Different wheat loci are associated to heritable free asparagine content in grain grown under different water and nitrogen availability.

KEY MESSAGE: Different wheat QTLs were associated to the free asparagine content of grain grown in four different conditions. Environmental effects are a key factor when selecting for low acrylamide-forming potential. The amount of free asparagine in grain of a wheat genotype determines its potential to form harmful acrylamide in derivative food products. Here, we explored the variation in the free asparagine, aspartate, glutamine and glutamate contents of 485 accessions reflecting wheat worldwide diversity to define the genetic architecture governing the accumulation of these amino acids in grain. Accessions were grown under high and low nitrogen availability and in water-deficient and well-watered conditions, and plant and grain phenotypes were measured. Free amino acid contents of grain varied from 0.01 to 1.02 mg g-1 among genotypes in a highly heritable way that did not correlate strongly with grain yield, protein content, specific weight, thousand-kernel weight or heading date. Mean free asparagine content was 4% higher under high nitrogen and 3% higher in water-deficient conditions. After genotyping the accessions, single-locus and multi-locus genome-wide association study models were used to identify several QTLs for free asparagine content located on nine chromosomes. Each QTL was associated with a single amino acid and growing environment, and none of the QTLs colocalised with genes known to be involved in the corresponding amino acid metabolism. This suggests that free asparagine content is controlled by several loci with minor effects interacting with the environment. We conclude that breeding for reduced asparagine content is feasible, but should be firmly based on multi-environment field trials. KEY MESSAGE: Different wheat QTLs were associated to the free asparagine content of grain grown in four different conditions. Environmental effects are a key factor when selecting for low acrylamide-forming potential.

Genetic regions determine tolerance to nitrogen deficiency in European elite bread wheats grown under contrasting nitrogen stress scenarios.

KEY MESSAGE: Clustering 24 environments in four contrasting nitrogen stress scenarios enabled the detection of genetic regions determining tolerance to nitrogen deficiency in European elite bread wheats. Increasing the nitrogen use efficiency of wheat varieties is an important goal for breeding. However, most genetic studies of wheat grown at different nitrogen levels in the field report significant interactions with the genotype. The chromosomal regions possibly involved in these interactions are largely unknown. The objective of this study was to quantify the response of elite bread wheat cultivars to different nitrogen field stress scenarios and identify genomic regions involved in this response. For this purpose, 212 elite bread wheat varieties were grown in a multi-environment trial at different nitrogen levels. Genomic regions associated with grain yield, protein concentration and grain protein deviation responses to nitrogen deficiency were identified. Environments were clustered according to adjusted means for grain yield, yield components and grain protein concentration. Four nitrogen availability scenarios were identified: optimal condition, moderate early deficiency, severe late deficiency, and severe continuous deficiency. A large range of tolerance to nitrogen deficiency was observed among varieties, which were ranked differently in different nitrogen deficiency scenarios. The well-known negative correlation between grain yield and grain protein concentration also existed between their respective tolerance indices. Interestingly, the tolerance indices for grain yield and grain protein deviation were either null or weakly positive meaning that breeding for the two traits should be less difficult than expected. Twenty-two QTL regions were identified for the tolerance indices. By selecting associated markers, these regions may be selected separately or combined to improve the tolerance to N deficiency within a breeding programme.

Bread wheat (T. aestivum) variability: Phenotypic and genotypic data from 75 varieties.

Most bread wheat is consumed after processing, which mainly depends on the quantity and quality of protein in the grain. Storage protein content and composition particularly influence the end use quality of milled grain products. Storage proteins are components of the gluten network that confer dough viscoelasticity, an essential property for processing. To explore grain storage protein diversity, 75 bread wheat accessions were grown with two replicates each at two locations. Grains were harvested at maturity and samples were phenotyped for each site and each replicate plant. Grain hardness, thousand-kernel weight and grain nitrogen content were measured. The protein composition of flour from each replicate was characterised by reverse phase-high performance liquid chromatography (RP-HPLC). The molecular distribution of flour polymers was determined by asymmetric flow field-flow fractionation (AF4) and dough technological properties were assessed using a Glutomatic system and a Chopin alveograph. In addition, the 75 accessions were genotyped by the BreedWheat 35k genotyping array (Axiom TaBW35K) containing 34,746 single nucleotide polymorphism markers (SNPs). The dataset produced by this work includes six files with raw data, two files with protocols and figures. Data show the genotypic and phenotypic variabilities of the material used and can be used to explore genetic and environmental effects on traits involved in grain protein quality. This dataset is associated to the research article "Differences in bread protein digestibility traced to wheat cultivar traits" [1].

Phenomic selection in wheat breeding: prediction of the genotype-by-environment interaction in multi-environment breeding trials.

KEY MESSAGE: Phenomic prediction of wheat grain yield and heading date in different multi-environmental trial scenarios is accurate. Modelling the genotype-by-environment interaction effect using phenomic data is a potentially low-cost complement to genomic prediction. The performance of wheat cultivars in multi-environmental trials (MET) is difficult to predict because of the genotype-by-environment interactions (G × E). Phenomic selection is supposed to be efficient for modelling the G × E effect because it accounts for non-additive effects. Here, phenomic data are near-infrared (NIR) spectra obtained from plant material. While phenomic selection has recently been shown to accurately predict wheat grain yield in single environments, its accuracy needs to be investigated for MET. We used four datasets from two winter wheat breeding programs to test and compare the predictive abilities of phenomic and genomic models for grain yield and heading date in different MET scenarios. We also compared different methods to model the G × E using different covariance matrices based on spectra. On average, phenomic and genomic prediction abilities are similar in all different MET scenarios. Better predictive abilities were obtained when G × E effects were modelled with NIR spectra than without them, and it was better to use all the spectra of all genotypes in all environments for modelling the G × E. To facilitate the implementation of phenomic prediction, we tested MET designs where the NIR spectra were measured only on the genotype-environment combinations phenotyped for the target trait. Missing spectra were predicted with a weighted multivariate ridge regression. Intermediate predictive abilities for grain yield were obtained in a sparse testing scenario and for new genotypes, which shows that phenomic selection is an efficient and practicable prediction method for dealing with G × E.

Phenomic selection in wheat breeding: identification and optimisation of factors influencing prediction accuracy and comparison to genomic selection.

KEY MESSAGE: Phenomic selection is a promising alternative or complement to genomic selection in wheat breeding. Models combining spectra from different environments maximise the predictive ability of grain yield and heading date of wheat breeding lines. Phenomic selection (PS) is a recent breeding approach similar to genomic selection (GS) except that genotyping is replaced by near-infrared (NIR) spectroscopy. PS can potentially account for non-additive effects and has the major advantage of being low cost and high throughput. Factors influencing GS predictive abilities have been intensively studied, but little is known about PS. We tested and compared the abilities of PS and GS to predict grain yield and heading date from several datasets of bread wheat lines corresponding to the first or second years of trial evaluation from two breeding companies and one research institute in France. We evaluated several factors affecting PS predictive abilities including the possibility of combining spectra collected in different environments. A simple H-BLUP model predicted both traits with prediction ability from 0.26 to 0.62 and with an efficient computation time. Our results showed that the environments in which lines are grown had a crucial impact on predictive ability based on the spectra acquired and was specific to the trait considered. Models combining NIR spectra from different environments were the best PS models and were at least as accurate as GS in most of the datasets. Furthermore, a GH-BLUP model combining genotyping and NIR spectra was the best model of all (prediction ability from 0.31 to 0.73). We demonstrated also that as for GS, the size and the composition of the training set have a crucial impact on predictive ability. PS could therefore replace or complement GS for efficient wheat breeding programs.

Genome-wide prediction of three important traits in bread wheat.

Five genomic prediction models were applied to three wheat agronomic traits-grain yield, heading date and grain test weight-in three breeding populations, each comprising about 350 doubled haploid or recombinant inbred lines evaluated in three locations during a 3-year period. The prediction accuracy, measured as the correlation between genomic estimated breeding value and observed trait, was in the range of previously published values for yield (r = 0.2-0.5), a trait with relatively low heritability. Accuracies for heading date and test weight, with relatively high heritabilities, were about 0.70. There was no improvement of prediction accuracy when two or three breeding populations were merged into one for a larger training set (e.g., for yield r ranged between 0.11 and 0.40 in the respective populations and between 0.18 and 0.35 in the merged populations). Cross-population prediction, when one population was used as the training population set and another population was used as the validation set, resulted in no prediction accuracy. This lack of cross-population prediction accuracy cannot be explained by a lower level of relatedness between populations, as measured by a shared SNP similarity, since it was only slightly lower between than within populations. Simulation studies confirm that cross-prediction accuracy decreases as the proportion of shared QTLs decreases, which can be expected from a higher level of QTL × environment interactions.

A multi-environmental study of recent breeding progress on nitrogen use efficiency in wheat (Triticum aestivum L.).

KEY MESSAGE: By comparing 195 varieties in eight trials, this study assesses nitrogen use efficiency improvement in high and low nitrogen conditions in European winter wheat over the last 25 years. In a context where European agriculture practices have to deal with environmental concerns and nitrogen (N) fertiliser cost, nitrogen use efficiency (NUE) has to be improved. This study assessed genetic progress in winter wheat (Triticum aestivum L.) NUE. Two hundred and twenty-five European elite varieties were tested in four environments under two levels of N. Global genetic progress was assessed on additive genetic values and on genotype × N interaction, covering 25 years of European breeding. To avoid sampling bias, quality, precocity and plant height were added as covariates in the analyses when needed. Genotype × environment interactions were highly significant for all the traits studied to such an extent that no additive genetic effect was detected on N uptake. Genotype × N interactions were significant for yield, grain protein content (GPC), N concentration in straw, N utilisation, and NUE. Grain yield improvement (+0.45 % year(-1)) was independent of the N treatment. GPC was stable, thus grain nitrogen yield was improved (+0.39 % year(-1)). Genetic progress on N harvest index (+0.12 % year(-1)) and on N concentration in straw (-0.52 % year(-1)) possibly revealed improvement in N remobilisation. There has been an improvement of NUE additive genetic value (+0.33 % year(-1)) linked to better N utilisation (+0.20 % year(-1)). Improved yield stability was detected as a significant improvement of NUE in low compared to high N conditions. The application of these results to breeding programs is discussed.

Anthesis date mainly explained correlations between post-anthesis leaf senescence, grain yield, and grain protein concentration in a winter wheat population segregating for flowering time QTLs.

The genetic variability of the duration of leaf senescence during grain filling has been shown to affect both carbon and nitrogen acquisition. In particular, maintaining green leaves during grain filling possibly leads to increased grain yield, but its associated effect on grain protein concentration has not been studied. The aim of this study was to dissect the genetic factors contributing to correlations observed at the phenotypic level between leaf senescence during grain filling, grain protein concentration, and grain yield in winter wheat. With this aim in view, an analysis of quantitative trait locus (QTL) co-locations for these traits was carried out on a doubled haploid mapping population grown in a large multienvironment trial network. Pleiotropic QTLs affecting leaf senescence and grain yield and/or grain protein concentration were identified on chromosomes 2D, 2A, and 7D. These were associated with QTLs for anthesis date, showing that the phenotypic correlations with leaf senescence were mainly explained by flowering time in this wheat population. Study of the allelic effects of these pleiotropic QTLs showed that delaying leaf senescence was associated with increased grain yield or grain protein concentration depending on the environments considered. It is proposed that this differential effect of delaying leaf senescence on grain yield and grain protein concentration might be related to the nitrogen availability during the post-anthesis period. It is concluded that the benefit of using leaf senescence as a selection criterion to improve grain protein concentration in wheat cultivars may be limited and would largely depend on the targeted environments, particularly on their nitrogen availability during the post-anthesis period.

Deviation from the grain protein concentration-grain yield negative relationship is highly correlated to post-anthesis N uptake in winter wheat.

In plants, carbon and nitrogen (N) economies are intimately linked at the physiological and biochemical level. The strong genetic negative correlation between grain yield and grain protein concentration observed in various cereals is an illustration of this inter-relationship. Studies have shown that deviation from this negative relationship (grain protein deviation or GPD) has a genetic basis, but its physiological basis is still poorly understood. This study analysed data on 27 genotypes grown in multienvironment field trials, representing a wide range of agricultural practices and climatic conditions. The objective was to identify physiological processes related to the genetic variability in GPD. Under most environments, GPD was significantly related to post-anthesis N uptake independently of anthesis date and total N at anthesis. The underlying physiological trait might be related to genotypic differences in either access to soil N, regulation of N uptake by plant N status, or ability to maintain root activity during the grain-filling period. GPD is an interesting potential target in breeding as it appears to be relatively robust across different environments and would be valuable in increasing total N uptake by maturity.

A quantitative genetic study for elucidating the contribution of glutamine synthetase, glutamate dehydrogenase and other nitrogen-related physiological traits to the agronomic performance of common wheat.

To better understand the genetic variability for nitrogen use efficiency in winter wheat is a necessity in the frame of the present economic and ecological context. The objective of this work was to investigate the role of the enzymes glutamine synthetase (GS) and glutamate dehydrogenase (GDH), and other nitrogen (N)-related physiological traits in the control of agronomic performance in wheat. A quantitative genetics approach was developed using the Arche x Récital population of doubled haploid lines grown for 3 years in the field. GS and GDH activities, ammonium, amino acid and protein contents were measured at different stages of plant development in different organs after flowering. Significant genotypic effects were observed for all measured physiological and agronomical traits. Heading date was negatively correlated with ammonium, amino acid, protein contents and GS activity in the flag leaf lamina. Grain protein content was positively correlated with both ammonium and amino acid content, and to a lesser extent with soluble protein content and GS activity. A total of 148 quantitative trait loci (QTLs) were detected, 104 QTLs for physiological traits and 44 QTLs for agronomic traits. Twenty-six QTLs were detected for GDH activity spread over 13 chromosomes and 25 QTLs for GS activity spread over 12 chromosomes. We found only a co-localization between a QTL for GS activity and GSe, a structural gene encoding cytosolic GS on chromosome 4B. A coincidence between a QTL for GDH activity and a gene encoding GDH was also found on chromosome 2B. QTL regions combining both physiological and agronomical QTLs were mainly identified on linkage groups 2A, 2B, 2D, 5A, 5B and 5D. This approach allowed us to propose possible functions of physiological traits to explain the variation observed for agronomic traits including yield and its components.

Using genotype x nitrogen interaction variables to evaluate the QTL involved in wheat tolerance to nitrogen constraints.

Lower market prices and environmental concerns now orientate wheat (Triticum aestivum L.) breeding programs towards low input agricultural practices, and more particularly low nitrogen (N) input management. Such programs require knowledge of the genetic determination of plant reaction to N deficiency. Our aim was to characterize the genetic basis of N use efficiency and genotype x N interactions. The detection of QTL for grain yield, grain protein yield and their components was performed on a mapping population of 222 doubled haploid lines (DH), obtained from the cross between an N stress tolerant variety and an N stress sensitive variety. Experiments on the population were carried out in seven different environments, and in each case under high (N(+)) and low (N(-)) N supplies. In total, 233 QTL were detected for traits measured in each combination of environment and N supply, for "global" interaction variables (N(+)-N(-) and N(-)/N(+)), for sensitivity to N stress and for performance under N-limited conditions which were assessed using factorial regression parameters. The 233 QTL were detected on the whole genome and clustered into 82 genome regions. The dwarfing gene (Rht-B1), the photoperiod sensitivity gene (Ppd-D1) and the awns inhibitor gene (B1) coincided with regions that contained the highest numbers of QTL. Non-interactive QTL were detected on linkage groups 3D, 4B, 5A1 and 7B2. Interactive QTL were revealed by interaction or factorial regression variables (2D2, 3D, 5A1, 5D, 6A, 6B, 7B2) or by both variables (1B, 2A1, 2A2, 2D1, 4B, 5A2, 5B). The usefulness of QTL meta-analysis and factorial regression to study QTL x N interactions and the impact of Rht-B1, Ppd-D1 and B1, are discussed.

Combined agronomic and physiological aspects of nitrogen management in wheat highlight a central role for glutamine synthetase.

In wheat the period of grain filling is characterized by a transition for all vegetative organs from sink to source status. To study this transition, the progression of physiological markers and enzyme activities representative of nitrogen metabolism was monitored from the vegetative stage to maturity in different leaf stages and stem sections of two wheat (Triticum aestivum) cultivars grown at high and low levels of N fertilization. In the two cultivars examined, we found a general decrease of the metabolic and enzyme markers occurred during leaf ageing, and that this decrease was enhanced when plants were N-limited. Both correlation studies and principal components analysis (PCA) showed that there was a strong relationship among total N, chlorophyll, soluble protein, ammonium, amino acids and glutamine synthetase (GS) activity. The use of a marker such as GS activity to predict the N status of wheat, as a function of both plant development and N availability, is discussed with the aim of selecting wheat genotypes with better N-use efficiency.

Estimation of genetic parameters of a DH wheat population grown at different N stress levels characterized by probe genotypes.

Low market prices and environmental concerns in Europe favor lower input wheat production systems. To efficiently breed for new varieties adapted to low input management while maintaining high yield levels, our objective was to characterize the heritability and its components for yield and nitrogen traits under different nitrogen levels. Two hundred and twenty-two doubled-haploid (DH) lines from the cross between Arche (tolerant) and Récital (sensitive) were tested in France at four locations in 2000, and three in 2001, under high (N+) and low (N-) nitrogen supplies. The response of yield to the environment of four probe genotypes, the parents and two controls, were tested and used as descriptors of these environments. Grain yield (GY), its components, and grain and straw nitrogen, called nitrogen traits, were studied. A factorial regression was performed to assess the sensitivity (slope) of the DH lines to nitrogen stress and their performance to low nitrogen supply. An index based on the nitrogen nutrition index at flowering of the probe genotype Récital was the best descriptor of the environment stress. Heritabilities of yield and nitrogen traits for both nitrogen supplies were always above 0.6. When nitrogen stress increased, heritabilities decreased and genotype x nitrogen interaction variances increased. The decrease in heritability was mainly explained by a decrease in genetic variance. Genetic variation for sensitivity to nitrogen stress and performance under low nitrogen supply were shown in the population. GY decreased from 278 to 760 g/m2 per unit of nitrogen stress index increase and GY under moderate nitrogen stress varied from 340 to 613 g/m2. Those contrasted reactions revealed specific lines to include in breeding programs for improving GY under low nitrogen supply.