Root-System Architectures of Two Cuban Rice Cultivars with Salt Stress at Early Development Stages.

Soil salinity is a critical problem for rice production and is also often associated with phosphors (P) deficiency. Plant hormones, like brassinosteroids, were shown to play a role in plant responses to different stresses and are also expected to mitigate salt stress. The aim of this study was to compare shoot growth and root architecture traits of two rice cultivars (INCA LP-5 and Perla de Cuba) during early plant development in response to salt, P limitation and a brassinosteroid. Seeds were placed in (I) paper rolls for 7 days and (II) mini-rhizotrons for 21 days without or with salt (50 mM NaCl), without or with 24-epibrassinolide (10-6 M) pre-treatment, and with two levels of P (10 or 1 ppm). The root system of LP-5 was larger in size and extent, while the roots of Perla were growing denser. Salt affected mainly the size- and extent-related root characteristics and explained about 70% of the variance. The effect of P was more pronounced without salt treatment. In Perla, P supply reduced the salt effect on root growth. The brassinosteroid had hardly any effect on the development of the plants in both experiments. Due to the high dependence on experimental factors, root length and related traits can be recommended for selecting young rice cultivars regarding salt stress and P deprivation.

ChronoRoot: High-throughput phenotyping by deep segmentation networks reveals novel temporal parameters of plant root system architecture.

BACKGROUND: Deep learning methods have outperformed previous techniques in most computer vision tasks, including image-based plant phenotyping. However, massive data collection of root traits and the development of associated artificial intelligence approaches have been hampered by the inaccessibility of the rhizosphere. Here we present ChronoRoot, a system that combines 3D-printed open-hardware with deep segmentation networks for high temporal resolution phenotyping of plant roots in agarized medium. RESULTS: We developed a novel deep learning-based root extraction method that leverages the latest advances in convolutional neural networks for image segmentation and incorporates temporal consistency into the root system architecture reconstruction process. Automatic extraction of phenotypic parameters from sequences of images allowed a comprehensive characterization of the root system growth dynamics. Furthermore, novel time-associated parameters emerged from the analysis of spectral features derived from temporal signals. CONCLUSIONS: Our work shows that the combination of machine intelligence methods and a 3D-printed device expands the possibilities of root high-throughput phenotyping for genetics and natural variation studies, as well as the screening of clock-related mutants, revealing novel root traits.

MEDIATOR16 orchestrates local and systemic responses to phosphate scarcity in Arabidopsis roots.

Phosphate (Pi ) is a critical macronutrient for the biochemical and molecular functions of cells. Under phosphate limitation, plants manifest adaptative strategies to increase phosphate scavenging. However, how low phosphate sensing links to the transcriptional machinery remains unknown. The role of the MEDIATOR (MED) transcriptional co-activator, through its MED16 subunit in Arabidopsis root system architecture remodeling in response to phosphate limitation was assessed. Its critical function acting over the SENSITIVE TO PROTON RHIZOTOXICITY1 (STOP1)-ALUMINUM-ACTIVATED MALATE TRANSPORT1 (ALMT1) signaling module was tested through a combination of genetic, biochemical, and genome-wide transcriptomic approaches. Root system configuration in response to phosphate scarcity involved MED16 functioning, which modulates the expression of a large set of low-phosphate-induced genes that respond to local and systemic signals in the Arabidopsis root tip, including those directly activated by STOP1. Biomolecular fluorescence complementation analysis suggests that MED16 is required for the transcriptional activation of STOP1 targets, including the membrane permease ALMT1, to increase malate exudation in response to low phosphate. Our results unveil the function of a critical transcriptional component, MED16, in the root adaptive responses to a scarce plant macronutrient, which helps understanding how plant cells orchestrate root morphogenesis to gene expression with the STOP1-ALMT1 module.

Phenotyping Root Systems in a Set of Japonica Rice Accessions: Can Structural Traits Predict the Response to Drought?

BACKGROUND: The root system plays a major role in plant growth and development and root system architecture is reported to be the main trait related to plant adaptation to drought. However, phenotyping root systems in situ is not suited to high-throughput methods, leading to the development of non-destructive methods for evaluations in more or less controlled root environments. This study used a root phenotyping platform with a panel of 20 japonica rice accessions in order to: (i) assess their genetic diversity for a set of structural and morphological root traits and classify the different types; (ii) analyze the plastic response of their root system to a water deficit at reproductive phase and (iii) explore the ability of the platform for high-throughput phenotyping of root structure and morphology. RESULTS: High variability for the studied root traits was found in the reduced set of accessions. Using eight selected traits under irrigated conditions, five root clusters were found that differed in root thickness, branching index and the pattern of fine and thick root distribution along the profile. When water deficit occurred at reproductive phase, some accessions significantly reduced root growth compared to the irrigated treatment, while others stimulated it. It was found that root cluster, as defined under irrigated conditions, could not predict the plastic response of roots under drought. CONCLUSIONS: This study revealed the possibility of reconstructing the structure of root systems from scanned images. It was thus possible to significantly class root systems according to simple structural traits, opening up the way for using such a platform for medium to high-throughput phenotyping. The study also highlighted the uncoupling between root structures under non-limiting water conditions and their response to drought.

Enhanced Properties of Chitosan Microparticles over Bulk Chitosan on the Modulation of the Auxin Signaling Pathway with Beneficial Impacts on Root Architecture in Plants.

Improving the root system architecture (RSA) under adverse environmental conditions by using biostimulants is emerging as a new way to boost crop productivity. Recently, we have reported the characterization of novel chitosan-based microparticles (CS-MPs) with promising biological properties as rooting agents in lettuce. In this work, we demonstrated that in contrast to bulk chitosan (CS), which exerts root growth inhibition, CS-MPs promoted root growth and development from 1 to 10 µg mL-1 without cytotoxicity effects at higher doses in Arabidopsis and lettuce seedlings. In addition, we studied the mechanistic mode of action of CS-MPs in the development of early RSA in the Arabidopsis model. CS-MPs unchained accurate and sustained spatio-temporal activation of the nuclear auxin signaling pathway. Our findings validated a promising scenario for the application of CS-MPs in the modulation of RSA to respond to changing soil environments and improve crop performance.

The genetic architecture of phosphorus efficiency in sorghum involves pleiotropic QTL for root morphology and grain yield under low phosphorus availability in the soil.

BACKGROUND: Phosphorus (P) fixation on aluminum (Al) and iron (Fe) oxides in soil clays restricts P availability for crops cultivated on highly weathered tropical soils, which are common in developing countries. Hence, P deficiency becomes a major obstacle for global food security. We used multi-trait quantitative trait loci (QTL) mapping to study the genetic architecture of P efficiency and to explore the importance of root traits on sorghum grain yield on a tropical low-P soil. RESULTS: P acquisition efficiency was the most important component of P efficiency, and both traits were highly correlated with grain yield under low P availability. Root surface area was positively associated with grain yield. The guinea parent, SC283, contributed 58% of all favorable alleles detected by single-trait mapping. Multi-trait mapping detected 14 grain yield and/or root morphology QTLs. Tightly linked or pleiotropic QTL underlying the surface area of fine roots (1-2 mm in diameter) and grain yield were detected at positions 1-7 megabase pairs (Mb) and 71 Mb on chromosome 3, respectively, and a root diameter/grain yield QTL was detected at 7 Mb on chromosome 7. All these QTLs were near sorghum homologs of the rice serine/threonine kinase, OsPSTOL1. The SbPSTOL1 genes on chromosome 3, Sb03g006765 at 7 Mb and Sb03g031690 at 60 Mb were more highly expressed in SC283, which donated the favorable alleles at all QTLs found nearby SbPSTOL1 genes. The Al tolerance gene, SbMATE, may also influence a grain yield QTL on chromosome 3. Another PSTOL1-like gene, Sb07g02840, appears to enhance grain yield via small increases in root diameter. Co-localization analyses suggested a role for other genes, such as a sorghum homolog of the Arabidopsis ubiquitin-conjugating E2 enzyme, phosphate 2 (PHO2), on grain yield advantage conferred by the elite parent, BR007 allele. CONCLUSIONS: Genetic determinants conferring higher root surface area and slight increases in fine root diameter may favor P uptake, thereby enhancing grain yield under low-P availability in the soil. Molecular markers for SbPSTOL1 genes and for QTL increasing grain yield by non-root morphology-based mechanisms hold promise in breeding strategies aimed at developing sorghum cultivars adapted to low-P soils.

Genetic and Phenotypic Analysis of Lateral Root Development in Arabidopsis thaliana.

Root system formation to a great extent depends on lateral root (LR) formation. In Arabidopsis thaliana, LRs are initiated within a parent root in pericycle that is an external tissue of the stele. LR initiation takes place in a strictly acropetal pattern, whereas posterior lateral root primordium (LRP) formation is asynchronous. In this chapter, we focus on methods of genetic and phenotypic analysis of LR initiation, LRP morphogenesis, and LR emergence in Arabidopsis. We provide details on how to make cleared root preparations and how to identify the LRP stages. We also pay attention to the categorization of the LRP developmental stages and their variations and to the normalization of the number of LRs and LRPs formed, per length of the primary root, and per number of cells produced within a root. Hormonal misbalances and mutations affect LRP morphogenesis significantly, and the evaluation of LRP abnormalities is addressed as well. Finally, we deal with various molecular markers that can be used for genetic and phenotypic analyses of LR development.

Root System Architecture and Abiotic Stress Tolerance: Current Knowledge in Root and Tuber Crops.

The challenge to produce more food for a rising global population on diminishing agricultural land is complicated by the effects of climate change on agricultural productivity. Although great progress has been made in crop improvement, so far most efforts have targeted above-ground traits. Roots are essential for plant adaptation and productivity, but are less studied due to the difficulty of observing them during the plant life cycle. Root system architecture (RSA), made up of structural features like root length, spread, number, and length of lateral roots, among others, exhibits great plasticity in response to environmental changes, and could be critical to developing crops with more efficient roots. Much of the research on root traits has thus far focused on the most common cereal crops and model plants. As cereal yields have reached their yield potential in some regions, understanding their root system may help overcome these plateaus. However, root and tuber crops (RTCs) such as potato, sweetpotato, cassava, and yam may hold more potential for providing food security in the future, and knowledge of their root system additionally focuses directly on the edible portion. Root-trait modeling for multiple stress scenarios, together with high-throughput phenotyping and genotyping techniques, robust databases, and data analytical pipelines, may provide a valuable base for a truly inclusive 'green revolution.' In the current review, we discuss RSA with special reference to RTCs, and how knowledge on genetics of RSA can be manipulated to improve their tolerance to abiotic stresses.