J Integr Plant Biol. ›› 2016, Vol. 58 ›› Issue (3): 254-265.DOI: 10.1111/jipb.12433

• Research Articles • Previous Articles     Next Articles

Statistical modeling of nitrogen-dependent modulation of root system architecture in Arabidopsis thaliana

Takao Araya1,2, Takuya Kubo3, Nicolaus von Wirén2 and Hideki Takahashi1*   

  1. 1Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA
    2Molecular Plant Nutrition, Leibniz Institute of Plant Genetics and Crop Plant Research, D-06466 Gatersleben, Germany
    3Graduate School of Environmental Science, Hokkaido University, Sapporo 060-0810, Japan
  • Received:2015-07-14 Accepted:2015-09-28 Published:2016-03-18
  • About author:*Correspondence: E-mail: htakaha@msu.edu

Abstract:

Plant root development is strongly affected by nutrient availability. Despite the importance of structure and function of roots in nutrient acquisition, statistical modeling approaches to evaluate dynamic and temporal modulations of root system architecture in response to nutrient availability have remained as widely open and exploratory areas in root biology. In this study, we developed a statistical modeling approach to investigate modulations of root system architecture in response to nitrogen availability. Mathematical models were designed for quantitative assessment of root growth and root branching phenotypes and their dynamic relationships based on hierarchical configuration of primary and lateral roots formulating the fishbone-shaped root system architecture in Arabidopsis thaliana. Time-series datasets reporting dynamic changes in root developmental traits on different nitrate or ammonium concentrations were generated for statistical analyses. Regression analyses unraveled key parameters associated with: (i) inhibition of primary root growth under nitrogen limitation or on ammonium; (ii) rapid progression of lateral root emergence in response to ammonium; and (iii) inhibition of lateral root elongation in the presence of excess nitrate or ammonium. This study provides a statistical framework for interpreting dynamic modulation of root system architecture, supported by meta-analysis of datasets displaying morphological responses of roots to diverse nitrogen supplies.

Key words: Ammonium, mathematical modeling, nitrate, nitrogen, root system architecture

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