Root angle is controlled by EGT1 in cereal crops employing an antigravitropic mechanism.

Root angle in crops represents a key trait for efficient capture of soil resources. Root angle is determined by competing gravitropic versus antigravitropic offset (AGO) mechanisms. Here we report a root angle regulatory gene termed ENHANCED GRAVITROPISM1 (EGT1) that encodes a putative AGO component, whose loss-of-function enhances root gravitropism. Mutations in barley and wheat EGT1 genes confer a striking root phenotype, where every root class adopts a steeper growth angle. EGT1 encodes an F-box and Tubby domain-containing protein that is highly conserved across plant species. Haplotype analysis found that natural allelic variation at the barley EGT1 locus impacts root angle. Gravitropic assays indicated that Hvegt1 roots bend more rapidly than wild-type. Transcript profiling revealed Hvegt1 roots deregulate reactive oxygen species (ROS) homeostasis and cell wall-loosening enzymes and cofactors. ROS imaging shows that Hvegt1 root basal meristem and elongation zone tissues have reduced levels. Atomic force microscopy measurements detected elongating Hvegt1 root cortical cell walls are significantly less stiff than wild-type. In situ analysis identified HvEGT1 is expressed in elongating cortical and stele tissues, which are distinct from known root gravitropic perception and response tissues in the columella and epidermis, respectively. We propose that EGT1 controls root angle by regulating cell wall stiffness in elongating root cortical tissue, counteracting the gravitropic machinery's known ability to bend the root via its outermost tissues. We conclude that root angle is controlled by EGT1 in cereal crops employing an antigravitropic mechanism.

Divide and conquer: using RhizoVision Explorer to aggregate data from multiple root scans using image concatenation and statistical methods.

Roots are important in agricultural and natural systems for determining plant productivity and soil carbon inputs. Sometimes, the amount of roots in a sample is too much to fit into a single scanned image, so the sample is divided among several scans, and there is no standard method to aggregate the data. Here, we describe and validate two methods for standardizing measurements across multiple scans: image concatenation and statistical aggregation. We developed a Python script that identifies which images belong to the same sample and returns a single, larger concatenated image. These concatenated images and the original images were processed with RhizoVision Explorer, a free and open-source software. An R script was developed, which identifies rows of data belonging to the same sample and applies correct statistical methods to return a single data row for each sample. These two methods were compared using example images from switchgrass, poplar, and various tree and ericaceous shrub species from a northern peatland and the Arctic. Most root measurements were nearly identical between the two methods except median diameter, which cannot be accurately computed by statistical aggregation. We believe the availability of these methods will be useful to the root biology community.

The auxin efflux carrier PIN1a regulates vascular patterning in cereal roots.

Barley (Hordeum vulgare) is an important global cereal crop and a model in genetic studies. Despite advances in characterising barley genomic resources, few mutant studies have identified genes controlling root architecture and anatomy, which plays a critical role in capturing soil resources. Our phenotypic screening of a TILLING mutant collection identified line TM5992 exhibiting a short-root phenotype compared with wild-type (WT) Morex background. Outcrossing TM5992 with barley variety Proctor and subsequent SNP array-based bulk segregant analysis, fine mapped the mutation to a cM scale. Exome sequencing pinpointed a mutation in the candidate gene HvPIN1a, further confirming this by analysing independent mutant alleles. Detailed analysis of root growth and anatomy in Hvpin1a mutant alleles exhibited a slower growth rate, shorter apical meristem and striking vascular patterning defects compared to WT. Expression and mutant analyses of PIN1 members in the closely related cereal brachypodium (Brachypodium distachyon) revealed that BdPIN1a and BdPIN1b were redundantly expressed in root vascular tissues but only Bdpin1a mutant allele displayed root vascular defects similar to Hvpin1a. We conclude that barley PIN1 genes have sub-functionalised in cereals, compared to Arabidopsis (Arabidopsis thaliana), where PIN1a sequences control root vascular patterning.

High-throughput, dynamic, multi-dimensional: an expanding repertoire of plant respiration measurements.

A recent burst of technological innovation and adaptation has greatly improved our ability to capture respiration rate data from plant sources. At the tissue level, several independent respiration measurement options are now available, each with distinct advantages and suitability, including high-throughput sampling capacity. These advancements facilitate the inclusion of respiration rate data into large-scale biological studies such as genetic screens, ecological surveys, crop breeding trials, and multi-omics molecular studies. As a result, our understanding of the correlations of respiration with other biological and biochemical measurements is rapidly increasing. Difficult questions persist concerning the interpretation and utilization of respiration data; concepts such as allocation of respiration to growth versus maintenance, the unnecessary or inefficient use of carbon and energy by respiration, and predictions of future respiration rates in response to environmental change are all insufficiently grounded in empirical data. However, we emphasize that new experimental designs involving novel combinations of respiration rate data with other measurements will flesh-out our current theories of respiration. Furthermore, dynamic recordings of respiration rate, which have long been used at the scale of mitochondria, are increasingly being used at larger scales of size and time to reflect processes of cellular signal transduction and physiological response to the environment. We also highlight how respiratory methods are being better adapted to different plant tissues including roots and seeds, which have been somewhat neglected historically.

Root system architecture in cereals: progress, challenges and perspective.

Roots are essential multifunctional plant organs involved in water and nutrient uptake, metabolite storage, anchorage, mechanical support, and interaction with the soil environment. Understanding of this 'hidden half' provides potential for manipulation of root system architecture (RSA) traits to optimize resource use efficiency and grain yield in cereal crops. Unfortunately, root traits are highly neglected in breeding due to the challenges of phenotyping, but could have large rewards if the variability in RSA traits can be fully exploited. Until now, a plethora of genes have been characterized in detail for their potential role in improving RSA. The use of forward genetics approaches to find sequence variations in genes underpinning desirable RSA would be highly beneficial. Advances in computer vision applications have allowed image-based approaches for high-throughput phenotyping of RSA traits that can be used by any laboratory worldwide to make progress in understanding root function and dissection of the genetics. At the same time, the frontiers of root measurement include non-invasive methods like X-ray computer tomography and magnetic resonance imaging that facilitate new types of temporal studies. Root physiology and ecology are further supported by spatiotemporal root simulation modeling. The discovery of component traits providing improved resilience and yield advantage in target environments is a key necessity for mainstreaming root-based cereal breeding. The integrated use of pan-genome resources, now available in most cereals, coupled with new in-field phenotyping platforms has the potential for precise selection of superior genotypes with improved RSA.

Expression quantitative trait loci mapping identified PtrXB38 as a key hub gene in adventitious root development in Populus.

Plant establishment requires the formation and development of an extensive root system with architecture modulated by complex genetic networks. Here, we report the identification of the PtrXB38 gene as an expression quantitative trait loci (eQTL) hotspot, mapped using 390 leaf and 444 xylem Populus trichocarpa transcriptomes. Among predicted targets of this trans-eQTL were genes involved in plant hormone responses and root development. Overexpression of PtrXB38 in Populus led to significant increases in callusing and formation of both stem-born roots and base-born adventitious roots. Omics studies revealed that genes and proteins controlling auxin transport and signaling were involved in PtrXB38-mediated adventitious root formation. Protein-protein interaction assays indicated that PtrXB38 interacts with components of endosomal sorting complexes required for transport machinery, implying that PtrXB38-regulated root development may be mediated by regulating endocytosis pathway. Taken together, this work identified a crucial root development regulator and sheds light on the discovery of other plant developmental regulators through combining eQTL mapping and omics approaches.

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.

Interactions among rooting traits for deep water and nitrogen uptake in upland and lowland ecotypes of switchgrass (Panicum virgatum L.).

The response of plant growth and development to nutrient and water availability is an important adaptation for abiotic stress tolerance. Roots need to intercept both passing nutrients and water while foraging into new soil layers for further resources. Substantial amounts of nitrate can be lost in the field when leaching into groundwater, yet very little is known about how deep rooting affects this process. Here, we phenotyped root system traits and deep 15N nitrate capture across 1.5 m vertical profiles of solid media using tall mesocosms in switchgrass (Panicum virgatum L.), a promising cellulosic bioenergy feedstock. Root and shoot biomass traits, photosynthesis and respiration measures, and nutrient uptake and accumulation traits were quantified in response to a water and nitrate stress factorial experiment for switchgrass upland (VS16) and lowland (AP13) ecotypes. The two switchgrass ecotypes shared common plastic abiotic responses to nitrogen (N) and water availability, and yet had substantial genotypic variation for root and shoot traits. A significant interaction between N and water stress combination treatments for axial and lateral root traits represents a complex and shared root development strategy for stress mitigation. Deep root growth and 15N capture were found to be closely linked to aboveground growth. Together, these results represent the wide genetic pool of switchgrass and show that deep rooting promotes nitrate capture, plant productivity, and sustainability.

Functional phenomics and genetics of the root economics space in winter wheat using high-throughput phenotyping of respiration and architecture.

The root economics space is a useful framework for plant ecology but is rarely considered for crop ecophysiology. In order to understand root trait integration in winter wheat, we combined functional phenomics with trait economic theory, utilizing genetic variation, high-throughput phenotyping, and multivariate analyses. We phenotyped a diversity panel of 276 genotypes for root respiration and architectural traits using a novel high-throughput method for CO2 flux and the open-source software RhizoVision Explorer to analyze scanned images. We uncovered substantial variation in specific root respiration (SRR) and specific root length (SRL), which were primary indicators of root metabolic and structural costs. Multiple linear regression analysis indicated that lateral root tips had the greatest SRR, and the residuals from this model were used as a new trait. Specific root respiration was negatively correlated with plant mass. Network analysis, using a Gaussian graphical model, identified root weight, SRL, diameter, and SRR as hub traits. Univariate and multivariate genetic analyses identified genetic regions associated with SRR, SRL, and root branching frequency, and proposed gene candidates. Combining functional phenomics and root economics is a promising approach to improving our understanding of crop ecophysiology. We identified root traits and genomic regions that could be harnessed to breed more efficient crops for sustainable agroecosystems.

An integrated framework of plant form and function: the belowground perspective.

Plant trait variation drives plant function, community composition and ecosystem processes. However, our current understanding of trait variation disproportionately relies on aboveground observations. Here we integrate root traits into the global framework of plant form and function. We developed and tested an overarching conceptual framework that integrates two recently identified root trait gradients with a well-established aboveground plant trait framework. We confronted our novel framework with published relationships between above- and belowground trait analogues and with multivariate analyses of above- and belowground traits of 2510 species. Our traits represent the leaf and root conservation gradients (specific leaf area, leaf and root nitrogen concentration, and root tissue density), the root collaboration gradient (root diameter and specific root length) and the plant size gradient (plant height and rooting depth). We found that an integrated, whole-plant trait space required as much as four axes. The two main axes represented the fast-slow 'conservation' gradient on which leaf and fine-root traits were well aligned, and the 'collaboration' gradient in roots. The two additional axes were separate, orthogonal plant size axes for height and rooting depth. This perspective on the multidimensional nature of plant trait variation better encompasses plant function and influence on the surrounding environment.

Root traits as drivers of plant and ecosystem functioning: current understanding, pitfalls and future research needs.

The effects of plants on the biosphere, atmosphere and geosphere are key determinants of terrestrial ecosystem functioning. However, despite substantial progress made regarding plant belowground components, we are still only beginning to explore the complex relationships between root traits and functions. Drawing on the literature in plant physiology, ecophysiology, ecology, agronomy and soil science, we reviewed 24 aspects of plant and ecosystem functioning and their relationships with a number of root system traits, including aspects of architecture, physiology, morphology, anatomy, chemistry, biomechanics and biotic interactions. Based on this assessment, we critically evaluated the current strengths and gaps in our knowledge, and identify future research challenges in the field of root ecology. Most importantly, we found that belowground traits with the broadest importance in plant and ecosystem functioning are not those most commonly measured. Also, the estimation of trait relative importance for functioning requires us to consider a more comprehensive range of functionally relevant traits from a diverse range of species, across environments and over time series. We also advocate that establishing causal hierarchical links among root traits will provide a hypothesis-based framework to identify the most parsimonious sets of traits with the strongest links on functions, and to link genotypes to plant and ecosystem functioning.

A starting guide to root ecology: strengthening ecological concepts and standardising root classification, sampling, processing and trait measurements.

In the context of a recent massive increase in research on plant root functions and their impact on the environment, root ecologists currently face many important challenges to keep on generating cutting-edge, meaningful and integrated knowledge. Consideration of the below-ground components in plant and ecosystem studies has been consistently called for in recent decades, but methodology is disparate and sometimes inappropriate. This handbook, based on the collective effort of a large team of experts, will improve trait comparisons across studies and integration of information across databases by providing standardised methods and controlled vocabularies. It is meant to be used not only as starting point by students and scientists who desire working on below-ground ecosystems, but also by experts for consolidating and broadening their views on multiple aspects of root ecology. Beyond the classical compilation of measurement protocols, we have synthesised recommendations from the literature to provide key background knowledge useful for: (1) defining below-ground plant entities and giving keys for their meaningful dissection, classification and naming beyond the classical fine-root vs coarse-root approach; (2) considering the specificity of root research to produce sound laboratory and field data; (3) describing typical, but overlooked steps for studying roots (e.g. root handling, cleaning and storage); and (4) gathering metadata necessary for the interpretation of results and their reuse. Most importantly, all root traits have been introduced with some degree of ecological context that will be a foundation for understanding their ecological meaning, their typical use and uncertainties, and some methodological and conceptual perspectives for future research. Considering all of this, we urge readers not to solely extract protocol recommendations for trait measurements from this work, but to take a moment to read and reflect on the extensive information contained in this broader guide to root ecology, including sections I-VII and the many introductions to each section and root trait description. Finally, it is critical to understand that a major aim of this guide is to help break down barriers between the many subdisciplines of root ecology and ecophysiology, broaden researchers' views on the multiple aspects of root study and create favourable conditions for the inception of comprehensive experiments on the role of roots in plant and ecosystem functioning.

Targeting Root Ion Uptake Kinetics to Increase Plant Productivity and Nutrient Use Efficiency.

Root system architecture has received increased attention in recent years; however, significant knowledge gaps remain for physiological phenes, or units of phenotype, that have been relatively less studied. Ion uptake kinetics studies have been invaluable in uncovering distinct nutrient uptake systems in plants with the use of Michaelis-Menten kinetic modeling. This review outlines the theoretical framework behind ion uptake kinetics, provides a meta-analysis for macronutrient uptake parameters, and proposes new strategies for using uptake kinetics parameters as selection criteria for breeding crops with improved resource acquisition capability. Presumably, variation in uptake kinetics is caused by variation in type and number of transporters, assimilation machinery, and anatomical features that can vary greatly within and among species. Critically, little is known about what determines transporter properties at the molecular level or how transporter properties scale to the entire root system. A meta-analysis of literature containing measures of crop nutrient uptake kinetics provides insights about the need for standardization of reporting, the differences among crop species, and the relationships among various uptake parameters and experimental conditions. Therefore, uptake kinetics parameters are proposed as promising target phenes that integrate several processes for functional phenomics and genetic analysis, which will lead to a greater understanding of this fundamental plant process. Exploiting this genetic and phenotypic variation has the potential to greatly advance breeding efforts for improved nutrient use efficiency in crops.

Iron-Sulfur Cluster Protein NITROGEN FIXATION S-LIKE1 and Its Interactor FRATAXIN Function in Plant Immunity.

Iron-sulfur (Fe-S) clusters are inorganic cofactors that are present in all kingdoms of life as part of a large number of proteins involved in several cellular processes, including DNA replication and metabolism. In this work, we demonstrate an additional role for two Fe-S cluster genes in biotic stress responses in plants. Eleven Fe-S cluster genes, including the NITROGEN FIXATION S-LIKE1 (NFS1) and its interactor FRATAXIN (FH), when silenced in Nicotiana benthamiana, compromised nonhost resistance to Pseudomonas syringae pv. tomato T1. NbNFS1 expression was induced by pathogens and salicylic acid. Arabidopsis (Arabidopsis thaliana) atnfs and atfh mutants, with reduced AtNFS1 or AtFH gene expression, respectively, showed increased susceptibility to both host and nonhost pathogen infection. Arabidopsis AtNFS1 and AtFH overexpressor lines displayed decreased susceptibility to infection by host pathogen P syringae pv. tomato DC3000. The AtNFS1 overexpression line exhibited constitutive upregulation of several defense-related genes and enrichment of gene ontology terms related to immunity and salicylic acid responses. Our results demonstrate that NFS1 and its interactor FH are involved not only in nonhost resistance but also in basal resistance, suggesting a new role of the Fe-S cluster pathway in plant immunity.

Can smart nutrient applications optimize the plant's hidden half to improve drought resistance?

Global agriculture is challenged with achieving sustainable food security while the climate changes and the threat of drought increases. Much of the research attention has focused on above-ground plant responses with an aim to improve drought resistance. The hidden half, that is, the root system belowground, is receiving increasing attention as the interface of the plant with the soil. Because roots are a sensing organ for nutrients and moisture, we speculate that crop root system traits can be managed using smart nutrient application in order to increase drought resistance. Roots are known to be influenced both by their underlying genetics and also by responses to the environment, termed root plasticity. Though very little is known about the combined effect of water and nutrients on root plasticity, we explore the possibilities of root system manipulation by nutrient application. We compare the effects of different water or nutrient levels on root plasticity and its genetic regulation, with a focus on how this may affect drought resistance. We propose four primary mechanisms through which smart nutrient management can optimize root traits for drought resistance: (1) overall plant vigor, (2) increased root allocation, (3) influence specific root traits, and (4) use smart placement and timing to encourage deep rooting. In the longer term, we envision that beneficial root traits, including plasticity, could be bred into efficient varieties and combined with advanced precision management of water and nutrients to achieve agricultural sustainability.

Functional phenomics: an emerging field integrating high-throughput phenotyping, physiology, and bioinformatics.

The emergence of functional phenomics signifies the rebirth of physiology as a 21st century science through the use of advanced sensing technologies and big data analytics. Functional phenomics seeks to fill the significant knowledge gaps that still exist in the relationship of plant phenotype to function. Here, a general approach for the theory and practice of functional phenomics is outlined. The functional phenomics pipeline is proposed as a general method for conceptualizing, measuring, and validating utility of plant phenes, or elemental units of phenotype. The functional phenomics pipeline begins with ideotype development. Second, a phenotyping platform is developed to maximize the throughput of phene measurements. Target phenes and indicators of plant function, or performance, are measured in a mapping population. Forward genetics allows genetic mapping, while functional phenomics links phenes to plant performance. Based on these data, genotypes with contrasting phenotypes can be selected for smaller yet more intensive experiments to understand phene-environment interactions in depth. Simulation modeling is used to further understand the phenotypes, and all stages of the pipeline feed back to ideotype and phenotyping platform development. In total, functional phenomics represents an evolution of pre-existing disciplines, but the goals and unique methodologies constitute a novel research program.

Maize with fewer nodal roots allocates mass to more lateral and deep roots that improve nitrogen uptake and shoot growth.

Simulations indicated that reduced nodal root (NR) number (NRN) was promising for maize breeding, and were partially confirmed by relying on variation in NRN among inbreds. Using maize inbred line B73, experiments were conducted in hydroponics and tall mesocosms containing solid media with treatments involving no NR excision (0% NRE) or excising either 33% or 67% of the NRs as they emerged under high or low levels of nitrogen (N). Reduced NRN was hypothesized to increase elongation of all remaining root classes, N acquisition under low N, and shoot mass. Plants with 67% NRE had 12% and 19% less root mass fraction, 61% and 91% greater lateral to axial root length ratio regardless of N levels, and 61% and 182% greater biomass of embryonic roots under low N, compared with 0% NRE for hydroponics and mesocosms studies, respectively. Under low N in mesocosms, plants with 67% NRE had 52% greater shoot biomass, 450% greater root length at depth, and 232% greater deep-injected 15N content in the shoot relative to 0% NRE. These results reveal the mechanism by which plants with fewer NRs increase N capture and shoot mass by reallocation of biomass to lateral roots, embryonic roots, and first whorl NRs that increases foraging efficiency in solid media.

Spatiotemporal variation of nitrate uptake kinetics within the maize (Zea mays L.) root system is associated with greater nitrate uptake and interactions with architectural phenes.

Increasing maize nitrogen acquisition efficiency is a major goal for the 21st century. Nitrate uptake kinetics (NUK) are defined by I max and K m, which denote the maximum uptake rate and the affinity of transporters, respectively. Because NUK have been studied predominantly at the molecular and whole-root system levels, little is known about the functional importance of NUK variation within root systems. A novel method was created to measure NUK of root segments that demonstrated variation in NUK among root classes (seminal, lateral, crown, and brace). I max varied among root class, plant age, and nitrate deprivation combinations, but was most affected by plant age, which increased I max, and nitrate deprivation time, which decreased I max K m was greatest for crown roots. The functional-structural simulation SimRoot was used for sensitivity analysis of plant growth to root segment I max and K m, as well as to test interactions of I max with root system architectural phenes. Simulated plant growth was more sensitive to I max than K m, and reached an asymptote near the maximum I max observed in the empirical studies. Increasing the I max of lateral roots had the largest effect on shoot growth. Additive effects of I max and architectural phenes on nitrate uptake were observed. Empirically, only lateral root tips aged 20 d operated at the maximum I max, and simulations demonstrated that increasing all seminal and lateral classes to this maximum rate could increase plant growth by as much as 26%. Therefore, optimizing I max for all maize root classes merits attention as a promising breeding goal.