Using numerical plant models and phenotypic correlation space to design achievable ideotypes

Numerical plant models can predict the outcome of plant traits modifications resulting from genetic variations, on plant performance, by simulating physiological processes and their interaction with the environment. Optimization methods complement those models to design ideotypes, i.e. ideal values of a set of plant traits resulting in optimal adaptation for given combinations of environment and management, mainly through the maximization of a performance criteria (e.g. yield, light interception). As use of simulation models gains momentum in plant breeding, numerical experiments must be carefully engineered to provide accurate and attainable results, rooting them in biological reality. Here, we propose a multi-objective optimization formulation that includes a metric of performance, returned by the numerical model, and a metric of feasibility, accounting for correlations between traits based on field observations. We applied this approach to two contrasting models: a process-based crop model of sunflower and a functional-structural plant model of apple trees. In both cases, the method successfully characterized key plant traits and identified a continuum of optimal solutions, ranging from the most feasible to the most efficient. The present study thus provides successful proof of concept for this enhanced modeling approach, which identified paths for desirable trait modification, including direction and intensity.Comment: 25 pages, 5 figures, 2017, Plant, Cell and Environmen

Increased genetic diversity improves crop yield stability under climate variability: a computational study on sunflower

A crop can be represented as a biotechnical system in which components are either chosen (cultivar, management) or given (soil, climate) and whose combination generates highly variable stress patterns and yield responses. Here, we used modeling and simulation to predict the crop phenotypic plasticity resulting from the interaction of plant traits (G), climatic variability (E) and management actions (M). We designed two in silico experiments that compared existing and virtual sunflower cultivars (Helianthus annuus L.) in a target population of cropping environments by simulating a range of indicators of crop performance. Optimization methods were then used to search for GEM combinations that matched desired crop specifications. Computational experiments showed that the fit of particular cultivars in specific environments is gradually increasing with the knowledge of pedo-climatic conditions. At the regional scale, tuning the choice of cultivar impacted crop performance the same magnitude as the effect of yearly genetic progress made by breeding. When considering virtual genetic material, designed by recombining plant traits, cultivar choice had a greater positive impact on crop performance and stability. Results suggested that breeding for key traits conferring plant plasticity improved cultivar global adaptation capacity whereas increasing genetic diversity allowed to choose cultivars with distinctive traits that were more adapted to specific conditions. Consequently, breeding genetic material that is both plastic and diverse may improve yield stability of agricultural systems exposed to climatic variability. We argue that process-based modeling could help enhancing spatial management of cultivated genetic diversity and could be integrated in functional breeding approaches

Genetic control of plasticity of oil yield for combined abiotic stresses using a joint approach of crop modeling and genome-wide association

Understanding the genetic basis of phenotypic plasticity is crucial for predicting and managing climate change effects on wild plants and crops. Here, we combined crop modeling and quantitative genetics to study the genetic control of oil yield plasticity for multiple abiotic stresses in sunflower. First we developed stress indicators to characterize 14 environments for three abiotic stresses (cold, drought and nitrogen) using the SUNFLO crop model and phenotypic variations of three commercial varieties. The computed plant stress indicators better explain yield variation than descriptors at the climatic or crop levels. In those environments, we observed oil yield of 317 sunflower hybrids and regressed it with three selected stress indicators. The slopes of cold stress norm reaction were used as plasticity phenotypes in the following genome-wide association study. Among the 65,534 tested SNP, we identified nine QTL controlling oil yield plasticity to cold stress. Associated SNP are localized in genes previously shown to be involved in cold stress responses: oligopeptide transporters, LTP, cystatin, alternative oxidase, or root development. This novel approach opens new perspectives to identify genomic regions involved in genotype-by-environment interaction of a complex traits to multiple stresses in realistic natural or agronomical conditions.Comment: 12 pages, 5 figures, Plant, Cell and Environmen

A Gene-Phenotype Network Based on Genetic Variability for Drought Responses Reveals Key Physiological Processes in Controlled and Natural Environments

Identifying the connections between molecular and physiological processes underlying the diversity of drought stress responses in plants is key for basic and applied science. Drought stress response involves a large number of molecular pathways and subsequent physiological processes. Therefore, it constitutes an archetypical systems biology model. We first inferred a gene-phenotype network exploiting differences in drought responses of eight sunflower (Helianthus annuus) genotypes to two drought stress scenarios. Large transcriptomic data were obtained with the sunflower Affymetrix microarray, comprising 32423 probesets, and were associated to nine morpho-physiological traits (integrated transpired water, leaf transpiration rate, osmotic potential, relative water content, leaf mass per area, carbon isotope discrimination, plant height, number of leaves and collar diameter) using sPLS regression. Overall, we could associate the expression patterns of 1263 probesets to six phenotypic traits and identify if correlations were due to treatment, genotype and/or their interaction. We also identified genes whose expression is affected at moderate and/or intense drought stress together with genes whose expression variation could explain phenotypic and drought tolerance variability among our genetic material. We then used the network model to study phenotypic changes in less tractable agronomical conditions, i.e. sunflower hybrids subjected to different watering regimes in field trials. Mapping this new dataset in the gene-phenotype network allowed us to identify genes whose expression was robustly affected by water deprivation in both controlled and field conditions. The enrichment in genes correlated to relative water content and osmotic potential provides evidence of the importance of these traits in agronomical conditions

Sunflower Hybrid Breeding: From Markers to Genomic Selection

In sunflower, molecular markers for simple traits as, e.g., fertility restoration, high oleic acid content, herbicide tolerance or resistances to Plasmopara halstedii, Puccinia helianthi, or Orobanche cumana have been successfully used in marker-assisted breeding programs for years. However, agronomically important complex quantitative traits like yield, heterosis, drought tolerance, oil content or selection for disease resistance, e.g., against Sclerotinia sclerotiorum have been challenging and will require genome-wide approaches. Plant genetic resources for sunflower are being collected and conserved worldwide that represent valuable resources to study complex traits. Sunflower association panels provide the basis for genome-wide association studies, overcoming disadvantages of biparental populations. Advances in technologies and the availability of the sunflower genome sequence made novel approaches on the whole genome level possible. Genotype-by-sequencing, and whole genome sequencing based on next generation sequencing technologies facilitated the production of large amounts of SNP markers for high density maps as well as SNP arrays and allowed genome-wide association studies and genomic selection in sunflower. Genome wide or candidate gene based association studies have been performed for traits like branching, flowering time, resistance to Sclerotinia head and stalk rot. First steps in genomic selection with regard to hybrid performance and hybrid oil content have shown that genomic selection can successfully address complex quantitative traits in sunflower and will help to speed up sunflower breeding programs in the future. To make sunflower more competitive toward other oil crops higher levels of resistance against pathogens and better yield performance are required. In addition, optimizing plant architecture toward a more complex growth type for higher plant densities has the potential to considerably increase yields per hectare. Integrative approaches combining omic technologies (genomics, transcriptomics, proteomics, metabolomics and phenomics) using bioinformatic tools will facilitate the identification of target genes and markers for complex traits and will give a better insight into the mechanisms behind the traits

Relations génétiques entre caractéristiques de la phase juvénile et productivité chez le maïs ensilage I. - Vigueur au stade jeune et productivité

La vigueur au stade jeune, facteur de productivité et de stabilité du maïs ensilage, est mesurée au stade plantule (2 à 3 feuilles visibles) et au moment de la différenciation florale à partir de critères pondéraux. Trente familles de demi-frères denté x corné sont comparées pour ces critères, qui sont par ailleurs mis en relation avec des caractéristiques du stade adulte : productivité et teneur en matière sèche à la récolte, caractères morphologiques. Les productivités en matière sèche des organes en croissance au stade plantule sont fortement liées au prélèvement de matière sèche dans la semence. Il subsiste toutefois, au niveau des parties aériennes, des différences de vigueur qui, dans les conditions de l'essai, sont positivement liées aux différences de rendement en matière sèche à la récolte. Le poids de la partie ( 1er entrenoeud + coléoptile) semble intéressant comme covariable pour estimer correctement au champ un critère de rapidité de levée. On n'observe pas de liaison entre caractéristiques du stade adulte et vigueur au moment de la différenciation florale. La corrélation (rendement en matière sèche, teneur en matière sèche) observée dans cet essai est proche de zéro. On interprète ce fait par l'intervention d'un stress hydrique au cours de la période floraison-maturité, qui aura

Relations entre rythme d’apparition des feuilles, nombre total de feuilles et précocité de floraison chez le maïs

Les rythmes comparés d’apparition des limbes et des gaines foliaires de maïs sont analysés dans leur relation avec la précocité de floraison et le nombre total de feuilles. Le phyllotherme, somme de température qui sépare l’apparition de deux gaines successives, varie selon le génotype en fonction de l’âge de la plante, en relation à la fois avec la taille du système foliaire et avec sa rapidité de mise en place. La valeur moyenne du phyllotherme au stade jeune pourrait constituer un critère de sélection intéressant pour accroître la vigueur de la plante adulte à précocité constante.The rate of sheath and blade emergence was analyzed in maize, in relation to earliness of flowering and total leaf number. The phyllotherm, defined as the sum of degree days between the emergence of two successive sheaths, was found to depend on the stage of development. Some correlations were found between the phyllotherm, the total number of leaves and earliness. The mean value of the phyllotherm at the juvenile stage could be used as a selection criterion to improve the vigour of the adult plant for a given earliness of flowering

Relations entre rythme d'apparition des feuilles, nombre total de feuilles et précocité de floraison chez le maïs

Les rythmes comparés d'apparition des limbes et des gaines foliaires de maïs sont analysés dans leur relation avec la précocité de floraison et le nombre total de feuilles. Le phyllotherme, somme de température qui sépare l'apparition de deux gaines successives, varie selon le génotype en fonction de l'âge de la plante, en relation à la fois avec la taille du système foliaire et avec sa rapidité de mise en place. La valeur moyenne du phyllotherme au stade jeune pourrait constituer un critère de sélection intéressant pour accroître la vigueur de la plante adulte à précocité constante