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Background Phenomic prediction has been defined as an alternative to genomic prediction by using spectra instead of molecular markers. A reflectance spectrum provides information on the biochemical composition within a tissue, itself being under genetic determinism. Thus, a relationship matrix built from spectra could potentially capture genetic signal. This new methodology has been mainly applied in several annual crop species but little is known so far about its interest in perennial species. Besides, phenomic prediction has only been tested for a restricted set of traits, mainly related to yield or phenology. This study aims at applying phenomic prediction for the first time in grapevine, using spectra collected on two tissues and over two consecutive years, on two populations and for 15 traits, related to berry composition, phenology, morphological and vigour. A major novelty of this study was to collect spectra and phenotypes several years apart from each other. First, we characterized the genetic signal in spectra and under which condition it could be maximized, then phenomic predictive ability was compared to genomic predictive ability. Results For the first time, we showed that the similarity between spectra and genomic relationship matrices was stable across tissues or years, but variable across populations, with co-inertia around 0.3 and 0.6 for diversity panel and half-diallel populations, respectively. Applying a mixed model on spectra data increased phenomic predictive ability, while using spectra collected on wood or leaves from one year or another had less impact. Differences between populations were also observed for predictive ability of phenomic prediction, with an average of 0.27 for the diversity panel and 0.35 for the half-diallel. For both populations, a significant positive correlation was found across traits between predictive ability of genomic and phenomic predictions. Conclusion NIRS is a new low-cost alternative to genotyping for predicting complex traits in perennial species such as grapevine. Having spectra and phenotypes from different years allowed us to exclude genotype-by-environment interactions and confirms that phenomic prediction can rely only on genetics.

Crop breeding involves two selection steps: choosing progenitors and selecting offspring within progenies. Genomic prediction, based on genome-wide marker estimation of genetic values, could facilitate these steps. However, its potential usefulness in grapevine (Vitis viniferaL.) has only been evaluated in non-breeding contexts mainly through cross-validation within a single population. We tested across-population genomic prediction in a more realistic breeding configuration, from a diversity panel to ten bi-parental crosses connected within a half-diallel mating design. Prediction quality was evaluated over 15 traits of interest (related to yield, berry composition, phenology and vigour), for both the average genetic value of each cross (cross mean) and the genetic values of individuals within each cross (individual values). Genomic prediction in these conditions was found useful: for cross mean, average per-trait predictive ability was 0.6, while per-cross predictive ability was halved on average, but reached a maximum of 0.7. Mean predictive ability for individual values within crosses was 0.26, about half the within-half-diallel value taken as a reference. For some traits and/or crosses, these across-population predictive ability values are promising for implementing genomic selection in grapevine breeding. This study also provided key insights on variables affecting predictive ability. Per-cross predictive ability was well predicted by genetic distance between parents and when this predictive ability was below 0.6, it was improved by training set optimization. For individual values, predictive ability mostly depended on trait-related variables (magnitude of the cross effect and heritability). These results will greatly help designing grapevine breeding programs assisted by genomic prediction.

Background Multi-omics represent a promising link between phenotypes and genome variation. Few studies yet address their integration to understand genetic architecture and improve predictability. Results Our study used 241 poplar genotypes, phenotyped in two common gardens, with xylem and cambium RNA sequenced at one site, yielding large phenotypic, genomic (SNP), and transcriptomic datasets. Prediction models for each trait were built separately for SNPs and transcripts, and compared to a third model integrated by concatenation of both omics. The advantage of integration varied across traits and, to understand such differences, an eQTL analysis was performed to characterize the interplay between the genome and transcriptome and classify the predicting features into cis or trans relationships. A strong, significant negative correlation was found between the change in predictability and the change in predictor ranking for trans eQTLs for traits evaluated in the site of transcriptomic sampling. Conclusions Consequently, beneficial integration happens when the redundancy of predictors is decreased, likely leaving the stage to other less prominent but complementary predictors. An additional gene ontology (GO) enrichment analysis appeared to corroborate such statistical output. To our knowledge, this is a novel finding delineating a promising method to explore data integration.

The recent availability of genome-wide sequencing techniques has allowed systematic screening for molecular signatures of adaptation, including in nonmodel organisms. Host–pathogen interactions constitute good models due to the strong selective pressures that they entail. We focused on an adaptive event which affected the poplar rust fungus Melampsora larici-populina when it overcame a resistance gene borne by its host, cultivated poplar. Based on 76 virulent and avirulent isolates framing narrowly the estimated date of the adaptive event, we examined the molecular signatures of selection. Using an array of genome scan methods based on different features of nucleotide diversity, we detected a single locus exhibiting a consistent pattern suggestive of a selective sweep in virulent individuals (excess of differentiation between virulent and avirulent samples, linkage disequilibrium, genotype–phenotype statistical association, and long-range haplotypes). Our study pinpoints a single gene and further a single amino acid replacement which may have allowed the adaptive event. Although our samples are nearly contemporary to the selective sweep, it does not seem to have affected genome diversity further than the immediate vicinity of the causal locus, which can be explained by a soft selective sweep (where selection acts on standing variation) and by the impact of recombination in mitigating the impact of selection. Therefore, it seems that properties of the life cycle of M. larici-populina, which entails both high genetic diversity and outbreeding, has facilitated its adaptation.

Plant metabolites are important to world food security due to their roles in crop yield and nutritional quality. Here we report the metabolic profile of 300 tomato accessions (Solanum lycopersicum and related wild species) by quantifying 60 primary and secondary metabolites, including volatile organic compounds, over a period of 2 yr. Metabolite content and genetic inheritance of metabolites varied broadly, both within and between different genetic groups. Using genotype information gained from 10 000 single nucleotide polymorphism markers, we performed a metabolite genome-wide association mapping (GWAS) study. We identified 79 associations influencing 13 primary and 19 secondary metabolites with large effects at high resolution. Four genome regions were detected, highlighting clusters of associations controlling the variation of several metabolites. Local linkage disequilibrium analysis and allele mining identified possible candidate genes which may modulate the content of metabolites that are of significant importance for human diet and fruit consumption. We precisely characterized two associations involved in fruit acidity and phenylpropanoid volatile production. Taken together, this study reveals complex and distinct metabolite regulation in tomato subspecies and demonstrates that GWAS is a powerful tool for gene-metabolite annotation and identification, pathways elucidation, and further crop improvement.

International audience; In a context of climate change and forest decline, a better understanding of the sources of tree flexibility involved in phenotypic plasticity and adaptation is needed. These last years, the role of epigenetics in the response to environmental variations has been established in several model plants at the genotype level but little is known at the level of natural populations grown in pedoclimatic sites. Here, we focused on three French natural populations of black poplar, a key pioneer tree from watersheds, planted in common garden and subjected to controlled variations of water availability. We estimated common genetic parameters such as narrow-sense heritability (h(2)), phenotypic differentiation index (P-ST), and the overall genetic differentiation index (F-ST) from genome-wide SNPs to evaluate the extent of epigenetic variations. Indeed, global DNA methylation levels from individuals exposed to drought or irrigated in a common garden were used. We found that the three populations were not distinguished by their levels of DNA methylation. However, a moderate drought was associated to a significant decrease in DNA methylation in the populations. Narrow-sense heritability and P-ST estimates of DNA methylation were similar to those found for biomass productivity. Heritability and P-ST were higher when trees were subjected to drought than in control condition. Negative genetic correlations between global DNA methylation and height or biomass were detected in drought condition only. Altogether, our data highlight that global DNA methylation acts as a genetic marker of natural population differentiation under drought stress in a pedoclimatic context.

Genomic selection - the prediction of breeding values using DNA polymorphisms - is a disruptive method that has widely been adopted by animal and plant breeders to increase productivity. It was recently shown that other sources of molecular variations such as those resulting from transcripts or metabolites could be used to accurately predict complex traits. These endophenotypes have the advantage of capturing the expressed genotypes and consequently the complex regulatory networks that occur in the different layers between the genome and the phenotype. However, obtaining such omics data at very large scales, such as those typically experienced in breeding, remains challenging. As an alternative, we proposed using near-infrared spectroscopy (NIRS) as a high-throughput, low cost and non-destructive tool to indirectly capture endophenotypic variants and compute relationship matrices for predicting complex traits, and coined this new approach ”phenomic selection” (PS). We tested PS on two species of economic interest (Triticum aestivum L. and Populus nigra L.) using NIRS on various tissues (grains, leaves, wood). We showed that one could reach predictions as accurate as with molecular markers, for developmental, tolerance and productivity traits, even in environments radically different from the one in which NIRS were collected. Our work constitutes a proof of concept and provides new perspectives for the breeding community, as PS is theoretically applicable to any organism at low cost and does not require any molecular information.

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.

Population structure causes genome-wide linkage disequilibrium between unlinked loci, leading to statistical confounding in genome-wide association studies. Mixed models have been shown to handle the confounding effects of a diffuse background of large numbers of loci of small effect well, but do not always account for loci of larger effect. Here we propose a multi-locus mixed model as a general method for mapping complex traits in structured populations. Simulations suggest that our method outperforms existing methods, in terms of power as well as false discovery rate. We apply our method to human and Arabidopsis thaliana data, identifying novel associations in known candidates as well as evidence for allelic heterogeneity. We also demonstrate how a priori knowledge from an A. thaliana linkage mapping study can be integrated into our method using a Bayesian approach. Our implementation is computationally efficient, making the analysis of large datasets (n > 10000) practicable.

The Art of Artemisia As the malaria parasite, which is transmitted through mosquito vectors, develops resistance, previously useful control mechanisms are beginning to fail. Combination therapies based on the plant product artemisinin are a promising alternative. Graham et al. (p. 328 ; see the Perspective by Milhous and Weina ) have now developed a genetic map of the plant Artemisia annua from which artemisinin is derived. The results lay the foundation for improving agricultural productivity of this natural product, which is becoming increasingly important in the fight against malaria.

UMR DAP équipe AFEF Publication Inra prise en compte dans l'analyse bibliométrique des publications scientifiques mondiales sur les Fruits, les Légumes et la Pomme de terre. Période 2000-2012. http://prodinra.inra.fr/record/256699; International audience; The present study aimed to dissect tree architectural plasticity into genetic, ontogenetic and environmental effects over the first 4 years of growth of an apple F1 progeny by means of quantitative traits loci (QTL) mapping. Both growth and branching processes were phenotyped on the consecutive annual shoots of different axes within a tree. For each studied trait, predicted values (best linear unbiased predictors, BLUPs) of the genotypic (G) effect or its interaction with tree age (G×A) and climatic year (G×Y) were extracted from mixed linear models of repeated data. These BLUPs, which are independent from autocorrelations between repeated measurements, were used for QTL mapping. QTL detection power was improved by this two-step approach. For each architectural process, numerous QTLs were detected and some particularly interesting co-localised in common genomic regions, for internode lengthening, top diameter, and number and percentage of axillary shoots. When several QTLs were detected for a given trait, global models were estimated, which explained a maximum of 40% of the total variance for both internode length and top diameter and 28% for branching. QTLs detected for BLUPs of G×Y effects were interpreted as resulting from the interaction between genetic maximal potential of growth and climatic factors, while those for G×A effects were interpreted in relation to tree ontogeny. Most of the latter ones were found to be concomitant with key development stages during which the trait average started to decrease, but with different magnitudes depending on genotype

International audience; Whole genome resequencing of 51 Populus nigra (L.) individuals from across Western Europe was performed on Illumina platforms. A total number of 1,878,727 SNPs distributed along a P. nigra reference sequence were identified. The SNP calling accuracy was validated by comparison with Sanger sequencing data. SNPs were selected within 14 previously identified QTL regions, 2916 expressional candidate genes related to rust resistance, wood properties, water-use efficiency and bud phenology, and 1732 genes randomly spread across the genome. Over 10,000 SNPs were filtered for the construction of a 12k Infinium BeadChip array dedicated to association mapping. The SNPs genotyping assay was performed with 888 P. nigra individuals. The genotyping success rate was 91%. Our high success rate was due to the discovery panel design and the stringent parameters applied for SNP calling and selection. In the same set of P. nigra genotypes, linkage disequilibrium throughout the genome decayed on average within 5 to 7 kb to half of its maximum value. As application test, ADMIXTURE analysis was performed with a selection of 600 SNPs spread out on the genome and 706 individuals collected along 12 river basins. The admixture pattern was consistent with genetic diversity revealed by neutral markers and geographical distribution of the populations. These newly developed SNP resources and genotyping array provide a valuable tool for population genetic studies and identification of QTLs through natural-population based genetic association in P. nigra.

In fruit trees, understanding genetic determinisms of architectural traits is considered as a promising manner to control vegetative development and yield regularity. In this context, our study aimed to classify 2-year-old apple hybrids on the basis of their architectural traits. From a fine phenotyping, trees were described as tree graphs, including topological and geometric information. To evaluate the similarity between trees, comparison methods based on edit operations (substitution, insertion and deletion) were carried out. Distance between two tree graphs was computed by minimising the sum of the costs of the edit operations applied to transform one tree into another. Two algorithms for the comparison of unordered and partially ordered tree graphs were applied to a sub-sample of the population, taking into account several geometric attributes. For each comparison, a dissimilarity matrix was computed, and subsequently trees were clustered. A local interpretation of the matched entities was proposed through schematic representations of the trees, and similarities between trees were analysed within and between clusters. The tree graphs, both unordered or partially ordered and whether the attributes were considered or not, were grouped, by clustering, according to the number of entities per tree. The robustness of the unordered comparison was demonstrated by its application to the whole population, since it provided results similar to those obtained on the sub-sample. Further developments towards a higher relative weight of geometric versus topological information are discussed in the perspective to define an architectural ideotype in apple.

Genome-wide association studies have been successful in identifying genes involved in polygenic traits and are valuable for crop improvement. Tomato (Solanum lycopersicum) is a major crop and is highly appreciated worldwide for its health value. We used a core collection of 163 tomato accessions composed of S. lycopersicum, S. lycopersicum var cerasiforme, and Solanum pimpinellifolium to map loci controlling variation in fruit metabolites. Fruits were phenotyped for a broad range of metabolites, including amino acids, sugars, and ascorbate. In parallel, the accessions were genotyped with 5,995 single-nucleotide polymorphism markers spread over the whole genome. Genome-wide association analysis was conducted on a large set of metabolic traits that were stable over 2 years using a multilocus mixed model as a general method for mapping complex traits in structured populations and applied to tomato. We detected a total of 44 loci that were significantly associated with a total of 19 traits, including sucrose, ascorbate, malate, and citrate levels. These results not only provide a list of candidate loci to be functionally validated but also a powerful analytical approach for finding genetic variants that can be directly used for crop improvement and deciphering the genetic architecture of complex traits.

INRA UMR 1334 AGAP, Equipe DAVEM = Diversité et Adaptation de la Vigne et des Espèces Méditerranéennes; Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accuracy of models based on GWAS or GS alone, or in combination, for predicting simple or complex traits, linked or not with population structure. In order to explore the relevance of these methods in this context, we performed simulations using approx 90,000 SNPs on a population of 3,000 individuals structured into three groups and corresponding to published diversity grapevine data. To estimate the parameters of the prediction models, we defined four training populations of 1,000 individuals, corresponding to these three groups and a core collection. Finally, to estimate the accuracy of the models, we also simulated four breeding populations of 200 individuals. Although prediction accuracy was low when breeding populations were too distant from the training populations, high accuracy levels were obtained using the sole core-collection as training population. The highest prediction accuracy was obtained (up to 0.9) using the combined GWAS-GS model. We thus recommend using the combined prediction model and a core-collection as training population for grapevine breeding or for other important economic crops with the same characteristics.

Arabidopsis thaliana is an important model organism for understanding the genetics and molecular biology of plants. Its highly selfing nature, small size, short generation time, small genome size, and wide geographic distribution make it an ideal model organism for understanding natural variation. Genome-wide association studies (GWAS) have proven a useful technique for identifying genetic loci responsible for natural variation in A. thaliana. Previously genotyped accessions (natural inbred lines) can be grown in replicate under different conditions and phenotyped for different traits. These important features greatly simplify association mapping of traits and allow for systematic dissection of the genetics of natural variation by the entire A. thaliana community. To facilitate this, we present GWAPP, an interactive Web-based application for conducting GWAS in A. thaliana. Using an efficient implementation of a linear mixed model, traits measured for a subset of 1386 publicly available ecotypes can be uploaded and mapped with a mixed model and other methods in just a couple of minutes. GWAPP features an extensive, interactive, and user-friendly interface that includes interactive Manhattan plots and linkage disequilibrium plots. It also facilitates exploratory data analysis by implementing features such as the inclusion of candidate polymorphisms in the model as cofactors.

Article en open access; Artemisia annua is an important medicinal crop used for the production of the anti-malarial compound artemisinin. In order to assist in the production of affordable high quality artemisinin we have carried out an A. annua breeding programme aimed at improving artemisinin concentration and biomass. Here we report on a combining ability analysis of a diallel cross to identify robust parental lines for hybrid breeding. The parental lines were selected based on a range of phenotypic traits to encourage heterosis. The general combining ability (GCA) values for the diallel parental lines correlated to the positive alleles of quantitative trait loci (QTL) in the same parents indicating the presence of beneficial alleles that contribute to parental performance. Hybrids generated from crossing specific parental lines with good GCA were identified as having an increase in both artemisinin concentration and biomass when grown either in glasshouse or experimental field trials and compared to controls. This study demonstrates that combining ability as determined by a diallel cross can be used to identify elite parents for the production of improved A. annua hybrids. Furthermore, the selection of material for breeding using this approach was found to be consistent with our QTL-based molecular breeding approach.

Genome-wide association studies (GWAS) are a standard approach for studying the genetics of natural variation. A major concern in GWAS is the need to account for the complicated dependence structure of the data, both between loci as well as between individuals. Mixed models have emerged as a general and flexible approach for correcting for population structure in GWAS. Here, we extend this linear mixed-model approach to carry out GWAS of correlated phenotypes, deriving a fully parameterized multi-trait mixed model (MTMM) that considers both the within-trait and between-trait variance components simultaneously for multiple traits. We apply this to data from a human cohort for correlated blood lipid traits from the Northern Finland Birth Cohort 1966 and show greatly increased power to detect pleiotropic loci that affect more than one blood lipid trait. We also apply this approach to an Arabidopsis thaliana data set for flowering measurements in two different locations, identifying loci whose effect depends on the environment.

We have characterized the genetic and molecular origin of the reiterated reproductive meristem (RRM) somatic variant phenotype of grapevine cultivar Carignan. Here, we show that the extreme cluster proliferation and delayed anthesis observed in this somatic variant is caused by a single dominant mutation. Transcriptional profiling of Carignan and RRM plants during early stages of inflorescence development demonstrated the overexpression of a few regulatory genes, including VvTFL1A, a close TFL1 Arabidopsis homolog, in RRM inflorescences. Genetic and molecular analyses correlated the insertion of a class-II transposable element, Hatvine1-rrm, in the VvTFL1A promoter, with upregulation of the corresponding VvTFL1A allele in reproductive and vegetative organs of the shoot apex. These results suggest a role for this TFL1 grapevine homolog in the determination of inflorescence structure, with a critical effect on the size and branching pattern of grapevine fruit clusters. Our results demonstrate the existence of spontaneous cis-activation processes caused by class-II transposable elements in grapevine plants, and point to their possible role as a mechanism to generate somatic cell variation in perennial plants. This mechanism is expected to generate dominant phenotypes in chimeric sectors that can be readily exposed to natural selection., This research was supported by grants BIO2005-07612 and BIO2008-03892 from the Spanish Ministry for Science and Innovation, and by funds from the INRA Plant Breeding and Genetics Department.

International audience; The aim of this study was to define a methodology for describing architectural traits in a quantitative way on tree descendants. Our strategy was to collect traits related to both tree structural organization, resulting from growth and branching, and tree form and then to select among these traits relevant descriptors on the basis of their genetic parameters. Because the complexity of tree architecture increases with tree age, we chose to describe the trees in the early stages of development. The study was carried out on a 1-year-old apple progeny derived from two parent cultivars with contrasted architecture. A large number of variables were collected at different positions and scales within the trees. Broad-sense heritability and genetic correlations were estimated and the within tree variability was analyzed for variables measured on long sylleptic axillary shoots (LSAS). These results were combined to select heritable and not correlated variables. Finally, the selection of variables proposed combines topological with geometric traits measured on both trunks and LSAS: (1) on the trunk, mean internode length, and number of sylleptic axillary shoots; (2) on axillary shoots, conicity, bending, and number of sylleptic axillary shoots born at order 3. The trees of the progeny were partitioned on the basis of these variables. The putative agronomic interest of the selected variables with respect to the subsequent tree development is discussed.

International audience; The purpose of this study was to identify relevant variables and appropriate stages in tree development to determine, as early as possible, genetic differences in growth and branching of apricot trees. Quantitative growth and branching traits of young trees were studied in four genotypes planted at three locations in the French growing area. Over the first three years of growth, the organisation of ten limbs was described for each genotype × location combination using 'AMAPmod' methodology. From the first year, the length, diameters, volume and sylleptic branching of limbs were influenced by genotype. In the second and third years, genetic variability was more clearly detected when cumulative variables, rather than annual variables, were considered on the cumulative components of limbs. At all three locations, the diameters, volume and number of long laterals were greatly affected, in particular, by genotype when the data were accumulated over the first 2 years. In addition, the abortion of short laterals developed on the first annual shoot was influenced by genotype. In contrast, from the second year, location clearly affected the length and number of “growth units” of limbs. As regards branching, location influenced the number of sylleptic shoots in the first year, then the number of long lateral shoots in the second year. Finally, the study showed that genetic differences in growth and branching need at least 3 years to be expressed on appropriate parts of the limbs and could be used to assess early breeding criteria for tree vigour and form.