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From 1970 to nowadays, breeders have improved oilseed rape (Brassica napus) in many ways: creation of double low varieties (free of erucic acid and with a low content in glucosinolates), increase of the seed yield and quality of seeds and improvement of resistance to diseases. All this work helped oilseed rape to become one of the most produced oilseed crop in the world. However, this intensive breeding on quality has reduced the genetic diversity of winter oilseed rape. In this study, a group of four breeding companies (RAGT, Limagrain, Syngenta, Euralis) called “GIE Colza” has been working with INRAE (National Research Institute for Agriculture, Food and Environment, France) on the FSRSO project “Printiver”. This project aimed at enlarging the genetic variability available in winter-type oilseed rape through crossing with spring-type materials to create lines with a winter-type behavior (need of vernalization) and a genetic background that has introgressed spring-type genetic diversity. Two pools have been created and selected for their need of vernalization, date of flowering, yield and other agronomic traits. The Group tested these two pools in multilocal trials. The results show interestingper sevalue and combining ability.

International audience; Introduce the technique of haploid induction in plant breeding.

Key message: We propose new methods to predict genotype × environment interaction by selecting relevant environmental covariates and using an AMMI decomposition of the interaction. Abstract: Farmers are asked to produce more efficiently and to reduce their inputs in the context of climate change. They have to face more and more limiting factors that can combine in numerous stress scenarios. One solution to this challenge is to develop varieties adapted to specific environmental stress scenarios. For this, plant breeders can use genomic predictions coupled with environmental characterization to identify promising combinations of genes in relation to stress covariates. One way to do it is to take into account the genetic similarity between varieties and the similarity between environments within a mixed model framework. Molecular markers and environmental covariates (EC) can be used to estimate relevant covariance matrices. In the present study, based on a multi-environment trial of 220 European elite winter bread wheat (Triticum aestivum L.) varieties phenotyped in 42 environments, we compared reference regression models potentially including ECs, and proposed alternative models to increase prediction accuracy. We showed that selecting a subset of ECs, and estimating covariance matrices using an AMMI decomposition to benefit from the information brought by the phenotypic records of the training set are promising approaches to better predict genotype-by-environment interactions (G × E). We found that using a different kinship for the main genetic effect and the G × E effect increased prediction accuracy. Our study also demonstrates that integrative stress indexes simulated by crop growth models are more efficient to capture G × E than climatic covariates.

International audience; Wheat (Triticum aestivum L.) is the most widely cultivated crop worldwide and faces a wide range of stresses. To make effective crop improvement decisions, environmental characterization is of paramount importance. This study presents a new methodology for characterizing the environment that enables replacing the conventional arbitrary classification of the environment by a series of environmental covariates that capture and describe the stresses the plant encounters. Three CIMMYT bread wheat populations, combining complementary heat and drought adaptive traits, were grown over 3 yr in northwestern Mexico under limited irrigation, heat stress, and irrigated conditions. The network comprised 15 trials representing seven treatment x year combinations as experimental environments, referred to here as the "Environment". Environmental characterization was performed at the trial scale. Twelve stress thresholds related to eight environmental factors were combined to obtain 11 potential growth limiting factors. Thirty-three environmental covariates were obtained by calculating when these limiting factors occurred for each of three key-developmental-phases across all trials. Cluster analysis allowed grouping environmental covariates into six distinct clusters corresponding to six "environmental scenarios". One representative environmental covariate was extracted from each cluster and taken together explained more than 90% of the variance for yield in the Environment. Principal component analysis discriminated the seven experimental environments and identified its stress characteristics. We conclude that the method developed characterized the main stresses and their impact on average population performance, and the representative covariates efficiently replaced the Environment. As such, they will facilitate the dissection of genotype x environment interaction (GEI) for yield-related traits.

Multiparental designs combined with dense genotyping of parents have been proposed as a way to increase the diversity and resolution of quantitative trait loci (QTL) mapping studies, using methods combining linkage disequilibrium information with linkage analysis (LDLA). Two new nested association mapping designs adapted to European conditions were derived from the complementary dent and flint heterotic groups of maize (Zea mays L.). Ten biparental dent families (N = 841) and 11 biparental flint families (N = 811) were genotyped with 56,110 single nucleotide polymorphism markers and evaluated as test crosses with the central line of the reciprocal design for biomass yield, plant height, and precocity. Alleles at candidate QTL were defined as (i) parental alleles, (ii) haplotypic identity by descent, and (iii) single-marker groupings. Between five and 16 QTL were detected depending on the model, trait, and genetic group considered. In the flint design, a major QTL (R2 = 27%) with pleiotropic effects was detected on chromosome 10, whereas other QTL displayed milder effects (R2 < 10%). On average, the LDLA models detected more QTL but generally explained lower percentages of variance, consistent with the fact that most QTL display complex allelic series. Only 15% of the QTL were common to the two designs. A joint analysis of the two designs detected between 15 and 21 QTL for the five traits. Of these, between 27 for silking date and 41% for tasseling date were significant in both groups. Favorable allelic effects detected in both groups open perspectives for improving biomass production.

Gynogenesis is an asexual mode of reproduction common to animals and plants, in which stimuli from the sperm cell trigger the development of the unfertilized egg cell into a haploid embryo. Fine mapping restricted a major maize QTL (quantitative trait locus) responsible for the aptitude of inducer lines to trigger gynogenesis to a zone containing a single gene NOT LIKE DAD ( NLD ) coding for a patatin‐like phospholipase A. In all surveyed inducer lines, NLD carries a 4‐bp insertion leading to a predicted truncated protein. This frameshift mutation is responsible for haploid induction because complementation with wild‐type NLD abolishes the haploid induction capacity. Activity of the NLD promoter is restricted to mature pollen and pollen tube. The translational NLD::citrine fusion protein likely localizes to the sperm cell plasma membrane. In Arabidopsis roots, the truncated protein is no longer localized to the plasma membrane, contrary to the wild‐type NLD protein. In conclusion, an intact pollen‐specific phospholipase is required for successful sexual reproduction and its targeted disruption may allow establishing powerful haploid breeding tools in numerous crops. ![][1] The function of the patatin‐like phospholipase A NOT LIKE DAD (NLD) in the sperm cells of maize pollen is necessary for successful fertilization, whereas its disruption promotes the development of haploid embryos, which represent an important plant breeding tool. [1]: /embed/graphic-1.gif

Resilience to soil water deficit is a priority of many maize breeding programmes. Its genetic analysis requires estimators that characterise each genotype in a reproducible way. We have tested and compared three methods for that, namely (i) the ability of hybrids to maintain leaf growth in a range of soil water potentials in a phenotyping platform, (ii) a direct estimator of resilience of seed number to water deficit in a network of field experiments and (iii) classical methods involving tolerance indices and variance analysis. A drought index was obtained by averaging soil water potential, measured with tensiometers, for the phenological phase during which seed number is determined (evaluated for each individual hybrid in each site). It closely correlated with seed number in each of the 19 hybrids that were analysed over 14 environmental situations in France, Hungary and Chile. The slope of the regression line between drought index and seed number, established for each hybrid, was taken as an estimate of the resilience to soil water deficit of that hybrid. Resilience estimated in this way varied 2-fold in the set of studied hybrids, and correlated with resilience of leaf growth to soil water deficit in short-term experiments in the phenotyping platform. In contrast, the resilience estimated via the interaction genotype × watering treatment resulted non-significant because of large differences in drought indices between genotypes in a given watering treatment. We therefore propose that direct estimation of resilience to water deficit is feasible in the field with a minimum amount of environmental measurements. This provides estimations that are consistent with those measured in a phenotyping platform. The combination of both estimates provides insight into the mechanisms associated with resilience of each hybrid, potentially contributing to accelerate the genetic gain.

International audience; Relationships between kernel vitreousness and proteins and starch partitioning to the floury and vitreous regions of the endosperm were monitored in a set of 13 maize inbred lines. Decrease of protein contents from the vitreous to the floury endosperms were mainly assigned to a-zeins. Using Raman microspectroscopy, we observed a protein gradient from the periphery to the center of endosperms that well fitted with the inverse relationships between vitreousness and protein content of the vitreous and floury regions. In addition, Raman microspectroscopy highlighted an increase of starch crystallinity from the periphery to the center of the maize endosperms. This agrees with the higher amylose and associated lipid contents within starches of vitreous than in those of floury endosperms. Finally, starch granules from vitreous regions displayed more channels than the floury ones. These channels contain proteins that might favor adhesion of proteins to starch granules or granule granule contacts to form the close packing of the vitreous endosperm. Therefore transition from vitreous to floury endosperm is at least the result of both protein and starch gradients. These gradients are probably associated with metabolic gradients that have been observed during endosperm development. (C) 2016 Elsevier Ltd. All rights reserved.

Background Nitrogen use efficiency is an important breeding trait that can be modified to improve the sustainability of many crop species used in agriculture. Rapeseed is a major oil crop with low nitrogen use efficiency, making its production highly dependent on nitrogen input. This complex trait is suspected to be sensitive to genotype × environment interactions, especially genotype × nitrogen interactions. Therefore, phenotyping diverse rapeseed populations under a dense network of trials is a powerful approach to study nitrogen use efficiency in this crop. The present study aimed to determine the quantitative trait loci (QTL) associated with yield in winter oilseed rape and to assess the stability of these regions under contrasting nitrogen conditions for the purpose of increasing nitrogen use efficiency. Results Genome-wide association studies and linkage analyses were performed on two diversity sets and two doubled-haploid populations. These populations were densely genotyped, and yield-related traits were scored in a multi-environment design including seven French locations, six growing seasons (2009 to 2014) and two nitrogen nutrition levels (optimal versus limited). Very few genotype × nitrogen interactions were detected, and a large proportion of the QTL were stable across nitrogen nutrition conditions. In contrast, strong genotype × trial interactions in which most of the QTL were specific to a single trial were found. To obtain further insight into the QTL × environment interactions, genetic analyses of ecovalence were performed to identify the genomic regions contributing to the genotype × nitrogen and genotype × trial interactions. Fifty-one critical genomic regions contributing to the additive genetic control of yield-associated traits were identified, and the structural organization of these regions in the genome was investigated. Conclusions Our results demonstrated that the effect of the trial was greater than the effect of nitrogen nutrition levels on seed yield-related traits under our experimental conditions. Nevertheless, critical genomic regions associated with yield that were stable across environments were identified in rapeseed. Electronic supplementary material The online version of this article (doi:10.1186/s12863-016-0432-z) contains supplementary material, which is available to authorized users.

Pairwise distance data for maize (Zea mays L.) inbred lines generated using sets of single nucleotide polymorphisms (SNPs) selected from a 50k Infinium array were compared with pairwise distances generated using a set of 163 simple sequence repeat (SSR) loci previously identified to help determine essentially derived variety (EDV) status (UPOV, 1991). Final comparisons were made using 26,874 SNPs after discarding SNPs with insufficient data quality or vulnerability to ascertainment bias. Inbred lines developed in the United States or in western Europe that had been previously published to establish SSR-based thresholds provided the means to determine equivalent SNP-based protocols. Use of 3072 SNPs selected to provide even genomic coverage according to genetic and physical maps provided robust, precise, high discrimination among inbred lines with consistent zonal classification with up to 20% missing data. Comparisons of intercepts and slopes for SSR and SNP inbred pairwise distance data translated the 82% SSR green-orange similarity threshold to 91% using SNPs and the 90% SSR orange-red threshold to 95% using SNPs. Information required to conduct analyses using these 3072 SNPS is presented.

A new method for characterizing the grinding characteristics of wheat grain is described. A micromill was designed for this purpose and equipped with on-line torque transducers to obtain accurate measurements of mechanical energy consumption during milling. This micromill can be used for testing the milling performance of small quantities of grain (100 g). It can distinguish between different types of wheat grain (soft wheat, hard wheat, durum wheat) on the basis of total specific energy during milling. Wheat characterization can be enhanced by taking particle sizes of the milled products into account. A milling index based on energy consumption and particle size reduction was developed to characterize wheat behavior during milling. This index had a high discriminatory potential, ranging from 100 kJ/kg for soft wheat flour to 600 kJ/kg for durum wheat flour. This micromill directly measures the grinding resistance of wheat kernels as a function of both the kernel hardness and vitreousness, contra...

The efficiency of marker-assisted prediction of phenotypes has been studied intensively for different types of plant breeding populations. However, one remaining question is how to incorporate and counterbalance information from biparental and multiparental populations into model training for genome-wide prediction. To address this question, we evaluated testcross performance of 1652 doubled-haploid maize (Zea mays L.) lines that were genotyped with 56,110 single nucleotide polymorphism markers and phenotyped for five agronomic traits in four to six European environments. The lines are arranged in two diverse half-sib panels representing two major European heterotic germplasm pools. The data set contains 10 related biparental dent families and 11 related biparental flint families generated from crosses of maize lines important for European maize breeding. With this new data set we analyzed genome-based best linear unbiased prediction in different validation schemes and compositions of estimation and test sets. Further, we theoretically and empirically investigated marker linkage phases across multiparental populations. In general, predictive abilities similar to or higher than those within biparental families could be achieved by combining several half-sib families in the estimation set. For the majority of families, 375 half-sib lines in the estimation set were sufficient to reach the same predictive performance of biomass yield as an estimation set of 50 full-sib lines. In contrast, prediction across heterotic pools was not possible for most cases. Our findings are important for experimental design in genome-based prediction as they provide guidelines for the genetic structure and required sample size of data sets used for model training.

Association mapping has permitted the discovery of major QTL in many species. It can be applied to existing populations and, as a consequence, it is generally necessary to take into account structure and relatedness among individuals in the statistical model to control false positives. We analytically studied power in association studies by computing noncentrality parameter of the tests and its relationship with parameters characterizing diversity (genetic differentiation between groups and allele frequencies) and kinship between individuals. Investigation of three different maize diversity panels genotyped with the 50k SNPs array highlighted contrasted average power among panels and revealed gaps of power of classical mixed models in regions with high linkage disequilibrium (LD). These gaps could be related to the fact that markers are used for both testing association and estimating relatedness. We thus considered two alternative approaches to estimating the kinship matrix to recover power in regions of high LD. In the first one, we estimated the kinship with all the markers that are not located on the same chromosome than the tested SNP. In the second one, correlation between markers was taken into account to weight the contribution of each marker to the kinship. Simulations revealed that these two approaches were efficient to control false positives and were more powerful than classical models.

International audience; In oilseed rape (Brassica napus L.) like in most oleaginous crops, seed oil content is the main qualitative determinant that confers its economic value to the harvest. Increasing seed oil content is then still an important objective in oilseed rape breeding. In the objective to get better knowledge on the genetic determinism of seed oil content, a genetic study was undertaken in two genetic backgrounds. Two populations of 445 and a 242 doubled haploids (DH) derived from the crosses "Darmor-bzh" x "Yudal" (DY) and "Rapid"" x "NSL96/25" (RNSL), respectively, were genotyped and evaluated for oil content in different trials. QTL mapping in the two populations indicate that additive effects are the main factors contributing to variation in oil content. A total of 14 and 10 genomic regions were involved in seed oil content in DY and RNSL populations, respectively, of which five and two were consistently revealed across the three trials performed for each population. Most of the QTL detected were not colocalised to QTL involved in flowering time. Few epistatic QTL involved regions that carry additive QTL in one or the other population. Only one QTL located on linkage group N3 was potentially common to the two populations. The comparisons of the QTL location in this study and in the literature showed that: (i) some of the QTL were more consistently revealed across different genetic backgrounds. The QTL on N3 was revealed in all the studies and the QTL on N1, N8 and N13 were revealed in three studies out of five, (ii) some of the QTL were specific to one genetic background with potentially some original alleles, (iii) some QTL were located in homeologous regions, and (iv) some of the regions carrying QTL for oil content in oilseed rape and in Arabidopsis could be collinear. These results show the possibility to combine favourable alleles at different QTL to increase seed oil content and to use Arabidopsis genomic data to derive markers for oilseed rape QTL and identify candidate genes, as well as the interest to combine information from different segregating populations in order to build a consolidated map of QTL involved in a specific trait.

The maximum rate and duration for grain dry matter (DM) and nitrogen (N) accumulation were evaluated in 194 recombinant inbred lines (RILs) from a cross between the two French wheat cultivars Récital and Renan. These cultivars were previously identified as having contrasting kinetics of grain DM and N accumulation. Grain protein composition was analysed by capillary electrophoresis (CE), which enabled quantification of the different storage protein fractions (alphabetagamma-gliadins, omega-gliadins, LMW glutenins, HMW glutenins, and each of their subunits). Correlation analyses revealed that DM and N accumulation rates were closely correlated and repeatable over several years, which was not the case for DM and N accumulation durations, and that protein composition was primarily influenced by the N accumulation rate. This was particularly true for the LMW-glutenins and the alphabetagamma-gliadins, the most abundant protein fractions. A genetic map of 254 molecular markers covering nearly 80% of the wheat genome was used for quantitative trait loci (QTL) analysis. A total of seven QTLs were found. Five QTLs were significantly associated with the kinetics of DM and N accumulation, and two of them also influenced protein composition. Two QTLs affected only the protein composition. One major QTL explained more than 70% of the total variation in HMW-GS Glu1B-x content.

International audience; The objectives of this experiment were to study the effects of corn hybrid and chop length of whole-plant corn silage (WPCS) on intake, and to quantify ruminal digestive processes that could help to identify factors limiting dry matter intake (DMI). Eight lactating cows and 4 dry cows fitted with a ruminal cannula were randomly assigned to 4 treatments in a 4 × 4 Latin square design with replications for lactating cows and without for ruminally cannulated cows. Treatments were fed in a total mixed ration (TMR) containing 75% WPCS and 25% concentrate. The 4 WPCS differed in the characteristics of 2 conventional hybrids, less degradable vs. more degradable in the rumen and in the chop length, fine vs. coarse. The DMI was measured for all cows, and digestion measurements and chewing activities were recorded with the cannulated cows. With lactating cows, DMI and milk yield varied with corn hybrids but not with chop length. The less degradable hybrid in the rumen was the less ingested. Dry matter intake of dry ears followed the same trend, but the differences between hybrids were lower than that observed with the lactating cows and not significant. Dry matter digestibility in the total tract and rumen fill were not different between hybrids. Ruminal mean retention time was greater for the least degradable hybrid. The rumen fill capacity could explain intake differences between hybrids. Ingestive mastication strongly reduced particle size, and the efficiency of particle size reduction was more important with the coarsely chopped WPCS than the finely chopped ones. The small differences in particle size of material entering the rumen after mastication of WPCS during eating might explain the lack of response for decreasing chop length. Because the rumen fill decreased with the decrease in chop length, rumen fill could not be the only factor responsible for DMI control of WPCS.

International audience; The increasing availability of expressed sequence tags (ESTs) in wheat (Triticum aestivum) and related cereals provides a valuable resource of non-anonymous DNA molecular markers. We examined 170,746 wheat ESTs from the public (International Triticeae EST Cooperative) and Génoplante databases, previously clustered in contigs, for the presence of di- to hexanucleotide simple sequence repeats (SSRs). Analysis of 46,510 contigs identified 3,530 SSRs, which represented 7.5% of the total number of contigs. Only 74% of the sequences allowed primer pairs to be designed, 70% led to an amplification product, mainly of a high quality (68%), and 53% exhibited polymorphism for at least one cultivar among the eight tested. Even though dinucleotide SSRs were less represented than trinucleotide SSRs (15.5% versus 66.5%, respectively), the former showed a much higher polymorphism level (83% versus 46%). The effect of the number and type of repeats is also discussed. The development of new EST-SSRs markers will have important implications for the genetic analysis and exploitation of the genetic resources of wheat and related species and will provide a more direct estimate of functional diversity.