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Flooding causes oxygen deprivation in soils. Plants adapt to low soil oxygen availability by changes in root morphology, anatomy, and architecture to maintain root system functioning. Essential traits include aerenchyma formation, a barrier to radial oxygen loss, and outgrowth of adventitious roots into the soil or the floodwater. We highlight recent findings of mechanisms of constitutive aerenchyma formation and of changes in root architecture. Moreover, we use modelling of internal aeration to demonstrate the beneficial effect of increasing cortex-to-stele ratio on sustaining root growth in waterlogged soils. We know the genes for some of the beneficial traits, and the next step is to manipulate these genes in breeding in order to enhance the flood tolerance of our crops.

The architecture of the branched root system of plants is a major determinant of vigor. Water availability is known to impact root physiology and growth; however, the spatial scale at which this stimulus influences root architecture is poorly understood. Here we reveal that differences in the availability of water across the circumferential axis of the root create spatial cues that determine the position of lateral root branches. We show that roots of several plant species can distinguish between a wet surface and air environments and that this also impacts the patterning of root hairs, anthocyanins, and aerenchyma in a phenomenon we describe as hydropatterning. This environmental response is distinct from a touch response and requires available water to induce lateral roots along a contacted surface. X-ray microscale computed tomography and 3D reconstruction of soil-grown root systems demonstrate that such responses also occur under physiologically relevant conditions. Using early-stage lateral root markers, we show that hydropatterning acts before the initiation stage and likely determines the circumferential position at which lateral root founder cells are specified. Hydropatterning is independent of endogenous abscisic acid signaling, distinguishing it from a classic water-stress response. Higher water availability induces the biosynthesis and transport of the lateral root-inductive signal auxin through local regulation of TRYPTOPHAN AMINOTRANSFERASE OF ARABIDOPSIS 1 and PIN-FORMED 3, both of which are necessary for normal hydropatterning. Our work suggests that water availability is sensed and interpreted at the suborgan level and locally patterns a wide variety of developmental processes in the root.

OsPIN2 is identified as the casual gene responsible for the phenotype of lta1, a rice mutant that displays large root angles and a shallow root system architecture, affecting the polar transport of auxin in the root tip. Abstract Root system architecture is very important for plant growth and crop yield. It is essential for nutrient and water uptake, anchoring, and mechanical support. Root growth angle (RGA) is a vital constituent of root system architecture and is used as a parameter for variety evaluation in plant breeding. However, little is known about the underlying molecular mechanisms that determine root growth angle in rice (Oryza sativa). In this study, a rice mutant large root angle1 (lra1) was isolated and shown to exhibit a large RGA and reduced sensitivity to gravity. Genome resequencing and complementation assays identified OsPIN2 as the gene responsible for the mutant phenotypes. OsPIN2 was mainly expressed in roots and the base of shoots, and showed polar localization in the plasma membrane of root epidermal and cortex cells. OsPIN2 was shown to play an important role in mediating root gravitropic responses in rice and was essential for plants to produce normal RGAs. Taken together, our findings suggest that OsPIN2 plays an important role in root gravitropic responses and determining the root system architecture in rice by affecting polar auxin transport in the root tip.

Phosphate (Pi) is an essential nutrient for all organisms. Roots are underground organs, but the majority of the root biology studies have been done on root systems growing in the presence of light. Root illumination alters the Pi starvation response (PSR) at different intensities. Thus, we have analyzed morphological, transcriptional and physiological responses to Pi starvation in dark-grown roots. We have identified new genes and pathways regulated by Pi starvation that were not described previously. We also show that Pi-starved plants increase the cis-zeatin (cZ) : trans-zeatin (tZ) ratio. Transcriptomic analyses show that tZ preferentially represses cell cycle and PSR genes, whereas cZ induces genes involved in cell and root hair elongation and differentiation. In fact, cZ-treated seedlings show longer root system as well as longer root hairs compared with tZ-treated seedlings, increasing the total absorbing surface. Mutants with low cZ concentrations do not allocate free Pi in roots during Pi starvation. We propose that Pi-starved plants increase the cZ : tZ ratio to maintain basal cytokinin responses and allocate Pi in the root system to sustain its growth. Therefore, cZ acts as a PSR hormone that stimulates root and root hair elongation to enlarge the root absorbing surface and to increase Pi concentrations in roots.

The authors introduce and study the class of groups graded by root systems. They prove that if \\Phi is an irreducible classical root system of rank \\geq 2 and G is a group graded by \\Phi, then under certain natural conditions on the grading, the union of the root subgroups is a Kazhdan subset of G. As the main application of this theorem the authors prove that for any reduced irreducible classical root system \\Phi of rank \\geq 2 and a finitely generated commutative ring R with 1, the Steinberg group {\\mathrm St}_{\\Phi}(R) and the elementary Chevalley group \\mathbb E_{\\Phi}(R) have property (T). They also show that there exists a group with property (T) which maps onto all finite simple groups of Lie type and rank \\geq 2, thereby providing a \"unified\" proof of expansion in these groups.

Morphological plasticity of root systems is critically important for plant survival because it allows plants to optimize their capacity to take up water and nutrients from the soil environment. Here we show that a signaling module composed of nitrogen (N)-responsive CLE (CLAVATA3/ESR-related) peptides and the CLAVATA1 (CLV1) leucine-rich repeat receptor-like kinase is expressed in the root vasculature in Arabidopsis thaliana and plays a crucial role in regulating the expansion of the root system under N-deficient conditions. CLE1, -3, -4, and -7 were induced by N deficiency in roots, predominantly expressed in root pericycle cells, and their overexpression repressed the growth of lateral root primordia and their emergence from the primary root. In contrast, clv1 mutants showed progressive outgrowth of lateral root primordia into lateral roots under N-deficient conditions. The clv1 phenotype was reverted by introducing a CLV1 promoter-driven CLV1:GFP construct producing CLV1:GFP fusion proteins in phloem companion cells of roots. The overaccumulation of CLE2, -3, -4, and -7 in clv1 mutants suggested the amplitude of the CLE peptide signals being feedback-regulated by CLV1. When CLE3 was overexpressed under its own promoter in wild-type plants, the length of lateral roots was negatively correlated with increasing CLE3 mRNA levels; however, this inhibitory action of CLE3 was abrogated in the clv1 mutant background. Our findings identify the N-responsive CLE-CLV1 signaling module as an essential mechanism restrictively controlling the expansion of the lateral root system in N-deficient environments.

OpenSimRoot is an open-source, functional–structural plant model and mathematical description of root growth and function. We describe OpenSimRoot and its functionality to broaden the benefits of root modeling to the plant science community. OpenSimRoot is an extended version of SimRoot, established to simulate root system architecture, nutrient acquisition and plant growth. OpenSimRoot has a plugin, modular infrastructure, coupling single plant and crop stands to soil nutrient and water transport models. It estimates the value of root traits for water and nutrient acquisition in environments and plant species. The flexible OpenSimRoot design allows upscaling from root anatomy to plant community to estimate the following: resource costs of developmental and anatomical traits; trait synergisms; and (interspecies) root competition. OpenSimRoot can model three-dimensional images from magnetic resonance imaging (MRI) and X-ray computed tomography (CT) of roots in soil. New modules include: soil water-dependent water uptake and xylem flow; tiller formation; evapotranspiration; simultaneous simulation of mobile solutes; mesh refinement; and root growth plasticity. OpenSimRoot integrates plant phenotypic data with environmental metadata to support experimental designs and to gain a mechanistic understanding at system scales.

Aims Root system architecture (RSA) is important for nutrient and water acquisition efficiency. The adaptation of root growth and RSA to soil structure under conservative strip tillage (ST) system warrants further investigation. Methods A three-year field experimentation was conducted in Northeast China to investigate the RSA and dynamic root growth of rain-fed maize under ST system by comparison with the conventional tillage (CT). Results Grain yield in ST and CT was not significantly different, but their yield components differed. Compared to CT, grain number per ear was reduced by 4.4%, while 1000-grain weight was increased by 6.6% in ST. Root growth in ST plants was inhibited in the vegetative stage, as indicated by the reduced total root length (by 27.7–40.1%) compared to CT. During post-silking stage, the total root length was not different between ST and CT plants but the root xylem bleeding rate in ST plants was 70.7%-449.9% greater than that in CT. The uneven horizontal distribution of soil bulk density and soil temperature made the RSA of ST plants steeper compared to CT. Moreover, the D 95 of root distribution in ST plant roots was greater. Conclusions In ST system, colder, more compacted soil in the inter-row soil likely caused the lower root growth and consequently lower shoot dry matter during the vegetative stage. However, root senescence was delayed which was beneficial for water and nitrogen acquisition during grain filling. Strategies to improve early root growth may increase maize productivity in ST systems.

Background and aims Although modelling of water and nutrient uptake by root systems has advanced considerably in recent years, steep local gradients of nutrient concentration near the root-soil interface in the rhizosphere are still a central challenge for accurate simulation of water and nutrient uptake at the root system scale. Conventionally, mesh refinement is used to resolve these gradients. However, it results in excessive computational costs. The object of the study is to present a multiscale approach which resolves the steep gradient of nutrient concentrations at rhizosphere scale and simulates nutrient and water fluxes within the entire root zone at macroscale scale in a computationally efficient way. Methods We developed a 3D water and nutrient transport model of the root-soil system with explicit consideration of the 3D root architecture. To capture the nutrient gradients at root surfaces, 1D axisymmetric soil models at rhizosphere scale were constructed and coupled to the coarse 3D root-system-scale simulations using a mass conservative approach. The multiscale model was investigated under different scenarios for water and potassium (K + ) uptake of a single root, multiple roots, and whole 3D architecture of a Zea mays L. root system in conditions of dynamic soil water and different soil buffer capacity of K + . Results The steep gradients of K + concentrations were efficiently resolved in the multiscale simulations thanks to the 1D model at the rhizosphere scale. In comparison with the refinement method, the multiscale model achieved a significant accuracy of K + uptake prediction with a relative error below 5%. Meanwhile, the simulation at macroscale with coarse mesh could overestimate the K + uptake in one order of magnitude. Moreover, the computational cost of multiscale simulations was decreased considerably by using coarse soil mesh. Conclusions The newly developed model can describe the effect of the drying and nutrient transport in the root zone on nutrient uptake. It also allows to simulate processes in larger and complex root systems because of the considerable reduction in computational cost.

Background and Scope Because of the crucial role coarse roots (>2 mm diameter) play in plant functions and terrestrial ecosystems, detecting and quantifying the size, architecture, and biomass of coarse roots are important. Traditional excavation methods are labor intensive and destructive, with limited quantification and repeatability of measurements over time. As anondestructive geophysical tool for delineating buried features in shallow subsurface, ground penetrating radar (GPR) has been applied for coarse root detection since 1999. This article reviews the state-ofknowledge of coarse root detection and quantification using GPR, and discusses its potentials, constraints, possible solutions, and future outlooks. Some useful suggestions are provided that can guide future studies in this field. Conclusions The feasibility and accuracy of coarse root investigation by GPR have been tested in various site conditions (mostly in controlled conditions or within plantations) and for different plant species (mostly tree root systems). Thus far, single coarse root identification and coarse root system mapping have been conducted using GPR, including roots under pavements in urban environment. Coarse root diameter and biomass have been estimated from indexes extracted from root GPR radargrams. Coarse root development can be observed by repeated GPR scanning over time. Successful GPR-based coarse root investigation is site specific, and only under suitable conditions can reliable measurements be accomplished. The best quality of root detection by GPR is achieved in well-drained and electrically-resistive soils (such as sands) under dry conditions. Numerous factors such as local soil conditions, root electromagnetic properties, and GPR antenna frequency can impact the reliability and accuracy of GPR detection and quantification of coarse roots. As GPR design, data processing software, field data collection protocols, and root parameters estimation methods are continuously improved, this noninvasive technique could offer greater potential to study coarse roots.