Genome-wide analysis of yield in Europe: allelic effects as functions of drought and heat scenarios
2016
Millet, Emilie | Welcker, Claude | Kruijer, Willem | Negro, Sandra | Coupel-Ledru, Aude | Nicolas, Stephane | Laborde, Jacques | Bauland, Cyril | Praud, Sebastien | Ranc, Nicolas | Presterl, Thomas | Tuberosa, Roberto | Bedo, Zoltan | Draye, Xavier | Usadel, Bjoern | Charcosset, Alain | van Eeuwijk, Fred | Tardieu, Francois | 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) | Biometrics applied Statistics, Department of Plant Science ; Wageningen University and Research [Wageningen] (WUR) | Génétique Quantitative et Evolution - Le Moulon (Génétique Végétale) (GQE-Le Moulon) ; Institut National de la Recherche Agronomique (INRA)-Université Paris-Sud - Paris 11 (UP11)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS) | Unité expérimentale du maïs (BORDX ST-MARTIN UE) ; Institut National de la Recherche Agronomique (INRA) | Centre de Recherche de Chappes ; BIOGEMMA | Syngenta | KWS SAAT SE & Co.KGaA | Department of Agricultural Sciences ; Alma Mater Studiorum Università di Bologna = University of Bologna (UNIBO) | MTA ATK/ AI CAR HAS ; Hungarian Academy of Sciences (MTA) | ELIA ; Université Catholique de Louvain = Catholic University of Louvain (UCL) | Institute for Botany and Molecular Genetics, BioSC ; RWTH Aachen University = Rheinisch-Westfälische Technische Hochschule Aachen (RWTH Aachen) | Biometris Applied Statistics, Department of Plant Science ; Wageningen University and Research [Wageningen] (WUR) | Amaizing, ANR-10-BTBR-01 | ANR-10-BTBR-0001,AMAIZING,Développer de nouvelles variétés de maïs pour une agriculture durable: une approche intégrée de la génomique à la sélection(2010) | European Project: 244374
Assessing the genetic variability of plant performance under heat and drought scenarios can contribute to reduce the negative effects of climate change. We propose here an approach that consisted of (1) clustering time courses of environmental variables simulated by a crop model in current (35 years × 55 sites) and future conditions, into six scenarios of temperature and water deficit as experienced by maize plants; (2) performing 29 field experiments in contrasting conditions across Europe with 244 maize hybrids; (3) assigning individual experiments to scenarios based on environmental conditions as measured in each field experiment; frequencies of temperature scenarios in our experiments corresponded to future heat scenarios (+5{degree sign}C); (4) analysing the genetic variation of plant performance for each environmental scenario. Forty-eight quantitative trait loci (QTLs) of yield were identified by association genetics using a multi-environment multi-locus model. Eight and twelve QTLs were associated to tolerances to heat and drought stresses because they were specific of hot and dry scenarios respectively, with low or even negative allelic effects in favourable scenarios. Twenty-four QTLs improved yield in favourable conditions but showed non-significant effects under stress, they were therefore associated with higher sensitivity. Our approach showed a pattern of QTL effects expressed as functions of environmental variables and scenarios, allowing us to suggest hypotheses for mechanisms and candidate genes underlying each QTL. It can be used for assessing the performance of genotypes and the contribution of genomic regions under current and future stress situations and to accelerate breeding for drought-prone environments.
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