PHENOVIGOUR | Elucidating the phenotypic determinants of hybrid vigour

Summary
How organismal traits are inherited in offspring is a long-standing, open question. Hybrids between unrelated individuals of plants or animals often show greater vigour, disease resistance, and fertility. The genetic mechanisms behind the deviation of hybrids from the parental phenotype have been widely studied. However, hybrid vigour remains difficult to predict qualitatively and quantitatively. A key bottleneck is that it remains difficult to explain why different traits are inherited differently. I will overcome this bottleneck to explain trait inheritance and predict hybrid vigour in crop plants from a phenotypic stand point. I will do this by bridging old evolutionary principles with modern models of ecological theory, via the following three objectives: 1. Determining whether in hybrids the degree of trait deviation from the parental phenotype increases with the degree of trait integration; 2. Testing whether modelling relationships between traits can quantitatively explain hybrid vigour; and 3. Building a predictive model of hybrid performance in the field. My project will build on a combination of comparative, experimental and modelling approaches, and a large collection of available phenotypic data in crop plants. In addition, I will use cutting-edge phenotyping facilities to test underlying hypotheses on two experimental species: maize (Zea mays) and sorghum (Sorghum bicolor). The novel hypothesis is that deviation of a trait in a hybrid is the geometric result of the nonlinear effects of traits at lower levels of integration. The objectives are designed to provide a timely breakthrough in the fundamental understanding of variation in trait inheritance. Further, my approach will also enable predictive models of hybrid performance in crop plants to be developed, which would be an outstanding tool for breeders.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/949843
Start date: 01-04-2021
End date: 31-03-2026
Total budget - Public funding: 1 495 182,00 Euro - 1 495 182,00 Euro
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Original description

How organismal traits are inherited in offspring is a long-standing, open question. Hybrids between unrelated individuals of plants or animals often show greater vigour, disease resistance, and fertility. The genetic mechanisms behind the deviation of hybrids from the parental phenotype have been widely studied. However, hybrid vigour remains difficult to predict qualitatively and quantitatively. A key bottleneck is that it remains difficult to explain why different traits are inherited differently. I will overcome this bottleneck to explain trait inheritance and predict hybrid vigour in crop plants from a phenotypic stand point. I will do this by bridging old evolutionary principles with modern models of ecological theory, via the following three objectives: 1. Determining whether in hybrids the degree of trait deviation from the parental phenotype increases with the degree of trait integration; 2. Testing whether modelling relationships between traits can quantitatively explain hybrid vigour; and 3. Building a predictive model of hybrid performance in the field. My project will build on a combination of comparative, experimental and modelling approaches, and a large collection of available phenotypic data in crop plants. In addition, I will use cutting-edge phenotyping facilities to test underlying hypotheses on two experimental species: maize (Zea mays) and sorghum (Sorghum bicolor). The novel hypothesis is that deviation of a trait in a hybrid is the geometric result of the nonlinear effects of traits at lower levels of integration. The objectives are designed to provide a timely breakthrough in the fundamental understanding of variation in trait inheritance. Further, my approach will also enable predictive models of hybrid performance in crop plants to be developed, which would be an outstanding tool for breeders.

Status

SIGNED

Call topic

ERC-2020-STG

Update Date

27-04-2024
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Horizon 2020
H2020-EU.1. EXCELLENT SCIENCE
H2020-EU.1.1. EXCELLENT SCIENCE - European Research Council (ERC)
ERC-2020
ERC-2020-STG