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International audience; Tree architecture shows large genotypic variability, but how this affects water-deficit responses is poorly understood. To assess the possibility of reaching ideotypes with adequate combinations of architectural and functional traits in the face of climate change, we combined high-throughput field phenotyping and genome-wide association studies (GWAS) on an apple tree (Malus domestica) core-collection. We used terrestrial light detection and ranging (T-LiDAR) scanning and airborne multispectral and thermal imagery to monitor tree architecture, canopy shape, light interception, vegetation indices and transpiration on 241 apple cultivars submitted to progressive field soil drying. GWAS was performed with single nucleotide polymorphism (SNP)-by-SNP and multi-SNP methods. Large phenotypic and genetic variability was observed for all traits examined within the collection, especially canopy surface temperature in both well-watered and water deficit conditions, suggesting control of water loss was largely genotype-dependent. Robust genomic associations revealed independent genetic control for the architectural and functional traits. Screening associated genomic regions revealed candidate genes involved in relevant pathways for each trait. We show that multiple allelic combinations exist for all studied traits within this collection. This opens promising avenues to jointly optimize tree architecture, light interception and water use in breeding strategies. Genotypes carrying favourable alleles depending on environmental scenarios and production objectives could thus be targeted.

Tree breeding programs and wood industries require simple, time- and cost-effective techniques to process large volumes of samples. In recent decades, near-infrared spectroscopy (NIRS) has been acknowledged as one of the most powerful techniques for wood analysis, making it the most used tool for high-throughput phenotyping. Previous studies have shown that a significant number of anatomical, physical, chemical and mechanical wood properties can be estimated through NIRS, both for angiosperm and gymnosperm species. However, the ability of this technique to predict functional traits related to drought resistance has been poorly explored, especially in angiosperm species. This is particularly relevant since determining xylem hydraulic properties by conventional techniques is complex and time-consuming, clearly limiting its use in studies and applications that demand large amounts of samples. In this study, we measured several wood anatomical and hydraulic traits and collected NIR spectra in branches of two Eucalyptus L'Hér species. We developed NIRS calibration models and discussed their ability to accurately predict the studied traits. The models generated allowed us to adequately calibrate the reference traits, with high R2 (≥0.75) for traits such as P12, P88, the slope of the vulnerability curves to xylem embolism or the fiber wall fraction, and with lower R2 (0.39–0.52) for P50, maximum hydraulic conductivity or frequency of ray parenchyma. We found that certain wavenumbers improve models’ calibration, with those in the range of 4000–5500 cm−1 predicting the highest number of both anatomical and functional traits. We concluded that the use of NIRS allows calibrating models with potential predictive value not only for wood structural and chemical variables but also for anatomical and functional traits related to drought resistance in wood types with complex structure as eucalypts. These results are promising in light of the required knowledge about species and genotypes adaptability to global climatic change.

Trees are long-lived organisms that continuously adapt to their environments, a process in which epigenetic mechanisms are likely to play a key role. Via down regulation of the chromatin remodeler DECREASED IN DNA METHYLATION 1 (DDM1) in poplar (Populus tremula 9 Populus alba) RNAi lines, we examined how DNA methylation coordinates genomic and physiological responses to moderate water deficit.We compared the growth and drought response of two RNAi-ddm1 lines to wild-type (WT) trees under well-watered and water deficit/rewatering conditions, and analyzed their methylomes, transcriptomes, mobilomes and phytohormone contents in the shoot apical meristem. The RNAi-ddm1 lines were more tolerant to drought-induced cavitation but did not differ in height or stem diameter growth. About 5000 differentially methylated regions were consistently detected in both RNAi-ddm1 lines, colocalizing with 910 genes and 89 active transposable elements. Under water deficit conditions, 136 differentially expressed genes were found, including many involved in phytohormone pathways ; changes in phytohormone concentrations were also detected. Finally, the combination of hypomethylation and drought led to the mobility of two transposable elements. Our findings suggest major roles for DNA methylation in regulation of genes involved in hormone-related stress responses, and the maintenance of genome integrity through repression of transposable elements.

Recently, it has been proposed to switch molecular markers to near-infrared (NIR) spectra for inferring relationships between individuals and further performing phenomic selection (PS), analogous to genomic selection (GS). The PS concept is similar to genomic-like omics-based (GLOB) selection, in which molecular markers are replaced by endophenotypes, such as metabolites or transcript levels, except that the phenomic information obtained for instance by near-infrared spectroscopy (NIRS) has usually a much lower cost than other omics. Though NIRS has been routinely used in breeding for several decades, especially to deal with end-product quality traits, its use to predict other traits of interest and further make selections is new. Since the seminal paper on PS, several publications have advocated the use of spectral acquisition (including NIRS and hyperspectral imaging) in plant breeding towards PS, potentially providing a scope of what is possible. In the present chapter, we first come back to the concept of PS as originally proposed and provide a classification of selected papers related to the use of phenomics in breeding. We further provide a review of the selected literature concerning the type of technology used, the preprocessing of the spectra, and the statistical modeling to make predictions. We discuss the factors that likely affect the efficiency of PS and compare it to GS in terms of predictive ability. Finally, we propose several prospects for future work and application of PS in the context of plant breeding.

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.

International audience; Context: Douglas-fir, a fast growing conifer from western North America, recently suffered diebacks following drought in France. We investigated the link between native-source climate and provenance drought resistance in a common garden in France. We compared the adaptive potential of provenances from different parts of the natural area. Methods: We collected branches from a 25-year-old provenance trial replicated in two test sites in southern France. We estimated provenance variation of cavitation resistance traits, survival and circumference. We compared Washington-Oregon provenances to coastal and interior Californian provenances. Results: In the common gardens, the hydraulic traits were significantly variable between provenances, with a strong site x provenance interaction, and significantly related to the climate of the natural area and survival. The relationships were different between variables and test-sites. The two test-sites and their particular climatic selective pressure revealed different geographical adaptive structures in the natural area. Conclusions: Douglas-fir evolutionary adaptation to drought results from natural selection to summer climate and shapes populations for cavitation resistance. In the dryer site only, the Interior California provenances seem more drought resistant. The strong within-provenance variations suggest that there is also a certain withinprovenance adaptation potential to drought at the cost of variable mortality rates.

As fixed and long living organisms subjected to repeated environmental stresses, trees have developed mechanisms such as phenotypic plasticity that help them to cope with fluctuating environmental conditions. Here, we tested the role DNA methylation as a hub of integration, linking plasticity and physiological response to water deficit in the shoot apical meristem of the model tree poplar (Populus). Using a reverse genetic approach, we compared hypomethylated RNAi-ddm1lines to wild-type trees for drought tolerance. An integrative analysis was realized with phytohormone balance, methylomes, transcriptomes and mobilomes.Hypomethylated lines were more tolerant when subjected to moderate water deficit and were intrinsically more tolerant to drought-induced cavitation. The alteration of theDDM1machinery induced variation in DNA methylation in a cytosine context dependent manner, both in genes and transposable elements. Hypomethylated lines subjected to water deficit showed altered expression of genes involved in phytohormone pathways, such as salicylic acid and modified hormonal balance. Several transposable elements showed stress- and/or line-specific patterns of reactivation, and we could detect copy number variations for two of them in stressedddm1lines.Overall, our data highlight two major roles for DNA methylation in the shoot apical meristem: control of stress response and plasticity through transduction of hormone signaling and maintenance of genome integrity through the control of transposable elements.

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.

Key message This review highlights some of the discoveries and applications made possible by “omics” technologies over the last 10 years and provides perspectives for pioneering research to increase our understanding of tree biology. Context A decade after the first forest tree genome sequence was released into the public domain, the rapidly evolving genomics and bioinformatics toolbox has advanced our understanding of the structure, functioning, and evolution of forest tree genomes. Aims and methods This review highlights some of the discoveries and applications that “omics” technologies have made possible for forest trees over the past 10 years. Results In this review, we start by our current understanding of genome evolution and intricacies of gene regulation for reproduction, development, and responses to biotic and abiotic stresses. We then skim over advances in interactome analysis and epigenomics, the knowledge of the extent of genetic variation within and between species, revealing micro- and macro-evolutionary processes and species history, together with the complex architecture of quantitative traits. We finally end with applications in genetic resource conservation and breeding. Conclusion The knowledge gained through the use of these technologies has a huge potential impact for adapting forests to the main challenges they will have to face: changing demand from ecosystem services with potentially conflicting strategies in terms of conservation and use, as well as climate changes and associated threats. Genomics will undoubtedly play a major role over the next decade and beyond, not only to further understand the mechanisms underlying adaptation and evolution but also to develop and implement innovative management and policy actions to preserve the adaptability of natural forests and intensively managed plantations.

Recent literature on the differential role of genes within networks, including the omnigenic model, distinguishes core from peripheral genes in the layout underlying phenotypes. Cores are typically few, each of them highly contributes to phenotypic variation, but because they are so few, they altogether only explain a small part of trait heritability. In contrast, peripherals, each of small influence, are so numerous that they finally lead phenotypic variation. We collected and sequenced RNA from 459 European black poplars and built co-expression networks to define core and peripheral genes as the most and least connected ones. We computed the role of each of these gene sets in the prediction of phenotypes and showed that cores contribute additively to phenotypes, consistent with a downstream position in a biological cascade, while peripherals interact to influence phenotypes, consistent with an upstream position. Quantitative and population genetics analyses further revealed that cores are more expressed than peripherals but they tend to vary less and to be more differentiated between populations suggesting that they are more constrained by natural selection. Our work is the first attempt to integrate core and peripheral terminologies from co-expression networks and omnigenic theory. In the end, we showed, that there seems to be a strong overlap between them, with core genes from co-expression networks likely being a mixture of integrative hubs with a direct effect on phenotype in agreement with the omnigenic theory, and master regulators which control the overall metabolic flow towards the phenotype.

International audience; Characterizing drought resistance of forest trees is an important aim in the worldwide context of increasing forest decline and dieback. Furthermore, wood demand is increasing all around the world, urging the need for the domestication of native species and the selection of the most resistant individuals. While near-infrared spectroscopy is now recognized as an efficient tool to predict wood physical and chemical properties involves in wood quality, its ability to predict wood hydraulic function remains anecdotic, although it has recently gained interest. In this study, we tested near-infrared spectroscopy as a high-throughput method for quantifying both resistance to cavitation and basic wood density in the South American conifer Austrocedrus chilensis. Models were obtained in two laboratories using the same sample set. To assess resistance to cavitation, vulnerability curves were obtained using the air-injection method. Basic wood density was measured in the same samples as used for resistance to cavitation. Partial least squares regression models with cross-validation were used to establish relationships between the NIRS spectra and wood traits. The accuracy of the models strongly depended on the traits being used for calibration. Models obtained in both laboratories were similar, demonstrating the genericity of the approach whatever equipment used. Promising results were obtained for two cavitation parameters (water potential at 12% and 50% of hydraulic conductivity loss) and basic wood density. Prediction errors for these traits were low. In contrast to studies at the interspecific level, basic wood density and resistance to cavitation were negatively correlated at the intraspecific level in the studied species, but our calibration models shown than basic wood density cannot be used as a good predictor of functional traits. The NIRS has high potential to be put into practice as a rapid, reliable, and non-destructive method to determine, resistance to xylem cavitation, a trait involved in drought resistance.

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.ARTICLE SUMMARYDespite its widely adopted interest in breeding, genomic selection - the prediction of breeding values using DNA polymorphisms - remains difficult to implement for many species because of genotyping costs. As an alternative or complement depending on the context, we propose “phenomic selection” (PS) as the use of low-cost and high-throughput phenotypic records to reconstruct similarities between genotypes and predict their performances. As a proof of concept of PS, we made use of near infrared spectroscopy applied to different tissues in poplar and wheat to predict various key traits and showed that PS could reach predictions as accurate as with molecular markers.

High-throughput and non-destructive methods for quantifying the content of the stilbene compounds of Scots pine ( Pinus sylvestris L.) heartwood are needed in the breeding for decay resistance of heartwood timber. In this study, near infrared (NIR) spectroscopy calibrations were developed for a large collection of solid heartwood increment core samples in order to predict the amount of the stilbene pinosylvin (PS), its monomethyl ether (PSM) and their sum (STB). The resulting models presented quite accurate predictions in an independent validation set with R2V values ranging between 0.79 and 0.91. The accuracy of the models strongly depended on the chemical being calibrated, with the lowest accuracy for PS, intermediate accuracy for PSM and highest accuracy for STB. The effect of collecting one, two or more (up to five) spectra per sample on the calibration models was studied and it was found that averaging multiple spectra yielded better accuracy as it may account for the heterogeneity of wood along the increment core within and between rings. Several statistical pretreatments of the spectra were tested and an automatic selection of wavenumbers prior to calibration. Without the automatic selection of wavenumbers, a first derivative of normalised spectra yielded the best accuracies, whereas after the automatic selection of wavenumbers, no particular statistical pretreatment appeared to yield better results than any other. Finally, the automatic selection of wavenumbers slightly improved the accuracy of the models for all traits. These results demonstrate the potential of NIR spectroscopy as a high-throughput and non-destructive phenotyping technique in tree breeding for the improvement of decay resistance in heartwood timber.

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.

International audience; Forest trees are long-lived organisms subject to repeated environmental constraints throughout their long lifetimes. They have developed various mechanisms enabling them to cope with fluctuating environmental conditions during their life span, and to survive to current climate change. Epigenetics has recently emerged as a powerful set of mechanisms regulating various developmental processes, plant growth and responses to environmental variations. Such epigenetic mechanisms, which may remain stable along tree life or across generations, constitute a source of rapid phenotypic variations potentially improving adaptation of the plants in situations in which naturally occurring mutations are very rare.In this review, we summarize recent advances in forest tree epigenomics. We first draw the particularities of trees and the available (epi) genomics resources and strategies. Then, we discuss the potential contributions of epigenetics to cope with global climate change and regulate various developmental processes, such as developmental transitions during the annual cycle, phenotypic plasticity in response to environmental variations and stress memory, as well as local adaptation. Finally, we propose some challenges for forest management and highlighted the need to take epigenetics into account in forest tree breeding strategies.

International audience; Trees have a long lifespan and must continually adapt to environmental pressures, notably in the context of climate change. Epigenetic mechanisms are doubtless involved in phenotypic plasticity and in stress memory; however, little evidence of the role of epigenetic processes is available for trees growing in fields. Here, we analyzed the possible involvement of epigenetic mechanisms in the winter-dormant shoot apical meristem of Populus × euramericana clones in memory of the growing conditions faced during the vegetative period. We aimed to estimate the range of genetic and environmentally induced variations in global DNA methylation and to evaluate their correlation with changes in biomass production, identify differentially methylated regions (DMRs), and characterize common DMRs between experiments. We showed that the variations in global DNA methylation between conditions were genotype dependent and correlated with biomass production capacity. Microarray chip analysis allowed detection of DMRs 6 months after the stressful summer period. The 161 DMRs identified as common to three independent experiments most notably targeted abiotic stress and developmental response genes. Results are consistent with a winter-dormant shoot apical meristem epigenetic memory of stressful environmental conditions that occurred during the preceding summer period. This memory may facilitate tree acclimation.

International audience; The adaptive capacity of long-lived organisms such as trees to the predicted climate changes, including severe and successive drought episodes, will depend on the presence of genetic diversity and phenotypic plasticity. Here, the involvement of epigenetic mechanisms in phenotypic plasticity toward soil water availability was examined in Populus×euramericana. This work aimed at characterizing (i) the transcriptome plasticity, (ii) the genome-wide plasticity of DNA methylation, and (iii) the function of genes affected by a drought-rewatering cycle in the shoot apical meristem. Using microarray chips, differentially expressed genes (DEGs) and differentially methylated regions (DMRs) were identified for each water regime. The rewatering condition was associated with the highest variations of both gene expression and DNA methylation. Changes in methylation were observed particularly in the body of expressed genes and to a lesser extent in transposable elements. Together, DEGs and DMRs were significantly enriched in genes related to phytohormone metabolism or signaling pathways. Altogether, shoot apical meristem responses to changes in water availability involved coordinated variations in DNA methylation, as well as in gene expression, with a specific targeting of genes involved in hormone pathways, a factor that may enable phenotypic plasticity.

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.

High-throughput techniques for the compositional analysis of lignocellulosic biomass are essential to allow the genetic analysis and genetic improvement of bioenergy feedstocks. In this study, we investigated the feasibility of using near-infrared (NIR) spectroscopy for rapid assessment of wood chemical traits in a large sample of Populus nigra L. individuals evaluated in clonal trials at two contrasting sites. Spectra were acquired from 5799 wood samples collected in 3 harvests corresponding to two coppice rotations at one site and one coppice rotation at the second. Calibrations were developed and validated using 120 reference samples, representing spectral and chemical variations in the samples. The resulting global and site specific calibrations for most of the traits were at least good enough for ranking of genotypes, demonstrating the usefulness of NIR analysis for phenotyping the studied population. Clonal repeatability (View the MathML sourceHc2) estimates of the studied traits based on all samples were moderate to high (View the MathML sourceHc2 ranging from 0.57 to 0.89 in the 3 harvests). When data were pooled over coppice rotations or sites, the genotype × environment interaction was more evident across sites than across rotations. However, the interaction was smaller than the genotype main effect for all traits, except for glucose and extractives contents. Importantly, the interaction resulted mainly from re-ranking of a few genotypes leaving a substantial amount of stable and performant genetic material, which may encourage breeding for improved main wood components. Optimization of the NIR analysis for assessing clonal trials would facilitate the exploitation of standing genetic variation of energy or chemical related traits in tree breeding program.

International audience; Angiosperm trees are able to reorient their axes thanks to their capacities to differentiate tension wood on the upper side of stems and branches. In poplar, tension wood fibres develop an extra cell wall layer, named G-layer, responsible for the peculiar mechanical properties of tension wood. G-layer is composed of highly crystalline cellulose microfibrils embedded in a polysaccharide/glycoprotein matrix devoid of lignin. During the G-layer deposition, cellulose microfibrils get oriented parallel to the fibre axis and placed under the state of high tensile stress. Chitinase-like proteins (CTL) have been proposed to play different roles in plant growth and development. Genes encoding CTL have been associated to cellulose synthesis and their mutation causes ectopic deposition of lignin. Transcripts of CTL2 gene were shown to be highly abundant in differentiating tension wood (Déjardin et al., 2004). Its homologue in Arabidopsis is specifically expressed in stems and co-expressed with the CesA genes involved in cellulose synthesis in secondary cell walls (Persson et al., 2005). In our study, we investigated potential function of CTL2 in the formation and mechanical properties of tension wood. Expression of CTL2 was quantified in different tissues and the effects of CTL2 down-regulation have been characterized in GM poplar trees. CTL2 gene appeared highly expressed in xylem with no difference in expression between tension and opposite wood. Downregulation of CTL2 did not seem to impact growth and development of trees in greenhouse conditions. However, stems appeared to be highly breakable in the transverse direction. Anatomical observations of xylem showed altered formation of Glayers in vessel-surrounding fibres in transgenic poplars. Further analyses indicated a substantial increase in wood lignin content. Cellulose crystallinity, microfibril angle and stem mechanical properties are currently assessed. Results will be presented and discussed in the light of present hypothesis regarding CTL2 function in plant development.

National audience; Global climate changes in progress will impact tree productivity in the northern hemisphere. The understanding of physiological as well as genetic/molecular processes controlling plants response to abiotic stress will help to improve plant breeding. Recently, epigenetic mechanisms such as DNA methylation have been shown to participate to the control of plant development and their adaptation to environment through modifications of chromatin compaction and gene expression profiles. Phenotypic plasticity defines as the different phenotypes for a given genotype in distinct environments is a key process for plant to adapt to their changing environment. This is particularly relevant for perennialplants such as trees that are exposed to repeated fluctuations of their living conditions. In this context, drought is a significant threat to forest health and agro-ecosystem productivity. With the availability of its genome and its important natural genetic and phenotypic variations, Populus became a model tree.The aim of our project is to develop an integrative approach to identify ecophysiological and molecular bases, particularly DNA methylation, involved in phenotypic plasticity. Contrary to animals, plants exhibit a continuous development and their germline arise from very specific somatic tissue: the shoot apical meristem. We focus our effort to the study the role of DNA methylation in shoot apical meristem using various epigenomic approaches (MeDIP-SEQ, MeDIP-CHIP, WGBS) in parallel to transcriptomics and phenotyping. Our experimental designs include collection of genotypes and are established in controlled conditions such as in greenhouse and nursery as well as in field plantations. We have also characterized the first hypomethylated tree (DDM1-RNAi poplars) in different environments.Altogether, our results demonstrate the role of DNA methylation in memorizing environmental influence and identify the corresponding genes network in relation to phenotypic plasticity.

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

UMR DAP, équipe AFEF, Correspondance: costes@supagro.inra.fr; International audience; • The present study aimed to dissect tree architectural plasticity into genetic, ontogenetic and environmental effects over the first 4 yr of growth of an apple (Malus . domestica) F1 progeny by means of mixed linear modelling of repeated data. • Traits related to both growth and branching processes were annually assessed on different axes of the trees planted in a staggered-start design. Both spatial repetitions, (i.e. different axis types) and temporal repetitions (i.e. successive ages of trees) wereconsidered in a mixed linear model of repeated data.• A significant genotype effect was found for most studied traits and interactions between genotype and year and/or age were also detected. The analysis of repeated temporal measures highlighted that the magnitude of the decrease in primary growth is mainly determined by the first year of growth, and the decrease in bottomdiameter increment is concomitant with the first fruiting occurrence.• This approach allowed us to distinguish among the traits that were under genetic control, those for which this control is exerted differentially throughout tree life or depending on climatic conditions or an axis type. Mapping quantitative trait loci (QTL) that are specific to these different effects will constitute the next step in the research.

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.

Highlight Tomato quality could be improved under deficit irrigation while maintaining yield. The underlying genetic architecture is polygenic and varies with water availability. Candidate genes related to primary metabolism were identified., Water scarcity constitutes a crucial constraint for agriculture productivity. High-throughput approaches in model plant species identified hundreds of genes potentially involved in survival under drought, but few having beneficial effects on quality and yield. Nonetheless, controlled water deficit may improve fruit quality through higher concentration of flavor compounds. The underlying genetic determinants are still poorly known. In this study, we phenotyped 141 highly diverse small fruit tomato accessions for 27 traits under two contrasting watering conditions. A subset of 55 accessions exhibited increased metabolite contents and maintained yield under water deficit. Using 6100 single nucleotide polymorphisms (SNPs), association mapping revealed 31, 41, and 44 quantitative trait loci (QTLs) under drought, control, and both conditions, respectively. Twenty-five additional QTLs were interactive between conditions, emphasizing the interest in accounting for QTLs by watering regime interactions in fruit quality improvement. Combining our results with the loci previously identified in a biparental progeny resulted in 11 common QTLs and contributed to a first detailed characterization of the genetic determinants of response to water deficit in tomato. Major QTLs for fruit quality traits were dissected and candidate genes were proposed using expression and polymorphism data. The outcomes provide a basis for fruit quality improvement under deficit irrigation while limiting yield losses.

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.

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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.

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Iron, cobalt and iron–cobalt nanoparticle properties, such as diameter, saturation magnetization (Ms), crystal structure, surface composition and stability in physiological solutions, were investigated according to the annealing temperature used prior to their encapsulation into poly(d, l-lactic-co-glycolic acid) (PLGA) microcarriers. These new 60-μm microparticles should exhibit an Ms around 70 emu g−1 to be guided in real time from their intravascular injection site to a tumor with a magnetic resonance imaging scanner. The challenge in the preparation of the nanoparticles consisted in limiting Ms loss by oxidation and the release of metallic ions. It was found that when the annealing temperature reached 650 °C, Fe nanoparticles coalesced, the mean diameter reached (O) 361 ± 138 nm and Ms increased to 171 emu g−1. These nanoparticles exhibited a core of α-Fe and a shell of Fe3O4. On the opposite, Co nanoparticle properties were not affected by the annealing temperature: O and Ms were around 120 nm and 140 emu g−1, respectively. FeCo (60:40, atomic percent) nanoparticles coalesced at an annealing temperature >550 °C, O and Ms reached 217 nm and 213 emu g−1, respectively. Co and FeCo nanoparticles with a Co atomic proportion >15 % were coated with a graphite shell when the temperature was set to 550 °C. In physiological solution, Fe and Co nanoparticles significantly released more ions than FeCo nanoparticles. After the preparation steps prior to their encapsulation, the Ms of Fe and FeCo nanoparticles decreased by 25 and 3 %, respectively. FeCo–PLGA microparticles possessed a relatively high Ms (73 emu g−1) while that of Fe–PLGA microparticle (20 emu g−1) was too low for efficient targeting. The graphite shell was efficient to preserve Ms during the encapsulation.