Nutrient Sensing and Root System Architecture

Root system architecture (RSA) is the spatial arrangement of different parts of the plant root system. Its plasticity clearly reflects the interdependency between plants and their environment. On the one hand RSA represents the overall output of cell growth and differentiation within the root, on the other hand it greatly influences growth and development of the entire plant by allocating water and nutrients from the ground. As different parts of the root system are exposed to microscopically subdivided conditions within the soil, RSA also fulfils a sensory function gathering information about environmental cues which allow the plant - via signal transduction – to physiologically adapt to changing external condition, in particular the concentration of essential mineral nutrients. Thus, besides its role in agricultural productivity, RSA is an interesting model system for fundamental research in plant development and signalling.

Being a complex trait composed of many parameters, e.g. overall and main root length, number, length and angles of lateral roots etc., RSA is difficult to assess. However, due the interdependence of RSA parameters at the level of growth, development and information flow real progress in this area can only be made if we measure RSA comprehensively. Quantitative data are also required to integrate the root phenotypes with genome information, for example through quantitative trait analysis (QTL) or genome-wide association mapping (GWA).

EZ-Rhizo is a computer programme developed in our lab to allow researchers to carry out high-throughput analysis of images of plant roots, for example those obtained from Arabidopsis plants growing on vertical agar plates. This program is freely available and can be downloaded here. EZ-Rhizo has already been proven suitable for determining the principal components underlying the natural variation of RSA among 23 ecotypes of Arabidopsis thaliana (Armengaud et al. 2009, Plant J 57: 945-956 [online version]).

In the laboratory, we are measuring spatial and dynamic changes of RSA of Arabidopsis thaliana and Brassica in response to varying nutrient conditions (K, N, P, S), and we integrate the obtained data with genome information (QTL, GWA) as well as gene expression (nutrient transporters and their regulators) and metabolic profiles. Mutants are used to identify signalling pathways involved in specific RSA-nutrient interactions. To facilitate unbiased, randomised and automated phenotyping of RSA we have developed a modular root phenomics platform.