Root system architecture in cereals: progress, challenges and perspective

From phenotyping to genetic mapping: identifying water-stress adaptations in legume root traits

BACKGROUND

Climate change induces perturbation in the global water cycle, profoundly impacting water availability for agriculture and therefore global food security. Water stress encompasses both drought (i.e. water scarcity) that causes the drying of soil and subsequent plant desiccation, and flooding, which results in excess soil water and hypoxia for plant roots. Terrestrial plants have evolved diverse mechanisms to cope with soil water stress, with the root system serving as the first line of defense. The responses of roots to water stress can involve both structural and physiological changes, and their plasticity is a vital feature of these adaptations. Genetic methodologies have been extensively employed to identify numerous genetic loci linked to water stress-responsive root traits. This knowledge is immensely important for developing crops with optimal root systems that enhance yield and guarantee food security under water stress conditions.

RESULTS

This review focused on the latest insights into modifications in the root system architecture and anatomical features of legume roots in response to drought and flooding stresses. Special attention was given to recent breakthroughs in understanding the genetic underpinnings of legume root development under water stress. The review also described various root phenotyping techniques and examples of their applications in different legume species. Finally, the prevailing challenges and prospective research avenues in this dynamic field as well as the potential for using root system architecture as a breeding target are discussed.

CONCLUSIONS

This review integrated the latest knowledge of the genetic components governing the adaptability of legume roots to water stress, providing a reference for using root traits as the new crop breeding targets.

Mapping quantitative trait loci for seminal root angle in a selected durum wheat population

Seminal root angle (SRA) is an important root architectural trait associated with drought adaptation in cereal crops. To date, all attempts to dissect the genetic architecture of SRA in durum wheat (Triticum durum Desf.) have used large association panels or structured mapping populations. Identifying changes in allele frequency generated by selection provides an alternative genetic mapping approach that can increase the power and precision of QTL detection. This study aimed to map quantitative trait loci (QTL) for SRA by genotyping durum lines created through divergent selection using a combination of marker-assisted selection (MAS) for the major SRA QTL (qSRA-6A) and phenotypic selection for SRA over multiple generations. The created 11 lines (BC1F2:5) were genotyped with genome-wide single-nucleotide polymorphism (SNP) markers to map QTL by identifying markers that displayed segregation distortion significantly different from the Mendelian expectation. QTL regions were further assessed in an independent validation population to confirm their associations with SRA. The experiment revealed 14 genomic regions under selection, 12 of which have not previously been reported for SRA. Five regions, including qSRA-6A, were confirmed in the validation population. The genomic regions identified in this study indicate that the genetic control of SRA is more complex than previously anticipated. Our study demonstrates that selection mapping is a powerful approach to complement genome-wide association studies for QTL detection. Moreover, the verification of qSRA-6A in an elite genetic background highlights the potential for MAS, although it is necessary to combine additional QTL to develop new cultivars with extreme SRA phenotypes.

Crop root system architecture in drought response

Drought is a natural disaster that profoundly impacts on global agricultural production, significantly reduces crop yields, and thereby poses a severe threat to worldwide food security. Addressing the challenge of effectively improving crop drought resistance (DR) to mitigate yield loss under drought conditions is a global issue. An optimal root system architecture (RSA) plays a pivotal role in enhancing crops' capacity to efficiently uptake water and nutrients, which consequently strengthens their resilience against environmental stresses. In this review, we discuss the compositions and roles of crop RSA and summarize the most recent developments in augmenting drought tolerance in crops by manipulating RSA-related genes. Based on the current research, we propose the potential optimal RSA configuration that could be helpful in enhancing crop DR. Lastly, we discussed the existing challenges and future directions for breeding crops with enhanced DR capabilities through genetic improvements targeting RSA.

The State of the Art in Root System Architecture Image Analysis Using Artificial Intelligence: A Review

Roots are essential for acquiring water and nutrients to sustain and support plant growth and anchorage. However, they have been studied less than the aboveground traits in phenotyping and plant breeding until recent decades. In modern times, root properties such as morphology and root system architecture (RSA) have been recognized as increasingly important traits for creating more and higher quality food in the "Second Green Revolution". To address the paucity in RSA and other root research, new technologies are being investigated to fill the increasing demand to improve plants via root traits and overcome currently stagnated genetic progress in stable yields. Artificial intelligence (AI) is now a cutting-edge technology proving to be highly successful in many applications, such as crop science and genetic research to improve crop traits. A burgeoning field in crop science is the application of AI to high-resolution imagery in analyses that aim to answer questions related to crops and to better and more speedily breed desired plant traits such as RSA into new cultivars. This review is a synopsis concerning the origins, applications, challenges, and future directions of RSA research regarding image analyses using AI.

Genomic basis determining root system architecture in maize

KEY MESSAGE

A total of 389 and 344 QTLs were identified by GWAS and QTL mapping explaining accumulatively 32.2-65.0% and 23.7-63.4% of phenotypic variation for 14 shoot-borne root traits using more than 1300 individuals across multiple field trails. Efficient nutrient and water acquisition from soils depends on the root system architecture (RSA). However, the genetic determinants underlying RSA in maize remain largely unexplored. In this study, we conducted a comprehensive genetic analysis for 14 shoot-borne root traits using 513 inbred lines and 800 individuals from four recombinant inbred line (RIL) populations at the mature stage across multiple field trails. Our analysis revealed substantial phenotypic variation for these 14 root traits, with a total of 389 and 344 QTLs identified through genome-wide association analysis (GWAS) and linkage analysis, respectively. These QTLs collectively explained 32.2-65.0% and 23.7-63.4% of the trait variation within each population. Several a priori candidate genes involved in auxin and cytokinin signaling pathways, such as IAA26, ARF2, LBD37 and CKX3, were found to co-localize with these loci. In addition, a total of 69 transcription factors (TFs) from 27 TF families (MYB, NAC, bZIP, bHLH and WRKY) were found for shoot-borne root traits. A total of 19 genes including PIN3, LBD15, IAA32, IAA38 and ARR12 and 19 GWAS signals were overlapped with selective sweeps. Further, significant additive effects were found for root traits, and pyramiding the favorable alleles could enhance maize root development. These findings could contribute to understand the genetic basis of root development and evolution, and provided an important genetic resource for the genetic improvement of root traits in maize.

Mitigating drought stress in wheat plants (Triticum Aestivum L.) through grain priming in aqueous extract of spirulina platensis

BACKGROUND

The study focuses on the global challenge of drought stress, which significantly impedes wheat production, a cornerstone of global food security. Drought stress disrupts cellular and physiological processes in wheat, leading to substantial yield losses, especially in arid and semi-arid regions. The research investigates the use of Spirulina platensis aqueous extract (SPAE) as a biostimulant to enhance the drought resistance of two Egyptian wheat cultivars, Sakha 95 (drought-tolerant) and Shandawel 1 (drought-sensitive). Each cultivar's grains were divided into four treatments: Cont, DS, SPAE-Cont, and SPAE + DS. Cont and DS grains were presoaked in distilled water for 18 h while SPAE-Cont and SPAE + DS were presoaked in 10% SPAE, and then all treatments were cultivated for 96 days in a semi-field experiment. During the heading stage (45 days: 66 days), two drought treatments, DS and SPAE + DS, were not irrigated. In contrast, the Cont and SPAE-Cont treatments were irrigated during the entire experiment period. At the end of the heading stage, agronomy, pigment fractions, gas exchange, and carbohydrate content parameters of the flag leaf were assessed. Also, at the harvest stage, yield attributes and biochemical aspects of yielded grains (total carbohydrates and proteins) were evaluated.

RESULTS

The study demonstrated that SPAE treatments significantly enhanced the growth vigor, photosynthetic rate, and yield components of both wheat cultivars under standard and drought conditions. Specifically, SPAE treatments increased photosynthetic rate by up to 53.4%, number of spikes by 76.5%, and economic yield by 190% for the control and 153% for the drought-stressed cultivars pre-soaked in SPAE. Leaf agronomy, pigment fractions, gas exchange parameters, and carbohydrate content were positively influenced by SPAE treatments, suggesting their effectiveness in mitigating drought adverse effects, and improving wheat crop performance.

CONCLUSION

The application of S. platensis aqueous extract appears to ameliorate the adverse effects of drought stress on wheat, enhancing the growth vigor, metabolism, and productivity of the cultivars studied. This indicates the potential of SPAE as an eco-friendly biostimulant for improving crop resilience, nutrition, and yield under various environmental challenges, thus contributing to global food security.

How plants sense and respond to osmotic stress

Drought is one of the most serious abiotic stresses to land plants. Plants sense and respond to drought stress to survive under water deficiency. Scientists have studied how plants sense drought stress, or osmotic stress caused by drought, ever since Charles Darwin, and gradually obtained clues about osmotic stress sensing and signaling in plants. Osmotic stress is a physical stimulus that triggers many physiological changes at the cellular level, including changes in turgor, cell wall stiffness and integrity, membrane tension, and cell fluid volume, and plants may sense some of these stimuli and trigger downstream responses. In this review, we emphasized water potential and movements in organisms, compared putative signal inputs in cell wall-containing and cell wall-free organisms, prospected how plants sense changes in turgor, membrane tension, and cell fluid volume under osmotic stress according to advances in plants, animals, yeasts, and bacteria, summarized multilevel biochemical and physiological signal outputs, such as plasma membrane nanodomain formation, membrane water permeability, root hydrotropism, root halotropism, Casparian strip and suberin lamellae, and finally proposed a hypothesis that osmotic stress responses are likely to be a cocktail of signaling mediated by multiple osmosensors. We also discussed the core scientific questions, provided perspective about the future directions in this field, and highlighted the importance of robust and smart root systems and efficient source-sink allocations for generating future high-yield stress-resistant crops and plants.

Understanding role of roots in plant response to drought: Way forward to climate-resilient crops

Drought stress leads to a significant amount of agricultural crop loss. Thus, with changing climatic conditions, it is important to develop resilience measures in agricultural systems against drought stress. Roots play a crucial role in regulating plant development under drought stress. In this review, we have summarized the studies on the role of roots and root-mediated plant responses. We have also discussed the importance of root system architecture (RSA) and the various structural and anatomical changes that it undergoes to increase survival and productivity under drought. Various genes, transcription factors, and quantitative trait loci involved in regulating root growth and development are also discussed. A summarization of various instruments and software that can be used for high-throughput phenotyping in the field is also provided in this review. More comprehensive studies are required to help build a detailed understanding of RSA and associated traits for breeding drought-resilient cultivars.

Epigenetic variation in maize agronomical traits for breeding and trait improvement

Epigenetics-mediated breeding (Epibreeding) involves engineering crop traits and stress responses through the targeted manipulation of key epigenetic features to enhance agricultural productivity. While conventional breeding methods raise concerns about reduced genetic diversity, epibreeding propels crop improvement through epigenetic variations that regulate gene expression, ultimately impacting crop yield. Epigenetic regulation in crops encompasses various modes, including histone modification, DNA modification, RNA modification, non-coding RNA, and chromatin remodeling. This review summarizes the epigenetic mechanisms underlying major agronomic traits in maize and identifies candidate epigenetic landmarks in the maize breeding process. We propose a valuable strategy for improving maize yield through epibreeding, combining CRISPR/Cas-based epigenome editing technology and Synthetic Epigenetics (SynEpi). Finally, we discuss the challenges and opportunities associated with maize trait improvement through epibreeding.

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

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

Modeling the effects of strigolactone levels on maize root system architecture

Maize is the most in-demand staple crop globally. Its production relies strongly on the use of fertilizers for the supply of nitrogen, phosphorus, and potassium, which the plant absorbs through its roots, together with water. The architecture of maize roots is determinant in modulating how the plant interacts with the microbiome and extracts nutrients and water from the soil. As such, attempts to use synthetic biology and modulate that architecture to make the plant more resilient to drought and parasitic plants are underway. These attempts often try to modulate the biosynthesis of hormones that determine root architecture and growth. Experiments are laborious and time-consuming, creating the need for simulation platforms that can integrate metabolic models and 3D root growth models and predict the effects of synthetic biology interventions on both, hormone levels and root system architectures. Here, we present an example of such a platform that is built using Mathematica. First, we develop a root model, and use it to simulate the growth of many unique 3D maize root system architectures (RSAs). Then, we couple this model to a metabolic model that simulates the biosynthesis of strigolactones, hormones that modulate root growth and development. The coupling allows us to simulate the effect of changing strigolactone levels on the architecture of the roots. We then integrate the two models in a simulation platform, where we also add the functionality to analyze the effect of strigolactone levels on root phenotype. Finally, using in silico experiments, we show that our models can reproduce both the phenotype of wild type maize, and the effect that varying strigolactone levels have on changing the architecture of maize roots.

Genetic Signature Controlling Root System Architecture in Diverse Spring Wheat Germplasm

Roots are the main sensing organ, initiating multiple signaling pathways in response to abiotic factors, including nutrients, drought, and salt stress. A focus on improving the root system architecture is a key strategy to mitigate these stresses in wheat crop. In the present study, a diversity panel comprising indigenous landraces and historical cultivars from Pakistan was characterized for the root system architecture (RSA) and important loci were identified using a genome-wide association study (GWAS). RSA of the diversity panel was characterized 30 days after sowing in brunch tubes, and root images were taken. A high-throughput root imaging analysis using Rhizovision software was performed by setting the scale to extract the eight RSA traits and four plant biomass-related traits. GWAS identified 323 association signals for 12 root and biomass traits present on all wheat chromosomes, while the most important and reliable genetic loci (based on pleotropic loci and candidate genes) were identified on chromosomes 2A, 2B, 5A, 5D, 6A, 7B, and 7D for RSA. SNP annotation and transcriptome profiling identified nine candidate genes regulating the RSA and plant biomass traits, including ROOTLESS WITH UNDETECTABLE MERISTEM1, MYB TRANSCRIPTION FACTOR4, BRASSINOSTEROID INSENSITIVE1, SLENDER RICE1, AUXIN-RESPONSIVE FACTOR25, SCARECROW, NARROW LEAF2, PIN-FORMED1 AND PHOSPHATE TRANSCRIPTION FACTOR1. This study provided pre-breeding information for deep-rooting genotypes and associated markers that will accelerate the incorporation of such traits in breeding.

Bridging Time-series Image Phenotyping and Functional-Structural Plant Modeling to Predict Adventitious Root System Architecture

Root system architecture (RSA) is an important measure of how plants navigate and interact with the soil environment. However, current methods in studying RSA must make tradeoffs between precision of data and proximity to natural conditions, with root growth in germination papers providing accessibility and high data resolution. Functional-structural plant models (FSPMs) can overcome this tradeoff, though parameterization and evaluation of FSPMs are traditionally based in manual measurements and visual comparison. Here, we applied a germination paper system to study the adventitious RSA and root phenology of Populus trichocarpa stem cuttings using time-series image-based phenotyping augmented by FSPM. We found a significant correlation between timing of root initiation and thermal time at cutting collection (P value = 0.0061, R2 = 0.875), but little correlation with RSA. We also present a use of RhizoVision [1] for automatically extracting FSPM parameters from time series images and evaluating FSPM simulations. A high accuracy of the parameterization was achieved in predicting 2D growth with a sensitivity rate of 83.5%. This accuracy was lost when predicting 3D growth with sensitivity rates of 38.5% to 48.7%, while overall accuracy varied with phenotyping methods. Despite this loss in accuracy, the new method is amenable to high throughput FSPM parameterization and bridges the gap between advances in time-series phenotyping and FSPMs.

RNAseq of diverse spring wheat cultivars released during last 110 years

Here, we performed RNA-seq based expression analysis of root and leaf tissues of a set of 24 historical spring wheat cultivars representing 110 years of temporal genetic variations. This huge 130 tissues RNAseq dataset was initially used to study expression pattern of 97 genes regulating root growth and development in wheat. Root system architecture (RSA) is an important target for breeding stress-resilient and high-yielding wheat cultivars under climatic fluctuations. However, root transcriptome analysis is usually obscured due to challenges in root research due to their below ground presence. We also validated the dataset by performing correlation analysis between expression of RSA related genes in roots and leaves with 25 root traits analyzed under varying moisture conditions and 10 yield-related traits. The Pearson's correlation coefficients between root phenotypes and expression of root-specific genes varied from -0.72 to 0.78, and strong correlations with genes such as DRO1, TaMOR, ARF4, PIN1 was observed. The presented datasets have multiple uses such as a) studying the change in expression pattern of genes during time, b) differential expression of genes in two very important tissues of wheat i.e., leaf and roots, and c) studying customized expression of genes associated with important phenotypes in diverse wheat cultivars. The initial findings presented here provided key insights into understanding the transcriptomic basis of phenotypic variability of RSA in wheat cultivars.

Enhancing climate change resilience in agricultural crops

Climate change threatens global food and nutritional security through negative effects on crop growth and agricultural productivity. Many countries have adopted ambitious climate change mitigation and adaptation targets that will exacerbate the problem, as they require significant changes in current agri-food systems. In this review, we provide a roadmap for improved crop production that encompasses the effective transfer of current knowledge into plant breeding and crop management strategies that will underpin sustainable agriculture intensification and climate resilience. We identify the main problem areas and highlight outstanding questions and potential solutions that can be applied to mitigate the impacts of climate change on crop growth and productivity. Although translation of scientific advances into crop production lags far behind current scientific knowledge and technology, we consider that a holistic approach, combining disciplines in collaborative efforts, can drive better connections between research, policy, and the needs of society.

Dissecting the genetic architecture of root-related traits in a grafted wild Vitis berlandieri population for grapevine rootstock breeding

In woody perennial plants, quantitative genetics and association studies remain scarce for root-related traits, due to the time required to obtain mature plants and the complexity of phenotyping. In grapevine, a grafted cultivated plant, most of the rootstocks used are hybrids between American Vitis species (V. rupestris, V. riparia, and V. berlandieri). In this study, we used a wild population of an American Vitis species (V. berlandieri) to analyze the genetic architecture of the root-related traits of rootstocks in a grafted context. We studied a population consisting of 211 genotypes, with one to five replicates each (n = 846 individuals), plus four commercial rootstocks as control genotypes (110R, 5BB, Börner, and SO4). After two independent years of experimentation, the best linear unbiased estimates method revealed root-related traits with a moderate-to-high heritability (0.36-0.82) and coefficient of genetic variation (0.15-0.45). A genome-wide association study was performed with the BLINK model, leading to the detection of 11 QTL associated with four root-related traits (one QTL was associated with the total number of roots, four were associated with the number of small roots (< 1 mm in diameter), two were associated with the number of medium-sized roots (1 mm < diameter < 2 mm), and four were associated with mean diameter) accounting for up to 25.1% of the variance. Three genotypes were found to have better root-related trait performances than the commercial rootstocks and therefore constitute possible new candidates for use in grapevine rootstock breeding programs.

Effects of Salt Tolerance Training on Multidimensional Root Distribution and Root-Shoot Characteristics of Summer Maize under Brackish Water Irrigation

To investigate the impact of brackish water irrigation on the multidimensional root distribution and root-shoot characteristics of summer maize under different salt-tolerance-training modes, a micro-plot experiment was conducted from June to October in 2022 at the experimental station in Hohai University, China. Freshwater irrigation was used as the control (CK), and different concentrations of brackish water (S0: 0.08 g·L-1, S1: 2.0 g·L-1, S2: 4.0 g·L-1, S3: 6.0 g·L-1) were irrigated at six-leaf stage, ten-leaf stage, and tasseling stage, constituting different salt tolerance training modes, referred to as S0-2-3, S0-3-3, S1-2-3, S1-3-3, S2-2-3, and S2-3-3. The results showed that although their fine root length density (FRLD) increased, the S0-2-3 and S0-3-3 treatments reduced the limit of root extension in the horizontal direction, causing the roots to be mainly distributed near the plants. This resulted in decreased leaf area and biomass accumulation, ultimately leading to significant yield reduction. Additionally, the S2-2-3 and S2-3-3 treatments stimulated the adaptive mechanism of maize roots, resulting in boosted fine root growth to increase the FRLD and develop into deeper soil layers. However, due to the prolonged exposure to a high level of salinity, their roots below 30 cm depth senesced prematurely, leading to an inhibition in shoot growth and also resulting in yield reduction of 10.99% and 11.75%, compared to CK, respectively. Furthermore, the S1-2-3 and S1-3-3 treatments produced more reasonable distributions of FRLD, which did not boost fine root growth but established fewer weak areas (FLRD < 0.66 cm-3) in their root systems. Moreover, the S1-2-3 treatment contributed to increasing leaf development and biomass accumulation, compared to CK, whereas it allowed for minimizing yield reduction. Therefore, our study proposed the S1-2-3 treatment as the recommended training mode for summer maize while utilizing brackish water resources.

Plasticity of root hair and rhizosheath traits and their relationship to phosphorus uptake in sorghum

Sorghum is an essential crop for resilient and adaptive responses to climate change. The root systems of crop plants significantly contribute to the tolerance of abiotic stresses. There is little information on sorghum genotypes' root systems and plasticity to external P supply. In this paper, we investigated the variations in root systems, as well as the responses, trait relationships, and plasticity of two sorghum genotypes (Naga Red and Naga White), popularly grown in Ghana, to five external P concentrations ([P]ext): 0, 100, 200, 300, and 400 mg P kg-1 soil. Sorghum plants were grown in greenhouse pots and harvested for root trait measurements at the five-leaf and growing point differentiation (GPD) developmental stages. The plants were responsive to [P]ext and formed rhizosheaths. The two genotypes showed similar characteristics for most of the traits measured but differed significantly in total and lateral root lengths in favor of the red genotype. For example, at the five-leaf growth stage, the lateral root length of the red and white genotypes was 22.8 and 16.2 cm, respectively, but 124 and 88.9 cm, at the GPD stage. The responses and plasticity of the root system traits, including rhizosheath, to [P]ext were more prominent, positive, and linear at the five-leaf stage than at the GPD growth stage. At the five-leaf growth stage, total root length increased by about 2.5-fold with increasing [P]ext compared to the unamended soil. At the GPD stage, however, total root length decreased by about 1.83-fold as [P]ext increased compared to the unamended soil. Specific rhizosheath weight correlated with RHD, albeit weakly, and together explained up to 59% of the variation in tissue P. Root hair density was more responsive to P supply than root hair length and showed a similar total and lateral root length pattern. Most desirable responses to P occurred at a rate of 200-300 mg P kg-1 soil. It is concluded that sorghum would form rhizosheath, and [P]ext could be critical for the early vigorous growth of sorghum's responsive root and shoot traits. Beyond the early days of development, additional P application might be necessary to sustain the responses and plasticity observed during the early growth period, but this requires further investigation, potentially under field conditions.

Perennial grass root system specializes for multiple resource acquisitions with differential elongation and branching patterns

Roots optimize the acquisition of limited soil resources, but relationships between root forms and functions have often been assumed rather than demonstrated. Furthermore, how root systems co-specialize for multiple resource acquisitions is unclear. Theory suggests that trade-offs exist for the acquisition of different resource types, such as water and certain nutrients. Measurements used to describe the acquisition of different resources should then account for differential root responses within a single system. To demonstrate this, we grew Panicum virgatum in split-root systems that vertically partitioned high water availability from nutrient availability so that root systems must absorb the resources separately to fully meet plant demands. We evaluated root elongation, surface area, and branching, and we characterized traits using an order-based classification scheme. Plants allocated approximately 3/4th of primary root length towards water acquisition, whereas lateral branches were progressively allocated towards nutrients. However, root elongation rates, specific root length, and mass fraction were similar. Our results support the existence of differential root functioning within perennial grasses. Similar responses have been recorded in many plant functional types suggesting a fundamental relationship. Root responses to resource availability can be incorporated into root growth models via maximum root length and branching interval parameters.

Crop root system plasticity for improved yields in saline soils

Crop yields must increase to meet the demands of a growing world population. Soil salinization is increasing due to the impacts of climate change, reducing the area of arable land for crop production. Plant root systems are plastic, and their architecture can be modulated to (1) acquire nutrients and water for growth, and (2) respond to hostile soil environments. Saline soils inhibit primary root growth and alter root system architecture (RSA) of crop plants. In this review, we explore how crop root systems respond and adapt to salinity, focusing predominately on the staple cereal crops wheat, maize, rice, and barley, that all play a major role in global food security. Cereal crops are classified as glycophytes (salt-sensitive) however salt-tolerance can differ both between species and within a species. In the past, due to the inherent difficulties associated with visualising and measuring root traits, crop breeding strategies have tended to focus on optimising shoot traits. High-resolution phenotyping techniques now make it possible to visualise and measure root traits in soil systems. A steep, deep and cheap root ideotype has been proposed for water and nitrogen capture. Changes in RSA can be an adaptive strategy to avoid saline soils whilst optimising nutrient and water acquisition. In this review we propose a new model for designing crops with a salt-tolerant root ideotype. The proposed root ideotype would exhibit root plasticity to adapt to saline soils, root anatomical changes to conserve energy and restrict sodium (Na⁺) uptake, and transport mechanisms to reduce the amount of Na⁺ transported to leaves. In the future, combining high-resolution root phenotyping with advances in crop genetics will allow us to uncover root traits in complex crop species such as wheat, that can be incorporated into crop breeding programs for yield stability in saline soils.

Quantification of the three-dimensional root system architecture using an automated rotating imaging system

BACKGROUND

Crop breeding based on root system architecture (RSA) optimization is an essential factor for improving crop production in developing countries. Identification, evaluation, and selection of root traits of soil-grown crops require innovations that enable high-throughput and accurate quantification of three-dimensional (3D) RSA of crops over developmental time.

RESULTS

We proposed an automated imaging system and 3D imaging data processing pipeline to quantify the 3D RSA of soil-grown individual plants across seedlings to the mature stage. A multi-view automated imaging system composed of a rotary table and an imaging arm with 12 cameras mounted with a combination of fan-shaped and vertical distribution was developed to obtain 3D image data of roots grown on a customized root support mesh. A 3D imaging data processing pipeline was developed to quantify the 3D RSA based on the point cloud generated from multi-view images. The global architecture of root systems can be quantified automatically. Detailed analysis of the reconstructed 3D root model also allowed us to investigate the Spatio-temporal distribution of roots. A method combining horizontal slicing and iterative erosion and dilation was developed to automatically segment different root types, and identify local root traits (e.g., length, diameter of the main root, and length, diameter, initial angle, and the number of nodal roots or lateral roots). One maize (Zea mays L.) cultivar and two rapeseed (Brassica napus L.) cultivars at different growth stages were selected to test the performance of the automated imaging system and 3D imaging data processing pipeline.

CONCLUSIONS

The results demonstrated the capabilities of the proposed imaging and analytical system for high-throughput phenotyping of root traits for both monocotyledons and dicotyledons across growth stages. The proposed system offers a potential tool to further explore the 3D RSA for improving root traits and agronomic qualities of crops.

Root system architecture of historical spring wheat cultivars is associated with alleles and transcripts of major functional genes

We evaluated root system architecture (RSA) of a set of 58 historical spring wheat cultivars from Pakistan representing 105 years of selection breeding. The evaluations were carried out under control and water-limited conditions using a high-throughput phenotyping system coupled with RhizoVision Explorer software. The cultivars were classified into three groups based on release year as cultivars released pre-1965, released between 1965 and 2000, and cultivars released post-2000. Under water-limited conditions a decline in 20 out of 25 RSA component traits was observed in pre-1965 cultivars group. Whereas cultivars released after the 1965, so-called green revolution period, showed a decline in 17 traits with significant increments in root length, depth, and steep angle frequency which are important root traits for resource-uptake under water-limited conditions. Similarly, cultivars released after 2000 indicated an increase in the number of roots, depth, diameter, surface area, and steep angle frequency. The coefficient of correlation analysis showed a positive correlation between root depth and yield-related traits under water-limited conditions. We also investigated the effects of green-revolution genes (Rht1) and some phenology-related genes such as DRO1, TaMOR, TaLTPs, TaSus-2B on RSA and identified significant associations of these genes with important root traits. There was strong selection pressure on DRO1 gene in cultivated wheat indicating the allele fixed in modern wheat cultivars is different from landraces. The expression of DRO1, and TaMOR were retrieved from an RNAseq experiment, and results were validated using qRT-PCR. The highest expression of DRO1 and TaMOR was found in Chakwal-50, a rainfed cultivar released in 2008, and MaxiPak-65 released in 1965. We conclude that there is a positive historic change in RSA after 1965 that might be attributed to genetic factors associated with favored RSA traits. Furthermore, we suggest root depth and steep angle as promising traits to withstand water-limited environments and may have implications in selection for breeding.

Responses of root system architecture to water stress at multiple levels: A meta-analysis of trials under controlled conditions

Plants are exposed to increasingly severe drought events and roots play vital roles in maintaining plant survival, growth, and reproduction. A large body of literature has investigated the adaptive responses of root traits in various plants to water stress and these studies have been reviewed in certain groups of plant species at a certain scale. Nevertheless, these responses have not been synthesized at multiple levels. This paper screened over 2000 literatures for studies of typical root traits including root growth angle, root depth, root length, root diameter, root dry weight, root-to-shoot ratio, root hair length and density and integrates their drought responses at genetic and morphological scales. The genes, quantitative trait loci (QTLs) and hormones that are involved in the regulation of drought response of the root traits were summarized. We then statistically analyzed the drought responses of root traits and discussed the underlying mechanisms. Moreover, we highlighted the drought response of 1-D and 2-D root length density (RLD) distribution in the soil profile. This paper will provide a framework for an integrated understanding of root adaptive responses to water deficit at multiple scales and such insights may provide a basis for selection and breeding of drought tolerant crop lines.

Transcriptomic analysis reveals the contribution of QMrl-7B to wheat root growth and development

Roots are the major organs for water and nutrient acquisition and substantially affect plant growth, development and reproduction. Improvements to root system architecture are highly important for the increased yield potential of bread wheat. QMrl-7B, a major stable quantitative trait locus (QTL) that controls maximum root length (MRL), essentially contributes to an improved root system in wheat. To further analyze the biological functions of QMrl-7B in root development, two sets of Triticum aestivum near-isogenic lines (NILs), one with superior QMrl-7B alleles from cultivar Kenong 9204 (KN9204) named NIL^KN9204 and another with inferior QMrl-7B alleles from cultivar Jing 411 (J411) named NIL^J411, were subjected to transcriptomic analysis. Among all the mapped genes analyzed, 4871 genes were identified as being differentially expressed between the pairwise NILs under different nitrogen (N) conditions, with 3543 genes expressed under normal-nitrogen (NN) condition and 2689 genes expressed under low-nitrogen (LN) condition. These genes encode proteins that mainly include N O 3 - transporters, phytohormone signaling components and transcription factors (TFs), indicating the presence of a complex regulatory network involved in root determination. In addition, among the 13524 LN-induced differentially expressed genes (DEGs) detected in this study, 4308 and 2463 were specifically expressed in the NIL^KN9204 and NIL^J411, respectively. These DEGs reflect different responses of the two sets of NILs to varying N supplies, which likely involve LN-induced root growth. These results explain the better-developed root system and increased root vitality conferred by the superior alleles of QMrl-7B and provide a deeper understanding of the genetic underpinnings of root traits, pointing to a valuable locus suitable for future breeding efforts for sustainable agriculture.

Genome-wide association study reveals that GhTRL1 and GhPIN8 affect cotton root development

Two regions located at chromosome A05 and D04 were found to be significantly associated with 0-0.5 mm and 0.5-2 mm diameter roots, respectively, and two candidate genes related to root development were identified. Roots absorb water and nutrients, and play an important role in plant growth. However, there are few genetic developmental studies on cotton root structural traits. In this study, we used 200 upland cotton (Gossypium hirsutum L.) varieties to analyze the phenotypic variation of 43 traits. A total of 2001 related single-nucleotide polymorphism (SNP) sites located within or near 1046 genes were detected through a genome-wide association study (GWAS). The 32 root traits were linked to SNPs that corresponded to 317 nonrepetitive genes. For SNPs associated with root length and 0-0.5 mm diameter root traits, a significant peak appeared on chromosome A05 (between 21.91 and 22.24 Mb). For SNPs associated with root surface area, root volume and 0.5-2 mm diameter root traits, a significant peak appeared on chromosome D04 (between 7.35 and 7.70 Mb). Within these two key regions, SNPs were detected in the promoter and coding regions of two candidate genes, GhTRL1-A05 and GhPIN8-D04. The expression levels of these two genes also changed significantly according to transcriptome sequencing and quantitative real-time PCR (qRT-PCR). After silencing the GhTRL1 and GhPIN8 genes via virus-induced gene silencing (VIGS), we found that the plants expressing TRV2::GhTRL1 and TRV2::GhPIN8 had a reduced root length, surface area. Moreover, the contents of cis-12-oxo-phytodienoic acid (cis-OPDA), isopentenyl adenosine (iPR) and cis-zeatin (cZ) in the roots of the plants expressing TRV2::GhTRL1 decreased. This study contributes to the cultivation and improvement of cotton varieties.

Association of Root Hair Length and Density with Yield-Related Traits and Expression Patterns of TaRSL4 Underpinning Root Hair Length in Spring Wheat

Root hairs play an important role in absorbing water and nutrients in crop plants. Here we optimized high-throughput root hair length (RHL) and root hair density (RHD) phenotyping in wheat using a portable Dinolite™ microscope. A collection of 24 century wide spring wheat cultivars released between 1911 and 2016 were phenotyped for RHL and RHD. The results revealed significant variations for both traits with five and six-fold variation for RHL and RHD, respectively. RHL ranged from 1.01 mm to 1.77 mm with an average of 1.39 mm, and RHD ranged from 17.08 mm^-2 to 20.8 mm^-2 with an average of 19.6 mm^-2. Agronomic and physiological traits collected from five different environments and their best linear unbiased predictions (BLUPs) were correlated with RHL and RHD, and results revealed that relative-water contents (RWC), biomass and grain per spike (GpS) were positively correlated with RHL in both water-limited and well-watered conditions. While RHD was negatively correlated with grain yield (GY) in four environments and their BLUPs. Both RHL and RHD had positive correlation indicating the possibility of simultaneous selection of both phenotypes during wheat breeding. The expression pattern of TaRSL4 gene involved in regulation of root hair length was determined in all 24 wheat cultivars based on RNA-seq data, which indicated the differentially higher expression of the A- and D- homeologues of the gene in roots, while B-homeologue was consistently expressed in both leaf and roots. The results were validated by qRT-PCR and the expression of TaRSL4 was consistently high in rainfed cultivars such as Chakwal-50, Rawal-87, and Margallah-99. Overall, the new phenotyping method for RHL and RHD along with correlations with morphological and physiological traits in spring wheat cultivars improved our understanding for selection of these phenotypes in wheat breeding.

A major quantitative trait locus for wheat total root length associated with precipitation distribution

Optimizing root system architecture (RSA) allows crops to better capture water and nutrients and adapt to harsh environment. Parental reproductive environment (PRE) has been reported to significantly affect growth and development throughout the life cycle of the next generation. In this study, 10 RSA-related traits were evaluated in seedling stage from five independent hydroponic tests using seeds harvested from five different PREs. Based on the Wheat55K SNP array-based genetic map, quantitative trait loci (QTL) for these traits were detected in a recombinant inbred line population. Twenty-eight putative QTL for RSA-related traits were detected, covering thirteen chromosomal regions. A major QTL, QTrl.sicau-2SY-4D for total root length (TRL), which was likely independent of PREs, explained 15.81-38.48% of phenotypic variations and was located at 14.96-19.59 Mb on chromosome arm 4DS. Interestingly, it showed pleiotropic effects on TRL, root area, root volume, root forks, root dry weight, and shoot dry weight. The functional marker KASP-Rht-D1 for Rht-D1 was used to genotype 2SY population and remapping QTL for TRL showed that QTrl.sicau-2SY-4D was not linked to Rht-D1. The kompetitive allele-specific PCR (KASP) marker, KASP-AX-110527441 linked to this major QTL, was developed and used to successfully validate its effect in three different genetic populations. Further analysis suggested that the positive allele at QTrl.sicau-2SY-4D was mainly utilized in wheat breeding of northwest China where precipitation was significantly lower, indicating that wheat requires longer TRL to capture water and nutrients in arid or semi-arid regions due to deficient precipitation. Additionally, four genes (TraesCS4D03G0059800, TraesCS4D03G0057800, TraesCS4D03G0064000, and TraesCS4D03G0064400) possibly related to root development were predicted in physical interval of QTrl.sicau-2SY-4D. Taken together, these results enrich our understanding on the genetic basis of RSA and provide a potentially valuable TRL QTL for wheat breeding.

Root traits in Crambe abyssinica Hochst and Raphanus sativus L. plants are associated with differential tolerance to water deficit and post-stress recovery

Background

Previous studies have shown that Crambe abyssinica and Raphanus sativus are physiologically tolerant to water deficits; however, there is a lack of information on the mechanisms responsible for their tolerance regarding root morphological characteristics. This study aimed to characterize morphological changes in the root system of C. abyssinica and R. sativus subjected water deficit, as well as to identify the responses that improve tolerance and post-stress recovery capacity of these plants.

Methods

Independent experiments for each specieswere performed in a controlled greenhouse, where plants were randomly set in a randomized block design with five replicates. Plants of C. abyssinica and R. sativus were cultivated in pots and exposed to well-watered treatment (WW; 90% water holding capacity–WHC of the substrate) or water deficit (WD; 40% WHC) conditions, at 28 days after planting. The plants were kept under WD for 7, 14, or 21 days with rehydration soon after each episode of water deficit. Assessment of water relations, biomass allocation, leaf and root system morphological characteristics and gas exchange were performed after each period of water deficit and 48 h after rehydration.

Results

The water deficit reduced the water status of both species, and morphological and biomass allocation were not recovered after rehydration. Photosynthesis of C. abyssinica decreased with prolonged water deficit, which was also not recovered after rehydration. In R. sativus, photosynthesis was not altered by WD for 21 days, and a higher WUE was recorded. Root morphology of R. sativus was mainly affected at 14 days of WD, while the traits related to very fine roots increased at 21 days of WD, when compared to WW plants. Thus, R. sativus has shown greater tolerance to water deficits mainly due to the presence of very fine roots throughout the period of stress, when compared to C. abyssinica in which the fine roots predominated.