A New Phenotyping Pipeline Reveals Three Types of Lateral Roots and a Random Branching Pattern in Two Cereals

Not so hidden anymore: Advances and challenges in understanding root growth under water deficits

Limited water availability is a major environmental factor constraining plant development and crop yields. One of the prominent adaptations of plants to water deficits is the maintenance of root growth that enables sustained access to soil water. Despite early recognition of the adaptive significance of root growth maintenance under water deficits, progress in understanding has been hampered by the inherent complexity of root systems and their interactions with the soil environment. We highlight selected milestones in the understanding of root growth responses to water deficits, with emphasis on founding studies that have shaped current knowledge and set the stage for further investigation. We revisit the concept of integrated biophysical and metabolic regulation of plant growth and use this framework to review central growth-regulatory processes occurring within root growth zones under water stress at subcellular to organ scales. Key topics include the primary processes of modifications of cell wall-yielding properties and osmotic adjustment, as well as regulatory roles of abscisic acid and its interactions with other hormones. We include consideration of long-recognized responses for which detailed mechanistic understanding has been elusive until recently, for example hydrotropism, and identify gaps in knowledge, ongoing challenges, and opportunities for future research.

Are high-throughput root phenotyping platforms suitable for informing root system architecture models with genotype-specific parameters? An evaluation based on the root model ArchiSimple and a small panel of wheat cultivars

Given the difficulties in accessing plant roots in situ, high-throughput root phenotyping (HTRP) platforms under controlled conditions have been developed to meet the growing demand for characterizing root system architecture (RSA) for genetic analyses. However, a proper evaluation of their capacity to provide the same estimates for strictly identical root traits across platforms has never been achieved. In this study, we performed such an evaluation based on six major parameters of the RSA model ArchiSimple, using a diversity panel of 14 bread wheat cultivars in two HTRP platforms that had different growth media and non-destructive imaging systems together with a conventional set-up that had a solid growth medium and destructive sampling. Significant effects of the experimental set-up were found for all the parameters and no significant correlations across the diversity panel among the three set-ups could be detected. Differences in temperature, irradiance, and/or the medium in which the plants were growing might partly explain both the differences in the parameter values across the experiments as well as the genotype × set-up interactions. Furthermore, the values and the rankings across genotypes of only a subset of parameters were conserved between contrasting growth stages. As the parameters chosen for our analysis are root traits that have strong impacts on RSA and are close to parameters used in a majority of RSA models, our results highlight the need to carefully consider both developmental and environmental drivers in root phenomics studies.

Glutaredoxin regulation of primary root growth is associated with early drought stress tolerance in pearl millet

Seedling root traits impact plant establishment under challenging environments. Pearl millet is one of the most heat and drought tolerant cereal crops that provides a vital food source across the sub-Saharan Sahel region. Pearl millet's early root system features a single fast-growing primary root which we hypothesize is an adaptation to the Sahelian climate. Using crop modeling, we demonstrate that early drought stress is an important constraint in agrosystems in the Sahel where pearl millet was domesticated. Furthermore, we show that increased pearl millet primary root growth is correlated with increased early water stress tolerance in field conditions. Genetics including genome-wide association study and quantitative trait loci (QTL) approaches identify genomic regions controlling this key root trait. Combining gene expression data, re-sequencing and re-annotation of one of these genomic regions identified a glutaredoxin-encoding gene PgGRXC9 as the candidate stress resilience root growth regulator. Functional characterization of its closest Arabidopsis homolog AtROXY19 revealed a novel role for this glutaredoxin (GRX) gene clade in regulating cell elongation. In summary, our study suggests a conserved function for GRX genes in conferring root cell elongation and enhancing resilience of pearl millet to its Sahelian environment.

Tapping into the plasticity of plant architecture for increased stress resilience

Plant architecture develops post-embryonically and emerges from a dialogue between the developmental signals and environmental cues. Length and branching of the vegetative and reproductive tissues were the focus of improvement of plant performance from the early days of plant breeding. Current breeding priorities are changing, as we need to prioritize plant productivity under increasingly challenging environmental conditions. While it has been widely recognized that plant architecture changes in response to the environment, its contribution to plant productivity in the changing climate remains to be fully explored. This review will summarize prior discoveries of genetic control of plant architecture traits and their effect on plant performance under environmental stress. We review new tools in phenotyping that will guide future discoveries of genes contributing to plant architecture, its plasticity, and its contributions to stress resilience. Subsequently, we provide a perspective into how integrating the study of new species, modern phenotyping techniques, and modeling can lead to discovering new genetic targets underlying the plasticity of plant architecture and stress resilience. Altogether, this review provides a new perspective on the plasticity of plant architecture and how it can be harnessed for increased performance under environmental stress.

Lateral root branching: evolutionary innovations and mechanistic divergence in land plants

The root system architecture in plants is a result of multiple evolutionary innovations over time in response to changing environmental cues. Dichotomy and endogenous lateral branching in the roots evolved in lycophytes lineage but extant seed plants use lateral branching instead. This has led to the development of complex and adaptive root systems, with lateral roots playing a key role in this process exhibiting conserved and divergent features in different plant species. The study of lateral root branching in diverse plant species can shed light on the orderly yet distinct nature of postembryonic organogenesis in plants. This insight provides an overview of the diversity in lateral root (LR) development in various plant species during the evolution of root system in plants.

Rhizosphere engineering for sustainable crop production: entropy-based insights

There is a growing interest in exploring interactions at root-soil interface in natural and agricultural ecosystems, but an entropy-based understanding of these dynamic rhizosphere processes is lacking. We have developed a new conceptual model of rhizosphere regulation by localized nutrient supply using thermodynamic entropy. Increased nutrient-use efficiency is achieved by rhizosphere management based on self-organization and minimized entropy via equilibrium attractors comprising (i) optimized root strategies for nutrient acquisition and (ii) improved information exchange related to root-soil-microbe interactions. The cascading effects through different hierarchical levels amplify the underlying processes in plant-soil system. We propose a strategy for manipulating rhizosphere dynamics and improving nutrient-use efficiency by localized nutrient supply with minimization of entropy to underpin sustainable food/feed/fiber production.

Root traits for low input agroecosystems in Africa: Lessons from three case studies

In many regions across Africa, agriculture is largely based on low-input and small-holder farming systems that use little inorganic fertilisers and have limited access to irrigation and mechanisation. Improving agricultural practices and developing new cultivars adapted to these environments, where production already suffers from climate change, is a major priority for food security. Here, we illustrate how breeding for specific root traits could improve crop resilience in Africa using three case studies covering very contrasting low-input agroecosystems. We first review how greater basal root whorl number and longer and denser root hairs increased P acquisition efficiency and yield in common bean in South East Africa. We then discuss how water-saving strategies, root hair density and deep root growth could be targeted to improve sorghum and pearl millet yield in West Africa. Finally, we evaluate how breeding for denser root systems in the topsoil and interactions with arbuscular mycorrhizal fungi could be mobilised to optimise water-saving alternate wetting and drying practices in West African rice agroecosystems. We conclude with a discussion on how to evaluate the utility of root traits and how to make root trait selection feasible for breeders so that improved varieties can be made available to farmers through participatory approaches.

Identifying Developmental Patterns in Structured Plant Phenotyping Data

Technological breakthroughs concerning both sensors and robotized plant phenotyping platforms have totally renewed the plant phenotyping paradigm in the last two decades. This has impacted both the nature and the throughput of data with the availability of data at high-throughput from the tissular to the whole plant scale. Sensor outputs often take the form of 2D or 3D images or time series of such images from which traits are extracted while organ shapes, shoot or root system architectures can be deduced. Despite this change of paradigm, many phenotyping studies often ignore the structure of the plant and therefore loose the information conveyed by the temporal and spatial patterns emerging from this structure. The developmental patterns of plants often take the form of succession of well-differentiated phases, stages or zones depending on the temporal, spatial or topological indexing of data. This entails the use of hierarchical statistical models for their identification.The objective here is to show potential approaches for analyzing structured plant phenotyping data using state-of-the-art methods combining probabilistic modeling, statistical inference and pattern recognition. This approach is illustrated using five different examples at various scales that combine temporal and topological index parameters, and development and growth variables obtained using prospective or retrospective measurements.

Dynamic Development of White Lupin Rootlets Along a Cluster Root

White lupin produces cluster roots in response to phosphorus deficiency. Along the cluster root, numerous short rootlets successively appear, creating a spatial and temporal gradient of developmental stages that constitutes a powerful biological model to study the dynamics of the structural and functional evolution of these organs. The present study proposes a fine histochemical, transcriptomic and functional analysis of the rootlet development from its emergence to its final length. Between these two stages, the tissue structures of the rootlets were observed, the course of transcript expressions for the genes differentially expressed was monitored and some physiological events linked to Pi nutrition were followed. A switch between (i) a growing phase, in which a normal apical meristem is present and (ii) a specialized phase for nutrition, in which the rootlet is completely differentiated, was highlighted. In the final stage of its determinate growth, the rootlet is an organ with a very active metabolism, especially for the solubilization and absorption of several nutrients. This work discusses how the transition between a growing to a determinate state in response to nutritional stresses is found in other species and underlines the fundamental dilemma of roots between soil exploration and soil exploitation.

Combining cross-section images and modeling tools to create high-resolution root system hydraulic atlases in Zea mays

Root hydraulic properties play a central role in the global water cycle, in agricultural systems productivity, and in ecosystem survival as they impact the canopy water supply. However, the existing experimental methods to quantify root hydraulic conductivities, such as the root pressure probing, are particularly challenging, and their applicability to thin roots and small root segments is limited. Therefore, there is a gap in methods enabling easy estimations of root hydraulic conductivities in diverse root types. Here, we present a new pipeline to quickly estimate root hydraulic conductivities across different root types, at high resolution along root axes. Shortly, free-hand root cross-sections were used to extract a selected number of key anatomical traits. We used these traits to parametrize the Generator of Root Anatomy in R (GRANAR) model to simulate root anatomical networks. Finally, we used these generated anatomical networks within the Model of Explicit Cross-section Hydraulic Anatomy (MECHA) to compute an estimation of the root axial and radial hydraulic conductivities (k x and k r , respectively). Using this combination of anatomical data and computational models, we were able to create a root hydraulic conductivity atlas at the root system level, for 14-day-old pot-grown Zea mays (maize) plants of the var. B73. The altas highlights the significant functional variations along and between different root types. For instance, predicted variations of radial conductivity along the root axis were strongly dependent on the maturation stage of hydrophobic barriers. The same was also true for the maturation rates of the metaxylem vessels. Differences in anatomical traits along and across root types generated substantial variations in radial and axial conductivities estimated with our novel approach. Our methodological pipeline combines anatomical data and computational models to turn root cross-section images into a detailed hydraulic atlas. It is an inexpensive, fast, and easily applicable investigation tool for root hydraulics that complements existing complex experimental methods. It opens the way to high-throughput studies on the functional importance of root types in plant hydraulics, especially if combined with novel phenotyping techniques such as laser ablation tomography.

Deep learning-based high-throughput phenotyping can drive future discoveries in plant reproductive biology

Advances in deep learning are providing a powerful set of image analysis tools that are readily accessible for high-throughput phenotyping applications in plant reproductive biology. High-throughput phenotyping systems are becoming critical for answering biological questions on a large scale. These systems have historically relied on traditional computer vision techniques. However, neural networks and specifically deep learning are rapidly becoming more powerful and easier to implement. Here, we examine how deep learning can drive phenotyping systems and be used to answer fundamental questions in reproductive biology. We describe previous applications of deep learning in the plant sciences, provide general recommendations for applying these methods to the study of plant reproduction, and present a case study in maize ear phenotyping. Finally, we highlight several examples where deep learning has enabled research that was previously out of reach and discuss the future outlook of these methods.

Maize lateral root developmental plasticity induced by mild water stress. II: Genotype-specific spatio-temporal effects on determinate development

Maize lateral roots exhibit determinate growth, whereby the meristem is genetically programmed to stop producing new cells. To explore whether lateral root determinacy is modified under water deficits, we studied two maize genotypes (B73 and FR697) with divergent responses of lateral root growth to mild water stress using an experimental system that provided near-stable water potential environments throughout lateral root development. First-order laterals of the primary root system of FR697 exhibited delayed determinacy when grown at a water potential of -0.28 MPa, resulting in longer and wider roots than in well-watered (WW) controls. In B73, in contrast, neither the length nor width of lateral roots was affected by water deficit. In water-stressed FR697, root elongation continued at or above the maximum rate in WW roots for 3 days longer, and was still 45% of maximum when WW roots approached their determinate length. Maintenance of root elongation was associated with sustained rates of cell production. In addition, kinematic analyses showed that reductions in tissue expansion rates with aging were delayed in the longitudinal, radial and tangential planes throughout the root growth zone. Thus, this study reveals large genotypic differences in the interaction of water stress with developmental determinacy of maize lateral roots.

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.

Modelling time variations of root diameter and elongation rate as related to assimilate supply and demand

In a given root system, individual roots usually exhibit a rather homogeneous tip structure although highly different diameters and growth patterns, and this diversity is of prime importance in the definition of the whole root system architecture and foraging characteristics. In order to represent and predict this diversity, we built a simple and generic model at root tip level combining structural and functional knowledge on root elongation. The tip diameter, reflecting meristem size, is used as a driving variable of elongation. It varies, in response to the fluctuations of photo-assimilate availability, between two limits (minimal and maximal diameter). The elongation rate is assumed to be dependent on the transient value of the diameter. Elongation stops when the tip reaches the minimal diameter. The model could satisfactorily reproduce patterns of root elongation and tip diameter changes observed in various species at different scales. Although continuous, the model could generate divergent root classes as classically observed within populations of lateral roots. This model should help interpret the large plasticity of root elongation patterns which can be obtained in response to different combinations of endogenous and exogenous factors. The parameters could be used in phenotyping the root system.

Lateral Roots: Random Diversity in Adversity

Lateral roots are essential for soil foraging and uptake of minerals and water. They feature a large morphological diversity that results from divergent primordia or root growth and development patterns. Besides a structured diversity, resulting from the hierarchical and developmental organization of root systems, there exists a random diversity, occurring between roots of similar age, of the same hierarchical order, and exposed to uniform conditions. The physiological bases and functional consequences of this random diversity are largely ignored. Here we review the evidence for such random diversity throughout the plant kingdom, present innovative approaches based on statistical modeling to account for such diversity, and set the list of its potential benefits in front of a variable and unpredictable soil environment.

Lateral Root Formation in Arabidopsis: A Well-Ordered LRexit

Lateral roots (LRs) are crucial for increasing the surface area of root systems to explore heterogeneous soil environments. Major advances have recently been made in the model plant arabidopsis (Arabidopsis thaliana) to elucidate the cellular basis of LR development and the underlying gene regulatory networks (GRNs) that control the morphogenesis of the new root organ. This has provided a foundation for understanding the sophisticated adaptive mechanisms that regulate how plants pattern their root branching to match the spatial availability of resources such as water and nutrients in their external environment. We review new insights into the molecular, cellular, and environmental regulation of LR development in arabidopsis.

Three-Dimensional Time-Lapse Analysis Reveals Multiscale Relationships in Maize Root Systems with Contrasting Architectures

Understanding how an organism's phenotypic traits are conditioned by genetic and environmental variation is a central goal of biology. Root systems are one of the most important but poorly understood aspects of plants, largely due to the three-dimensional (3D), dynamic, and multiscale phenotyping challenge they pose. A critical gap in our knowledge is how root systems build in complexity from a single primary root to a network of thousands of roots that collectively compete for ephemeral, heterogeneous soil resources. We used time-lapse 3D imaging and mathematical modeling to assess root system architectures (RSAs) of two maize (Zea mays) inbred genotypes and their hybrid as they grew in complexity from a few to many roots. Genetically driven differences in root branching zone size and lateral branching densities along a single root, combined with differences in peak growth rate and the relative allocation of carbon resources to new versus existing roots, manifest as sharply distinct global RSAs over time. The 3D imaging of mature field-grown root crowns showed that several genetic differences in seedling architectures could persist throughout development and across environments. This approach connects individual and system-wide scales of root growth dynamics, which could eventually be used to predict genetic variation for complex RSAs and their functions.

Three-Dimensional Time-Lapse Analysis Reveals Multiscale Relationships in Maize Root Systems with Contrasting Architectures

Understanding how an organism's phenotypic traits are conditioned by genetic and environmental variation is a central goal of biology. Root systems are one of the most important but poorly understood aspects of plants, largely due to the three-dimensional (3D), dynamic, and multiscale phenotyping challenge they pose. A critical gap in our knowledge is how root systems build in complexity from a single primary root to a network of thousands of roots that collectively compete for ephemeral, heterogeneous soil resources. We used time-lapse 3D imaging and mathematical modeling to assess root system architectures (RSAs) of two maize (Zea mays) inbred genotypes and their hybrid as they grew in complexity from a few to many roots. Genetically driven differences in root branching zone size and lateral branching densities along a single root, combined with differences in peak growth rate and the relative allocation of carbon resources to new versus existing roots, manifest as sharply distinct global RSAs over time. The 3D imaging of mature field-grown root crowns showed that several genetic differences in seedling architectures could persist throughout development and across environments. This approach connects individual and system-wide scales of root growth dynamics, which could eventually be used to predict genetic variation for complex RSAs and their functions.

Development of a model estimating root length density from root impacts on a soil profile in pearl millet (Pennisetum glaucum (L.) R. Br). Application to measure root system response to water stress in field conditions

Pearl millet is able to withstand dry and hot conditions and plays an important role for food security in arid and semi-arid areas of Africa and India. However, low soil fertility and drought constrain pearl millet yield. One target to address these constraints through agricultural practices or breeding is root system architecture. In this study, in order to easily phenotype the root system in field conditions, we developed a model to predict root length density (RLD) of pearl millet plants from root intersection densities (RID) counted on a trench profile in field conditions. We identified root orientation as an important parameter to improve the relationship between RID and RLD. Root orientation was notably found to depend on soil depth and to differ between thick roots (more anisotropic with depth) and fine roots (isotropic at all depths). We used our model to study pearl millet root system response to drought and showed that pearl millet reorients its root growth toward deeper soil layers that retain more water in these conditions. Overall, this model opens ways for the characterization of the impact of environmental factors and management practices on pearl millet root system development.

Plasticity of Lateral Root Branching in Maize

Extensively branched root systems can efficiently capture soil resources by increasing their absorbing surface in soil. Lateral roots are the roots formed from pericycle cells of other roots that can be of any type. As a consequence, lateral roots provide a higher surface to volume ratio and are important for water and nutrients acquisition. Discoveries from recent studies have started to shed light on how plant root systems respond to environmental changes in order to improve capture of soil resources. In this Mini Review, we will mainly focus on the spatial distribution of lateral roots of maize and their developmental plasticity in response to the availability of water and nutrients.