Recent developments in several omics platforms have made it possible to generate huge amounts
of genetic data. However, when trying to unravel how a genotype translates into a phenotype,
research often returns to traditional and laborious methods, and GxE interaction remains difficult
to detect. Ecophysiological models can quantify the effect of an environment on a phenotype, but
incorporation of genetic data within these models has been limited to black box-models.
In this research, we aim to bridge the gap between genotype and phenotype through the new
domain of crop systems biology. More specifically, the effect of cell wall-related enzymes will be
translated to an altered drought response and yield in wheat (T. aestivum). To this end, several
wheat genotypes, differing in their drought response, will be monitored with sensors for plant
modelling and sampled for gene expression analysis. The up- or downregulation in gene
expression will be linked to different simulated plant variables to detect GxE interaction. Gene
expression will be translated into an altered cell growth, affecting the hydraulic properties in the
plant and thereby affecting its drought response. This drought response will be modelled with an
ecophysiological model, which will be combined with existing growth models to simulate yield.
With this project, we aim to show that hydraulic properties should be included in breeding
programs and we want to point out key regulating genes that should be focussed on.