Moritz Hess, PhD student

Moritz Hess, PhD student in Ensminger lab


It is expected that almost all plant populations are locally adapted to the environmental conditions in their habitat. This adaptation is governed by the results of beneficial genetic mutations that provide the carrying owner with increased fitness. Knowing the influence of these mutations on global physiology would allow us to better understand adaptation and could be used to anticipate an individual’s performance in a defined environmental condition. In the forestry or crop industries, this would lead to the opportunity to select a certain clone or race that would be perfectly adapted to the habitat it was intended to be planted in. While a detailed, albeit incomplete picture of the relationship of genomic mutations and global molecular physiology has been drawn in model organisms like Arabidopsis thaliana, Oryza sativa, or Populus Trichocarpa, there is a lack of knowledge in commercially important gymnosperm forest tree species like Pseudotsuga menziesii (Douglas-fir). The DougAdapt project aims at closing this gap. Here, the variability of drought responses in differentially adapted Douglas-fir populations is analyzed on various scales and will be linked with allelic variation in protein coding genes.

My thesis project, which is embedded in the DougAdapt project, aims at studying the reaction of differentially adapted populations to changing availability of water on the level of global gene expression in leaf tissue. I investigate this response to changing conditions in free growing trees, during the course of a growing season on two common garden sites. Global gene expression is measured by Illumina RNA-Seq. The high-dimensional data will be interpreted by exploiting co-expression behaviour of functionally related genes.  This will result in a global picture of a tree’s physiological state, dependent on origin and water availability. I will interpret this picture by including global gene expression data from controlled drought stressed Douglas-fir seedlings as well as data from drought-stressed model organisms. Thus I will select a set of genes whose expression is highly correlated with the availability of water. The expression dynamics of this gene set, inferred by Illumina RNA-Seq, will be validated by qPCR.