Hybrid wheat: quantitative genetic parameters and heterosis for quality and rheological traits as well as baking volume.

KEY MESSAGE: Heterosis effects for dough quality and baking volume were close to zero. However, hybrids have a higher grain yield at a given level of bread making quality compared to their parental lines. Bread wheat cultivars have been selected according to numerous quality traits to fulfill the requirements of the bread making industry. These include beside protein content and quality also rheological traits and baking volume. We evaluated 35 male and 73 female lines and 119 of their single-cross hybrids at three different locations for grain yield, protein content, sedimentation value, extensograph traits and baking volume. No significant differences (p < 0.05) were found in the mean comparisons of males, females and hybrids, except for higher grain yield and lower protein content in the hybrids. Mid-parent and better-parent heterosis values were close to zero and slightly negative, respectively, for baking volume and extensograph traits. However, the majority of heterosis values resulted in the finding that hybrids had higher grain yield than lines for a given level of baking volume, sedimentation value or energy value of extensograph. Due to the high correlation with the mid-parent values (r > 0.70), an initial prediction of hybrid performance based on line per se performance for protein content, sedimentation value, most traits of the extensograph and baking volume is possible. The low variance due to specific combining ability effects for most quality traits points toward an additive gene action requires quality selection within both heterotic groups. Consequently, hybrid wheat can combine high grain yield with high bread making quality. However, the future use of wheat hybrids strongly depends on the establishment of a cost-efficient and reliable seed production system.

Association mapping of wheat Fusarium head blight resistance-related regions using a candidate-gene approach and their verification in a biparental population.

KEY MESSAGE: Markers, located in Dicer1 and Ara6 genes, which are likely involved in cross-kingdom RNA trafficking, are associated with FHB resistance in GABI wheat population and were validated in biparental population. Association studies are a common approach to detect marker-trait associations for Fusarium head blight (FHB) resistance in wheat (Triticum aestivum), although verification of detected associations is exceptional. In the present study, candidate-gene association mapping (CG) of genes from silencing and secretory pathways, which may be involved in wheat resistance against FHB and cross-kingdom RNA trafficking, was performed. Fourteen markers, located in nine genes, were tested for association with FHB resistance in 356 lines from the GABI (genome analysis of the biological system of plants) wheat population. Three markers located in the genes Dicer1 and Ara6 were shown to be significantly associated with the studied trait. Verification of this finding was performed using the recombinant inbred lines (RILs) population 'Apache × Biscay', segregating for four of our 14 selected markers. We could show association of the Ara6 marker with plant height as well as association with FHB resistance for three markers located in Rab5-like GTPase gene Ara6 and Dicer1. These results confirmed the trait-marker associations detected also in the CG approach. Gene products of the associated genes are involved in response of the plant to pathogens, plant metabolism and may be involved in cross-kingdom RNA trafficking efficiency. The markers detected in the GABI wheat population, which were also validated in the biparental population, can potentially be used in wheat breeding.

Dissecting the genetics underlying the relationship between protein content and grain yield in a large hybrid wheat population.

KEY MESSAGE: Additive 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.

Identification of QTL hot spots for malting quality in two elite breeding lines with distinct tolerance to abiotic stress.

BACKGROUND: Barley (Hordeum vulgare) is an important crop cultivated across the world. Drought is a major abiotic factor compromising barley yield worldwide, therefore in modern spring barley cultivars superior seed and malting quality characteristics should be combined with reasonable level of drought tolerance. Previously we have identified a number of barley lines demonstrating the superior yield performance under drought conditions. The aim of this work was to perform a QTL analysis of malting quality traits in a doubled haploid (DH) mapping population of two elite barley lines that differ in their reaction pattern to drought stress. RESULTS: A population of DH lines was developed by crossing two drought-tolerant elite breeding lines, Victoriana and Sofiara, exploiting distinct mechanism of drought tolerance, sustaining assimilation vs remobilization. The mapping population was assayed under field conditions at four distinct locations that differed in precipitation rate. DH lines were genotyped with the Illumina 9 K iSelect assay, and linkage map including 1782 polymorphic markers and covering a total map length of 1140 cM was constructed. The result of quantitative trait loci (QTL) analysis showed that majority of the traits were affected by several main effect QTL and/or QTL x environment (QE) interactions. In total, 57, 41, and 5 QTL were associated with yield-related traits, malting quality traits and seed quality traits, respectively. 11 and 29 of mapped QTL explained more than 10 and 5% of phenotypic variation, respectively. In several chromosomal regions co-localization between QTL for various traits were observed. The largest clusters were detected on chromosomes 3H and 4H. CONCLUSIONS: Our QTL mapping results revealed several novel consistent genomic regions controlling malting quality which could be exploited in marker assisted selection. In this context, the complex QTL region on chromosome 3H seems of particular interest, as it harbors several large effect QTL.

Use of genotyping-by-sequencing to determine the genetic structure in the medicinal plant chamomile, and to identify flowering time and alpha-bisabolol associated SNP-loci by genome-wide association mapping.

BACKGROUND: Chamomile (Matricaria recutita L.) has a long history of use in herbal medicine with various applications, and the flower heads contain numerous secondary metabolites which are medicinally active. In the major crop plants, next generation sequencing (NGS) approaches are intensely applied to exploit genetic resources, to develop genomic resources and to enhance breeding. Here, genotyping-by-sequencing (GBS) has been used in the non-model medicinal plant chamomile to evaluate the genetic structure of the cultivated varieties/populations, and to perform genome wide association study (GWAS) focusing on genes with large effect on flowering time and the medicinally important alpha-bisabolol content. RESULTS: GBS analysis allowed the identification of 6495 high-quality SNP-markers in our panel of 91 M. recutita plants from 33 origins (2-4 genotypes each) and 4 M. discoidea plants as outgroup, grown in the greenhouse in Gatersleben, Germany. M. recutita proved to be clearly distinct from the outgroup, as was demonstrated by different cluster and principal coordinate analyses using the SNP-markers. Chamomile genotypes from the same origin were mostly genetically similar. Model-based cluster analysis revealed one large group of tetraploid genotypes with low genetic differentiation including 39 plants from 14 origins. Tetraploids tended to display lower genetic diversity than diploids, probably reflecting their origin by artificial polyploidisation from only a limited set of genetic backgrounds. Analyses of flowering time demonstrated that diploids generally flowered earlier than tetraploids, and the analysis of alpha-bisabolol identified several tetraploid genotypes with a high content. GWAS identified highly significant (P < 0.01) SNPs for flowering time (9) and alpha-bisabolol (71). One sequence harbouring SNPs associated with flowering time was described to play a role in self-pollination in Arabidopsis thaliana, whereas four sequences harbouring SNPs associated with alpha-bisabolol were identified to be involved in plant biotic and abiotic stress response in various plants species. CONCLUSIONS: The first genomic resource for future applications to enhance breeding in chamomile was created, andanalyses of diversity will facilitate the exploitation of these genetic resources. The GWAS data pave the way for future research towards the genetics underlying important traits in chamomile, the identification of marker-trait associations, and development of reliable markers for practical breeding.

Genome-metabolite associations revealed low heritability, high genetic complexity, and causal relations for leaf metabolites in winter wheat (Triticum aestivum).

We investigated associations between the metabolic phenotype, consisting of quantitative data of 76 metabolites from 135 contrasting winter wheat (Triticum aestivum) lines, and 17 372 single nucleotide polymorphism (SNP) markers. Metabolite profiles were generated from flag leaves of plants from three different environments, with average repeatabilities of 0.5-0.6. The average heritability of 0.25 was unaffected by the heading date. Correlations among metabolites reflected their functional grouping, highlighting the strict coordination of various routes of the citric acid cycle. Genome-wide association studies identified significant associations for six metabolic traits, namely oxalic acid, ornithine, L-arginine, pentose alcohol III, L-tyrosine, and a sugar oligomer (oligo II), with between one and 17 associated SNPs. Notable associations with genes regulating transcription or translation explained between 2.8% and 32.5% of the genotypic variance (pG). Further candidate genes comprised metabolite carriers (pG 32.5-38.1%), regulatory proteins (pG 0.3-11.1%), and metabolic enzymes (pG 2.5-32.5%). The combinatorial use of genomic and metabolic data to construct partially directed networks revealed causal inferences in the correlated metabolite traits and associated SNPs. The evaluated causal relationships will provide a basis for predicting the effects of genetic interferences on groups of correlated metabolic traits, and thus on specific metabolic phenotypes.

Efficient strategies to assess yield stability in winter wheat.

KEY MESSAGE: Selecting contrasting environments allows decreasing phenotyping intensity but still maintaining high accuracy to assess yield stability. Improving yield stability of wheat varieties is important to cope with enhanced abiotic stresses caused by climate change. The objective of our study was to (1) develop and implement an improved heritability estimate to examine the required scale of phenotyping for assessing yield stability in wheat, (2) compare yield performance and yield stability of wheat hybrids and inbred lines, (3) investigate the association of agronomic traits with yield stability, and (4) explore the possibility of selecting subsets of environments allowing to portray large proportion of the variation of yield stability. Our study is based on phenotypic data from five series of official winter wheat registration trials in Germany each including 119-132 genotypes evaluated in up to 50 environments. Our findings suggested that phenotyping in at least 40 environments is required to reliably estimate yield stability to guarantee heritability estimates above 0.7. Contrasting the yield stability of hybrids versus lines revealed no significant differences. Absence of stable associations between yield stability and further agronomic traits suggested low potential of indirect selection to improve yield stability. Selecting posteriori contrasting environments based on the genotype-by-environment interaction effects allowed decreasing phenotyping intensity, but still maintaining high accuracy to assess yield stability. The huge potential of the developed strategy to select contrasting and informative environments has to be validated as a next step in an a priori scenario based on genotype-by-location interaction effects.

Extracting genotype information of Arabidopsis thaliana recombinant inbred lines from transcript profiles established with high-density oligonucleotide arrays.

KEY MESSAGE: Polymorphic probes identified via a sequence-based approach are suitable to infer the genotypes of recombinant inbred lines from hybridisation intensities of GeneChip ® transcript profiling experiments. The sequences of the probes of the ATH1 GeneChip® exactly match transcript sequences of the Arabidopsis thaliana reference genome Col-0, whereas nucleotide differences and/or insertions/deletions may be observed for transcripts of other A. thaliana accessions. Individual probes of the GeneChip® that show sequence polymorphisms between different A. thaliana accessions may serve as single-feature polymorphism (SFP) markers, provided that the sequence changes cause differences in hybridisation intensity for the accessions of interest. A sequence-based approach identified features on the high-density oligonucleotide array that showed sequence polymorphisms between A. thaliana accessions Col-0 and C24. Hybridisation intensities of polymorphic probes were extracted from genome-wide transcript profiles of Col-0/C24 and C24/Col-0 recombinant inbred lines and assessed after standardisation via sliding window analyses to identify SFP markers. The genotypes of the recombinant inbred lines were determined with the SFP markers and the resulting data were integrated with information, which had been established previously with single nucleotide polymorphism and insertion/deletion markers, to enrich the linkage map of the Col-0/C24 and C24/Col-0 recombinant inbred populations. Congruence between the molecular marker map and the sequence maps of the A. thaliana Col-0 chromosomes proved the reliability of the genotype information which was deduced from the transcript profiles of the Col-0/C24 and C24/Col-0 recombinant inbred lines.

Modelling the genetic architecture of flowering time control in barley through nested association mapping.

BACKGROUND: Barley, globally the fourth most important cereal, provides food and beverages for humans and feed for animal husbandry. Maximizing grain yield under varying climate conditions largely depends on the optimal timing of flowering. Therefore, regulation of flowering time is of extraordinary importance to meet future food and feed demands. We developed the first barley nested association mapping (NAM) population, HEB-25, by crossing 25 wild barleys with one elite barley cultivar, and used it to dissect the genetic architecture of flowering time. RESULTS: Upon cultivation of 1,420 lines in multi-field trials and applying a genome-wide association study, eight major quantitative trait loci (QTL) were identified as main determinants to control flowering time in barley. These QTL accounted for 64% of the cross-validated proportion of explained genotypic variance (pG). The strongest single QTL effect corresponded to the known photoperiod response gene Ppd-H1. After sequencing the causative part of Ppd-H1, we differentiated twelve haplotypes in HEB-25, whereof the strongest exotic haplotype accelerated flowering time by 11 days compared to the elite barley haplotype. Applying a whole genome prediction model including main effects and epistatic interactions allowed predicting flowering time with an unmatched accuracy of 77% of cross-validated pG. CONCLUSIONS: The elaborated causal models represent a fundamental step to explain flowering time in barley. In addition, our study confirms that the exotic biodiversity present in HEB-25 is a valuable toolbox to dissect the genetic architecture of important agronomic traits and to replenish the elite barley breeding pool with favorable, trait-improving exotic alleles.

Yield performance and stability of CMS-based triticale hybrids.

KEY MESSAGE: CMS-based triticale hybrids showed only marginal midparent heterosis for grain yield and lower dynamic yield stability compared to inbred lines. Hybrids of triticale (×Triticosecale Wittmack) are expected to possess outstanding yield performance and increased dynamic yield stability. The objectives of the present study were to (1) examine the optimum choice of the biometrical model to compare yield stability of hybrids versus lines, (2) investigate whether hybrids exhibit a more pronounced grain yield performance and yield stability, and (3) study optimal strategies to predict yield stability of hybrids. Thirteen female and seven male parental lines and their 91 factorial hybrids as well as 30 commercial lines were evaluated for grain yield in up to 20 environments. Hybrids were produced using a cytoplasmic male sterility (CMS)-inducing cytoplasm that originated from Triticumtimopheevii Zhuk. We found that the choice of the biometrical model can cause contrasting results and concluded that a group-by-environment interaction term should be added to the model when estimating stability variance of hybrids and lines. midparent heterosis for grain yield was on average 3 % with a range from -15.0 to 11.5 %. No hybrid outperformed the best inbred line. Hybrids had, on average, lower dynamic yield stability compared to the inbred lines. Grain yield performance of hybrids could be predicted based on midparent values and general combining ability (GCA)-predicted values. In contrast, stability variance of hybrids could be predicted only based on GCA-predicted values. We speculated that negative effects of the used CMS cytoplasm might be the reason for the low performance and yield stability of the hybrids. For this purpose a detailed study on the reasons for the drawback of the currently existing CMS system in triticale is urgently required comprising also the search of potentially alternative hybridization systems.

Exploitation of yield stability in barley.

KEY MESSAGE: Analyses of registration trials of winter barley suggested that yield and yield stability can be enhanced by developing hybrid instead of line varieties. Yield stability is central to cope with the expected increased frequency of extreme weather conditions. The objectives of our study were to (1) examine the dimensioning of field trials needed to precisely portray yield stability of individual winter barley (Hordeum vulgare L.) genotypes, (2) compare grain yield performance and yield stability of two-rowed lines with those of six-rowed lines and hybrids, and (3) investigate the association of various agronomic traits with yield stability. Static and dynamic yield stability as well as grain yield performance was determined in five series of 3-year registration trials of winter barley in Germany. Each series included 4 or 5 six-rowed hybrids, 40-46 six-rowed inbred lines, as well as 42-49 two-rowed inbred lines. The genotypes were evaluated in 10-45 environments, i.e. year-by-location combinations. We found that precise assessment of yield stability of individual genotypes requires phenotyping in at least 40 test environments. Therefore, selection for yield stability is not usually feasible since the required number of test environments exceeds the common capacity of barley breeding programs. Also, indirect improvement of yield stability by means of agronomic traits seemed not possible since there was no constant association of any agronomic trait with yield stability. We found that compared with line varieties, hybrids showed on average higher grain yield performance combined with high dynamic yield stability. In conclusion, breeding hybrid instead of line varieties may be a promising way to develop high yielding and yield stable varieties.

Yield stability of hybrids versus lines in wheat, barley, and triticale.

KEY MESSAGE: We present experimental data for wheat, barley, and triticale suggesting that hybrids manifest on average higher yield stability than inbred lines. Yield stability is assumed to be higher for hybrids than for inbred lines, but experimental data proving this hypothesis is scarce for autogamous cereals. We used multi-location grain yield trials and compared the yield stability of hybrids versus lines for wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), and triticale (×Triticosecale Wittmack). Our study comprised three phenotypic data sets of 1,749 wheat, 96 barley, and 130 triticale genotypes, which were evaluated for grain yield in up to five contrasting locations. Yield stability of the group of hybrids was compared with that of the group of inbred lines estimating the stability variance. For all three crops we observed a significantly (P < 0.05) higher yield stability of hybrids compared to lines. The enhanced yield stability of hybrids as compared to lines represents a major step forward, facilitating coping with the increasing abiotic stress expected from the predicted climate change.

Hybrid wheat: quantitative genetic parameters and consequences for the design of breeding programs.

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.

Hybrid breeding in autogamous cereals.

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.

Capturing Wheat Phenotypes at the Genome Level.

Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world's most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public-private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.

Genome-wide association mapping reveals epistasis and genetic interaction networks in sugar beet.

Epistasis is defined as interactions between alleles of two or more genetic loci. Detection of epistatic interactions is the key to understand the genetic architecture and gene networks underlying complex traits. Here, we examined the extent of epistasis for seven quantitative traits with an association mapping approach in a large population of elite sugar beet lines. We found that correction for population stratification is required and that in terms of reducing the false-positive rate the mixed model approach including the kinship matrix performed best. In genome-wide scans, we detected both main effects and epistatic QTL. For physiological traits, the detected digenic and higher-order epistasis explained a considerable proportion of the genotypic variance. We illustrate that the identified epistatic interactions define comprehensive genetic networks, which may serve as starting points towards a systems-oriented approach to understand the regulation of complex traits.

Genome-wide association mapping of agronomic traits in sugar beet.

Recent results indicate that association mapping in populations from applied plant breeding is a powerful tool to detect QTL which are of direct relevance for breeding. The focus of this study was to unravel the genetic architecture of six agronomic traits in sugar beet. To this end, we employed an association mapping approach, based on a very large population of 924 elite sugar beet lines from applied plant breeding, fingerprinted with 677 single nucleotide polymorphism (SNP) markers covering the entire genome. We show that in this population linkage disequilibrium decays within a short genetic distance and is sufficient for the detection of QTL with a large effect size. To increase the QTL detection power and the mapping resolution a much higher number of SNPs is required. We found that for QTL detection, the mixed model including only the kinship matrix performed best, even in the presence of a considerable population structure. In genome-wide scans, main effect QTL and epistatic QTL were detected for all six traits. Our full two-dimensional epistasis scan revealed that for complex traits there appear to be epistatic master regulators, loci which are involved in a large number of epistatic interactions throughout the genome.

Association mapping in an elite maize breeding population.

Association mapping (AM) is a powerful approach to dissect the genetic architecture of quantitative traits. The main goal of our study was to empirically compare several statistical methods of AM using data of an elite maize breeding program with respect to QTL detection power and possibility to correct for population stratification. These models were based on the inclusion of cofactors (Model A), cofactors and population effect (Model B), and SNP effects nested within populations (Model C). A total of 930 testcross progenies of an elite maize breeding population were field-evaluated for grain yield and grain moisture in multi-location trials and fingerprinted with 425 SNP markers. For grain yield, population stratification was effectively controlled by Model A. For grain moisture with a high ratio of variance among versus within populations, Model B should be applied in order to avoid potential false positives. Model C revealed large differences among allele substitution effects for trait-associated SNPs across multiple plant breeding populations. This heterogeneous SNP allele substitution effects have a severe impact for genomic selection studies, where SNP effects are often assumed to be independent of the genetic background.

Efficiency of a Seedling Phenotyping Strategy to Support European Wheat Breeding Focusing on Leaf Rust Resistance.

Leaf rust resistance is of high importance for a sustainable European wheat production. The expression of known resistance genes starts at different developmental stages of wheat. Breeding for resistance can be supported by a fast, precise, and resource-saving phenotyping. The examination of detached leaf assays of juvenile plants inoculated under controlled conditions and phenotyped by a robotic- and computer-based, high-throughput system is a promising approach in this respect. Within this study, the validation of the phenotyping workflow was conducted based on a winter wheat set derived from Central Europe and examined at different plant developmental stages. Moderate Pearson correlations of 0.38-0.45 comparing leaf rust resistance of juvenile and adult plants were calculated and may be mainly due to different environmental conditions. Specially, the infection under controlled conditions was limited by the application of a single rust race at only one time point. Our results suggest that the diversification with respect to the applied rust race spectrum is promising to increase the consistency of detached leaf assays and the transferability of its results to the field.

Reciprocal Recurrent Genomic Selection Is Impacted by Genotype-by-Environment Interactions.

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 F2 (60 out of 629 plants) and the F5 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.