Are high-throughput root phenotyping platforms suitable for informing root system architecture models with genotype-specific parameters? An evaluation based on the root model ArchiSimple and a small panel of wheat cultivars.

Given the difficulties in accessing plant roots in situ, high-throughput root phenotyping (HTRP) platforms under controlled conditions have been developed to meet the growing demand for characterizing root system architecture (RSA) for genetic analyses. However, a proper evaluation of their capacity to provide the same estimates for strictly identical root traits across platforms has never been achieved. In this study, we performed such an evaluation based on six major parameters of the RSA model ArchiSimple, using a diversity panel of 14 bread wheat cultivars in two HTRP platforms that had different growth media and non-destructive imaging systems together with a conventional set-up that had a solid growth medium and destructive sampling. Significant effects of the experimental set-up were found for all the parameters and no significant correlations across the diversity panel among the three set-ups could be detected. Differences in temperature, irradiance, and/or the medium in which the plants were growing might partly explain both the differences in the parameter values across the experiments as well as the genotype × set-up interactions. Furthermore, the values and the rankings across genotypes of only a subset of parameters were conserved between contrasting growth stages. As the parameters chosen for our analysis are root traits that have strong impacts on RSA and are close to parameters used in a majority of RSA models, our results highlight the need to carefully consider both developmental and environmental drivers in root phenomics studies.

Modification of the Expression of the Aquaporin ZmPIP2;5 Affects Water Relations and Plant Growth.

The plasma membrane intrinsic protein PIP2;5 is the most highly expressed aquaporin in maize (Zea mays) roots. Here, we investigated how deregulation of PIP2;5 expression affects water relations and growth using maize overexpression (OE; B104 inbred) or knockout (KO; W22 inbred) lines. The hydraulic conductivity of the cortex cells of roots grown hydroponically was higher in PIP2;5 OE and lower in pip2;5 KO lines compared with the corresponding wild-type plants. While whole-root conductivity decreased in the KO lines compared to the wild type, no difference was observed in OE plants. This paradox was interpreted using the MECHA hydraulic model, which computes the radial flow of water within root sections. The model hints that the plasma membrane permeability of the cells is not radially uniform but that PIP2;5 may be saturated in cell layers with apoplastic barriers, i.e. the endodermis and exodermis, suggesting the presence of posttranslational mechanisms controlling the abundance of PIP in the plasma membrane in these cells. At the leaf level, where the PIP2;5 gene is weakly expressed in wild-type plants, the hydraulic conductance was higher in the PIP2;5 OE lines compared with the wild-type plants, whereas no difference was observed in the pip2;5 KO lines. The temporal trend of leaf elongation rate, used as a proxy for that of xylem water potential, was faster in PIP2;5 OE plants upon mild stress, but not in well-watered conditions, demonstrating that PIP2;5 may play a beneficial role in plant growth under specific conditions.

RBOH-mediated ROS production facilitates lateral root emergence in Arabidopsis.

Lateral root (LR) emergence represents a highly coordinated process in which the plant hormone auxin plays a central role. Reactive oxygen species (ROS) have been proposed to function as important signals during auxin-regulated LR formation; however, their mode of action is poorly understood. Here, we report that Arabidopsis roots exposed to ROS show increased LR numbers due to the activation of LR pre-branch sites and LR primordia (LRP). Strikingly, ROS treatment can also restore LR formation in pCASP1:shy2-2 and aux1 lax3 mutant lines in which auxin-mediated cell wall accommodation and remodeling in cells overlying the sites of LR formation is disrupted. Specifically, ROS are deposited in the apoplast of these cells during LR emergence, following a spatiotemporal pattern that overlaps the combined expression domains of extracellular ROS donors of the RESPIRATORY BURST OXIDASE HOMOLOGS (RBOH). We also show that disrupting (or enhancing) expression of RBOH in LRP and/or overlying root tissues decelerates (or accelerates) the development and emergence of LRs. We conclude that RBOH-mediated ROS production facilitates LR outgrowth by promoting cell wall remodeling of overlying parental tissues.

Going with the Flow: Multiscale Insights into the Composite Nature of Water Transport in Roots.

As water often limits crop production, a more complete understanding of plant water capture and transport is necessary. Here, we developed MECHA, a mathematical model that computes the flow of water across the root at the scale of walls, membranes, and plasmodesmata of individual cells, and used it to test hypotheses related to root water transport in maize (Zea mays). The model uses detailed root anatomical descriptions and a minimal set of experimental cell properties, including the conductivity of plasma membranes, cell walls, and plasmodesmata, which yield quantitative and scale-consistent estimations of water pathways and root radial hydraulic conductivity (k r). MECHA revealed that the mainstream hydraulic theories derived independently at the cell and root segment scales are compatible only if osmotic potentials within the apoplastic domains are uniform. The results suggested that the convection-diffusion of apoplastic solutes explained most of the offset between estimated k r in pressure clamp and osmotic experiments, while the contribution of water-filled intercellular spaces was limited. Furthermore, sensitivity analyses quantified the relative impact of cortex and endodermis cell conductivity of plasma membranes on root k r and suggested that only the latter contributed substantially to k r due to the composite nature of water flow across roots. The explicit root hydraulic anatomy framework brings insights into contradictory interpretations of experiments from the literature and suggests experiments to efficiently address questions pertaining to root water relations. Its scale consistency opens avenues for cross-scale communication in the world of root hydraulics.

Connecting the dots between computational tools to analyse soil-root water relations.

In recent years, many computational tools, such as image analysis, data management, process-based simulation, and upscaling tools, have been developed to help quantify and understand water flow in the soil-root system, at multiple scales (tissue, organ, plant, and population). Several of these tools work together or at least are compatible. However, for the uninformed researcher, they might seem disconnected, forming an unclear and disorganized succession of tools. In this article, we show how different studies can be further developed by connecting them to analyse soil-root water relations in a comprehensive and structured network. This 'explicit network of soil-root computational tools' informs readers about existing tools and helps them understand how their data (past and future) might fit within the network. We also demonstrate the novel possibilities of scale-consistent parameterizations made possible by the network with a set of case studies from the literature. Finally, we discuss existing gaps in the network and how we can move forward to fill them.

Genome-Wide Analysis of Yield in Europe: Allelic Effects Vary with Drought and Heat Scenarios.

Assessing the genetic variability of plant performance under heat and drought scenarios can contribute to reduce the negative effects of climate change. We propose here an approach that consisted of (1) clustering time courses of environmental variables simulated by a crop model in current (35 years × 55 sites) and future conditions into six scenarios of temperature and water deficit as experienced by maize (Zea mays L.) plants; (2) performing 29 field experiments in contrasting conditions across Europe with 244 maize hybrids; (3) assigning individual experiments to scenarios based on environmental conditions as measured in each field experiment; frequencies of temperature scenarios in our experiments corresponded to future heat scenarios (+5°C); (4) analyzing the genetic variation of plant performance for each environmental scenario. Forty-eight quantitative trait loci (QTLs) of yield were identified by association genetics using a multi-environment multi-locus model. Eight and twelve QTLs were associated to tolerances to heat and drought stresses because they were specific to hot and dry scenarios, respectively, with low or even negative allelic effects in favorable scenarios. Twenty-four QTLs improved yield in favorable conditions but showed nonsignificant effects under stress; they were therefore associated with higher sensitivity. Our approach showed a pattern of QTL effects expressed as functions of environmental variables and scenarios, allowing us to suggest hypotheses for mechanisms and candidate genes underlying each QTL. It can be used for assessing the performance of genotypes and the contribution of genomic regions under current and future stress situations and to accelerate breeding for drought-prone environments.

Segregation distortion and genome-wide digenic interactions affect transmission of introgressed chromatin from wild cotton species.

KEY MESSAGE: This study reports transmission genetics of chromosomal segments into Gossypium hirsutum from its most distant euploid relative, Gossypium mustelinum . Mutilocus interactions and structural rearrangements affect introgression and segregation of donor chromatin. Wild allotetraploid relatives of cotton are a rich source of genetic diversity that can be used in genetic improvement, but linkage drag and non-Mendelian transmission genetics are prevalent in interspecific crosses. These problems necessitate knowledge of transmission patterns of chromatin from wild donor species in cultivated recipient species. From an interspecific cross, Gossypium hirsutum × Gossypium mustelinum, we studied G. mustelinum (the most distant tetraploid relative of Upland cotton) allele retention in 35 BC3F1 plants and segregation patterns in BC3F2 populations totaling 3202 individuals, using 216 DNA marker loci. The average retention of donor alleles across BC3F1 plants was higher than expected and the average frequency of G. mustelinum alleles in BC3F2 segregating families was less than expected. Despite surprisingly high retention of G. mustelinum alleles in BC3F1, 46 genomic regions showed no introgression. Regions on chromosomes 3 and 15 lacking introgression were closely associated with possible small inversions previously reported. Nonlinear two-locus interactions are abundant among loci with single-locus segregation distortion, and among loci originating from one of the two subgenomes. Comparison of the present results with those of prior studies indicates different permeability of Upland cotton for donor chromatin from different allotetraploid relatives. Different contributions of subgenomes to two-locus interactions suggest different fates of subgenomes in the evolution of allotetraploid cottons. Transmission genetics of G. hirsutum × G. mustelinum crosses reveals allelic interactions, constraints on fixation and selection of donor alleles, and challenges with retention of introgressed chromatin for crop improvement.

QTL analysis of cotton fiber length in advanced backcross populations derived from a cross between Gossypium hirsutum and G. mustelinum.

KEY MESSAGE: QTLs for fiber length mapped in three generations of advanced backcross populations derived from crossing Gossypium hirsutum and Gossypium mustelinum showed opportunities to improve elite cottons by introgression from wild relatives. The molecular basis of cotton fiber length in crosses between Gossypium hirsutum and Gossypium mustelinum was dissected using 21 BC3F2 and 12 corresponding BC3F2:3 and BC3F2:4 families. Sixty-five quantitative trait loci (QTLs) were detected by one-way analysis of variance. The QTL numbers detected for upper-half mean length (UHM), fiber uniformity index (UI), and short fiber content (SFC) were 19, 20, and 26 respectively. Twenty-three of the 65 QTLs could be detected at least twice near adjacent markers in the same family or near the same markers across different families/generations, and 32 QTLs were detected in both one-way variance analyses and mixed model-based composite interval mapping. G. mustelinum alleles increased UHM and UI and decreased SFC for five, one, and one QTLs, respectively. In addition to the main-effect QTLs, 17 epistatic QTLs were detected which helped to elucidate the genetic basis of cotton fiber length. Significant among-family genotypic effects were detected at 18, 16, and 16 loci for UHM, UI, and SFC, respectively. Six, two, and two loci showed genotype × family interaction for UHM, UI and SFC, respectively, illustrating complexities that might be faced in introgression of exotic germplasm into cultivated cotton. Co-location of many QTLs for UHM, UI, and SFC accounted for correlations among these traits, and selection of these QTLs may improve the three traits simultaneously. The simple sequence repeat (SSR) markers associated with G. mustelinum QTLs will assist breeders in transferring and maintaining valuable traits from this exotic source during cultivar development.

Root system markup language: toward a unified root architecture description language.

The number of image analysis tools supporting the extraction of architectural features of root systems has increased in recent years. These tools offer a handy set of complementary facilities, yet it is widely accepted that none of these software tools is able to extract in an efficient way the growing array of static and dynamic features for different types of images and species. We describe the Root System Markup Language (RSML), which has been designed to overcome two major challenges: (1) to enable portability of root architecture data between different software tools in an easy and interoperable manner, allowing seamless collaborative work; and (2) to provide a standard format upon which to base central repositories that will soon arise following the expanding worldwide root phenotyping effort. RSML follows the XML standard to store two- or three-dimensional image metadata, plant and root properties and geometries, continuous functions along individual root paths, and a suite of annotations at the image, plant, or root scale at one or several time points. Plant ontologies are used to describe botanical entities that are relevant at the scale of root system architecture. An XML schema describes the features and constraints of RSML, and open-source packages have been developed in several languages (R, Excel, Java, Python, and C#) to enable researchers to integrate RSML files into popular research workflow.

Analysis of root growth from a phenotyping data set using a density-based model.

Major research efforts are targeting the improved performance of root systems for more efficient use of water and nutrients by crops. However, characterizing root system architecture (RSA) is challenging, because roots are difficult objects to observe and analyse. A model-based analysis of RSA traits from phenotyping image data is presented. The model can successfully back-calculate growth parameters without the need to measure individual roots. The mathematical model uses partial differential equations to describe root system development. Methods based on kernel estimators were used to quantify root density distributions from experimental image data, and different optimization approaches to parameterize the model were tested. The model was tested on root images of a set of 89 Brassica rapa L. individuals of the same genotype grown for 14 d after sowing on blue filter paper. Optimized root growth parameters enabled the final (modelled) length of the main root axes to be matched within 1% of their mean values observed in experiments. Parameterized values for elongation rates were within ±4% of the values measured directly on images. Future work should investigate the time dependency of growth parameters using time-lapse image data. The approach is a potentially powerful quantitative technique for identifying crop genotypes with more efficient root systems, using (even incomplete) data from high-throughput phenotyping systems.

Plant water uptake in drying soils.

Over the last decade, investigations on root water uptake have evolved toward a deeper integration of the soil and roots compartment properties, with the goal of improving our understanding of water acquisition from drying soils. This evolution parallels the increasing attention of agronomists to suboptimal crop production environments. Recent results have led to the description of root system architectures that might contribute to deep-water extraction or to water-saving strategies. In addition, the manipulation of root hydraulic properties would provide further opportunities to improve water uptake. However, modeling studies highlight the role of soil hydraulics in the control of water uptake in drying soil and call for integrative soil-plant system approaches.

The Emerging Role of Reactive Oxygen Species Signaling during Lateral Root Development.

Overall root architecture is the combined result of primary and lateral root growth and is influenced by both intrinsic genetic programs and external signals. One of the main questions for root biologists is how plants control the number of lateral root primordia and their emergence through the main root. We recently identified S-phase kinase-associated protein2 (SKP2B) as a new early marker for lateral root development. Here, we took advantage of its specific expression pattern in Arabidopsis (Arabidopsis thaliana) in a cell-sorting and transcriptomic approach to generate a lateral root-specific cell sorting SKP2B data set that represents the endogenous genetic developmental program. We first validated this data set by showing that many of the identified genes have a function during root growth or lateral root development. Importantly, genes encoding peroxidases were highly represented in our data set. Thus, we next focused on this class of enzymes and showed, using genetic and chemical inhibitor studies, that peroxidase activity and reactive oxygen species signaling are specifically required during lateral root emergence but, intriguingly, not for primordium specification itself.

Analyzing lateral root development: how to move forward.

Roots are important to plants for a wide variety of processes, including nutrient and water uptake, anchoring and mechanical support, storage functions, and as the major interface between the plant and various biotic and abiotic factors in the soil environment. Therefore, understanding the development and architecture of roots holds potential for the manipulation of root traits to improve the productivity and sustainability of agricultural systems and to better understand and manage natural ecosystems. While lateral root development is a traceable process along the primary root and different stages can be found along this longitudinal axis of time and development, root system architecture is complex and difficult to quantify. Here, we comment on assays to describe lateral root phenotypes and propose ways to move forward regarding the description of root system architecture, also considering crops and the environment.

Root systems biology: integrative modeling across scales, from gene regulatory networks to the rhizosphere.

Genetic and genomic approaches in model organisms have advanced our understanding of root biology over the last decade. Recently, however, systems biology and modeling have emerged as important approaches, as our understanding of root regulatory pathways has become more complex and interpreting pathway outputs has become less intuitive. To relate root genotype to phenotype, we must move beyond the examination of interactions at the genetic network scale and employ multiscale modeling approaches to predict emergent properties at the tissue, organ, organism, and rhizosphere scales. Understanding the underlying biological mechanisms and the complex interplay between systems at these different scales requires an integrative approach. Here, we describe examples of such approaches and discuss the merits of developing models to span multiple scales, from network to population levels, and to address dynamic interactions between plants and their environment.

Mutations in chicory FEH genes are statistically associated with enhanced resistance to post-harvest inulin depolymerization.

KEY MESSAGE: Nucleotidic polymorphisms were identified in fructan exohydrolases genes which are statistically associated with enhanced susceptibility to post-harvest inulin depolymerization. Industrial chicory (Cichorium intybus L.) root is the main commercial source of inulin, a linear fructose polymer used as dietary fiber. Post-harvest, inulin is depolymerized into fructose which drastically increases processing cost. To identify genetic variations associated with enhanced susceptibility to post-harvest inulin depolymerization and related free sugars content increase, we used a candidate-gene approach focused on inulin and sucrose synthesis and degradation genes, all members of the family 32 of glycoside hydrolases (GH32). Polymorphism in these genes was first investigated by carrying out EcoTILLING on two groups of chicory breeding lines exhibiting contrasted response to post-harvest inulin depolymerization. This allowed the identification of polymorphisms significantly associated with depolymerization in three fructan exohydrolase genes (FEH). This association was confirmed on a wider panel of 116 unrelated families in which the FEH polymorphism explained 35 % of the post-harvest variance for inulin content, 36 % of variance for sucrose content, 18 % for inulin degree of polymerization, 23 % for free fructose content and 22 % for free glucose content. These polymorphisms were associated with significant post-harvest changes of inulin content, inulin chain length and free sugars content.

Effects of Rhizophagus irregularis MUCL 41833 on the reproduction of Radopholus similis in banana plantlets grown under in vitro culture conditions.

The role of arbuscular mycorrhizal fungi (AMF) in the control of migratory endoparasitic nematodes is nowadays largely admitted. Most studies were conducted under greenhouse conditions and a few used in vitro cultures with transgenic root organs. Here, we reported, for the first time, on the interaction between an AMF, Rhizophagus irregularis MUCL 41833 and Radopholus similis in roots of banana plantlets grown under in vitro culture conditions. The banana plantlets were pre-mycorrhized in an extraradical mycelium network arising from a Medicago truncatula donor seedling, before transfer to an autotrophic in vitro cultivation system and subsequent nematode inoculation. Both microorganisms were able to complete their life cycle in the absence as well as in presence of each other. The total R. similis population (i.e., summed over the roots and growth medium) as well as the surface of root necrosis was significantly reduced by 60 and 56 %, respectively, in the AMF-colonized banana plantlets. By contrast, nematodes had no visible impact on root colonization (i.e., percentage of arbuscules, intraradical spores/vesicles, and hyphae) by AMF and on the number of spores and hyphal length produced in the medium. These results clearly demonstrated that pre-mycorrhized banana plants could outcompete R. similis, while root colonization was not affected by the nematodes. They underline the interest of the novel in vitro cultivation system as a promising tool to investigate the biochemical factors and molecular mechanisms involved in the bio-protection conferred by AMF to a major root pathogen of banana.

Identification of quantitative trait loci controlling nitrogen use efficiency-related traits in rice at the seedling stage under salt condition by genome-wide association study.

Rice cultivation is facing both salt intrusion and overuse of nitrogen fertilizers. Hence, breeding new varieties aiming to improve nitrogen use efficiency (NUE), especially under salt conditions, is indispensable. We selected 2,391 rice accessions from the 3K Rice Genomes Project to evaluate the dry weight under two N concentrations [2.86 mM - standard N (SN), and 0.36 mM - low N (LN)] crossed with two NaCl concentrations [0 (0Na) and 60 mM (60Na)] at the seedling stage. Genome-wide association studies for shoot, root, and plant dry weight (DW) were carried out. A total of 55 QTLs - 32, 16, and 7 in the whole, indica, and japonica panel - associated with one of the tested traits were identified. Among these, 27 QTLs co-localized with previously identified QTLs for DW-related traits while the other 28 were newly detected; 24, 8, 11, and 4 QTLs were detected in SN-0Na, LN-0Na, SN-60Na, and LN-60Na, respectively, and the remaining 8 QTLs were for the relative plant DW between treatments. Three of the 11 QTLs in SN-60Na were close to the regions containing three QTLs detected in SN-0Na. Eleven candidate genes for eight important QTLs were identified. Only one of them was detected in both SN-0Na and SN-60Na, while 5, 0, 3, and 2 candidate genes were identified only once under SN-0Na, LN-0Na, SN-60Na, and LN-60Na, respectively. The identified QTLs and genes provide useful materials and genetic information for future functional characterization and genetic improvement of NUE in rice, especially under salt conditions.

A novel image-analysis toolbox enabling quantitative analysis of root system architecture.

We present in this paper a novel, semiautomated image-analysis software to streamline the quantitative analysis of root growth and architecture of complex root systems. The software combines a vectorial representation of root objects with a powerful tracing algorithm that accommodates a wide range of image sources and quality. The root system is treated as a collection of roots (possibly connected) that are individually represented as parsimonious sets of connected segments. Pixel coordinates and gray level are therefore turned into intuitive biological attributes such as segment diameter and orientation as well as distance to any other segment or topological position. As a consequence, user interaction and data analysis directly operate on biological entities (roots) and are not hampered by the spatially discrete, pixel-based nature of the original image. The software supports a sampling-based analysis of root system images, in which detailed information is collected on a limited number of roots selected by the user according to specific research requirements. The use of the software is illustrated with a time-lapse analysis of cluster root formation in lupin (Lupinus albus) and an architectural analysis of the maize (Zea mays) root system. The software, SmartRoot, is an operating system-independent freeware based on ImageJ and relies on cross-platform standards for communication with data-analysis software.

Investigating Soil-Root Interactions with the Numerical Model R-SWMS.

In this chapter, we present the Root and Soil Water Movement and Solute transport model R-SWMS, which can be used to simulate flow and transport in the soil-plant system. The equations describing water flow in soil-root systems are presented and numerical solutions are provided. An application of R-SWMS is then briefly discussed, in which we combine in vivo and in silico experiments in order to decrypt water flow in the soil-root domain. More precisely, light transmission imaging experiments were conducted to generate data that can serve as input for the R-SWMS model. These data include the root system architecture, the soil hydraulic properties and the environmental conditions (initial soil water content and boundary conditions, BC). Root hydraulic properties were not acquired experimentally, but set to theoretical values found in the literature. In order to validate the results obtained by the model, the simulated and experimental water content distributions were compared. The model was then used to estimate variables that were not experimentally accessible, such as the actual root water uptake distribution and xylem water potential.

Physiological adaptive traits are a potential allele reservoir for maize genetic progress under challenging conditions.

Combined phenomic and genomic approaches are required to evaluate the margin of progress of breeding strategies. Here, we analyze 65 years of genetic progress in maize yield, which was similar (101 kg ha-1 year-1) across most frequent environmental scenarios in the European growing area. Yield gains were linked to physiologically simple traits (plant phenology and architecture) which indirectly affected reproductive development and light interception in all studied environments, marked by significant genomic signatures of selection. Conversely, studied physiological processes involved in stress adaptation remained phenotypically unchanged (e.g. stomatal conductance and growth sensitivity to drought) and showed no signatures of selection. By selecting for yield, breeders indirectly selected traits with stable effects on yield, but not physiological traits whose effects on yield can be positive or negative depending on environmental conditions. Because yield stability under climate change is desirable, novel breeding strategies may be needed for exploiting alleles governing physiological adaptive traits.