Standardized mapping of nodulation patterns in legume roots

• Published in: The New phytologist 2014-05, Vol.202 (3), p.1083-1094
• Main Authors: Remmler, Lauren, Clairmont, Lindsey, Rolland‐Lagan, Anne‐Gaëlle, Guinel, Frédérique Catherine
• Format: Article
• Language: English
• Subjects: Comparative analysis; Computer programs; Computer software; Crop improvement; Crops; Data analysis; Datasets; Density; Drug therapy; Environmental conditions; environmental factors; genotype; Genotypes; image analysis; Image processing; Legumes; Methods; mutants; Mutation - genetics; Nodulation; nodulation zone; Nodules; nodule‐to‐root density; Organogenesis; Peas; phenotype; Phenotypes; Phenotyping; Pisum sativum; Pisum sativum - physiology; Plant Root Nodulation - physiology; Plant roots; Plant Roots - physiology; Plants; quantitative analysis; root system architecture; root system equivalent; Root systems; Roots; Roots of functions; Software; soil; Spatial analysis; spatial nodule distribution
• ISSN: 0028-646X; 1469-8137
• DOI: 10.1111/nph.12712

Optimizing nodulation in legumes is a target for crop improvement, and the spatial control of nodulation is just beginning to be unravelled. However, there is currently no method for standard phenotyping of nodulation patterns. Here we present a method and software for the quantitative analysis of nodulation phenotypes. Roots of nodulated peas (Pisum sativum), wild‐type and two mutants, were photographed. Data from the photographs were extracted using custom image and data analysis software. The software makes it possible to extract each nodule's position along primary and lateral roots, and to represent the nodulated root system in a standardized way independent of the way roots are arranged in the soil. A wide variety of nodulation and root variables are calculated, and average spatial nodulation patterns can be computed from multiple samples. Standardized spatial analysis of nodulation patterns opens the way for comparative analyses among genotypes of a single legume species, as here in pea. This approach could also be used to compare nodulation patterns among crops, among plants grown under different environmental conditions, or among plants exposed to different pharmacological treatments. The proposed method should therefore prove useful for studies on nodule organogenesis and nodule physiology and for optimizing nodulation in crops.