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Simulating the Yield Impacts of Organ-Level Quantitative Trait Loci Associated With Drought Response in Maize: A “Gene-to-Phenotype” Modeling Approach
Open accessAbstract
Under drought, substantial genotype–environment (G × E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this “gene-to-phenotype” gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G × E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such “leafy” genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G × E interactions for complex traits such as drought tolerance.
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“In fact, such component trait QTL have been successfully used to parametrize CGMs for studying genotype dependent response to environmental conditions [28, 29, 73, 94, 95].”
From Integrating Crop Growth Models with Whole Genome Prediction through Approximate Bayesian Computation (2015) · cites this paper as [73]
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Metadata
- Authors
- Chenu, K., Chapman, S. C., Tardieu, F., McLean, G., Welcker, C., & Hammer, G. L.
- Affiliations
- Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR)
- Commonwealth Scientific and Industrial Research Organisation (AU)
- Institut National de la Recherche Agronomique, Unité Mixte de Recherche 759, Laboratoire d'Ecophysiologie des Plantes sous Stress Environnementaux, 34060 Montpellier, France
- Department of Primary Industries (AU)
- The University of Queensland (AU)
- Corresponding author
- Chenu, Karine
- Venue
- Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-12-01
- Volume
- 183
- Issue
- 4
- Pages
- 1507-1523
- ISSN
- 0016-6731 (ISSN-L)
- 1943-2631
- PMC
- PMC2787435
- OpenAlex
- W2158656445
- Cited by
- 237
- References
- 70
- Citations by year
- 2026: 3 · 2025: 6 · 2024: 6 · 2023: 7 · 2022: 11 · 2021: 16 · 2020: 20 · 2019: 11 · 2018: 19 · 2017: 17 · 2016: 14 · 2015: 19 · 2014: 22 · 2013: 18 · 2012: 16
- FWCI
- 19.39
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Genetics (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- HAL (submittedVersion)
- Queensland Department of Agriculture and Fisheries archive of scientific and research publications (Queensland Department of Agriculture and Fisheries) (submittedVersion)
- Topics
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Genetics and Plant Breeding
- Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Crop Yield and Soil Fertility
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- maize, drought tolerance, quantitative trait loci, gene-environment interaction, leaf elongation, grain yield, recombinant inbred lines, pleiotropy, grain set, water consumption, drought simulation
- MeSH terms
- Breeding, Zea mays, Environment, Genotype, Models, Genetic, Phenotype, Rain, Stress, Physiological, Volatilization, Water, Plant Leaves, Quantitative Trait Loci, Droughts
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