Predictions of heading date in bread wheat (Triticum aestivum L.) using QTL-based parameters of an ecophysiological model
Open Access
- 22 August 2014
- journal article
- research article
- Published by Oxford University Press (OUP) in Journal of Experimental Botany
- Vol. 65 (20), 5849-5865
- https://doi.org/10.1093/jxb/eru328
Abstract
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 ( Vsat and Pbase , 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 Vsat and Pbase with 11 and 12 associated genetic markers accounted for 71 and 68% of the variance of these parameters, respectively. QTL-based Vsat and Pbase 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.Keywords
This publication has 85 references indexed in Scilit:
- Integration of molecular and physiological models to explain time of anthesis in wheatAnnals of Botany, 2013
- Copy Number Variation Affecting the Photoperiod-B1 and Vernalization-A1 Genes Is Associated with Altered Flowering Time in Wheat (Triticum aestivum)PLOS ONE, 2012
- Modelling predicts that heat stress, not drought, will increase vulnerability of wheat in EuropeScientific Reports, 2011
- Genetic Architecture of Flowering-Time Variation in Arabidopsis thalianaGenetics, 2011
- Simulating the Yield Impacts of Organ-Level Quantitative Trait Loci Associated With Drought Response in Maize: A “Gene-to-Phenotype” Modeling ApproachGenetics, 2009
- A genetic network of flowering‐time genes in wheat leaves, in which an APETALA1/FRUITFULL‐like gene, VRN1, is upstream of FLOWERING LOCUS TThe Plant Journal, 2009
- Quantitative Genetics and Functional-Structural Plant Growth Models: Simulation of Quantitative Trait Loci Detection for Model Parameters and Application to Potential Yield OptimizationAnnals of Botany, 2007
- The wheat and barley vernalization gene VRN3 is an orthologue of FTProceedings of the National Academy of Sciences of the United States of America, 2006
- Most significant genome regions involved in the control of earliness traits in bread wheat, as revealed by QTL meta-analysisTheoretical and Applied Genetics, 2006
- A Brief History of Systems BiologyPlant Cell, 2006