A Comparative Analysis of Quantitative Metrics of Root Architecture

Abstract

High throughput phenotyping is important to bridge the gap between genotype and phenotype. The methods used to describe the phenotype therefore should be robust to measurement errors, relatively stable over time, and most importantly, provide a reliable estimate of elementary phenotypic components. In this study, we use functional-structural modeling to evaluate quantitative phenotypic metrics used to describe root architecture to determine how they fit these criteria. Our results show that phenes such as root number, root diameter, and lateral root branching density are stable, reliable measures and are not affected by imaging method or plane. Metrics aggregating multiple phenes such as total length, total volume, convex hull volume, and bushiness index estimate different subsets of the constituent phenes; they however do not provide any information regarding the underlying phene states. Estimates of phene aggregates are not unique representations of underlying constituent phenes: multiple phenotypes having phenes in different states could have similar aggregate metrics. Root growth angle is an important phene which is susceptible to measurement errors when 2D projection methods are used. Metrics that aggregate phenes which are complex functions of root growth angle and other phenes are also subject to measurement errors when 2D projection methods are used. These results support the hypothesis that estimates of phenes are more useful than metrics aggregating multiple phenes for phenotyping root architecture. We propose that these concepts are broadly applicable in phenotyping and phenomics.

Aus rice root architecture variation contributing to grain yield under drought suggests a key role of nodal root diameter class

“…Dissecting the component root traits that underly composite traits such as RDW at depth is more likely to reveal a greater degree of genetic variation than measuring the composite traits alone (Rangarajan & Lynch, 2021). As the trait that most consistently correlated with high and stable grain yield, we hypothesized that greater deep RDW of aus genotypes could be due to three main mechanisms involving deep root growth component traits (in addition to the evidence of plasticity mentioned above): nodal root elongation, nodal root angle and lateral root formation.…”

Many paths to one goal: Identifying integrated rice root phenotypes for diverse drought environments

“…All phenes exist as part of one organism, and multiple root phenes interact to produce synergistic effects on soil resource capture ( Ma et al, 2001 ; York et al, 2013 ; Miguel et al, 2015 ; Klein et al, 2020 ; Rangarajan and Lynch, 2021 ). In this study, integrated root phenotypes, i.e., specific combinations of root phenes, were better associated with performance (greater biomass) under drought within and across experiments compared to either individual phenes or those grouped by phenotypic bulked segregant analysis.…”

Association mapping uncovers maize ZmbZIP107 regulating root system architecture and lead absorption under lead stress

“…Root bushiness that is equal to the ratio of the maximum of roots to the median of roots has been extensively used to evaluate the lush degree of plant roots in different species ( Ambreetha et al., 2017 ; Liang et al., 2018 ; Rangarajan and Lynch, 2021 ). Herein, for the first time, we used BSH-LTC that reflects the relative BSH under Pb treatment as an indicator for evaluating maize seedlings tolerance to Pb stress.…”

“…root length, root surface area, and total number of roots) (Mollier and Botany, 1999). Among these original traits, bushiness is described as ratio of the maximum of roots to the median of roots, which is considered an important indicator to evaluate the lush degree of plant roots and has been widely studied in soybeans, maize (Rangarajan and Lynch, 2021), Arabidopsis (Liang et al, 2018), and rice (Ambreetha et al, 2017). Some genes involved in heavy metal tolerance have been reported in plants.…”