Abstract
Roots play an immediate role as the interface for water acquisition. To improve sustainability in low-water environments, breeders of major crops must therefore pay closer attention to advantageous root phenotypes; however, the complexity of root architecture in response to stress can be difficult to quantify. Here, the Sholl method, an established technique from neurobiology used for the characterization of neural network anatomy, was adapted to more adequately describe root responses to osmotic stress. This method was used to investigate the influence of in vitro osmotic stress on early root architecture and distribution in drought-resistant and -susceptible genotypes of winter oilseed rape. Interactive changes in root architecture can be easily captured by individual intersection profiles generated by Sholl analysis. Validation using manual measurements confirmed that the number of lateral roots decreased, while mean lateral root length was enhanced, under osmotic stress conditions. Both genotypes reacted to osmotic stress with a shift in their intersection patterns measured with Sholl analysis. Changes in interactive root architecture and distribution under stress were more pronounced in the drought-resistant genotype, indicating that these changes may contribute to drought resistance under mild osmotic stress conditions. The Sholl methodology is presented as a promising tool for selection of cultivars with advantageous root phenotypes under osmotic stress conditions.
Highlights
This paper presents a novel and practicable method for the characterization of plant root architectural properties
Several climate reports and modelling studies predict a future increase of flooding events in northern Europe, while an increase of drought events is forecast for southern and Abbreviations: DR, drought resistant; DS, drought sensitive; fresh weights (FW), fresh weight; LRL, lateral root length; NaOCl, sodium hypochlorite; Mean length of lateral roots (MLRL), mean lateral root length; MS powder, Murashige and Skoog nutrient mixture; NLR, number of lateral roots; PEG, polyethylene glycol; r, radius; PC, principal component; PCA, principal component analysis; PRL, primary root length; RL, total root length; dpi: dots per inch
In genotype DR, NLR decreased to almost 50% compared to the control, while genotype DS showed a reduction of 40% under stress
Summary
This paper presents a novel and practicable method for the characterization of plant root architectural properties. The method was adapted from the analysis technique of Sholl (1953), an established neurobiological approach still applied today for morphological characterization of neural networks (Binley et al, 2014; Ferreira et al, 2014; Garcia-Segura and Perez-Marquez, 2014). Known as the Sholl method, this approach uses a coordinate system consisting of a series of concentric circles centred at the soma of a neuron. Local variables are extracted by counting the number of intersections on regular concentric circles surrounding cell dendrites, giving a metric representation of the architectural characteristics of the network and how they change with distance and time. Several climate reports and modelling studies predict a future increase of flooding events in northern Europe, while an increase of drought events is forecast for southern and Abbreviations: DR, drought resistant; DS, drought sensitive; FW, fresh weight; LRL, lateral root length; NaOCl, sodium hypochlorite; MLRL, mean lateral root length; MS powder, Murashige and Skoog nutrient mixture; NLR, number of lateral roots; PEG, polyethylene glycol; r, radius; PC, principal component; PCA, principal component analysis; PRL, primary root length; RL, total root length; dpi: dots per inch
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