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

Automating measurements of fluorescent signals in freely moving plant leaf specimens

Existing methods to quantify fluorescent signals are primarily limited to non-moving objects or tracking a limited number of cells. These techniques, however, are unsuitable for measuring fluorescent signals in time-lapse experiments using plant specimens that move naturally during a course of imaging. We developed an automated method to measure fluorescent signal intensities in transgenic Arabidopsis plants using a stereomicroscope with standard microscopy software. The features of our technique include: 1) recognizing the shape of plant specimens using autofluorescent signals; 2) merging targeted fluorescent signals to specimen outlines; 3) extracting signals within the shape of specimens from their background signals. Our method facilitates the measurement of fluorescent signals on freely moving plant leaves that are physically unrestrained. The method we developed addresses the challenge of recognizing plant shapes without relying on: a) manual definition which is prone to subjectivity and human error; b) introducing stable fluorescent markers to define plant shapes; c) recognizing plant shapes from bright field images which include a wide range of colors and background noise; d) unnecessarily stressing plants by immobilizing them; e) the use of multiple software packages or software development expertise.

HY5 Contributes to Light-Regulated Root System Architecture Under a Root-Covered Culture System

Light is essential for plant organogenesis and development. Light-regulated shoot morphogenesis has been extensively studied; however, the mechanisms by which plant roots perceive and respond to aboveground light are largely unknown, particularly because the roots of most terrestrial plants are usually located underground in darkness. To mimic natural root growth conditions, we developed a root-covered system (RCS) in which the shoots were illuminated and the plant roots could be either exposed to light or cultivated in darkness. Using the RCS, we observed that root growth of wild-type plants was significantly promoted when the roots were in darkness, whereas it was inhibited by direct light exposure. This growth change seems to be regulated by ELONGATED HYPOCOTYL 5 (HY5), a master regulator of photomorphogenesis. Light was found to regulate HY5 expression in the roots, while a HY5 deficiency partially abolished the inhibition of growth in roots directly exposed to light, suggesting that HY5 expression is induced by direct light exposure and inhibits root growth. However, no differences in HY5 expression were observed between illuminated and dark-grown cop1 roots, indicating that HY5 may be regulated by COP1-mediated proteasome degradation. We confirmed the crucial role of HY5 in regulating root development in response to light under soil-grown conditions. A transcriptomic analysis revealed that light controls the expression of numerous genes involved in phytohormone signaling, stress adaptation, and metabolic processes in a HY5-dependent manner. In combination with the results of the flavonol quantification and exogenous quercetin application, these findings suggested that HY5 regulates the root response to light through a complex network that integrates flavonol biosynthesis and reactive oxygen species signaling. Collectively, our results indicate that HY5 is a master regulator of root photomorphogenesis.

The Quantitative Genetic Control of Root Architecture in Maize

Roots remain an underexplored frontier in plant genetics despite their well-known influence on plant development, agricultural performance and competition in the wild. Visualizing and measuring root structures and their growth is vastly more difficult than characterizing aboveground parts of the plant and is often simply avoided. The majority of research on maize root systems has focused on their anatomy, physiology, development and soil interaction, but much less is known about the genetics that control quantitative traits. In maize, seven root development genes have been cloned using mutagenesis, but no genes underlying the many root-related quantitative trait loci (QTLs) have been identified. In this review, we discuss whether the maize mutants known to control root development may also influence quantitative aspects of root architecture, including the extent to which they overlap with the most recent maize root trait QTLs. We highlight specific challenges and anticipate the impacts that emerging technologies, especially computational approaches, may have toward the identification of genes controlling root quantitative traits.

Transcriptome analysis reveals interplay between hormones, ROS metabolism and cell wall biosynthesis for drought-induced root growth in wheat

The ability of roots to grow under drought stress is an adaptive trait for crop plants especially under rain fed and restricted irrigation regime. To unravel the molecular mechanism of drought induced-root growth, root transcriptomes of two wheat genotypes viz. Raj3765 and HD2329, with contrasting root growth under drought stress were analyzed. Drought stress significantly enhanced total root length in Raj3765 as compared to that of HD2329. RNA-seq analysis led to the identification of 2783 and 2638 differentially expressed genes (DEGs) in Raj3765 and HD2329, respectively, under drought stress as compared with non-stress conditions. Functional annotation, gene ontology and MapMan analysis of the DEGs revealed differential regulation of genes for pathways associated with root growth and stress tolerance. Drought stress significantly upregulated auxin receptor (AFB2) and ABA responsive transcription factors (MYB78, WRKY18 and GBF3) in roots of Raj3765. Although certain genes for ethylene pathway were downregulated in both the genotypes, ACC oxidase and 2OG-Fe(II) oxygenase were upregulated only in Raj3765 which might contribute to maintenance of a basal ethylene level to maintain root growth. Several genes related to cell wall biosynthesis and ROS metabolism were significantly upregulated in Raj3765. Genes related to gibberellic acid, jasmonic acid and phenylpropanoid pathways were downregulated in roots of both the genotypes under drought stress. Our analysis suggests that a coordinated yet complex interplay between hormones, cellular tolerance, cell wall synthesis and ROS metabolism are required for drought induced root growth in wheat.

Adaptation to Phosphate Scarcity: Tips from Arabidopsis Roots

Phosphorus (P) availability is a limiting factor for plant growth and development. Root tip contact with low Pi media triggers diverse changes in the root architecture of Arabidopsis thaliana. The most conspicuous among these modifications is the inhibition of root growth, which is triggered by a shift from an indeterminate to a determinate root growth program. This phenomenon takes place in the root tip and involves a reduction in cell elongation, a decrease in cell proliferation, and the induction of premature cell differentiation, resulting in meristem exhaustion. Here, we review recent findings in the root response of A. thaliana to low Pi availability and discuss the cellular and genetic basis of the inhibition of root growth in Pi-deprived seedlings.

Need for Laboratory Ecosystems To Unravel the Structures and Functions of Soil Microbial Communities Mediated by Chemistry

The chemistry underpinning microbial interactions provides an integrative framework for linking the activities of individual microbes, microbial communities, plants, and their environments. Currently, we know very little about the functions of genes and metabolites within these communities because genome annotations and functions are derived from the minority of microbes that have been propagated in the laboratory. Yet the diversity, complexity, inaccessibility, and irreproducibility of native microbial consortia limit our ability to interpret chemical signaling and map metabolic networks. In this perspective, we contend that standardized laboratory ecosystems are needed to dissect the chemistry of soil microbiomes. We argue that dissemination and application of standardized laboratory ecosystems will be transformative for the field, much like how model organisms have played critical roles in advancing biochemistry and molecular and cellular biology. Community consensus on fabricated ecosystems ("EcoFABs") along with protocols and data standards will integrate efforts and enable rapid improvements in our understanding of the biochemical ecology of microbial communities.

Listening to earthworms burrowing and roots growing - acoustic signatures of soil biological activity

We report observations of acoustic emissions (AE) from growing plant roots and burrowing earthworms in soil, as a noninvasive method for monitoring biophysical processes that modify soil structure. AE emanating from earthworm and plants root activity were linked with time-lapse imaging in glass cells. Acoustic waveguides where installed in soil columns to monitor root growth in real time (mimicking field application). The cumulative AE events were in correlation with earthworm burrow lengths and with root growth. The number of AE events recorded from the soil columns with growing maize roots were several orders of magnitude larger than AE emanating from bare soil under similar conditions. The results suggest that AE monitoring may offer a window into largely unobservable dynamics of soil biomechanical processes such as root growth or patterns of earthworm activity - both important soil structure forming processes.

RhizoChamber-Monitor: a robotic platform and software enabling characterization of root growth

BACKGROUND

In order to efficiently determine genotypic differences in rooting patterns of crops, novel hardware and software are needed simultaneously to characterize dynamics of root development.

RESULTS

We describe a prototype robotic monitoring platform-the RhizoChamber-Monitor for analyzing growth patterns of plant roots automatically. The RhizoChamber-Monitor comprises an automatic imaging system for acquiring sequential images of roots which grow on a cloth substrate in custom rhizoboxes, an automatic irrigation system and a flexible shading arrangement. A customized image processing software was developed to analyze the spatio-temporal dynamics of root growth from time-course images of multiple plants. This software can quantify overall growth of roots and extract detailed growth traits (e.g. dynamics of length and diameter) of primary roots and of individual lateral roots automatically. It can also identify local growth traits of lateral roots (pseudo-mean-length and pseudo-maximum-length) semi-automatically. Two cotton genotypes were used to test both the physical platform and the analysis software.

CONCLUSIONS

The combination of hardware and software is expected to facilitate quantification of root geometry and its spatio-temporal growth patterns, and therefore to provide opportunities for high-throughput root phenotyping in support of crop breeding to optimize root architecture.

Accelerating genetic gains in legumes for the development of prosperous smallholder agriculture: integrating genomics, phenotyping, systems modelling and agronomy

Grain legumes form an important component of the human diet, provide feed for livestock, and replenish soil fertility through biological nitrogen fixation. Globally, the demand for food legumes is increasing as they complement cereals in protein requirements and possess a high percentage of digestible protein. Climate change has enhanced the frequency and intensity of drought stress, posing serious production constraints, especially in rainfed regions where most legumes are produced. Genetic improvement of legumes, like other crops, is mostly based on pedigree and performance-based selection over the past half century. To achieve faster genetic gains in legumes in rainfed conditions, this review proposes the integration of modern genomics approaches, high throughput phenomics, and simulation modelling in support of crop improvement that leads to improved varieties that perform with appropriate agronomy. Selection intensity, generation interval, and improved operational efficiencies in breeding are expected to further enhance the genetic gain in experimental plots. Improved seed access to farmers, combined with appropriate agronomic packages in farmers' fields, will deliver higher genetic gains. Enhanced genetic gains, including not only productivity but also nutritional and market traits, will increase the profitability of farming and the availability of affordable nutritious food especially in developing countries.

Improving nitrogen use efficiency in plants: effective phenotyping in conjunction with agronomic and genetic approaches

For global sustainable food production and environmental benefits, there is an urgent need to improve N use efficiency (NUE) in crop plants. Excessive and inefficient use of N fertiliser results in increased crop production costs and environmental pollution. Therefore, cost-effective strategies such as proper management of the timing and quantity of N fertiliser application, and breeding for better varieties are needed to improve NUE in crops. However, for these efforts to be feasible, high-throughput and reliable phenotyping techniques would be very useful for monitoring N status in planta, as well as to facilitate faster decisions during breeding and selection processes. This review provides an insight into contemporary approaches to phenotyping NUE-related traits and associated challenges. We discuss recent and advanced, sensor- and image-based phenotyping techniques that use a variety of equipment, tools and platforms. The review also elaborates on how high-throughput phenotyping will accelerate efforts for screening large populations of diverse genotypes in controlled environment and field conditions to identify novel genotypes with improved NUE.

Ecosystem Fabrication (EcoFAB) Protocols for The Construction of Laboratory Ecosystems Designed to Study Plant-microbe Interactions

Beneficial plant-microbe interactions offer a sustainable biological solution with the potential to boost low-input food and bioenergy production. A better mechanistic understanding of these complex plant-microbe interactions will be crucial to improving plant production as well as performing basic ecological studies investigating plant-soil-microbe interactions. Here, a detailed description for ecosystem fabrication is presented, using widely available 3D printing technologies, to create controlled laboratory habitats (EcoFABs) for mechanistic studies of plant-microbe interactions within specific environmental conditions. Two sizes of EcoFABs are described that are suited for the investigation of microbial interactions with various plant species, including Arabidopsis thaliana, Brachypodium distachyon, and Panicum virgatum. These flow-through devices allow for controlled manipulation and sampling of root microbiomes, root chemistry as well as imaging of root morphology and microbial localization. This protocol includes the details for maintaining sterile conditions inside EcoFABs and mounting independent LED light systems onto EcoFABs. Detailed methods for addition of different forms of media, including soils, sand, and liquid growth media coupled to the characterization of these systems using imaging and metabolomics are described. Together, these systems enable dynamic and detailed investigation of plant and plant-microbial consortia including the manipulation of microbiome composition (including mutants), the monitoring of plant growth, root morphology, exudate composition, and microbial localization under controlled environmental conditions. We anticipate that these detailed protocols will serve as an important starting point for other researchers, ideally helping create standardized experimental systems for investigating plant-microbe interactions.

Ecosystem Fabrication (EcoFAB) Protocols for The Construction of Laboratory Ecosystems Designed to Study Plant-microbe Interactions

Beneficial plant-microbe interactions offer a sustainable biological solution with the potential to boost low-input food and bioenergy production. A better mechanistic understanding of these complex plant-microbe interactions will be crucial to improving plant production as well as performing basic ecological studies investigating plant-soil-microbe interactions. Here, a detailed description for ecosystem fabrication is presented, using widely available 3D printing technologies, to create controlled laboratory habitats (EcoFABs) for mechanistic studies of plant-microbe interactions within specific environmental conditions. Two sizes of EcoFABs are described that are suited for the investigation of microbial interactions with various plant species, including Arabidopsis thaliana, Brachypodium distachyon, and Panicum virgatum. These flow-through devices allow for controlled manipulation and sampling of root microbiomes, root chemistry as well as imaging of root morphology and microbial localization. This protocol includes the details for maintaining sterile conditions inside EcoFABs and mounting independent LED light systems onto EcoFABs. Detailed methods for addition of different forms of media, including soils, sand, and liquid growth media coupled to the characterization of these systems using imaging and metabolomics are described. Together, these systems enable dynamic and detailed investigation of plant and plant-microbial consortia including the manipulation of microbiome composition (including mutants), the monitoring of plant growth, root morphology, exudate composition, and microbial localization under controlled environmental conditions. We anticipate that these detailed protocols will serve as an important starting point for other researchers, ideally helping create standardized experimental systems for investigating plant-microbe interactions.

Buffered delivery of phosphate to Arabidopsis alters responses to low phosphate

Arabidopsis has been reported to respond to phosphate (Pi) stress by arresting primary root growth and increasing lateral root branching. We developed a system to buffer Pi availability to Arabidopsis in gel media systems by charging activated aluminum oxide particles with low and sufficient concentrations of Pi, based on previous work in horticultural and sand culture systems. This system more closely mimics soil chemistry and results in different growth and transcriptional responses to Pi stress compared with plants grown in standard gel media. Low Pi availability in buffered medium results in reduced root branching and preferential investment of resources in axial root growth. Root hair length and density, known responses to Pi stress, increase in low-buffered Pi medium. Plants grown under buffered Pi conditions have different gene expression profiles of canonical Pi stress response genes as compared with their unbuffered counterparts. The system also eliminates known complications with iron (Fe) nutrition. The growth responses of Arabidopsis supplied with buffered Pi indicate that the widely accepted low-Pi phenotype is an artifact of the standard gel-based growth system. Buffering Pi availability through the method presented here will improve the utility and accuracy of gel studies by more closely approximating soil conditions.

Dual-flow-RootChip reveals local adaptations of roots towards environmental asymmetry at the physiological and genetic levels

Roots grow in highly dynamic and heterogeneous environments. Biological activity as well as uneven nutrient availability or localized stress factors result in diverse microenvironments. Plants adapt their root morphology in response to changing environmental conditions, yet it remains largely unknown to what extent developmental adaptations are based on systemic or cell-autonomous responses. We present the dual-flow-RootChip, a microfluidic platform for asymmetric perfusion of Arabidopsis roots to investigate root-environment interactions under simulated environmental heterogeneity. Applications range from investigating physiology, root hair development and calcium signalling upon selective exposure to environmental stresses to tracing molecular uptake, performing selective drug treatments and localized inoculations with microbes. Using the dual-flow-RootChip, we revealed cell-autonomous adaption of root hair development under asymmetric phosphate (Pi) perfusion, with unexpected repression in root hair growth on the side exposed to low Pi and rapid tip-growth upregulation when Pi concentrations increased. The asymmetric root environment further resulted in an asymmetric gene expression of RSL4, a key transcriptional regulator of root hair growth. Our findings demonstrate that roots possess the capability to locally adapt to heterogeneous conditions in their environment at the physiological and transcriptional levels. Being able to generate asymmetric microenvironments for roots will help further elucidate decision-making processes in root-environment interactions.

Breakout-lateral root emergence in Arabidopsis thaliana

Lateral roots are determinants of plant root system architecture. Besides providing anchorage, they are a plant's means to explore the soil environment for water and nutrients. Lateral roots form post-embryonically and initiate deep within the root. On its way to the surface, the newly formed organ needs to grow through three overlying cell layers; the endodermis, cortex and epidermis. A picture is emerging that a tight integration of chemical and mechanical signalling between the lateral root and the surrounding tissue is essential for proper organogenesis. Here we review the latest progress made towards our understanding of the fascinating biology underlying lateral root emergence in Arabidopsis.

Green light for quantitative live-cell imaging in plants

Plants exhibit an intriguing morphological and physiological plasticity that enables them to thrive in a wide range of environments. To understand the cell biological basis of this unparalleled competence, a number of methodologies have been adapted or developed over the last decades that allow minimal or non-invasive live-cell imaging in the context of tissues. Combined with the ease to generate transgenic reporter lines in specific genetic backgrounds or accessions, we are witnessing a blooming in plant cell biology. However, the imaging of plant cells entails a number of specific challenges, such as high levels of autofluorescence, light scattering that is caused by cell walls and their sensitivity to environmental conditions. Quantitative live-cell imaging in plants therefore requires adapting or developing imaging techniques, as well as mounting and incubation systems, such as micro-fluidics. Here, we discuss some of these obstacles, and review a number of selected state-of-the-art techniques, such as two-photon imaging, light sheet microscopy and variable angle epifluorescence microscopy that allow high performance and minimal invasive live-cell imaging in plants.

The Next Generation of Training for Arabidopsis Researchers: Bioinformatics and Quantitative Biology

Training for experimental plant biologists needs to combine bioinformatics, quantitative approaches, computational biology, and training in the art of collaboration, best achieved through fully integrated curriculum development.

Image-Based Analysis to Dissect Vertical Distribution and Horizontal Asymmetry of Conspecific Root System Interactions in Response to Planting Densities, Nutrients and Root Exudates in Arabidopsis thaliana

Intraspecific competition is an important plant interaction that has been studied extensively aboveground, but less so belowground, due to the difficulties in accessing the root system experimentally. Recent in vivo and in situ automatic imaging advances help understand root system architecture. In this study, a portable imaging platform and a scalable transplant technique were applied to test intraspecific competition in Arabidopsis thaliana. A single green fluorescent protein labeled plant was placed in the center of a grid of different planting densities of neighboring unlabeled plants or empty spaces, into which different treatments were made to the media. The root system of the central plant showed changes in the vertical distribution with increasing neighbor density, becoming more positively kurtotic, and developing an increasing negative skew with time. Horizontal root distribution was initially asymmetric, but became more evenly circular with time, and mean direction was not affected by the presence of adjacent empty spaces as initially hypothesized. To date, this is the first study to analyze the patterns of both vertical and horizontal growth in conspecific root systems. We present a portable imaging platform with simplicity, accessibility, and scalability, to capture the dynamic interactions of plant root systems.

Virtual Plants Need Water Too: Functional-Structural Root System Models in the Context of Drought Tolerance Breeding

Developing a sustainable agricultural model is one of the great challenges of the coming years. The agricultural practices inherited from the Green Revolution of the 1960s show their limits today, and new paradigms need to be explored to counter rising issues such as the multiplication of climate-change related drought episodes. Two such new paradigms are the use of functional-structural plant models to complement and rationalize breeding approaches and a renewed focus on root systems as untapped sources of plant amelioration. Since the late 1980s, numerous functional and structural models of root systems were developed and used to investigate the properties of root systems in soil or lab-conditions. In this review, we focus on the conception and use of such root models in the broader context of research on root-driven drought tolerance, on the basis of root system architecture (RSA) phenotyping. Such models result from the integration of architectural, physiological and environmental data. Here, we consider the different phenotyping techniques allowing for root architectural and physiological study and their limits. We discuss how QTL and breeding studies support the manipulation of RSA as a way to improve drought resistance. We then go over the integration of the generated data within architectural models, how those architectural models can be coupled with functional hydraulic models, and how functional parameters can be measured to feed those models. We then consider the assessment and validation of those hydraulic models through confrontation of simulations to experimentations. Finally, we discuss the up and coming challenges facing root systems functional-structural modeling approaches in the context of breeding.

Quantitatively Understanding Plant Signaling: Novel Theoretical-Experimental Approaches

With the need to respond to and integrate a multitude of external and internal stimuli, plant signaling is highly complex, exhibiting signaling component redundancy and high interconnectedness between individual pathways. We review here novel theoretical-experimental approaches in manipulating plant signaling towards the goal of a comprehensive understanding and targeted quantitative control of plant processes. We highlight approaches taken in the field of synthetic biology used in other systems and discuss their applicability in plants. Finally, we introduce existing tools for the quantitative analysis and monitoring of plant signaling and the integration of experimentally obtained quantitative data into mathematical models. Incorporating principles of synthetic biology into plant sciences more widely will lead this field forward in both fundamental and applied research.

Morphological Plant Modeling: Unleashing Geometric and Topological Potential within the Plant Sciences

The geometries and topologies of leaves, flowers, roots, shoots, and their arrangements have fascinated plant biologists and mathematicians alike. As such, plant morphology is inherently mathematical in that it describes plant form and architecture with geometrical and topological techniques. Gaining an understanding of how to modify plant morphology, through molecular biology and breeding, aided by a mathematical perspective, is critical to improving agriculture, and the monitoring of ecosystems is vital to modeling a future with fewer natural resources. In this white paper, we begin with an overview in quantifying the form of plants and mathematical models of patterning in plants. We then explore the fundamental challenges that remain unanswered concerning plant morphology, from the barriers preventing the prediction of phenotype from genotype to modeling the movement of leaves in air streams. We end with a discussion concerning the education of plant morphology synthesizing biological and mathematical approaches and ways to facilitate research advances through outreach, cross-disciplinary training, and open science. Unleashing the potential of geometric and topological approaches in the plant sciences promises to transform our understanding of both plants and mathematics.

New Strategies and Tools in Quantitative Genetics: How to Go from the Phenotype to the Genotype

Quantitative genetics has a long history in plants: It has been used to study specific biological processes, identify the factors important for trait evolution, and breed new crop varieties. These classical approaches to quantitative trait locus mapping have naturally improved with technology. In this review, we show how quantitative genetics has evolved recently in plants and how new developments in phenotyping, population generation, sequencing, gene manipulation, and statistics are rejuvenating both the classical linkage mapping approaches (for example, through nested association mapping) as well as the more recently developed genome-wide association studies. These strategies are complementary in most instances, and indeed, one is often used to confirm the results of the other. Despite significant advances, an emerging trend is that the outcome and efficiency of the different approaches depend greatly on the genetic architecture of the trait in the genetic material under study.

TNO1, a TGN-localized SNARE-interacting protein, modulates root skewing in Arabidopsis thaliana

BACKGROUND

The movement of plant roots within the soil is key to their ability to interact with the environment and maximize anchorage and nutrient acquisition. Directional growth of roots occurs by a combination of sensing external cues, hormonal signaling and cytoskeletal changes in the root cells. Roots growing on slanted, impenetrable growth medium display a characteristic waving and skewing, and mutants with deviations in these phenotypes assist in identifying genes required for root movement. Our study identifies a role for a trans-Golgi network-localized protein in root skewing.

RESULTS

We found that Arabidopsis thaliana TNO1 (TGN-localized SYP41-interacting protein), a putative tethering factor localized at the trans-Golgi network, affects root skewing. tno1 knockout mutants display enhanced root skewing and epidermal cell file rotation. Skewing of tno1 roots increases upon microtubule stabilization, but is insensitive to microtubule destabilization. Microtubule destabilization leads to severe defects in cell morphology in tno1 seedlings. Microtubule array orientation is unaffected in the mutant roots, suggesting that the increase in cell file rotation is independent of the orientation of microtubule arrays.

CONCLUSIONS

We conclude that TNO1 modulates root skewing in a mechanism that is dependent on microtubules but is not linked to disruption of the orientation of microtubule arrays. In addition, TNO1 is required for maintenance of cell morphology in mature regions of roots and the base of hypocotyls. The TGN-localized SNARE machinery might therefore be important for appropriate epidermal cell file rotation and cell expansion during root growth.

DRO1 influences root system architecture in Arabidopsis and Prunus species

Roots provide essential uptake of water and nutrients from the soil, as well as anchorage and stability for the whole plant. Root orientation, or angle, is an important component of the overall architecture and depth of the root system; however, little is known about the genetic control of this trait. Recent reports in Oryza sativa (rice) identified a role for DEEPER ROOTING 1 (DRO1) in influencing the orientation of the root system, leading to positive changes in grain yields under water-limited conditions. Here we found that DRO1 and DRO1-related genes are present across diverse plant phyla, and fall within the IGT gene family. The IGT family also includes TAC1 and LAZY1, which are known to affect the orientation of lateral shoots. Consistent with a potential role in root development, DRO1 homologs in Arabidopsis and peach showed root-specific expression. Promoter-reporter constructs revealed that AtDRO1 is predominantly expressed in both the root vasculature and root tips, in a distinct developmental pattern. Mutation of AtDRO1 led to more horizontal lateral root angles. Overexpression of AtDRO1 under a constitutive promoter resulted in steeper lateral root angles, as well as shoot phenotypes including upward leaf curling, shortened siliques and narrow lateral branch angles. A conserved C-terminal EAR-like motif found in IGT genes was required for these ectopic phenotypes. Overexpression of PpeDRO1 in Prunus domestica (plum) led to deeper-rooting phenotypes. Collectively, these data indicate a potential application for DRO1-related genes to alter root architecture for drought avoidance and improved resource use.

Reshaping Plant Biology: Qualitative and Quantitative Descriptors for Plant Morphology

An emerging challenge in plant biology is to develop qualitative and quantitative measures to describe the appearance of plants through the integration of mathematics and biology. A major hurdle in developing these metrics is finding common terminology across fields. In this review, we define approaches for analyzing plant geometry, topology, and shape, and provide examples for how these terms have been and can be applied to plants. In leaf morphological quantifications both geometry and shape have been used to gain insight into leaf function and evolution. For the analysis of cell growth and expansion, we highlight the utility of geometric descriptors for understanding sepal and hypocotyl development. For branched structures, we describe how topology has been applied to quantify root system architecture to lend insight into root function. Lastly, we discuss the importance of using morphological descriptors in ecology to assess how communities interact, function, and respond within different environments. This review aims to provide a basic description of the mathematical principles underlying morphological quantifications.

Evaluating physiological responses of plants to salinity stress

BACKGROUND

Because soil salinity is a major abiotic constraint affecting crop yield, much research has been conducted to develop plants with improved salinity tolerance. Salinity stress impacts many aspects of a plant's physiology, making it difficult to study in toto Instead, it is more tractable to dissect the plant's response into traits that are hypothesized to be involved in the overall tolerance of the plant to salinity.

SCOPE AND CONCLUSIONS

We discuss how to quantify the impact of salinity on different traits, such as relative growth rate, water relations, transpiration, transpiration use efficiency, ionic relations, photosynthesis, senescence, yield and yield components. We also suggest some guidelines to assist with the selection of appropriate experimental systems, imposition of salinity stress, and obtaining and analysing relevant physiological data using appropriate indices. We illustrate how these indices can be used to identify relationships amongst the proposed traits to identify which traits are the most important contributors to salinity tolerance. Salinity tolerance is complex and involves many genes, but progress has been made in studying the mechanisms underlying a plant's response to salinity. Nevertheless, several previous studies on salinity tolerance could have benefited from improved experimental design. We hope that this paper will provide pertinent information to researchers on performing proficient assays and interpreting results from salinity tolerance experiments.

Morphological Plant Modeling: Unleashing Geometric and Topological Potential within the Plant Sciences

The geometries and topologies of leaves, flowers, roots, shoots, and their arrangements have fascinated plant biologists and mathematicians alike. As such, plant morphology is inherently mathematical in that it describes plant form and architecture with geometrical and topological techniques. Gaining an understanding of how to modify plant morphology, through molecular biology and breeding, aided by a mathematical perspective, is critical to improving agriculture, and the monitoring of ecosystems is vital to modeling a future with fewer natural resources. In this white paper, we begin with an overview in quantifying the form of plants and mathematical models of patterning in plants. We then explore the fundamental challenges that remain unanswered concerning plant morphology, from the barriers preventing the prediction of phenotype from genotype to modeling the movement of leaves in air streams. We end with a discussion concerning the education of plant morphology synthesizing biological and mathematical approaches and ways to facilitate research advances through outreach, cross-disciplinary training, and open science. Unleashing the potential of geometric and topological approaches in the plant sciences promises to transform our understanding of both plants and mathematics.

Evaluating physiological responses of plants to salinity stress

BACKGROUND

Because soil salinity is a major abiotic constraint affecting crop yield, much research has been conducted to develop plants with improved salinity tolerance. Salinity stress impacts many aspects of a plant's physiology, making it difficult to study in toto Instead, it is more tractable to dissect the plant's response into traits that are hypothesized to be involved in the overall tolerance of the plant to salinity.

SCOPE AND CONCLUSIONS

We discuss how to quantify the impact of salinity on different traits, such as relative growth rate, water relations, transpiration, transpiration use efficiency, ionic relations, photosynthesis, senescence, yield and yield components. We also suggest some guidelines to assist with the selection of appropriate experimental systems, imposition of salinity stress, and obtaining and analysing relevant physiological data using appropriate indices. We illustrate how these indices can be used to identify relationships amongst the proposed traits to identify which traits are the most important contributors to salinity tolerance. Salinity tolerance is complex and involves many genes, but progress has been made in studying the mechanisms underlying a plant's response to salinity. Nevertheless, several previous studies on salinity tolerance could have benefited from improved experimental design. We hope that this paper will provide pertinent information to researchers on performing proficient assays and interpreting results from salinity tolerance experiments.

Setaria Comes of Age: Meeting Report on the Second International Setaria Genetics Conference

Setaria viridis is an emerging model for cereal and bioenergy grasses because of its short stature, rapid life cycle and expanding genetic and genomic toolkits. Its close phylogenetic relationship with economically important crops such as maize and sorghum positions Setaria as an ideal model system for accelerating discovery and characterization of crop genes that control agronomically important traits. The Second International Setaria Genetics Conference was held on March 6-8, 2017 at the Donald Danforth Plant Science Center, St. Louis, MO, United States to discuss recent technological breakthroughs and research directions in Setaria (presentation abstracts can be downloaded at https://www.brutnelllab.org/setaria). Here, we highlight topics presented in the conference including inflorescence architecture, C₄ photosynthesis and abiotic stress. Genetic and genomic toolsets including germplasm, mutant populations, transformation and gene editing technologies are also discussed. Since the last meeting in 2014, the Setaria community has matured greatly in the quality of research being conducted. Outreach and increased communication with maize and other plant communities will allow broader adoption of Setaria as a model system to translate fundamental discovery research to crop improvement.

Using a Structural Root System Model to Evaluate and Improve the Accuracy of Root Image Analysis Pipelines

Root system analysis is a complex task, often performed with fully automated image analysis pipelines. However, the outcome is rarely verified by ground-truth data, which might lead to underestimated biases. We have used a root model, ArchiSimple, to create a large and diverse library of ground-truth root system images (10,000). For each image, three levels of noise were created. This library was used to evaluate the accuracy and usefulness of several image descriptors classically used in root image analysis softwares. Our analysis highlighted that the accuracy of the different traits is strongly dependent on the quality of the images and the type, size, and complexity of the root systems analyzed. Our study also demonstrated that machine learning algorithms can be trained on a synthetic library to improve the estimation of several root system traits. Overall, our analysis is a call to caution when using automatic root image analysis tools. If a thorough calibration is not performed on the dataset of interest, unexpected errors might arise, especially for large and complex root images. To facilitate such calibration, both the image library and the different codes used in the study have been made available to the community.

Roots Withstanding their Environment: Exploiting Root System Architecture Responses to Abiotic Stress to Improve Crop Tolerance

To face future challenges in crop production dictated by global climate changes, breeders and plant researchers collaborate to develop productive crops that are able to withstand a wide range of biotic and abiotic stresses. However, crop selection is often focused on shoot performance alone, as observation of root properties is more complex and asks for artificial and extensive phenotyping platforms. In addition, most root research focuses on development, while a direct link to the functionality of plasticity in root development for tolerance is often lacking. In this paper we review the currently known root system architecture (RSA) responses in Arabidopsis and a number of crop species to a range of abiotic stresses, including nutrient limitation, drought, salinity, flooding, and extreme temperatures. For each of these stresses, the key molecular and cellular mechanisms underlying the RSA response are highlighted. To explore the relevance for crop selection, we especially review and discuss studies linking root architectural responses to stress tolerance. This will provide a first step toward understanding the relevance of adaptive root development for a plant's response to its environment. We suggest that functional evidence on the role of root plasticity will support breeders in their efforts to include root properties in their current selection pipeline for abiotic stress tolerance, aimed to improve the robustness of crops.

Plant developmental responses to climate change

Climate change is multi-faceted, and includes changing concentrations of greenhouse gases in the atmosphere, rising temperatures, changes in precipitation patterns, and increasing frequency of extreme weather events. Here, we focus on the effects of rising atmospheric CO₂ concentrations, rising temperature, and drought stress and their interaction on plant developmental processes in leaves, roots, and in reproductive structures. While in some cases these responses are conserved across species, such as decreased root elongation, perturbation of root growth angle and reduced seed yield in response to drought, or an increase in root biomass in shallow soil in response to elevated CO₂, most responses are variable within and between species and are dependent on developmental stage. These variable responses include species-specific thresholds that arrest development of reproductive structures, reduce root growth rate and the rate of leaf initiation and expansion in response to elevated temperature. Leaf developmental responses to elevated CO₂ vary by cell type and by species. Variability also exists between C₃ and C₄ species in response to elevated CO₂, especially in terms of growth and seed yield stimulation. At the molecular level, significantly less is understood regarding conservation and variability in molecular mechanisms underlying these traits. Abscisic acid-mediated changes in cell wall expansion likely underlie reductions in growth rate in response to drought, and changes in known regulators of flowering time likely underlie altered reproductive transitions in response to elevated temperature and CO₂. Genes that underlie most other organ or tissue-level responses have largely only been identified in a single species in response to a single stress and their level of conservation is unknown. We conclude that there is a need for further research regarding the molecular mechanisms of plant developmental responses to climate change factors in general, and that this lack of data is particularly prevalent in the case of interactive effects of multiple climate change factors. As future growing conditions will likely expose plants to multiple climate change factors simultaneously, with a sum negative influence on global agriculture, further research in this area is critical.

Grasses suppress shoot-borne roots to conserve water during drought

Many important crops are members of the Poaceae family, which develop root systems characterized by a high degree of root initiation from the belowground basal nodes of the shoot, termed the crown. Although this postembryonic shoot-borne root system represents the major conduit for water uptake, little is known about the effect of water availability on its development. Here we demonstrate that in the model C4 grass Setaria viridis, the crown locally senses water availability and suppresses postemergence crown root growth under a water deficit. This response was observed in field and growth room environments and in all grass species tested. Luminescence-based imaging of root systems grown in soil-like media revealed a shift in root growth from crown-derived to primary root-derived branches, suggesting that primary root-dominated architecture can be induced in S. viridis under certain stress conditions. Crown roots of Zea mays and Setaria italica, domesticated relatives of teosinte and S. viridis, respectively, show reduced sensitivity to water deficit, suggesting that this response might have been influenced by human selection. Enhanced water status of maize mutants lacking crown roots suggests that under a water deficit, stronger suppression of crown roots actually may benefit crop productivity.

Growing Out of Stress: The Role of Cell- and Organ-Scale Growth Control in Plant Water-Stress Responses

Water is the most limiting resource on land for plant growth, and its uptake by plants is affected by many abiotic stresses, such as salinity, cold, heat, and drought. While much research has focused on exploring the molecular mechanisms underlying the cellular signaling events governing water-stress responses, it is also important to consider the role organismal structure plays as a context for such responses. The regulation of growth in plants occurs at two spatial scales: the cell and the organ. In this review, we focus on how the regulation of growth at these different spatial scales enables plants to acclimate to water-deficit stress. The cell wall is discussed with respect to how the physical properties of this structure affect water loss and how regulatory mechanisms that affect wall extensibility maintain growth under water deficit. At a higher spatial scale, the architecture of the root system represents a highly dynamic physical network that facilitates access of the plant to a heterogeneous distribution of water in soil. We discuss the role differential growth plays in shaping the structure of this system and the physiological implications of such changes.

Grasses suppress shoot-borne roots to conserve water during drought

Many important crops are members of the Poaceae family, which develop root systems characterized by a high degree of root initiation from the belowground basal nodes of the shoot, termed the crown. Although this postembryonic shoot-borne root system represents the major conduit for water uptake, little is known about the effect of water availability on its development. Here we demonstrate that in the model C4 grass Setaria viridis, the crown locally senses water availability and suppresses postemergence crown root growth under a water deficit. This response was observed in field and growth room environments and in all grass species tested. Luminescence-based imaging of root systems grown in soil-like media revealed a shift in root growth from crown-derived to primary root-derived branches, suggesting that primary root-dominated architecture can be induced in S. viridis under certain stress conditions. Crown roots of Zea mays and Setaria italica, domesticated relatives of teosinte and S. viridis, respectively, show reduced sensitivity to water deficit, suggesting that this response might have been influenced by human selection. Enhanced water status of maize mutants lacking crown roots suggests that under a water deficit, stronger suppression of crown roots actually may benefit crop productivity.

Nitrate Transport, Sensing, and Responses in Plants

Nitrogen (N) is an essential macronutrient that affects plant growth and development. N is an important component of chlorophyll, amino acids, nucleic acids, and secondary metabolites. Nitrate is one of the most abundant N sources in the soil. Because nitrate and other N nutrients are often limiting, plants have developed sophisticated mechanisms to ensure adequate supply of nutrients in a variable environment. Nitrate is absorbed in the root and mobilized to other organs by nitrate transporters. Nitrate sensing activates signaling pathways that impinge upon molecular, metabolic, physiological, and developmental responses locally and at the whole plant level. With the advent of genomics technologies and genetic tools, important advances in our understanding of nitrate and other N nutrient responses have been achieved in the past decade. Furthermore, techniques that take advantage of natural polymorphisms present in divergent individuals from a single species have been essential in uncovering new components. However, there are still gaps in our understanding of how nitrate signaling affects biological processes in plants. Moreover, we still lack an integrated view of how all the regulatory factors identified interact or crosstalk to orchestrate the myriad N responses plants typically exhibit. In this review, we provide an updated overview of mechanisms by which nitrate is sensed and transported throughout the plant. We discuss signaling components and how nitrate sensing crosstalks with hormonal pathways for developmental responses locally and globally in the plant. Understanding how nitrate impacts on plant metabolism, physiology, and growth and development in plants is key to improving crops for sustainable agriculture.

The holistic rhizosphere: integrating zones, processes, and semantics in the soil influenced by roots

Despite often being conceptualized as a thin layer of soil around roots, the rhizosphere is actually a dynamic system of interacting processes. Hiltner originally defined the rhizosphere as the soil influenced by plant roots. However, soil physicists, chemists, microbiologists, and plant physiologists have studied the rhizosphere independently, and therefore conceptualized the rhizosphere in different ways and using contrasting terminology. Rather than research-specific conceptions of the rhizosphere, the authors propose a holistic rhizosphere encapsulating the following components: microbial community gradients, macroorganisms, mucigel, volumes of soil structure modification, and depletion or accumulation zones of nutrients, water, root exudates, volatiles, and gases. These rhizosphere components are the result of dynamic processes and understanding the integration of these processes will be necessary for future contributions to rhizosphere science based upon interdisciplinary collaborations. In this review, current knowledge of the rhizosphere is synthesized using this holistic perspective with a focus on integrating traditionally separated rhizosphere studies. The temporal dynamics of rhizosphere activities will also be considered, from annual fine root turnover to diurnal fluctuations of water and nutrient uptake. The latest empirical and computational methods are discussed in the context of rhizosphere integration. Clarification of rhizosphere semantics, a holistic model of the rhizosphere, examples of integration of rhizosphere studies across disciplines, and review of the latest rhizosphere methods will empower rhizosphere scientists from different disciplines to engage in the interdisciplinary collaborations needed to break new ground in truly understanding the rhizosphere and to apply this knowledge for practical guidance.

Making microscopy count: quantitative light microscopy of dynamic processes in living plants

Cell theory has officially reached 350 years of age as the first use of the word 'cell' in a biological context can be traced to a description of plant material by Robert Hooke in his historic publication 'Micrographia: or some physiological definitions of minute bodies'. The 2015 Royal Microscopical Society Botanical Microscopy meeting was a celebration of the streams of investigation initiated by Hooke to understand at the subcellular scale how plant cell function and form arises. Much of the work presented, and Honorary Fellowships awarded, reflected the advanced application of bioimaging informatics to extract quantitative data from micrographs that reveal dynamic molecular processes driving cell growth and physiology. The field has progressed from collecting many pixels in multiple modes to associating these measurements with objects or features that are meaningful biologically. The additional complexity involves object identification that draws on a different type of expertise from computer science and statistics that is often impenetrable to biologists. There are many useful tools and approaches being developed, but we now need more interdisciplinary exchange to use them effectively. In this review we show how this quiet revolution has provided tools available to any personal computer user. We also discuss the oft-neglected issue of quantifying algorithm robustness and the exciting possibilities offered through the integration of physiological information generated by biosensors with object detection and tracking.

Environmental Control of Root System Biology

The plant root system traverses one of the most complex environments on earth. Understanding how roots support plant life on land requires knowing how soil properties affect the availability of nutrients and water and how roots manipulate the soil environment to optimize acquisition of these resources. Imaging of roots in soil allows the integrated analysis and modeling of environmental interactions occurring at micro- to macroscales. Advances in phenotyping of root systems is driving innovation in cross-platform-compatible methods for data analysis. Root systems acclimate to the environment through architectural changes that act at the root-type level as well as through tissue-specific changes that affect the metabolic needs of the root and the efficiency of nutrient uptake. A molecular understanding of the signaling mechanisms that guide local and systemic signaling is providing insight into the regulatory logic of environmental responses and has identified points where crosstalk between pathways occurs.

How can we harness quantitative genetic variation in crop root systems for agricultural improvement?

Root systems are a black box obscuring a comprehensive understanding of plant function, from the ecosystem scale down to the individual. In particular, a lack of knowledge about the genetic mechanisms and environmental effects that condition root system growth hinders our ability to develop the next generation of crop plants for improved agricultural productivity and sustainability. We discuss how the methods and metrics we use to quantify root systems can affect our ability to understand them, how we can bridge knowledge gaps and accelerate the derivation of structure-function relationships for roots, and why a detailed mechanistic understanding of root growth and function will be important for future agricultural gains.

Analysis of root growth from a phenotyping data set using a density-based model

Major research efforts are targeting the improved performance of root systems for more efficient use of water and nutrients by crops. However, characterizing root system architecture (RSA) is challenging, because roots are difficult objects to observe and analyse. A model-based analysis of RSA traits from phenotyping image data is presented. The model can successfully back-calculate growth parameters without the need to measure individual roots. The mathematical model uses partial differential equations to describe root system development. Methods based on kernel estimators were used to quantify root density distributions from experimental image data, and different optimization approaches to parameterize the model were tested. The model was tested on root images of a set of 89 Brassica rapa L. individuals of the same genotype grown for 14 d after sowing on blue filter paper. Optimized root growth parameters enabled the final (modelled) length of the main root axes to be matched within 1% of their mean values observed in experiments. Parameterized values for elongation rates were within ±4% of the values measured directly on images. Future work should investigate the time dependency of growth parameters using time-lapse image data. The approach is a potentially powerful quantitative technique for identifying crop genotypes with more efficient root systems, using (even incomplete) data from high-throughput phenotyping systems.

Soil-on-a-Chip: microfluidic platforms for environmental organismal studies

Soil is the habitat of countless organisms and encompasses an enormous variety of dynamic environmental conditions. While it is evident that a thorough understanding of how organisms interact with the soil environment may have substantial ecological and economical impact, current laboratory-based methods depend on reductionist approaches that are incapable of simulating natural diversity. The application of Lab-on-a-Chip or microfluidic technologies to organismal studies is an emerging field, where the unique benefits afforded by system miniaturisation offer new opportunities for the experimentalist. Indeed, precise spatiotemporal control over the microenvironments of soil organisms in combination with high-resolution imaging has the potential to provide an unprecedented view of biological events at the single-organism or single-cell level, which in turn opens up new avenues for environmental and organismal studies. Herein we review some of the most recent and interesting developments in microfluidic technologies for the study of soil organisms and their interactions with the environment. We discuss how so-called "Soil-on-a-Chip" technology has already contributed significantly to the study of bacteria, nematodes, fungi and plants, as well as inter-organismal interactions, by advancing experimental access and environmental control. Most crucially, we highlight where distinct advantages over traditional approaches exist and where novel biological insights will ensue.

Setaria viridis as a Model System to Advance Millet Genetics and Genomics

Millet is a common name for a group of polyphyletic, small-seeded cereal crops that include pearl, finger and foxtail millet. Millet species are an important source of calories for many societies, often in developing countries. Compared to major cereal crops such as rice and maize, millets are generally better adapted to dry and hot environments. Despite their food security value, the genetic architecture of agronomically important traits in millets, including both morphological traits and climate resilience remains poorly studied. These complex traits have been challenging to dissect in large part because of the lack of sufficient genetic tools and resources. In this article, we review the phylogenetic relationship among various millet species and discuss the value of a genetic model system for millet research. We propose that a broader adoption of green foxtail (Setaria viridis) as a model system for millets could greatly accelerate the pace of gene discovery in the millets, and summarize available and emerging resources in S. viridis and its domesticated relative S. italica. These resources have value in forward genetics, reverse genetics and high throughput phenotyping. We describe methods and strategies to best utilize these resources to facilitate the genetic dissection of complex traits. We envision that coupling cutting-edge technologies and the use of S. viridis for gene discovery will accelerate genetic research in millets in general. This will enable strategies and provide opportunities to increase productivity, especially in the semi-arid tropics of Asia and Africa where millets are staple food crops.

Digital imaging of root traits (DIRT): a high-throughput computing and collaboration platform for field-based root phenomics

BACKGROUND

Plant root systems are key drivers of plant function and yield. They are also under-explored targets to meet global food and energy demands. Many new technologies have been developed to characterize crop root system architecture (CRSA). These technologies have the potential to accelerate the progress in understanding the genetic control and environmental response of CRSA. Putting this potential into practice requires new methods and algorithms to analyze CRSA in digital images. Most prior approaches have solely focused on the estimation of root traits from images, yet no integrated platform exists that allows easy and intuitive access to trait extraction and analysis methods from images combined with storage solutions linked to metadata. Automated high-throughput phenotyping methods are increasingly used in laboratory-based efforts to link plant genotype with phenotype, whereas similar field-based studies remain predominantly manual low-throughput.

DESCRIPTION

Here, we present an open-source phenomics platform "DIRT", as a means to integrate scalable supercomputing architectures into field experiments and analysis pipelines. DIRT is an online platform that enables researchers to store images of plant roots, measure dicot and monocot root traits under field conditions, and share data and results within collaborative teams and the broader community. The DIRT platform seamlessly connects end-users with large-scale compute "commons" enabling the estimation and analysis of root phenotypes from field experiments of unprecedented size.

CONCLUSION

DIRT is an automated high-throughput computing and collaboration platform for field based crop root phenomics. The platform is accessible at http://www.dirt.iplantcollaborative.org/ and hosted on the iPlant cyber-infrastructure using high-throughput grid computing resources of the Texas Advanced Computing Center (TACC). DIRT is a high volume central depository and high-throughput RSA trait computation platform for plant scientists working on crop roots. It enables scientists to store, manage and share crop root images with metadata and compute RSA traits from thousands of images in parallel. It makes high-throughput RSA trait computation available to the community with just a few button clicks. As such it enables plant scientists to spend more time on science rather than on technology. All stored and computed data is easily accessible to the public and broader scientific community. We hope that easy data accessibility will attract new tool developers and spur creative data usage that may even be applied to other fields of science.