Quantifying wheat sensitivities to environmental constraints to dissect G x E in the field
2017
Parent, Boris | Bonneau, Julien | Maphosa, Lance | Kovalchuk, Alex | Langridge, Peter | Fleury, Delphine | Écophysiologie des Plantes sous Stress environnementaux (LEPSE) ; Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro) | Australian Centre for Plant Functional Genomics (ACPFG) and School of Agriculture, Food and Wine, Waite Research Institute ; University of Adelaide | Australian Research Council; The Grains Research and Development Corporation [ACP00002-Q] | European Project: 244374
Yield is subject to strong Genotype by Environment interactions (G x E) in the field, especially under abiotic constraints such as soil water deficit (Drought, D) and high temperature (Heat, H). Since environmental conditions show strong fluctuations during the whole crop cycle, geneticists usually do not consider the environmental measures as quantitative variables, but rather as factors in multi-environment analyses. Based on 11 experiments in a field platform with contrasted temperature and soil water deficit, we determined the periods of sensitivity to drought and heat constraints in wheat (Triticum aestivum L.) and determined the average sensitivities for major yield components. G x E interactions were separated into their underlying components, constitutive (G), G x D, G x H and G x H x D, and were analysed for two genotypes, highlighting contrasted responses to heat and drought constraints. We then tested the constitutive and responsive behaviours of two strong Quantitative Trait Loci (QTL) previously associated with yield components. This analysis confirmed the constitutive effect of chromosome 1B QTL, and explained the G x E interaction of chromosome 3B QTL by a benefit of one allele when temperature rises. In addition to the method itself which can be applied to other datasets and populations, this study will support the cloning of a major yield QTL on chromosome 3B which is highly dependent on environmental conditions, and for which the climatic interaction is now quantified.
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