111 research outputs found
Prediction of sunflower leaf area at vegetative stage by image analysis and application to the estimation of water stress response parameters in post-registration varieties
The automatic measurement of developmental and physiological responses of
sunflowers to water stress represents an applied challenge for a better
knowledge of the varieties available to growers, but also a fundamental one for
identifying the biological, genetic and molecular bases of plant response to
their environment.On INRAE Toulouse's Heliaphen high-throughput phenotyping
platform, we set up two experiments, each with 8 varieties (2*96 plants), and
acquired images of plants subjected or not to water stress, using a light
barrier on a daily basis. At the same time, we manually measured the leaf
surfaces of these plants every other day for the duration of the stress, which
lasted around ten days. The images were analyzed to extract morphological
characteristics of the segmented plants and different models were evaluated to
estimate total plant leaf areas using these data.A linear model with a
posteriori smoothing was used to estimate total leaf area with a relative
squared error of 11% and an efficiency of 93%. Leaf areas estimated
conventionally or with the developed model were used to calculate the leaf
expansion and transpiration responses (LER and TR) used in the SUNFLO crop
model for 8 sunflower varieties studied. Correlation coefficients of 0.61 and
0.81 for LER and TR respectively validate the use of image-based leaf area
estimation. However, the estimated values for LER are lower than for the manual
method on Heliaphen, but closer overall to the manual method on
greenhouse-grown plants, potentially suggesting an overestimation of stress
sensitivity.It can be concluded that the LE and TR parameter estimates can be
used for simulations. The low cost of this method (compared with manual
measurements), the possibility of parallelizing and repeating measurements on
the Heliaphen platform, and of benefiting from the Heliaphen platform's data
management, are major improvements for valorizing the SUNFLO model and
characterizing the drought sensitivity of cultivated varieties.Comment: in French languag
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
Genome-wide and comparative phylogenetic analysis of senescence-associated NAC transcription factors in sunflower (Helianthus annuus)
Leaf senescence delay impacts positively in grain yield by maintaining the photosynthetic area during the reproductive stage and during grain filling. Therefore a comprehensive understanding of the gene families associated with leaf senescence is essential. NAC transcription factors (TF) form a large plant-specific gene family involved in regulating development, senescence, and responses to biotic and abiotic stresses. The main goal of this work was to identify sunflower NAC TF (HaNAC) and their association with senescence, studying their orthologous to understand possible functional relationships between genes of different species. To clarify the orthologous relationships, we used an in-depth comparative study of four divergent taxa, in dicots and monocots, with completely sequenced genomes (Arabidopsis thaliana, Vitis vinifera, Musa acuminata and Oryza sativa). These orthologous groups provide a curated resource for large scale protein sequence annotation of NAC TF. From the 151 HaNAC genes detected in the latest version of the sunflower genome, 50 genes were associated with senescence traits. These genes showed significant differential expression in two contrasting lines according to an RNAseq assay. An assessment of overexpressing the Arabidopsis line for HaNAC001 (a gene of the same orthologous group of Arabidopsis thaliana ORE1) revealed that this line displayed a significantly higher number of senescent leaves and a pronounced change in development rate. This finding suggests HaNAC001 as an interesting candidate to explore the molecular regulation of senescence in sunflower
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
Tinkering with the C-Function: A Molecular Frame for the Selection of Double Flowers in Cultivated Roses
International audienc
Gene banks for wild and cultivated sunflower genetic resources
Modern breeding of sunflower (Helianthus annuus L.), which started 100 years ago, increased the number and the diversity of cultivated forms. In addition, for more than 50 years, wild sunflower and other Helianthus species have been collected in North America where they all originated. Collections of both cultivated and wild forms are maintained in gene banks in many countries where sunflower is an important crop, with some specificity according to the availability of germplasm and to local research and breeding programmes. Cultivated material includes land races, open pollinated varieties, synthetics and inbred lines. The majority of wild accessions are ecotypes of wild Helianthus annuus, but also 52 other species of Helianthus and a few related genera. The activities of three gene banks, in USA, France and Serbia, are described in detail, supplemented by data from seven other countries. Past and future uses of the genetic resources for environmental adaptation and breeding are discussed in relation to genomic and improved phenotypic knowledge of the cultivated and wild accessions available in the gene banks.L’amélioration moderne du tournesol (Helianthus annuus L.) a débuté il y a un siècle, diversifiant et augmentant le nombre des formes cultivées du tournesol. De plus, des collectes de tournesols sauvages et d’espèces du genre Helianthus ont lieu depuis 50 ans en Amérique du Nord d’où ils sont tous originaires. Ainsi, des collections de tournesols cultivés et sauvages sont conservées par des centres de ressources génétiques dans de nombreux pays où le tournesol est une culture importante. Chacun d’eux présente des spécificités par rapport aux ressources génétiques maintenues, en fonction des programmes de recherche ou de sélection variétale locales. Le matériel génétique cultivé comprend des écotypes, des populations et des lignées tandis que les accessions sauvages correspondent eux écotypes d’Helianthus annuus sauvages et des 52 autres espèces apparentées du genre Helianthus. Les activités de trois centres de ressources génétiques des États-Unis, de la France et de la Serbie sont décrites en détail, complétées par des données provenant des centres de sept autres pays. L’historique de l’utilisation des ressources génétiques et les perspectives futures pour l’adaptation des variétés à l’environnement sont discutés ainsi que leur caractérisation au niveau génomique et phénotypique.The Supplementary Material is available at [https://www.ocljournal.org/10.1051/ocl/2020004/olm]
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