Signal communication during microbial modulation of root system architecture.

Every living organism on Earth depends on its interactions with other organisms. In the rhizosphere, plants and microorganisms constantly exchange signals and influence each other's behavior. Recent studies have shown that many beneficial rhizosphere microbes can produce specific signaling molecules that affect plant root architecture and therefore could have substantial effects on above-ground growth. This review examines these chemical signals and summarizes their mechanisms of action, with the aim of enhancing our understanding of plant-microbe interactions and providing references for the comprehensive development and utilization of these active components in agricultural production. In addition, we highlight future research directions and challenges, such as searching for microbial signals to induce primary root development.

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.

Plant nitrogen availability and crosstalk with phytohormones signallings and their biotechnology breeding application in crops.

Nitrogen (N), one of the most important nutrients, limits plant growth and crop yields in sustainable agriculture system, in which phytohormones are known to play essential roles in N availability. Hence, it is not surprising that massive studies about the crosstalk between N and phytohormones have been constantly emerging. In this review, with the intellectual landscape of N and phytohormones crosstalk provided by the bibliometric analysis, we trace the research story of best-known crosstalk between N and various phytohormones over the last 20 years. Then, we discuss how N regulates various phytohormones biosynthesis and transport in plants. In reverse, we also summarize how phytohormones signallings modulate root system architecture (RSA) in response to N availability. Besides, we expand to outline how phytohormones signallings regulate uptake, transport, and assimilation of N in plants. Further, we conclude advanced biotechnology strategies, explain their application, and provide potential phytohormones-regulated N use efficiency (NUE) targets in crops. Collectively, this review provides not only a better understanding on the recent progress of crosstalk between N and phytohormones, but also targeted strategies for improvement of NUE to increase crop yields in future biotechnology breeding of crops.

Genome-wide association study reveals candidate genes controlling root system architecture under low phosphorus supply at seedling stage in Brassica napus.

Optimal root system architecture (RSA) is essential for vigorous growth and yield in crops. Plants have evolved adaptive mechanisms in response to low phosphorus (LP) stress, and one of those is changes in RSA. Here, more than five million single-nucleotide polymorphisms (SNPs) obtained from whole-genome re-sequencing data (WGR) of an association panel of 370 oilseed rape (Brassica napus L.) were used to conduct a genome-wide association study (GWAS) of RSA traits of the panel at LP in "pouch and wick" system. Fifty-two SNPs were forcefully associated with lateral root length (LRL), total root length (TRL), lateral root density (LRD), lateral root number (LRN), mean lateral root length (MLRL), and root dry weight (RDW) at LP. There were significant correlations between phenotypic variation and the number of favorable alleles of the associated loci on chromosomes A06 (chrA06_20030601), C03 (chrC03_3535483), and C07 (chrC07_42348561), respectively. Three candidate genes (BnaA06g29270D, BnaC03g07130D, and BnaC07g43230D) were detected by combining transcriptome, candidate gene association analysis, and haplotype analysis. Cultivar carrying "CCGC" at BnaA06g29270DHap1, "CAAT" at BnaC03g07130DHap1, and "ATC" at BnaC07g43230DHap1 had greater LRL, LRN, and RDW than lines carrying other haplotypes at LP supply. The RSA of a cultivar harboring the three favorable haplotypes was further confirmed by solution culture experiments. These findings define exquisite insights into genetic architectures underlying B. napus RSA at LP and provide valuable gene resources for root breeding. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01411-2.

Convergent evolution of root system architecture in two independently evolved lineages of weedy rice.

Root system architecture (RSA) is a critical aspect of plant growth and competitive ability. Here we used two independently evolved strains of weedy rice, a de-domesticated form of rice, to study the evolution of weed-associated RSA traits and the extent to which they evolve through shared or different genetic mechanisms. We characterised 98 two-dimensional and three-dimensional RSA traits in 671 plants representing parents and descendants of two recombinant inbred line populations derived from two weed × crop crosses. A random forest machine learning model was used to assess the degree to which root traits can predict genotype and the most diagnostic traits for doing so. We used quantitative trait locus (QTL) mapping to compare genetic architecture between the weed strains. The two weeds were distinguishable from the crop in similar and predictable ways, suggesting independent evolution of a 'weedy' RSA phenotype. Notably, comparative QTL mapping revealed little evidence for shared underlying genetic mechanisms. Our findings suggest that despite the double bottlenecks of domestication and de-domestication, weedy rice nonetheless shows genetic flexibility in the repeated evolution of weedy RSA traits. Whereas the root growth of cultivated rice may facilitate interactions among neighbouring plants, the weedy rice phenotype may minimise below-ground contact as a competitive strategy.

Evaluation of high yielding soybean germplasm under water limitation.

Limited information is available for soybean root traits and their plasticity under drought stress. To date, no studies have focused on examining diverse soybean germplasm for regulation of shoot and root response under water limited conditions across varying soil types. In this study, 17 genetically diverse soybean germplasm lines were selected to study root response to water limited conditions in clay (trial 1) and sandy soil (trial 2) in two target environments. Physiological data on shoot traits was measured at multiple crop stages ranging from early vegetative to pod filling. The phenotypic root traits, and biomass accumulation data are collected at pod filling stage. In trial 1, the number of lateral roots and forks were positively correlated with plot yield under water limitation and in trial 2, lateral root thickness was positively correlated with the hill plot yield. Plant Introduction (PI) 578477A and 088444 were found to have higher later root number and forks in clay soil with higher yield under water limitation. In sandy soil, PI458020 was found to have a thicker lateral root system and higher yield under water limitation. The genotypes identified in this study could be used to enhance drought tolerance of elite soybean cultivars through improved root traits specific to target environments.

Challenges and opportunities for quantifying roots and rhizosphere interactions through imaging and image analysis.

The morphology of roots and root systems influences the efficiency by which plants acquire nutrients and water, anchor themselves and provide stability to the surrounding soil. Plant genotype and the biotic and abiotic environment significantly influence root morphology, growth and ultimately crop yield. The challenge for researchers interested in phenotyping root systems is, therefore, not just to measure roots and link their phenotype to the plant genotype, but also to understand how the growth of roots is influenced by their environment. This review discusses progress in quantifying root system parameters (e.g. in terms of size, shape and dynamics) using imaging and image analysis technologies and also discusses their potential for providing a better understanding of root:soil interactions. Significant progress has been made in image acquisition techniques, however trade-offs exist between sample throughput, sample size, image resolution and information gained. All of these factors impact on downstream image analysis processes. While there have been significant advances in computation power, limitations still exist in statistical processes involved in image analysis. Utilizing and combining different imaging systems, integrating measurements and image analysis where possible, and amalgamating data will allow researchers to gain a better understanding of root:soil interactions.

Root phenotyping: from component trait in the lab to breeding.

In the last decade cheaper and faster sequencing methods have resulted in an enormous increase in genomic data. High throughput genotyping, genotyping by sequencing and genomic breeding are becoming a standard in plant breeding. As a result, the collection of phenotypic data is increasingly becoming a limiting factor in plant breeding. Genetic studies on root traits are being hampered by the complexity of these traits and the inaccessibility of the rhizosphere. With an increasing interest in phenotyping, breeders and scientists try to overcome these limitations, resulting in impressive developments in automated phenotyping platforms. Recently, many such platforms have been thoroughly described, yet their efficiency to increase genetic gain often remains undiscussed. This efficiency depends on the heritability of the phenotyped traits as well as the correlation of these traits with agronomically relevant breeding targets. This review provides an overview of the latest developments in root phenotyping and describes the environmental and genetic factors influencing root phenotype and heritability. It also intends to give direction to future phenotyping and breeding strategies for optimizing root system functioning. A quantitative framework to determine the efficiency of phenotyping platforms for genetic gain is described. By increasing heritability, managing effects caused by interactions between genotype and environment and by quantifying the genetic relation between traits phenotyped in platforms and ultimate breeding targets, phenotyping platforms can be utilized to their maximum potential.

Genome-wide linkage mapping of root system architecture-related traits in common wheat (Triticum aestivum L.).

Identifying loci for root system architecture (RSA) traits and developing available markers are crucial for wheat breeding. In this study, RSA-related traits, including total root length (TRL), total root area (TRA), and number of root tips (NRT), were evaluated in the Doumai/Shi4185 recombinant inbred line (RIL) population under hydroponics. In addition, both the RILs and parents were genotyped using the wheat 90K single-nucleotide polymorphism (SNP) array. In total, two quantitative trait loci (QTLs) each for TRL (QTRL.caas-4A.1 and QTRL.caas-4A.2), TRA (QTRA.caas-4A and QTRA.caas-4D), and NRT (QNRT.caas-5B and QNRT.caas-5D) were identified and each explaining 5.94%-9.47%, 6.85%-7.10%, and 5.91%-10.16% phenotypic variances, respectively. Among these, QTRL.caas-4A.1 and QTRA.caas-4A overlapped with previous reports, while QTRL.caas-4A.2, QTRA.caas-4D, QNRT.caas-5B, and QNRT.caas-5D were novel. The favorable alleles of QTRL.caas-4A.1, QTRA.caas-4A, and QTRA.caas-5B were contributed by Doumai, whereas the favorable alleles of QTRL.caas-4A.2, QTRA.caas-4D, and QTRA.caas-5D originated from Shi 4185. Additionally, two competitive allele-specific PCR (KASP) markers, Kasp_4A_RL (QTRA.caas-4A) and Kasp_5D_RT (QNRT.caas-5D), were developed and validated in 165 wheat accessions. This study provides new loci and available KASP markers, accelerating wheat breeding for higher yields.

'Root of all success': Plasticity in root architecture of invasive wild radish for adaptive benefit.

Successful plant establishment in a particular environment depends on the root architecture of the seedlings and the extent of edaphic resource utilization. However, diverse habitats often pose a predicament on the suitability of the fundamental root structure of a species that evolved over a long period. We hypothesized that the plasticity in the genetically controlled root architecture in variable habitats provides an adaptive advantage to worldwide-distributed wild radish (Raphanus raphanistrum, Rr) over its close relative (R. pugioniformis, Rp) that remained endemic to the East Mediterranean region. To test the hypothesis, we performed a reciprocal comparative analysis between the two species, growing in a common garden experiment on their native soils (Hamra/Sandy for Rr, Terra Rossa for Rp) and complementary controlled experiments mimicking the major soil compositions. Additionally, we analyzed the root growth kinetics via semi-automated digital profiling and compared the architecture between Rr and Rp. In both experiments, the primary roots of Rr were significantly longer, developed fewer lateral roots, and showed slower growth kinetics than Rp. Multivariate analyses of seven significant root architecture variables revealed that Rr could successfully adapt to different surrogate growth conditions by only modulating their main root length and number of lateral roots. In contrast, Rp needs to modify several other root parameters, which are very resource-intensive, to grow on non-native soil. Altogether the findings suggest an evo-devo adaptive advantage for Rr as it can potentially establish in various habitats with the minimal tweak of key root parameters, hence allocating resources for other developmental requirements.

Unraveling Genomic Regions Controlling Root Traits as a Function of Nitrogen Availability in the MAGIC Wheat Population WM-800.

An ever-growing world population demands to be fed in the future and environmental protection and climate change need to be taken into account. An important factor here is nitrogen uptake efficiency (NUpE), which is influenced by the root system (the interface between plant and soil). To understand the natural variation of root system architecture (RSA) as a function of nitrogen (N) availability, a subset of the multiparent advanced generation intercross (MAGIC) winter wheat population WM-800 was phenotyped under two contrasting N treatments in a high-throughput phenotyping system at the seedling stage. Fourteen root and shoot traits were measured. Subsequently, these traits were genetically analyzed using 13,060 polymorphic haplotypes and SNPs in a genome-wide association study (GWAS). In total, 64 quantitative trait loci (QTL) were detected; 60 of them were N treatment specific. Candidate genes for the detected QTL included NRT1.1 and genes involved in stress signaling under N-, whereas candidate genes under N+ were more associated with general growth, such as mei2 and TaWOX11b. This finding may indicate (i) a disparity of the genetic control of root development under low and high N supply and, furthermore, (ii) the need for an N specific selection of genes and genotypes in breeding new wheat cultivars with improved NUpE.

Rice immediately adapts the dynamics of photosynthates translocation to roots in response to changes in soil water environment.

Rice is susceptible to abiotic stresses such as drought stress. To enhance drought resistance, elucidating the mechanisms by which rice plants adapt to intermittent drought stress that may occur in the field is an important requirement. Roots are directly exposed to changes in the soil water condition, and their responses to these environmental changes are driven by photosynthates. To visualize the distribution of photosynthates in the root system of rice plants under drought stress and recovery from drought stress, we combined X-ray computed tomography (CT) with open type positron emission tomography (OpenPET) and positron-emitting tracer imaging system (PETIS) with 11C tracer. The short half-life of 11C (20.39 min) allowed us to perform multiple experiments using the same plant, and thus photosynthate translocation was visualized as the same plant was subjected to drought stress and then re-irrigation for recovery. The results revealed that when soil is drier, 11C-photosynthates mainly translocated to the seminal roots, likely to promote elongation of the root with the aim of accessing water stored in the lower soil layers. The photosynthates translocation to seminal roots immediately stopped after rewatering then increased significantly in crown roots. We suggest that when rice plant experiencing drought is re-irrigated from the bottom of pot, the destination of 11C-photosynthates translocation immediately switches from seminal root to crown roots. We reveal that rice roots are responsive to changes in soil water conditions and that rice plants differentially adapts the dynamics of photosynthates translocation to crown roots and seminal roots depending on soil conditions.

Mechanism of Intermittent Deep Tillage and Different Depths Improving Crop Growth From the Perspective of Rhizosphere Soil Nutrients, Root System Architectures, Bacterial Communities, and Functional Profiles.

Long-term conventional shallow tillage reduced soil quality and limited the agriculture development. Intermittent deep tillage could effectively promote agricultural production, through optimizing soil structure, underground ecology system, and soil fertility. However, the microecological mechanism of intermittent deep tillage promoting agriculture production has never been reported, and the effect of tillage depth on crop growth has not been explored in detail. In this study, three levels of intermittent deep tillage (30, 40, and 50 cm) treatments were conducted in an experimental field site with over 10 years of conventional shallow tillage (20 cm). Our results indicated that intermittent deep tillage practices helped to improve plant physiological growth status, chlorophyll a, and resistance to diseases, and the crop yield and value of output were increased with the deeper tillage practices. Crop yield (18.59%) and value of output (37.03%) were highest in IDT-50. There were three mechanisms of intermittent deep tillage practices that improved crop growth: (1) Intermittent deep tillage practices increased soil nutrients and root system architecture traits, which improved the fertility and nutrient uptake of crop through root system. (2) Changing rhizosphere environments, especially for root length, root tips, pH, and available potassium contributed to dissimilarity of bacterial communities and enriched plant growth-promoting species. (3) Functions associated with stress tolerance, including signal transduction and biosynthesis of other secondary metabolites were increased significantly in intermittent deep tillage treatments. Moreover, IDT-30 only increased soil characters and root system architecture traits compared with CK, but deeper tillage could also change rhizosphere bacterial communities and functional profiles. Plant height and stem girth in IDT-40 and IDT-50 were higher compared with IDT-30, and infection rates of black shank and black root rot in IDT-50 were even lower in IDT-40. The study provided a comprehensive explanation into the effects of intermittent deep tillage in plant production and suggested an optimal depth.

4D Structural root architecture modeling from digital twins by X-Ray Computed Tomography.

BACKGROUND: Breakthrough imaging technologies may challenge the plant phenotyping bottleneck regarding marker-assisted breeding and genetic mapping. In this context, X-Ray CT (computed tomography) technology can accurately obtain the digital twin of root system architecture (RSA) but computational methods to quantify RSA traits and analyze their changes over time are limited. RSA traits extremely affect agricultural productivity. We develop a spatial-temporal root architectural modeling method based on 4D data from X-ray CT. This novel approach is optimized for high-throughput phenotyping considering the cost-effective time to process the data and the accuracy and robustness of the results. Significant root architectural traits, including root elongation rate, number, length, growth angle, height, diameter, branching map, and volume of axial and lateral roots are extracted from the model based on the digital twin. Our pipeline is divided into two major steps: (i) first, we compute the curve-skeleton based on a constrained Laplacian smoothing algorithm. This skeletal structure determines the registration of the roots over time; (ii) subsequently, the RSA is robustly modeled by a cylindrical fitting to spatially quantify several traits. The experiment was carried out at the Ag Alumni Seed Phenotyping Facility (AAPF) from Purdue University in West Lafayette (IN, USA). RESULTS: Roots from three samples of tomato plants at two different times and three samples of corn plants at three different times were scanned. Regarding the first step, the PCA analysis of the skeleton is able to accurately and robustly register temporal roots. From the second step, several traits were computed. Two of them were accurately validated using the root digital twin as a ground truth against the cylindrical model: number of branches (RRMSE better than 9%) and volume, reaching a coefficient of determination (R2) of 0.84 and a P < 0.001. CONCLUSIONS: The experimental results support the viability of the developed methodology, being able to provide scalability to a comprehensive analysis in order to perform high throughput root phenotyping.

A quick protocol for the identification and characterization of early growth mutants in tomato.

Root system architecture (RSA) manipulation may improve water and nutrient capture by plants under normal and extreme climate conditions. With the aim of initiating the genetic dissection of RSA in tomato, we established a defined ontology that allowed the curated annotation of the observed phenotypes on 12 traits at four consecutive growth stages. In addition, we established a quick approach for the molecular identification of the mutations associated with the trait-of-interest by using a whole-genome sequencing approach that does not require the building of an additional mapping population. As a proof-of-concept, we screened 4543 seedlings from 300 tomato M3 lines (Solanum lycopersicum L. cv. Micro-Tom) generated by chemical mutagenesis with ethyl methanesulfonate. We studied the growth and early development of both the root system (primary and lateral roots) and the aerial part of the seedlings as well as the wound-induced adventitious roots emerging from the hypocotyl. We identified 659 individuals (belonging to 203 M3 lines) whose early seedling and RSA phenotypes differed from those of their reference background. We confirmed the genetic segregation of the mutant phenotypes affecting primary root length, seedling viability and early RSA in 31 M4 families derived from 15 M3 lines selected in our screen. Finally, we identified a missense mutation in the SlCESA3 gene causing a seedling-lethal phenotype with short roots. Our results validated the experimental approach used for the identification of tomato mutants during early growth, which will allow the molecular identification of the genes involved.

Pseudomonas PS01 Isolated from Maize Rhizosphere Alters Root System Architecture and Promotes Plant Growth.

The objectives of this study were to evaluate the plant growth promoting effects on Arabidopsis by Pseudomonas sp. strains associated with rhizosphere of crop plants grown in Mekong Delta, Vietnam. Out of all the screened isolates, Pseudomonas PS01 isolated from maize rhizosphere showed the most prominent plant growth promoting effects on Arabidopsis and maize (Zea mays). We also found that PS01 altered root system architecture (RSA). The full genome of PS01 was resolved using high-throughput sequencing. Phylogenetic analysis identified PS01 as a member of the Pseudomonas putida subclade, which is closely related to Pseudomonas taiwanensis.. PS01 genome size is 5.3 Mb, assembled in 71 scaffolds comprising of 4820 putative coding sequence. PS01 encodes genes for the indole-3-acetic acid (IAA), acetoin and 2,3-butanediol biosynthesis pathways. PS01 promoted the growth of Arabidopsis and altered the root system architecture by inhibiting primary root elongation and promoting lateral root and root hair formation. By employing gene expression analysis, genetic screening and pharmacological approaches, we suggested that the plant-growth promoting effects of PS01 and the alteration of RSA might be independent of bacterial auxin and could be caused by a combination of different diffusible compounds and volatile organic compounds (VOCs). Taken together, our results suggest that PS01 is a potential candidate to be used as bio-fertilizer agent for enhancing plant growth.

Root Branching and Nutrient Efficiency: Status and Way Forward in Root and Tuber Crops.

Plants are immobile organisms that require roots to efficiently and cost-effectively exploit their habitat for water and nutrients. Plant root systems are dynamic structures capable of altering root branching, root angle, and root growth rates determining overall architecture. This plasticity involves belowground plant-root mediated synergies coupled through a continuum of environmental interactions and endogenous developmental processes facilitating plants to adapt to favorable or adverse soil conditions. Plant root branching is paramount to ensure adequate access to soil water and nutrients. Although substantial resources have been devoted toward this goal, significant knowledge gaps exist. In well-studied systems such as rice and maize, it has become evident that root branching plays a significant role in the acquisition of nutrients and other soil-based resources. In these crop species, specific root branching traits that confer enhanced nutrient acquisition are well-characterized and are already being incorporated into breeding populations. In contrast, the understanding of root branching in root and tuber crop productivity has lagged behind. In this review article, we highlight what is known about root branching in root and tuber crops (RTCs) and mark new research directions, such as the use novel phenotyping methods, examining the changes in root morphology and anatomy under nutrient stress, and germplasm screening with enhanced root architecture for more efficient nutrient capture. These directions will permit a better understanding of the interaction between root branching and nutrient acquisition in these globally important crop species.

Arabidopsis: An Adequate Model for Dicot Root Systems?

The Arabidopsis root system is frequently considered to have only three classes of root: primary, lateral, and adventitious. Research with other plant species has suggested up to eight different developmental/functional classes of root for a given plant root system. If Arabidopsis has only three classes of root, it may not be an adequate model for eudicot plant root systems. Recent research, however, can be interpreted to suggest that pre-flowering Arabidopsis does have at least five (5) of these classes of root. This then suggests that Arabidopsis root research can be considered an adequate model for dicot plant root systems.

Root System Architecture and Abiotic Stress Tolerance: Current Knowledge in Root and Tuber Crops.

The challenge to produce more food for a rising global population on diminishing agricultural land is complicated by the effects of climate change on agricultural productivity. Although great progress has been made in crop improvement, so far most efforts have targeted above-ground traits. Roots are essential for plant adaptation and productivity, but are less studied due to the difficulty of observing them during the plant life cycle. Root system architecture (RSA), made up of structural features like root length, spread, number, and length of lateral roots, among others, exhibits great plasticity in response to environmental changes, and could be critical to developing crops with more efficient roots. Much of the research on root traits has thus far focused on the most common cereal crops and model plants. As cereal yields have reached their yield potential in some regions, understanding their root system may help overcome these plateaus. However, root and tuber crops (RTCs) such as potato, sweetpotato, cassava, and yam may hold more potential for providing food security in the future, and knowledge of their root system additionally focuses directly on the edible portion. Root-trait modeling for multiple stress scenarios, together with high-throughput phenotyping and genotyping techniques, robust databases, and data analytical pipelines, may provide a valuable base for a truly inclusive 'green revolution.' In the current review, we discuss RSA with special reference to RTCs, and how knowledge on genetics of RSA can be manipulated to improve their tolerance to abiotic stresses.

Roots Withstanding their Environment: Exploiting Root System Architecture Responses to Abiotic Stress to Improve Crop Tolerance.

To face future challenges in crop production dictated by global climate changes, breeders and plant researchers collaborate to develop productive crops that are able to withstand a wide range of biotic and abiotic stresses. However, crop selection is often focused on shoot performance alone, as observation of root properties is more complex and asks for artificial and extensive phenotyping platforms. In addition, most root research focuses on development, while a direct link to the functionality of plasticity in root development for tolerance is often lacking. In this paper we review the currently known root system architecture (RSA) responses in Arabidopsis and a number of crop species to a range of abiotic stresses, including nutrient limitation, drought, salinity, flooding, and extreme temperatures. For each of these stresses, the key molecular and cellular mechanisms underlying the RSA response are highlighted. To explore the relevance for crop selection, we especially review and discuss studies linking root architectural responses to stress tolerance. This will provide a first step toward understanding the relevance of adaptive root development for a plant's response to its environment. We suggest that functional evidence on the role of root plasticity will support breeders in their efforts to include root properties in their current selection pipeline for abiotic stress tolerance, aimed to improve the robustness of crops.