Functional phenomics and genetics of the root economics space in winter wheat using high-throughput phenotyping of respiration and architecture

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.

Paenibacillus lentimorbus alleviates nutrient deficiency-induced stress in Zea mays by modulating root system architecture, auxin signaling, and metabolic pathways

KEY MESSAGE

Paenibacillus lentimorbus reprograms auxin signaling and metabolic pathways for modulating root system architecture to mitigate nutrient deficiency in maize crops. The arable land across the world is having deficiency and disproportionate nutrients, limiting crop productivity. In this study, the potential of plant growth-promoting rhizobacteria (PGPR) viz., Pseudomonas putida, Paenibacillus lentimorbus, and their consortium was explored for growth promotion in maize (Zea mays) under nutrient-deficient conditions. PGPR inoculation improved the overall health of plants under nutrient-deficient conditions. The PGPR inoculation significantly improved the root system architecture and also induced changes in root cortical aerenchyma. Based on plant growth and physiological parameters inoculation with P. lentimorbus performed better as compared to P. putida, consortium, and uninoculated control. Furthermore, expression of auxin signaling (rum1, rul1, lrp1, rtcs, rtcl) and root hair development (rth)-related genes modulated the root development process to improve nutrient acquisition and tolerance to nutrient-deficient conditions in P. lentimorbus inoculated maize plants. Further, GC-MS analysis indicated the involvement of metabolites including carbohydrates and organic acids due to the interaction between maize roots and P. lentimorbus under nutrient-deficient conditions. These findings affirm that P. lentimorbus enhance overall plant growth by modulating the root system of maize to provide better tolerance to nutrient-deficient condition.

Phenotyping of Salvia miltiorrhiza Roots Reveals Associations between Root Traits and Bioactive Components

Plant phenomics aims to perform high-throughput, rapid, and accurate measurement of plant traits, facilitating the identification of desirable traits and optimal genotypes for crop breeding. Salvia miltiorrhiza (Danshen) roots possess remarkable therapeutic effect on cardiovascular diseases, with huge market demands. Although great advances have been made in metabolic studies of the bioactive metabolites, investigation for S. miltiorrhiza roots on other physiological aspects is poor. Here, we developed a framework that utilizes image feature extraction software for in-depth phenotyping of S. miltiorrhiza roots. By employing multiple software programs, S. miltiorrhiza roots were described from 3 aspects: agronomic traits, anatomy traits, and root system architecture. Through K-means clustering based on the diameter ranges of each root branch, all roots were categorized into 3 groups, with primary root-associated key traits. As a proof of concept, we examined the phenotypic components in a series of randomly collected S. miltiorrhiza roots, demonstrating that the total surface of root was the best parameter for the biomass prediction with high linear regression correlation (R2 = 0.8312), which was sufficient for subsequently estimating the production of bioactive metabolites without content determination. This study provides an important approach for further grading of medicinal materials and breeding practices.

Crop/Plant Modeling Supports Plant Breeding: II. Guidance of Functional Plant Phenotyping for Trait Discovery

Observable morphological traits are widely employed in plant phenotyping for breeding use, which are often the external phenotypes driven by a chain of functional actions in plants. Identifying and phenotyping inherently functional traits for crop improvement toward high yields or adaptation to harsh environments remains a major challenge. Prediction of whole-plant performance in functional-structural plant models (FSPMs) is driven by plant growth algorithms based on organ scale wrapped up with micro-environments. In particular, the models are flexible for scaling down or up through specific functions at the organ nexus, allowing the prediction of crop system behaviors from the genome to the field. As such, by virtue of FSPMs, model parameters that determine organogenesis, development, biomass production, allocation, and morphogenesis from a molecular to the whole plant level can be profiled systematically and made readily available for phenotyping. FSPMs can provide rich functional traits representing biological regulatory mechanisms at various scales in a dynamic system, e.g., Rubisco carboxylation rate, mesophyll conductance, specific leaf nitrogen, radiation use efficiency, and source-sink ratio apart from morphological traits. High-throughput phenotyping such traits is also discussed, which provides an unprecedented opportunity to evolve FSPMs. This will accelerate the co-evolution of FSPMs and plant phenomics, and thus improving breeding efficiency. To expand the great promise of FSPMs in crop science, FSPMs still need more effort in multiscale, mechanistic, reproductive organ, and root system modeling. In summary, this study demonstrates that FSPMs are invaluable tools in guiding functional trait phenotyping at various scales and can thus provide abundant functional targets for phenotyping toward crop improvement.

Selection of oat (Avena sativa L.) drought-tolerant genotypes based on multiple yield-associated traits

BACKGROUND

Most plant breeding and agricultural practices are based on selecting genotypes for yield. However, this is inadequate to screen crop varieties for specific attributes, such as drought tolerance. In this study, we quantified the response of oat (Avena sativa L.) plant physiological and morphological traits to drought stress and selected some key traits to establish a genotype by yield*trait (GYT)-based method for ranking 30 oat genotypes. The effectiveness of this method was also evaluated under drought conditions.

RESULTS

Water-deficit treatment significantly reduced leaf chlorophyll, root morphological traits, groat yield and associated components, such as mean grain weight. We observed that the genotypes 'JUSTICE' and 'BOLINA' had the smallest and largest yield loss, respectively, after exposure to drought stress, but showed opposite trends in the biomass allocation of roots and grains. This indicated that drought tolerance was highly dependent on the distribution of photoassimilates. Our results also illustrated that the GYT method is a trade-off approach and more effective in selecting oat ideotypes under drought conditions than the yield-related index method because it combines yield, yield stability, and related agronomic traits in the calculation process.

CONCLUSION

Drought-tolerant genotypes had more biomass allocated to roots and grains with higher chlorophyll content and better root structure, e.g. longer root lengths than drought-sensitive lines. By integrating yield and yield-related traits, the GYT approach is more practical than traditional single-trait selection methods when assessing drought tolerance. © 2023 His Majesty the King in Right of Canada. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. Reproduced with the permission of the Minister of Agriculture and Agri-Food Canada.

High-throughput, dynamic, multi-dimensional: an expanding repertoire of plant respiration measurements

A recent burst of technological innovation and adaptation has greatly improved our ability to capture respiration rate data from plant sources. At the tissue level, several independent respiration measurement options are now available, each with distinct advantages and suitability, including high-throughput sampling capacity. These advancements facilitate the inclusion of respiration rate data into large-scale biological studies such as genetic screens, ecological surveys, crop breeding trials, and multi-omics molecular studies. As a result, our understanding of the correlations of respiration with other biological and biochemical measurements is rapidly increasing. Difficult questions persist concerning the interpretation and utilization of respiration data; concepts such as allocation of respiration to growth versus maintenance, the unnecessary or inefficient use of carbon and energy by respiration, and predictions of future respiration rates in response to environmental change are all insufficiently grounded in empirical data. However, we emphasize that new experimental designs involving novel combinations of respiration rate data with other measurements will flesh-out our current theories of respiration. Furthermore, dynamic recordings of respiration rate, which have long been used at the scale of mitochondria, are increasingly being used at larger scales of size and time to reflect processes of cellular signal transduction and physiological response to the environment. We also highlight how respiratory methods are being better adapted to different plant tissues including roots and seeds, which have been somewhat neglected historically.

Natural variation of respiration-related traits in plants

Plant respiration is one of the greatest global metabolic fluxes, but rates of respiration vary massively both within different cell types as well as between different individuals and different species. Whilst this is well known, few studies have detailed population-level variation of respiration until recently. The last 20 years have seen a renaissance in studies of natural variance. In this review, we describe how experimental breeding populations and collections of large populations of accessions can be used to determine the genetic architecture of plant traits. We further detail how these approaches have been used to study the rate of respiration per se as well as traits that are intimately associated with respiration. The review highlights specific breakthroughs in these areas but also concludes that the approach should be more widely adopted in the study of respiration per se as opposed to the more frequently studied respiration-related traits.

Comparative metabolomics of root-tips reveals distinct metabolic pathways conferring drought tolerance in contrasting genotypes of rice

Background

The mechanisms underlying rice root responses to drought during the early developmental stages are yet unknown.

Results

This study aimed to determine metabolic differences in IR64, a shallow-rooting, drought-susceptible genotype, and Azucena, a drought-tolerant and deep-rooting genotype under drought stress. The morphological evaluation revealed that Azucena might evade water stress by increasing the lateral root system growth, the root surface area, and length to access water. At the same time, IR64 may rely mainly on cell wall thickening to tolerate stress. Furthermore, significant differences were observed in 49 metabolites in IR64 and 80 metabolites in Azucena, for which most metabolites were implicated in secondary metabolism, amino acid metabolism, nucleotide acid metabolism and sugar and sugar alcohol metabolism. Among these metabolites, a significant positive correlation was found between allantoin, galactaric acid, gluconic acid, glucose, and drought tolerance. These metabolites may serve as markers of drought tolerance in genotype screening programs. Based on corresponding biological pathways analysis of the differentially abundant metabolites (DAMs), biosynthesis of alkaloid-derivatives of the shikimate pathway, fatty acid biosynthesis, purine metabolism, TCA cycle and amino acid biosynthesis were the most statistically enriched biological pathway in Azucena in drought response. However, in IR64, the differentially abundant metabolites of starch and sucrose metabolism were the most statistically enriched biological pathways.

Conclusion

Metabolic marker candidates for drought tolerance were identified in both genotypes. Thus, these markers that were experimentally determined in distinct metabolic pathways can be used for the development or selection of drought-tolerant rice genotypes.

Functional phenomics for improved climate resilience in Nordic agriculture

The five Nordic countries span the most northern region for field cultivation in the world. This presents challenges per se, with short growing seasons, long days, and a need for frost tolerance. Climate change has additionally increased risks for micro-droughts and water logging, as well as pathogens and pests expanding northwards. Thus, Nordic agriculture demands crops that are adapted to the specific Nordic growth conditions and future climate scenarios. A focus on crop varieties and traits important to Nordic agriculture, including the unique resource of nutritious wild crops, can meet these needs. In fact, with a future longer growing season due to climate change, the region could contribute proportionally more to global agricultural production. This also applies to other northern regions, including the Arctic. To address current growth conditions, mitigate impacts of climate change, and meet market demands, the adaptive capacity of crops that both perform well in northern latitudes and are more climate resilient has to be increased, and better crop management systems need to be built. This requires functional phenomics approaches that integrate versatile high-throughput phenotyping, physiology, and bioinformatics. This review stresses key target traits, the opportunities of latitudinal studies, and infrastructure needs for phenotyping to support Nordic agriculture.

High-Throughput Phenotypic Characterization and Diversity Analysis of Soybean Roots (Glycine max L.)

Soybean (Glycine max L.) is a crop native to Northeast Asia, including China, Korea, and Japan, but currently cultivated all over the world. The National Agrobiodiversity Center in Korea at the Rural Development Administration (RDA) conserves approximately 26,000 accessions and conducts characterizations of its accessions, to accumulate new information. Roots are essential organs of a plant, providing mechanical support, as well as aiding water and nutrient acquisition. Currently, not much information is available in international gene banks regarding root characterization. We studied the root phenotype of 374 soybean accessions, using a high-throughput method. Eight root morphological traits (RMT) were studied and we observed that the surface area (SA), number of forks (NF), and number of tips (NT) had a positive correlation with total length (LENGTH), and that link average length (LAL) and other traits all had a negative correlation. Additionally, the correlation between seed traits (height, width, and 100-seed weight) and root traits was confirmed for the first time in this experiment. The germplasms were divided into three clusters by k-means clustering, and orthogonal projections to latent structures discriminant analysis (OPLS-DA) was used to compare clusters. The most distinctive characteristics between clusters were total lateral average length (LAD) and total lateral average length (DIAM). Cluster 3 had the highest LENGTH, SA, NF, and NF, whereas cluster 1 had the smallest LENGTH, SA, and NF. We selected the top 10 accessions for each RMT, and IT208321, IT216313, and IT216137 were nominated as the best germplasms. These accessions can be recommended to breeders as materials for breeding programs. This is a preliminary report on the characterization of the root phenotype at an international gene bank and will open up the possibility of improving the available information on accessions in gene banks worldwide.

Genotypic variation of plant biomass under nitrogen deficiency is positively correlated with conservative economic traits in wheat

Plant functional traits, including leaf and root economic traits, are important for understanding the composition and function of ecosystems. However, plant functional traits of crop species and the relationships between them, and their responses to environmental variations are not fully understood. In the present study, the traits in the leaf and root economics spectrum (LES and RES) and plant biomass were investigated in 14 wheat genotypes grown with sufficient or limited nitrogen (N) supply. We found that N had significant impacts on the LES and RES traits and on the relationships among them. Our results generally supported the hypothesized LES, but did not support the RES or plant economics spectrum concept among wheat plants regardless of N treatment. More importantly, we found that more conservative leaf and root economic traits are beneficial for shoot biomass accumulation in wheat plants grown with limited N supply, and for the improvement in the tolerance of wheat to N stress. The data presented suggest that growth conditions should be accounted for when studying trait-to-trait relationships, and that more conservative resource use strategies could be used as promising targets for wheat breeding programs with limited N input.

Root system architecture in cereals: progress, challenges and perspective

Roots are essential multifunctional plant organs involved in water and nutrient uptake, metabolite storage, anchorage, mechanical support, and interaction with the soil environment. Understanding of this 'hidden half' provides potential for manipulation of root system architecture (RSA) traits to optimize resource use efficiency and grain yield in cereal crops. Unfortunately, root traits are highly neglected in breeding due to the challenges of phenotyping, but could have large rewards if the variability in RSA traits can be fully exploited. Until now, a plethora of genes have been characterized in detail for their potential role in improving RSA. The use of forward genetics approaches to find sequence variations in genes underpinning desirable RSA would be highly beneficial. Advances in computer vision applications have allowed image-based approaches for high-throughput phenotyping of RSA traits that can be used by any laboratory worldwide to make progress in understanding root function and dissection of the genetics. At the same time, the frontiers of root measurement include non-invasive methods like X-ray computer tomography and magnetic resonance imaging that facilitate new types of temporal studies. Root physiology and ecology are further supported by spatiotemporal root simulation modeling. The discovery of component traits providing improved resilience and yield advantage in target environments is a key necessity for mainstreaming root-based cereal breeding. The integrated use of pan-genome resources, now available in most cereals, coupled with new in-field phenotyping platforms has the potential for precise selection of superior genotypes with improved RSA.

Optimisation of root traits to provide enhanced ecosystem services in agricultural systems: A focus on cover crops

Roots are the interface between the plant and the soil and play a central role in multiple ecosystem processes. With intensification of agricultural practices, rhizosphere processes are being disrupted and are causing degradation of the physical, chemical and biotic properties of soil. However, cover crops, a group of plants that provide ecosystem services, can be utilised during fallow periods or used as an intercrop to restore soil health. The effectiveness of ecosystem services provided by cover crops varies widely as very little breeding has occurred in these species. Improvement of ecosystem service performance is rarely considered as a breeding trait due to the complexities and challenges of belowground evaluation. Advancements in root phenotyping and genetic tools are critical in accelerating ecosystem service improvement in cover crops. In this study, we provide an overview of the range of belowground ecosystem services provided by cover crop roots: (1) soil structural remediation, (2) capture of soil resources and (3) maintenance of the rhizosphere and building of organic matter content. Based on the ecosystem services described, we outline current and promising phenotyping technologies and breeding strategies in cover crops that can enhance agricultural sustainability through improvement of root traits.

Whole-plant phenotypic engineering: moving beyond ratios for multi-objective optimization of nutrient use efficiency

Nutrient use efficiency (NUE) is typically measured as the ratio of yield to soil nutrient availability but ignores contributions of underlying plant traits. Relevant plant traits can be grouped as root acquisition efficiency, shoot radiation use efficiency, and plant metabolic efficiency. The intentional integration of these traits will lead to synergistic improvements of NUE. Recent progress in trait-focused research includes phenotyping root nutrient uptake rates and respiration, engineering reduced photorespiration, and identification of nutrient assimilation pathways. Traits need to be conceptualized in agricultural systems contexts to improve synchrony of plant demand and soil supply of nutrients, including consideration of crop mixtures. Use of simulation modeling and multi-objective optimization will allow accelerating NUE gains beyond selection for a single ratio.

Interactions among rooting traits for deep water and nitrogen uptake in upland and lowland ecotypes of switchgrass (Panicum virgatum L.)

The response of plant growth and development to nutrient and water availability is an important adaptation for abiotic stress tolerance. Roots need to intercept both passing nutrients and water while foraging into new soil layers for further resources. Substantial amounts of nitrate can be lost in the field when leaching into groundwater, yet very little is known about how deep rooting affects this process. Here, we phenotyped root system traits and deep 15N nitrate capture across 1.5 m vertical profiles of solid media using tall mesocosms in switchgrass (Panicum virgatum L.), a promising cellulosic bioenergy feedstock. Root and shoot biomass traits, photosynthesis and respiration measures, and nutrient uptake and accumulation traits were quantified in response to a water and nitrate stress factorial experiment for switchgrass upland (VS16) and lowland (AP13) ecotypes. The two switchgrass ecotypes shared common plastic abiotic responses to nitrogen (N) and water availability, and yet had substantial genotypic variation for root and shoot traits. A significant interaction between N and water stress combination treatments for axial and lateral root traits represents a complex and shared root development strategy for stress mitigation. Deep root growth and 15N capture were found to be closely linked to aboveground growth. Together, these results represent the wide genetic pool of switchgrass and show that deep rooting promotes nitrate capture, plant productivity, and sustainability.

Variations in Arbuscular Mycorrhizal Colonization Associated with Root Diameter and Hypodermis Passages Cells across Temperate and Tropical Woody Species

Root hypodermis passage cells (PCs) lack suberin and lignin deposition, responsible for nutrient absorption and arbuscular mycorrhizal colonization, which are crucial for root resource acquisition. Nevertheless, their quantitative variability across diverse woody species and their relationships with root morphology and anatomy, as well as arbuscular mycorrhizal colonization, are still not well understood. Herein, the number and proportion of PCs in the root cross-section, root morphology, anatomy, and arbuscular mycorrhizal colonization rate were quantified across 10 temperate and 12 tropical woody species. The objectives of this study were to determine how PCs vary across contrasting environmental conditions and to explore their relationships with arbuscular mycorrhizal colonization rate and other root functional traits. The results showed that tropical species possessed 56% more PCs than temperate species; by contrast, they had similar proportions of PCs. In both biomes, the number of PCs had a tightly positive correlation with arbuscular mycorrhizal colonization rate (R2 = 0.35–0.87), root diameter (R2 = 0.84–0.93), and cortex thickness (R2 = 0.87–0.89), but the proportion of PCs was mostly independent of root morphological and anatomical traits. Our results suggest that variation in passage cells could well explain the tight linkage between arbuscular mycorrhizal colonization and root diameter across species and biomes, which provides insight into the collaboration gradient between plant roots and mycorrhizal fungi that dominates the root economics space.

Omics-Facilitated Crop Improvement for Climate Resilience and Superior Nutritive Value

Novel crop improvement approaches, including those that facilitate for the exploitation of crop wild relatives and underutilized species harboring the much-needed natural allelic variation are indispensable if we are to develop climate-smart crops with enhanced abiotic and biotic stress tolerance, higher nutritive value, and superior traits of agronomic importance. Top among these approaches are the "omics" technologies, including genomics, transcriptomics, proteomics, metabolomics, phenomics, and their integration, whose deployment has been vital in revealing several key genes, proteins and metabolic pathways underlying numerous traits of agronomic importance, and aiding marker-assisted breeding in major crop species. Here, citing several relevant examples, we appraise our understanding on the recent developments in omics technologies and how they are driving our quest to breed climate resilient crops. Large-scale genome resequencing, pan-genomes and genome-wide association studies are aiding the identification and analysis of species-level genome variations, whilst RNA-sequencing driven transcriptomics has provided unprecedented opportunities for conducting crop abiotic and biotic stress response studies. Meanwhile, single cell transcriptomics is slowly becoming an indispensable tool for decoding cell-specific stress responses, although several technical and experimental design challenges still need to be resolved. Additionally, the refinement of the conventional techniques and advent of modern, high-resolution proteomics technologies necessitated a gradual shift from the general descriptive studies of plant protein abundances to large scale analysis of protein-metabolite interactions. Especially, metabolomics is currently receiving special attention, owing to the role metabolites play as metabolic intermediates and close links to the phenotypic expression. Further, high throughput phenomics applications are driving the targeting of new research domains such as root system architecture analysis, and exploration of plant root-associated microbes for improved crop health and climate resilience. Overall, coupling these multi-omics technologies to modern plant breeding and genetic engineering methods ensures an all-encompassing approach to developing nutritionally-rich and climate-smart crops whose productivity can sustainably and sufficiently meet the current and future food, nutrition and energy demands.

The genetic basis of the root economics spectrum in a perennial grass

Construction economics of plant roots exhibit predictable relationships with root growth, death, and nutrient uptake strategies. Plant taxa with inexpensively constructed roots tend to more precisely explore nutrient hotspots than do those with costly constructed roots but at the price of more frequent tissue turnover. This trade-off underlies an acquisitive to conservative continuum in resource investment, described as the "root economics spectrum (RES)." Yet the adaptive role and genetic basis of RES remain largely unclear. Different ecotypes of switchgrass (Panicum virgatum) display root features exemplifying the RES, with costly constructed roots in southern lowland and inexpensively constructed roots in northern upland ecotypes. We used an outbred genetic mapping population derived from lowland and upland switchgrass ecotypes to examine the genetic architecture of the RES. We found that absorptive roots (distal first and second orders) were often "deciduous" in winter. The percentage of overwintering absorptive roots was decreased by northern upland alleles compared with southern lowland alleles, suggesting a locally-adapted conservative strategy in warmer and acquisitive strategy in colder regions. Relative turnover of absorptive roots was genetically negatively correlated with their biomass investment per unit root length, suggesting that the key trade-off in framing RES is genetically facilitated. We also detected strong genetic correlations among root morphology, root productivity, and shoot size. Overall, our results reveal the genetic architecture of multiple traits that likely impacts the evolution of RES and plant aboveground-belowground organization. In practice, we provide genetic evidence that increasing switchgrass yield for bioenergy does not directly conflict with enhancing its root-derived carbon sequestration.

Dark Respiration Measurement from Arabidopsis Shoots

Dark respiration refers to experimental measures of leaf respiration in the absence of light, done to distinguish it from the photorespiration that occurs during photosynthesis. Dark aerobic respiration reactions occur solely in the mitochondria and convert glucose molecules from cytoplasmatic glycolysis and oxygen into carbon dioxide and water, with the generation of ATP molecules. Previous methods typically use oxygen sensors to measure oxygen depletion or complicated and expensive photosynthesis instruments to measure CO₂ accumulation. Here, we provide a detailed, step-by-step approach to measure dark respiration in plants by recording CO₂ fluxes of Arabidopsis shoot and root tissues. Briefly, plants are dark acclimated for 1 hour, leaves and roots are excised and placed separately in airtight chambers, and CO₂ accumulation is measured over time with standard infrared gas analyzers. The time-series data is processed with R scripts to produce dark respiration rates, which can be standardized by fresh or dry tissue mass. The current method requires inexpensive infrared gas analyzers, off-the-shelf parts for chambers, and publicly available data analysis scripts.