Meta-Quantitative Trait Loci Analysis and Candidate Gene Mining for Drought Tolerance-Associated Traits in Maize (Zea mays L.).

Drought is one of the major abiotic stresses with a severe negative impact on maize production globally. Understanding the genetic architecture of drought tolerance in maize is a crucial step towards the breeding of drought-tolerant varieties and a targeted exploitation of genetic resources. In this study, 511 quantitative trait loci (QTL) related to grain yield components, flowering time, and plant morphology under drought conditions, as well as drought tolerance index were collected from 27 published studies and then projected on the IBM2 2008 Neighbors reference map for meta-analysis. In total, 83 meta-QTL (MQTL) associated with drought tolerance in maize were identified, of which 20 were determined as core MQTL. The average confidence interval of MQTL was strongly reduced compared to that of the previously published QTL. Nearly half of the MQTL were confirmed by co-localized marker-trait associations from genome-wide association studies. Based on the alignment of rice proteins related to drought tolerance, 63 orthologous genes were identified near the maize MQTL. Furthermore, 583 candidate genes were identified within the 20 core MQTL regions and maize-rice homologous genes. Based on KEGG analysis of candidate genes, plant hormone signaling pathways were found to be significantly enriched. The signaling pathways can have direct or indirect effects on drought tolerance and also interact with other pathways. In conclusion, this study provides novel insights into the genetic and molecular mechanisms of drought tolerance in maize towards a more targeted improvement of this important trait in breeding.

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.

Maximization through optimization? On the relationship between hybrid performance and parental genetic distance.

Heterosis is the improved performance of hybrids compared with their parental components and is widely exploited in agriculture. According to quantitative genetic theory, genetic distance between parents at heterotic quantitative trait loci is required for heterosis, but how heterosis varies with genetic distance has remained elusive, despite intensive research on the topic. Experimental studies have often found a positive association between heterosis and genetic distance that, however, varied in strength. Most importantly, it has remained unclear whether heterosis increases continuously with genetic distance or whether there is an optimum genetic distance after which heterosis declines again. Here, we revisit the relationship between heterosis and genetic distance and provide perspectives on how to maximize heterosis and hybrid performance in breeding, as well as the consequences for the design of heterotic groups and the utilization of more exotic material and genetic resources.

Do lower nitrogen fertilization levels require breeding of different types of cultivars in triticale?

KEY MESSAGE: The comparably low genotype-by-nitrogen level interaction suggests that selection in early generations can be done under high-input conditions followed by selection under different nitrogen levels to identify genotypes ideally suited for the target environment. Breeding high-yielding, nitrogen-efficient crops is of utmost importance to achieve greater agricultural sustainability. The aim of this study was to evaluate nitrogen use efficiency (NUE) of triticale, investigate long-term genetic trends and the genetic architecture, and develop strategies for NUE improvement by breeding. For this, we evaluated 450 different triticale genotypes under four nitrogen fertilization levels in multi-environment field trials for grain yield, protein content, starch content and derived indices. Analysis of temporal trends revealed that modern cultivars are better in exploiting the available nitrogen. Genome-wide association mapping revealed a complex genetic architecture with many small-effect QTL and a high level of pleiotropy for NUE-related traits, in line with phenotypic correlations. Furthermore, the effect of some QTL was dependent on the nitrogen fertilization level. High correlations of each trait between N levels and the rather low genotype-by-N-level interaction variance showed that generally the same genotypes perform well over different N levels. Nevertheless, the best performing genotype was always a different one. Thus, selection in early generations can be done under high nitrogen fertilizer conditions as these provide a stronger differentiation, but the final selection in later generations should be conducted with a nitrogen fertilization as in the target environment.

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.

High-resolution association mapping with libraries of immortalized lines from ancestral landraces.

KEY MESSAGE: Association mapping with immortalized lines of landraces offers several advantages including a high mapping resolution, as demonstrated here in maize by identifying the causal variants underlying QTL for oil content and the metabolite allantoin. Landraces are traditional varieties of crops that present a valuable yet largely untapped reservoir of genetic variation to meet future challenges of agriculture. Here, we performed association mapping in a panel comprising 358 immortalized maize lines from six European Flint landraces. Linkage disequilibrium decayed much faster in the landraces than in the elite lines included for comparison, permitting a high mapping resolution. We demonstrate this by fine-mapping a quantitative trait locus (QTL) for oil content down to the phenylalanine insertion F469 in DGAT1-2 as the causal variant. For the metabolite allantoin, related to abiotic stress response, we identified promoter polymorphisms and differential expression of an allantoinase as putative cause of variation. Our results demonstrate the power of this approach to dissect QTL potentially down to the causal variants, toward the utilization of natural or engineered alleles in breeding. Moreover, we provide guidelines for studies using ancestral landraces for crop genetic research and breeding.

Genetic Dissection of Phosphorus Use Efficiency and Genotype-by-Environment Interaction in Maize.

Genotype-by-environment interaction (G-by-E) is a common but potentially problematic phenomenon in plant breeding. In this study, we investigated the genotypic performance and two measures of plasticity on a phenotypic and genetic level by assessing 234 maize doubled haploid lines from six populations for 15 traits in seven macro-environments with a focus on varying soil phosphorus levels. It was found intergenic regions contributed the most to the variation of phenotypic linear plasticity. For 15 traits, 124 and 31 quantitative trait loci (QTL) were identified for genotypic performance and phenotypic plasticity, respectively. Further, some genes associated with phosphorus use efficiency, such as Zm00001eb117170, Zm00001eb258520, and Zm00001eb265410, encode small ubiquitin-like modifier E3 ligase were identified. By significantly testing the main effect and G-by-E effect, 38 main QTL and 17 interaction QTL were identified, respectively, in which MQTL38 contained the gene Zm00001eb374120, and its effect was related to phosphorus concentration in the soil, the lower the concentration, the greater the effect. Differences in the size and sign of the QTL effect in multiple environments could account for G-by-E. At last, the superiority of G-by-E in genomic selection was observed. In summary, our findings will provide theoretical guidance for breeding P-efficient and broadly adaptable varieties.

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.

Genetic architecture underlying the expression of eight α-amylase trypsin inhibitors.

KEY MESSAGE: Wheat cultivars largely differ in the content and composition of ATI proteins, but heritability was quite low for six out of eight ATIs. The genetic architecture of ATI proteins is built up of few major and numerous small effect QTL. Amylase trypsin inhibitors (ATIs) are important allergens in baker's asthma and suspected triggers of non-celiac wheat sensitivity (NCWS) inducing intestinal and extra-intestinal inflammation. As studies on the expression and genetic architecture of ATI proteins in wheat are lacking, we evaluated 149 European old and modern bread wheat cultivars grown at three different field locations for their content of eight ATI proteins. Large differences in the content and composition of ATIs in the different cultivars were identified ranging from 3.76 pmol for ATI CM2 to 80.4 pmol for ATI 0.19, with up to 2.5-fold variation in CM-type and up to sixfold variation in mono/dimeric ATIs. Generally, heritability estimates were low except for ATI 0.28 and ATI CM2. ATI protein content showed a low correlation with quality traits commonly analyzed in wheat breeding. Similarly, no trends were found regarding ATI content in wheat cultivars originating from numerous countries and decades of breeding history. Genome-wide association mapping revealed a complex genetic architecture built of many small, few medium and two major quantitative trait loci (QTL). The major QTL were located on chromosomes 3B for ATI 0.19-like and 6B for ATI 0.28, explaining 70.6 and 68.7% of the genotypic variance, respectively. Within close physical proximity to the medium and major QTL, we identified eight potential candidate genes on the wheat reference genome encoding structurally related lipid transfer proteins. Consequently, selection and breeding of wheat cultivars with low ATI protein amounts appear difficult requiring other strategies to reduce ATI content in wheat products.

Optimum breeding strategies using genomic and phenotypic selection for the simultaneous improvement of two traits.

KEY MESSAGE: A breeding strategy combining genomic with one-stage phenotypic selection maximizes annual selection gain for net merit. Choice of the selection index strongly affects the selection gain expected in individual traits. Selection indices using genomic information have been proposed in crop-specific scenarios. Routine use of genomic selection (GS) for simultaneous improvement of multiple traits requires information about the impact of the available economic and logistic resources and genetic properties (variances, trait correlations, and prediction accuracies) of the breeding population on the expected selection gain. We extended the R package "selectiongain" from single trait to index selection to optimize and compare breeding strategies for simultaneous improvement of two traits. We focused on the expected annual selection gain (ΔGa) for traits differing in their genetic correlation, economic weights, variance components, and prediction accuracies of GS. For all scenarios considered, breeding strategy GSrapid (one-stage GS followed by one-stage phenotypic selection) achieved higher ΔGa than classical two-stage phenotypic selection, regardless of the index chosen to combine the two traits and the prediction accuracy of GS. The Smith-Hazel or base index delivered higher ΔGa for net merit and individual traits compared to selection by independent culling levels, whereas the restricted index led to lower ΔGa in net merit and divergent results for selection gain of individual traits. The differences among the indices depended strongly on the correlation of traits, their variance components, and economic weights, underpinning the importance of choosing the selection indices according to the goal of the breeding program. We demonstrate our theoretical derivations and extensions of the R package "selectiongain" with an example from hybrid wheat by designing indices to simultaneously improve grain yield and grain protein content or sedimentation volume.

Genetic Dissection of Phosphorus Use Efficiency in a Maize Association Population under Two P Levels in the Field.

Phosphorus (P) deficiency is an important challenge the world faces while having to increase crop yields. It is therefore necessary to select maize (Zea may L.) genotypes with high phosphorus use efficiency (PUE). Here, we extensively analyzed the biomass, grain yield, and PUE-related traits of 359 maize inbred lines grown under both low-P and normal-P conditions. A significant decrease in grain yield per plant and biomass, an increase in PUE under low-P condition, as well as significant correlations between the two treatments were observed. In a genome-wide association study, 49, 53, and 48 candidate genes were identified for eleven traits under low-P, normal-P conditions, and in low-P tolerance index (phenotype under low-P divided by phenotype under normal-P condition) datasets, respectively. Several gene ontology pathways were enriched for the genes identified under low-P condition. In addition, seven key genes related to phosphate transporter or stress response were molecularly characterized. Further analyses uncovered the favorable haplotype for several core genes, which is less prevalent in modern lines but often enriched in a specific subpopulation. Collectively, our research provides progress in the genetic dissection and molecular characterization of PUE in maize.

Misexpression of a transcriptional repressor candidate provides a molecular mechanism for the suppression of awns by Tipped 1 in wheat.

Awns are bristle-like structures formed at the tip of the lemma on the florets of some cereal grasses. Wild-type wheat is awned, but awnletted and awnless variants have been selected and nowadays all forms are cultivated. In this study, we dissected the genetic control underlying variation of this characteristic feature by association mapping in a large panel of 1110 winter wheat cultivars of worldwide origin. We identified the B1 (Tipped 1) locus on chromosome 5A as the major determinant of awnlessness globally. Using a combination of fine-mapping and expression analysis, we identified a putative C2H2 zinc finger protein with an EAR domain, characteristic of transcriptional repressors, as a likely candidate for Tipped 1. This gene was found to be up-regulated in awnless B1 compared with awned b1 plants, indicating that misexpression of this transcriptional regulator may contribute to the reduction of awn length in B1 plants. Taken together, our study provides an entry point towards a better molecular understanding of the evolution of morphological features in cereals through selection and breeding.

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.

Refining the genetic architecture of flag leaf glaucousness in wheat.

KEY MESSAGE: The cuticle is the plant's barrier against abiotic and biotic stresses, and the deposition of epicuticular wax crystals results in the scattering of light, an effect termed glaucousness. Here, we dissect the genetic architecture of flag leaf glaucousness in wheat toward a future targeted design of the cuticle. The cuticle serves as a barrier that protects plants against abiotic and biotic stresses. Differences in cuticle composition can be detected by the scattering of light on epicuticular wax crystals, which causes a phenotype termed glaucousness. In this study, we dissected the genetic architecture of flag leaf glaucousness in a panel of 1106 wheat cultivars of global origin. We observed a large genotypic variation, but the geographic pattern suggests that other wax layer characteristics besides glaucousness may be important in conferring tolerance to abiotic stresses such as heat and drought. Genome-wide association mapping identified two major quantitative trait loci (QTL) on chromosomes 3A and 2B. The latter corresponds to the W1 locus, but further characterization revealed that it is likely to contain additional QTL. The same holds true for the major QTL on 3A, which was also found to show an epistatic interaction with another locus located a few centiMorgan distal to it. Genome-wide prediction and the identification of a few additional putative QTL revealed that small-effect QTL also contribute to the trait. Collectively, our results illustrate the complexity of the genetic control of flag leaf glaucousness, with additive effects and epistasis, and lay the foundation for the cloning of the underlying genes toward a more targeted design of the cuticle by plant breeding.

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.

Hybrid durum wheat: heterosis of grain yield and quality traits and genetic architecture of anther extrusion.

KEY MESSAGE: Hybrid durum has a promising yield potential coupled with good quality, but the efficiency of hybrid seed production must be improved. Hybrid breeding is a tremendous success story in many crops, but has not yet made a breakthrough in wheat, mainly due to inefficient hybrid seed production. In this study, we investigated the heterosis for grain yield and important quality traits in durum wheat of 33 hybrids built up from 24 parental lines, as well as the variation in anther extrusion and its genetic architecture in a vast collection of Central European elite durum lines. Average mid-parent heterosis for grain yield was 5.8%, and the best hybrids had a more than one ton per hectare higher grain yield than the best line cultivars. Furthermore, hybrids had a higher grain yield than lines at a given level of protein content or sedimentation value, underpinning their potential for a sustainable agriculture. However, seed set in our experimental hybrid seed production was low. We therefore evaluated 315 elite durum lines for visual anther extrusion, which revealed a large genetic variance and a heritability of 0.66. Results from association mapping suggest a mainly quantitative inheritance of visual anther extrusion with few putative QTL being identified, the largest one explaining less than 20% of the genotypic variance. Genome-wide prediction taking the four largest putative QTL into account yielded a mean cross-validated prediction ability of 0.55. Consequently, breeding for improved male floral characteristics is feasible in durum wheat, but should be mainly based on phenotypic selection.

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.

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.

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.

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.