Plasticity of the Arabidopsis Root System under Nutrient Deficiencies

Plant roots show a particularly high variation in their morphological response to different nutrient deficiencies. Although such changes often determine the nutrient efficiency or stress tolerance of plants, it is surprising that a comprehensive and comparative analysis of root morphological responses to different nutrient deficiencies has not yet been conducted. Since one reason for this is an inherent difficulty in obtaining nutrient-deficient conditions in agar culture, we first identified conditions appropriate for producing nutrient-deficient plants on agar plates. Based on a careful selection of agar specifically for each nutrient being considered, we grew Arabidopsis (Arabidopsis thaliana) plants at four levels of deficiency for 12 nutrients and quantified seven root traits. In combination with measurements of biomass and elemental concentrations, we observed that the nutritional status and type of nutrient determined the extent and type of changes in root system architecture (RSA). The independent regulation of individual root traits further pointed to a differential sensitivity of root tissues to nutrient limitations. To capture the variation in RSA under different nutrient supplies, we used principal component analysis and developed a root plasticity chart representing the overall modulations in RSA under a given treatment. This systematic comparison of RSA responses to nutrient deficiencies provides a comprehensive view of the overall changes in root plasticity induced by the deficiency of single nutrients and provides a solid basis for the identification of nutrient-sensitive steps in the root developmental program.Plant survival and performance are highly dependent on the plant’s ability to efficiently explore the soil in the search for water and minerals. Thus, root growth and architecture are extremely relevant for the plant’s adaptation to the growth medium, as they determine the soil volume that a plant is able to explore at a given time. Root system architecture (RSA) represents the spatial arrangement of roots of different ages and orders (Lynch, 1995; Osmont et al., 2007) and is determined by genetic factors and the integration of environmental cues (Malamy, 2005). The genetic component determines the fundamental morphology and blueprint of a plant’s root system, whereas environmental cues shape root architecture by modifying the intrinsic genetic program. The existence of this additional level of regulation allows plants to display a high level of root plasticity, which reflects the shape, three-dimensional distribution, branching pattern, and age of the primary and postembryonically generated roots (Pacheco-Villalobos and Hardtke, 2012). The dynamic modulation of RSA is based on the intrinsic developmental nature of the different components of the root system. In fact, the primary root (PR) is established during embryogenesis, while the lateral roots (LRs) that originate from the PR develop postembryonically (Osmont et al., 2007; Péret et al., 2009). These highly dynamic changes in the overall RSA throughout time finally determine root plasticity and allow plants to efficiently adapt to environmental constraints.Nutrient availability can exert a profound impact on RSA by altering the number, length, angle, and diameter of roots and root hairs (for review, see Forde and Lorenzo, 2001; López-Bucio et al., 2003; Malamy, 2005; Osmont et al., 2007). In fact, plants can respond to the heterogenous availability of resources by allocating roots where the most favorable conditions are found (Zhang and Forde, 1998; Linkohr et al., 2002; Remans et al., 2006; Lima et al., 2010; Giehl et al., 2012). When grown under limited phosphorus (P) availability, roots exhibit a shallower architecture that results from the inhibition of PR elongation and the concomitant increase in LR formation (Williamson et al., 2001; López-Bucio et al., 2002; Sanchez-Calderon et al., 2005). Such an architectural rearrangement of the root is thought to improve the plant’s ability to forage P from the usually P-enriched topsoil horizon (Lynch and Brown, 2001; Rubio et al., 2003; Zhu et al., 2005). In contrast to low P, reduced nitrogen (N) availability stimulates PR and particularly LR elongation but not LR initiation (Linkohr et al., 2002; López-Bucio et al., 2003). However, it is noteworthy that under severe N shortage, LR formation is almost completely absent (Krouk et al., 2010), suggesting that plants require a certain level of N to sustain an active foraging strategy. These examples indicate that the availability of different nutrients can evoke distinct effects on RSA that depend upon which nutrient is supplied and the concentration of the supplied nutrient.Unfortunately, for the majority of the nutrients, a more detailed analysis of the architectural modifications under deficient conditions is still missing. In fact, most studies describe the effect of nutrient deficiencies on root growth and development only in terms of root biomass or total root length (Hermans and Verbruggen, 2005; Hermans et al., 2006; Richard-Molard et al., 2008; Jung et al., 2009; Cailliatte et al., 2010). Thus, important features of the root system are not comprehensible from these rather basic measurements. The characterization of RSA in more detail appears justified due to the positive correlations found between single root characteristics and plant yield, especially when the supply of water or mineral resources was limited (Landi et al., 2002; Tuberosa et al., 2002; Manschadi et al., 2006; Kirkegaard et al., 2007; Steele et al., 2007). Although a large number of studies have been conducted on the root development of grasses (Hochholdinger and Tuberosa, 2009; Iyer-Pascuzzi et al., 2010; Pacheco-Villalobos and Hardtke, 2012), our understanding of the molecular players involved in the regulation of root growth and development has benefited most from studies of the reference plant Arabidopsis (Arabidopsis thaliana) grown under controlled conditions to minimize variability. However, imposing consistent nutrient deficiencies presents an experimental challenge as long as plants are grown on agar medium, which is the method of choice to preserve the spatial arrangement of the root system and access a larger number of root traits.A major drawback of agar and agarose media is their inherent nutrient load, such that traces of nutrient contamination must often be made unavailable to plants, for example by adding chelating agents to lower the free activities of micronutrients (Bell et al., 1991; Yang et al., 1994; Rengel, 1999). Additionally, in many cases, symptoms of deficiency are only observed in mutants impaired in the uptake of the nutrient in question (Tomatsu et al., 2007; Mills et al., 2008; Assunção et al., 2010). In general, gelling agents may contribute considerable amounts of nutrients (Debergh, 1983; Scholten and Pierik, 1998), hampering the occurrence of deficiency for specific nutrients (Jain et al., 2009). Thus, it becomes crucial to select the most suitable gelling agent when particular nutrient deficiencies are to be obtained. This is particularly relevant as strategies depending upon the use of gelling media are being developed to overcome the bottleneck that often limits RSA traits from being characterized in high-throughput phenotyping studies (Iyer-Pascuzzi et al., 2010; Clark et al., 2011).In our approach to compare RSA under different nutrient deficiencies in Arabidopsis plants grown on solid medium, we first identified the most appropriate conditions for producing nutrient-deficient plants on agar plates. Once identified, these conditions allowed us to characterize the effects of 12 deficiencies at four intensity levels on the RSA by measuring seven root traits. These measurements, in combination with biomass and elemental concentrations, allowed us to determine the nutrient-specific effects on particular parameters of the RSA and thus to describe the root plasticity of Arabidopsis and analyze the underlying traits under different nutrient deficiencies.     

Quantitative Trait Locus Mapping Reveals Regions of the Maize Genome Controlling Root System Architecture

The quest to determine the genetic basis of root system architecture (RSA) has been greatly facilitated by recent developments in root phenotyping techniques. Methods that are accurate, high throughput, and control for environmental factors are especially attractive for quantitative trait locus mapping. Here, we describe the adaptation of a nondestructive in vivo gel-based root imaging platform for use in maize (Zea mays). We identify a large number of contrasting RSA traits among 25 founder lines of the maize nested association mapping population and locate 102 quantitative trait loci using the B73 (compact RSA) × Ki3 (exploratory RSA) mapping population. Our results suggest that a phenotypic tradeoff exists between small, compact RSA and large, exploratory RSA.Maize (Zea mays) serves a key role in food, feedstock, and biofuel production throughout the world. To date, maize improvement through breeding has kept pace with the increasing demand for this crop (faostat3.fao.org). This feat has been accomplished through the utilization of the tremendous genetic diversity in maize (Flint-Garcia et al., 2005; Jiao et al., 2012), but increasing environmental pressures and a growing global population will require unprecedented gains in yield in the coming years. In the last decade, researchers have begun to explore the possibility of yield improvements through the manipulation of root systems, for example through breeding for roots better able to cope with drought (Uga et al., 2013) and flooding (Jackson and Armstrong, 1999), the use of plant growth-promoting rhizobacteria (Silby et al., 2009), or increasing nutrient use efficiency (Garnett et al., 2009). The potential of belowground solutions to enhanced plant productivity has driven the development of numerous methodologies for phenotyping root system architecture (RSA), which is the spatial organization of the plant’s root system.Several methods ranging from techniques adapted from medical imaging, such as x-ray tomography (Hargreaves et al., 2008) and combined positron emission tomography-magnetic resonance imaging (Jahnke et al., 2009), to refined versions of classical methods, such as field excavations (Trachsel et al., 2010) and pouch systems (Le Marié et al., 2014), have been used in attempts to understand the phenotypic consequences of genetic and environmental variation on root traits. Each root-phenotyping method has its advantages and disadvantages. Although the medical imaging-based techniques can produce highly detailed representations of roots, they are also very time consuming and require specialized equipment. Excavations, although more easily scaled to higher throughput and not requiring special equipment, are destructive and offer only coarse measurements of RSA. An alternative method for root phenotyping based on an optically clear gel substrate strikes an effective balance between throughput and detail, using a simple digital camera while maintaining precise control over environmental conditions. This platform has been used to quantify and classify distinctive root architectures from 12 rice (Oryza sativa) genotypes (Iyer-Pascuzzi et al., 2010), conduct a quantitative trait locus (QTL) mapping study of rice root traits in three dimensions (Topp et al., 2013), study interspecific and intraspecific rice root interactions (Fang et al., 2013), and quantify contributions of different root types to overall RSA (Clark et al., 2011).Here, we describe the adaptation of this gel imaging platform for use with the large maize root system. We used the platform to quantify the phenotypic diversity of RSA among 25 of the 26 nested association mapping (NAM) founder lines, which encompass a wide spectrum of maize genetic diversity (Yu et al., 2008; McMullen et al., 2009). We found that these lines exhibit diverse RSAs, ranging from small and compact to large and exploratory, suggesting tradeoffs between different types of architectures. In order to identify genetic loci that control maize RSA traits, we characterized a subpopulation that best represented the contrast between the compact and exploratory RSAs. We phenotyped the B73 (compact) × Ki3 (exploratory) recombinant inbred line (RIL) NAM subpopulation for 19 RSA traits at three time points (Topp et al., 2013). These data were used to map 102 QTLs that localized to nine genomic clusters. We found high heritability and large-effect QTLs for most traits, in contrast to maize flowering time QTLs (Buckler et al., 2009). Additionally, several of our QTL clusters overlapped with meta-QTLs for yield traits (Tuberosa et al., 2003; Semagn et al., 2013) as well as novel and previously unreported loci, suggesting that this system can provide a time- and cost-effective means to identify genes controlling root architecture in maize.     

Capturing Arabidopsis Root Architecture Dynamics with root-fit Reveals Diversity in Responses to Salinity

The plant root is the first organ to encounter salinity stress, but the effect of salinity on root system architecture (RSA) remains elusive. Both the reduction in main root (MR) elongation and the redistribution of the root mass between MRs and lateral roots (LRs) are likely to play crucial roles in water extraction efficiency and ion exclusion. To establish which RSA parameters are responsive to salt stress, we performed a detailed time course experiment in which Arabidopsis (Arabidopsis thaliana) seedlings were grown on agar plates under different salt stress conditions. We captured RSA dynamics with quadratic growth functions (root-fit) and summarized the salt-induced differences in RSA dynamics in three growth parameters: MR elongation, average LR elongation, and increase in number of LRs. In the ecotype Columbia-0 accession of Arabidopsis, salt stress affected MR elongation more severely than LR elongation and an increase in LRs, leading to a significantly altered RSA. By quantifying RSA dynamics of 31 different Arabidopsis accessions in control and mild salt stress conditions, different strategies for regulation of MR and LR meristems and root branching were revealed. Different RSA strategies partially correlated with natural variation in abscisic acid sensitivity and different Na⁺/K⁺ ratios in shoots of seedlings grown under mild salt stress. Applying root-fit to describe the dynamics of RSA allowed us to uncover the natural diversity in root morphology and cluster it into four response types that otherwise would have been overlooked.Salt stress is known to affect plant growth and productivity as a result of its osmotic and ionic stress components. Osmotic stress imposed by salinity is thought to act in the early stages of the response, by reducing cell expansion in growing tissues and causing stomatal closure to minimize water loss. The build-up of ions in photosynthetic tissues leads to toxicity in the later stages of salinity stress and can be reduced by limiting sodium transport into the shoot tissue and compartmentalization of sodium ions into the root stele and vacuoles (Munns and Tester, 2008). The effect of salt stress on plant development was studied in terms of ion accumulation, plant survival, and signaling (Munns et al., 2012; Hasegawa, 2013; Pierik and Testerink, 2014). Most studies focus on traits in the aboveground tissues, because minimizing salt accumulation in leaf tissue is crucial for plant survival and its productivity. This approach has led to the discovery of many genes underlying salinity tolerance (Munns and Tester, 2008; Munns et al., 2012; Hasegawa, 2013; Maathuis, 2014). Another way to estimate salinity stress tolerance is by studying the rate of main root (MR) elongation of seedlings transferred to medium supplemented with high salt concentration. This is how Salt Overly Sensitive mutants were identified, being a classical example of genes involved in salt stress signaling and tolerance (Hasegawa, 2013; Maathuis, 2014). The success of this approach is to be explained by the important role that the root plays in salinity tolerance. Roots not only provide anchorage and ensure water and nutrient uptake, but also act as a sensory system, integrating changes in nutrient availability, water content, and salinity to adjust root morphology to exploit available resources to the maximum capacity (Galvan-Ampudia et al., 2013; Gruber et al., 2013). Understanding the significance of environmental modifications of root system architecture (RSA) for plant productivity is one of the major challenges of modern agriculture (de Dorlodot et al., 2007; Den Herder et al., 2010; Pierik and Testerink, 2014).The RSA of dicotyledonous plants consists of an embryonically derived MR and lateral roots (LRs) that originate from xylem pole pericycle cells of the MR, or from LRs in the case of higher-order LRs. Root growth and branching is mainly guided through the antagonistic action of two plant hormones: auxin and cytokinins (Petricka et al., 2012). Under environmental stress conditions, the synthesis of abscisic acid (ABA), ethylene, and brassinosteroids is known to be induced and to modulate the growth of MRs and LRs (Achard et al., 2006; Osmont et al., 2007; Achard and Genschik, 2009; Duan et al., 2013; Geng et al., 2013). In general, lower concentrations of salt were observed to slightly induce MR and LR elongation, whereas higher concentrations resulted in decreased growth of both MRs and LRs (Wang et al., 2009; Zolla et al., 2010). The reduction of growth is a result of the inhibition of cell cycle progression and a reduction in root apical meristem size (West et al., 2004). However, conflicting results were presented for the effect of salinity on lateral root density (LRD; Wang et al., 2009; Zolla et al., 2010; Galvan-Ampudia and Testerink, 2011). Some studies suggest that mild salinity enhances LR initiation or emergence events, thereby affecting patterning, whereas other studies imply that salinity arrests LR development. The origin of those contradictory observations could be attributable to studying LR initiation and density at single time points, rather than observing the dynamics of LR development, because LR formation changes as a function of root growth rate (De Smet et al., 2012). The dynamics of LR growth and development were characterized previously for the MR region formed before the salt stress exposure, identifying the importance of ABA in early growth arrest of postemerged LRs in response to salt stress (Duan et al., 2013). The effect of salt on LR emergence and initiation was found to differ for MR regions formed prior and subsequent to salinity exposure (Duan et al., 2013), consistent with LR patterning being determined at the root tip (Moreno-Risueno et al., 2010). Yet the effect of salt stress on the reprogramming of the entire RSA on a longer timescale remains elusive.Natural variation in Arabidopsis (Arabidopsis thaliana) is a great source for dissecting the genetic components underlying phenotypic diversity (Trontin et al., 2011; Weigel, 2012). Genes underlying phenotypic plasticity of RSA to environmental stimuli were also found to have high allelic variation leading to differences in root development between different Arabidopsis accessions (Rosas et al., 2013). Supposedly, genes responsible for phenotypic plasticity of the root morphology to different environmental conditions are under strong selection for adaptation to local environments. Various populations of Arabidopsis accessions were used to study natural variation in ion accumulation and salinity tolerance (Rus et al., 2006; Jha et al., 2010; Katori et al., 2010; Roy et al., 2013). In addition, a number of studies focusing on the natural variation in RSA have been published, identifying quantitative trait loci and allelic variation for genes involved in RSA development under control conditions (Mouchel et al., 2004; Meijón et al., 2014) and nutrient-deficient conditions (Chevalier et al., 2003; Gujas et al., 2012; Gifford et al., 2013; Kellermeier et al., 2013; Rosas et al., 2013). Exploring natural variation not only expands the knowledge of genes and molecular mechanisms underlying biological processes, but also provides insight on how plants adapt to challenging environmental conditions (Weigel, 2012) and whether the mechanisms are evolutionarily conserved. The early growth arrest of newly emerged LRs upon exposure to salt stress was observed to be conserved among the most commonly used Arabidopsis accessions Columbia-0 (Col-0), Landsberg erecta, and Wassilewskija (Ws; Duan et al., 2013). By studying salt stress responses of the entire RSA and a wider natural variation in root responses to stress, one could identify new morphological traits that are under environmental selection and possibly contribute to stress tolerance.In this work, we not only identify the RSA components that are responsive to salt stress, but we also describe the natural variation in dynamics of salt-induced changes leading to redistribution of root mass and different root morphology. The growth dynamics of MRs and LRs under different salt stress conditions were described by fitting a set of quadratic growth functions (root-fit) to individual RSA components. Studying salt-induced changes in RSA dynamics of 31 Arabidopsis accessions revealed four major strategies conserved among the accessions. Those four strategies were due to differences in salt stress sensitivity of individual RSA components (i.e. growth rates of MRs and LRs, and increases in the number of emerged LRs). This diversity in root morphology responses caused by salt stress was observed to be partially associated with differences in ABA, but not ethylene sensitivity. In addition, we observed that a number of accessions exhibiting a relatively strong inhibition of LR elongation showed a smaller increase in the Na⁺/K⁺ ratio in shoot tissue after exposure to salt stress. Our results imply that different RSA strategies identified in this study reflect diverse adaptations to different soil conditions and thus might contribute to efficient water extraction and ion compartmentalization in their native environments.     

RootScape: A Landmark-Based System for Rapid Screening of Root Architecture in Arabidopsis

The architecture of plant roots affects essential functions including nutrient and water uptake, soil anchorage, and symbiotic interactions. Root architecture comprises many features that arise from the growth of the primary and lateral roots. These root features are dictated by the genetic background but are also highly responsive to the environment. Thus, root system architecture (RSA) represents an important and complex trait that is highly variable, affected by genotype × environment interactions, and relevant to survival/performance. Quantification of RSA in Arabidopsis (Arabidopsis thaliana) using plate-based tissue culture is a very common and relatively rapid assay, but quantifying RSA represents an experimental bottleneck when it comes to medium- or high-throughput approaches used in mutant or genotype screens. Here, we present RootScape, a landmark-based allometric method for rapid phenotyping of RSA using Arabidopsis as a case study. Using the software AAMToolbox, we created a 20-point landmark model that captures RSA as one integrated trait and used this model to quantify changes in the RSA of Arabidopsis (Columbia) wild-type plants grown under different hormone treatments. Principal component analysis was used to compare RootScape with conventional methods designed to measure root architecture. This analysis showed that RootScape efficiently captured nearly all the variation in root architecture detected by measuring individual root traits and is 5 to 10 times faster than conventional scoring. We validated RootScape by quantifying the plasticity of RSA in several mutant lines affected in hormone signaling. The RootScape analysis recapitulated previous results that described complex phenotypes in the mutants and identified novel gene × environment interactions.Roots have a crucial impact on plant survival because of their major functions: anchorage of the plant in the soil, water and nutrient acquisition, and symbiotic interaction with other organisms (Den Herder et al., 2010). One important characteristic of root systems is the manner in which the primary and lateral roots comprise the superstructure or root architecture. Root architecture is an ideal system for studying developmental plasticity, as it continually integrates intrinsic and environmental responses (Malamy, 2005), which represents a vital and dynamic component of agricultural productivity (Lynch, 1995).Root system architecture (RSA) is defined as the spatial configuration of the roots in their environment (Lynch, 1995). The complexity of RSA was initially appreciated several decades ago, and terms like morphology, topology, distribution, and architecture were often used to describe the nature of RSA (Fitter, 1987; Fitter and Stickland, 1991; Lynch, 1995). These early reports argued that simple traits like root mass are insufficient to describe roots, because they do not capture the spatial configuration of roots in the soil, which is critical to plant performance (Fitter and Stickland, 1991). Root systems are integrated organs that adopt specific architectures to maximal foraging of the heterogeneous soil environment in different ways (Fitter, 1987; Fitter and Stickland, 1991; Lynch, 1995). More recently, new approaches have incorporated the measurement of many individual developmental traits that together comprise RSA (De Smet et al., 2012; Dubrovsky and Forde, 2012). For example, one recent report identified three fundamental components of RSA in generating complex topologies, including the contribution of lateral axes to branching, the rate and path of growth of the axis, and the increase in root surface area (Topp and Benfey, 2012). Thus, RSA is an important and complex trait that requires convenient measurement methods for rapid screening of diverse plant mutants and genotypes.With increasing research in RSA in the genetically tractable model plant Arabidopsis (Arabidopsis thaliana), the need for high-throughput methods of root phenotyping has dramatically increased over the years. Consequently, different methods and approaches have been developed in order to address this demand. Currently, three major approaches for phenotyping RSA are used (for review, see Zhu et al., 2011; De Smet et al., 2012). The first group of methods uses classical measures of RSA, which involve measurements of individual root traits. These methods often use software to manually draw the RSA onto digital two-dimensional images to quantify root length and number (Abramoff et al., 2004; http://www.machinevision.nl). These traditional methods provide the most accurate measurements of the root system but have a major disadvantage in being extremely time consuming.The second group of methods utilizes advanced semiautomated software for RSA measurements like EZ-Rhizo (Armengaud et al., 2009). EZ-Rhizo also uses digital two-dimensional images of plants grown on vertical plates (similar to the classical methods above) but is faster and produces different traits and basic statistics. The method works best when root features do not physically overlap, but we have found root overlap to be common when working with Arabidopsis plants older than 10 d. Other recent programs also provide semiautomated analysis of RSA, including RootReader2D (http://www.plantmineralnutrition.net/rootreader.htm) and SmartRoot (Lobet et al., 2011). However, while completely automated detection is potentially the highest throughput, we found that the root surface detection step is frequently prone to failure when using both of these programs, even after considerable adjustment by the user, where root features are missed or background noise is incorrectly labeled as roots.Finally, in a third group, recent developments include three-dimensional analysis of RSA of plants grown on transparent gel cylinders or in soil. The three-dimensional gel-based imaging approach is reported to be suitable for high-throughput phenotyping (Iyer-Pascuzzi et al., 2010). However, this approach requires special equipment, and imaging the root system of single plants can take 10 min (Iyer-Pascuzzi et al., 2010). X-ray computed tomography (Perret et al., 2007; Tracy et al., 2010) and magnetic resonance imaging (Van As, 2007) also provide highly detailed three-dimensional RSA analysis, but they require long scanning times and are extremely expensive and inaccessible. Most laboratories still utilize relatively convenient, inexpensive, and rapid two-dimensional phenotypic characterization of RSA, at least for initial screening purposes.The aim of this work is to address the need for a simple method to measure many different aspects of root architecture for high-throughput laboratory screening of mutants and genotypes in Arabidopsis. Here, we describe a landmark-based allometric (size and shape) approach called RootScape, a user-friendly software platform that enables rapid, comprehensive, and integrative phenotyping of the RSA in Arabidopsis. Unlike recent methods that collect information on different root traits to describe the RSA, RootScape places user-defined root landmarks on a two-dimensional grid to measure root architecture as a single integrated root system. The method employs rapid manual placement of root system landmarks. This manual step avoids one of the most problematic steps in automated image analysis (recognition of the root surface), providing a simple tool that does not require image processing. This method uses simple, two-dimensional digital images of the root system and a 20-point landmark model created in AAMToolbox, a freely available MATLAB plugin. While in-depth developmental analysis of root systems will often require knowing the contribution of individual traits, RootScape is a rapid method to access the holistic contribution of many individual root traits to RSA and to capture the overall property of the spatial configuration of roots in the soil (Fitter and Stickland, 1991). To demonstrate its utility, we used RootScape to quantify the root plasticity of Arabidopsis plants (Columbia [Col-0]) grown on four different media and compared the RootScape results with conventional measurements of individual root traits captured using the Optimas6 image-analysis software or Image J (Abramoff et al., 2004). This analysis showed that by measuring integrative root traits using RootScape, we could capture the vast majority of the individual trait variation, as verified by multiple regression analysis. Additionally, we tested the ability of RootScape to quantify the plasticity response in Arabidopsis mutants defective in hormone signaling. For this analysis, wild-type Col-0 and three hormone signaling mutants (auxin-resistant4 [axr4], abscisic acid insensitive4 [abi4], and cytokinin response1 [cre1]) were treated with auxin, cytokinin, or abscisic acid (ABA) versus controls. Statistical analyses (ANOVA/multivariate ANOVA [MANOVA]) allowed us to confirm most of the previously known interactions of genotype with these distinct environments and to potentially identify novel ones. Thus, we demonstrate that RootScape can be used as a rapid and efficient approach for quantifying the plasticity of the RSA in mutant (or ecotype) backgrounds of Arabidopsis and can identify new conditional root phenotypes.     

Focus Issue on Roots: Duplicate and Conquer: Multiple Homologs of PHOSPHORUS-STARVATION TOLERANCE1 Enhance Phosphorus Acquisition and Sorghum Performance on Low-Phosphorus Soils

Low soil phosphorus (P) availability is a major constraint for crop production in tropical regions. The rice (Oryza sativa) protein kinase, PHOSPHORUS-STARVATION TOLERANCE1 (OsPSTOL1), was previously shown to enhance P acquisition and grain yield in rice under P deficiency. We investigated the role of homologs of OsPSTOL1 in sorghum (Sorghum bicolor) performance under low P. Association mapping was undertaken in two sorghum association panels phenotyped for P uptake, root system morphology and architecture in hydroponics and grain yield and biomass accumulation under low-P conditions, in Brazil and/or in Mali. Root length and root surface area were positively correlated with grain yield under low P in the soil, emphasizing the importance of P acquisition efficiency in sorghum adaptation to low-P availability. SbPSTOL1 alleles reducing root diameter were associated with enhanced P uptake under low P in hydroponics, whereas Sb03g006765 and Sb03g0031680 alleles increasing root surface area also increased grain yield in a low-P soil. SbPSTOL1 genes colocalized with quantitative trait loci for traits underlying root morphology and dry weight accumulation under low P via linkage mapping. Consistent allelic effects for enhanced sorghum performance under low P between association panels, including enhanced grain yield under low P in the soil in Brazil, point toward a relatively stable role for Sb03g006765 across genetic backgrounds and environmental conditions. This study indicates that multiple SbPSTOL1 genes have a more general role in the root system, not only enhancing root morphology traits but also changing root system architecture, which leads to grain yield gain under low-P availability in the soil.Increasing food production is one of the major global challenges in dealing with continuously growing population and food consumption (Godfray et al., 2010). One of the major obstacles to improve crop production in tropical regions is phosphorus (P) deficiency caused by P fixation in the soil clays. P is one of the most important plant nutrients, contributing approximately 0.2% of a plant’s dry weight, and is a component of key organic molecules such as nucleic acids, phospholipids, and ATP (Schachtman et al., 1998). On tropical soils, even when the total amount of soil P is high, its bioavailability is low due to P fixation by aluminum and iron oxides in clay minerals (Marschner, 1995) and immobilization into organic forms (Schachtman et al., 1998). Approximately half of the world’s agricultural lands occurs on low-P soils (Lynch, 2011); hence, crop adaptation to P insufficiency should be a major breeding target to enable sustainable agricultural production worldwide. In addition, because phosphate rock fertilizer is a nonrenewable resource that is being depleted by agricultural demands, increasing fertilizer prices negatively impact agriculture, particularly for small-holder farmers in developing countries in the tropics and subtropics (Cordell et al., 2009; Sattari et al., 2012). In sorghum (Sorghum bicolor), breeding strategies for low-P adaptation have been developed based on multienvironment trials in West Africa, indicating the importance of undertaking selection in low-P soil conditions (Leiser et al., 2012a, 2012b). Therefore, developing crops with greater ability to grow and maintain satisfactory yields on soils with reduced P availability is expected to substantially improve food security worldwide.Tolerance to P deficiency in plants can be achieved by mechanisms underlying both P acquisition and P internal utilization efficiency (Parentoni and Souza Junior, 2008). One of the major mechanisms that plants have evolved to overcome low-P availability is to maximize the ability of the roots to acquire and absorb P from the soil. Plants can mobilize P through the exudation of organic acids, acid phosphatases, and ribonucleases, resulting in enhanced P availability and uptake (Hinsinger, 2001; Ryan et al., 2001; Dakora and Phillips, 2002; Hammond and White, 2008; Ma et al., 2009; Pang et al., 2009). Another strategy to cope with low-P availability is to increase the soil volume accessed by root systems by forming mycorrhizal symbioses (Li et al., 2012; Smith and Smith, 2012; Rai et al., 2013). Due to low-P mobility on tropical soils, changes in root architecture and morphology enhance P uptake by facilitating soil exploration (Williamson et al., 2001; Ho et al., 2005; Walk et al., 2006; Svistoonoff et al., 2007; Lynch, 2011; Ingram et al., 2012; Niu et al., 2013). Root structural changes leading to higher P uptake include increased root hair growth (Yan et al., 2004; Haling et al., 2013; Lan et al., 2013) and length and enhancing lateral root over primary root growth (Williamson et al., 2001; Wang et al., 2013). In addition, increased root surface area is achieved by a combination of reduced root diameter and enhanced elongation of relatively thinner roots (Fitter et al., 2002). There is both intraspecific and interspecific genetic variation for P deficiency tolerance in crop species (Lynch and Brown, 2001, 2012; Mudge et al., 2002; Paszkowski et al., 2002; Rausch and Bucher, 2002; Huang et al., 2011; Zhang et al., 2011; Leiser et al., 2014a) that can be explored to develop P-efficient cultivars.In rice (Oryza sativa), Phosphorus uptake1 (Pup1), a major quantitative trait locus (QTL) for P deficiency tolerance donated by an aus-type Indian variety, Kasalath, was mapped to the long arm of chromosome 12 (Ni et al., 1998; Wissuwa et al., 1998, 2002; Heuer et al., 2009). Near-isogenic lines bearing the Kasalath allele at Pup1 showed 3-fold higher P uptake and grain yield in low-P trials compared with the recurrent parent, cv Nipponbare, which is intolerant to P starvation (Wissuwa and Ae, 2001). Following high-resolution mapping of Pup1, comparative sequence analyses of homologous bacterial artificial chromosomes showed that a Kasalath genomic fragment contained several genes not present in cv Nipponbare, highlighting an approximately 90-kb deletion in the cv Nipponbare reference genome that encompassed the Pup1 locus (Heuer et al., 2009). Within this insertion/deletion, OsPupK46-2, a gene encoding a Ser/Thr kinase of the Receptor-like Protein Kinase LRK10L-2 subfamily, was found to enhance grain yield and P uptake in rice lines overexpressing this gene, indicating that this protein kinase underlies the Pup1 locus (Gamuyao et al., 2012). OsPupK46-2, which is now designated PHOSPHORUS-STARVATION TOLERANCE1 (OsPSTOL1), was found to be up-regulated in the root tissues of tolerant near-isogenic lines under P-deficient conditions and was shown to increase P uptake by a physiological mechanism based on the enhancement of early root growth and development. Furthermore, lines overexpressing OsPupK46-2 showed an approximately 30% grain yield increase in comparison with the null lines, suggesting that PSTOL1 has potential for molecular breeding applications to improve crop performance under low-P conditions. Consistent with the proposed physiological mechanism underlying OsPSTOL1, the superior performance of the transgenic lines was related to enhanced root dry weight, root length, and root surface area (Gamuyao et al., 2012).Sorghum is the world’s fifth most important cereal crop and is a staple food for more than half a billion people. It is widely adapted to harsh environmental conditions, and more specifically, to arid and semiarid regions of the world (Doumbia et al., 1993, 1998). It has been estimated that rice diverged from its most recent common ancestor with sorghum and maize (Zea mays) approximately 50 million years ago (Kellogg, 1998; Paterson et al., 2000, 2004; Paterson, 2008). About 60% of the genes in the sorghum genome are located in syntenic regions to rice (Paterson et al., 2009), emphasizing the potential for using comparative genomics for cross-species identification of genes underlying abiotic stress tolerance in the grass family. Here, we applied association analysis to specifically study the role of sorghum homologs of rice OsPSTOL1 in tolerance to P starvation in sorghum. Single-nucleotide polymorphisms (SNPs) within PSTOL1 homologs in sorghum, collectively designated SbPSTOL1, were significantly associated with grain yield under low-P conditions and also root morphology and root system architecture (RSA) traits phenotyped from hydroponically grown plants. Under low P, SbPSTOL1 genes increased biomass accumulation and P content in the African landrace panel and grain yield in the sorghum association panel phenotyped in a low-P Brazilian soil. This suggests a stable effect across environments and sorghum genotypes that potentially can be used for molecular breeding applications. QTL mapping with a large sorghum recombinant inbred line population was used to validate the association results, indicating that SbPSTOL1 homologs colocalize with QTLs related to root morphology and performance under low P. Our results indicate that SbPSTOL1 homologs have the ability to enhance P uptake and sorghum performance in low-P soils by a mechanism related not only to early root growth enhancement, as was the case for rice OsPSTOL1, but also by modulating RSA.     

Natural Variation of Arabidopsis Root Architecture Reveals Complementing Adaptive Strategies to Potassium Starvation

Root architecture is a highly plastic and environmentally responsive trait that enables plants to counteract nutrient scarcities with different foraging strategies. In potassium (K) deficiency (low K), seedlings of the Arabidopsis (Arabidopsis thaliana) reference accession Columbia (Col-0) show a strong reduction of lateral root elongation. To date, it is not clear whether this is a direct consequence of the lack of K as an osmoticum or a triggered response to maintain the growth of other organs under limiting conditions. In this study, we made use of natural variation within Arabidopsis to look for novel root architectural responses to low K. A comprehensive set of 14 differentially responding root parameters were quantified in K-starved and K-replete plants. We identified a phenotypic gradient that links two extreme strategies of morphological adaptation to low K arising from a major tradeoff between main root (MR) and lateral root elongation. Accessions adopting strategy I (e.g. Col-0) maintained MR growth but compromised lateral root elongation, whereas strategy II genotypes (e.g. Catania-1) arrested MR elongation in favor of lateral branching. K resupply and histochemical staining resolved the temporal and spatial patterns of these responses. Quantitative trait locus analysis of K-dependent root architectures within a Col-0 × Catania-1 recombinant inbred line population identified several loci each of which determined a particular subset of root architectural parameters. Our results indicate the existence of genomic hubs in the coordinated control of root growth in stress conditions and provide resources to facilitate the identification of the underlying genes.The ability of plants to actively respond to nutrient scarcity with changes in root architecture is a fascinating phenomenon. Advances in root research and breeding efforts that focus on the enhancement of root traits have been recognized as principal goals to ensure those high yields necessary to feed an ever-growing human population (Hammer et al., 2009; Den Herder et al., 2010). Indeed, understanding the adaptations of root systems to environmental factors has been pointed out as a key issue in modern agriculture (Den Herder et al., 2010).Potassium (K) is the quantitatively most important cation for plant growth, as it serves as the major osmoticum for cell expansion (Leigh and Wyn Jones, 1984; Amtmann et al., 2006). Moreover, K is essential for many cellular and tissue processes, such as enzymatic activity, transport of minerals and metabolites, and regulation of stomatal aperture (Amtmann et al., 2006). Even in fertilized fields, rapid K uptake by plants can lead to K shortage in the root environment, especially early in the growth season. Root adaptations to K deficiency (low K) take place at the physiological (Armengaud et al., 2004; Shin and Schachtman, 2004; Alemán et al., 2011), metabolic (Armengaud et al., 2009a), and morphological levels. In a classic study, Drew (1975) showed an increase in overall lateral root (LR) growth of barley seedlings, even when K was supplied only to parts of the root system. Conversely, a typical response of Arabidopsis (Arabidopsis thaliana) Columbia (Col-0) seedlings to low K is the drastic reduction of LR elongation (Armengaud et al., 2004; Shin and Schachtman, 2004). Conflicting data have been published on the effect of low K on main root (MR) growth in the same species, ranging from no effect (Shin and Schachtman, 2004) to impaired MR elongation (Jung et al., 2009; Kim et al., 2010). Some components involved in K starvation responses have been identified, such as jasmonates (Armengaud et al., 2004, 2010), reactive oxygen species (Shin and Schachtman, 2004), and ethylene (Jung et al., 2009). However, the molecular identity of a root K sensor acting at the base of the signaling cascade is so far unknown.Genetic variation within species is a useful resource to dissect the genetic components determining phenotypes (Koornneef et al., 2004; Trontin et al., 2011; Weigel, 2012). Natural variation within Arabidopsis has been the basis for many studies on plant morphology, physiology, and development as well as stress response (Alonso-Blanco et al., 2009; Weigel, 2012). Natural variation of root traits such as primary root length (Mouchel et al., 2004; Loudet et al., 2005; Sergeeva et al., 2006), LR length (Loudet et al., 2005), and total root size (Fitz Gerald et al., 2006) have pinpointed genomic regions underlying the phenotypic variation via mapping of quantitative trait loci (QTLs) as a first step toward the identification of novel regulatory genes (Mouchel et al., 2004). This strategy has also been applied to environmental responses, such as growth responses to phosphate starvation (Reymond et al., 2006; Svistoonoff et al., 2007). However, despite their importance for plant growth and their strong effect on overall root architecture, root responses to K deficiency have not been genetically dissected.Here, we show that Arabidopsis accessions follow different strategies to adapt to K starvation. We present the quantification of a comprehensive set of root architectural parameters of Arabidopsis grown in K-sufficient and K-deficient media and the identification of genetic loci, each of which determines the response of a distinct subset of root architectural parameters to K starvation.     

Focus Issue on Roots: Root Cortical Aerenchyma Enhances Nitrogen Acquisition from Low-Nitrogen Soils in Maize

Suboptimal nitrogen (N) availability is a primary constraint for crop production in developing nations, while in rich nations, intensive N fertilization carries substantial environmental and economic costs. Therefore, understanding root phenes that enhance N acquisition is of considerable importance. Structural-functional modeling predicts that root cortical aerenchyma (RCA) could improve N acquisition in maize (Zea mays). We evaluated the utility of RCA for N acquisition by physiological comparison of maize recombinant inbred lines contrasting in RCA grown under suboptimal and adequate N availability in greenhouse mesocosms and in the field in the United States and South Africa. N stress increased RCA formation by 200% in mesocosms and by 90% to 100% in the field. RCA formation substantially reduced root respiration and root N content. Under low-N conditions, RCA formation increased rooting depth by 15% to 31%, increased leaf N content by 28% to 81%, increased leaf chlorophyll content by 22%, increased leaf CO₂ assimilation by 22%, increased vegetative biomass by 31% to 66%, and increased grain yield by 58%. Our results are consistent with the hypothesis that RCA improves plant growth under N-limiting conditions by decreasing root metabolic costs, thereby enhancing soil exploration and N acquisition in deep soil strata. Although potential fitness tradeoffs of RCA formation are poorly understood, increased RCA formation appears be a promising breeding target for enhancing crop N acquisition.Nitrogen (N) deficiency is one of the most limiting factors in maize (Zea mays) production worldwide (Ladha et al., 2005). In developing countries such as those in sub-Saharan Africa, less than 20 kg N ha⁻¹ is applied to fields of smallholder farmers due to high fertilizer cost (Azeez et al., 2006; Worku et al., 2007). In developed countries, intensive N fertilization is used to maintain satisfactory yield (Tilman et al., 2002). In the United States, N fertilizers are the greatest economic and energy cost for maize production (Ribaudo et al., 2011). However, less than half of the N applied to crops is actually acquired, and most of the remaining N becomes a source of environmental pollution (Raun and Johnson, 1999; Smil, 1999; Tilman et al., 2002). For example, N and phosphorus (P) effluents into marine systems from agriculture cause eutrophication and hypoxic zones (Diaz and Rosenberg, 2008; Robertson and Vitousek, 2009). Nitrate contamination in surface water and groundwater systems poses serious health risks, such as methemoglobinemia and N-nitroso-induced cancers (UNEP and WHRC, 2007). Emission of nitrous oxides from agricultural activities contributes to ozone damage and global warming (Kulkarni et al., 2008; Sutton et al., 2011). Furthermore, the production of N fertilizers requires considerable energy from fossil fuels, and since energy costs have risen in recent years, farmers face economic pressure from increasing N fertilizer costs, which are linked to higher food prices. It is estimated that a 1% increase in crop N efficiency could save more than $1 billion (U.S.) annually worldwide (Kant et al., 2011). Therefore, even a small improvement in N efficiency would have significant positive impacts on the environment and the economy.Soil N is heterogenous and dynamic. The bioavailability of soil N depends on the balance between the rates of mineralization, nitrification, and denitrification. These processes are determined by several factors, including soil composition, microbial activity, soil temperature, and soil water status (Miller and Cramer, 2004). The predominant form of soil N available to plants in most agricultural systems is nitrate, which is highly soluble in water and thus mobile in the soil (Barber, 1995; Marschner, 1995). Mineralization of organic matter and/or the application of N fertilizer at the beginning of the growing season followed by precipitation and irrigation create a pulse of nitrate that may exceed the N acquisition capacity of seedlings and leach below the root zone. Therefore, it has been proposed that increasing the speed of root exploration of deep soil strata could benefit N acquisition (Lynch, 2013). However, the structural investments and metabolic expenditures of root systems are substantial and can exceed half of daily photosynthesis (Lambers et al., 2002). Therefore, full consideration of the costs and benefits of root systems is crucial for identifying root traits to improve crop production, especially in water- and nutrient-deficient environments (Lynch, 2007). Taking rhizoeconomics and the spatiotemporal availability of soil N into account, Lynch (2013) proposed a root ideotype for enhanced N acquisition in maize called Steep, Cheap, and Deep, in which Steep refers to architectural phenes and Cheap refers to phenes that reduce the metabolic cost of soil exploration. One element of this ideotype is abundant root cortical aerenchyma (RCA).RCA consists of enlarged air spaces in the root cortex (Esau, 1977). RCA is known to form in response to hypoxia, and the role of RCA in improving oxygen transport to roots of many plant species under hypoxic conditions has been well researched (Vartapetian and Jackson, 1997; Jackson and Armstrong, 1999; Mano and Omori, 2007, 2013). Interestingly, RCA can also form in response to drought and edaphic stresses such as N, P, and sulfur deficiencies (Drew et al., 1989; Bouranis et al., 2003; Fan et al., 2003; Zhu et al., 2010a), which suggests that the benefit of RCA extends beyond facilitating oxygen transport. Several lines of evidence suggest that RCA enhances root metabolic efficiency under stress. Fan et al. (2003) found that RCA formation significantly reduced root segment respiration and P content of root tissue, which allowed greater shoot growth in soils with low P availability. Under drought, maize genotypes with high RCA formation had greater root length, deeper rooting, better leaf water status, and 8 times greater yield than closely related genotypes with low RCA (Zhu et al., 2010a). Effects of RCA on root respiration were more pronounced for large-diameter roots compared with small-diameter roots (Jaramillo et al., 2013). Results from the functional-structural plant model SimRoot showed that RCA formation could be an adaptive response to deficiency of N, P, and potassium by decreasing the metabolic cost of soil exploration. By reducing root respiration, RCA decreases the carbon cost of soil exploration, and by decreasing the N and P content of root tissue, RCA permits internal reallocation of nutrients to growing root tissue, which is particularly beneficial under conditions of low N and P availability (Postma and Lynch, 2011a). Under suboptimal P availability, RCA increased the growth of a simulated 40-d-old maize plant by 70% (Postma and Lynch, 2011b). In the case of N, RCA increased the growth of simulated maize plants up to 55% in low-N conditions, and plants benefit from RCA more in high-N-leaching environments than in low-N-leaching environments (Postma and Lynch, 2011a). In addition, the formation of RCA decreases critical soil nutrient levels, defined as the soil fertility below which growth is reduced, suggesting that cultivars with high RCA may require less fertilizer under nonstressed conditions. These in silico results suggest that RCA has potential utility for improving crop nutrient acquisition in both high- and low-input agroecosystems.The overall objective of this research was to assess the utility of RCA for N acquisition in maize under N-limiting conditions. Maize near-isophenic recombinant inbred lines (RILs) sharing a common genetic background (i.e. descending from the same parents) with common root phenotypes but contrasting in RCA formation were grown under N stress to test the hypothesis that RCA formation is associated with reduced root respiration, reduced tissue nutrient content, greater rooting depth, enhanced N acquisition, and therefore greater plant growth and yield under N limitation.     

Quantitative 3D Analysis of Plant Roots Growing in Soil Using Magnetic Resonance Imaging

Precise measurements of root system architecture traits are an important requirement for plant phenotyping. Most of the current methods for analyzing root growth require either artificial growing conditions (e.g. hydroponics), are severely restricted in the fraction of roots detectable (e.g. rhizotrons), or are destructive (e.g. soil coring). On the other hand, modalities such as magnetic resonance imaging (MRI) are noninvasive and allow high-quality three-dimensional imaging of roots in soil. Here, we present a plant root imaging and analysis pipeline using MRI together with an advanced image visualization and analysis software toolbox named NMRooting. Pots up to 117 mm in diameter and 800 mm in height can be measured with the 4.7 T MRI instrument used here. For 1.5 l pots (81 mm diameter, 300 mm high), a fully automated system was developed enabling measurement of up to 18 pots per day. The most important root traits that can be nondestructively monitored over time are root mass, length, diameter, tip number, and growth angles (in two-dimensional polar coordinates) and spatial distribution. Various validation measurements for these traits were performed, showing that roots down to a diameter range between 200 μm and 300 μm can be quantitatively measured. Root fresh weight correlates linearly with root mass determined by MRI. We demonstrate the capabilities of MRI and the dedicated imaging pipeline in experimental series performed on soil-grown maize (Zea mays) and barley (Hordeum vulgare) plants.The root system is of critical importance for the survival, development, and performance of higher plants, because it is the major organ for anchorage, acquisition of water and nutrients, and carbon storage. Therefore, there is a long-standing interest in the scientific community regarding the structure, function, and development of root systems. Rising concerns about the environmental impact and increasing cost of fertilizers have initiated breeding programs for more resource-efficient cultivars and the development of methods for phenotyping root systems. The opaque nature of soils generally demands destructive methods such as root excavation for subsequent optical assessment (Lynch, 2007; Trachsel et al., 2011). Although efficient for screening large numbers of plants for a limited set of clearly discernible traits, this approach does not allow detailed monitoring of root development over time. Other approaches, such as rhizotrons or mini-rhizotron tubes, where root growth is observed along transparent windows (Nagel et al., 2009), monitor only a fraction of the roots. Methods in which the whole root system is visible are typically based on artificial media such as paper pouches (Chen et al., 2011; Le Marié et al., 2014), three-dimensional (3D) gels (Iyer-Pascuzzi et al., 2010), and hydro- or aeroponics (Herdel et al., 2001). Results may thus not be directly transferable to plants grown in natural 3D soil environments (Gregory et al., 2003). For example, roots are known to grow faster and thinner when the penetration resistance is low (Bengough et al., 2011; Chimungu et al., 2015). Computed tomography (CT; both x-ray and neutron) has been proposed to overcome the mentioned difficulties with studying roots in natural soil. CT has been successfully used to obtain high-resolution images of roots (Moradi et al., 2009; Flavel et al., 2012; Mooney et al., 2012). High resolution is necessary for segmenting roots due to a poor contrast between roots and soil (Jassogne et al., 2009; Mairhofer et al., 2012; Mairhofer et al., 2013). A first direct comparison (to our knowledge) of magnetic resonance imaging (MRI) and x-ray CT for 3D root imaging has recently been published (Metzner et al., 2015), showing that the two modalities pose different opportunities and limitations for root imaging.MRI is based on the magnetic moment of atomic nuclei like ¹H (protons), which are highly abundant in living tissues, mainly in water molecules. The magnetic moment can be manipulated using strong magnetic and radio frequency fields that have no known impact on plant development to produce 3D datasets of samples. MRI offers several contrast parameters that can be manipulated for discriminating different structures such as roots from soil background (Rogers and Bottomley, 1987; Jahnke et al., 2009). The basic principles of MRI are described in detail in several textbooks (Callaghan, 1993; Haacke et al., 1999) or review articles (Köckenberger et al., 2004; Blümler et al., 2009; van As et al., 2009; Borisjuk et al., 2012). Research applications to plant roots range from phytopathology (Hillnhütter et al., 2012), across storage root internal structures (Metzner et al., 2014) and water uptake modeling (Stingaciu et al., 2013), to coregistration with positron emission tomography for investigating structure-function relations (Jahnke et al., 2009). Water mobility in roots and soil has also been shown to be detectable with MRI (MacFall and Johnson, 2012; Gruwel, 2014). In particular for imaging roots with MRI, these studies generally explored the applicability of MRI but largely lacked validation of the data against conventional techniques of root visualization after harvest. Our goal was to develop MRI protocols to image roots of plants growing in soil to obtain global root parameters such as root length, mass, or root diameters; gather root growth angles and number of root tips; get spatial information on the distribution of root system architecture (RSA) parameters such as root length densities; and, wherever possible, verify these parameters against harvest data.     

Phene Synergism between Root Hair Length and Basal Root Growth Angle for Phosphorus Acquisition

Shallow basal root growth angle (BRGA) increases phosphorus acquisition efficiency by enhancing topsoil foraging because in most soils, phosphorus is concentrated in the topsoil. Root hair length and density (RHL/D) increase phosphorus acquisition by expanding the soil volume subject to phosphorus depletion through diffusion. We hypothesized that shallow BRGA and large RHL/D are synergetic for phosphorus acquisition, meaning that their combined effect is greater than the sum of their individual effects. To evaluate this hypothesis, phosphorus acquisition in the field in Mozambique was compared among recombinant inbred lines of common bean (Phaseolus vulgaris) having four distinct root phenotypes: long root hairs and shallow basal roots, long root hairs and deep basal roots, short root hairs and shallow basal roots, and short root hairs and deep basal roots. The results revealed substantial synergism between BRGA and RHL/D. Compared with short-haired, deep-rooted phenotypes, long root hairs increased shoot biomass under phosphorus stress by 89%, while shallow roots increased shoot biomass by 58%. Genotypes with both long root hairs and shallow roots had 298% greater biomass accumulation than short-haired, deep-rooted phenotypes. Therefore, the utility of shallow basal roots and long root hairs for phosphorus acquisition in combination is twice as large as their additive effects. We conclude that the anatomical phene of long, dense root hairs and the architectural phene of shallower basal root growth are synergetic for phosphorus acquisition. Phene synergism may be common in plant biology and can have substantial importance for plant fitness, as shown here.Suboptimal phosphorus availability is a primary limitation to plant growth in terrestrial ecosystems (Vance et al., 2003). Large areas of tropical and subtropical soils in Africa, Latin America, and Asia have phosphorus availability limited by low total phosphorus content as well as high phosphorus fixation (Sanchez and Uehara, 1980). The use of phosphorus fertilizer to correct phosphorus deficiency is only a partial solution, since phosphorus fertilizers are costly, nonrenewable, potentially harmful to the environment, and often marginally effective in tropical soils because of immobilization by the soil (Cathcart, 1980). Therefore, the development of crop cultivars with enhanced ability to acquire phosphorus is an important strategy to increase agricultural productivity in low-input agroecosystems and to reduce input requirements in intensive agriculture (Vance et al., 2003; Gahoonia and Nielsen, 2004; Lambers et al., 2006; Lynch, 2007, 2011).Several root phenes (i.e. basic units of the phenotype; Serebrovsky, 1925; Lynch, 2011; for discussion, see York et al., 2013) enhance phosphorus acquisition, including root architectural phenes for topsoil foraging (Lynch and Brown, 2001), such as shallow root growth angles (Liao et al., 2004; Ho et al., 2005), increased basal root whorl number (Lynch and Brown, 2012; Miguel et al., 2013), and adventitious rooting (Miller et al., 2003); phenes to enhance soil exploitation, including root hair length and density (RHL/D; Bates and Lynch, 2000a, 2000b, 2001; Ma et al., 2001a; Gahoonia and Nielsen, 2004; Yan et al., 2004) and phosphorus-solubilizing root exudates (Ryan et al., 2001); mycorrhizal symbioses (Smith and Read, 2008); and phenes that reduce the metabolic cost of soil exploration (Lynch and Ho, 2005), such as root etiolation and root cortical aerenchyma (Fan et al., 2003; Postma and Lynch, 2010, 2011). It is probable that interactions among these phenes are important in determining the phosphorus acquisition of integrated phenotypes. Results from the structural-functional model SimRoot indicate that RHL/D, the distance from the root tip to the first appearance of root hairs, and the pattern of root hair-bearing epidermal cells (trichoblasts) among non-hair-bearing cells (atrichoblasts) are synergetic for phosphorus acquisition in Arabidopsis (Arabidopsis thaliana; Ma et al., 2001b). Another SimRoot study showed that on low-phosphorus soils, the utility of root cortical aerenchyma in maize (Zea mays) may be 2.9 times greater in plants with increased lateral branching density than in plants with normal branching (Postma and Lynch, 2011). Morphological, anatomical, symbiotic, and biochemical phenes expressed by root axes should have significant synergies with architectural phenes, since architectural phenes determine the position of root axes in time and space and, therefore, the soil domain in which spatially localized phenes are expressed (Lynch, 2011).Phosphorus availability is greater in the topsoil, with a steep decline with depth. Therefore, root architectural phenes that increase topsoil foraging can improve phosphorus acquisition (Lynch and Brown, 2001). Root shallowness regulated by basal root growth angle (BRGA) has been demonstrated to be of particular importance for topsoil foraging (Bonser et al., 1996; Liao et al., 2001; Rubio et al., 2001; Ho et al., 2005). These studies show that common bean (Phaseolus vulgaris) genotypes with smaller BRGA (i.e. shallower roots) have better performance in low-phosphorus soils. Shallow root distribution is also important for phosphorus acquisition in maize (Zhu et al., 2005).RHL/D are also important for phosphorus acquisition (Bates and Lynch, 2000a, 2000b, 2001; Gahoonia and Nielsen, 2004). Since phosphorus mobility in soil is governed by diffusion rather than mass flow, phosphorus uptake by roots is limited by localized phosphorus depletion in the rhizosphere (Barber, 1995). Long root hairs extend the phosphorus depletion zone surrounding the root, thereby increasing the total amount of phosphorus accessible by the roots and phosphorus acquisition. In many plant species, the length and density of root hairs increase in response to low phosphorus availability (Bates and Lynch, 1996; Ma et al., 2001a). Increased RHL/D increases phosphorus accumulation in Arabidopsis growing in low-phosphorus conditions (Bates and Lynch, 2000a, 2000b), and mutants lacking root hairs have reduced phosphorus acquisition (Bates and Lynch, 2000b; Gahoonia et al., 2001). Species that develop more and/or longer root hairs (e.g. Lolium perenne) are more efficient in accessing inorganic phosphorus from soils and thus show greater growth response to phosphorus fertilization than species that lack these traits (e.g. Podocarpus totara). Genotypic variation for root hairs is associated with increased phosphorus acquisition in several species, including barley (Hordeum vulgare; Gahoonia and Nielsen, 2004), common bean (Miguel, 2004; Yan et al., 2004), and maize (Zhu et al., 2010).We hypothesize that the utilities of BRGA and RHL/D for phosphorus acquisition are synergetic. Root hairs will be more valuable for phosphorus acquisition if located in surface soil horizons by arising from roots with a shallow growth angle; shallow roots will have greater benefit for phosphorus acquisition if they have long and dense hairs. Therefore, genotypes possessing long, dense root hairs on shallow roots should have greater phosphorus acquisition than genotypes with either long root hairs on deep roots or short root hairs on shallow roots. We expect the combined benefit of long root hairs and shallow root growth angles to exceed the sum of their individual effects, since they permit greater exploitation of soil strata with the greatest phosphorus availability.In this study, we evaluated the potential synergism between the architectural phene of BRGA and the morphological phene of RHL/D for phosphorus acquisition by comparison of contrasting phenotypes of common bean growing in a weathered tropical soil.     

Reduced Root Cortical Cell File Number Improves Drought Tolerance in Maize

We tested the hypothesis that reduced root cortical cell file number (CCFN) would improve drought tolerance in maize (Zea mays) by reducing the metabolic costs of soil exploration. Maize genotypes with contrasting CCFN were grown under well-watered and water-stressed conditions in greenhouse mesocosms and in the field in the United States and Malawi. CCFN ranged from six to 19 among maize genotypes. In mesocosms, reduced CCFN was correlated with 57% reduction of root respiration per unit of root length. Under water stress in the mesocosms, genotypes with reduced CCFN had between 15% and 60% deeper rooting, 78% greater stomatal conductance, 36% greater leaf CO₂ assimilation, and between 52% to 139% greater shoot biomass than genotypes with many cell files. Under water stress in the field, genotypes with reduced CCFN had between 33% and 40% deeper rooting, 28% lighter stem water oxygen isotope enrichment (δ¹⁸O) signature signifying deeper water capture, between 10% and 35% greater leaf relative water content, between 35% and 70% greater shoot biomass at flowering, and between 33% and 114% greater yield than genotypes with many cell files. These results support the hypothesis that reduced CCFN improves drought tolerance by reducing the metabolic costs of soil exploration, enabling deeper soil exploration, greater water acquisition, and improved growth and yield under water stress. The large genetic variation for CCFN in maize germplasm suggests that CCFN merits attention as a breeding target to improve the drought tolerance of maize and possibly other cereal crops.Drought is a primary constraint to global crop production (Schmidhuber and Tubiello, 2007), and global climate change is likely to increase the risk of drought, especially in rain-fed agriculture (Battisti and Naylor, 2009; Burke et al., 2009; Mishra and Cherkauer, 2010; Lobell et al., 2011). Therefore, the development of crops with greater drought tolerance is an important global objective. Yield under drought is often not an efficient selection criterion in drought breeding programs, since yield is affected by many elements of the phenotype and the environment, interacting in complex and often unknown ways. Trait-based selection or ideotype breeding is generally a more efficient selection strategy, permitting the identification of useful sources of variation among lines that have poor agronomic adaptation, elucidation of genotype-by-environment interactions, and informed trait stacking (Araus et al., 2002, 2008; Manschadi et al., 2006; Lynch, 2007b, 2011; York et al., 2013).In most agroecosystems, the topsoil dries before the subsoil as drought progresses. In such environments, plants with deeper roots are able to acquire water available in deeper soil domains that may not be available to plants with shallower roots (Ludlow and Muchow, 1990; Ho et al., 2005; Hammer et al., 2009). An ideotype has been proposed to guide the breeding of crops with deeper roots and, therefore, greater water acquisition from drying soil, called Steep, Cheap, and Deep, integrating architectural, anatomical, and physiological phenes (Lynch, 2013). The term Cheap denotes phenes that reduce the metabolic cost of soil exploration, which is an important limitation to the acquisition of scarce soil resources, including water in dry soil (Fan et al., 2003; Lynch, 2007b; Zhu et al., 2010; Postma and Lynch, 2011a, 2011b; Jaramillo et al., 2013). Plant resource allocation to root growth typically increases under drought to enhance water acquisition; therefore, the metabolic cost of root growth becomes a significant component of plant fitness and adaptation under drought (Lynch, 2007b, 2013). Therefore, a plant that is able to access water in deep soil domains at reduced metabolic cost will have superior productivity, because it will have more metabolic resources available for further resource acquisition, growth, and reproduction. Evidence in support of this hypothesis comes from empirical and modeling studies for maize (Zea mays) under water and edaphic stress (Lynch, 2007a; Zhu et al., 2010; Postma and Lynch, 2011a, 2011b; Jaramillo et al., 2013).Root cortical aerenchyma (RCA) is the enlarged air space in the root cortex that forms either through cell death or cell separation (Evans, 2004). RCA is associated with a disproportionate reduction of root respiration in maize by converting living cortical tissue to air volume (Fan et al., 2003; Zhu et al., 2010). Reduction of root metabolic costs permits more internal resources to be allocated to greater root growth and, consequently, greater soil resource acquisition. RCA formation is also associated with a reduction of phosphorus content in root tissue on a volume basis, since air spaces do not contain phosphorus (Fan et al., 2003), and with improved growth in low-phosphorus soil (Lynch, 2011). RCA also reduces the nitrogen content of root tissue and is beneficial for nitrogen capture and maize growth on low-nitrogen soils (Saengwilai, 2014a). Modeling studies suggest that RCA improves crop adaptation to suboptimal nutrient availability by reducing the metabolic costs of soil exploration (Postma and Lynch, 2011a, 2011b). Under drought, Zhu et al. (2010) found that maize genotypes with more RCA had five times greater biomass and eight times greater yield than genotypes with less RCA. Living cortical area (LCA) is total transverse root cortical area minus RCA area. Jaramillo et al. (2013) found that root respiration is positively correlated with LCA, and a 3.5-fold reduction in LCA is associated with a 2.5-fold improvement in plant growth under drought. These results indicate that the metabolic demand of living cortical tissue is a primary determinant of root growth, soil exploration, and resource acquisition in soil environments with suboptimal resource availability.This study builds on earlier studies indicating that substantial reduction of root metabolic cost is associated with variation in LCA. The cortex of the maize root is composed of several concentric layers of parenchyma cells, the number of which we refer to as the cortical cell file number (CCFN). Recently, Burton et al. (2013) reported that there is 3-fold variation for CCFN in Zea spp. In that study, the variation was wider in maize landraces (six to 16 cell files) than in wild Zea spp. (seven to 13 cell files). It has been proposed that reduced CCFN would decrease the metabolic costs of root growth and maintenance, in terms of both the carbon cost of root respiration and the nutrient content of living tissue, by reducing the proportion of root volume occupied by living cortical tissue, which has greater metabolic demands than the stele (Lynch, 2013). However, the physiological utility of CCFN has not been explored.The objective of this study was to test the hypothesis that reduced CCFN would reduce root respiration, permitting greater rooting depth, thereby enhancing water acquisition and improving both plant growth and yield under water stress.