Separation of the effects of two reduced height (Rht) genes and genomic background to select for less Fusarium head blight of short-strawed winter wheat (Triticum aestivum L.) varieties.

KEY MESSAGE: FHB resistance shared pleiotropic loci with plant height and anther retention. Genomic prediction allows to select for genomic background reducing FHB susceptibility in the presence of the dwarfing allele Rht-D1b. With the high interest for semi-dwarf cultivars in wheat, finding locally adapted resistance sources against Fusarium head blight (FHB) and FHB-neutral reduced height (Rht) genes is of utmost relevance. In this study, 401 genotypes of European origin without/with dwarfing alleles of Rht-D1 and/or Rht24 were analysed across five environments on FHB severity and the morphological traits such as plant height (PH), anther retention (AR), number of spikelets per ear, ear length and ear density. Data were analysed by combined correlation and path analyses, association mapping and coupling single- and multi-trait genome-wide association studies (ST-GWAS and MT-GWAS, respectively) and genomic prediction (GP). All FHB data were corrected for flowering date or heading stage. High genotypic correlation (rg = 0.74) and direct path effect (0.57) were detected between FHB severity and anther retention (AR). Moderate correlation (rg = - 0.55) was found between FHB severity and plant height (PH) with a high indirect path via AR (- 0.31). Indirect selection for FHB resistance should concentrate on AR and PH. ST-GWAS identified 25 quantitative trait loci (QTL) for FHB severity, PH and AR, while MT-GWAS detected six QTL across chromosomes 2A, 4D, 5A, 6B and 7B conveying pleiotropic effects on the traits. Rht-D1b was associated with high AR and FHB susceptibility. Our study identified a promising positively acting pleiotropic QTL on chromosome 7B which can be utilized to improve FHB resistance while reducing PH and AR. Rht-D1b genotypes having a high resistance genomic background exhibited lower FHB severity and AR. The use of GP for estimating the genomic background was more effective than selection of GWAS-detected markers. We demonstrated that GP has a great potential and should be exploited by selecting for semi-dwarf winter wheat genotypes with higher FHB resistance due to their genomic background.

Studying Stem Rust and Leaf Rust Resistances of Self-Fertile Rye Breeding Populations.

Stem rust (SR) and leaf rust (LR) are currently the two most important rust diseases of cultivated rye in Central Europe and resistant cultivars promise to prevent yield losses caused by those pathogens. To secure long-lasting resistance, ideally pyramided monogenic resistances and race-nonspecific resistances are applied. To find respective genes, we screened six breeding populations and one testcross population for resistance to artificially inoculated SR and naturally occurring LR in multi-environmental field trials. Five populations were genotyped with a 10K SNP marker chip and one with DArTseqTM. In total, ten SR-QTLs were found that caused a reduction of 5-17 percentage points in stem coverage with urediniospores. Four QTLs thereof were mapped to positions of already known SR QTLs. An additional gene at the distal end of chromosome 2R, Pgs3.1, that caused a reduction of 40 percentage points SR infection, was validated. One SR-QTL on chromosome 3R, QTL-SR4, was found in three populations linked with the same marker. Further QTLs at similar positions, but from different populations, were also found on chromosomes 1R, 4R, and 6R. For SR, additionally seedling tests were used to separate between adult-plant and all-stage resistances and a statistical method accounting for the ordinal-scaled seedling test data was used to map seedling resistances. However, only Pgs3.1 could be detected based on seedling test data, even though genetic variance was observed in another population, too. For LR, in three of the populations, two new large-effect loci (Pr7 and Pr8) on chromosomes 1R and 2R were mapped that caused 34 and 21 percentage points reduction in leaf area covered with urediniospores and one new QTL on chromosome 1R causing 9 percentage points reduction.

Genome-wide association study for deoxynivalenol production and aggressiveness in wheat and rye head blight by resequencing 92 isolates of Fusarium culmorum.

BACKGROUND: Fusarium culmorum is an important pathogen causing head blight of cereals in Europe. This disease is of worldwide importance leading to reduced yield, grain quality, and contamination by mycotoxins. These mycotoxins are harmful for livestock and humans; therefore, many countries have strict regulatory limits for raw materials and processed food. Extensive genetic diversity is described among field populations of F. culmorum isolates for aggressiveness and production of the trichothecene mycotoxin deoxynivalenol (DON). However, the causes for this quantitative variation are not clear, yet. We analyzed 92 isolates sampled from different field populations in Germany, Russia, and Syria together with an international collection for aggressiveness and DON production in replicated field experiments at two locations in two years with two hosts, wheat and rye. The 30x coverage whole-genome resequencing of all isolates resulted in the identification of 130,389 high quality single nucleotide polymorphisms (SNPs) that were used for the first genome-wide association study in this phytopathogenic fungus. RESULTS: In wheat, 20 and 27 SNPs were detected for aggressiveness and DON content, respectively, of which 10 overlapped. Additionally, two different SNPs were significantly associated with aggressiveness in rye that were among those SNPs being associated with DON production in wheat. Most of the SNPs explained only a small proportion of genotypic variance (pG), however, four SNPs were associated with major quantitative trait loci (QTLs) with pG ranging from 12 to 48%. The QTL with the highest pG was involved in DON production and associated with a SNP most probably located within the Tri4 gene. CONCLUSIONS: The diversity of 92 isolates of F. culmorum were captured using a heuristic approach. Key phenotypic traits, SNPs, and candidate genes underlying aggressiveness and DON production were identified. Clearly, many QTLs are responsible for aggressiveness and DON content in wheat, both traits following a quantitative inheritance. Several SNPs involved in DON metabolism, among them the Tri4 gene of the trichothecene pathway, were inferred as important source of variation in fungal aggressiveness. Using this information underlying the phenotypic variation will be of paramount importance in evaluating strategies for successful resistance breeding.

Climate change will influence disease resistance breeding in wheat in Northwestern Europe.

Wheat productivity is threatened by global climate change. In several parts of NW Europe it will get warmer and dryer during the main crop growing period. The resulting likely lower realized on-farm crop yields must be kept by breeding for resistance against already existing and emerging diseases among other measures. Multi-disease resistance will get especially crucial. In this review, we focus on disease resistance breeding approaches in wheat, especially related to rust diseases and Fusarium head blight, because simulation studies of potential future disease risk have shown that these diseases will be increasingly relevant in the future. The long-term changes in disease occurrence must inevitably lead to adjustments of future resistance breeding strategies, whereby stability and durability of disease resistance under heat and water stress will be important in the future. In general, it would be important to focus on non-temperature sensitive resistance genes/QTLs. To conclude, research on the effects of heat and drought stress on disease resistance reactions must be given special attention in the future.

Mapping and validating stem rust resistance genes directly in self-incompatible genetic resources of winter rye.

KEY MESSAGE: Individual stem rust resistance genes could be directly mapped within self-incompatible rye populations. Genetic resources of rye (Secale cereale L.) are cross-pollinating populations that can be highly diverse and are naturally segregating. In this study, we show that this segregation could be used for mapping stem rust resistance. Populations of pre-selected donors from the Russian Federation, the USA and Austria were tested on a single-plant basis for stem rust resistance by a leaf-segment test with three rust isolates. Seventy-four plants per population were genotyped with a 10 K-SNP chip. Using cumulative logit models, significant associations between the ordinal infection score and the marker alleles could be found. Three different loci (Pgs1, Pgs2, Pgs3) in three populations were highly significant, and resistance-linked markers could be validated with field experiments of an independent seed sample from the original population and were used to fix two populations for resistance. We showed that it is possible to map monogenically inherited seedling resistance genes directly in genetic resources, thus providing a competitive alternative to linkage mapping approaches that require a tedious and time-consuming inbreeding over several generations.

Intercontinental trials reveal stable QTL for Northern corn leaf blight resistance in Europe and in Brazil.

KEY MESSAGE: NCLB is the most devastating leaf disease in European maize, and the introduction of Brazilian resistance donors can efficiently increase the resistance levels of European maize germplasm. Northern corn leaf blight (NCLB) is one of the most devastating leaf pathogens in maize (Zea mays L.). Maize cultivars need to be equipped with broad and stable NCLB resistance to cope with production intensification and climate change. Brazilian germplasm is a great source to increase low NCLB resistance levels in European materials, but little is known about their effect in European environments. To investigate the usefulness of Brazilian germplasm as NCLB resistance donors, we conducted multi-parent QTL mapping, evaluated the potential of marker-assisted selection as well as genome-wide selection of 742 F1-derived DH lines. The line per se performance was evaluated in one location in Brazil and six location-by-year combinations (= environments) in Europe, while testcrosses were assessed in two locations in Brazil and further 10 environments in Europe. Jointly, we identified 17 QTL for NCLB resistance explaining 3.57-30.98% of the genotypic variance each. Two of these QTL were detected in both Brazilian and European environments indicating the stability of these QTL in contrasting ecosystems. We observed moderate to high genomic prediction accuracies between 0.58 and 0.83 depending on population and continent. Collectively, our study illustrates the potential use of tropical resistance sources to increase NCLB resistance level in applied European maize breeding programs.

Snow mold of winter cereals: a complex disease and a challenge for resistance breeding.

KEY MESSAGE: Snow mold resistance is a complex quantitative trait highly affected by environmental conditions during winter that must be addressed by resistance breeding. Snow mold resistance in winter cereals is an important trait for many countries in the Northern Hemisphere. The disease is caused by at least four complexes of soilborne fungi and oomycetes of which Microdochium nivale and M. majus are among the most common pathogens. They have a broad host range covering all winter and spring cereals and can basically affect all plant growth stages and organs. Their attack leads to a low germination rate, and/or pre- and post-emergence death of seedlings after winter and, depending on largely unknown environmental conditions, also to foot rot, leaf blight, and head blight. Resistance in winter wheat and triticale is governed by a multitude of quantitative trait loci (QTL) with mainly additive effects highly affected by genotype × environment interaction. Snow mold resistance interacts with winter hardiness in a complex way leading to a co-localization of resistance QTLs with QTLs/genes for freezing tolerance. In practical breeding, a multistep procedure is necessary with (1) freezing tolerance tests, (2) climate chamber tests for snow mold resistance, and (3) field tests in locations with and without regularly occurring snow cover. In the future, resistance sources should be genetically characterized also in rye by QTL mapping or genome-wide association studies. The development of genomic selection procedures should be prioritized in breeding research.

Early prediction of biomass in hybrid rye based on hyperspectral data surpasses genomic predictability in less-related breeding material.

KEY MESSAGE: Hyperspectral data is a promising complement to genomic data to predict biomass under scenarios of low genetic relatedness. Sufficient environmental connectivity between data used for model training and validation is required. The demand for sustainable sources of biomass is increasing worldwide. The early prediction of biomass via indirect selection of dry matter yield (DMY) based on hyperspectral and/or genomic prediction is crucial to affordably untap the potential of winter rye (Secale cereale L.) as a dual-purpose crop. However, this estimation involves multiple genetic backgrounds and genetic relatedness is a crucial factor in genomic selection (GS). To assess the prospect of prediction using reflectance data as a suitable complement to GS for biomass breeding, the influence of trait heritability ([Formula: see text]) and genetic relatedness were compared. Models were based on genomic (GBLUP) and hyperspectral reflectance-derived (HBLUP) relationship matrices to predict DMY and other biomass-related traits such as dry matter content (DMC) and fresh matter yield (FMY). For this, 270 elite rye lines from nine interconnected bi-parental families were genotyped using a 10 k-SNP array and phenotyped as testcrosses at four locations in two years (eight environments). From 400 discrete narrow bands (410 nm-993 nm) collected by an uncrewed aerial vehicle (UAV) on two dates in each environment, 32 hyperspectral bands previously selected by Lasso were incorporated into a prediction model. HBLUP showed higher prediction abilities (0.41 - 0.61) than GBLUP (0.14 - 0.28) under a decreased genetic relationship, especially for mid-heritable traits (FMY and DMY), suggesting that HBLUP is much less affected by relatedness and [Formula: see text]. However, the predictive power of both models was largely affected by environmental variances. Prediction abilities for DMY were further enhanced (up to 20%) by integrating both matrices and plant height into a bivariate model. Thus, data derived from high-throughput phenotyping emerges as a suitable strategy to efficiently leverage selection gains in biomass rye breeding; however, sufficient environmental connectivity is needed.

Exploiting genetic diversity in two European maize landraces for improving Gibberella ear rot resistance using genomic tools.

KEY MESSAGE: High genetic variation in two European maize landraces can be harnessed to improve Gibberella ear rot resistance by integrated genomic tools. Fusarium graminearum (Fg) causes Gibberella ear rot (GER) in maize leading to yield reduction and contamination of grains with several mycotoxins. This study aimed to elucidate the molecular basis of GER resistance among 500 doubled haploid lines derived from two European maize landraces, "Kemater Landmais Gelb" (KE) and "Petkuser Ferdinand Rot" (PE). The two landraces were analyzed individually using genome-wide association studies and genomic selection (GS). The lines were genotyped with a 600-k maize array and phenotyped for GER severity, days to silking, plant height, and seed-set in four environments using artificial infection with a highly aggressive Fg isolate. High genotypic variances and broad-sense heritabilities were found for all traits. Genotype-environment interaction was important throughout. The phenotypic (r) and genotypic ([Formula: see text]) correlations between GER severity and three agronomic traits were low (r = - 0.27 to 0.20; [Formula: see text]= - 0.32 to 0.22). For GER severity, eight QTLs were detected in KE jointly explaining 34% of the genetic variance. In PE, no significant QTLs for GER severity were detected. No common QTLs were found between GER severity and the three agronomic traits. The mean prediction accuracies ([Formula: see text]) of weighted GS (wRR-BLUP) were higher than [Formula: see text] of marker-assisted selection (MAS) and unweighted GS (RR-BLUP) for GER severity. Using KE as the training set and PE as the validation set resulted in very low [Formula: see text] that could be improved by using fixed marker effects in the GS model.

Molecular tracking of multiple disease resistance in a winter wheat diversity panel.

KEY MESSAGE: About 10% of cultivars possessed superior resistance to four fungal diseases and association mapping for multiple disease resistance identified loci which are not detected by analyzing individual disease resistances. Multiple disease resistance (MDR) aims for cultivars that are resistant to more than one disease which is an important prerequisite for the registration of commercial cultivars. We analyzed a European winter wheat diversity panel of 158 old and new cultivars for four diseases by natural (powdery mildew) and artificial inoculation (yellow rust, stem rust, Fusarium head blight) observed on the same plot in a multilocation trial. Genotypic analyses were based on 21,543 genotype-by-sequencing markers. By association mapping, eight to 18 quantitative-trait loci (QTL) were detected for individual disease resistances, explaining in total 67-90% of the total genotypic variation. For MDR, nine QTL could be found explaining 62% of the total genotypic variation. Only three of them were also found as QTL for a single disease resistance illustrating that mapping of MDR-associated QTL can be regarded as a complementary approach. The high prediction ability obtained for MDR (> 0.9) implies that genomic prediction could be used in future, thereby eliminating the necessity to separately screen large numbers of lines in breeding programs for several diseases.

Integration of genotypic, hyperspectral, and phenotypic data to improve biomass yield prediction in hybrid rye.

KEY MESSAGE: Hyperspectral and genomic data are effective predictors of biomass yield in winter rye. Variable selection procedures can improve the informativeness of reflectance data. Integrating cutting-edge technologies is imperative to sustainably breed crops for a growing global population. To predict dry matter yield (DMY) in winter rye (Secale cereale L.), we tested single-kernel models based on genomic (GBLUP) and hyperspectral reflectance-derived (HBLUP) relationship matrices, a multi-kernel model combining both matrices and a bivariate model fitted with plant height as a secondary trait. In total, 274 elite rye lines were genotyped using a 10 k-SNP array and phenotyped as testcrosses for DMY and plant height at four locations in Germany in two years (eight environments). Spectral data consisted of 400 discrete narrow bands ranging between 410 and 993 nm collected by an unmanned aerial vehicle (UAV) on two dates on each environment. To reduce data dimensionality, variable selection of bands was performed, resulting in the least absolute shrinkage and selection operator (Lasso) as the best method in terms of predictive abilities. The mean heritability of reflectance data was moderate ([Formula: see text] = 0.72) and highly variable across the spectrum. Correlations between DMY and single bands were generally significant (p < 0.05) but low (≤ 0.29). Across environments and training set (TRN) sizes, the bivariate model showed the highest prediction abilities (0.56-0.75), followed by the multi-kernel (0.45-0.71) and single-kernel (0.33-0.61) models. With reduced TRN, HBLUP performed better than GBLUP. The HBLUP model fitted with a set of selected bands was preferred. Within and across environments, prediction abilities increased with larger TRN. Our results suggest that in the era of digital breeding, the integration of high-throughput phenotyping and genomic selection is a promising strategy to achieve superior selection gains in hybrid rye.

Genomics-Assisted Breeding for Quantitative Disease Resistances in Small-Grain Cereals and Maize.

Generating genomics-driven knowledge opens a way to accelerate the resistance breeding process by family or population mapping and genomic selection. Important prerequisites are large populations that are genomically analyzed by medium- to high-density marker arrays and extensive phenotyping across locations and years of the same populations. The latter is important to train a genomic model that is used to predict genomic estimated breeding values of phenotypically untested genotypes. After reviewing the specific features of quantitative resistances and the basic genomic techniques, the possibilities for genomics-assisted breeding are evaluated for six pathosystems with hemi-biotrophic fungi: Small-grain cereals/Fusarium head blight (FHB), wheat/Septoria tritici blotch (STB) and Septoria nodorum blotch (SNB), maize/Gibberella ear rot (GER) and Fusarium ear rot (FER), maize/Northern corn leaf blight (NCLB). Typically, all quantitative disease resistances are caused by hundreds of QTL scattered across the whole genome, but often available in hotspots as exemplified for NCLB resistance in maize. Because all crops are suffering from many diseases, multi-disease resistance (MDR) is an attractive aim that can be selected by specific MDR QTL. Finally, the integration of genomic data in the breeding process for introgression of genetic resources and for the improvement within elite materials is discussed.

Genomics-assisted breeding for ear rot resistances and reduced mycotoxin contamination in maize: methods, advances and prospects.

KEY MESSAGE: Genetic mapping, genomic profiling and bioinformatic approaches were used to identify putative resistance genes for ear rots and low mycotoxin contamination in maize. Genomic selection seems to have good perspectives. Maize is globally an indispensable crop for humans and livestock. About 30% of yield is lost by fungal diseases with Gibberella, Fusarium and Aspergillus ear rots (ERs) having a high economic impact in most maize-growing regions of the world. They reduce not only yield, but also contaminate grains with mycotoxins like deoxynivalenol, zearalenone, fumonisins and aflatoxins, respectively. These mycotoxins pose serious health problems to humans and animals. A number of studies have been conducted to dissect the genetic architecture of resistance to these three major ear rots over the past decade. The review concentrates on studies carried out to locate quantitative trait loci (QTL) and candidate genes (CG) on the maize genome as well as the application of genomic selection in maize for resistance against Fusarium graminearum, Fusarium verticillioides and Aspergillus flavus. QTL studies by linkage or genome-wide association mapping, omic technologies (genomics, proteomics, transcriptomics and metabolomics) and bioinformatics are the methods used in the current studies to propose resistance genes against ear rot pathogens. Though a number of QTL and CG are reported, only a few specific genes were found to directly confer ER resistance in maize. A combination of two or more gene identification methods would provide a more powerful and reliable tool. Genomic selection seems to be promising for ER resistance breeding, but there are only a limited number of studies in this area. A strategy that can accurately validate and predict genotypes with major effect QTL and CG for selection will be worthwhile for practical breeding against ERs and mycotoxin contamination in maize.

An experimental approach for estimating the genomic selection advantage for Fusarium head blight and Septoria tritici blotch in winter wheat.

KEY MESSAGE: The genomic selection advantage for Fusarium head blight is promising but failed for Septoria tritici blotch. Selection of new breeding parents based on predictions must be treated with caution. Genomic selection (GS) is an approach that uses whole-genome marker data to estimate breeding values of untested genotypes and holds the potential to improve the genetic gain in breeding programs by shortening the breeding cycle and increasing the selection intensity. However, reported realized gain from genomic selection is limited to few experiments. In this study, a training population of 1120 winter wheat lines derived from 14 bi-parental families was genotyped with genome-wide single nucleotide polymorphism markers and phenotyped for Fusarium head blight (FHB) and Septoria tritici blotch (STB) severity, plant height and heading date. We used weighted ridge regression best linear unbiased prediction to calculate genomic estimated breeding values (GEBVs) of 2500 genotypes. Based on GEBVs, we selected the most resistant individuals as well as a random sample and tested them in a multi-location field trial. We computed moderate coefficients of correlation between observed and predicted trait values for FHB severity, plant height and heading date and achieved a genomic selection advantage of 10.62 percentage points for FHB resistance compared to the randomly chosen subpopulation. Genomic selection failed for the improvement of STB resistance with a genomic selection advantage of only 2.14 percentage points. Our results also indicate that the selection of new breeding parents based on GEBVs must be treated with caution. Taken together, the implementation of GS for FHB resistance, plant height and heading date seems to be promising. For traits with very strong genotype × environment variance, like STB resistance, GS appears to be still challenging.

Accuracy of within- and among-family genomic prediction for Fusarium head blight and Septoria tritici blotch in winter wheat.

Genomic selection is an approach that uses whole-genome marker data to predict breeding values of genotypes and holds the potential to improve the genetic gain in breeding programs. In this study, two winter wheat populations (DS1 and DS2) consisting of 438 and 585 lines derived from six and eight bi-parental families, respectively, were genotyped with genome-wide single nucleotide polymorphism markers and phenotyped for Fusarium head blight and Septoria tritici blotch severity, plant height and heading date. We used ridge regression-best linear unbiased prediction to investigate the potential of genomic selection under different selection scenarios: prediction across each winter wheat population, within- and among-family prediction in each population, and prediction from DS1 to DS2 and vice versa. Moreover, we compared a full random model to a model incorporating quantitative trait loci (QTL) as fixed effects. The prediction accuracies obtained by cross-validation within populations were moderate to high for all traits. Accuracies for individual families were in general lower and varied with population size and genetic architecture of the trait. In the among-family prediction scenario, highest accuracies were achieved by predicting from one half-sib family to another, while accuracies were lowest between unrelated families. Our results further demonstrate that the prediction accuracy can be considerably increased by a fixed effect model approach when major QTL are present. Taken together, the implementation of genomic selection for Fusarium head blight and Septoria tritici blotch resistance seems to be promising, but the composition of the training population is of utmost importance.

Copy number variation of Ppd-B1 is the major determinant of heading time in durum wheat.

BACKGROUND: Heading time is an important adaptive trait in durum wheat. In hexaploid wheat, Photoperiod-1 (Ppd) loci are essential regulators of heading time, with Ppd-B1 conferring photoperiod insensitivity through copy number variations (CNV). In tetraploid wheat, the D-genome Ppd-D1 locus is absent and generally, our knowledge on the genetic architecture underlying heading time lacks behind that of bread wheat. RESULTS: In this study, we employed a panel of 328 diverse European durum genotypes that were evaluated for heading time at five environments. Genome-wide association mapping identified six putative QTL, with a major QTL on chromosome 2B explaining 26.2% of the genotypic variance. This QTL was shown to correspond to copy number variation at Ppd-B1, for which two copy number variants appear to be present. The higher copy number confers earlier heading and was more frequent in the heat and drought prone countries of lower latitude. In addition, two other QTL, corresponding to Vrn-B3 (TaFT) and Ppd-A1, were found to explain 9.5 and 5.3% of the genotypic variance, respectively. CONCLUSIONS: Our results revealed the yet unknown role of copy number variation of Ppd-B1 as the major source underlying the variation in heading time in European durum wheat. The observed geographic patterns underline the adaptive value of this polymorphism and suggest that it is already used in durum breeding to tailor cultivars to specific target environments. In a broader context our findings provide further support for a more widespread role of copy number variation in mediating abiotic and biotic stress tolerance in plants.

Rht24 reduces height in the winter wheat population 'Solitär × Bussard' without adverse effects on Fusarium head blight infection.

KEY MESSAGE: The dwarfing gene Rht24 on chromosome 6A acts in the wheat population 'Solitär × Bussard', considerably reducing plant height without increasing Fusarium head blight severity and delaying heading stage. The introduction of the Reduced height (Rht)-B1 and Rht-D1 semi-dwarfing genes led to remarkable increases in wheat yields during the Green Revolution. However, their utilization also brings about some unwanted characteristics, including the increased susceptibility to Fusarium head blight. Thus, Rht loci that hold the potential to reduce plant height in wheat without concomitantly increasing Fusarium head blight (FHB) susceptibility are urgently required. The biparental population 'Solitär × Bussard' fixed for the Rht-1 wild-type alleles, but segregating for the recently described gibberellic acid (GA)-sensitive Rht24 gene, was analyzed to identify quantitative trait loci (QTL) for FHB severity, plant height, and heading date and to evaluate the effect of the Rht24 locus on these traits. The most prominent QTL was Rht24 on chromosome 6A explaining 51% of genotypic variation for plant height and exerting an additive effect of - 4.80 cm. For FHB severity three QTL were detected, whereas five and six QTL were found for plant height and heading date, respectively. No FHB resistance QTL was co-localized with QTL for plant height. Unlike the Rht-1 semi-dwarfing alleles, Rht24b did not significantly affect FHB severity. This demonstrates that the choice of semi-dwarfing genes used in plant breeding programs is of utmost consideration where resistance to FHB is an important breeding target.

Fine mapping of the restorer gene Rfp3 from an Iranian primitive rye (Secale cereale L.).

KEY MESSAGE: A comparative genetics approach allowed to precisely determine the map position of the restorer gene Rfp3 in rye and revealed that Rfp3 and the restorer gene Rfm1 in barley reside at different positions in a syntenic 4RL/6HS segment. Cytoplasmic male sterility (CMS) is a reliable and striking genetic mechanism for hybrid seed production. Breeding of CMS-based hybrids in cereals requires the use of effective restorer genes as an indispensable pre-requisite. We report on the fine mapping of a restorer gene for the Pampa cytoplasm in winter rye that has been tapped from the Iranian primitive rye population Altevogt 14160. For this purpose, we have mapped 41 gene-derived markers to a 38.8 cM segment in the distal part of the long arm of chromosome 4R, which carries the restorer gene. Male fertility restoration was comprehensively analyzed in progenies of crosses between a male-sterile tester genotype and 21 recombinant as well as six non-recombinant BC4S2 lines. This approach allowed us to validate the position of this restorer gene, which we have designated Rfp3, on chromosome 4RL. Rfp3 was mapped within a 2.5 cM interval and cosegregated with the EST-derived marker c28385. The gene-derived conserved ortholog set (COS) markers enabled us to investigate the orthology of restorer genes originating from different genetic resources of rye as well as barley. The observed localization of Rfp3 and Rfm1 in a syntenic 4RL/6HS segment asks for further efforts towards cloning of both restorer genes as an option to study the mechanisms of male sterility and fertility restoration in cereals.

High accuracy of predicting hybrid performance of Fusarium head blight resistance by mid-parent values in wheat.

KEY MESSAGE: Mid-parent values of Fusarium head blight (FHB) resistance tested across several locations are a good predictor of hybrid performance caused by a preponderance of additive gene action in wheat. Hybrid breeding is intensively discussed as one solution to boost yield and yield stability including an enhanced biotic stress resistance. Our objectives were to investigate (1) the heterosis for Fusarium head blight (FHB) resistance, (2) the importance of general (GCA) vs. specific combining ability (SCA) for FHB resistance, and (3) the possibility to predict the FHB resistance of the hybrids by the parental means. We re-analyzed phenotypic data of a large population comprising 1604 hybrids and their 120 female and 15 male parental lines evaluated in inoculation trials across seven environments. Mid-parent heterosis of FHB severity averaged -9%, with a range from -36 to +35%. Mean better parent heterosis was 2% and 78 of the hybrids significantly (P < 0.05) outperformed the best commercial check variety included in our study. FHB resistance was not correlated with grain yield in healthy status for lines (r = 0.01) and hybrids (r = 0.09, P < 0.01). While a preponderance of GCA variance (P < 0.01) was found, SCA variance was not significantly different from zero. Accuracy to predict hybrid performance of FHB severity based on mid-parent values and on GCA effects was high (r = 0.70 and 0.86, respectively; P < 0.01). Similarly, line per se performance and GCA effects were significantly correlated (r = 0.77; P < 0.01). The substantial level of mid-parent heterosis in the desired direction of decreased susceptibility and the negligible better parent heterosis suggest that hybrids are an attractive alternative variety type to improve FHB resistance.

QTL mapping and comparative genome analysis of agronomic traits including grain yield in winter rye.

KEY MESSAGE: Genetic diversity in elite rye germplasm as well as F 2:3 testcross design enables fast QTL mapping to approach genes controlling grain yield, grain weight, tiller number and heading date in rye hybrids. Winter rye (Secale cereale L.) is a multipurpose cereal crop closely related to wheat, which offers the opportunity for a sustainable production of food and feed and which continues to emerge as a renewable energy source for the production of bioethanol and biomethane. Rye contributes to increase agricultural crop species diversity particularly in Central and Eastern Europe. In contrast to other small grain cereals, knowledge on the genetic architecture of complex inherited, agronomic important traits is yet limited for the outbreeding rye. We have performed a QTL analysis based on a F2:3 design and testcross performance of 258 experimental hybrids in multi-environmental field trials. A genetic linkage map covering 964.9 cM based on SSR, conserved-orthologous set (COS), and mixed-phase dominant DArT markers allowed to describe 22 QTL with significant effects for grain yield, heading date, tiller number, and thousand grain weight across seven environments. Using rye COS markers, orthologous segments for these traits have been identified in the rice genome, which carry cloned and functionally characterized rice genes. The initial genome scan described here together with the existing knowledge on candidate genes provides the basis for subsequent analyses of the genetic and molecular mechanisms underlying agronomic important traits in rye.