Generation of high oleic acid sunflower lines using gamma radiation mutagenesis and high-throughput fatty acid profiling.

Sunflower (Helianthus annuus L.) is the second most important oil seed crop in Europe. The seeds are used as confection seeds and, more importantly, to generate an edible vegetable oil, which in normal varieties is rich in the polyunsaturated fatty acid linoleic acid. Linoleic acid is biosynthesized from oleic acid through activity of the oleate desaturase FATTY ACID DESATURASE 2 (FAD2), which in seeds is encoded by FAD2-1, a gene that's present in single copy in sunflowers. Defective FAD2-1 expression enriches oleic acid, yielding the high oleic (HO) acid trait, which is of great interest in oil seed crops, since HO oil bears benefits for both food and non-food applications. Chemical mutagenesis has previously been used to generate sunflower mutants with reduced FAD2-1 expression and here it was aimed to produce further genetic material in which FAD2-1 activity is lost and the HO trait is stably expressed. For this purpose, a sunflower mutant population was created using gamma irradiation and screened for fad2-1 mutants with a newly developed HPLC-based fatty-acid profiling system that's suitable for high-throughput analyses. With this approach fad2-1 knock-out mutants could be isolated, which stably hyper-accumulate oleic acid in concentrations of 85-90% of the total fatty acid pool. The genetic nature of these new sunflower lines was characterized and will facilitate marker development, for the rapid introgression of the trait into elite sunflower breeding material.

Do We Need to Breed for Regional Adaptation in Soybean?-Evaluation of Genotype-by-Location Interaction and Trait Stability of Soybean in Germany.

Soybean is a crop in high demand, in particular as a crucial source of plant protein. As a short-day plant, soybean is sensitive to the latitude of the growing site. Consequently, varieties that are well adapted to higher latitudes are required to expand the cultivation. In this study, we employed 50 soybean genotypes to perform a multi-location trial at seven locations across Germany in 2021. Two environmental target regions were determined following the latitude of the locations. Adaptation and trait stability of seed yield and protein content across all locations were evaluated using Genotype plus Genotype-by-Environment (GGE) biplots and Shukla's stability variance. We found a moderate level of crossing-over type genotype-by-location interaction across all locations. Within the environmental target regions, the genotype-by-location interaction could be minimised. Despite the positive correlation (R = 0.59) of seed yield between the environmental target regions and the same best-performing genotype, the genotype rankings differed in part substantially. In conclusion, we found that soybean can be grown at a wide range of latitudes across Germany. However, the performance of genotypes differed between the northern and southern locations, with an 18.8% higher mean yield in the south. This in combination with the observed rank changes of high-performing genotypes between both environmental target regions suggests that selection targeted towards environments in northern Germany could improve soybean breeding for those higher latitude regions.

The genetic architecture of soybean photothermal adaptation to high latitudes.

Soybean is a major plant protein source for both human food and animal feed, but to meet global demands as well as a trend towards regional production, soybean cultivation needs to be expanded to higher latitudes. In this study, we developed a large diversity panel consisting of 1503 early-maturing soybean lines and used genome-wide association mapping to dissect the genetic architecture underlying two crucial adaptation traits, flowering time and maturity. This revealed several known maturity loci, E1, E2, E3, and E4, and the growth habit locus Dt2 as causal candidate loci, and also a novel putative causal locus, GmFRL1, encoding a homolog of the vernalization pathway gene FRIGIDA-like 1. In addition, the scan for quantitative trait locus (QTL)-by-environment interactions identified GmAPETALA1d as a candidate gene for a QTL with environment-dependent reversed allelic effects. The polymorphisms of these candidate genes were identified using whole-genome resequencing data of 338 soybeans, which also revealed a novel E4 variant, e4-par, carried by 11 lines, with nine of them originating from Central Europe. Collectively, our results illustrate how combinations of QTL and their interactions with the environment facilitate the photothermal adaptation of soybean to regions far beyond its center of origin.

Unraveling the potential of phenomic selection within and among diverse breeding material of maize (Zea mays L.).

Genomic selection is a well-investigated approach that facilitates and supports selection decisions for complex traits and has meanwhile become a standard tool in modern plant breeding. Phenomic selection has only recently been suggested and uses the same statistical procedures to predict the targeted traits but replaces marker data with near-infrared spectroscopy data. It may represent an attractive low-cost, high-throughput alternative but has not been sufficiently studied until now. Here, we used 400 genotypes of maize (Zea mays L.) comprising elite lines of the Flint and Dent heterotic pools as well as 6 Flint landraces, which were phenotyped in multienvironment trials for anthesis-silking-interval, early vigor, final plant height, grain dry matter content, grain yield, and phosphorus concentration in the maize kernels, to compare the predictive abilities of genomic as well as phenomic prediction under different scenarios. We found that both approaches generally achieved comparable predictive abilities within material groups. However, phenomic prediction was less affected by population structure and performed better than its genomic counterpart for predictions among diverse groups of breeding material. We therefore conclude that phenomic prediction is a promising tool for practical breeding, for instance when working with unknown and rather diverse germplasm. Moreover, it may make the highly monopolized sector of plant breeding more accessible also for low-tech institutions by combining well established, widely available, and cost-efficient spectral phenotyping with the statistical procedures elaborated for genomic prediction - while achieving similar or even better results than with marker data.

The performance of phenomic selection depends on the genetic architecture of the target trait.

KEY MESSAGE: The phenomic predictive ability depends on the genetic architecture of the target trait, being high for complex traits and low for traits with major QTL. Genomic selection is a powerful tool to assist breeding of complex traits, but a limitation is the costs required for genotyping. Recently, phenomic selection has been suggested, which uses spectral data instead of molecular markers as predictors. It was shown to be competitive with genomic prediction, as it achieved predictive abilities as high or even higher than its genomic counterpart. The objective of this study was to evaluate the performance of phenomic prediction for triticale and the dependency of the predictive ability on the genetic architecture of the target trait. We found that for traits with a complex genetic architecture, like grain yield, phenomic prediction with NIRS data as predictors achieved high predictive abilities and performed better than genomic prediction. By contrast, for mono- or oligogenic traits, for example, yellow rust, marker-based approaches achieved high predictive abilities, while those of phenomic prediction were very low. Compared with molecular markers, the predictive ability obtained using NIRS data was more robust to varying degrees of genetic relatedness between the training and prediction set. Moreover, for grain yield, smaller training sets were required to achieve a similar predictive ability for phenomic prediction than for genomic prediction. In addition, our results illustrate the potential of using field-based spectral data for phenomic prediction. Overall, our result confirmed phenomic prediction as an efficient approach to improve the selection gain for complex traits in plant breeding.

Can we abandon phosphorus starter fertilizer in maize? Results from a diverse panel of elite and doubled haploid landrace lines of maize (Zea mays L.).

The importance of phosphorus (P) in agriculture contrasts with the negative environmental impact and the limited resources worldwide. Reducing P fertilizer application by utilizing more efficient genotypes is a promising way to address these issues. To approach this, a large panel of maize (Zea mays L.) comprising each 100 Flint and Dent elite lines and 199 doubled haploid lines from six landraces was assessed in multi-environment field trials with and without the application of P starter fertilizer. The treatment comparison showed that omitting the starter fertilizer can significantly affect traits in early plant development but had no effect on grain yield. Young maize plants provided with additional P showed an increased biomass, faster growth and superior vigor, which, however, was only the case under environmental conditions considered stressful for maize cultivation. Importantly, though the genotype-by-treatment interaction variance was comparably small, there is genotypic variation for this response that can be utilized in breeding. The comparison of elite and doubled haploid landrace lines revealed a superior agronomic performance of elite material but also potentially valuable variation for early traits in the landrace doubled haploid lines. In conclusion, our results illustrate that breeding for P efficient maize cultivars is possible towards a reduction of P fertilizer in a more sustainable agriculture.

Training set design in genomic prediction with multiple biparental families.

Genomic selection is a powerful tool to reduce the cycle length and enhance the genetic gain of complex traits in plant breeding. However, questions remain about the optimum design and composition of the training set. In this study, we used 944 soybean [Glycine max (L.) Merr.] recombinant inbred lines from eight families derived through a partial-diallel mating design among five parental lines. The cross-validated prediction accuracies for the six traits seed yield, 1,000-seed weight, protein yield, plant height, protein content, and oil content were high, ranging from 0.79 to 0.87. We investigated among-family predictions, making use of the special mating design with different degrees of relatedness among families. Generally, the prediction accuracy decreased from full-sibs to half-sib families to unrelated families. However, half-sib and unrelated families also showed substantial variation in their prediction accuracy for a given family, which appeared to be caused at least in part by the shared segregation of quantitative trait loci in both the training and prediction sets. Combining several half-sib families in composite training sets generally led to an increase in the prediction accuracy compared with the best family alone. The prediction accuracy increased with the size of the training set, but for comparable prediction accuracy, substantially more half-sibs were required than full-sibs. Collectively, our results highlight the potential of genomic selection for soybean breeding and, in a broader context, illustrate the importance of the targeted design of the training set.

Priming Soybean cv. Primus Leads to Successful Systemic Defense Against the Root-Lesion Nematode, Pratylenchus penetrans.

Root lesion nematodes, Pratylenchus penetrans, are major pests of legumes with little options for their control. We aimed to prime soybean cv. Primus seedlings to improve basic defense against these nematodes by root application of N-3-oxo-tetradecanoyl-L-homoserine lactone (oxo-C14-HSL). The invasion of soybean roots by P. penetrans was significantly reduced in plants that were pre-treated with the oxo-C14-HSL producing rhizobacterium Ensifer meliloti strain ExpR+, compared to non-inoculated plants or plants inoculated with the nearly isogenic strain E. meliloti AttM with plasmid-mediated oxo-C14-HSL degradation. The nematodes were more clustered in the root tissues of plants treated with the AttM strain or the control compared to roots treated with the ExpR+ strain. In split-root systems primed on one side with strain ExpR+, root invasion was reduced on the opposite side compared to non-primed plants indicating a systemic plant response to oxo-C14-HSL. No additional local effect was detected, when inoculating nematodes on the ExpR+ primed side. Removal of oxo-C14-HSL after root exposure resulted in reduced root invasion compared to non-primed plants when the nematodes were added 3, 7, or 15 days later. Thus, probably the plant memorized the priming stimulus. Similarly, the plants were primed by compounds released from the surface of the nematodes. HPLC analysis of the root extracts of oxo-C14-HSL treated and untreated plants revealed that priming resulted in enhanced phytoalexin synthesis upon P. penetrans challenge. Without root invading nematodes, the phytoalexin concentrations of primed and non-primed plants did not significantly differ, indicating that priming did not lead to a persistently increased stress level of the plants. Upon nematode invasion, the phytoalexins coumestrol, genistein, and glyceollin increased in concentration in the roots compared to control plants without nematodes. Glyceollin synthesis was significantly more triggered by nematodes in primed plants compared to non-primed plants. The results indicated that the priming of soybean plants led to a more rapid and strong defense induction upon root invasion of nematodes.

Optimizing the P balance: How do modern maize hybrids react to different starter fertilizers?

Phosphorus (P) is an essential macronutrient for plants, but also a limited resource worldwide. Strict regulations for fertilizer applications in the European Union are a consequence of the negative environmental effects in case of improper use. Maize is typically grown with the application of P starter fertilizer, which, however, might be reduced or even omitted if suitable varieties were available. This study was performed with the 20 commercially most important maize hybrids in Germany evaluated in multi-location field trials with the aim to investigate the potential to breed for high-performing maize hybrids under reduced P starter fertilizer. At the core location, three starter fertilizers with either phosphate (triple superphosphate, TSP), ammonium nitrate (calcium ammonium nitrate, CAN), or a combination of ammonium and phosphate (diammonium phosphate, DAP) were evaluated relative to a control and traits from youth development to grain yield were assessed. Significant differences were mainly observed for the DAP starter fertilizer, which was also reflected in a yield increase of on average +0.67 t/ha (+5.34%) compared to the control. Correlations among the investigated traits varied with starter fertilizer, but the general trends remained. As expected, grain yield was negatively correlated with grain P concentration, likely due to a dilution effect. Importantly, the genotype-by-starter fertilizer interaction was always non-significant in the multi-location analysis. This indicates that best performing genotypes can be identified irrespective of the starter fertilizer. Taken together, our results provide valuable insights regarding the potential to reduce starter fertilizers in maize cultivation as well as for breeding maize for P efficiency under well-supplied conditions.

Speed breeding short-day crops by LED-controlled light schemes.

KEY MESSAGE: A simple and rapid speed breeding system was developed for short-day crops that enables up to five generations per year using LED lighting systems that allow very specific adjustments regarding light intensity and quality. Plant breeding is a key element for future agricultural production that needs to cope with a growing human population and climate change. However, the process of developing suitable cultivars is time-consuming, not least because of the long generation times of crops. Recently, speed breeding has been introduced for long-day crops, but a similar protocol for short-day crops is lacking to date. In this study, we present a speed breeding protocol based on light-emitting diodes (LEDs) that allow to modify light quality, and exemplarily demonstrate its effectiveness for the short-day crops soybean (Glycine max), rice (Oryza sativa) and amaranth (Amaranthus spp.). Adjusting the photoperiod to 10 h and using a blue-light enriched, far-red-deprived light spectrum facilitated the growth of short and sturdy soybean plants that flowered ~ 23 days after sowing and matured within 77 days, thus allowing up to five generations per year. In rice and amaranth, flowering was achieved ~ 60 and ~ 35 days after sowing, respectively. Interestingly, the use of far-red light advanced flowering by 10 and 20 days in some amaranth and rice genotypes, respectively, but had no impact on flowering in soybeans, highlighting the importance of light quality for speed breeding protocols. Taken together, our short-day crops' speed breeding protocol enables several generations per year using crop-specific LED-based lighting regimes, without the need of tissue culture tools such as embryo rescue. Moreover, this approach can be readily applied to a multi-storey 96-cell tray-based system to integrate speed breeding with genomics, toward a higher improvement rate in breeding.

The soybean experiment '1000 Gardens': a case study of citizen science for research, education, and beyond.

KEY MESSAGE: Citizen science, an approach that includes normal citizens in scientific research, holds great potential also for plant sciences and breeding and can be a powerful research tool to complement traditional approaches. Citizen science is an approach that includes normal citizens in scientific research, but has so far not been exploited by the various disciplines in plant sciences. Moreover, global threats challenge human well-being and science can provide solutions, but needs to leave the ivory tower in the mind of the broader public. In 2016, we performed the '1000 Gardens-the soybean experiment' citizen science project, that aimed at finding citizens in Germany who would grow soybean lines in their own gardens and evaluate them for a range of traits related to adaptation and agronomic performance. Here, we describe details of this project, i.e. the recruitment, performance, and compliance of the citizen scientists. A total of 2492 citizen scientists volunteered for the project, but through the high media coverage a much broader audience than just the participants was reached. Our 1000 Gardens project was successful in collecting a scientifically unique data set with heritabilities ranging up to 0.60 for maturity date or 0.69 for plant height. Our results suggest that the citizen science approach holds great potential also for plant sciences and can be a powerful research tool to complement traditional approaches. Our project was also successful in raising public awareness about the importance of plant breeding and in communicating key messages on the manifold benefits of legumes for a sustainable agriculture to a broader public. Thus, citizen science appears as a promising avenue to demonstrate the value of breeding and science to the general public by including normal citizens in scientific research.

Cadmium concentrations in German soybeans are elevated in conurbations and in regions dominated by mining and the metal industry.

BACKGROUND: Cadmium (Cd) is a mobile heavy metal and soybeans accumulate more of this element compared to other grain crops. Because vegan and vegetarian lifestyles are increasingly popular, plant-based diets should be free from contaminants. Cd minimization has recently been identified as a breeding aim in addition to protein and oil levels. It is also important to consider the regional variability of Cd in crops. RESULTS: A large sample collection (n = 602) was subjected to Cd analyses. Soybeans were grown using a standard protocol by private gardeners in a citizen science program. Some 12.5% of samples exceeded European Union limits, although Cd concentrations and exceedances showed regional variation around the national mean (0.13 mg kg-1 ). Contamination was higher in densely populated regions, possibly as a result of the long-term emissions of heavy metal loaded dusts from industry, traffic and energy production. Cd concentrations were also elevated in regions once characterized by mining and heavy industry. Values were low overall in rural areas and agricultural regions despite potential inputs via phosphate fertilizers. CONCLUSION: Grain Cd levels are highly variable across Germany. Soybean farming may be problematic in regions with a long history of mining and heavy metal deposition. © 2018 Society of Chemical Industry.

Identification of mega-environments in Europe and effect of allelic variation at maturity E loci on adaptation of European soybean.

Soybean cultivation holds great potential for a sustainable agriculture in Europe, but adaptation remains a central issue. In this large mega-environment (MEV) study, 75 European cultivars from five early maturity groups (MGs 000-II) were evaluated for maturity-related traits at 22 locations in 10 countries across Europe. Clustering of the locations based on phenotypic similarity revealed six MEVs in latitudinal direction and suggested several more. Analysis of maturity identified several groups of cultivars with phenotypic similarity that are optimally adapted to the different growing regions in Europe. We identified several haplotypes for the allelic variants at the E1, E2, E3 and E4 genes, with each E haplotype comprising cultivars from different MGs. Cultivars with the same E haplotype can exhibit different flowering and maturity characteristics, suggesting that the genetic control of these traits is more complex and that adaptation involves additional genetic pathways, for example temperature requirement. Taken together, our study allowed the first unified assessment of soybean-growing regions in Europe and illustrates the strong effect of photoperiod on soybean adaptation and MEV classification, as well as the effects of the E maturity loci for soybean adaptation in Europe.

Copy number variations of CBF genes at the Fr-A2 locus are essential components of winter hardiness in wheat.

Winter hardiness is important for the adaptation of wheat to the harsh winter conditions in temperate regions and is thus also an important breeding goal. Here, we employed a panel of 407 European winter wheat cultivars to dissect the genetic architecture of winter hardiness. We show that copy number variation (CNV) of CBF (C-repeat Binding Factor) genes at the Fr-A2 locus is the essential component for winter survival, with CBF-A14 CNV being the most likely causal polymorphism, accounting for 24.3% of the genotypic variance. Genome-wide association mapping identified several markers in the Fr-A2 chromosomal region, which even after accounting for the effects of CBF-A14 copy number explained approximately 15% of the genotypic variance. This suggests that additional, as yet undiscovered, polymorphisms are present at the Fr-A2 locus. Furthermore, CNV of Vrn-A1 explained an additional 3.0% of the genotypic variance. The allele frequencies of all loci associated with winter hardiness were found to show geographic patterns consistent with their role in adaptation. Collectively, our results from the candidate gene analysis, association mapping and genome-wide prediction show that winter hardiness in wheat is a quantitative trait, but with a major contribution of the Fr-A2 locus.

Diversity analysis and genomic prediction of Sclerotinia resistance in sunflower using a new 25 K SNP genotyping array.

KEY MESSAGE: We have developed a SNP array for sunflower containing more than 25 K markers, representing single loci mostly in or near transcribed regions of the genome. The array was successfully applied to genotype a diversity panel of lines, hybrids, and mapping populations and represented well the genetic diversity of cultivated sunflower. Results of PCoA and population substructure analysis underlined the complexity of the genetic composition of current elite breeding material. The performance of this genotyping platform for genome-based prediction of phenotypes and detection of QTL with improved resolution could be demonstrated based on the re-evaluation of a population segregating for resistance to Sclerotinia midstalk rot. Given our results, the newly developed 25 K SNP array is expected to be of great utility for the most important applications in genome-based sunflower breeding and research. ABSTRACT: Genotyping with a large number of molecular markers is a prerequisite to conduct genome-based genetic analyses with high precision. Here, we report the design and performance of a 25 K SNP genotyping array for sunflower (Helianthus annuus L.). SNPs were discovered based on variant calling in de novo assembled, UniGene-based contigs of sunflower derived from whole genome sequencing and amplicon sequences originating from four and 48 inbred lines, respectively. After inclusion of publically available transcriptome-derived SNPs, in silico design of the Illumina(®) Infinium iSelect HD BeadChip yielded successful assays for 22,299 predominantly haplotype-specific SNPs. The array was validated in a sunflower diversity panel including inbred lines, open-pollinated varieties, introgression lines, landraces, recombinant inbred lines, and F2 populations. Validation provided 20,502 high-quality bi-allelic SNPs with stable cluster performance whereby each SNP marker represents a single locus mostly in or near transcribed regions of the sunflower genome. Analyses of population structure and quantitative resistance to Sclerotinia midstalk rot demonstrate that this array represents a significant improvement over currently available genomic tools for genetic diversity analyses, genome-wide marker-trait association studies, and genetic mapping in sunflower.

Adult plant development in triticale (× triticosecale wittmack) is controlled by dynamic genetic patterns of regulation.

Many biologically and agronomically important traits are dynamic and show temporal variation. In this study, we used triticale (× Triticosecale Wittmack) as a model crop to assess the genetic dynamics underlying phenotypic plasticity of adult plant development. To this end, a large mapping population with 647 doubled haploid lines derived from four partially connected families from crosses among six parents was scored for developmental stage at three different time points. Using genome-wide association mapping, we identified main effect and epistatic quantitative trait loci (QTL) at all three time points. Interestingly, some of these QTL were identified at all time points, whereas others appear to only contribute to the genetic architecture at certain developmental stages. Our results illustrate the temporal contribution of QTL to the genetic control of adult plant development and more generally, the temporal genetic patterns of regulation that underlie dynamic traits.

Mapping dynamic QTL for plant height in triticale.

BACKGROUND: Plant height is a prime example of a dynamic trait that changes constantly throughout adult development. In this study we utilised a large triticale mapping population, comprising 647 doubled haploid lines derived from 4 families, to phenotype for plant height by a precision phenotyping platform at multiple time points. RESULTS: Using multiple-line cross QTL mapping we identified main effect and epistatic QTL for plant height for each of the time points. Interestingly, some QTL were detected at all time points whereas others were specific to particular developmental stages. Furthermore, the contribution of the QTL to the genotypic variance of plant height also varied with time as exemplified by a major QTL identified on chromosome 6A. CONCLUSIONS: Taken together, our results in the small grain cereal triticale reveal the importance of considering temporal genetic patterns in the regulation of complex traits such as plant height.

Genetic dynamics underlying phenotypic development of biomass yield in triticale.

BACKGROUND: The nature of dynamic traits with their phenotypic plasticity suggests that they are under the control of a dynamic genetic regulation. We employed a precision phenotyping platform to non-invasively assess biomass yield in a large mapping population of triticale at three developmental stages. RESULTS: Using multiple-line cross QTL mapping we identified QTL for each of these developmental stages which explained a considerable proportion of the genotypic variance. Some QTL were identified at each developmental stage and thus contribute to biomass yield throughout the studied developmental phases. Interestingly, we also observed QTL that were only identified for one or two of the developmental stages illustrating a temporal contribution of these QTL to the trait. In addition, epistatic QTL were detected and the epistatic interaction landscape was shown to dynamically change with developmental progression. CONCLUSIONS: In summary, our results reveal the temporal dynamics of the genetic architecture underlying biomass accumulation in triticale and emphasize the need for a temporal assessment of dynamic traits.

Genetic architecture of winter hardiness and frost tolerance in triticale.

Abiotic stress experienced by autumn-sown crops during winter is of great economic importance as it can have a severe negative impact on yield. In this study, we investigated the genetic architecture of winter hardiness and frost tolerance in triticale. To this end, we used a large mapping population of 647 DH lines phenotyped for both traits in combination with genome-wide marker data. Employing multiple-line cross QTL mapping, we identified nine main effect QTL for winter hardiness and frost tolerance of which six were overlapping between both traits. Three major QTL were identified on chromosomes 5A, 1B and 5R. In addition, an epistasis scan revealed the contribution of epistasis to the genetic architecture of winter hardiness and frost tolerance in triticale. Taken together, our results show that winter hardiness and frost tolerance are complex traits that can be improved by phenotypic selection, but also that genomic approaches hold potential for a knowledge-based improvement of these important traits in elite triticale germplasm.

Multiple-line cross QTL mapping for biomass yield and plant height in triticale (× Triticosecale Wittmack).

KEY MESSAGE: QTL mapping in multiple families identifies trait-specific and pleiotropic QTL for biomass yield and plant height in triticale. Triticale shows a broad genetic variation for biomass yield which is of interest for a range of purposes, including bioenergy. Plant height is a major contributor to biomass yield and in this study, we investigated the genetic architecture underlying biomass yield and plant height by multiple-line cross QTL mapping. We employed 647 doubled haploid lines from four mapping populations that have been evaluated in four environments and genotyped with 1710 DArT markers. Twelve QTL were identified for plant height and nine for biomass yield which cross-validated explained 59.6 and 38.2 % of the genotypic variance, respectively. A major QTL for both traits was identified on chromosome 5R which likely corresponds to the dominant dwarfing gene Ddw1. In addition, we detected epistatic QTL for plant height and biomass yield which, however, contributed only little to the genetic architecture of the traits. In conclusion, our results demonstrate the potential of genomic approaches for a knowledge-based improvement of biomass yield in triticale.