Multicellular Cell Differentiation Model: The control of root hair patterning in Aspergillus thaliana

Plants absorb water and nutrients from the soil through hairs that grow along their roots. As such, being able to manipulate root hair numbers may be advantageous to the development of crops more resistant to drought and nutrient deficient soils.

The outer layer of root cells, in contact with the soil, is called the epidermis. Epidermal cells have the ability to grow a hair, in fact hair growth is thought to be their default developmental pathway. It would, however, be expensive for the plant to grow a hair from every epidermal cell and mechanisms have evolved to prevent hair growth in some. These mechanisms control the pattern of hair cells and are thus heavily dependent on spatial information, obtained by cell signalling.

In Arabidopsis, a complex transcription network, controlling the exit from the hair growth fate, has been uncovered. Mathematical modelling has shown this network to be sufficient to control many aspects of Arabidopsis root hair patterning [Savage 2008, Savage 2013]. Unpublished modelling data has highlighted gaps in our knowledge of root hair patterning control.

In this project we will be asking: Is there any way (parameter sets, initial conditions) the current network can reproduce some specific biological data? And what can be added/removed from the network to make it (more) robustly reproduce the data?

The student will generate and analyse mathematical/computational multicellular models of the Arabidopsis patterning network. The student will work in close collaboration with the Bishopp Lab, who will be performing the experiments within the project. The student will use modelling to help understand biological data, uncover biological mechanism, predict the outcome of experiments and aid experimental design.

Applicants should have a degree in mathematics, physics or computer science. Students with other degrees must have strong evidence of interest and achievement in mathematics and/or computation.