Optimization modeling of plant root architecture for water and phosphorus acquisition

OsbZIP1 regulates phosphorus uptake and nitrogen utilization, contributing to improved yield

Increasing nutrient uptake and use efficiency in plants can contribute to improved crop yields and reduce the demand for fertilizers in crop production. In this study, we characterized a rice mutant, 88n which showed long roots under low nitrogen (N) or phosphorus (P) conditions. Low expression levels of N transporter genes were observed in 88n root, and total N concentration in 88n shoots were decreased, however, C concentrations and shoot dry weight in 88n were comparable to that in WT. Therefore, 88n showed high nitrogen utilization efficiency (NUtE). mRNA accumulation of Pi transporter genes was higher in 88n roots, and Pi concentration and uptake activity were higher in 88n than in WT. Therefore, 88n also showed high phosphorus uptake efficiency (PUpE). Molecular genetic analysis revealed that the causal gene of 88n phenotypes was OsbZIP1, a monocot-specific ortholog of the A. thaliana bZIP transcription factor HY5. Similar to the hy5 mutant, chlorophyll content in roots was decreased and root angle was shallower in 88n than in WT. Finally, we tested the yield of 88n in paddy fields over 3 years because 88n mutant plants showed higher PUpE and NUtE activity and different root architecture at the seedling stage. 88n showed large panicles and increased panicle weight/plant. Taken together, a mutation in OsbZIP1 could contribute to improved crop yields.

Unlocking dynamic root phenotypes for simultaneous enhancement of water and phosphorus uptake

Phosphorus (P) and water are crucial for plant growth, but their availability is challenged by climate change, leading to reduced crop production and global food security. In many agricultural soils, crop productivity is confronted by both water and P limitations. The diminished soil moisture decreases available P due to reduced P diffusion, and inadequate P availability diminishes tissue water status through modifications in stomatal conductance and a decrease in root hydraulic conductance. P and water display contrasting distributions in the soil, with P being concentrated in the topsoil and water in the subsoil. Plants adapt to water- and P-limited environments by efficiently exploring localized resource hotspots of P and water through the adaptation of their root system. Thus, developing cultivars with improved root architecture is crucial for accessing and utilizing P and water from arid and P-deficient soils. To meet this goal, breeding towards multiple advantageous root traits can lead to better cultivars for water- and P-limited environments. This review discusses the interplay of P and water availability and highlights specific root traits that enhance the exploration and exploitation of optimal resource-rich soil strata while reducing metabolic costs. We propose root ideotype models, including 'topsoil foraging', 'subsoil foraging', and 'topsoil/subsoil foraging' for maize (monocot) and common bean (dicot). These models integrate beneficial root traits and guide the development of water- and P-efficient cultivars for challenging environments.

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.

Maize root behavior as three-inputs-three-outputs logical gates due to positive gravitropism and nutritropism

Root growth and their interactions can provide valuable information for the development of asynchronous logic systems. Here, maize root behavior due to positive gravitropism and nutritropism is evaluated as three-inputs-three-outputs logical gates. Using plant roots as the element for unconventional computing, the Boolean functions of each root tropism were constructed through arithmetic-logical operations. One gravity gate (rGG) and two nutrient gates (rNG1 and rNG2) were fabricated using additive manufacturing. The rGG platform was oriented with roots directly pulled down by gravity which computes (x, y, z) = (xz + yz, x + y¯z+yz¯, xy + yz), whereas specific output channels in rNG1 and rNG2 were fertigated with high phosphorus concentration resulting in (x, y, z) = (x + y + z, xy + xz, xyz) for rNG1 and (x, y, z) = (xyz, xy¯z+xyz¯, x + y + z) for rNG2. For rGG, rNG1, and rNG2, the symbols x, y, and z pertain to "root presence" in the related channel, whereas top bar on the symbols indicates "root absence". Anatomical traits of roots were evaluated to assess possible differences in vascular tissues due to gravitropic and nutritropic responses. Overall, maize primary roots showed prominent positive gravitropism and nutritropism, and the roots that were most attracted by gravitational or nutritional stimuli showed an increase in the diameter of phloem and xylem. The logic exhibited by roots was dependent on the gravitropic and nutritropic stimuli to which they were exposed in the different logic gates. The responsiveness of maize roots to environmental stimuli such as gravity and nutrients provided valuable information to be used in computational bioelectronics.

Phosphite treatment can improve root biomass and nutrition use efficiency in wheat

Phosphite represents a reduced form of phosphate that belongs to a class of crop growth-promoting chemicals termed biostimulants. Previous research has shown that phosphite application can enhance root growth, but its underlying mechanism, especially during environmental stresses, remains elusive. To uncover this, we undertook a series of morphological and physiological analyses under nutrient, water and heat stresses following a foliar application in wheat. Non-invasive 3D imaging of root system architecture directly in soil using X-ray Computed Tomography revealed that phosphite treatment improves root architectural traits and increased root biomass. Biochemical and physiological assays identified that phosphite treatment significantly increases Nitrate Reductase (NR) activity, leaf photosynthesis and stomatal conductance, suggesting improved Nitrogen and Carbon assimilation, respectively. These differences were more pronounced under heat or drought treatment (photosynthesis and photosystem II stability) and nutrient deficiency (root traits and NR). Overall our results suggest that phosphite treatment improves the ability of plants to tolerate abiotic stresses through improved Nitrogen and Carbon assimilation, combined with improved root growth which may improve biomass and yield.

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.

Modeling Auxin Signaling in Roots: Auxin Computations

Auxin signaling and patterning is an inherently complex process, involving polarized auxin transport, metabolism, and signaling, its effect on developmental zones, as well as growth rates, and the feedback between all these different aspects. This complexity has led to an important role for computational modeling in unraveling the multifactorial roles of auxin in plant developmental and adaptive processes. Here we discuss the basic ingredients of auxin signaling and patterning models for root development as well as a series of key modeling studies in this area. These modeling studies have helped elucidate how plants use auxin signaling to compute the size of their root meristem, the direction in which to grow, and when and where to form lateral roots. Importantly, these models highlight how auxin, through patterning of and collaborating with other factors, can fulfill all these roles simultaneously.

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.

Low nitrogen availability inhibits the phosphorus starvation response in maize (Zea mays ssp. mays L.)

BACKGROUND

Nitrogen (N) and phosphorus (P) are macronutrients essential for crop growth and productivity. In cultivated fields, N and P levels are rarely sufficient, contributing to the gap between realized and potential production. Fertilizer application increases nutrient availability, but is not available to all farmers, nor are current rates of application sustainable or environmentally desirable. Transcriptomic studies of cereal crops have revealed dramatic responses to either low N or low P single stress treatments. In the field, however, levels of both N and P may be suboptimal. The interaction between N and P starvation responses remains to be fully characterized.

RESULTS

We characterized growth and root and leaf transcriptomes of young maize plants under nutrient replete, low N, low P or combined low NP conditions. We identified 1555 genes to respond to our nutrient treatments, in one or both tissues. A large group of genes, including many classical P starvation response genes, were regulated antagonistically between low N and P conditions. An additional experiment over a range of N availability indicated that a mild reduction in N levels was sufficient to repress the low P induction of P starvation genes. Although expression of P transporter genes was repressed under low N or low NP, we confirmed earlier reports of P hyper accumulation under N limitation.

CONCLUSIONS

Transcriptional responses to low N or P were distinct, with few genes responding in a similar way to the two single stress treatments. In combined NP stress, the low N response dominated, and the P starvation response was largely suppressed. A mild reduction in N availability was sufficient to repress the induction of P starvation associated genes. We conclude that activation of the transcriptional response to P starvation in maize is contingent on N availability.

Collective colony growth is optimized by branching pattern formation in Pseudomonas aeruginosa

Branching pattern formation is common in many microbes. Extensive studies have focused on addressing how such patterns emerge from local cell-cell and cell-environment interactions. However, little is known about whether and to what extent these patterns play a physiological role. Here, we consider the colonization of bacteria as an optimization problem to find the colony patterns that maximize colony growth efficiency under different environmental conditions. We demonstrate that Pseudomonas aeruginosa colonies develop branching patterns with characteristics comparable to the prediction of modeling; for example, colonies form thin branches in a nutrient-poor environment. Hence, the formation of branching patterns represents an optimal strategy for the growth of Pseudomonas aeruginosa colonies. The quantitative relationship between colony patterns and growth conditions enables us to develop a coarse-grained model to predict diverse colony patterns under more complex conditions, which we validated experimentally. Our results offer new insights into branching pattern formation as a problem-solving social behavior in microbes and enable fast and accurate predictions of complex spatial patterns in branching colonies.

Root phenotyping: important and minimum information required for root modeling in crop plants

As plants cannot relocate, they require effective root systems for water and nutrient uptake. Root development plasticity enables plants to adapt to different environmental conditions. Research on improvements in crop root systems is limited in comparison with that in shoots as the former are difficult to image. Breeding more effective root systems is proposed as the "second green revolution". There are several recent publications on root system architecture (RSA), but the methods used to analyze the RSA have not been standardized. Here, we introduce traditional and current root-imaging methods and discuss root structure phenotyping. Some important root structures have not been standardized as roots are easily affected by rhizosphere conditions and exhibit greater plasticity than shoots; moreover, root morphology significantly varies even in the same genotype. For these reasons, it is difficult to define the ideal root systems for breeding. In this review, we introduce several types of software to analyze roots and identify important root parameters by modeling to simplify the root system characterization. These parameters can be extracted from photographs captured in the field. This modeling approach is applicable to various legacy root data stored in old or unpublished formats. Standardization of RSA data could help estimate root ideotypes.

WinRoots: A High-Throughput Cultivation and Phenotyping System for Plant Phenomics Studies Under Soil Stress

Soil stress, such as salinity, is a primary cause of global crop yield reduction. Existing crop phenotyping platforms cannot fully meet the specific needs of phenomics studies of plant response to soil stress in terms of throughput, environmental controllability, or root phenotypic acquisition. Here, we report the WinRoots, a low-cost and high-throughput plant soil cultivation and phenotyping system that can provide uniform, controlled soil stress conditions and accurately quantify the whole-plant phenome, including roots. Using soybean seedlings exposed to salt stress as an example, we demonstrate the uniformity and controllability of the soil environment in this system. A high-throughput multiple-phenotypic assay among 178 soybean cultivars reveals that the cotyledon character can serve as a non-destructive indicator of the whole-seedling salt tolerance. Our results demonstrate that WinRoots is an effective tool for high-throughput plant cultivation and soil stress phenomics studies.

Genome-Wide Association Study of Topsoil Root System Architecture in Field-Grown Soybean [Glycine max (L.) Merr.]

Water and nutrient acquisition is a critical function of plant root systems. Root system architecture (RSA) traits are often complex and controlled by many genes. This is the first genome-wide association study reporting genetic loci for RSA traits for field-grown soybean (Glycine max). A collection of 289 soybean genotypes was grown in three environments, root crowns were excavated, and 12 RSA traits assessed. The first two components of a principal component analysis of these 12 traits were used as additional aggregate traits for a total of 14 traits. Marker-trait association for RSA traits were identified using 31,807 single-nucleotide polymorphisms (SNPs) by a genome-wide association analysis. In total, 283 (non-unique) SNPs were significantly associated with one or more of the 14 root traits. Of these, 246 were unique SNPs and 215 SNPs were associated with a single root trait, while 26, four, and one SNPs were associated with two, three, and four root traits, respectively. The 246 SNPs marked 67 loci associated with at least one of the 14 root traits. Seventeen loci on 13 chromosomes were identified by SNPs associated with more than one root trait. Several genes with annotation related to processes that could affect root architecture were identified near these 67 loci. Additional follow-up studies will be needed to confirm the markers and candidate genes identified for RSA traits and to examine the importance of the different root characteristics for soybean productivity under a range of soil and environmental conditions.

A design principle of root length distribution of plants

Shaping a plant root into an ideal structure for water capture is increasingly important for sustainable agriculture in the era of global climate change. Although the current genetic engineering of crops favours deep-reaching roots, here we show that nature has apparently adopted a different strategy of shaping roots. We construct a mathematical model for optimal root length distribution by considering that plants seek maximal water uptake at the metabolic expenses of root growth. Our theory finds a logarithmic decrease of root length density with depth to be most beneficial for efficient water uptake, which is supported by biological data as well as our experiments using root-mimicking network systems. Our study provides a tool to gauge the relative performance of root networks in transgenic plants engineered to endure a water deficit. Moreover, we lay a fundamental framework for mechanical understanding and design of water-absorptive growing networks, such as medical and industrial fluid transport systems and soft robots, which grow in porous media including soils and biotissues.

Inoculation with the mycorrhizal fungus Rhizophagus irregularis modulates the relationship between root growth and nutrient content in maize (Zea mays ssp. mays L.)

Plant root systems play a fundamental role in nutrient and water acquisition. In resource-limited soils, modification of root system architecture is an important strategy to optimize plant performance. Most terrestrial plants also form symbiotic associations with arbuscular mycorrhizal fungi to maximize nutrient uptake. In addition to direct delivery of nutrients, arbuscular mycorrhizal fungi benefit the plant host by promoting root growth. Here, we aimed to quantify the impact of arbuscular mycorrhizal symbiosis on root growth and nutrient uptake in maize. Inoculated plants showed an increase in both biomass and the total content of twenty quantified elements. In addition, image analysis showed mycorrhizal plants to have denser, more branched root systems. For most of the quantified elements, the increase in content in mycorrhizal plants was proportional to root and overall plant growth. However, the increase in boron, calcium, magnesium, phosphorus, sulfur, and strontium was greater than predicted by root system size alone, indicating fungal delivery to be supplementing root uptake.

Root growth and force chains in a granular soil

Roots provide basic functions to plants such as water and nutrient uptake and anchoring in soil. The growth and development of root systems contribute to colonizing the surrounding soil and optimizing the access to resources. It is generally known that the variability of plant root architecture results from the combination of genetic, physiological, and environmental factors, in particular soil mechanical resistance. However, this last factor has never been investigated at the soil grain scale for roots. In this paper, we are interested in the effect of the disordered texture of granular soils on the evolution of forces experienced by the root cap during its growth. We introduce a numerical model in which the root is modeled as a flexible self-elongating tube that probes a soil composed of solid particles. By means of extensive simulations, we show that the forces exerted on the root cap reflect interparticle force chains. Our simulations also show that the mean force declines exponentially with root flexibility, the highest force corresponding to the soil hardness. Furthermore, we find that this functional dependence is characterized by a single dimensionless parameter that combines granular structure and root bending stiffness. This finding will be useful to further address the biological issues of mechanosensing and thigmomorphogenesis in plant roots.

Co-optimization of axial root phenotypes for nitrogen and phosphorus acquisition in common bean

Background and Aims

Root architecture is a primary determinant of soil resource acquisition. We hypothesized that root architectural phenes will display both positive and negative interactions with each other for soil resource capture because of competition for internal resources and functional trade-offs in soil exploration.

Methods

We employed the functional-structural plant model SimRoot to explore how interactions among architectural phenes in common bean determine the acquisition of phosphate and nitrate, two key soil resources contrasting in mobility. We evaluated the utility of basal root whorl number (BRWN) when basal root growth angle, hypocotyl-borne roots and lateral root branching density (LRBD) were varied, under varying availability of phosphate and nitrate.

Key Results

Three basal root whorls were optimal in most phenotypes. This optimum shifted towards greater values when LRBD decreased and to smaller numbers when LRBD increased. The maximum biomass accumulated for a given BRWN phenotype in a given limiting nutrient scenario depended upon root growth angle. Under phosphorus stress shallow phenotypes grew best, whereas under nitrate stress fanned phenotypes grew best. The effect of increased hypocotyl-borne roots depended upon BRWN as well as the limiting nutrient. Greater production of axial roots due to BRWN or hypocotyl-borne roots reduced rooting depth, leading to reduced biomass under nitrate-limiting conditions. Increased BRWN as well as greater LRBD increased root carbon consumption, resulting in reduced shoot biomass.

Conclusions

We conclude that the utility of a root architectural phenotype is determined by whether the constituent phenes are synergistic or antagonistic. Competition for internal resources and trade-offs for external resources result in multiple phenotypes being optimal under a given nutrient regime. We also find that no single phenotype is optimal across contrasting environments. These results have implications for understanding plant evolution and also for the breeding of more stress-tolerant crop phenotypes.

Buffered delivery of phosphate to Arabidopsis alters responses to low phosphate

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

Uncovering the contribution of epigenetics to plant phenotypic variation in Mediterranean ecosystems

Epigenetic signals can affect plant phenotype and fitness and be stably inherited across multiple generations. Epigenetic regulation plays a key role in the mechanisms of plant response to the environment, without altering DNA sequence. As plants cannot adapt behaviourally or migrate instantly, such dynamic epigenetic responses may be particularly crucial for survival of plants within changing and challenging environments, such as the Mediterranean-Type Ecosystems (MTEs). These ecosystems suffer recurrent stressful events (warm and dry summers with associated fire regimes) that have selected for plants with similar phenotypic complex traits, resulting in similar vegetation growth forms. However, the potential role of epigenetics in plant adaptation to recurrent stressful environments such as the MTEs has generally been ignored. To understand the full spectrum of adaptive processes in such contexts, it is imperative to prompt study of the causes and consequences of epigenetic variation in natural populations. With this purpose, we review here current knowledge on epigenetic variation in natural populations and the genetic and epigenetic basis of some key traits for plants in the MTEs, namely those traits involved in adaptation to drought, fire and oligotrophic soils. We conclude there is still much to be learned about 'plant epigenetics in the wild' and, thus, we propose future research steps in the study of natural epigenetic variation of key traits in the MTEs at different scales.

Rice Root Architectural Plasticity Traits and Genetic Regions for Adaptability to Variable Cultivation and Stress Conditions

Future rice (Oryza sativa) crops will likely experience a range of growth conditions, and root architectural plasticity will be an important characteristic to confer adaptability across variable environments. In this study, the relationship between root architectural plasticity and adaptability (i.e. yield stability) was evaluated in two traditional × improved rice populations (Aus 276 × MTU1010 and Kali Aus × MTU1010). Forty contrasting genotypes were grown in direct-seeded upland and transplanted lowland conditions with drought and drought + rewatered stress treatments in lysimeter and field studies and a low-phosphorus stress treatment in a Rhizoscope study. Relationships among root architectural plasticity for root dry weight, root length density, and percentage lateral roots with yield stability were identified. Selected genotypes that showed high yield stability also showed a high degree of root plasticity in response to both drought and low phosphorus. The two populations varied in the soil depth effect on root architectural plasticity traits, none of which resulted in reduced grain yield. Root architectural plasticity traits were related to 13 (Aus 276 population) and 21 (Kali Aus population) genetic loci, which were contributed by both the traditional donor parents and MTU1010. Three genomic loci were identified as hot spots with multiple root architectural plasticity traits in both populations, and one locus for both root architectural plasticity and grain yield was detected. These results suggest an important role of root architectural plasticity across future rice crop conditions and provide a starting point for marker-assisted selection for plasticity.

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

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

Environmental Control of Root System Biology

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

Root structural and functional dynamics in terrestrial biosphere models--evaluation and recommendations

There is wide breadth of root function within ecosystems that should be considered when modeling the terrestrial biosphere. Root structure and function are closely associated with control of plant water and nutrient uptake from the soil, plant carbon (C) assimilation, partitioning and release to the soils, and control of biogeochemical cycles through interactions within the rhizosphere. Root function is extremely dynamic and dependent on internal plant signals, root traits and morphology, and the physical, chemical and biotic soil environment. While plant roots have significant structural and functional plasticity to changing environmental conditions, their dynamics are noticeably absent from the land component of process-based Earth system models used to simulate global biogeochemical cycling. Their dynamic representation in large-scale models should improve model veracity. Here, we describe current root inclusion in models across scales, ranging from mechanistic processes of single roots to parameterized root processes operating at the landscape scale. With this foundation we discuss how existing and future root functional knowledge, new data compilation efforts, and novel modeling platforms can be leveraged to enhance root functionality in large-scale terrestrial biosphere models by improving parameterization within models, and introducing new components such as dynamic root distribution and root functional traits linked to resource extraction.

Genetic analysis of root morphological traits in wheat

Traits related to root architecture are of great importance for yield performance of crop species, although they remain poorly understood. The present study is aimed at identifying the genomic regions involved in the control of root morphological traits in durum wheat (Triticum durum Desf.). A set of 123 recombinant inbred lines derived from the durum wheat cross of cvs. 'Creso' × 'Pedroso' were grown hydroponically to two growth stages, and were phenotypically evaluated for a number of root traits. In addition, meta-(M)QTL analysis was performed that considered the results of other root traits studies in wheat, to compare with the 'Creso' × 'Pedroso' cross and to increase the QTL detection power. Eight quantitative trait loci (QTL) for traits related to root morphology were identified on chromosomes 1A, 1B, 2A, 3A, 6A and 6B in the 'Creso' × 'Pedroso' segregating population. Twenty-two MQTL that comprised from two to six individual QTL that had widely varying confidence intervals were found on 14 chromosomes. The data from the present study provide a detailed analysis of the genetic basis of morphological root traits in wheat. This study of the 'Creso' × 'Pedroso' durum-wheat population has revealed some QTL that had not been previously identified.

Integration of root phenes for soil resource acquisition

Suboptimal availability of water and nutrients is a primary limitation to plant growth in terrestrial ecosystems. The acquisition of soil resources by plant roots is therefore an important component of plant fitness and agricultural productivity. Plant root systems comprise a set of phenes, or traits, that interact. Phenes are the units of the plant phenotype, and phene states represent the variation in form and function a particular phene may take. Root phenes can be classified as affecting resource acquisition or utilization, influencing acquisition through exploration or exploitation, and in being metabolically influential or neutral. These classifications determine how one phene will interact with another phene, whether through foraging mechanisms or metabolic economics. Phenes that influence one another through foraging mechanisms are likely to operate within a phene module, a group of interacting phenes, that may be co-selected. Examples of root phene interactions discussed are: (1) root hair length × root hair density, (2) lateral branching × root cortical aerenchyma (RCA), (3) adventitious root number × adventitious root respiration and basal root growth angle (BRGA), (4) nodal root number × RCA, and (5) BRGA × root hair length and density. Progress in the study of phenes and phene interactions will be facilitated by employing simulation modeling and near-isophenic lines that allow the study of specific phenes and phene combinations within a common phenotypic background. Developing a robust understanding of the phenome at the organismal level will require new lines of inquiry into how phenotypic integration influences plant function in diverse environments. A better understanding of how root phenes interact to affect soil resource acquisition will be an important tool in the breeding of crops with superior stress tolerance and reduced dependence on intensive use of inputs.

Dynamic root growth and architecture responses to limiting nutrient availability: linking physiological models and experimentation

In recent years the study of root phenotypic plasticity in response to sub-optimal environmental factors and the genetic control of these responses have received renewed attention. As a path to increased productivity, in particular for low fertility soils, several applied research projects worldwide target the improvement of crop root traits both in plant breeding and biotechnology contexts. To assist these tasks and address the challenge of optimizing root growth and architecture for enhanced mineral resource use, the development of realistic simulation models is of great importance. We review this research field from a modeling perspective focusing particularly on nutrient acquisition strategies for crop production on low nitrogen and low phosphorous soils. Soil heterogeneity and the dynamics of nutrient availability in the soil pose a challenging environment in which plants have to forage efficiently for nutrients in order to maintain their internal nutrient homeostasis throughout their life cycle. Mathematical models assist in understanding plant growth strategies and associated root phenes that have potential to be tested and introduced in physiological breeding programs. At the same time, we stress that it is necessary to carefully consider model assumptions and development from a whole plant-resource allocation perspective and to introduce or refine modules simulating explicitly root growth and architecture dynamics through ontogeny with reference to key factors that constrain root growth. In this view it is important to understand negative feedbacks such as plant-plant competition. We conclude by briefly touching on available and developing technologies for quantitative root phenotyping from lab to field, from quantification of partial root profiles in the field to 3D reconstruction of whole root systems. Finally, we discuss how these approaches can and should be tightly linked to modeling to explore the root phenome.

Root cortical burden influences drought tolerance in maize

BACKGROUND AND AIMS

Root cortical aerenchyma (RCA) increases water and nutrient acquisition by reducing the metabolic costs of soil exploration. In this study the hypothesis was tested that living cortical area (LCA; transversal root cortical area minus aerenchyma area and intercellular air space) is a better predictor of root respiration, soil exploration and, therefore, drought tolerance than RCA formation or root diameter.

METHODS

RCA, LCA, root respiration, root length and biomass loss in response to drought were evaluated in maize (Zea mays) recombinant inbred lines grown with adequate and suboptimal irrigation in soil mesocosms.

KEY RESULTS

Root respiration was highly correlated with LCA. LCA was a better predictor of root respiration than either RCA or root diameter. RCA reduced respiration of large-diameter roots. Since RCA and LCA varied in different parts of the root system, the effects of RCA and LCA on root length were complex. Greater crown-root LCA was associated with reduced crown-root length relative to total root length. Reduced LCA was associated with improved drought tolerance.

CONCLUSIONS

The results are consistent with the hypothesis that LCA is a driver of root metabolic costs and may therefore have adaptive significance for water acquisition in drying soil.

Responses of root architecture development to low phosphorus availability: a review

BACKGROUND

Phosphorus (P) is an essential element for plant growth and development but it is often a limiting nutrient in soils. Hence, P acquisition from soil by plant roots is a subject of considerable interest in agriculture, ecology and plant root biology. Root architecture, with its shape and structured development, can be considered as an evolutionary response to scarcity of resources.

SCOPE

This review discusses the significance of root architecture development in response to low P availability and its beneficial effects on alleviation of P stress. It also focuses on recent progress in unravelling cellular, physiological and molecular mechanisms in root developmental adaptation to P starvation. The progress in a more detailed understanding of these mechanisms might be used for developing strategies that build upon the observed explorative behaviour of plant roots.

CONCLUSIONS

The role of root architecture in alleviation of P stress is well documented. However, this paper describes how plants adjust their root architecture to low-P conditions through inhibition of primary root growth, promotion of lateral root growth, enhancement of root hair development and cluster root formation, which all promote P acquisition by plants. The mechanisms for activating alterations in root architecture in response to P deprivation depend on changes in the localized P concentration, and transport of or sensitivity to growth regulators such as sugars, auxins, ethylene, cytokinins, nitric oxide (NO), reactive oxygen species (ROS) and abscisic acid (ABA). In the process, many genes are activated, which in turn trigger changes in molecular, physiological and cellular processes. As a result, root architecture is modified, allowing plants to adapt effectively to the low-P environment. This review provides a framework for understanding how P deficiency alters root architecture, with a focus on integrated physiological and molecular signalling.

A conceptual model of root hair ideotypes for future agricultural environments: what combination of traits should be targeted to cope with limited P availability?

BACKGROUND

Phosphorus (P) often limits crop production and is frequently applied as fertilizer; however, supplies of quality rock phosphate for fertilizer production are diminishing. Plants have evolved many mechanisms to increase their P acquisition, and an understanding of these traits could result in improved long-term sustainability of agriculture. This Viewpoint focuses on the potential benefits of root hairs to sustainable production.

SCOPE

First the various root-related traits that could be deployed to improve agricultural sustainability are catalogued, and their potential costs and benefits to the plant are discussed. A novel mathematical model describing the effects of length, density and longevity of root hairs on P acquisition is developed, and the relative benefits of these three root-hair traits to plant P nutrition are calculated. Insights from this model are combined with experimental data to assess the relative benefits of a range of root hair ideotypes for sustainability of agriculture.

CONCLUSIONS

A cost-benefit analysis of root traits suggests that root hairs have the greatest potential for P acquisition relative to their cost of production. The novel modelling of root hair development indicates that the greatest gains in P-uptake efficiency are likely to be made through increased length and longevity of root hairs rather than by increasing their density. Synthesizing this information with that from published experiments we formulate six potential ideotypes to improve crop P acquisition. These combine appropriate root hair phenotypes with architectural, anatomical and biochemical traits, such that more root-hair zones are produced in surface soils, where P resources are found, on roots which are metabolically cheap to construct and maintain, and that release more P-mobilizing exudates. These ideotypes could be used to inform breeding programmes to enhance agricultural sustainability.

Contributions of roots and rootstocks to sustainable, intensified crop production

Sustainable intensification is seen as the main route for meeting the world's increasing demands for food and fibre. As demands mount for greater efficiency in the use of resources to achieve this goal, so the focus on roots and rootstocks and their role in acquiring water and nutrients, and overcoming pests and pathogens, is increasing. The purpose of this review is to explore some of the ways in which understanding root systems and their interactions with soils could contribute to the development of more sustainable systems of intensive production. Physical interactions with soil particles limit root growth if soils are dense, but root-soil contact is essential for optimal growth and uptake of water and nutrients. X-ray microtomography demonstrated that maize roots elongated more rapidly with increasing root-soil contact, as long as mechanical impedance was not limiting root elongation, while lupin was less sensitive to changes in root-soil contact. In addition to selecting for root architecture and rhizosphere properties, the growth of many plants in cultivated systems is profoundly affected by selection of an appropriate rootstock. Several mechanisms for scion control by rootstocks have been suggested, but the causal signals are still uncertain and may differ between crop species. Linkage map locations for quantitative trait loci for disease resistance and other traits of interest in rootstock breeding are becoming available. Designing root systems and rootstocks for specific environments is becoming a feasible target.

From lab to field, new approaches to phenotyping root system architecture

Plant root system architecture (RSA) is plastic and dynamic, allowing plants to respond to their environment in order to optimize acquisition of important soil resources. A number of RSA traits are known to be correlated with improved crop performance. There is increasing recognition that future gains in productivity, especially under low input conditions, can be achieved through optimization of RSA. However, realization of this goal has been hampered by low resolution and low throughput approaches for characterizing RSA. To overcome these limitations, new methods are being developed to facilitate high throughput and high content RSA phenotyping. Here we summarize laboratory and field approaches for phenotyping RSA, drawing particular attention to recent advances in plant imaging and analysis. Improvements in phenotyping will facilitate the genetic analysis of RSA and aid in the identification of the genetic loci underlying useful agronomic traits.

Three-dimensional root phenotyping with a novel imaging and software platform

A novel imaging and software platform was developed for the high-throughput phenotyping of three-dimensional root traits during seedling development. To demonstrate the platform's capacity, plants of two rice (Oryza sativa) genotypes, Azucena and IR64, were grown in a transparent gellan gum system and imaged daily for 10 d. Rotational image sequences consisting of 40 two-dimensional images were captured using an optically corrected digital imaging system. Three-dimensional root reconstructions were generated and analyzed using a custom-designed software, RootReader3D. Using the automated and interactive capabilities of RootReader3D, five rice root types were classified and 27 phenotypic root traits were measured to characterize these two genotypes. Where possible, measurements from the three-dimensional platform were validated and were highly correlated with conventional two-dimensional measurements. When comparing gellan gum-grown plants with those grown under hydroponic and sand culture, significant differences were detected in morphological root traits (P < 0.05). This highly flexible platform provides the capacity to measure root traits with a high degree of spatial and temporal resolution and will facilitate novel investigations into the development of entire root systems or selected components of root systems. In combination with the extensive genetic resources that are now available, this platform will be a powerful resource to further explore the molecular and genetic determinants of root system architecture.

Root growth models: towards a new generation of continuous approaches

Models of root system growth emerged in the early 1970s, and were based on mathematical representations of root length distribution in soil. The last decade has seen the development of more complex architectural models and the use of computer-intensive approaches to study developmental and environmental processes in greater detail. There is a pressing need for predictive technologies that can integrate root system knowledge, scaling from molecular to ensembles of plants. This paper makes the case for more widespread use of simpler models of root systems based on continuous descriptions of their structure. A new theoretical framework is presented that describes the dynamics of root density distributions as a function of individual root developmental parameters such as rates of lateral root initiation, elongation, mortality, and gravitropsm. The simulations resulting from such equations can be performed most efficiently in discretized domains that deform as a result of growth, and that can be used to model the growth of many interacting root systems. The modelling principles described help to bridge the gap between continuum and architectural approaches, and enhance our understanding of the spatial development of root systems. Our simulations suggest that root systems develop in travelling wave patterns of meristems, revealing order in otherwise spatially complex and heterogeneous systems. Such knowledge should assist physiologists and geneticists to appreciate how meristem dynamics contribute to the pattern of growth and functioning of root systems in the field.

3D reconstruction and dynamic modeling of root architecture in situ and its application to crop phosphorus research

Root architecture plays important roles in plant water and nutrient acquisition. However, accurate modeling of the root system that provides a realistic representation of roots in the soil is limited by a lack of appropriate tools for the non-destructive and precise measurement of the root system architecture in situ. Here we describe a root growth system in which the roots grow in a solid gel matrix that was used to reconstruct 3D root architecture in situ and dynamically simulate its changes under various nutrient conditions with a high degree of precision. A 3D laser scanner combined with a transparent gel-based growth system was used to capture 3D images of roots. The root system skeleton was extracted using a skeleton extraction method based on the Hough transformation, and mesh modeling using Ball-B spline was employed. We successfully used this system to reconstruct rice and soybean root architectures and determine their changes under various phosphorus (P) supply conditions. Our results showed that the 3D root architecture parameters that were dynamically calculated based on the skeletonization and simulation of root systems were significantly correlated with the biomass and P content of rice and soybean based on both the simulation system and previous reports. Therefore, this approach provides a novel technique for the study of crop root growth and its adaptive changes to various environmental conditions.

Plant competition and exclusion with optimizing individuals

Most models of plant competition represent competition as taking place between species when realistically competition takes place between individuals. We model individual plants as optimally choosing biomass in order to maximize net energy that is directed into reproduction. Competition is for access to light and a plant that grows more biomass adds to the leaf area index, creating negative feedback in the form of more self shading and shading of its neighbors. In each period and for given species densities, simultaneous maximization by all plants yields an equilibrium characterized by optimum biomasses. Between periods the net energies plants obtain are used to update the densities, and if densities change the equilibrium changes in the subsequent period. A steady state is attained when all plants have net energies that just allow for replacement. Four main predictions of the resource-ratio theory of competition are obtained, providing behavioral underpinnings for species level models. However, if individual plant parameters are not identical across species, then the predictions do not follow. The optimization framework yields many other predictions, including how specific leaf areas and resource stress impact biomass and leaf area indices.

Root system architecture: opportunities and constraints for genetic improvement of crops

Abiotic stresses increasingly curtail crop yield as a result of global climate change and scarcity of water and nutrients. One way to minimize the negative impact of these factors on yield is to manipulate root system architecture (RSA) towards a distribution of roots in the soil that optimizes water and nutrient uptake. It is now established that most of the genetic variation for RSA is driven by a suite of quantitative trait loci. As we discuss here, marker-assisted selection and quantitative trait loci cloning for RSA are underway, exploiting genomic resources, candidate genes and the knowledge gained from Arabidopsis, rice and other crops. Nonetheless, efficient and accurate phenotyping, modelling and collaboration with breeders remain important challenges, particularly when defining ideal RSA for different crops and target environments.

Ethylene modulates genetic, positional, and nutritional regulation of root plagiogravitropism

Plagiogravitropic growth of roots strongly affects root architecture and topsoil exploration, which are important for the acquisition of water and nutrients. Here we show that basal roots of Phaseolus vulgaris L. develop from 2-3 definable whorls at the root-shoot interface and exhibit position-dependent plagiogravitropic growth. The whorl closest to the shoot produces the shallowest roots, and lower whorls produce deeper roots. Genotypes vary in both the average growth angles of roots within whorls and the range of growth angles, i.e. the difference between the shallowest and deepest basal roots within a root system. Since ethylene has been implicated in both gravitropic and edaphic stress responses, we studied the role of ethylene and its interaction with phosphorus availability in regulating growth angles of genotypes with shallow or deep basal roots. There was a weak correlation between growth angle and ethylene production in the basal rooting zone, but ethylene sensitivity was strongly correlated with growth angle. Basal roots emerging from the uppermost whorl were more responsive to ethylene treatment than the lower-most whorl, displaying shallower angles and inhibition of growth. Ethylene sensitivity is greater for shallow than for deep genotypes and for plants grown with low phosphorus compared with those supplied with high phosphorus. Ethylene exposure increased the range of angles, although deep genotypes grown in low phosphorus were less affected. Our results identify basal root whorl number as a novel architectural trait, and show that ethylene mediates regulation of growth angle by position of origin, genotype and phosphorus availability.

Assessing the importance of genotype x environment interaction for root traits in rice using a mapping population II: conventional QTL analysis

Modifying plant root systems is considered a means of crop improvement targeted to low-resource environments, particularly low nutrient and drought-prone agriculture. The identification of quantitative trait loci (QTLs) for root traits has stimulated marker-assisted breeding to this end, but different QTLs have been detected in different populations of the same species, and importantly, in the same population when grown in different experimental environments. The presence of QTL x environment interaction is implicated, and this must be characterised if the utility of the target QTLs is to be realised. Previous attempts to do this suffer from a lack of control over replicate environments and inadequate statistical rigour. The Bala x Azucena mapping population was grown in two replicate experiments of four treatment environments, a control, a low light, a low soil nitrogen and a low soil water treatment. After a 4 weeks growth, maximum root length, maximum root thickness, root mass below 50 cm, total plant dry mass, % root mass and shoot length were measured. A summary of the overall results is presented in an accompanying paper. Here, QTL analysis by composite interval mapping is presented. A total of 145 QTLs were detected, mapping to 37 discrete loci on all chromosomes. Superficial evidence of QTL x E (great difference in LOD score) was tested by single-marker analysis which confirmed QTL x E for five loci representing only five individual trait-loci interactions. Some loci appeared to be stable across environments. Some QTLs were clearly more or less active under low light, low nitrogen or drought. A few notable loci on chromosomes 1, 2, 3, 5, 7 and 9 are briefly discussed. Also discussed are some remaining statistical shortcomings that will be addressed in another companion paper.

Detection of quantitative trait loci for seminal root traits in maize (Zea mays L.) seedlings grown under differential phosphorus levels

Suboptimal phosphorus availability is a primary constraint for terrestrial plant growth. Seminal roots play an important role in acquisition of nutrients by plant seedlings. The length and number of seminal roots may be particularly important in acquisition of immobile nutrients such as phosphorus by increasing soil exploration. The objective of this study was to identify quantitative trait loci (QTL) controlling seminal root growth in response to phosphorus stress in maize, and to characterize epistatic interactions among QTL. Seminal root length and number were evaluated in 162 recombinant inbred lines derived from a cross between B73 and Mo17 in seedlings grown in a controlled environment. B73 and Mo17 significantly differed for seminal root length under low phosphorus, but not under adequate phosphorus conditions. Seminal root length of the population grown under low phosphorus ranged from 0 to 79.2 cm with a mean of 32.3 cm; while seminal root length of plants grown under high phosphorus ranged from 0.67 to 59.0 cm with a mean of 23.4 cm. Under low phosphorus, one main-effect QTL was associated with seminal root length and three QTL with seminal root number; under high phosphorus, two QTL with seminal root length and three QTL for seminal root number. These accounted for 11, 25.4, 22.8, and 24.1% of the phenotypic variations for seminal root length and number at low phosphorus, and seminal root length and number at high phosphorus, respectively. Di-genic epistatic loci were detected for seminal root length at low phosphorus (two pairs) seminal root number at low phosphorus (eight pairs), seminal root length at high phosphorus (four pairs), and seminal root number at high phosphorus (two pairs), which accounted for 23.2, 50.6, 32.2, and 20.3% of the total variations, respectively. Seminal root traits observed here were positively yet weakly correlated with shoot biomass in the field under low phosphorus, although no coincident QTL were detected. These results suggest that epistatic interactions are important in controlling genotypic variation associated with seedling seminal root traits.

Root architectural tradeoffs for water and phosphorus acquisition

Root architectural traits that increase topsoil foraging are advantageous for phosphorus acquisition but may incur tradeoffs for the acquisition of deep soil resources such as water. To examine this relationship, common bean genotypes contrasting for rooting depth were grown in the field and in the greenhouse with phosphorus stress, water stress and combined phosphorus and water stress. In the greenhouse, water and phosphorus availability were vertically stratified to approximate field conditions, with higher phosphorus in the upper layer and more moisture in the bottom layer. Under phosphorus stress, shallow-rooted genotypes grew best, whereas under drought stress, deep-rooted genotypes grew best. In the combined stress treatment, the best genotype in the greenhouse had a dimorphic root system that permitted vigorous rooting throughout the soil profile. In the field, shallow-rooted genotypes surpassed deep-rooted genotypes under combined stress. This may reflect the importance of early vegetative growth in terminal drought environments. Our results support the hypothesis that root architectural tradeoffs exist for multiple resource acquisition, particularly when resources are differentially localised in the soil profile. Architectural plasticity and root dimorphism achieved through complementary growth of distinct root classes may be important means to optimise acquisition of multiple soil resources.

Topsoil foraging and phosphorus acquisition efficiency in maize (Zea mays)

In soybean and common bean, enhanced topsoil foraging permitted by shallow root architectures is advantageous for phosphorus acquisition from stratified soils. The importance of this phenomenon in graminaceous crops, which have different root architecture and morphology from legumes, is unclear. In this study we evaluated the importance of shallow roots for phosphorus acquisition in maize (Zea mays L.). In a field study, maize genotypes with shallower roots had greater growth in low phosphorus soil than deep-rooted genotypes. For physiological analysis, four maize genotypes differing in root shallowness in the field were grown in solid media with stratified phosphorus availability in a controlled environment. Of the four genotypes, one shallow and one deep genotype were also inoculated with arbuscular mycorrhiza (AM). Shallower genotypes had significantly greater growth and phosphorus accumulation compared with deeper genotypes at low phosphorus availability. Mycorrhizal colonisation altered root shallowness under low phosphorus conditions, increasing shallowness substantially in a deep-rooted genotype but slightly decreasing shallowness in a shallow-rooted genotype. Mycorrhizal colonisation increased phosphorus acquisition under low phosphorus availability. Respiration costs of roots and shoots of phosphorus-efficient genotypes were significantly lower under low phosphorus conditions compared with inefficient genotypes. The physiological efficiency of phosphorus acquisition, expressed as root respiration per unit of phosphorus acquisition, was greater in shallow rooted genotypes. Our results demonstrate that genetic variation for root shallowness exists in maize, that phosphorus and AM can modulate root shallowness independently, and that a shallower root system is beneficial for plant performance in maize at low phosphorus availability. We propose that root architectural traits that enhance topsoil foraging are important traits for improved phosphorus acquisition efficiency of annual grain crops such as maize in addition to legumes.

Evolution of phenotypic plasticity: where are we going now?

The study of phenotypic plasticity has progressed significantly over the past few decades. We have moved from variation for plasticity being considered as a nuisance in evolutionary studies to it being the primary target of investigations that use an array of methods, including quantitative and molecular genetics, as well as of several approaches that model the evolution of plastic responses. Here, I consider some of the major aspects of research on phenotypic plasticity, assessing where progress has been made and where additional effort is required. I suggest that some areas of research, such the study of the quantitative genetic underpinning of plasticity, have been either settled in broad outline or superseded by new approaches and questions. Other issues, such as the costs of plasticity are currently at the forefront of research in this field, and are likely to be areas of major future development.

Intrinsic and environmental response pathways that regulate root system architecture

Root system development is an important agronomic trait. The right architecture in a given environment allows plants to survive periods of water of nutrient deficit, and compete effectively for resources. Root systems also provide an optimal system for studying developmental plasticity, a characteristic feature of plant growth. This review proposes a framework for describing the pathways regulating the development of complex structures such as root systems: intrinsic pathways determine the characteristic architecture of the root system in a given plant species, and define the limits for plasticity in that species. Response pathways co-ordinate environmental cues with development by modulating intrinsic pathways. The current literature describing the regulation of root system development is summarized here within this framework. Regulatory pathways are also organized based on their specific developmental effect in the root system. All the pathways affect lateral root formation, but some specifically target initiation of the lateral root, while others target the development and activation of the lateral root primordium, or the elongation of the lateral root. Finally, we discuss emerging approaches for understanding the regulation of root system architecture.

Genetic mapping of basal root gravitropism and phosphorus acquisition efficiency in common bean

Root gravitropism determines the relative distribution of plant roots in different soil layers, and therefore, may influence the acquisition of shallow soil resources such as phosphorus (P). Growth pouch and field studies were conducted to evaluate root gravitropism of common bean (Phaseolus vulgaris L.) in response to P deficiency and to detect quantitative trait loci (QTL) associated with this trait. A deep-rooted genotype, DOR364, was crossed with a shallow-rooted genotype, G19833, to obtain 86 F_5.7 recombinant inbred lines (RILs). Root gravitropic traits were measured as basal root growth angle (BRGA), shallow basal root length (SBRL, basal root length in the top 0-3 cm of soil) and relative shallow basal root length (RSBRL, percentage of basal root length in the top 0-3 cm of soil relative to total basal root length). Large genetic variability for these traits was found in the parents and RILs, with BRGA ranging from -18.73 to 56.69º and SBRL ranging from 0.42 to 2.63 m per plant. The parents and six RILs with contrasting root gravitropism were further evaluated in the field, where root shallowness was significantly correlated with plant growth and P uptake. QTL were detected by single point analysis (SPA), interval mapping (IM) and composite interval mapping (CIM) techniques with a genetic map for the DOR364 × G19833 population consisting of 236 molecular markers. The IM / CIM QTL were detected among the 11 linkage groups of common bean, with 16 QTL controlling the above root traits and six QTL controlling P acquisition efficiency (PAE) in the field study. At least three of the root trait QTL were associated with QTL for PAE, suggesting that root gravitropic traits are associated with PAE and that QTL for these traits can be used to facilitate selection and breeding for higher P efficiency in common bean and other crops.