Genetic control of plasticity of oil yield for combined abiotic stresses using a joint approach of crop modelling 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 modelling and quantitative genetics to study the genetic control of oil yield plasticity for multiple abiotic stresses in sunflower....

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Published in:Plant, cell and environment cell and environment, 2017-10, Vol.40 (10), p.2276-2291
Main Authors: Mangin, Brigitte, Casadebaig, Pierre, Cadic, Eléna, Blanchet, Nicolas, Boniface, Marie‐Claude, Carrère, Sébastien, Gouzy, Jérôme, Legrand, Ludovic, Mayjonade, Baptiste, Pouilly, Nicolas, André, Thierry, Coque, Marie, Piquemal, Joël, Laporte, Marion, Vincourt, Patrick, Muños, Stéphane, Langlade, Nicolas B.
Format: Article
Language:English
Subjects:
Abiotic stress
Agricultural production
Agronomy
Alternative oxidase
Chromosome Mapping
Climate change
Climate effects
Cold
Cold Temperature
crop model
Crop yield
Crops
Crops, Agricultural - genetics
Cystatins
Drought
Environment
Genes
Genes, Plant
Genetic control
genetic variation
Genetics
Genome-wide association studies
Genome-Wide Association Study
Genomes
Hot Temperature
Hybrids
Indicators
Life Sciences
Modelling
Models, Theoretical
multi‐stress
Nitrogen
Oil
Oxidase
Phenotypic plasticity
Phenotypic variations
Plant Oils - metabolism
Plant stress
Plants (botany)
Plastic properties
Plasticity
Polymorphism, Single Nucleotide - genetics
Protein transport
Quantitative genetics
Quantitative trait loci
Quantitative Trait Loci - genetics
Regression analysis
Root development
Single-nucleotide polymorphism
Stress, Physiological - genetics
Vegetable oils
Vegetal Biology
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Summary: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 modelling 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 Single Nucleotide Polymorphisms (SNPs), we identified nine quantitative trait loci controlling oil yield plasticity to cold stress. Associated single nucleotide polymorphisms are localized in genes previously shown to be involved in cold stress responses: oligopeptide transporters, lipid transfer protein, 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. First, we developed a novel method to describe the abiotic stresses perceived by the plant using the dynamic ecophysiological model included in the SUNFLO crop model. This allowed us characterize 17 environments corresponding to a large range of cold, drought and nitrogen stresses situations. Secondly, we characterized, in the 17 environments, the oil yield plasticity to those three abiotic stresses in a sunflower core collection, defined as the linear response of oil yield to the modelled stresses. This allowed us to perform a genome‐wide association study on these oil yield plasticity phenotypes. In this article, we describe the GWAS only for cold stress, for which we identified nine regions bearing candidate genes. We restricted the publication of our results to cold because drought and nitrogen stress plasticities were genetically correlated and we believe the GWAS results on those phenotypes must be interpreted with caution. Nevertheless, the analysis on cold stress identified very promising candidate genes and
ISSN:0140-7791
1365-3040
DOI:10.1111/pce.12961