to increase outcrossing ability required for hybrid wheat seed production. Hybrid wheat breeding is a promising approach to increase grain yield and yield stability. However, the identification of lines with favorable male floral characteristics required for hybrid seed production currently poses a severe bottleneck for hybrid wheat breeding. This study therefore aimed to unravel the genetic architecture of floral traits and to assess the potential of genomic approaches to accelerate their improvement. To this end, we employed a panel of 209 diverse winter wheat lines assessed for male floral traits and genotyped with genome-wide markers as well as for Rht-B1 and Rht-D1. We found the highest proportion of explained genotypic variance for the Rht-D1 locus (11-24 %), for which the dwarfing allele Rht-D1b had a negative effect on anther extrusion, visual anther extrusion and pollen mass. The genome-wide scan detected only few QTL with small or medium effects, indicating a complex genetic architecture. Consequently, marker-assisted selection yielded only moderate prediction abilities (0.44-0.63), mainly relying on Rht-D1. Genomic selection based on weighted ridge-regression best linear unbiased prediction achieved higher prediction abilities of up to 0.70 for anther extrusion. In conclusion, recurrent phenotypic selection appears most cost-effective for the initial improvement of floral traits in wheat, while genome-wide prediction approaches may be worthwhile when complete marker profiles are already available in a hybrid wheat breeding program.

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.