Predictions of heading date in bread wheat (Triticum aestivum L.) using QTL-based parameters of an ecophysiological model
| Autor: | Jacques Le Gouis, Etienne Paux, Vincent Allard, Scott Chapman, Jacques Bordes, François Balfourier, Matthieu Bogard, Catherine Ravel |
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| Přispěvatelé: | Génétique Diversité et Ecophysiologie des Céréales (GDEC), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), CSIRO, St Lucia, Qld, Australia, Partenaires INRAE, European Project: 289842,EC:FP7:KBBE,FP7-KBBE-2011-5,ADAPTAWHEAT(2012) |
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Time Factors
Genotype Physiology Photoperiod [SDV]Life Sciences [q-bio] Quantitative Trait Loci Flowers Plant Science Breeding Environment Biology Quantitative trait locus Models Biological phenology heading date SPRING WHEAT wheat Linear regression [SDV.BV]Life Sciences [q-bio]/Vegetal Biology Cultivar Triticum Selection (genetic algorithm) 2. Zero hunger RECOMBINANT INBRED LINES Phenology Sowing Vernalization Quantitative genetics Association genetics WINTER-WHEAT Adaptation Physiological ecophysiological model FLOWERING-TIME GENES WATER-DEFICIT Phenotype Agronomy CROP SIMULATION SYSTEMS BIOLOGY [SDE]Environmental Sciences gene-based modelling HEXAPLOWHEAT EARLINESS COMPONENTS Genome Plant QUANTITATIVE GENETICS Research Paper |
| Zdroj: | Journal of Experimental Botany Journal of Experimental Botany, Oxford University Press (OUP), 2014, 65 (20), pp.5849-5865. ⟨10.1093/jxb/eru328⟩ |
| ISSN: | 0022-0957 1460-2431 |
| DOI: | 10.1093/jxb/eru328⟩ |
| Popis: | Highlight text QTL-based parameters of an ecophysiological model, calibrated on an association genetics panel of 210 genotypes, allowed prediction of heading dates of 80 independent genotypes in six independent experiments with a median prediction error of 5.6 days. Prediction of wheat phenology facilitates the selection of cultivars with specific adaptations to a particular environment. However, while QTL analysis for heading date can identify major genes controlling phenology, the results are limited to the environments and genotypes tested. Moreover, while ecophysiological models allow accurate predictions in new environments, they may require substantial phenotypic data to parameterize each genotype. Also, the model parameters are rarely related to all underlying genes, and all the possible allelic combinations that could be obtained by breeding cannot be tested with models. In this study, a QTL-based model is proposed to predict heading date in bread wheat (Triticum aestivum L.). Two parameters of an ecophysiological model (V sat and P base, representing genotype vernalization requirements and photoperiod sensitivity, respectively) were optimized for 210 genotypes grown in 10 contrasting location × sowing date combinations. Multiple linear regression models predicting V sat and P base with 11 and 12 associated genetic markers accounted for 71 and 68% of the variance of these parameters, respectively. QTL-based V sat and P base estimates were able to predict heading date of an independent validation data set (88 genotypes in six location × sowing date combinations) with a root mean square error of prediction of 5 to 8.6 days, explaining 48 to 63% of the variation for heading date. The QTL-based model proposed in this study may be used for agronomic purposes and to assist breeders in suggesting locally adapted ideotypes for wheat phenology. |
| Databáze: | OpenAIRE |
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