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Implementation of genomic tools is desirable to increase the efficiency of apple breeding. The apple reference population (apple REFPOP) proved useful for rediscovering loci, estimating genomic prediction accuracy, and studying genotype by environment interactions (G×E). Here we show contrasting genetic architecture and genomic prediction accuracies for 30 quantitative traits across up to six European locations using the apple REFPOP. A total of 59 stable and 277 location-specific associations were found using GWAS, 69.2% of which are novel when compared with 41 reviewed publications. Average genomic prediction accuracies of 0.18–0.88 were estimated using single-environment univariate, single-environment multivariate, multi-environment univariate, and multi-environment multivariate models. The G×E accounted for up to 24% of the phenotypic variability. This most comprehensive genomic study in apple in terms of trait-environment combinations provided knowledge of trait biology and prediction models that can be readily applied for marker-assisted or genomic selection, thus facilitating increased breeding efficiency.

Background Single nucleotide polymorphism (SNP) array technology has been increasingly used to generate large quantities of SNP data for use in genetic studies. As new arrays are developed to take advantage of new technology and of improved probe design using new genome sequence and panel data, a need to integrate data from different arrays and array platforms has arisen. This study was undertaken in view of our need for an integrated high-quality dataset of Illumina Infinium® 20 K and Affymetrix Axiom® 480 K SNP array data in apple (Malus × domestica). In this study, we qualify and quantify the compatibility of SNP calling, defined as SNP calls that are both accurate and concordant, across both arrays by two approaches. First, the concordance of SNP calls was evaluated using a set of 417 duplicate individuals genotyped on both arrays starting from a set of 10,295 robust SNPs on the Infinium array. Next, the accuracy of the SNP calls was evaluated on additional germplasm (n = 3141) from both arrays using Mendelian inconsistent and consistent errors across thousands of pedigree links. While performing this work, we took the opportunity to evaluate reasons for probe failure and observed discordant SNP calls. Results Concordance among the duplicate individuals was on average of 97.1% across 10,295 SNPs. Of these SNPs, 35% had discordant call(s) that were further curated, leading to a final set of 8412 (81.7%) SNPs that were deemed compatible. Compatibility was highly influenced by the presence of alternate probe binding locations and secondary polymorphisms. The impact of the latter was highly influenced by their number and proximity to the 3′ end of the probe. Conclusions The Infinium and Axiom SNP array data were mostly compatible. However, data integration required intense data filtering and curation. This work resulted in a workflow and information that may be of use in other data integration efforts. Such an in-depth analysis of array concordance and accuracy as ours has not been previously described in the literature and will be useful in future work on SNP array data integration and interpretation, and in probe/platform development.

Genomic selection is an attractive strategy for apple breeding that could reduce the length of breeding cycles. A possible limitation to the practical implementation of this approach lies in the creation of a training set large and diverse enough to ensure accurate predictions. In this study, we investigated the potential of combining two available populations, i.e. genetic resources and elite material, in order to obtain a large training set with a high genetic diversity. We compared the predictive ability of genomic predictions within-population, across-population or when combining both populations, and tested a model accounting for population-specific marker effects in this last case. The obtained predictive abilities were moderate to high according to the studied trait and were always highest when the two populations were combined into a unique training set. We also investigated the potential of such a training set to predict hybrids resulting from crosses between the two populations, with a focus on the method to design the training set and the best proportion of each population to optimize predictions. The measured predictive abilities were very similar for all the proportions, except for the extreme cases where only one of the two populations was used in the training set, in which case predictive abilities could be lower than when using both populations. Using an optimization algorithm to choose the genotypes in the training set also led to higher predictive abilities than when the genotypes were chosen at random. Our results provide guidelines to initiate breeding programs that use genomic selection when the implementation of the training set is a limitation.

International audience; A wealth of previously unknown pedigree information has been generated for apple (Malus × domestica) through recent studies and an ongoing pedigree identification project using SNP array data. This information has been postulated to be useful in a number of ways for germplasm collections and breeding programs. For example, pedigree information is an important part of genetic characterization of material in germplasm collections. Germplasm collections often seek to preserve cultivars that currently lack commercial relevance but have regional or historical significance or are phenotypically interesting. Pedigree information is often limited on such material. With pedigree information, an accurate genetic structure of these collections can be conveyed to breeders who wish to incorporate novel germplasm into new cultivars. To illustrate ways in which this newly generated pedigree information can be used, we provide examples involving accessions from the germplasm collection Ökowerk and the breeding association “apfel:gut e.V.”, which focus in the development of apples for regional organic production. Both organizations are located in northern Germany. Despite focusing on regional apple cultivars and genetic diversity, many of their accessions and breeding lines are common, cosmopolitan, and foundational cultivars. However, the SNP-based analyses also reveal regionally specific founders, not true-to-type accessions, and genetically unique historical cultivars. This new information has benefitted these organizations by providing genetic characterization that was previously lacking, enabling them to better utilize these genetic resources. Additionally, this information will also be useful in the context of an ongoing larger scale apple pedigree reconstruction project.

Pedigree information is of fundamental importance in breeding programs and related genetics efforts. However, many individuals have unknown pedigrees. While methods to identify and confirm direct parent–offspring relationships are routine, those for other types of close relationships have yet to be effectively and widely implemented with plants, due to complications such as asexual propagation and extensive inbreeding. The objective of this study was to develop and demonstrate methods that support complex pedigree reconstruction via the total length of identical by state haplotypes (referred to in this study as “summed potential lengths of shared haplotypes”, SPLoSH). A custom Python script, HapShared, was developed to generate SPLoSH data in apple and sweet cherry. HapShared was used to establish empirical distributions of SPLoSH data for known relationships in these crops. These distributions were then used to estimate previously unknown relationships. Case studies in each crop demonstrated various pedigree reconstruction scenarios using SPLoSH data. For cherry, a full-sib relationship was deduced for ‘Emperor Francis, and ‘Schmidt’, a half-sib relationship for ‘Van’ and ‘Windsor’, and the paternal grandparents of ‘Stella’ were confirmed. For apple, 29 cultivars were found to share an unknown parent, the pedigree of the unknown parent of ‘Cox’s Pomona’ was reconstructed, and ‘Fameuse’ was deduced to be a likely grandparent of ‘McIntosh’. Key genetic resources that enabled this empirical study were large genome-wide SNP array datasets, integrated genetic maps, and previously identified pedigree relationships. Crops with similar resources are also expected to benefit from using HapShared for empowering pedigree reconstruction.

Breeding of apple is a long-term and costly process due to the time and space requirements for screening selection candidates. Genomics-assisted breeding utilizes genomic and phenotypic information to increase the selection efficiency in breeding programs, and measurements of phenotypes in different environments can facilitate the application of the approach under various climatic conditions. Here we present an apple reference population: the apple REFPOP, a large collection formed of 534 genotypes planted in six European countries, as a unique tool to accelerate apple breeding. The population consisted of 269 accessions and 265 progeny from 27 parental combinations, representing the diversity in cultivated apple and current European breeding material, respectively. A high-density genome-wide dataset of 303,239 SNPs was produced as a combined output of two SNP arrays of different densities using marker imputation with an imputation accuracy of 0.95. Based on the genotypic data, linkage disequilibrium was low and population structure was weak. Two well-studied phenological traits of horticultural importance were measured. We found marker–trait associations in several previously identified genomic regions and maximum predictive abilities of 0.57 and 0.75 for floral emergence and harvest date, respectively. With decreasing SNP density, the detection of significant marker–trait associations varied depending on trait architecture. Regardless of the trait, 10,000 SNPs sufficed to maximize genomic prediction ability. We confirm the suitability of the apple REFPOP design for genomics-assisted breeding, especially for breeding programs using related germplasm, and emphasize the advantages of a coordinated and multinational effort for customizing apple breeding methods in the genomics era., This work was partially supported by the project RIS3CAT (COTPA-FRUIT3CAT) financed by the European Regional Development Fund through the FEDER frame of Catalonia 2014–2020 and by the CERCA Program from Generalitat de Catalunya. We acknowledge financial support from the Spanish Ministry of Economy and Competitiveness through the “Severo Ochoa Program for Centres of Excellence in R&D” 2016–2019 (SEV‐20150533). This work has been partially funded by the EU seventh Framework Program, the FruitBreedomics project No. 265582: Integrated Approach for Increasing Breeding Efficiency in Fruit Tree Crops.

Texture is a complex trait and a major component of fruit quality in apple. While the major effect of MdPG1, a gene controlling firmness, has already been exploited in elite cultivars, the genetic basis of crispness remains poorly understood. To further improve fruit texture, harnessing loci with minor effects via genomic selection is therefore necessary. In this study, we measured acoustic and mechanical features in 537 genotypes to dissect the firmness and crispness components of fruit texture. Predictions of across-year phenotypic values for these components were calculated using a model calibrated with 8,294 SNP markers. The best prediction accuracies following cross-validations within the training set of 259 genotypes were obtained for the acoustic linear distance (0.64). Predictions for biparental families using the entire training set varied from low to high accuracy, depending on the family considered. While adding siblings or half-siblings into the training set did not clearly improve predictions, we performed an optimization of the training set size and composition for each validation set. This allowed us to increase prediction accuracies by 0.17 on average, with a maximal accuracy of 0.81 when predicting firmness in the ‘Gala’ × ‘Pink Lady’ family. Our results therefore identified key genetic parameters to consider when deploying genomic selection for texture in apple. In particular, we advise to rely on a large training population, with high phenotypic variability from which a ‘tailored training population’ can be extracted using a priori information on genetic relatedness, in order to predict a specific target population.

Texture plays a major role in the determination of fruit quality in apple. Due to its physiological and economic relevance, this trait has been largely investigated, leading to the fixation of the major gene PG1 controlling firmness in elite cultivars. To further improve fruit texture, the targeting of an undisclosed reservoir of loci with minor effects is compelling. In this work, we aimed to unlock this potential with a genomic selection approach by predicting fruit acoustic and mechanical features as obtained with a TA.XTplus texture analyzer in 537 individuals genotyped with 8,294 SNP markers. The best prediction accuracies following cross-validations within the training set (TRS) of 259 individuals were obtained for the acoustic linear distance (0.64). Prediction accuracy was further improved through the optimization of TRS size and composition according to the test set. With this strategy, a maximal accuracy of 0.81 was obtained when predicting the synthetic trait PC1 in the family ‘Gala × Pink Lady’. We discuss the impact of genetic relatedness and clustering on trait variability and predictability. Moreover, we demonstrated the need for a comprehensive dissection of the complex texture phenotype and the potentiality of using genomic selection to improve fruit quality in apple.HighlightA genomic selection study, together with the optimization of the training set, demonstrated the possibility to accurately predict texture sub-traits valuable for the amelioration of fruit quality in apple.

Evaluer la sélection génomique au sein de croisements bi-parentaux d’espèces pérennes fruitières génotypés par séquençage : point d’étape du projet FruitSelGen. Séminaire SelGen 2017 : "La sélection génomique, bilan et perspectives"

International audience; The aim of Genome Wide Association Studies (GWAS) is to identify markers in tight linkage disequilibrium with loci controlling quantitative trait variation. These markers can then be used in marker-assisted selection (MAS) in fruit crops such as apple. The GWAS approach involves both phenotyping of a large population of mostly unrelated individuals for the traits of interest, and genotyping at high marker density. In the EU-FP7 project FruitBreedomics, almost 1,200 European diploid dessert apple accessions (old and/or local cultivars) from six germplasm collections were genotyped with the Affymetrix Axiom_Apple480K array (487,000 SNPs). Phenotypic data on a large number of traits have been gathered during the project. Here we focus on flowering period and harvesting date. Knowledge of the genetic control of these traits is necessary to develop cultivars that can face the challenges imposed by global climate change and to target cultivar development as a function of a prolonged vegetation period in the production regions. Different models were tested, including control for effects of population structure and relatedness between cultivars. The full model, controlling for both structure and relatedness, was shown to be the most appropriate to avoid spurious marker-trait associations. When analyzing data over all collections, one significant marker-trait association was obtained for each trait, on chromosomes 9 and 3, for flowering period and harvesting date, respectively. Thereby, genomic locations previously identified in bi-parental populations could now be confirmed for a genetically diverse germplasm.

Since apple fruit skin reddens poorly under warmer climates, new apple cultivars are desired that are adapted to global warming in terms of bearing well-reddened fruit. We developed a simple sequence repeat marker, Mdo.chr9.4, which is suitable for red skin color selection. It amplified four alleles (Mdo.chr9.4-R-0, Mdo.chr9.4-Y-3, Mdo.chr9.4-Y-9, and Mdo.chr9.4-Y-15) distinguished by length. Mdo. chr9.4-R-0 associated with MdMYB1-1 which confers red fruit skin. The presence of Mdo. chr9.4-R-0 was consistent with empirical skin color in all 160 tested accessions. Mdo. chr9.4 was identified as the only significant marker that contributed to red skin color intensity by a genome wide association study (GWAS), and it accounted for 52.0% of phenotypic variation, confirming that MdMYB1 was the major and principal determinant of fruit skin color in apples. Individuals with a homozygous state of Mdo.chr9.4-R-0 (dose 2) were significantly redder than those showing a heterozygote state (dose 1) in both the accession set and full-sib families, indicating a partially dominant effect of MdMYB1-1. Therefore, the selection of dose 2 individuals would target individuals with intensive red skin. We applied Mdo.chr9.4 to several application populations using a time and cost-efficient genotyping system developed in the present study. This system, along with Mdo.chr9.4, provide advanced marker-assisted breeding for intensive red skin color apples adapted to a global warming climate.

Eyespot disease caused by the soil-borne facultative fungi Oculimacula yallundae and O. acuformis is the major component of the stem-base disease complex of wheat in temperate regions of the world with a cool and wet climate. In this review, we focus on results of genetic studies concerning both partners of the host-pathogen interaction. This comprises analyses of genetic diversity of the pathogen and identification of particular genes within it, evaluation and screening methods for host resistance, resistance sources and genetics of these resistances, breeding of resistant cultivars in wheat, and application of genetic markers in tagging and tracking of eyespot resistance genes. We also attempt to foresee some of the key issues and developments that may occur in future. The identification of markers tightly linked to eyespot resistance genes is the important research focus opening the door to marker-assisted selection of resistant varieties.

International audience; Powdery mildew (Blumeria graminis f. sp. tritici) is one of the major diseases of wheat (Triticum aestivum). Adult plant resistance (APR) to powdery mildew is considered more durable than resistance conferred by major race-specific resistance genes. The objective of the present study was a better understanding of the genetic basis of APR in RE714 by means of QTL analysis of several resistance scores along the growing season. A population of 160 recombinant inbred lines obtained from the cross between RE714 and Hardi (susceptible) was assessed for APR under natural infection conditions during 3 years and a genetic map with whole genome coverage was developed with microsatellite and AFLP markers in this population. Two major QTL on chromosomes 5D and 6A were detected each year, and 6 minor QTL were detected only in 1 or 2 years. The QTL on chromosome 5D was detected during all the growing season each year and its R 2 value varied between 8.5 and 56.3%, whereas the QTL on chromosome 6A was detected at 1–4 scoring dates in the 3 years, and its R 2 value varied between 6.1 and 20.5%. The two QTL explained between 24.4 and 52.1% of the phenotypic variance for AUDPC, depending on the year. The models including QTL and cofactors in the composite interval mapping explained between 29 and 72% of the variance. The molecular markers linked to the two major QTL could be used in marker-assisted selection for adult plant resistance to powdery mildew.

Cultivated apple (Malus x domestica Borkh.) is one of the most important fruit crops in temperate regions, and has great economic and cultural value. The apple genome is highly heterozygous and has undergone a recent duplication which, combined with a rapid linkage disequilibrium decay, makes it difficult to perform genome-wide association (GWA) studies. Single nucleotide polymorphism arrays offer highly multiplexed assays at a relatively low cost per data point and can be a valid tool for the identification of the markers associated with traits of interest. Here, we describe the development and validation of a 487K SNP Affymetrix Axiom (R) genotyping array for apple and discuss its potential applications. The array has been built from the high-depth resequencing of 63 different cultivars covering most of the genetic diversity in cultivated apple. The SNPs were chosen by applying a focal points approach to enrich genic regions, but also to reach a uniform coverage of non-genic regions. A total of 1324 apple accessions, including the 92 progenies of two mapping populations, have been genotyped with the Axiom (R) Apple480K to assess the effectiveness of the array. A large majority of SNPs (359994 or 74%) fell in the stringent class of poly high resolution polymorphisms. We also devised a filtering procedure to identify a subset of 275K very robust markers that can be safely used for germplasm surveys in apple. The Axiom (R) Apple480K has now been commercially released both for public and proprietary use and will likely be a reference tool for GWA studies in apple.

International audience; Quantitative trait loci (QTL) mapping approaches rely on the correct ordering of molecular markers along the chromosomes, which can be obtained from genetic linkage maps or a reference genome sequence. For apple (Malus domestica Borkh), the genome sequence v1 and v2 could not meet this need; therefore, a novel approach was devised to develop a dense genetic linkage map, providing the most reliable marker-loci order for the highest possible number of markers. The approach was based on four strategies: (i) the use of multiple full-sib families, (ii) the reduction of missing information through the use of HaploBlocks and alternative calling procedures for single-nucleotide polymorphism (SNP) markers, (iii) the construction of a single backcross-type data set including all families, and (iv) a two-step map generation procedure based on the sequential inclusion of markers. The map comprises 15 417 SNP markers, clustered in 3 K HaploBlock markers spanning 1 267 cM, with an average distance between adjacent markers of 0.37 cM and a maximum distance of 3.29 cM. Moreover, chromosome 5 was oriented according to its homoeologous chromosome 10. This map was useful to improve the apple genome sequence, design the Axiom Apple 480 K SNP array and perform multifamily-based QTL studies. Its collinearity with the genome sequences v1 and v3 are reported. To our knowledge, this is the shortest published SNP map in apple, while including the largest number of markers, families and individuals. This result validates our methodology, proving its value for the construction of integrated linkage maps for any outbreeding species.

International audience; The application of genomic selection in fruit tree crops is expected to enhance breeding efficiency by increasing prediction accuracy, increasing selection intensity and decreasing generation interval. The objectives of this study were to assess the accuracy of prediction and selection response in commercial apple breeding programmes for key traits. The training population comprised 977 individuals derived from 20 pedigreed full-sib families. Historic phenotypic data were available on 10 traits related to productivity and fruit external appearance and genotypic data for 7829 SNPs obtained with an Illumina 20K SNP array. From these data, a genome-wide prediction model was built and subsequently used to calculate genomic breeding values of five application full-sib families. The application families had genotypes at 364 SNPs from a dedicated 512 SNP array, and these genotypic data were extended to the high-density level by imputation. These five families were phenotyped for 1 year and their phenotypes were compared to the predicted breeding values. Accuracy of genomic prediction across the 10 traits reached a maximum value of 0.5 and had a median value of 0.19. The accuracies were strongly affected by the phenotypic distribution and heritability of traits. In the largest family, significant selection response was observed for traits with high heritability and symmetric phenotypic distribution. Traits that showed non-significant response often had reduced and skewed phenotypic variation or low heritability. Among the five application families the accuracies were uncorrelated to the degree of relatedness to the training population. The results underline the potential of genomic prediction to accelerate breeding progress in outbred fruit tree crops that still need to overcome long generation intervals and extensive phenotyping costs.

International audience; Unravelling the genomic processes at play during variety diversification is of fundamental interest for understanding evolution, but also of applied interest in crop science. It can indeed provide knowledge on the genetic bases of traits for crop improvement and germplasm diversity management. Apple is one of the most important fruit crops in temperate regions, having both great economic and cultural values. Sweet dessert apples are used for direct consumption while bitter cider apples are used to produce cider. Several important traits are known to differentiate the two variety types, in particular fruit size, biennial versus annual fruit bearing and bitterness, caused by a higher content in polyphenols. Here, we used an Illumina 8K SNP chip on two core collections, of 48 dessert and 48 cider apples, respectively, for identifying genomic regions responsible for the differences between cider and dessert apples. The genome-wide level of genetic differentiation between cider and dessert apples was low, although 17 candidate regions showed signatures of divergent selection, displaying either outlier FST values or significant association with phenotypic traits (bitter versus sweet fruits). These candidate regions encompassed 420 genes involved in a variety of functions and metabolic pathways, including several colocalizations with QTLs for polyphenol compounds.

Powdery mildew is one of the major diseases of wheat in regions with a maritime or semi-continental climate which can strongly affect grain yield. The objective of the study was to identify and compare quantitative resistance to powdery mildew of line RE9001 at the adult plant and vernalized seedling stages. RE9001 has no known Pm gene and shows a high level of adult plant resistance in the field. Using 104 recombinant inbred lines (RILs) of an RE9001 x 'Courtot' F8 population, a genetic map was developed with 363 markers distributed over 26 linkage groups and covering 3825 cM. The global map density was 1 locus/10.3 cM. RILs were assessed under field and tunnel greenhouse conditions for 2 years in two locations. Eleven quantitative trait loci (QTL) were detected at the adult stage and they explained 63% of the variation, depending on the environment. Three QTLs were found, at least, in the two environments. One QTL from RE9001, mapped on chromosome 2B, was stable in each environment. This QTL, QPm.inra.2B, explained 10.3 36.6% of the variation and could be mapped in the vicinity of the Pm6 gene. At the vernalized seedling stage. one QTL detected by the isolate 93-27 could be an allele of the Pm3g gene present in 'Courtot'. No residual effect of the Pm3g gene was detected at either stage. Markers flanking the QTL 2B could be useful tools to combine resistance to powdery mildew in wheat cultivars.

Cacopsylla pyri (pear psylla) is one of the most serious pests of pear (Pyrus spp.) in Europe. It can cause high yield losses, and its control has become difficult since it has developed resistance to a wide range of pesticides. Pear breeders are developing new cultivars resistant to pear psyllids, and Asian species, such as Pyrus ussuriensis and Pyrus × bretschneideri, are good sources of resistance. Antixenosis and antibiosis resistance to psylla were both identified in pear; they may differ in the biological mechanism and probably have different genetic backgrounds. We crossed interspecific P. × bretschneideri × Pyrus communis hybrid PEAR3, resistant to pear psylla, with the susceptible European pear cultivar ‘Moonglow’ to obtain an F1 population for the genetic mapping of the resistance. Quantitative trait locus (QTL) analysis was carried out for antibiosis by measuring the number of surviving nymphs and the nymphal development, using a novel phenotyping protocol and a saturated genetic map made of single-nucleotide polymorphism (SNP) and microsatellite (simple sequence repeats (SSR)) markers. A stable QTL was detected on linkage group (LG) 8 of PEAR3 (R 2 = 17.2–39.1 %). In addition, QTLs were detected on LG5 (R 2 = 10.8 %) of PEAR3 and on LG15 of ‘Moonglow’ (R 2 = 13.7 %).

Present address for H. Muranty : INRA, UMR1345 Institut de Recherche en Horticulture et Semences, 49071 Beaucouzé; International audience; For the most part, molecular markers and detection of quantitative trait loci have been developed for forest tree species in view to performing marker-assisted selection (MAS). However, MAS has not been applied to forest trees until now. In parallel, some success stories of MAS in crop breeding have been reported. Recently, genotyping techniques have undergone a tremendous increase in throughput, moving the trend from MAS to genomic selection. We analyzed 250 papers reporting the use of MAS in plant breeding and found that the most popular schemes used were gene pyramiding and marker-assisted backcross manipulating a single or very few genomic regions which have a major impact on crop value. We reviewed theoretical and simulation studies to identify the parametric space in which MAS is expected to bring about significant advantages over phenotypic selection. Then, we tried to explain why MAS has not been applied to forest trees and discuss the opportunities offered by recent advances in these species.

Strategies for mapping quantitative trait (QT) loci (QTL) need special studies in species where inbred lines cannot easily be obtained. We propose the detection of QTL with schemes including several full-sib families and study here the efficiency of such schemes — diallel, factorial, cyclic or single-pair mating designs — for a varying number of parents, on the basis of the power of tests for QTL detection. We considered a single, fully informative marker completely linked to the QTL. The tests proposed for QTL detection are based on linear additive models. The results show that for a given number of parents, in given conditions, the mating design has no effect on power. It increases as the total number of individuals genotyped increases. The number of parents affects the power of QTL detection insofar as the effect of substituting QT alleles varies from one parent to another and as some parents can be homozygous at the QTL: with only two parents QTL detection is often less powerful than with more parents. The size of the genetic effects that can be detected with a given power decreases as the number of parents increases from two to six and is quite stable for more than six parents. If QTL heterozygote frequency in the base population is high enough (greater than 0.2) mating designs with six parents should give a good sample of variance attributable to QTL and allow the detection of QTL with reasonable power.

Le nombre optimal de ramets par clone dans des dispositifs de tests clonaux a ete etudie a l'aide de tirages aleatoires dans des donnees reelles de vigueur, de forme et de qualite du bois. Ces donnees provenaient d'un essai de 32 clones de merisier (Prunus avium) replique sur trois sites et âge de 7 ans et d'un essai monostationnel de 96 clones de meleze hybride (Larix × eurolepis) âge de 8 ans. La precision d'estimation des valeurs genetiques et des parametres genetiques de variance-covariance approche son maximum vers six a huit ramets par clone. Pour estimer les gains genetiques correspondant aux differentes situations pour le nombre de ramets, on a considere que le nombre d'arbres en test etait constant et que le nombre de genotypes etudies augmentait quand le nombre de ramets par clone diminuait. Dans ce cadre, avec six ramets par clone, l'esperance de gain pour des caracteres d'heritabilites comprises entre 0,20 et 0,70 est de 20 % plus importante que celle obtenue avec 18 ramets par clone, nombre de ramets par clone utilise frequemment dans les tests clonaux. Les resultats obtenus pour un index multilocal sont similaires a ceux obtenus pour des caracteres etudies dans un seul site.

Moderate resistance to eyespot was first incorporated in the variety Cappelle-Desprez (CD). Later the gene Pch1, which could confer a higher level of resistance, was introduced from Aegilops ventricosa. However Pch1-carrying varieties can sustain significant eyespot-induced yield losses in severe attack situations. A strategy to further enhance the resistance of wheat is by pyramiding Pch1 and the genes for resistance in CD. The first requirement to achieve this is a better understanding of the genetics of resistance in CD. The resistance of the 21 Cappelle-Desprez (Bezostaya) disomic substitution lines was evaluated. Chromosome 7A was confirmed as carrying a major gene for resistance to eyespot at the seedling stage. However, this study demonstrates that this chromosome has no effects at the adult stage. Chromosome 5A was shown to carry a major gene for resistance to eyespot at the adult stage, which was stably expressed each year of testing. Chromosomes 1A and 2B had significant effects for only two years among four.

With 2 figures and 3 tables Abstract RE714 is a winter wheat breeding line obtained from two interspecific crosses [(Aegilops tauschii no. 33/Triticum dicoccum no. 119) and VPM = (Aegilops ventricosa no. 10/T. persicum)///Marne]. RE714 expresses powdery mildew resistance at the seedling, vernalized and adult stages. The origin of the main genetic factors involved in RE714 powdery mildew resistance (Pm4b, QPm.inra-5D, QPm.inra-6A2, QPm.inra-7A3a and QPm.inra-7A3b) was studied by comparing alleles of RE714 and those of seven of its parental lines with 36 microsatellite markers previously detected as linked to these factors. VPM, and among its parental lines, the T. persicum accession, were identified as the donor of Pm4b to RE714. Aegilops tauschii no. 33 and T. dicoccum no. 119 were identified as the donors of QPm.inra-5D and QPm.inra-6A2 to RE714, respectively. Beauchamp, a line used at the end of the breeding scheme that created RE714, might be the donor of the favourable alleles of RE714 at quantitative trait loci on linkage group 7A3. These results are discussed in the context of introgression of valuable genetic factors from related species of the primary gene pool into wheat.

International audience; Powdery mildew (Blumeria graminis f. sp. tritici) is one of the major diseases of wheat (Triticum aestivum). The objective of the present study was to describe the quantitative resistance to powdery mildew of the winter wheat line RE714 at the seedling stage and to identify microsatellite markers tightly linked to the RE714 resistance QTL, which could be used in marker-assisted selection. A population of 160 recombinant inbred lines obtained from the cross between RE714 (resistant) and Hardi (susceptible) was genotyped with microsatellite and AFLP markers. Fifteen powdery mildew isolates were used to test the resistance of these lines at the seedling stage. QTL analysis enabled us to identify three major QTLs controlling powdery mildew resistance in RE714: a QTL located on chromosome 2A, corresponding to the Pm4b gene, explaining 76-93% of the phenotypic variance for resistance to six isolates; two QTLs located on chromosomes 5D and 6A, each explaining 20-67%of the phenotypic variance for resistance tofive isolates.AminorQTLfor resistance to four of the six isolates revealing Pm4b was detected in the same region as the 5D QTL. Other minor QTLs were detected on chromosomes 2A and 6B, explaining, respectively, 10.9 and 11.5% of the phenotypic variance for resistance to isolate 96-27. The maps around the three major QTLs were enriched with microsatellite markers that could be used in marker-assisted selection of these QTLs.

International audience; Partial resistance of Populus nigra L. to three races of the foliar rust Melampsora larici-populina Kleb. was studied in a field trial and in laboratory tests, using a collection of P. nigra originating from different places throughout France. No total resistance was found. The partial resistance was split into epidemiological components, which proved to be under genetic control. Various patterns of association of epidemiological components values were found. Principal components analysis revealed their relationships. Only 24% of the variance of the field susceptibility could be explained by the variation of the epidemiological components of susceptibility. This variable was significantly correlated with susceptibility to the most ancient and widespread race of the pathogen, and with the variables related to the size of the lesions of the different races. Analysis of variance showed significant differences in susceptibility between regions and between stands within one region. Up to 20% of variation was between regions, and up to 22% between stands, so that these genetic factors appeared to be more differentiated than the neutral diversity (up to 3.5%; Legionnet & Lefevre, 1996). However, no clear pattern of geographical distribution of diversity was detected.

Selective genotyping, i.e. increasing the size of the population phenotyped and genotyping only individuals from the high and low tails of the population, can considerably improve the efficiency of experiments aimed at detecting and locating quantitative trait loci (QTLs) affecting a single trait. In this paper we study how selective genotyping can increase the efficiency of multitrait QTL experiments. By selecting on an index combining the variables of interest and having the maximum correlation with each variable, the efficiency of QTL detection is increased for each trait. The efficiency of selective genotyping relative to random selection strongly depends on the correlation between the index and each variable. The optimum selection rate that minimizes costs for a given experimental power depends also on this correlation and on the genotyping costs relative to phenotyping costs. When the population segregating for the quantitative traits and the markers is not as simple as a backcross or an F2 population, but is composed of several connected or unconnected families, selective genotyping can be used to improve the efficiency of the QTL study. In this case, the extreme individuals should be selected within each family. A method is provided to choose the selection rates within each family in order to optimize the global power of the experiment when the family sizes are unequal.

Usually, experiments designed for mapping quantitative trait loci (QTL) involve the genotyping of all individuals of a segregating population but are not very efficient with populations of feasible sizes. The use of selective genotyping, i.e., genotyping only a selected sample of the population (the high and low phenotypic tails), can considerably increase the efficiency of an experiment, provided the size of the population phenotyped is increased. In this paper, we examine the consequences of the use of this method for backcross and similar populations. New formulas, derived from likelihood functions, are proposed to estimate easily, without numerical maximization of the likelihood function, the effect of a QTL on the selected trait and on other traits of interest. This estimation procedure is shown to be reliable and quite robust to nonnormality, at least when the selection rate is not too low. The effect of selection on the efficiency of QTL detection for a trait other than the trait selected on is also considered: we show that selective genotyping never results in a loss of accuracy compared to random selection. Formulas to estimate QTL effects in more complex segregating populations could be easily derived in the same way as those proposed here.