Laser ablation tomography for visualization of root colonization by edaphic organisms

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

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

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

Greater lateral root branching density in maize improves phosphorus acquisition from low phosphorus soil

The development of crops with better growth under suboptimal phosphorus availability would improve food security in developing countries while reducing environmental pollution in developed countries. We tested the hypothesis that maize (Zea mays) phenotypes with greater lateral root branching density have greater phosphorus acquisition from low phosphorus soils. Recombinant inbred lines with either 'many short' (MS) or 'few long' (FL) lateral root phenotypes were grown under high and low phosphorus conditions in greenhouse mesocosms and in the field. Under low phosphorus in mesocosms, lines with the MS phenotype had 89% greater phosphorus acquisition and 48% more shoot biomass than FL lines. Under low phosphorus in the field, MS lines had 16% shallower rooting depth (D95), 81% greater root length density in the top 20 cm of the soil, 49% greater shoot phosphorus content, 12% greater leaf photosynthesis, 19% greater shoot biomass, and 14% greater grain yield than FL lines. These results are consistent with the hypothesis that the phenotype of many, shorter lateral roots improves phosphorus acquisition under low phosphorus availability and merits consideration for genetic improvement of phosphorus efficiency in maize and other crops.

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.

Maize Genomes to Fields: 2014 and 2015 field season genotype, phenotype, environment, and inbred ear image datasets

OBJECTIVES

Crop improvement relies on analysis of phenotypic, genotypic, and environmental data. Given large, well-integrated, multi-year datasets, diverse queries can be made: Which lines perform best in hot, dry environments? Which alleles of specific genes are required for optimal performance in each environment? Such datasets also can be leveraged to predict cultivar performance, even in uncharacterized environments. The maize Genomes to Fields (G2F) Initiative is a multi-institutional organization of scientists working to generate and analyze such datasets from existing, publicly available inbred lines and hybrids. G2F's genotype by environment project has released 2014 and 2015 datasets to the public, with 2016 and 2017 collected and soon to be made available.

DATA DESCRIPTION

Datasets include DNA sequences; traditional phenotype descriptions, as well as detailed ear, cob, and kernel phenotypes quantified by image analysis; weather station measurements; and soil characterizations by site. Data are released as comma separated value spreadsheets accompanied by extensive README text descriptions. For genotypic and phenotypic data, both raw data and a version with outliers removed are reported. For weather data, two versions are reported: a full dataset calibrated against nearby National Weather Service sites and a second calibrated set with outliers and apparent artifacts removed.

Reduced root cortical burden improves growth and grain yield under low phosphorus availability in maize

Root phenes and phene states that reduce the metabolic cost of soil exploration may improve plant growth under low phosphorus availability. We tested the hypothesis that under low phosphorus, reduced living cortical area (LCA) would increase soil exploration, phosphorus capture, biomass, and grain yield. Maize genotypes contrasting in LCA were grown in the field and in greenhouse mesocosms under optimal and suboptimal phosphorus regimes. Percent LCA in nodal roots ranged from 25% to 67%. Plants with 0.2 mm² less LCA under low phosphorus had 75% less root segment respiration, 54% less root phosphorus content, rooted 20 cm deeper, allocated up to four times more roots between 60 and 120 cm depth, had between 20% and 150% more biomass, 35-40% greater leaf phosphorus content, and 60% greater grain yield compared with plants with high LCA. Low-LCA plants had up to 55% less arbuscular mycorrhizal colonization in axial roots, but this decrease was not correlated with biomass or phosphorus content. The LCA components cortical cell file number and cortical cell size were important for biomass and phosphorus content under low phosphorus. These results are consistent with the hypothesis that root phenes that decrease the metabolic cost of soil exploration are adaptive under phosphorus stress.

Ethylene modulates root cortical senescence in barley

Background and Aims

Root cortical senescence (RCS) is a poorly understood phenomenon with implications for adaptation to edaphic stress. It was hypothesized that RCS in barley (Hordeum vulgare L.) is (1) accelerated by exogenous ethylene exposure; (2) accompanied by differential expression of ethylene synthesis and signalling genes; and (3) associated with differential expression of programmed cell death (PCD) genes.

Methods

Gene expression of root segments from four barley genotypes with and without RCS was evaluated using quantitative real-time PCR (qRT-PCR). The progression of RCS was manipulated with root zone ethylene and ethylene inhibitor applications.

Key Results

The results demonstrate that ethylene modulates RCS. Four genes related to ethylene synthesis and signalling were upregulated during RCS in optimal, low nitrogen and low phosphorus nutrient regimes. RCS was accelerated by root zone ethylene treatment, and this effect was reversed by an ethylene action inhibitor. Roots treated with exogenous ethylene had 35 and 46 % more cortical senescence compared with the control aeration treatment in seminal and nodal roots, respectively. RCS was correlated with expression of two genes related to programmed cell death (PCD).

Conclusions

The development of RCS is similar to root cortical aerenchyma formation with respect to ethylene modulation of the PCD process.

Rightsizing root phenotypes for drought resistance

I propose that reduced root development would be advantageous for drought resistance in high-input agroecosystems. Selection regimes for crop ancestors and landraces include multiple stresses, intense competition, and variable resource distribution, which favored prolific root production, developmental plasticity in response to resource availability, and maintenance of unspecialized root tissues. High-input agroecosystems have removed many of these constraints to root function. Therefore, root phenotypes that focus on water capture at the expense of ancestral adaptations would be better suited to high-input agroecosystems. Parsimonious architectural phenotypes include fewer axial roots, reduced density of lateral roots, reduced growth responsiveness to local resource availability, and greater loss of roots that do not contribute to water capture. Parsimonious anatomical phenotypes include a reduced number of cortical cell files, greater loss of cortical parenchyma to aerenchyma and senescence, and larger cortical cell size. Parsimonious root phenotypes may be less useful in low-input agroecosystems, which are characterized by multiple challenges and trade-offs for root function in addition to water capture. Analysis of the fitness landscape of root phenotypes is a complex challenge that will be aided by the development of robust functional-structural models capable of simulating the dynamics of root-soil interactions.

Large Crown Root Number Improves Topsoil Foraging and Phosphorus Acquisition

Suboptimal phosphorus (P) availability is a primary constraint to plant growth on Earth. We tested the hypothesis that maize (Zea mays) genotypes with large crown root number (CN) will have shallower rooting depth and improved P acquisition from low-P soils. Maize recombinant inbred lines with contrasting CN were evaluated under suboptimal P availability in greenhouse mesocosms and the field. Under P stress in mesocosms, the large-CN phenotype had 48% greater root respiration, 24% shallower rooting depth, 32% greater root length density in the topsoil, 37% greater leaf P concentration, 48% greater leaf photosynthesis, 33% greater stomatal conductance, and 44% greater shoot biomass than the small-CN phenotype. Under P stress in the field, the large-CN phenotype had 32% shallower rooting depth, 51% greater root length density in the topsoil, 44% greater leaf P concentration, 18% greater leaf photosynthesis, 21% greater stomatal conductance, 23% greater shoot biomass at anthesis, and 28% greater yield than the small-CN phenotype. These results support the hypothesis that large CN improves plant P acquisition from low-P soils by reducing rooting depth and increasing topsoil foraging. The large-CN phenotype merits consideration as a selection target to improve P capture in maize and possibly other cereal crops.

A mechanistic framework for auxin dependent Arabidopsis root hair elongation to low external phosphate

Phosphate (P) is an essential macronutrient for plant growth. Roots employ adaptive mechanisms to forage for P in soil. Root hair elongation is particularly important since P is immobile. Here we report that auxin plays a critical role promoting root hair growth in Arabidopsis in response to low external P. Mutants disrupting auxin synthesis (taa1) and transport (aux1) attenuate the low P root hair response. Conversely, targeting AUX1 expression in lateral root cap and epidermal cells rescues this low P response in aux1. Hence auxin transport from the root apex to differentiation zone promotes auxin-dependent hair response to low P. Low external P results in induction of root hair expressed auxin-inducible transcription factors ARF19, RSL2, and RSL4. Mutants lacking these genes disrupt the low P root hair response. We conclude auxin synthesis, transport and response pathway components play critical roles regulating this low P root adaptive response.

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.

Reduction in Root Secondary Growth as a Strategy for Phosphorus Acquisition

We tested the hypothesis that reduced root secondary growth of dicotyledonous species improves phosphorus acquisition. Functional-structural modeling in SimRoot indicates that, in common bean (Phaseolus vulgaris), reduced root secondary growth reduces root metabolic costs, increases root length, improves phosphorus capture, and increases shoot biomass in low-phosphorus soil. Observations from the field and greenhouse confirm that, under phosphorus stress, resource allocation is shifted from secondary to primary root growth, genetic variation exists for this response, and reduced secondary growth improves phosphorus capture from low-phosphorus soil. Under low phosphorus in greenhouse mesocosms, genotypes with reduced secondary growth had 39% smaller root cross-sectional area, 60% less root respiration, 27% greater root length, 78% greater shoot phosphorus content, and 68% greater shoot mass than genotypes with advanced secondary growth. In the field under low phosphorus, these genotypes had 43% smaller root cross-sectional area, 32% greater root length, 58% greater shoot phosphorus content, and 80% greater shoot mass than genotypes with advanced secondary growth. Secondary growth eliminated arbuscular mycorrhizal associations as cortical tissue was destroyed. These results support the hypothesis that reduced root secondary growth is an adaptive response to low phosphorus availability and merits investigation as a potential breeding target.

The Prognostic Importance of Bronchoalveolar Lavage Fluid CXCL9 During Minimal Acute Rejection on the Risk of Chronic Lung Allograft Dysfunction

The clinical significance and treatment strategies for minimal acute rejection (grade A1), the most common form of acute rejection (AR), remain controversial. In this retrospective single-center cohort study of 441 lung transplant recipients, we formally evaluate the association between minimal AR and chronic lung allograft dysfunction (CLAD) and test a novel hypothesis using bronchoalveolar lavage (BAL) CXCL9 concentration during minimal AR as a biomarker of subsequent CLAD development. In univariable and multivariable models adjusted for all histopathologic injury patterns, minimal AR was not associated with CLAD development. However, minimal AR with elevated BAL CXCL9 concentrations markedly increased CLAD risk in a dose-response manner. Minimal AR with CXCL9 concentrations greater than the 25th, 50th, and 75th percentile had adjusted hazard ratios (HRs) for CLAD of 1.1 (95% confidence interval [CI] 0.8-1.6), 1.6 (95% CI 1.1-2.3), and 2.2 (95% CI 1.4-3.4), respectively. Thus we demonstrate the utility of BAL CXCL9 measurement as a prognostic biomarker that allows discrimination of recipients at increased risk of CLAD development after minimal AR. BAL CXCL9 measurement during transbronchial biopsies may provide clinically useful prognostic data and guide treatment decisions for this common form of AR, as a possible strategy to minimize CLAD development.

Root cortical senescence decreases root respiration, nutrient content and radial water and nutrient transport in barley

The functional implications of root cortical senescence (RCS) are poorly understood. We tested the hypotheses that RCS in barley (1) reduces the respiration and nutrient content of root tissue; (2) decreases radial water and nutrient transport; and (3) is accompanied by increased suberization to protect the stele. Genetic variation for RCS exists between modern germplasm and landraces. Nitrogen and phosphorus deficiency increased the rate of RCS. Maximal RCS, defined as the disappearance of the entire root cortex, reduced root nitrogen content by 66%, phosphorus content by 63% and respiration by 87% compared with root segments with no RCS. Roots with maximal RCS had 90, 92 and 84% less radial water, nitrate and phosphorus transport, respectively, compared with segments with no RCS. The onset of RCS coincided with 30% greater aliphatic suberin in the endodermis. These results support the hypothesis that RCS reduces root carbon and nutrient costs and may therefore have adaptive significance for soil resource acquisition. By reducing root respiration and nutrient content, RCS could permit greater root growth, soil resource acquisition and resource allocation to other plant processes. RCS merits investigation as a trait for improving the performance of barley, wheat, triticale and rye under edaphic stress.

OpenSimRoot: widening the scope and application of root architectural models

OpenSimRoot is an open-source, functional-structural plant model and mathematical description of root growth and function. We describe OpenSimRoot and its functionality to broaden the benefits of root modeling to the plant science community. OpenSimRoot is an extended version of SimRoot, established to simulate root system architecture, nutrient acquisition and plant growth. OpenSimRoot has a plugin, modular infrastructure, coupling single plant and crop stands to soil nutrient and water transport models. It estimates the value of root traits for water and nutrient acquisition in environments and plant species. The flexible OpenSimRoot design allows upscaling from root anatomy to plant community to estimate the following: resource costs of developmental and anatomical traits; trait synergisms; and (interspecies) root competition. OpenSimRoot can model three-dimensional images from magnetic resonance imaging (MRI) and X-ray computed tomography (CT) of roots in soil. New modules include: soil water-dependent water uptake and xylem flow; tiller formation; evapotranspiration; simultaneous simulation of mobile solutes; mesh refinement; and root growth plasticity. OpenSimRoot integrates plant phenotypic data with environmental metadata to support experimental designs and to gain a mechanistic understanding at system scales.

Root Cortical Senescence Improves Growth under Suboptimal Availability of N, P, and K

Root cortical senescence (RCS) in Triticeae reduces nutrient uptake, nutrient content, respiration, and radial hydraulic conductance of root tissue. We used the functional-structural model SimRoot to evaluate the functional implications of RCS in barley (Hordeum vulgare) under suboptimal nitrate, phosphorus, and potassium availability. The utility of RCS was evaluated using sensitivity analyses in contrasting nutrient regimes. At flowering (80 d), RCS increased simulated plant growth by up to 52%, 73%, and 41% in nitrate-, phosphorus-, and potassium-limiting conditions, respectively. Plants with RCS had reduced nutrient requirement of root tissue for optimal plant growth, reduced total cumulative cortical respiration, and increased total carbon reserves. Nutrient reallocation during RCS had a greater effect on simulated plant growth than reduced respiration or nutrient uptake. Under low nutrient availability, RCS had greater benefit in plants with fewer tillers. RCS had greater benefit in phenotypes with fewer lateral roots at low nitrate availability, but the opposite was true in low phosphorus or potassium availability. Additionally, RCS was quantified in field-grown barley in different nitrogen regimes. Field and virtual soil coring simulation results demonstrated that living cortical volume per root length (an indicator of RCS) decreased with depth in younger plants, while roots of older plants had very little living cortical volume per root length. RCS may be an adaptive trait for nutrient acquisition by reallocating nutrients from senescing tissue and secondarily by reducing root respiration. These simulated results suggest that RCS merits investigation as a breeding target for enhanced soil resource acquisition and edaphic stress tolerance.

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

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

Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform

Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop.

Impact of Allograft Injury Time of Onset on the Development of Chronic Lung Allograft Dysfunction After Lung Transplantation

The impact of allograft injury time of onset on the risk of chronic lung allograft dysfunction (CLAD) remains unknown. We hypothesized that episodes of late-onset (≥6 months) allograft injury would produce an augmented CXCR3/ligand immune response, leading to increased CLAD. In a retrospective single-center study, 1894 transbronchial biopsy samples from 441 lung transplant recipients were reviewed for the presence of acute rejection (AR), lymphocytic bronchiolitis (LB), diffuse alveolar damage (DAD), and organizing pneumonia (OP). The association between the time of onset of each injury pattern and CLAD was assessed by using multivariable Cox models with time-dependent covariates. Bronchoalveolar lavage (BAL) CXCR3 ligand concentrations were compared between early- and late-onset injury patterns using linear mixed-effects models. Late-onset DAD and OP were strongly associated with CLAD: adjusted hazard ratio 2.8 (95% confidence interval 1.5-5.3) and 2.0 (1.1-3.4), respectively. The early-onset form of these injury patterns did not increase CLAD risk. Late-onset LB and acute rejection (AR) predicted CLAD in univariable models but lost significance after multivariable adjustment for late DAD and OP. AR was the only early-onset injury pattern associated with CLAD development. Elevated BAL CXCR3 ligand concentrations during late-onset allograft injury parallel the increase in CLAD risk and support our hypothesis that late allograft injuries result in a more profound CXCR3/ligand immune response.

Genome-wide association mapping and agronomic impact of cowpea root architecture

Genetic analysis of data produced by novel root phenotyping tools was used to establish relationships between cowpea root traits and performance indicators as well between root traits and Striga tolerance. Selection and breeding for better root phenotypes can improve acquisition of soil resources and hence crop production in marginal environments. We hypothesized that biologically relevant variation is measurable in cowpea root architecture. This study implemented manual phenotyping (shovelomics) and automated image phenotyping (DIRT) on a 189-entry diversity panel of cowpea to reveal biologically important variation and genome regions affecting root architecture phenes. Significant variation in root phenes was found and relatively high heritabilities were detected for root traits assessed manually (0.4 for nodulation and 0.8 for number of larger laterals) as well as repeatability traits phenotyped via DIRT (0.5 for a measure of root width and 0.3 for a measure of root tips). Genome-wide association study identified 11 significant quantitative trait loci (QTL) from manually scored root architecture traits and 21 QTL from root architecture traits phenotyped by DIRT image analysis. Subsequent comparisons of results from this root study with other field studies revealed QTL co-localizations between root traits and performance indicators including seed weight per plant, pod number, and Striga (Striga gesnerioides) tolerance. The data suggest selection for root phenotypes could be employed by breeding programs to improve production in multiple constraint environments.

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

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

Genetic Variability in Phosphorus Responses of Rice Root Phenotypes

BACKGROUND

Low phosphorus availability is a major factor limiting rice productivity. Since root traits determine phosphorus acquisition efficiency, they are logical selection targets for breeding rice with higher productivity in low phosphorus soils. Before using these traits for breeding, it is necessary to identify genetic variation and to assess the plasticity of each trait in response to the environment. In this study, we measured phenotypic variation and effect of phosphorus deficiency on root architectural, morphological and anatomical traits in 15 rice (Oryza sativa) genotypes. Rice plants were grown with diffusion-limited phosphorus using solid-phase buffered phosphorus to mimic realistic phosphorus availability conditions.

RESULTS

Shoot dry weight, tiller number, plant height, number of nodal roots and shoot phosphorus content were reduced under low phosphorus availability. Phosphorus deficiency significantly reduced large lateral root density and small and large lateral root length in all genotypes, though the degree of plasticity and relative allocation of root length between the two root classes varied among genotypes. Root hair length and density increased in all genotypes in response to low phosphorus. Nodal root cross-sectional area was significantly less under low phosphorus availability, and reduced cortical area was disproportionately responsible for this decline. Phosphorus deficiency caused a 20 % increase in the percent cortical area converted to aerenchyma. Total stele area and meta-xylem vessel area responses to low phosphorus differed significantly among genotypes. Phosphorus treatment did not significantly affect theoretical water conductance overall, but increased or reduced it in a few genotypes. All genotypes had restricted water conductance at the base of the nodal root compared to other positions along the root axis.

CONCLUSIONS

There was substantial genetic variation for all root traits investigated. Low phosphorus availability significantly affected most traits, often to an extent that varied with the genotype. With the exception of stele and meta-xylem vessel area, root responses to low phosphorus were in the same direction for all genotypes tested. Therefore, phenotypic evaluations conducted with adequate fertility should be useful for genetic mapping studies and identifying potential sources of trait variation, but these should be confirmed in low-phosphorus environments.

Impact of axial root growth angles on nitrogen acquisition in maize depends on environmental conditions

BACKGROUNDS AND AIMS

Crops with reduced requirement for nitrogen (N) fertilizer would have substantial benefits in developed nations, while improving food security in developing nations. This study employs the functional structural plant model SimRoot to test the hypothesis that variation in the growth angles of axial roots of maize (Zea mays L.) is an important determinant of N capture.

METHODS

Six phenotypes contrasting in axial root growth angles were modelled for 42 d at seven soil nitrate levels from 10 to 250 kg ha(-1) in a sand and a silt loam, and five precipitation regimes ranging from 0·5× to 1·5× of an ambient rainfall pattern. Model results were compared with soil N measurements of field sites with silt loam and loamy sand textures.

KEY RESULTS

For optimal nitrate uptake, root foraging must coincide with nitrate availability in the soil profile, which depends on soil type and precipitation regime. The benefit of specific root architectures for efficient N uptake increases with decreasing soil N content, while the effect of soil type increases with increasing soil N level. Extreme root architectures are beneficial under extreme environmental conditions. Extremely shallow root systems perform well under reduced precipitation, but perform poorly with ambient and greater precipitation. Dimorphic phenotypes with normal or shallow seminal and very steep nodal roots performed well in all scenarios, and consistently outperformed the steep phenotypes. Nitrate uptake increased under reduced leaching conditions in the silt loam and with low precipitation.

CONCLUSIONS

Results support the hypothesis that root growth angles are primary determinants of N acquisition in maize. With decreasing soil N status, optimal angles resulted in 15-50 % greater N acquisition over 42 d. Optimal root phenotypes for N capture varied with soil and precipitation regimes, suggesting that genetic selection for root phenotypes could be tailored to specific environments.

Reduced crown root number improves water acquisition under water deficit stress in maize (Zea mays L.)

In this study we test the hypothesis that maize genotypes with reduced crown root number (CN) will have greater root depth and improved water acquisition from drying soil. Maize recombinant inbred lines with contrasting CN were evaluated under water stress in greenhouse mesocosms and field rainout shelters. CN varied from 25 to 62 among genotypes. Under water stress in the mesocosms, genotypes with low CN had 31% fewer crown roots, 30% deeper rooting, 56% greater stomatal conductance, 45% greater leaf CO2 assimilation, 61% net canopy CO2 assimilation, and 55% greater shoot biomass than genotypes with high CN at 35 days after planting. Under water stress in the field, genotypes with low CN had 21% fewer crown roots, 41% deeper rooting, 48% lighter stem water oxygen isotope enrichment (δ(18)O) signature signifying deeper water capture, 13% greater leaf relative water content, 33% greater shoot biomass at anthesis, and 57% greater yield than genotypes with high CN. These results support the hypothesis that low CN improves drought tolerance by increasing rooting depth and water acquisition from the subsoil.