GLO-Roots: an imaging platform enabling multidimensional characterization of soil-grown root systems

RhizoNet segments plant roots to assess biomass and growth for enabling self-driving labs

Flatbed scanners are commonly used for root analysis, but typical manual segmentation methods are time-consuming and prone to errors, especially in large-scale, multi-plant studies. Furthermore, the complex nature of root structures combined with noisy backgrounds in images complicates automated analysis. Addressing these challenges, this article introduces RhizoNet, a deep learning-based workflow to semantically segment plant root scans. Utilizing a sophisticated Residual U-Net architecture, RhizoNet enhances prediction accuracy and employs a convex hull operation for delineation of the primary root component. Its main objective is to accurately segment root biomass and monitor its growth over time. RhizoNet processes color scans of plants grown in a hydroponic system known as EcoFAB, subjected to specific nutritional treatments. The root detection model using RhizoNet demonstrates strong generalization in the validation tests of all experiments despite variable treatments. The main contributions are the standardization of root segmentation and phenotyping, systematic and accelerated analysis of thousands of images, significantly aiding in the precise assessment of root growth dynamics under varying plant conditions, and offering a path toward self-driving labs.

Super-Transparent Soil for In Situ Observation of Root Phenotypes

Transparent soil (TS) presents immense potential for root phenotyping due to its ability to facilitate high-resolution imaging. However, challenges related to transparency, mechanical properties, and cost hinder its development. Herein, we introduce super-transparent soil (s-TS) prepared via the droplet method using low acyl gellan gum and hydroxyethyl cellulose crosslinked with magnesium ions. The refractive index of the hydroxyethyl cellulose solution (1.345) closely aligns with that of water (1.333) and the low acyl gellan gum solution (1.340), thereby significantly enhancing the transmittance of hydrogel-based transparent soil. Optimal transmittance (98.45%) is achieved with polymer concentrations ranging from 0.8 to 1.6 wt.% and ion concentrations between 0.01 and 0.09 mol·L-1. After 60 days of plant cultivation, s-TS maintains a transmittance exceeding 89.5%, enabling the detailed visualization of root growth dynamics. Furthermore, s-TS exhibits remarkable mechanical properties, withstanding a maximum compressive stress of 477 kPa and supporting a maximum load-bearing depth of 186 cm. This innovative approach holds promising implications for advanced root phenotyping studies, fostering the investigation of root heterogeneity and the development of selective expression under controlled conditions.

The role of phenomics and genomics in delineating the genetic basis of complex traits in millets

Millets, comprising a diverse group of small-seeded grains, have emerged as vital crops with immense nutritional, environmental, and economic significance. The comprehension of complex traits in millets, influenced by multifaceted genetic determinants, presents a compelling challenge and opportunity in agricultural research. This review delves into the transformative roles of phenomics and genomics in deciphering these intricate genetic architectures. On the phenomics front, high-throughput platforms generate rich datasets on plant morphology, physiology, and performance in diverse environments. This data, coupled with field trials and controlled conditions, helps to interpret how the environment interacts with genetics. Genomics provides the underlying blueprint for these complex traits. Genome sequencing and genotyping technologies have illuminated the millet genome landscape, revealing diverse gene pools and evolutionary relationships. Additionally, different omics approaches unveil the intricate information of gene expression, protein function, and metabolite accumulation driving phenotypic expression. This multi-omics approach is crucial for identifying candidate genes and unfolding the intricate pathways governing complex traits. The review highlights the synergy between phenomics and genomics. Genomically informed phenotyping targets specific traits, reducing the breeding size and cost. Conversely, phenomics identifies promising germplasm for genomic analysis, prioritizing variants with superior performance. This dynamic interplay accelerates breeding programs and facilitates the development of climate-smart, nutrient-rich millet varieties and hybrids. In conclusion, this review emphasizes the crucial roles of phenomics and genomics in unlocking the genetic enigma of millets.

The State of the Art in Root System Architecture Image Analysis Using Artificial Intelligence: A Review

Roots are essential for acquiring water and nutrients to sustain and support plant growth and anchorage. However, they have been studied less than the aboveground traits in phenotyping and plant breeding until recent decades. In modern times, root properties such as morphology and root system architecture (RSA) have been recognized as increasingly important traits for creating more and higher quality food in the "Second Green Revolution". To address the paucity in RSA and other root research, new technologies are being investigated to fill the increasing demand to improve plants via root traits and overcome currently stagnated genetic progress in stable yields. Artificial intelligence (AI) is now a cutting-edge technology proving to be highly successful in many applications, such as crop science and genetic research to improve crop traits. A burgeoning field in crop science is the application of AI to high-resolution imagery in analyses that aim to answer questions related to crops and to better and more speedily breed desired plant traits such as RSA into new cultivars. This review is a synopsis concerning the origins, applications, challenges, and future directions of RSA research regarding image analyses using AI.

Non-destructive, whole-plant phenotyping reveals dynamic changes in water use efficiency, photosynthesis, and rhizosphere acidification of sorghum accessions under osmotic stress

Noninvasive phenotyping can quantify dynamic plant growth processes at higher temporal resolution than destructive phenotyping and can reveal phenomena that would be missed by end-point analysis alone. Additionally, whole-plant phenotyping can identify growth conditions that are optimal for both above- and below-ground tissues. However, noninvasive, whole-plant phenotyping approaches available today are generally expensive, complex, and non-modular. We developed a low-cost and versatile approach to noninvasively measure whole-plant physiology over time by growing plants in isolated hydroponic chambers. We demonstrate the versatility of our approach by measuring whole-plant biomass accumulation, water use, and water use efficiency every two days on unstressed and osmotically stressed sorghum accessions. We identified relationships between root zone acidification and photosynthesis on whole-plant water use efficiency over time. Our system can be implemented using cheap, basic components, requires no specific technical expertise, and should be suitable for any non-aquatic vascular plant species.

Unraveling plant-microbe interactions: can integrated omics approaches offer concrete answers?

Advances in high throughput omics techniques provide avenues to decipher plant microbiomes. However, there is limited information on how integrated informatics can help provide deeper insights into plant-microbe interactions in a concerted way. Integrating multi-omics datasets can transform our understanding of the plant microbiome from unspecified genetic influences on interacting species to specific gene-by-gene interactions. Here, we highlight recent progress and emerging strategies in crop microbiome omics research and review key aspects of how the integration of host and microbial omics-based datasets can be used to provide a comprehensive outline of complex crop-microbe interactions. We describe how these technological advances have helped unravel crucial plant and microbial genes and pathways that control beneficial, pathogenic, and commensal plant-microbe interactions. We identify crucial knowledge gaps and synthesize current limitations in our understanding of crop microbiome omics approaches. We highlight recent studies in which multi-omics-based approaches have led to improved models of crop microbial community structure and function. Finally, we recommend holistic approaches in integrating host and microbial omics datasets to achieve precision and efficiency in data analysis, which is crucial for biotic and abiotic stress control and in understanding the contribution of the microbiota in shaping plant fitness.

How plant roots respond to waterlogging

Plant submergence is a major abiotic stress that impairs plant performance. Under water, reduced gas diffusion exposes submerged plant cells to an environment that is enriched in gaseous ethylene and is limited in oxygen (O2) availability (hypoxia). The capacity for plant roots to avoid and/or sustain critical hypoxia damage is essential for plants to survive waterlogging. Plants use spatiotemporal ethylene and O2 dynamics as instrumental flooding signals to modulate potential adaptive root growth and hypoxia stress acclimation responses. However, how non-adapted plant species modulate root growth behaviour during actual waterlogged conditions to overcome flooding stress has hardly been investigated. Here we discuss how changes in the root growth rate, lateral root formation, density, and growth angle of non-flood adapted plant species (mainly Arabidopsis) could contribute to avoiding and enduring critical hypoxic conditions. In addition, we discuss current molecular understanding of how ethylene and hypoxia signalling control these adaptive root growth responses. We propose that future research would benefit from less artificial experimental designs to better understand how plant roots respond to and survive waterlogging. This acquired knowledge would be instrumental to guide targeted breeding of flood-tolerant crops with more resilient root systems.

C-TERMINALLY ENCODED PEPTIDE (CEP) and cytokinin hormone signaling intersect to promote shallow lateral root angles

Root system architecture (RSA) influences the acquisition of heterogeneously dispersed soil nutrients. Cytokinin and C-TERMINALLY ENCODED PEPTIDE (CEP) hormones affect RSA, in part by controlling the angle of lateral root (LR) growth. Both hormone pathways converge on CEP DOWNSTREAM 1 (CEPD1) and CEPD2 to control primary root growth; however, a role for CEPDs in controlling the growth angle of LRs is unknown. Using phenotyping combined with genetic and grafting approaches, we show that CEP hormone-mediated shallower LR growth requires cytokinin biosynthesis and perception in roots via ARABIDOPSIS HISTIDINE KINASE 2 (AHK2) and AHK3. Consistently, cytokinin biosynthesis and ahk2,3 mutants phenocopied the steeper root phenotype of cep receptor 1 (cepr1) mutants on agar plates, and CEPR1 was required for trans-Zeatin (tZ)-type cytokinin-mediated shallower LR growth. In addition, the cepd1,2 mutant was less sensitive to CEP and tZ, and showed basally steeper LRs on agar plates. Cytokinin and CEP pathway mutants were grown in rhizoboxes to define the role of these pathways in controlling RSA. Only cytokinin receptor mutants and cepd1,2 partially phenocopied the steeper-rooted phenotype of cepr1 mutants. These results show that CEP and cytokinin signaling intersect to promote shallower LR growth, but additional components contribute to the cepr1 phenotype in soil.

Diversity, Variance, and Stability of Root Phenes of Peanut (Arachis hypogaea L.)

Root phenes are associated with the absorptive efficiency of water and fertilizers. However, there are few reports on the genetic variation and stability of peanut (Arachis hypogaea L.) root architecture under different environments. In this study, the diversity, variance and stability of root phenes of 89 peanut varieties were investigated with shovelomics (high throughput phenotyping of root system architecture) for two years in both field and laboratory experiments. The root phenes of these peanut genotypes presented rich diversity; for example, the value of total root length (TRL) ranged from 347.84 cm to 1013.80 cm in the field in 2018, and from 55.14 cm to 206.22 cm in the laboratory tests. The root phenes of different genotypes varied differently; for example, the coefficient of variation (CV) of TRL ranged from 24.0 to 83.5 across the two-year field test. Field and laboratory evaluations were highly correlated, especially on lateral root density (LRD) and root angle (RA), and the quadrant graph analysis of LRD and RA implied that 69.7% of the roots belong to the same type. These not only further reflect root phenes stability through different environment but also demonstrate that some root phenes identified at early stage can indicate their status at later growth stage. In addition, root phenes showed a strong correlation with shoot growth, especially root dry weight (RDW), TRL and（nodule number）NN. Thus, laboratory tests in combination with field shovelomics can efficiently screen and select genotypes with contrasting root phenes to optimize water and nutrient management.

Zoom-in to molecular mechanisms underlying root growth and function under heterogeneous soil environment and abiotic stresses

MAIN CONCLUSION

The review describes tissue-specific and non-cell autonomous molecular responses regulating the root system architecture and function in plants. Phenotypic plasticity of roots relies on specific molecular and tissue specific responses towards local and microscale heterogeneity in edaphic factors. Unlike gravitropism, hydrotropism in Arabidopsis is regulated by MIZU KUSSIE1 (MIZ1)-dependent asymmetric distribution of cytokinin and activation of Arabidopsis response regulators, ARR16 and ARR17 on the lower water potential side of the root leading to higher cell division and root bending. The cortex specific role of Abscisic acid (ABA)-activated SNF1-related protein kinase 2.2 (SnRK2.2) and MIZ1 in elongation zone is emerging for hydrotropic curvature. Halotropism involves clathrin-mediated internalization of PIN FORMED 2 (PIN2) proteins at the side facing higher salt concentration in the root tip, and ABA-activated SnRK2.6 mediated phosphorylation of cortical microtubule-associated protein Spiral2-like (SP2L) in the root transition zone, which results in anisotropic cell expansion and root bending away from higher salt. In hydropatterning, Indole-3-acetic acid 3 (IAA3) interacts with SUMOylated-ARF7 (Auxin response factor 7) and prevents expression of Lateral organ boundaries-domain 16 (LBD16) in air-side of the root, while on wet side of the root, IAA3 cannot repress the non-SUMOylated-ARF7 thereby leading to LBD16 expression and lateral root development. In root vasculature, ABA induces expression of microRNA165/microRNA166 in endodermis, which moves into the stele to target class III Homeodomain leucine zipper protein (HD-ZIP III) mRNA in non-cell autonomous manner. The bidirectional gradient of microRNA165/6 and HD-ZIP III mRNA regulates xylem patterning under stress. Understanding the tissue specific molecular mechanisms regulating the root responses under heterogeneous and stress environments will help in designing climate-resilient crops.

Rhizosphere frame system enables nondestructive live-imaging of legume-rhizobium interactions in the soil

Most plants interact with various soil microorganisms as they grow through the soil. Root nodule symbiosis by legumes and rhizobia is a well-known phenomenon of plant-microbe interactions in the soil. Although microscopic observations are useful for understanding the infection processes of rhizobia, nondestructive observation methods have not been established for monitoring interactions between rhizobia and soil-grown roots. In this study, we constructed Bradyrhizobium diazoefficiens strains that constitutively express different fluorescent proteins, which allows identification of tagged rhizobia by the type of fluorophores. In addition, we constructed a plant cultivation device, Rhizosphere Frame (RhizoFrame), which is a soil-filled container made of transparent acrylic plates that allows observation of roots growing along the acrylic plates. Combining fluorescent rhizobia with RhizoFrame, we established a live imaging system, RhizoFrame system, that enabled us to track the nodulation processes with fluorescence stereomicroscope while retaining spatial information about roots, rhizobia, and soil. Mixed inoculation with different fluorescent rhizobia using RhizoFrame enabled the visualization of mixed infection of a single nodule with two strains. In addition, observation of transgenic Lotus japonicus expressing auxin-responsive reporter genes indicated that RhizoFrame system could be used for a real-time and nondestructive reporter assay. Thus, the use of RhizoFrame system is expected to enhance the study of the spatiotemporal dynamics of plant-microbe interactions in the soil.

A bench-top Dark-Root device built with LEGO® bricks enables a non-invasive plant root development analysis in soil conditions mirroring nature

Roots are the hidden parts of plants, anchoring their above-ground counterparts in the soil. They are responsible for water and nutrient uptake and for interacting with biotic and abiotic factors in the soil. The root system architecture (RSA) and its plasticity are crucial for resource acquisition and consequently correlate with plant performance while being highly dependent on the surrounding environment, such as soil properties and therefore environmental conditions. Thus, especially for crop plants and regarding agricultural challenges, it is essential to perform molecular and phenotypic analyses of the root system under conditions as near as possible to nature (#asnearaspossibletonature). To prevent root illumination during experimental procedures, which would heavily affect root development, Dark-Root (D-Root) devices (DRDs) have been developed. In this article, we describe the construction and different applications of a sustainable, affordable, flexible, and easy to assemble open-hardware bench-top LEGO® DRD, the DRD-BIBLOX (Brick Black Box). The DRD-BIBLOX consists of one or more 3D-printed rhizoboxes, which can be filled with soil while still providing root visibility. The rhizoboxes sit in a scaffold of secondhand LEGO® bricks, which allows root development in the dark and non-invasive root tracking with an infrared (IR) camera and an IR light-emitting diode (LED) cluster. Proteomic analyses confirmed significant effects of root illumination on barley root and shoot proteomes. Additionally, we confirmed the significant effect of root illumination on barley root and shoot phenotypes. Our data therefore reinforces the importance of the application of field conditions in the lab and the value of our novel device, the DRD-BIBLOX. We further provide a DRD-BIBLOX application spectrum, spanning from investigating a variety of plant species and soil conditions and simulating different environmental conditions and stresses, to proteomic and phenotypic analyses, including early root tracking in the dark.

Studying root-environment interactions in structured microdevices

In negotiating with the environment, plant roots integrate sensory information over space and time, as the basis of decision making in roots under non-uniform conditions. The complexity and dynamic properties of soil across spatial and temporal scales pose a significant technical challenge for research on mechanisms that drive metabolism, growth and development in roots, as well as on inter-organismal networks in the rhizosphere. Synthetic environments, combining microscopic access and manipulation capabilities with soil-like heterogeneity, are needed to elucidate the intriguing tug-of-war that characterises subsurface ecosystems. Microdevices have provided opportunities for innovative approaches to observe, analyse and manipulate plant roots and advanced our understanding of their development, physiology and interactions with the environment. Initially conceived as perfusion platforms for root cultivation under hydroponic conditions, microdevice design has, in recent years, increasingly shifted to better reflect the complex growth conditions in soil. Heterogeneous micro-environments have been created through co-cultivation with microbes, laminar flow-based local stimulation and physical obstacles and constraints. As such, structured microdevices provide an experimental entry point to the complex network behaviour of soil communities.

Assembly and operation of an imaging system for long-term monitoring of bioluminescent and fluorescent reporters in plants

BACKGROUND

Non-invasive reporter systems are powerful tools to query physiological and transcriptional responses in organisms. For example, fluorescent and bioluminescent reporters have revolutionized cellular and organismal assays and have been used to study plant responses to abiotic and biotic stressors. Integrated, cooled charge-coupled device (CCD) camera systems have been developed to image bioluminescent and fluorescent signals in a variety of organisms; however, these integrated long-term imaging systems are expensive.

RESULTS

We have developed self-assembled systems for both growing and monitoring plant fluorescence and bioluminescence for long-term experiments under controlled environmental conditions. This system combines environmental growth chambers with high-sensitivity CCD cameras, multi-wavelength LEDs, open-source software, and several options for coordinating lights with imaging. This easy-to-assemble system can be used for short and long-term imaging of bioluminescent reporters, acute light-response, circadian rhythms, delayed fluorescence, and fluorescent-protein-based assays in vivo.

CONCLUSIONS

We have developed two self-assembled imaging systems that will be useful to researchers interested in continuously monitoring in vivo reporter systems in various plant species.

Four-dimensional measurement of root system development using time-series three-dimensional volumetric data analysis by backward prediction

BACKGROUND

Root system architecture (RSA) is an essential characteristic for efficient water and nutrient absorption in terrestrial plants; its plasticity enables plants to respond to different soil environments. Better understanding of root plasticity is important in developing stress-tolerant crops. Non-invasive techniques that can measure roots in soils nondestructively, such as X-ray computed tomography (CT), are useful to evaluate RSA plasticity. However, although RSA plasticity can be measured by tracking individual root growth, only a few methods are available for tracking individual roots from time-series three-dimensional (3D) images.

RESULTS

We developed a semi-automatic workflow that tracks individual root growth by vectorizing RSA from time-series 3D images via two major steps. The first step involves 3D alignment of the time-series RSA images by iterative closest point registration with point clouds generated by high-intensity particles in potted soils. This alignment ensures that the time-series RSA images overlap. The second step consists of backward prediction of vectorization, which is based on the phenomenon that the root length of the RSA vector at the earlier time point is shorter than that at the last time point. In other words, when CT scanning is performed at time point A and again at time point B for the same pot, the CT data and RSA vectors at time points A and B will almost overlap, but not where the roots have grown. We assumed that given a manually created RSA vector at the last time point of the time series, all RSA vectors except those at the last time point could be automatically predicted by referring to the corresponding RSA images. Using 21 time-series CT volumes of a potted plant of upland rice (Oryza sativa), this workflow revealed that the root elongation speed increased with age. Compared with a workflow that does not use backward prediction, the workflow with backward prediction reduced the manual labor time by 95%.

CONCLUSIONS

We developed a workflow to efficiently generate time-series RSA vectors from time-series X-ray CT volumes. We named this workflow 'RSAtrace4D' and are confident that it can be applied to the time-series analysis of RSA development and plasticity.

Responses of root system architecture to water stress at multiple levels: A meta-analysis of trials under controlled conditions

Plants are exposed to increasingly severe drought events and roots play vital roles in maintaining plant survival, growth, and reproduction. A large body of literature has investigated the adaptive responses of root traits in various plants to water stress and these studies have been reviewed in certain groups of plant species at a certain scale. Nevertheless, these responses have not been synthesized at multiple levels. This paper screened over 2000 literatures for studies of typical root traits including root growth angle, root depth, root length, root diameter, root dry weight, root-to-shoot ratio, root hair length and density and integrates their drought responses at genetic and morphological scales. The genes, quantitative trait loci (QTLs) and hormones that are involved in the regulation of drought response of the root traits were summarized. We then statistically analyzed the drought responses of root traits and discussed the underlying mechanisms. Moreover, we highlighted the drought response of 1-D and 2-D root length density (RLD) distribution in the soil profile. This paper will provide a framework for an integrated understanding of root adaptive responses to water deficit at multiple scales and such insights may provide a basis for selection and breeding of drought tolerant crop lines.

Integrating advancements in root phenotyping and genome-wide association studies to open the root genetics gateway

Plant adaptation to challenging environmental conditions around the world has made root growth and development an important research area for plant breeders and scientists. Targeted manipulation of root system architecture (RSA) to increase water and nutrient use efficiency can minimize the adverse effects of climate change on crop production. However, phenotyping of RSA is a major bottleneck since the roots are hidden in the soil. Recently the development of 2- and 3D root imaging techniques combined with the genome-wide association studies (GWASs) have opened up new research tools to identify the genetic basis of RSA. These approaches provide a comprehensive understanding of the RSA, by accelerating the identification and characterization of genes involved in root growth and development. This review summarizes the latest developments in phenotyping techniques and GWAS for RSA, which are used to map important genes regulating various aspects of RSA under varying environmental conditions. Furthermore, we discussed about the state-of-the-art image analysis tools integrated with various phenotyping platforms for investigating and quantifying root traits with the highest phenotypic plasticity in both artificial and natural environments which were used for large scale association mapping studies, leading to the identification of RSA phenotypes and their underlying genetics with the greatest potential for RSA improvement. In addition, challenges in root phenotyping and GWAS are also highlighted, along with future research directions employing machine learning and pan-genomics approaches.

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

High temperatures inhibit plant growth. A proposed strategy for improving plant productivity under elevated temperatures is the use of plant growth-promoting rhizobacteria (PGPR). While the effects of PGPR on plant shoots have been extensively explored, roots-particularly their spatial and temporal dynamics-have been hard to study, due to their below-ground nature. Here, we characterized the time- and tissue-specific morphological changes in bacterized plants using a novel non-invasive high-resolution plant phenotyping and imaging platform-GrowScreen-Agar II. The platform uses custom-made agar plates, which allow air exchange to occur with the agar medium and enable the shoot to grow outside the compartment. The platform provides light protection to the roots, the exposure of it to the shoots, and the non-invasive phenotyping of both organs. Arabidopsis thaliana, co-cultivated with Paraburkholderia phytofirmans PsJN at elevated and ambient temperatures, showed increased lengths, growth rates, and numbers of roots. However, the magnitude and direction of the growth promotion varied depending on root type, timing, and temperature. The root length and distribution per depth and according to time was also influenced by bacterization and the temperature. The shoot biomass increased at the later stages under ambient temperature in the bacterized plants. The study offers insights into the timing of the tissue-specific, PsJN-induced morphological changes and should facilitate future molecular and biochemical studies on plant-microbe-environment interactions.

Pisum sativum has no competitive responses to neighbors: A case study in (non)reproducible plant biology

Plant-plant competition is ubiquitous in nature. However, studying below ground behavior of roots has always posed certain difficulties. Pea (Pisum sativum L.) has become a common study species for questions about how plant roots respond to neighboring plant roots and barriers in soil. However, published results point in several different directions. This has sometimes been interpreted as pea having sophisticated context dependent responses that can change in complex ways depending on its surroundings, but it could also just point to small statistical power resulting in type I or II statistical errors. To explore this further, here, we combine the result of five new experiments with published results to examine 18 unique experiments from 10 different studies and 6 cultivars of pea for a total of 254 replicate plants. We used a Bayesian hierarchical meta-analysis approach to estimating the likely effect size from the available data, as well as quantify heterogeneity among different experiments, studies and cultivars. The posterior distributions show that, at the coarsest possible scale of total root production, it is unlikely that P. sativum root growth is influenced by either neighbors or pot volume that varies primarily by depth. We find no evidence of publication bias and conclude that this is simply due to statistical sampling error and the scientific method combined with frequentist statistics operating as intended. We suggest that further work on pea should consider repeating experiments that reported finer scale root plasticity at the rhizosphere scale or consider exploring different pot geometries such as volume that varies by depth or width. We also suggest that more diversity in study species are needed to better understand the neighbor-volume response.

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

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 in 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.

Genetic Circuit Design in Rhizobacteria

Genetically engineered plants hold enormous promise for tackling global food security and agricultural sustainability challenges. However, construction of plant-based genetic circuitry is constrained by a lack of well-characterized genetic parts and circuit design rules. In contrast, advances in bacterial synthetic biology have yielded a wealth of sensors, actuators, and other tools that can be used to build bacterial circuitry. As root-colonizing bacteria (rhizobacteria) exert substantial influence over plant health and growth, genetic circuit design in these microorganisms can be used to indirectly engineer plants and accelerate the design-build-test-learn cycle. Here, we outline genetic parts and best practices for designing rhizobacterial circuits, with an emphasis on sensors, actuators, and chassis species that can be used to monitor/control rhizosphere and plant processes.

Recent advances in methods for in situ root phenotyping

Roots assist plants in absorbing water and nutrients from soil. Thus, they are vital to the survival of nearly all land plants, considering that plants cannot move to seek optimal environmental conditions. Crop species with optimal root system are essential for future food security and key to improving agricultural productivity and sustainability. Root systems can be improved and bred to acquire soil resources efficiently and effectively. This can also reduce adverse environmental impacts by decreasing the need for fertilization and fresh water. Therefore, there is a need to improve and breed crop cultivars with favorable root system. However, the lack of high-throughput root phenotyping tools for characterizing root traits in situ is a barrier to breeding for root system improvement. In recent years, many breakthroughs in the measurement and analysis of roots in a root system have been made. Here, we describe the major advances in root image acquisition and analysis technologies and summarize the advantages and disadvantages of each method. Furthermore, we look forward to the future development direction and trend of root phenotyping methods. This review aims to aid researchers in choosing a more appropriate method for improving the root system.

Recent trends in root phenomics of plant systems with available methods- discrepancies and consonances

The phenotyping of plant roots is a challenging task and poses a major lacuna in plant root research. Roots rhizospheric zone is affected by several environmental cues among which salinity, drought, heavy metal and soil pH are key players. Among biological factors, fungal, nematode and bacterial interactions with roots are vital for improving nutrient uptake efficiency in plants. The subterranean nature of a plant root and the limited number of approaches for root phenotyping offers a great challenge to the plant breeders to select a desirable root trait under different stress conditions. Identification of key root traits can provide a basic understanding for generating crop plants with enhanced ability to withstand various biotic or abiotic stresses. For instance, crops with improved soil exploration potential, phosphate uptake efficiency, water use efficiency and others. Laboratory methods such as hydroponics, rhizotron, rhizoslide and luminescence observatory for roots do not provide precise and desired root quantification attributes. Though 3D imaging by X-ray computed tomography (X-ray-CT) and magnetic resonance imaging techniques are complex, however, it provides the most applicable and practically relevant data for quantifying root system architecture traits. This review outlines the current developments in root studies including recent approaches viz. X-ray-CT, MRI, thermal infrared imaging and minirhizotron. Although root phenotyping is a laborious procedure, it offers multiple advantages by removing discrepancies and providing the actual practical significance of plant roots for breeding programs.

CHIQUITA1 maintains the temporal transition between proliferation and differentiation in Arabidopsis thaliana

Body size varies widely among species, populations and individuals, depending on the environment. Transitioning between proliferation and differentiation is a crucial determinant of final organ size, but how the timing of this transition is established and maintained remains unknown. Using cell proliferation markers and genetic analysis, we show that CHIQUITA1 (CHIQ1) is required to maintain the timing of the transition from proliferation to differentiation in Arabidopsis thaliana. Combining kinematic and cell lineage-tracking studies, we found that the number of actively dividing cells in chiquita1-1 plants decreases prematurely compared with wild-type plants, suggesting CHIQ1 maintains the proliferative capacity in dividing cells and ensures that cells divide a specific number of times. CHIQ1 belongs to a plant-specific gene family of unknown molecular function and genetically interacts with three close members of its family to control the timing of proliferation exit. Our work reveals the interdependency between cellular and organ-level processes underlying final organ size determination.

Root growth direction in simulated microgravity is modulated by a light avoidance mechanism mediated by flavonols

In a microgravity environment, without any gravitropic signal, plants are not able to define and establish a longitudinal growth axis. Consequently, absorption of water and nutrients by the root and exposure of leaves to sunlight for efficient photosynthesis is hindered. In these conditions, other external cues can be explored to guide the direction of organ growth. Providing a unilateral light source can guide the shoot growth, but prolonged root exposure to light causes a stress response, affecting growth and development, and also affecting the response to other environmental factors. Here, we have investigated how the protection of the root from light exposure, while the shoot is illuminated, influences the direction of root growth in microgravity. We report that the light avoidance mechanism existing in roots guides their growth towards diminishing light and helps establish the proper longitudinal seedling axis in simulated microgravity conditions. This process is regulated by flavonols, as shown in the flavonoid-accumulating mutant transparent testa 3, which shows an increased correction of the root growth direction in microgravity, when the seedling is grown with the root protected from light. This finding may improve the efficiency of water and nutrient sourcing and photosynthesis under microgravity conditions, as they exist in space, contributing to better plant fitness and biomass production in space farming enterprises, necessary for space exploration by humans.

Natural Genotypic Variation Underpins Root System Response to Drought Stress in Bambara Groundnut [Vigna subterranea (L.) Verdc.]

Bambara groundnut [Vigna subterranea (L.) Verdc.] is grown in rainfed production systems and suffers from periodic drought stress (DS), leading to yield reductions. Natural genotypic variation for root traits is essential for adaptation to water deficit conditions. However, root traits have not been fully utilised as selection criteria to improve DS in bambara groundnut. The present study explored the natural genotypic variation found in single genotypes of bambara groundnut derived from landraces to identify adaptive differences in tap root length (TRL) and root length density (RLD) in response to DS. A diverse core collection of eight bambara groundnut genotypes from various locations (namely, Gresik, LunT, IITA-686, DodR, S19-3, Tiga nicuru, and Ankpa-4, DipC1), were grown for two seasons (2018 and 2019) in polyvinyl chloride (PVC) columns with well-watered (WW) and 30-day DS treatments. Plant samples were collected at 55 days after emergence (DAE) (30 days of DS) and at 105 DAE (30 days of DS plus 50 days of recovery). Under DS, differential TRL among genotypes at 55 DAE was observed, with DodR recording the longest among genotypes with an increase (1% in 2018) in TRL under DS compared to WW, whereas LunT and IITA-686 showed significant (p < 0.001) decrease in TRL (27 and 25%, respectively, in 2018). Average RLD was observed to have the highest reduction under DS in the 90-110 cm layer (42 and 58%, respectively, in 2018 and 2019). Rainy habitat LunT had limited roots in 2018 and recorded the least (0.06 ± 0.013 cm^-3) RLD in 2019. However, dry-habitat DodR showed an increase in the RLD (60-90 cm) under DS compared to WW, while dry-habitat S19-3 densely occupied all depths with RLD of 0.16 ± 0.05 and 0.18 ± 0.01 cm cm^-3 in the deepest layer in both seasons, respectively. Reduced RLD under DS showed recovery when the plants were re-watered. These plants were additionally observed to have RLD that surpasses the density in WW at all soil depths at 105 DAE. Also, recovery was shown in Tiga nicuru and DodR (0-30 cm) and IITA-686 (90-110 cm) in 2019. Average RLD under DS treatment was associated with substantial grain yield advantage (R ² = 0.27 and R ² = 0.49, respectively) in 2018 and 2019. An increase in TRL allowed DodR to quickly explore water at a deeper soil depth in response to gradually declining soil water availability. High RLD in genotypes such as DodR, DipC1 and S19-3 also offered adaptive advantage over other genotypes under DS. Variation in intrinsic RLD in deeper soil depths in the studied genotypes determines root foraging capacity when facing DS. This suggests that different agroecological environments to which bambara groundnut is subjected in its natural habitat have promoted a phenotypic differentiation in root systems to adapt to ecotypic conditions, which may help offset the impact of DS. The natural genotypic variation exhibited, especially by DodR, could be exploited to identify potential quantitative trait loci (QTLs) that control deep rooting and root length density.

MultipleXLab: A high-throughput portable live-imaging root phenotyping platform using deep learning and computer vision

BACKGROUND

Profiling the plant root architecture is vital for selecting resilient crops that can efficiently take up water and nutrients. The high-performance imaging tools available to study root-growth dynamics with the optimal resolution are costly and stationary. In addition, performing nondestructive high-throughput phenotyping to extract the structural and morphological features of roots remains challenging.

RESULTS

We developed the MultipleXLab: a modular, mobile, and cost-effective setup to tackle these limitations. The system can continuously monitor thousands of seeds from germination to root development based on a conventional camera attached to a motorized multiaxis-rotational stage and custom-built 3D-printed plate holder with integrated light-emitting diode lighting. We also developed an image segmentation model based on deep learning that allows the users to analyze the data automatically. We tested the MultipleXLab to monitor seed germination and root growth of Arabidopsis developmental, cell cycle, and auxin transport mutants non-invasively at high-throughput and showed that the system provides robust data and allows precise evaluation of germination index and hourly growth rate between mutants.

CONCLUSION

MultipleXLab provides a flexible and user-friendly root phenotyping platform that is an attractive mobile alternative to high-end imaging platforms and stationary growth chambers. It can be used in numerous applications by plant biologists, the seed industry, crop scientists, and breeding companies.

A spatial model of the plant circadian clock reveals design principles for coordinated timing

Individual plant cells possess a genetic network, the circadian clock, that times internal processes to the day‐night cycle. Mathematical models of the clock are typically either “whole‐plant” that ignore tissue or cell type‐specific clock behavior, or “phase‐only” that do not include molecular components. To address the complex spatial coordination observed in experiments, here we implemented a clock network model on a template of a seedling. In our model, the sensitivity to light varies across the plant, and cells communicate their timing via local or long‐distance sharing of clock components, causing their rhythms to couple. We found that both varied light sensitivity and long‐distance coupling could generate period differences between organs, while local coupling was required to generate the spatial waves of clock gene expression observed experimentally. We then examined our model under noisy light‐dark cycles and found that local coupling minimized timing errors caused by the noise while allowing each plant region to maintain a different clock phase. Thus, local sensitivity to environmental inputs combined with local coupling enables flexible yet robust circadian timing.

Deconstructing the root system of grasses through an exploration of development, anatomy and function

Well-adapted root systems allow plants to grow under resource-limiting environmental conditions and are important determinants of yield in agricultural systems. Important staple crops such as rice and maize belong to the family of grasses, which develop a complex root system that consists of an embryonic root system that emerges from the seed, and a postembryonic nodal root system that emerges from basal regions of the shoot after germination. While early seedling establishment is dependent on the embryonic root system, the nodal root system, and its associated branches, gains in importance as the plant matures and will ultimately constitute the bulk of below-ground growth. In this review, we aim to give an overview of the different root types that develop in cereal grass root systems, explore the different physiological roles they play by defining their anatomical features, and outline the genetic networks that control their development. Through this deconstructed view of grass root system function, we provide a parts-list of elements that function together in an integrated root system to promote survival and crop productivity.

May the dark be with roots: a perspective on how root illumination may bias in vitro research on plant-environment interactions

Roots anchor plants to the soil, providing them with nutrients and water while creating a defence network and facilitating beneficial interactions with a multitude of living organisms and climatological conditions. To facilitate morphological and molecular studies, root research has been conducted using in vitro systems. However, under natural conditions, roots grow in the dark, mainly in the absence of illumination, except for the relatively low illumination of the upper soil surface, and this has been largely ignored. Here, we discuss the results found over the last decade on how experimental exposure of roots to light may bias root development and responses through the alteration of hormonal signalling, cytoskeleton organization, reactive oxygen species or the accumulation of flavonoids, among other factors. Illumination alters the uptake of nutrients or water, and also affects the response of the roots to abiotic stresses and root interactions with the microbiota. Furthermore, we review in vitro systems created to maintain roots in darkness, and provide a comparative analysis of root transcriptomes obtained with these devices. Finally, we identify other experimental variables that should be considered to better mimic soil conditions, whose improvement would benefit studies using in vitro cultivation or enclosed ecosystems.

Root dynamic growth strategies in response to salinity

Increasing soil salinization largely impacts crop yield worldwide. To deal with salinity stress, plants exhibit an array of responses, including root system architecture remodelling. Here, we review recent progress in physiological, developmental and cellular mechanisms of root growth responses to salinity. Most recent research in modulation of root branching, root tropisms, as well as in root cell wall modifications under salinity stress, is discussed in the context of the contribution of these responses to overall plant performance. We highlight the power of natural variation approaches revealing novel potential pathways responsible for differences in root salt stress responses. Together, these new findings promote our understanding of how salt shapes the root phenotype, which may provide potential avenues for engineering crops with better yield and survival in saline soils.

Model-based plant phenomics on morphological traits using morphometric descriptors

The morphological traits of plants contribute to many important functional features such as radiation interception, lodging tolerance, gas exchange efficiency, spatial competition between individuals and/or species, and disease resistance. Although the importance of plant phenotyping techniques is increasing with advances in molecular breeding strategies, there are barriers to its advancement, including the gap between measured data and phenotypic values, low quantitativity, and low throughput caused by the lack of models for representing morphological traits. In this review, we introduce morphological descriptors that can be used for phenotyping plant morphological traits. Geometric morphometric approaches pave the way to a general-purpose method applicable to single units. Hierarchical structures composed of an indefinite number of multiple elements, which is often observed in plants, can be quantified in terms of their multi-scale topological characteristics using topological data analysis. Theoretical morphological models capture specific anatomical structures, if recognized. These morphological descriptors provide us with the advantages of model-based plant phenotyping, including robust quantification of limited datasets. Moreover, we discuss the future possibilities that a system of model-based measurement and model refinement would solve the lack of morphological models and the difficulties in scaling out the phenotyping processes.

ABA regulation of root growth during soil drying and recovery can involve auxin response

Abscisic acid (ABA) plays an important role in plant adaptation to water deficits, but its role in regulating root growth (primary root elongation and lateral root number) during different drought-phases remains unclear. Here, we exposed wild-type (WT) and ABA-deficient (not) tomato plants to three continuous drought-phases (moderate drying: day 0-21; severe drying: day 22-47 and re-watering: day 48-51). It was found that WT increased primary root growth during moderate drying; maintained more lateral roots, and greater primary root and total root length under severe drying; and produced more roots after re-watering. After RNA-Seq analysis, we found that the auxin-related genes in root showed different expression patterns between WT and not under drying or re-watering. Further, exogenous supply of IAA partially recovered the root growth of ABA-deficient not plants under three continuous drought-phases. Our results suggested that ABA regulation of tomato root growth during soil drying and recovery can involve auxin response.

Mechanisms of temperature-regulated growth and thermotolerance in crop species

Temperature is a major environmental factor affecting the development and productivity of crop species. The ability to cope with periods of high temperatures, also known as thermotolerance, is becoming an increasingly indispensable trait for the future of agriculture owing to the current trajectory of average global temperatures. From temperature sensing to downstream transcriptional changes, here, we review recent findings involving the thermal regulation of plant growth and the effects of heat on hormonal pathways, reactive oxygen species, and epigenetic regulation. We also highlight recent approaches and strategies that could be integrated to confront the challenges in sustaining crop productivity in future decades.

High-Throughput Root Imaging Analysis Reveals Wide Variation in Root Morphology of Wild Adzuki bean (Vigna angularis) Accessions

Root system architecture and morphological diversification in wild accessions are important for crop improvement and productivity in adzuki beans. In this study, via analysis using 2-dimensional (2D) root imaging and WinRHIZO Pro software, we described the root traits of 61 adzuki bean accessions in their early vegetative growth stage. These accessions were chosen for study because they are used in Korea’s crop improvement programs; however, their root traits have not been sufficiently investigated. Analysis of variance revealed a significant difference between the accessions of all measured root traits. Distribution analysis demonstrated that most of the root traits followed normal distribution. The accessions showed up to a 17-fold increase in the values in contrasting accessions for the root traits. For total root length (TRL), the values ranged from 82.43 to 1435 cm, and for surface area (SA), they ranged from 12.30 to 208.39 cm². The values for average diameter (AD) ranged from 0.23 to 0.56 mm. Significant differences were observed for other traits. Overall, the results showed that the accession IT 305544 had the highest TRL, SA, and number of tips (NT), whereas IT 262477 and IT 262492 showed the lowest values for TRL, SA, and AD. Principal component analysis showed an 89% variance for PC1 and PC2. K-mean clustering explained 77.4% of the variance in the data and grouped the accessions into three clusters. All six root traits had greater coefficients of variation (≥15%) among the tested accessions. Furthermore, to determine which root traits best distinguished different accessions, the correlation within our set of accessions provided trait-based ranking depending on their contribution. The identified accessions may be advantageous for the development of new crossing combinations to improve root features in adzuki beans during the early growth stage. The root traits assessed in this study could be attributes for future adzuki bean crop selection and improvement.

Dissecting the Root Phenotypic and Genotypic Variability of the Iowa Mung Bean Diversity Panel

Mung bean [Vigna radiata (L.) Wilczek] is a drought-tolerant, short-duration crop, and a rich source of protein and other valuable minerals, vitamins, and antioxidants. The main objectives of this research were (1) to study the root traits related with the phenotypic and genetic diversity of 375 mung bean genotypes of the Iowa (IA) diversity panel and (2) to conduct genome-wide association studies of root-related traits using the Automated Root Image Analysis (ARIA) software. We collected over 9,000 digital images at three-time points (days 12, 15, and 18 after germination). A broad sense heritability for days 15 (0.22-0.73) and 18 (0.23-0.87) was higher than that for day 12 (0.24-0.51). We also reported root ideotype classification, i.e., PI425425 (India), PI425045 (Philippines), PI425551 (Korea), PI264686 (Philippines), and PI425085 (Sri Lanka) that emerged as the top five in the topsoil foraging category, while PI425594 (unknown origin), PI425599 (Thailand), PI425610 (Afghanistan), PI425485 (India), and AVMU0201 (Taiwan) were top five in the drought-tolerant and nutrient uptake "steep, cheap, and deep" ideotype. We identified promising genotypes that can help diversify the gene pool of mung bean breeding stocks and will be useful for further field testing. Using association studies, we identified markers showing significant associations with the lateral root angle (LRA) on chromosomes 2, 6, 7, and 11, length distribution (LED) on chromosome 8, and total root length-growth rate (TRL_GR), volume (VOL), and total dry weight (TDW) on chromosomes 3 and 5. We discussed genes that are potential candidates from these regions. We reported beta-galactosidase 3 associated with the LRA, which has previously been implicated in the adventitious root development via transcriptomic studies in mung bean. Results from this work on the phenotypic characterization, root-based ideotype categories, and significant molecular markers associated with important traits will be useful for the marker-assisted selection and mung bean improvement through breeding.

New approaches to improve crop tolerance to biotic and abiotic stresses

During the last years, a great effort has been dedicated at the development and employment of diverse approaches for achieving more stress-tolerant and climate-flexible crops and sustainable yield increases to meet the food and energy demands of the future. The ongoing climate change is in fact leading to more frequent extreme events with a negative impact on food production, such as increased temperatures, drought, and soil salinization as well as invasive arthropod pests and diseases. In this review, diverse "green strategies" (e.g., chemical priming, root-associated microorganisms), and advanced technologies (e.g., genome editing, high-throughput phenotyping) are described on the basis of the most recent research evidence. Particularly, attention has been focused on the potential use in a context of sustainable and climate-smart agriculture (the so called "next agriculture generation") to improve plant tolerance and resilience to abiotic and biotic stresses. In addition, the gap between the results obtained in controlled experiments and those from application of these technologies in real field conditions (lab to field step) is also discussed.

Root plasticity under abiotic stress

Abiotic stresses increasingly threaten existing ecological and agricultural systems across the globe. Plant roots perceive these stresses in the soil and adapt their architecture accordingly. This review provides insights into recent discoveries showing the importance of root system architecture (RSA) and plasticity for the survival and development of plants under heat, cold, drought, salt, and flooding stress. In addition, we review the molecular regulation and hormonal pathways involved in controlling RSA plasticity, main root growth, branching and lateral root growth, root hair development, and formation of adventitious roots. Several stresses affect root anatomy by causing aerenchyma formation, lignin and suberin deposition, and Casparian strip modulation. Roots can also actively grow toward favorable soil conditions and avoid environments detrimental to their development. Recent advances in understanding the cellular mechanisms behind these different root tropisms are discussed. Understanding root plasticity will be instrumental for the development of crops that are resilient in the face of abiotic stress.

Visualizing the Hidden Half: Plant-Microbe Interactions in the Rhizosphere

Plant roots and the associated rhizosphere constitute a dynamic environment that fosters numerous intra- and interkingdom interactions, including metabolite exchange between plants and soil mediated by root exudates and the rhizosphere microbiome. These interactions affect plant fitness and performance, soil health, and the belowground carbon budget. Exploring and understanding the molecular mechanisms governing ecosystem responses via rhizosphere interactions allow the rational and sustainable design of future ecosystems. However, visualizing the plant root system architecture with spatially resolved root exudate and microbiome profiles along the root in its native state remains an ambitious grand challenge in rhizosphere biology. To address this challenge, we developed a three-dimensional (3D) root cartography platform to accurately visualize molecular and microbial constituents and their interactions in the root-rhizosphere zone.

DIRT/3D: 3D root phenotyping for field-grown maize (Zea mays)

The development of crops with deeper roots holds substantial promise to mitigate the consequences of climate change. Deeper roots are an essential factor to improve water uptake as a way to enhance crop resilience to drought, to increase nitrogen capture, to reduce fertilizer inputs, and to increase carbon sequestration from the atmosphere to improve soil organic fertility. A major bottleneck to achieving these improvements is high-throughput phenotyping to quantify root phenotypes of field-grown roots. We address this bottleneck with Digital Imaging of Root Traits (DIRT)/3D, an image-based 3D root phenotyping platform, which measures 18 architecture traits from mature field-grown maize (Zea mays) root crowns (RCs) excavated with the Shovelomics technique. DIRT/3D reliably computed all 18 traits, including distance between whorls and the number, angles, and diameters of nodal roots, on a test panel of 12 contrasting maize genotypes. The computed results were validated through comparison with manual measurements. Overall, we observed a coefficient of determination of r2>0.84 and a high broad-sense heritability of Hmean2> 0.6 for all but one trait. The average values of the 18 traits and a developed descriptor to characterize complete root architecture distinguished all genotypes. DIRT/3D is a step toward automated quantification of highly occluded maize RCs. Therefore, DIRT/3D supports breeders and root biologists in improving carbon sequestration and food security in the face of the adverse effects of climate change.

Complete root specimen of plants grown in soil-filled root box: sampling, measuring, and staining method

BACKGROUND

Detailed datasets containing root system and its architecture in soil are required to improve understanding of resource capture by roots. However, most of the root study methods have paid little attention to make and preserve whole root specimens. This study introduces root system sampling equipment that makes the entire root specimen with minimum impairment and without displacement of the spatial arrangement of the root system in root boxes. The objectives are to assess: whether the equipment can rapidly sample the entire root system; whether root surface area is measurable from a scanned digital image of the root specimen; and whether staining of the entire root specimens would provide multidimensional visual information on the interaction between soil and physiological function of root system architecture (RSA). For validation, we examined the root response of two soybean cultivars to arbuscular mycorrhizal (AM) inoculation and the effect of waterlogging stress on the physiological activity of buckwheat RSA.

RESULTS

The root boxes allowed soybean and buckwheat plants to grow uniformly across the replications. Both species showed significant differences between cultivars and/or among treatments in shoot and root traits. The equipment enabled to sample the whole-root specimens of soybean and buckwheat, where the tips of the fine roots were alive (diameter < 0.2 mm). Also, the whole root specimens of soybean were made in about 7 min. The root surface area calculated from the scanned soybean specimens showed a significant correlation with that calculated from the roots spread out in water (a common method). Staining of the soybean root specimens enabled us to observe the localized root proliferation induced by AM colonization. Moreover, staining of the buckwheat root specimens made it possible to examine the respiratory activity of each root at different depths.

CONCLUSIONS

The present method realized: fast and accurate production of the whole root specimen and precise calculation of the specimens' root surface area. Moreover, staining of the root specimens enabled analyzing the interaction between soil and physiological function of RSA. The evaluation of root traits, using our methods, will contribute to developing agronomic management and breeding program for sustainable food production.

Genome-wide association screening and verification of potential genes associated with root architectural traits in maize (Zea mays L.) at multiple seedling stages

Background

Breeding for new maize varieties with propitious root systems has tremendous potential in improving water and nutrients use efficiency and plant adaptation under suboptimal conditions. To date, most of the previously detected root-related trait genes in maize were new without functional verification. In this study, seven seedling root architectural traits were examined at three developmental stages in a recombinant inbred line population (RIL) of 179 RILs and a genome-wide association study (GWAS) panel of 80 elite inbred maize lines through quantitative trait loci (QTL) mapping and genome-wide association study.

Results

Using inclusive composite interval mapping, 8 QTLs accounting for 6.44–8.83 % of the phenotypic variation in root traits, were detected on chromosomes 1 (qRDW_v3-1-1 and qRDW/SDW_v3-1-1), 2 (qRBN_v1-2-1), 4 (qSUA_v1-4-1, qSUA_v2-4-1, and qROV_v2-4-1), and 10 (qTRL_v1-10-1, qRBN_v1-10-1). GWAS analysis involved three models (EMMAX, FarmCPU, and MLM) for a set of 1,490,007 high-quality single nucleotide polymorphisms (SNPs) obtained via whole genome next-generation sequencing (NGS). Overall, 53 significant SNPs with a phenotypic contribution rate ranging from 5.10 to 30.2 % and spread all over the ten maize chromosomes exhibited associations with the seven root traits. 17 SNPs were repeatedly detected from at least two growth stages, with several SNPs associated with multiple traits stably identified at all evaluated stages. Within the average linkage disequilibrium (LD) distance of 5.2 kb for the significant SNPs, 46 candidate genes harboring substantial SNPs were identified. Five potential genes viz. Zm00001d038676, Zm00001d015379, Zm00001d018496, Zm00001d050783, and Zm00001d017751 were verified for expression levels using maize accessions with extreme root branching differences from the GWAS panel and the RIL population. The results showed significantly (P < 0.001) different expression levels between the outer materials in both panels and at all considered growth stages.

Conclusions

This study provides a key reference for uncovering the complex genetic mechanism of root development and genetic enhancement of maize root system architecture, thus supporting the breeding of high-yielding maize varieties with propitious root systems.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07874-x.

Nature and Nurture: Genotype-Dependent Differential Responses of Root Architecture to Agar and Soil Environments

Root development is crucial for plant growth and therefore a key factor in plant performance and food production. Arabidopsis thaliana is the most commonly used system to study root system architecture (RSA). Growing plants on agar-based media has always been routine practice, but this approach poorly reflects the natural situation, which fact in recent years has led to a dramatic shift toward studying RSA in soil. Here, we directly compare RSA responses to agar-based medium (plates) and potting soil (rhizotrons) for a set of redundant loss-of-function plethora (plt) CRISPR mutants with variable degrees of secondary root defects. We demonstrate that plt3plt7 and plt3plt5plt7 plants, which produce only a handful of emerged secondary roots, can be distinguished from other genotypes based on both RSA shape and individual traits on plates and rhizotrons. However, in rhizotrons the secondary root density and the total contribution of the side root system to the RSA is increased in these two mutants, effectively rendering their phenotypes less distinct compared to WT. On the other hand, plt3, plt3plt5, and plt5plt7 mutants showed an opposite effect by having reduced secondary root density in rhizotrons. This leads us to believe that plate versus rhizotron responses are genotype dependent, and these differential responses were also observed in unrelated mutants short-root and scarecrow. Our study demonstrates that the type of growth system affects the RSA differently across genotypes, hence the optimal choice of growth conditions to analyze RSA phenotype is not predetermined.

Root developmental responses to phosphorus nutrition

Phosphorus is an essential macronutrient for plant growth and development. Root system architecture (RSA) affects a plant's ability to obtain phosphate, the major form of phosphorus that plants uptake. In this review, I first consider the relationship between RSA and plant phosphorus-acquisition efficiency, describe how external phosphorus conditions both induce and impose changes in the RSA of major crops and of the model plant Arabidopsis, and discuss whether shoot phosphorus status affects RSA and whether there is a universal root developmental response across all plant species. I then summarize the current understanding of the molecular mechanisms governing root developmental responses to phosphorus deficiency. I also explore the possible reasons for the inconsistent results reported by different research groups and comment on the relevance of some studies performed under laboratory conditions to what occurs in natural environments.

Root-omics for drought tolerance in cool-season grain legumes

Root traits can be exploited to increase the physiological efficiency of crop water use under drought. Root length, root hairs, root branching, root diameter, and root proliferation rate are genetically defined traits that can help to improve the water productivity potential of crops. Recently, high-throughput phenotyping techniques/platforms have been used to screen the germplasm of major cool-season grain legumes for root traits and their impact on different physiological processes, including nutrient uptake and yield potential. Advances in omics approaches have led to the dissection of genomic, proteomic, and metabolomic structures of these traits. This knowledge facilitates breeders to improve the water productivity and nutrient uptake of cultivars under limited soil moisture conditions in major cool-season grain legumes that usually face terminal drought. This review discusses the advances in root traits and their potential for developing drought-tolerant cultivars in cool-season grain legumes.

A multiple ion-uptake phenotyping platform reveals shared mechanisms affecting nutrient uptake by roots

Nutrient uptake is critical for crop growth and is determined by root foraging in soil. Growth and branching of roots lead to effective root placement to acquire nutrients, but relatively little is known about absorption of nutrients at the root surface from the soil solution. This knowledge gap could be alleviated by understanding sources of genetic variation for short-term nutrient uptake on a root length basis. A modular platform called RhizoFlux was developed for high-throughput phenotyping of multiple ion-uptake rates in maize (Zea mays L.). Using this system, uptake rates were characterized for the crop macronutrients nitrate, ammonium, potassium, phosphate, and sulfate among the Nested Association Mapping (NAM) population founder lines. The data revealed substantial genetic variation for multiple ion-uptake rates in maize. Interestingly, specific nutrient uptake rates (nutrient uptake rate per length of root) were found to be both heritable and distinct from total uptake and plant size. The specific uptake rates of each nutrient were positively correlated with one another and with specific root respiration (root respiration rate per length of root), indicating that uptake is governed by shared mechanisms. We selected maize lines with high and low specific uptake rates and performed an RNA-seq analysis, which identified key regulatory components involved in nutrient uptake. The high-throughput multiple ion-uptake kinetics pipeline will help further our understanding of nutrient uptake, parameterize holistic plant models, and identify breeding targets for crops with more efficient nutrient acquisition.

Specialized Plant Growth Chamber Designs to Study Complex Rhizosphere Interactions

The rhizosphere is a dynamic ecosystem shaped by complex interactions between plant roots, soil, microbial communities and other micro- and macro-fauna. Although studied for decades, critical gaps exist in the study of plant roots, the rhizosphere microbiome and the soil system surrounding roots, partly due to the challenges associated with measuring and parsing these spatiotemporal interactions in complex heterogeneous systems such as soil. To overcome the challenges associated with in situ study of rhizosphere interactions, specialized plant growth chamber systems have been developed that mimic the natural growth environment. This review discusses the currently available lab-based systems ranging from widely known rhizotrons to other emerging devices designed to allow continuous monitoring and non-destructive sampling of the rhizosphere ecosystems in real-time throughout the developmental stages of a plant. We categorize them based on the major rhizosphere processes it addresses and identify their unique challenges as well as advantages. We find that while some design elements are shared among different systems (e.g., size exclusion membranes), most of the systems are bespoke and speaks to the intricacies and specialization involved in unraveling the details of rhizosphere processes. We also discuss what we describe as the next generation of growth chamber employing the latest technology as well as the current barriers they face. We conclude with a perspective on the current knowledge gaps in the rhizosphere which can be filled by innovative chamber designs.

Characterization of CYCLOPHILLIN38 shows that a photosynthesis-derived systemic signal controls lateral root emergence

Photosynthesis in leaves generates fixed-carbon resources and essential metabolites that support sink tissues, such as roots. Two of these metabolites, sucrose and auxin, promote growth in root systems, but the explicit connection between photosynthetic activity and control of root architecture has not been explored. Through a mutant screen to identify pathways regulating root system architecture, we identified a mutation in the Arabidopsis thaliana CYCLOPHILIN 38 (CYP38) gene, which causes accumulation of pre-emergent stage lateral roots. CYP38 was previously reported to stabilize photosystem II (PSII) in chloroplasts. CYP38 expression is enriched in shoots, and grafting experiments show that the gene acts non-cell-autonomously to promote lateral root emergence. Growth of wild-type plants under low-light conditions phenocopies the cyp38 lateral root emergence defect, as does the inhibition of PSII-dependent electron transport or Nicotinamide adenine dinucleotide phosphate (NADPH) production. Importantly, these perturbations to photosynthetic activity rapidly suppress lateral root emergence, which is separate from their effects on shoot size. Supplementary exogenous sucrose largely rescued primary root (PR) growth in cyp38, but not lateral root growth. Auxin (indole-3-acetic acid (IAA)) biosynthesis from tryptophan is dependent on reductant generated during photosynthesis. Consistently, we found that wild-type seedlings grown under low light and cyp38 mutants have highly diminished levels of IAA in root tissues. IAA treatment rescued the cyp38 lateral root defect, revealing that photosynthesis promotes lateral root emergence partly through IAA biosynthesis. These data directly confirm the importance of CYP38-dependent photosynthetic activity in supporting root growth, and define the specific contributions of two metabolites in refining root architecture under light-limited conditions.

Cell kinetics of auxin transport and activity in Arabidopsis root growth and skewing

Auxin is a key regulator of plant growth and development. Local auxin biosynthesis and intercellular transport generates regional gradients in the root that are instructive for processes such as specification of developmental zones that maintain root growth and tropic responses. Here we present a toolbox to study auxin-mediated root development that features: (i) the ability to control auxin synthesis with high spatio-temporal resolution and (ii) single-cell nucleus tracking and morphokinetic analysis infrastructure. Integration of these two features enables cutting-edge analysis of root development at single-cell resolution based on morphokinetic parameters under normal growth conditions and during cell-type-specific induction of auxin biosynthesis. We show directional auxin flow in the root and refine the contributions of key players in this process. In addition, we determine the quantitative kinetics of Arabidopsis root meristem skewing, which depends on local auxin gradients but does not require PIN2 and AUX1 auxin transporter activities. Beyond the mechanistic insights into root development, the tools developed here will enable biologists to study kinetics and morphology of various critical processes at the single cell-level in whole organisms.