Cortical parenchyma wall width regulates root metabolic cost and maize performance under suboptimal water availability

We describe how increased root cortical parenchyma wall width (CPW) can improve tolerance to drought stress in maize by reducing the metabolic costs of soil exploration. Significant variation (1.0 to 5.0 µm) for CPW was observed in maize germplasm. The functional-structural model RootSlice predicts that increasing CPW from 2 to 4 µm is associated with ca. 15% reduction in root cortical cytoplasmic volume, respiration rate, and nitrogen content. Analysis of genotypes with contrasting CPW grown with and without water stress in the field confirms that increased CPW is correlated with ca. 32 to 42% decrease in root respiration. Under water stress in the field, increased CPW is correlated with 125% increased stomatal conductance, 325% increased leaf CO2 assimilation rate, 73 to 78% increased shoot biomass, and 92 to 108% increased yield. CPW was correlated with leaf mesophyll midrib parenchyma wall width, indicating pleiotropy. GWAS analysis identified candidate genes underlying CPW. OpenSimRoot modeling predicts that a reduction in root respiration due to increased CPW would also benefit maize growth under suboptimal nitrogen, which requires empirical testing. We propose CPW as a new phene that has utility under edaphic stress meriting further investigation.

Cortical cell size regulates root metabolic cost

It has been hypothesized that vacuolar occupancy in mature root cortical parenchyma cells regulates root metabolic cost and thereby plant fitness under conditions of drought, suboptimal nutrient availability, and increased soil mechanical impedance. However, the mechanistic role of vacuoles in reducing root metabolic cost was unproven. Here we provide evidence to support this hypothesis. We first show that root cortical cell size is determined by both cortical cell diameter and cell length. Significant genotypic variation for both cortical cell diameter (~1.1- to 1.5-fold) and cortical cell length (~ 1.3- to 7-fold) was observed in maize and wheat. GWAS and QTL analyses indicate cortical cell diameter and length are heritable and under independent genetic control. We identify candidate genes for both phenes. Empirical results from isophenic lines contrasting for cortical cell diameter and length show that increased cell size, due to either diameter or length, is associated with reduced root respiration, nitrogen content, and phosphorus content. RootSlice, a functional-structural model of root anatomy, predicts that an increased vacuolar: cytoplasmic ratio per unit cortical volume causes reduced root respiration and nutrient content. Ultrastructural imaging of cortical parenchyma cells with varying cortical diameter and cortical cell length confirms the in silico predictions and shows that an increase in cell size is correlated with increased vacuolar volume and reduced cytoplasmic volume. Vacuolar occupancy and its relationship with cell size merits further investigation as a phene for improving crop adaptation to edaphic stress.

Location: root architecture structures rhizosphere microbial associations

Root architectural phenotypes are promising targets for crop breeding, but root architectural effects on microbial associations in agricultural fields are not well understood. Architecture determines the location of microbial associations within root systems, which, when integrated with soil vertical gradients, determines the functions and the metabolic capability of rhizosphere microbial communities. We argue that variation in root architecture in crops has important implications for root exudation, microbial recruitment and function, and the decomposition and fate of root tissues and exudates. Recent research has shown that the root microbiome changes along root axes and among root classes, that root tips have a unique microbiome, and that root exudates change within the root system depending on soil physicochemical conditions. Although fresh exudates are produced in larger amounts in root tips, the rhizosphere of mature root segments also plays a role in influencing soil vertical gradients. We argue that more research is needed to understand specific root phenotypes that structure microbial associations and discuss candidate root phenotypes that may determine the location of microbial hotspots within root systems with relevance to agricultural systems.

A role for fermentation in aerobic conditions as revealed by computational analysis of maize root metabolism during growth by cell elongation

The root is a well-studied example of cell specialisation, yet little is known about the metabolism that supports the transport functions and growth of different root cell types. To address this, we used computational modelling to study metabolism in the elongation zone of a maize lateral root. A functional-structural model captured the cell-anatomical features of the root and modelled how they changed as the root elongated. From these data, we derived constraints for a flux balance analysis model that predicted metabolic fluxes of the 11 concentric rings of cells in the root. We discovered a distinct metabolic flux pattern in the cortical cell rings, endodermis and pericycle (but absent in the epidermis) that involved a high rate of glycolysis and production of the fermentation end-products lactate and ethanol. This aerobic fermentation was confirmed experimentally by metabolite analysis. The use of fermentation in the model was not obligatory but was the most efficient way to meet the specific demands for energy, reducing power and carbon skeletons of expanding cells. Cytosolic acidification was avoided in the fermentative mode due to the substantial consumption of protons by lipid synthesis. These results expand our understanding of fermentative metabolism beyond that of hypoxic niches and suggest that fermentation could play an important role in the metabolism of aerobic tissues.

RootSlice-A novel functional-structural model for root anatomical phenotypes

Root anatomy is an important determinant of root metabolic costs, soil exploration, and soil resource capture. Root anatomy varies substantially within and among plant species. RootSlice is a multicellular functional-structural model of root anatomy developed to facilitate the analysis and understanding of root anatomical phenotypes. RootSlice can capture phenotypically accurate root anatomy in three dimensions of different root classes and developmental zones, of both monocotyledonous and dicotyledonous species. Several case studies are presented illustrating the capabilities of the model. For maize nodal roots, the model illustrated the role of vacuole expansion in cell elongation; and confirmed the individual and synergistic role of increasing root cortical aerenchyma and reducing the number of cortical cell files in reducing root metabolic costs. Integration of RootSlice for different root zones as the temporal properties of the nodal roots in the whole-plant and soil model OpenSimRoot/maize enabled the multiscale evaluation of root anatomical phenotypes, highlighting the role of aerenchyma formation in enhancing the utility of cortical cell files for improving plant performance over varying soil nitrogen supply. Such integrative in silico approaches present avenues for exploring the fitness landscape of root anatomical phenotypes.

Large root cortical cells and reduced cortical cell files improve growth under suboptimal nitrogen in silico

Suboptimal nitrogen availability is a primary constraint to plant growth. We used OpenSimRoot, a functional-structural plant/soil model, to test the hypothesis that larger root cortical cell size (CCS), reduced cortical cell file number (CCFN), and their interactions with root cortical aerenchyma (RCA) and lateral root branching density (LRBD) are useful adaptations to suboptimal soil nitrogen availability in maize (Zea mays). Reduced CCFN increased shoot dry weight over 80%. Reduced respiration, reduced nitrogen content, and reduced root diameter accounted for 23%, 20%, and 33% of increased shoot biomass, respectively. Large CCS increased shoot biomass by 24% compared with small CCS. When simulated independently, reduced respiration and reduced nutrient content increased the shoot biomass by 14% and 3%, respectively. However, increased root diameter resulting from large CCS decreased shoot biomass by 4% due to an increase in root metabolic cost. Under moderate N stress, integrated phenotypes with reduced CCFN, large CCS, and high RCA improved shoot biomass in silt loam and loamy sand soils. In contrast, integrated phenotypes composed of reduced CCFN, large CCS and reduced lateral root branching density had the greatest growth in silt loam, while phenotypes with reduced CCFN, large CCS and high LRBD were the best performers in loamy sands. Our results support the hypothesis that larger CCS, reduced CCFN, and their interactions with RCA and LRBD could increase nitrogen acquisition by reducing root respiration and root nutrient demand. Phene synergisms may exist between CCS, CCFN, and LRBD. CCS and CCFN merit consideration for breeding cereal crops with improved nitrogen acquisition, which is critical for global food security.

Modeling root loss reveals impacts on nutrient uptake and crop development

Despite the widespread prevalence of root loss in plants, its effects on crop productivity are not fully understood. While root loss reduces the capacity of plants to take up water and nutrients from the soil, it may provide benefits by decreasing the resources required to maintain the root system. Here, we simulated a range of root phenotypes in different soils and root loss scenarios for barley (Hordeum vulgare), common bean (Phaseolus vulgaris), and maize (Zea mays) using and extending the open-source, functional-structural root/soil simulation model OpenSimRoot. The model enabled us to quantify the impact of root loss on shoot dry weight in these scenarios and identify in which scenarios root loss is beneficial, detrimental, or has no effect. The simulations showed that root loss is detrimental for phosphorus uptake in all tested scenarios, whereas nitrogen uptake was relatively insensitive to root loss unless main root axes were lost. Loss of axial roots reduced shoot dry weight for all phenotypes in all species and soils, whereas lateral root loss had a smaller impact. In barley and maize plants with high lateral branching density that were not phosphorus-stressed, loss of lateral roots increased shoot dry weight. The fact that shoot dry weight increased due to root loss in these scenarios indicates that plants overproduce roots for some environments, such as those found in high-input agriculture. We conclude that a better understanding of the effects of root loss on plant development is an essential part of optimizing root system phenotypes for maximizing yield.

Response of Southeast Asian rice root architecture and anatomy phenotypes to drought stress

Drought stress in Southeast Asia greatly affects rice production, and the rice root system plays a substantial role in avoiding drought stress. In this study, we examined the phenotypic and genetic correlations among root anatomical, morphological, and agronomic phenotypes over multiple field seasons. A set of >200 rice accessions from Southeast Asia (a subset of the 3000 Rice Genomes Project) was characterized with the aim to identify root morphological and anatomical phenotypes related to productivity under drought stress. Drought stress resulted in slight increases in the basal metaxylem and stele diameter of nodal roots. Although few direct correlations between root phenotypes and grain yield were identified, biomass was consistently positively correlated with crown root number and negatively correlated with stele diameter. The accessions with highest grain yield were characterized by higher crown root numbers and median metaxylem diameter and smaller stele diameter. Genome-wide association study (GWAS) revealed 162 and 210 significant SNPs associated with root phenotypes in the two seasons which resulted in identification of 59 candidate genes related to root development. The gene OsRSL3 was found in a QTL region for median metaxylem diameter. Four SNPs in OsRSL3 were found that caused amino acid changes and significantly associated with the root phenotype. Based on the haplotype analysis for median metaxylem diameter, the rice accessions studied were classified into five allele combinations in order to identify the most favorable haplotypes. The candidate genes and favorable haplotypes provide information useful for the genetic improvement of root phenotypes under drought stress.

Root and xylem anatomy varies with root length, root order, soil depth and environment in intermediate wheatgrass (Kernza®) and alfalfa

BACKGROUND AND AIMS

Deep roots (i.e. >1 m depth) are important for crops to access water when the topsoil is dry. Root anatomy and hydraulic conductance play important roles in the uptake of soil water, particularly water located deep in the soil. We investigated whether root and xylem anatomy vary as a function of root type, order and length, or with soil depth in roots of two deep-rooted perennial crops: intermediate wheatgrass [Thinopyrum intermedium (Kernza®)] and alfalfa (Medicago sativa). We linked the expression of these anatomical traits to the plants' capacity to take up water from deep soil layers.

METHODS

Using laser ablation tomography, we compared the roots of the two crops for cortical area, number and size of metaxylem vessels, and their estimated root axial hydraulic conductance (ERAHCe). The deepest roots investigated were located at soil depths of 2.25 and at 3.5 m in the field and in rhizoboxes, respectively. Anatomical differences were characterized along 1-m-long individual roots, among root types and orders, as well as between environmental conditions.

KEY RESULTS

For both crops, a decrease in the number and diameter, or both, of metaxylem vessels along individual root segments and with soil depth in the field resulted in a decrease in ERAHCe. Alfalfa, with a greater number of metaxylem vessels per root throughout the soil profile and, on average, a 4-fold greater ERAHCe, took up more water from the deep soil layers than intermediate wheatgrass. Root anatomical traits were significantly different across root types, classes and growth conditions.

CONCLUSIONS

Root anatomical traits are important tools for the selection of crops with enhanced exploitation of deep soil water. The development and breeding of perennial crops for improved subsoil exploitation will be aided by greater understanding of root phenotypes linked to deep root growth and activity.

Multi-objective optimization of root phenotypes for nutrient capture using evolutionary algorithms

Root phenotypes are avenues to the development of crop cultivars with improved nutrient capture, which is an important goal for global agriculture. The fitness landscape of root phenotypes is highly complex and multidimensional. It is difficult to predict which combinations of traits (phene states) will create the best performing integrated phenotypes in various environments. Brute force methods to map the fitness landscape by simulating millions of phenotypes in multiple environments are computationally challenging. Evolutionary optimization algorithms may provide more efficient avenues to explore high dimensional domains such as the root phenotypic space. We coupled the three-dimensional functional-structural plant model, SimRoot, to the Borg Multi-Objective Evolutionary Algorithm (MOEA) and the evolutionary search over several generations facilitated the identification of optimal root phenotypes balancing trade-offs across nutrient uptake, biomass accumulation, and root carbon costs in environments varying in nutrient availability. Our results show that several combinations of root phenes generate optimal integrated phenotypes where performance in one objective comes at the cost of reduced performance in one or more of the remaining objectives, and such combinations differed for mobile and non-mobile nutrients and for maize (a monocot) and bean (a dicot). Functional-structural plant models can be used with multi-objective optimization to identify optimal root phenotypes under various environments, including future climate scenarios, which will be useful in developing the more resilient, efficient crops urgently needed in global agriculture.

Anatomics: High-throughput phenotyping of plant anatomy

Anatomics is a novel phenotyping strategy focused on high-throughput imaging and quantification of plant anatomy from field-grown plants. Here we highlight its potential applications for genetic and physiological analysis of plant anatomical phenotypes.

Improving Soil Resource Uptake by Plants Through Capitalizing on Synergies Between Root Architecture and Anatomy and Root-Associated Microorganisms

Root architectural and anatomical phenotypes are highly diverse. Specific root phenotypes can be associated with better plant growth under low nutrient and water availability. Therefore, root ideotypes have been proposed as breeding targets for more stress-resilient and resource-efficient crops. For example, root phenotypes that correspond to the Topsoil Foraging ideotype are associated with better plant growth under suboptimal phosphorus availability, and root phenotypes that correspond to the Steep, Cheap and Deep ideotype are linked to better performance under suboptimal availability of nitrogen and water. We propose that natural variation in root phenotypes translates into a diversity of different niches for microbial associations in the rhizosphere, rhizoplane and root cortex, and that microbial traits could have synergistic effects with the beneficial effect of specific root phenotypes. Oxygen and water content, carbon rhizodeposition, nutrient availability, and root surface area are all factors that are modified by root anatomy and architecture and determine the structure and function of the associated microbial communities. Recent research results indicate that root characteristics that may modify microbial communities associated with maize include aerenchyma, rooting angle, root hairs, and lateral root branching density. Therefore, the selection of root phenotypes linked to better plant growth under specific edaphic conditions should be accompanied by investigating and selecting microbial partners better adapted to each set of conditions created by the corresponding root phenotype. Microbial traits such as nitrogen transformation, phosphorus solubilization, and water retention could have synergistic effects when correctly matched with promising plant root ideotypes for improved nutrient and water capture. We propose that elucidation of the interactive effects of root phenotypes and microbial functions on plant nutrient and water uptake offers new opportunities to increase crop yields and agroecosystem sustainability.

Future roots for future soils

Mechanical impedance constrains root growth in most soils. Crop cultivation changed the impedance characteristics of native soils, through topsoil erosion, loss of organic matter, disruption of soil structure and loss of biopores. Increasing adoption of Conservation Agriculture in high-input agroecosystems is returning cultivated soils to the soil impedance characteristics of native soils, but in the low-input agroecosystems characteristic of developing nations, ongoing soil degradation is generating more challenging environments for root growth. We propose that root phenotypes have evolved to adapt to the altered impedance characteristics of cultivated soil during crop domestication. The diverging trajectories of soils under Conservation Agriculture and low-input agroecosystems have implications for strategies to develop crops to meet global needs under climate change. We present several root ideotypes as breeding targets under the impedance regimes of both high-input and low-input agroecosystems, as well as a set of root phenotypes that should be useful in both scenarios. We argue that a 'whole plant in whole soil' perspective will be useful in guiding the development of future crops for future soils.

Stomata-mediated interactions between plants, herbivores, and the environment

Stomata play a central role in plant responses to abiotic and biotic stresses. Existing knowledge regarding the roles of stomata in plant stress is centered on abiotic stresses and plant-pathogen interactions, but how stomata influence plant-herbivore interactions remains largely unclear. Here, we summarize the functions of stomata in plant-insect interactions and highlight recent discoveries of how herbivores manipulate plant stomata. Because stomata are linked to interrelated physiological processes in plants, herbivory-induced changes in stomatal dynamics might have cellular, organismic, and/or even community-level impacts. We summarize our current understanding of how stomata mediate plant responses to herbivory and environmental stimuli, propose how herbivores may influence these responses, and identify key knowledge gaps in plant-herbivore interactions.

Integrated root phenotypes for improved rice performance under low nitrogen availability

Greater nitrogen efficiency would substantially reduce the economic, energy and environmental costs of rice production. We hypothesized that synergistic balancing of the costs and benefits for soil exploration among root architectural phenes is beneficial under suboptimal nitrogen availability. An enhanced implementation of the functional-structural model OpenSimRoot for rice integrated with the ORYZA_v3 crop model was used to evaluate the utility of combinations of root architectural phenes, namely nodal root angle, the proportion of smaller diameter nodal roots, nodal root number; and L-type and S-type lateral branching densities, for plant growth under low nitrogen. Multiple integrated root phenotypes were identified with greater shoot biomass under low nitrogen than the reference cultivar IR64. The superiority of these phenotypes was due to synergism among root phenes rather than the expected additive effects of phene states. Representative optimal phenotypes were predicted to have up to 80% greater grain yield with low N supply in the rainfed dry direct-seeded agroecosystem over future weather conditions, compared to IR64. These phenotypes merit consideration as root ideotypes for breeding rice cultivars with improved yield under rainfed dry direct-seeded conditions with limited nitrogen availability. The importance of phene synergism for the performance of integrated phenotypes has implications for crop breeding.

Root angle in maize influences nitrogen capture and is regulated by calcineurin B-like protein (CBL)-interacting serine/threonine-protein kinase 15 (ZmCIPK15)

Crops with reduced nutrient and water requirements are urgently needed in global agriculture. Root growth angle plays an important role in nutrient and water acquisition. A maize diversity panel of 481 genotypes was screened for variation in root angle employing a high-throughput field phenotyping platform. Genome-wide association mapping identified several single nucleotide polymorphisms (SNPs) associated with root angle, including one located in the root expressed CBL-interacting serine/threonine-protein kinase 15 (ZmCIPK15) gene (LOC100285495). Reverse genetic studies validated the functional importance of ZmCIPK15, causing a approximately 10° change in root angle in specific nodal positions. A steeper root growth angle improved nitrogen capture in silico and in the field. OpenSimRoot simulations predicted at 40 days of growth that this change in angle would improve nitrogen uptake by 11% and plant biomass by 4% in low nitrogen conditions. In field studies under suboptimal N availability, the cipk15 mutant with steeper growth angles had 18% greater shoot biomass and 29% greater shoot nitrogen accumulation compared to the wild type after 70 days of growth. We propose that a steeper root growth angle modulated by ZmCIPK15 will facilitate efforts to develop new crop varieties with optimal root architecture for improved performance under edaphic stress.

Soil penetration by maize roots is negatively related to ethylene-induced thickening

Radial expansion is a classic response of roots to a mechanical impedance that has generally been assumed to aid penetration. We analysed the response of maize nodal roots to impedance to test the hypothesis that radial expansion is not related to the ability of roots to cross a compacted soil layer. Genotypes varied in their ability to cross the compacted layer, and those with a steeper approach to the compacted layer or less radial expansion in the compacted layer were more likely to cross the layer and achieve greater depth. Root radial expansion was due to cortical cell size expansion, while cortical cell file number remained constant. Genotypes and nodal root classes that exhibited radial expansion in the compacted soil layer generally also thickened in response to exogenous ethylene in hydroponic culture, that is, radial expansion in response to ethylene was correlated with the thickening response to impedance in soil. We propose that ethylene insensitive roots, that is, those that do not thicken and can overcome impedance, have a competitive advantage under mechanically impeded conditions as they can maintain their elongation rates. We suggest that prolonged exposure to ethylene could function as a stop signal for axial root growth.

Theoretical evidence that root penetration ability interacts with soil compaction regimes to affect nitrate capture

BACKGROUND AND AIMS

Although root penetration of strong soils has been intensively studied at the scale of individual root axes, interactions between soil physical properties and soil foraging by whole plants are less clear. Here we investigate how variation in the penetration ability of distinct root classes and bulk density profiles common to real-world soils interact to affect soil foraging strategies.

METHODS

We utilize the functional-structural plant model 'OpenSimRoot' to simulate the growth of maize (Zea mays) root systems with variable penetration ability of axial and lateral roots in soils with (1) uniform bulk density, (2) plow pans and (3) increasing bulk density with depth. We also modify the availability and leaching of nitrate to uncover reciprocal interactions between these factors and the capture of mobile resources.

KEY RESULTS

Soils with plow pans and bulk density gradients affected overall size, distribution and carbon costs of the root system. Soils with high bulk density at depth impeded rooting depth and reduced leaching of nitrate, thereby improving the coincidence of nitrogen and root length. While increasing penetration ability of either axial or lateral root classes produced root systems of comparable net length, improved penetration of axial roots increased allocation of root length in deeper soil, thereby amplifying N acquisition and shoot biomass. Although enhanced penetration ability of both root classes was associated with greater root system carbon costs, the benefit to plant fitness from improved soil exploration and resource capture offset these.

CONCLUSIONS

While lateral roots comprise the bulk of root length, axial roots function as a scaffold determining the distribution of these laterals. In soils with high soil strength and leaching, root systems with enhanced penetration ability of axial roots have greater distribution of root length at depth, thereby improving capture of mobile resources.

Developmental Morphology and Anatomy Shed Light on Both Parallel and Convergent Evolution of the Umbellate Inflorescence in Monocots, Underlain by a New Variant of Metatopy

Inflorescence structure is very diverse and homoplasious, yet the developmental basis of their homoplasy is poorly understood. To gain an understanding of the degree of homology that these diverse structures share, we characterize the developmental morphology and anatomy of various umbellate inflorescences across the monocots and analyzed them in an evolutionary context. To characterize branching order, we characterized the developmental morphology of multiple inflorescences with epi-illumination, and vascular anatomy with Laser Ablation Tomography, a novel high-throughput method to reconstruct three-dimensional vasculature. We used these approaches to analyze the umbellate inflorescences in five instances of presumed homoplasy: in three members of the Amaryllidaceae; in three members of the Asparagaceae, including a putatively derived raceme in Dichelostemma congestum; in Butomus umbellatus (Alismataceae), in Tacca chantrieri (Dioscoreaceae), and in umbellate structure in Fritillaria imperialis (Liliaceae). We compare these with racemes found in three members of the subfamily Scilliioideae (Asparagaceae). We find there are three convergent developmental programs that generate umbellate inflorescences in the monocots, bostryx-derived, cincinnus-derived and raceme-derived. Additionally, among the bostryx-derived umbellate inflorescence, there are three instances of parallel evolution found in the Amaryllidaceae, in two members of Brodiaeoideae (Asparagaceae), and Butomus umbellatus, all of which share the same generative developmental program. We discuss the morphological modifications necessary to generate such complex and condensed structures and use these insights to describe a new variant of metatopy, termed horizontal concaulesence. We contextualize our findings within the broader literature of monocot inflorescence development, with a focus on synthesizing descriptive developmental morphological studies.

In silico evidence for the utility of parsimonious root phenotypes for improved vegetative growth and carbon sequestration under drought

Drought is a primary constraint to crop yields and climate change is expected to increase the frequency and severity of drought stress in the future. It has been hypothesized that crops can be made more resistant to drought and better able to sequester atmospheric carbon in the soil by selecting appropriate root phenotypes. We introduce OpenSimRoot_v2, an upgraded version of the functional-structural plant/soil model OpenSimRoot, and use it to test the utility of a maize root phenotype with fewer and steeper axial roots, reduced lateral root branching density, and more aerenchyma formation (i.e. the 'Steep, Cheap, and Deep' (SCD) ideotype) and different combinations of underlying SCD root phene states under rainfed and drought conditions in three distinct maize growing pedoclimatic environments in the USA, Nigeria, and Mexico. In all environments where plants are subjected to drought stress the SCD ideotype as well as several intermediate phenotypes lead to greater shoot biomass after 42 days. As an additional advantage, the amount of carbon deposited below 50 cm in the soil is twice as great for the SCD phenotype as for the reference phenotype in 5 out of 6 simulated environments. We conclude that crop growth and deep soil carbon deposition can be improved by breeding maize plants with fewer axial roots, reduced lateral root branching density, and more aerenchyma formation.

Harnessing root architecture to address global challenges

Root architecture can be targeted in breeding programs to develop crops with better capture of water and nutrients. In rich nations, such crops would reduce production costs and environmental pollution and, in developing nations, they would improve food security and economic development. Crops with deeper roots would have better climate resilience while also sequestering atmospheric CO₂ . Deeper rooting, which improves water and N capture, is facilitated by steeper root growth angles, fewer axial roots, reduced lateral branching, and anatomical phenotypes that reduce the metabolic cost of root tissue. Mechanical impedance, hypoxia, and Al toxicity are constraints to subsoil exploration. To improve topsoil foraging for P, K, and other shallow resources, shallower root growth angles, more axial roots, and greater lateral branching are beneficial, as are metabolically cheap roots. In high-input systems, parsimonious root phenotypes that focus on water capture may be advantageous. The growing prevalence of Conservation Agriculture is shifting the mechanical impedance characteristics of cultivated soils in ways that may favor plastic root phenotypes capable of exploiting low resistance pathways to the subsoil. Root ideotypes for many low-input systems would not be optimized for any one function, but would be resilient against an array of biotic and abiotic challenges. Root hairs, reduced metabolic cost, and developmental regulation of plasticity may be useful in all environments. The fitness landscape of integrated root phenotypes is large and complex, and hence will benefit from in silico tools. Understanding and harnessing root architecture for crop improvement is a transdisciplinary opportunity to address global challenges.

Many paths to one goal: Identifying integrated rice root phenotypes for diverse drought environments

Drought is a major source of yield loss in the production of rice (Oryza sativa L.), and cultivars that maintain yield under drought across environments and drought stress scenarios are urgently needed. Root phenotypes directly affect water interception and uptake, so plants with root systems optimized for water uptake under drought would likely exhibit reduced yield loss. Deeper nodal roots that have a low metabolic cost per length (i.e., cheaper roots) via smaller root diameter and/or more aerenchyma and that transport water efficiently through smaller diameter metaxylem vessels may be beneficial during drought. Subsets of the Rice Diversity Panel 1 and Azucena × IR64 recombinant inbred lines were grown in two greenhouse and two rainout shelter experiments under drought stress to assess their shoot, root anatomical, and root architectural phenotypes. Root traits and root trait plasticity in response to drought varied with genotype and environment. The best-performing groups in the rainout shelter experiments had less plasticity of living tissue area in nodal roots than the worst performing groups. Root traits under drought were partitioned into similar groups or clusters via the partitioning-around-medoids algorithm, and this revealed two favorable integrated root phenotypes common within and across environments. One favorable integrated phenotype exhibited many, deep nodal roots with larger root cross-sectional area and more aerenchyma, while the other favorable phenotype exhibited many, deep nodal roots with small root cross-sectional area and small metaxylem vessels. Deeper roots with high theoretical axial hydraulic conductance combined with reduced root metabolic cost contributed to greater shoot biomass under drought. These results reflect how some root anatomical and architectural phenes work in concert as integrated phenotypes to influence the performance of plant under drought stress. Multiple integrated root phenotypes are therefore recommended to be selected in breeding programs for improving rice yield across diverse environments and drought scenarios.

Root hair phenotypes influence nitrogen acquisition in maize

BACKGROUND AND AIMS

The utility of root hairs for nitrogen (N) acquisition is poorly understood.

METHODS

We explored the utility of root hairs for N acquisition in the functional-structural model SimRoot and with maize genotypes with variable root hair length (RHL) in greenhouse and field environments.

KEY RESULTS

Simulation results indicate that long, dense root hairs can improve N acquisition under varying N availability. In the greenhouse, ammonium availability had no effect on RHL and low nitrate availability increased RHL, while in the field low N reduced RHL. Longer RHL was associated with 216 % increase in biomass and 237 % increase in plant N content under low-N conditions in the greenhouse and a 250 % increase in biomass and 200 % increase in plant N content in the field compared with short-RHL phenotypes. In a low-N field environment, genotypes with long RHL had 267 % greater yield than those with short RHL. We speculate that long root hairs improve N capture by increased root surface area and expanded soil exploration beyond the N depletion zone surrounding the root surface.

CONCLUSIONS

We conclude that root hairs play an important role in N acquisition. We suggest that root hairs merit consideration as a breeding target for improved N acquisition in maize and other crops.

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

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

Increased seminal root number associated with domestication improves nitrogen and phosphorus acquisition in maize seedlings

BACKGROUND AND AIMS

Domesticated maize (Zea mays ssp. mays) generally forms between two and six seminal roots, while its wild ancestor, Mexican annual teosinte (Zea mays ssp. parviglumis), typically lacks seminal roots. Maize also produces larger seeds than teosinte, and it generally has higher growth rates as a seedling. Maize was originally domesticated in the tropical soils of southern Mexico, but it was later brought to the Mexican highlands before spreading to other parts of the continent, where it experienced different soil resource constraints. The aims of this study were to understand the impacts of increased seminal root number on seedling nitrogen and phosphorus acquisition and to model how differences in maize and teosinte phenotypes might have contributed to increased seminal root number in domesticated maize.

METHODS

Seedling root system architectural models of a teosinte accession and a maize landrace were constructed by parameterizing the functional-structural plant model OpenSimRoot using plants grown in mesocosms. Seedling growth was simulated in a low-phosphorus environment, multiple low-nitrogen environments, and at variable planting densities. Models were also constructed to combine individual components of the maize and teosinte phenotypes.

KEY RESULTS

Seminal roots contributed ~35 % of the nitrogen and phosphorus acquired by maize landrace seedlings in the first 25 d after planting. Increased seminal root number improved plant nitrogen acquisition under low-nitrogen environments with varying precipitation patterns, fertilization rates, soil textures and planting densities. Models suggested that the optimal number of seminal roots for nutrient acquisition in teosinte is constrained by its limited seed carbohydrate reserves.

CONCLUSIONS

Seminal roots can improve the acquisition of both nitrogen and phosphorus in maize seedlings, and the increase in seed size associated with maize domestication may have facilitated increased seminal root number.

The importance of dominance and genotype-by-environment interactions on grain yield variation in a large-scale public cooperative maize experiment

High-dimensional and high-throughput genomic, field performance, and environmental data are becoming increasingly available to crop breeding programs, and their integration can facilitate genomic prediction within and across environments and provide insights into the genetic architecture of complex traits and the nature of genotype-by-environment interactions. To partition trait variation into additive and dominance (main effect) genetic and corresponding genetic-by-environment variances, and to identify specific environmental factors that influence genotype-by-environment interactions, we curated and analyzed genotypic and phenotypic data on 1918 maize (Zea mays L.) hybrids and environmental data from 65 testing environments. For grain yield, dominance variance was similar in magnitude to additive variance, and genetic-by-environment variances were more important than genetic main effect variances. Models involving both additive and dominance relationships best fit the data and modeling unique genetic covariances among all environments provided the best characterization of the genotype-by-environment interaction patterns. Similarity of relative hybrid performance among environments was modeled as a function of underlying weather variables, permitting identification of weather covariates driving correlations of genetic effects across environments. The resulting models can be used for genomic prediction of mean hybrid performance across populations of environments tested or for environment-specific predictions. These results can also guide efforts to incorporate high-throughput environmental data into genomic prediction models and predict values in new environments characterized with the same environmental characteristics.

Utility of Climatic Information via Combining Ability Models to Improve Genomic Prediction for Yield Within the Genomes to Fields Maize Project

Genomic prediction provides an efficient alternative to conventional phenotypic selection for developing improved cultivars with desirable characteristics. New and improved methods to genomic prediction are continually being developed that attempt to deal with the integration of data types beyond genomic information. Modern automated weather systems offer the opportunity to capture continuous data on a range of environmental parameters at specific field locations. In principle, this information could characterize training and target environments and enhance predictive ability by incorporating weather characteristics as part of the genotype-by-environment (G×E) interaction component in prediction models. We assessed the usefulness of including weather data variables in genomic prediction models using a naïve environmental kinship model across 30 environments comprising the Genomes to Fields (G2F) initiative in 2014 and 2015. Specifically four different prediction scenarios were evaluated (i) tested genotypes in observed environments; (ii) untested genotypes in observed environments; (iii) tested genotypes in unobserved environments; and (iv) untested genotypes in unobserved environments. A set of 1,481 unique hybrids were evaluated for grain yield. Evaluations were conducted using five different models including main effect of environments; general combining ability (GCA) effects of the maternal and paternal parents modeled using the genomic relationship matrix; specific combining ability (SCA) effects between maternal and paternal parents; interactions between genetic (GCA and SCA) effects and environmental effects; and finally interactions between the genetics effects and environmental covariates. Incorporation of the genotype-by-environment interaction term improved predictive ability across all scenarios. However, predictive ability was not improved through inclusion of naive environmental covariates in G×E models. More research should be conducted to link the observed weather conditions with important physiological aspects in plant development to improve predictive ability through the inclusion of weather data.

Nodal root diameter and node number in maize (Zea mays L.) interact to influence plant growth under nitrogen stress

Under nitrogen limitation, plants increase resource allocation to root growth relative to shoot growth. The utility of various root architectural and anatomical phenotypes for nitrogen acquisition are not well understood. Nodal root number and root cross-sectional area were evaluated in maize in field and greenhouse environments. Nodal root number and root cross-sectional area were inversely correlated under both high and low nitrogen conditions. Attenuated emergence of root nodes, as opposed to differences in the number of axial roots per node, was associated with substantially reduced root number. Greater root cross-sectional area was associated with a greater stele area and number of cortical cell files. Genotypes that produced few, thick nodal roots rather than many, thin nodal roots had deeper rooting and better shoot growth in low nitrogen environments. Fewer nodal roots offset the respiratory and nitrogen costs of thicker diameter roots, since total nodal root respiration and nitrogen content was similar for genotypes with many, thin and few, thick nodal roots. We propose that few, thick nodal roots may enable greater capture of deep soil nitrogen and improve plant performance under nitrogen stress. Synergistic interactions between an architectural and anatomical trait may be an important strategy for nitrogen acquisition. Understanding trait interactions among different root nodes has important implications in for improving crop nutrient uptake and stress tolerance.

Multiseriate cortical sclerenchyma enhance root penetration in compacted soils

Mechanical impedance limits soil exploration and resource capture by plant roots. We examine the role of root anatomy in regulating plant adaptation to mechanical impedance and identify a root anatomical phene in maize (Zea mays) and wheat (Triticum aestivum) associated with penetration of hard soil: Multiseriate cortical sclerenchyma (MCS). We characterize this trait and evaluate the utility of MCS for root penetration in compacted soils. Roots with MCS had a greater cell wall-to-lumen ratio and a distinct UV emission spectrum in outer cortical cells. Genome-wide association mapping revealed that MCS is heritable and genetically controlled. We identified a candidate gene associated with MCS. Across all root classes and nodal positions, maize genotypes with MCS had 13% greater root lignin concentration compared to genotypes without MCS. Genotypes without MCS formed MCS upon exogenous ethylene exposure. Genotypes with MCS had greater lignin concentration and bending strength at the root tip. In controlled environments, MCS in maize and wheat was associated improved root tensile strength and increased penetration ability in compacted soils. Maize genotypes with MCS had root systems with 22% greater depth and 49% greater shoot biomass in compacted soils in the field compared to lines without MCS. Of the lines we assessed, MCS was present in 30 to 50% of modern maize, wheat, and barley cultivars but was absent in teosinte and wild and landrace accessions of wheat and barley. MCS merits investigation as a trait for improving plant performance in maize, wheat, and other grasses under edaphic stress.

Three-dimensional imaging reveals that positions of cyst nematode feeding sites relative to xylem vessels differ between susceptible and resistant wheat

Resistance conferred by the Cre8 locus of wheat prevents cereal cyst nematode feeding sites from reaching and invading root metaxylem vessels. Cyst nematodes develop syncytial feeding sites within plant roots. The success of these sites is affected by host plant resistance. In wheat (Triticum aestivum L.), 'Cre' loci affect resistance against the cereal cyst nematode (CCN) Heterodera avenae. To investigate how one of these loci (Cre8, on chromosome 6B) confers resistance, CCN-infected root tissue from susceptible (-Cre8) and resistant (+Cre8) wheat plants was examined using confocal microscopy and laser ablation tomography. Confocal analysis of transverse sections showed that feeding sites in the roots of -Cre8 plants were always adjacent to metaxylem vessels, contained many intricate 'web-like' cell walls, and sometimes 'invaded' metaxylem vessels. In contrast, feeding sites in the roots of +Cre8 plants were usually not directly adjacent to metaxylem vessels, had few inner cell walls and did not 'invade' metaxylem vessels. Models based on data from laser ablation tomography confirmed these observations. Confocal analysis of longitudinal sections revealed that CCN-induced xylem modification that had previously been reported for susceptible (-Cre8) wheat plants is less extreme in resistant (+Cre8) plants. Application of a lignin-specific stain revealed that secondary thickening around xylem vessels in CCN-infected roots was greater in +Cre8 plants than in -Cre8 plants. Collectively, these results indicate that Cre8 resistance in wheat acts by preventing cyst nematode feeding sites from reaching and invading root metaxylem vessels.

Plant roots sense soil compaction through restricted ethylene diffusion

Soil compaction represents a major challenge for modern agriculture. Compaction is intuitively thought to reduce root growth by limiting the ability of roots to penetrate harder soils. We report that root growth in compacted soil is instead actively suppressed by the volatile hormone ethylene. We found that mutant Arabidopsis and rice roots that were insensitive to ethylene penetrated compacted soil more effectively than did wild-type roots. Our results indicate that soil compaction lowers gas diffusion through a reduction in air-filled pores, thereby causing ethylene to accumulate in root tissues and trigger hormone responses that restrict growth. We propose that ethylene acts as an early warning signal for roots to avoid compacted soils, which would be relevant to research into the breeding of crops resilient to soil compaction.

A Comparative Analysis of Quantitative Metrics of Root Architecture

High throughput phenotyping is important to bridge the gap between genotype and phenotype. The methods used to describe the phenotype therefore should be robust to measurement errors, relatively stable over time, and most importantly, provide a reliable estimate of elementary phenotypic components. In this study, we use functional-structural modeling to evaluate quantitative phenotypic metrics used to describe root architecture to determine how they fit these criteria. Our results show that phenes such as root number, root diameter, and lateral root branching density are stable, reliable measures and are not affected by imaging method or plane. Metrics aggregating multiple phenes such as total length, total volume, convex hull volume, and bushiness index estimate different subsets of the constituent phenes; they however do not provide any information regarding the underlying phene states. Estimates of phene aggregates are not unique representations of underlying constituent phenes: multiple phenotypes having phenes in different states could have similar aggregate metrics. Root growth angle is an important phene which is susceptible to measurement errors when 2D projection methods are used. Metrics that aggregate phenes which are complex functions of root growth angle and other phenes are also subject to measurement errors when 2D projection methods are used. These results support the hypothesis that estimates of phenes are more useful than metrics aggregating multiple phenes for phenotyping root architecture. We propose that these concepts are broadly applicable in phenotyping and phenomics.

Root metaxylem and architecture phenotypes integrate to regulate water use under drought stress

At the genus and species level, variation in root anatomy and architecture may interact to affect strategies of drought avoidance. To investigate this idea, root anatomy and architecture of the drought-sensitive common bean (Phaseolus vulgaris) and drought-adapted tepary bean (Phaseolus acutifolius) were analyzed in relation to water use under terminal drought. Intraspecific variation for metaxylem anatomy and axial conductance was found in the roots of both species. Genotypes with high-conductance root metaxylem phenotypes acquired and transpired more water per unit leaf area, shoot mass, and root mass than genotypes with low-conductance metaxylem phenotypes. Interspecific variation in root architecture and root depth was observed where P. acutifolius has a deeper distribution of root length than P. vulgaris. In the deeper-rooted P. acutifolius, genotypes with high root conductance were better able to exploit deep soil water than genotypes with low root axial conductance. Contrastingly, in the shallower-rooted P. vulgaris, genotypes with low root axial conductance had improved water status through conservation of soil moisture for sustained water capture later in the season. These results indicate that metaxylem morphology interacts with root system depth to determine a strategy of drought avoidance and illustrate synergism among architectural and anatomical phenotypes for root function.

An Analysis of Soil Coring Strategies to Estimate Root Depth in Maize (Zea mays) and Common Bean (Phaseolus vulgaris)

A soil coring protocol was developed to cooptimize the estimation of root length distribution (RLD) by depth and detection of functionally important variation in root system architecture (RSA) of maize and bean. The functional-structural model OpenSimRoot was used to perform in silico soil coring at six locations on three different maize and bean RSA phenotypes. Results were compared to two seasons of field soil coring and one trench. Two one-sided T-test (TOST) analysis of in silico data suggests a between-row location 5 cm from plant base (location 3), best estimates whole-plot RLD/D of deep, intermediate, and shallow RSA phenotypes, for both maize and bean. Quadratic discriminant analysis indicates location 3 has ~70% categorization accuracy for bean, while an in-row location next to the plant base (location 6) has ~85% categorization accuracy in maize. Analysis of field data suggests the more representative sampling locations vary by year and species. In silico and field studies suggest location 3 is most robust, although variation is significant among seasons, among replications within a field season, and among field soil coring, trench, and simulations. We propose that the characterization of the RLD profile as a dynamic rhizo canopy effectively describes how the RLD profile arises from interactions among an individual plant, its neighbors, and the pedosphere.

Root secondary growth: an unexplored component of soil resource acquisition

BACKGROUND AND AIMS

Despite recent progress in elucidating the molecular basis of secondary growth (cambial growth), the functional implications of this developmental process remain poorly understood. Targeted studies exploring how abiotic and biotic factors affect this process, as well as the relevance of secondary growth to fitness of annual dicotyledonous crop species under stress, are almost entirely absent from the literature. Specifically, the physiological role of secondary growth in roots has been completely neglected yet entails a unique array of implications for plant performance that are distinct from secondary growth in shoot tissue.

SCOPE

Since roots are directly responsible for soil resource capture, understanding of the fitness landscape of root phenotypes is important in both basic and applied plant biology. Interactions between root secondary growth, edaphic conditions and soil resource acquisition may have significant effects on plant fitness. Our intention here is not to provide a comprehensive review of a sparse and disparate literature, but rather to highlight knowledge gaps, propose hypotheses and identify opportunities for novel and agriculturally relevant research pertaining to secondary growth of roots. This viewpoint: (1) summarizes evidence from our own studies and other published work; (2) proposes hypotheses regarding the fitness landscape of secondary growth of roots in annual dicotyledonous species for abiotic and biotic stress; and (3) highlights the importance of directing research efforts to this topic within an agricultural context.

CONCLUSIONS

Secondary growth of the roots of annual dicots has functional significance with regards to soil resource acquisition and transport, interactions with soil organisms and carbon sequestration. Research on these topics would contribute significantly toward understanding the agronomic value of secondary growth of roots for crop improvement.

Root anatomical traits contribute to deeper rooting of maize under compacted field conditions

To better understand the role of root anatomy in regulating plant adaptation to soil mechanical impedance, 12 maize lines were evaluated in two soils with and without compaction treatments under field conditions. Penetrometer resistance was 1-2 MPa greater in the surface 30 cm of the compacted plots at a water content of 17-20% (v/v). Root thickening in response to compaction varied among genotypes and was negatively associated with rooting depth at one field site under non-compacted plots. Thickening was not associated with rooting depth on compacted plots. Genotypic variation in root anatomy was related to rooting depth. Deeper-rooting plants were associated with reduced cortical cell file number in combination with greater mid cortical cell area for node 3 roots. For node 4, roots with increased aerenchyma were deeper roots. A greater influence of anatomy on rooting depth was observed for the thinner root classes. We found no evidence that root thickening is related to deeper rooting in compacted soil; however, anatomical traits are important, especially for thinner root classes.

Multiscale computational models can guide experimentation and targeted measurements for crop improvement

Computational models of plants have identified gaps in our understanding of biological systems, and have revealed ways to optimize cellular processes or organ-level architecture to increase productivity. Thus, computational models are learning tools that help direct experimentation and measurements. Models are simplifications of complex systems, and often simulate specific processes at single scales (e.g. temporal, spatial, organizational, etc.). Consequently, single-scale models are unable to capture the critical cross-scale interactions that result in emergent properties of the system. In this perspective article, we contend that to accurately predict how a plant will respond in an untested environment, it is necessary to integrate mathematical models across biological scales. Computationally mimicking the flow of biological information from the genome to the phenome is an important step in discovering new experimental strategies to improve crops. A key challenge is to connect models across biological, temporal and computational (e.g. CPU versus GPU) scales, and then to visualize and interpret integrated model outputs. We address this challenge by describing the efforts of the international Crops in silico consortium.

Multiple Integrated Root Phenotypes Are Associated with Improved Drought Tolerance

To test the hypothesis that multiple integrated root phenotypes would co-optimize drought tolerance, we phenotyped the root anatomy and architecture of 400 mature maize (Zea mays) genotypes under well-watered and water-stressed conditions in the field. We found substantial variation in all 23 root phenes measured. A phenotypic bulked segregant analysis revealed that bulks representing the best and worst performers in the field displayed distinct root phenotypes. In contrast to the worst bulk, the root phenotype of the best bulk under drought consisted of greater cortical aerenchyma formation, more numerous and narrower metaxylem vessels, and thicker nodal roots. Partition-against-medians clustering revealed several clusters of unique root phenotypes related to plant performance under water stress. Clusters associated with improved drought tolerance consisted of phene states that likely enable greater soil exploration by reallocating internal resources to greater root construction (increased aerenchyma content, larger cortical cells, fewer cortical cell files), restrict uptake of water to conserve soil moisture (reduced hydraulic conductance, narrow metaxylem vessels), and improve penetrability of hard, dry soils (thick roots with a larger proportion of stele, and smaller distal cortical cells). We propose that the most drought-tolerant-integrated phenotypes merit consideration as breeding ideotypes.

Genetic control of root architectural plasticity in maize

Root phenotypes regulate soil resource acquisition; however, their genetic control and phenotypic plasticity are poorly understood. We hypothesized that the responses of root architectural phenes to water deficit (stress plasticity) and different environments (environmental plasticity) are under genetic control and that these loci are distinct. Root architectural phenes were phenotyped in the field using a large maize association panel with and without water deficit stress for three seasons in Arizona and without water deficit stress for four seasons in South Africa. All root phenes were plastic and varied in their plastic response. We identified candidate genes associated with stress and environmental plasticity and candidate genes associated with phenes in well-watered conditions in South Africa and in well-watered and water-stress conditions in Arizona. Few candidate genes for plasticity overlapped with those for phenes expressed under each condition. Our results suggest that phenotypic plasticity is highly quantitative, and plasticity loci are distinct from loci that control phene expression in stress and non-stress, which poses a challenge for breeding programs. To make these loci more accessible to the wider research community, we developed a public online resource that will allow for further experimental validation towards understanding the genetic control underlying phenotypic plasticity.

Should Root Plasticity Be a Crop Breeding Target?

Root phenotypic plasticity has been proposed as a target for the development of more productive crops in variable environments. However, the plasticity of root anatomical and architectural responses to environmental cues is highly complex, and the consequences of these responses for plant fitness are poorly understood. We propose that root phenotypic plasticity may be beneficial in natural or low-input systems in which the availability of soil resources is spatiotemporally dynamic. Crop ancestors and landraces were selected with multiple stresses, competition, significant root loss and heterogenous resource distribution which favored plasticity in response to resource availability. However, in high-input agroecosystems, the value of phenotypic plasticity is unclear, since human management has removed many of these constraints to root function. Further research is needed to understand the fitness landscape of plastic responses including understanding the value of plasticity in different environments, environmental signals that induce plastic responses, and the genetic architecture of plasticity before it is widely adopted in breeding programs. Phenotypic plasticity has many potential ecological, and physiological benefits, but its costs and adaptive value in high-input agricultural systems is poorly understood and merits further research.

Genetic components of root architecture and anatomy adjustments to water-deficit stress in spring barley

Roots perform vital roles for adaptation and productivity under water-deficit stress, even though their specific functions are poorly understood. In this study, the genetic control of the nodal-root architectural and anatomical response to water deficit were investigated among diverse spring barley accessions. Water deficit induced substantial variations in the nodal root traits. The cortical, stele, and total root cross-sectional areas of the main-shoot nodal roots decreased under water deficit, but increased in the tiller nodal roots. Root xylem density and arrested nodal roots increased under water deficit, with the formation of root suberization/lignification and large cortical aerenchyma. Genome-wide association study implicated 11 QTL intervals in the architectural and anatomical nodal root response to water deficit. Among them, three and four QTL intervals had strong effects across seasons and on both root architectural and anatomical traits, respectively. Genome-wide epistasis analysis revealed 44 epistatically interacting SNP loci. Further analyses showed that these QTL intervals contain important candidate genes, including ZIFL2, MATE, and PPIB, whose functions are shown to be related to the root adaptive response to water deprivation in plants. These results give novel insight into the genetic architectures of barley nodal root response to soil water deficit stress in the fields, and thus offer useful resources for root-targeted marker-assisted selection.

Genetic control of root anatomical plasticity in maize

Root anatomical phenes have important roles in soil resource capture and plant performance; however, their phenotypic plasticity and genetic architecture is poorly understood. We hypothesized that (a) the responses of root anatomical phenes to water deficit (stress plasticity) and different environmental conditions (environmental plasticity) are genetically controlled and (b) stress and environmental plasticity are associated with different genetic loci than those controlling the expression of phenes under water-stress and well-watered conditions. Root anatomy was phenotyped in a large maize (Zea mays L.) association panel in the field with and without water deficit stress in Arizona and without water deficit stress in South Africa. Anatomical phenes displayed stress and environmental plasticity; many phenotypic responses to water deficit were adaptive, and the magnitude of response varied by genotype. We identified 57 candidate genes associated with stress and environmental plasticity and 64 candidate genes associated with phenes under well-watered and water-stress conditions in Arizona and under well-watered conditions in South Africa. Four candidate genes co-localized between plasticity groups or for phenes expressed under each condition. The genetic architecture of phenotypic plasticity is highly quantitative, and many distinct genes control plasticity in response to water deficit and different environments, which poses a challenge for breeding programs.

Maize genomes to fields (G2F): 2014-2017 field seasons: genotype, phenotype, climatic, soil, and inbred ear image datasets

OBJECTIVES

Advanced tools and resources are needed to efficiently and sustainably produce food for an increasing world population in the context of variable environmental conditions. The maize genomes to fields (G2F) initiative is a multi-institutional initiative effort that seeks to approach this challenge by developing a flexible and distributed infrastructure addressing emerging problems. G2F has generated large-scale phenotypic, genotypic, and environmental datasets using publicly available inbred lines and hybrids evaluated through a network of collaborators that are part of the G2F's genotype-by-environment (G × E) project. This report covers the public release of datasets for 2014-2017.

DATA DESCRIPTION

Datasets include inbred genotypic information; phenotypic, climatic, and soil measurements and metadata information for each testing location across years. For a subset of inbreds in 2014 and 2015, yield component phenotypes were quantified by image analysis. Data released are accompanied by README descriptions. For genotypic and phenotypic data, both raw data and a version without outliers are reported. For climatic data, a version calibrated to the nearest airport weather station and a version without outliers are reported. The 2014 and 2015 datasets are updated versions from the previously released files [1] while 2016 and 2017 datasets are newly available to the public.

Spatio-Temporal Variation in Water Uptake in Seminal and Nodal Root Systems of Barley Plants Grown in Soil

The spatial and temporal dynamics of root water uptake in nodal and seminal roots are poorly understood, especially in relation to root system development and aging. Here we non-destructively quantify 1) root water uptake and 2) root length of nodal and seminal roots of barley in three dimensions during 43 days of growth. We developed a concentric split root system to hydraulically and physically isolate the seminal and nodal root systems. Using magnetic resonance imaging (MRI), roots were visualized, root length was determined, and soil water depletion in both compartments was measured. From 19 days after germination and onwards, the nodal root system had greater water uptake compared to the seminal root system due to both greater root length and greater root conductivity. At 29 days after germination onwards, the average age of the seminal and nodal root systems was similar and no differences were observed in water uptake per root length between seminal and nodal root systems, indicating the importance of embryonic root systems for seedling establishment and nodal root systems in more mature plants. Since nodal roots perform the majority of water uptake at 29 days after germination and onwards, nodal root phenes merit consideration as a selection target to improve water capture in barley and possibly other crops.

Root cortical anatomy is associated with differential pathogenic and symbiotic fungal colonization in maize

Root anatomical phenotypes vary among maize (Zea mays) cultivars and may have adaptive value by modifying the metabolic cost of soil exploration. However, the microbial trade-offs of these phenotypes are unknown. We hypothesized that nodal roots of maize with contrasting cortical anatomy have different patterns of mutualistic and pathogenic fungal colonization. Arbuscular mycorrhizal colonization in the field and mesocosms, root rots in the field, and Fusarium verticillioides colonization in mesocosms were evaluated in maize genotypes with contrasting root cortical anatomy. Increased aerenchyma and decreased living cortical area were associated with decreased mycorrhizal colonization in mesocosm and field experiments with inbred genotypes. In contrast, mycorrhizal colonization of hybrids increased with larger aerenchyma lacunae; this increase coincided with larger root diameters of hybrid roots. F. verticillioides colonization was inversely correlated with living cortical area in mesocosm-grown inbreds, and no relation was found between root rots and living cortical area or aerenchyma in field-grown hybrids. Root rots were positively correlated with cortical cell file number and inversely correlated with cortical cell size. Mycorrhizae and root rots were inversely correlated in field-grown hybrids. We conclude that root anatomy is associated with differential effects on pathogens and mycorrhizal colonization of nodal roots in maize.

Genotypic variation and nitrogen stress effects on root anatomy in maize are node specific

Root phenotypes that improve nitrogen acquisition are avenues for crop improvement. Root anatomy affects resource capture, metabolic cost, hydraulic conductance, anchorage, and soil penetration. Cereal root phenotyping has centered on primary, seminal, and early nodal roots, yet critical nitrogen uptake occurs when the nodal root system is well developed. This study examined root anatomy across nodes in field-grown maize (Zea mays L.) hybrid and inbred lines under high and low nitrogen regimes. Genotypes with high nitrogen use efficiency (NUE) had larger root diameter and less cortical aerenchyma across nodes under stress than genotypes with lower NUE. Anatomical phenes displayed slightly hyperallometric relationships to shoot biomass. Anatomical plasticity varied across genotypes; most genotypes decreased root diameter under stress when averaged across nodes. Cortex, stele, total metaxylem vessel areas, and cortical cell file and metaxylem vessel numbers scaled strongly with root diameter across nodes. Within nodes, metaxylem vessel size and cortical cell size were correlated, and root anatomical phenotypes in the first and second nodes were not representative of subsequent nodes. Node, genotype, and nitrogen treatment affect root anatomy. Understanding nodal variation in root phenes will enable the development of plants that are adapted to low nitrogen conditions.

Laser ablation tomography for visualization of root colonization by edaphic organisms

Soil biota have important effects on crop productivity, but can be difficult to study in situ. Laser ablation tomography (LAT) is a novel method that allows for rapid, three-dimensional quantitative and qualitative analysis of root anatomy, providing new opportunities to investigate interactions between roots and edaphic organisms. LAT was used for analysis of maize roots colonized by arbuscular mycorrhizal fungi, maize roots herbivorized by western corn rootworm, barley roots parasitized by cereal cyst nematode, and common bean roots damaged by Fusarium. UV excitation of root tissues affected by edaphic organisms resulted in differential autofluorescence emission, facilitating the classification of tissues and anatomical features. Samples were spatially resolved in three dimensions, enabling quantification of the volume and distribution of fungal colonization, western corn rootworm damage, nematode feeding sites, tissue compromised by Fusarium, and as well as root anatomical phenotypes. Owing to its capability for high-throughput sample imaging, LAT serves as an excellent tool to conduct large, quantitative screens to characterize genetic control of root anatomy and interactions with edaphic organisms. Additionally, this technology improves interpretation of root-organism interactions in relatively large, opaque root segments, providing opportunities for novel research investigating the effects of root anatomical phenes on associations with edaphic organisms.

Root phenotypes for improved nutrient capture: an underexploited opportunity for global agriculture

Nutrient-efficient crops are a solution to the two grand challenges of modern agriculture: improving food security while reducing environmental impacts. The primary challenges are (1) nitrogen (N) and phosphorus (P) efficiency; (2) potassium (K), calcium (Ca), and magnesium (Mg) efficiency for acid soils; and (3) iron (Fe) and zinc (Zn) efficiency for alkaline soils. Root phenotypes are promising breeding targets for each of these. The Topsoil Foraging ideotype is beneficial for P capture and should also be useful for capture of K, Ca, and Mg in acid soils. The Steep, Cheap, and Deep ideotype for subsoil foraging is beneficial for N and water capture. Fe and Zn capture can be improved by targeting mechanisms of metal mobilization in the rhizosphere. Root hairs and phenes that reduce the metabolic cost of soil exploration should be prioritized in breeding programs. Nutrient-efficient crops should provide benefits at all input levels. Although our current understanding is sufficient to deploy root phenotypes for improved nutrient capture in crop breeding, this complex topic does not receive the resources it merits in either applied or basic plant biology. Renewed emphasis on these topics is needed in order to develop the nutrient-efficient crops urgently needed in global agriculture.