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Prediction and Modeling of Hybrid Performance and Yield Gain in Oilseed Rape by Systems Biology (PROGReSs)

Project

Production processes

This project contributes to the research aim 'Production processes'. Which funding institutions are active for this aim? What are the sub-aims? Take a look:
Production processes


Project code: JKI-PB-08-1215
Contract period: 01.07.2014 - 31.08.2018
Purpose of research: Applied research

The PROGReSs project constitutes a nationwide effort of sufficient scale and expertise to combine iterative modeling, based on the ad hoc production of new quantitative data, with the relevant aspects of genetic, developmental and environmental responses - a systems biology approach. Such an approach would particularly benefit translational research. The systems biological approach to model genotype-phenotype-environment relations will deal with large scale quantitative data generated in a tri-dimensional experimental design (genome/phenome/environment). For this purpose new genetic variation illustrated by 2 different sets of 400 double haploid (DHs) winter oilseed rape genotypes, and 1600 experimental hybrid combinations (produced by crossing the 2 sets of DHs with two different mother lines) will be used. As shown schematically in Figure 1 (Appendix 1), all the participants in our PROGReSs network will contribute to the coordinated hypothesis-driven production of experimental data, which will be derived from (1) plant material and field trials, (2) high-throughput genome-wide (genomic, transcriptomic and epigenetic) and deep phenotyping techniques, (3) geo-referenced soil and phenotype sensing and (4) registration of climatic data in an iterative process for modeling and validation of different algorithms destined to dissect and predict hybrid performance and yield gain in oilseed rape. These data will be integrated into progressively more powerful computational and mathematical models that span the molecular and tissue/organ scales. In turn, these models will provide further hypotheses to be tested, as well as increasingly more powerful analysis tools, ultimately leading to a general model of hybrid performance and yield architecture and their genesis under natural conditions.

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Subjects

Framework programme

BMEL Frameworkprogramme 2008

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