Uncovering natural variation in root system architecture and growth dynamics using a robotics-assisted phenomics platform

Abstract

The plant kingdom contains a stunning array of complex morphologies easily observed above-ground, but more challenging to visualize below-ground. Understanding the magnitude of diversity in root distribution within the soil, termed root system architecture (RSA), is fundamental to determining how this trait contributes to species adaptation in local environments. Roots are the interface between the soil environment and the shoot system and therefore play a key role in anchorage, resource uptake, and stress resilience. Previously, we presented the GLO-Roots (Growth and Luminescence Observatory for Roots) system to study the RSA of soil-grown Arabidopsis thaliana plants from germination to maturity (Rellán-Álvarez et al. 2015). In this study, we present the automation of GLO-Roots using robotics and the development of image analysis pipelines in order to examine the temporal dynamic regulation of RSA and the broader natural variation of RSA in Arabidopsis, over time. These datasets describe the developmental dynamics of two independent panels of accessions and reveal highly complex and polygenic RSA traits that show significant correlation with climate variables of the accessions' respective origins.

Genome-Wide Association Study Reveals Influence of Cell-specific Gene Networks on Soybean Root System Architecture

“…Conversely, certain traits such as dry root mass, primary root length, and width were solely associated with loci on a single chromosome (Figure 2c). Past studies have found RSA traits to be polygenic (LaRue et al 2022), and these results are consistent with the suggestion that multiple GC genes distributed across the genome collectively influence traits, such as total root length and primary root tip depth, in RSA.…”

Plant Growth Promotion and Heat Stress Amelioration in Arabidopsis Inoculated with Paraburkholderia phytofirmans PsJN Rhizobacteria Quantified with the GrowScreen-Agar II Phenotyping Platform

“…Notably, the strategic design of the agar plates allowed the unobstructed, open-air growth of the shoots which still is a distinguishing feature, also, in the newer systems. This is also a trait in another recent platform GLO-Roots [ 97 , 98 ] which has a similar “open-top” approach, while the MultipleXLab [ 99 ] one sticks to the conventional “closed-plate” system. Having access to the leaves opens the potential for the non-invasive monitoring of the plant’s physiological parameters such as chlorophyll fluorescence and gas exchange, i.e., net photosynthetic rate, stomatal conductance, and transpiration, which are important indicators of the plant’s response to the climate and environmental changes (e.g., [ 4 , 100 , 101 ]).…”

Dynamic Dark Root Chamber: Advancing non-invasive phenotyping of roots kept in darkness using infrared imaging

“…While many publications suggest advanced methods of data analysis using deep learning techniques, the experimental designs and image acquisition frequently expose the root to light, which can affect the root phenotype. The development of reliable, automated image processing software is crucial to evaluate a large number of individual roots, due to their high variability, and to associate different phenotypes with specific quantitative trait loci (QTLs) (Fernandez et al ., 2022; LaRue et al ., 2022; Lube et al ., 2022; Ohlsson et al ., 2023). The extraction and analysis of multiple root traits and growth dynamics are constantly improved (Seethepalli et al ., 2021).…”