Genetic Signature Controlling Root System Architecture in Diverse Spring Wheat Germplasm.

BackgroundThe root distribution in the soil is one of the elements that comprise the root system architecture (RSA). In monocots, RSA comprises radicle and crown roots, each of which can be basically represented by a single curve with lateral root branches or approximated using a polyline. Moreover, RSA vectorization (polyline conversion) is useful for RSA phenotyping. However, a robust software that can enable RSA vectorization while using noisy three-dimensional (3D) volumes is unavailable.ResultsWe developed RSAtrace3D, which is a robust 3D RSA vectorization software for monocot RSA phenotyping. It manages the single root (radicle or crown root) as a polyline (a vector), and the set of the polylines represents the entire RSA. RSAtrace3D vectorizes root segments between the two ends of a single root. By utilizing several base points on the root, RSAtrace3D suits noisy images if it is difficult to vectorize it using only two end nodes of the root. Additionally, by employing a simple tracking algorithm that uses the center of gravity (COG) of the root voxels to determine the tracking direction, RSAtrace3D efficiently vectorizes the roots. Thus, RSAtrace3D represents the single root shape more precisely than straight lines or spline curves. As a case study, rice (Oryza sativa) RSA was vectorized from X-ray computed tomography (CT) images, and RSA traits were calculated. In addition, varietal differences in RSA traits were observed. The vector data were 32,000 times more compact than raw X-ray CT images. Therefore, this makes it easier to share data and perform re-analyses. For example, using data from previously conducted studies. For monocot plants, the vectorization and phenotyping algorithm are extendable and suitable for numerous applications.ConclusionsRSAtrace3D is an RSA vectorization software for 3D RSA phenotyping for monocots. Owing to the high expandability of the RSA vectorization and phenotyping algorithm, RSAtrace3D can be applied not only to rice in X-ray CT images but also to other monocots in various 3D images. Since this software is written in Python language, it can be easily modified and will be extensively applied by researchers in this field.

Characterising shoot and root system trait variability and contribution to genotypic variability in juvenile cassava (Manihot esculenta Crantz) plants

The root system architecture (RSA) determines plant growth and yield. The characterization of optimal RSA and discovery of genetic loci or candidate genes that control root traits are therefore important research goals. However, the hidden nature of the root system makes it difficult to perform nondestructive, rapid analyses of RSA. In this study, we developed an automated, nondestructive, high-throughput root phenotyping platform (Root-HTP) and a corresponding data processing pipeline for efficient, large-scale characterization of wheat (Triticum aestivum L.) RSA. This system is capable of tracking root growth dynamics and RSA variation across all wheat developmental stages. In situ phenotyping using Root-HTP extracted 47 RSA traits, including 33 novel traits in wheat and 23 novel traits in other crops. We used root trait data from the phenotyping system and yield trait data to conduct a genome-wide association study (GWAS) of 155 wheat accessions, which identified 2,650 SNPs and 233 quantitative trait loci (QTLs) associated with aspects of root architecture. The candidate gene TaMYB93 was detected in a QTL for root tortuosity, and EMS mutants confirmed its effect on RSA in wheat. We explored the relationship between root- and yield-related traits and identified 20 root-related QTLs that were also associated with yield traits. Furthermore, we have built a predictive model for wheat yield based on 18 RSA traits and propose a parsimonious RSA ideotype associated with high yields. The data generated from this study provide insight into the genetic architecture of wheat RSA and support for RSA ideotype-based wheat breeding and yield prediction.

In the emerging new agricultural context, a drastic reduction in fertilizer usage is required. A promising way to maintain high crop yields while reducing fertilizer inputs is to breed new varieties with optimized root system architecture (RSA), designed to reach soil resources more efficiently. This relies on identifying key traits that underlie genotypic variability and plasticity of RSA in response to nutrient availability. The aim of our study was to characterize the RSA plasticity in response to nitrogen limitation of a set of contrasted oilseed rape genotypes, by using the ArchiSimple model parameters as screening traits. Eight accessions of Brassica napus were grown in long tubes in the greenhouse, under two contrasting levels of nitrogen availability. After plant excavation, roots were scanned at high resolution. Six RSA traits relative to root diameter, elongation rate and branching were measured, as well as nine growth and biomass allocation traits. The plasticity of each trait to nitrogen availability was estimated. Nitrogen-limited plants were characterized by a strong reduction in total biomass and leaf area. Even if the architecture traits were shown to be less plastic than allocation traits, significant nitrogen and genotype effects were highlighted on each RSA trait, except the root minimal diameter. Thus, the RSA of nitrogen-limited plants was primarily characterised by a reduced lateral root density, a smaller primary root diameter, associated with a stronger root dominance. Among the RSA traits measured, the inter-branch distance showed the highest plasticity with a level of 70%, in the same range as the most plastic allocation traits. This work suggests that lateral root density plays the key role in the adaptation of the root system to nitrogen availability and highlights inter-branch distance as a major target trait for breeding new varieties, better adapted to low input systems.

AimsSelection for optimal root system architecture (RSA) is important to ensure genetic gains in the sustainable production of wheat (Triticum aestivum L.). Here we examine the hypothesis that past wheat breeding has led to changes in RSA and that future breeding efforts can focus directly on RSA to improve adaptation to target environments.MethodsWe conducted field trials using diverse wheat varieties, including modern and historic UK varieties and non-UK landraces, tested under contrasting tillage regimes (non-inversion tillage versus conventional ploughing) for two trial years or different seeding rates (standard versus high rate) for one trial year. We used field excavation, washing and measurement of root crowns (‘shovelomics’) to characterise RSA traits, including: numbers of seminal, crown and nodal roots per plant, and crown root growth angle.ResultsWe found differences among genotypes for all root traits. Modern varieties generally had fewer roots per plant than historic varieties. On average, there were fewer crown roots and root angles were wider under shallow non-inversion tillage compared with conventional ploughing. Crown root numbers per plant also tended to be smaller at a high seeding rate compared with the standard. There were significant genotype-by-year, genotype-by-tillage and genotype-by-seeding-rate interactions for many root traits.ConclusionsSmaller root systems are likely to be a result of past selection that facilitated historical yield increases by reducing below-ground competition within the crop. The effects of crop management practices on RSA depend on genotype, suggesting that future breeding could select for improved RSA traits in resource-efficient farming systems.

Understanding the root system architecture (RSA) is necessary for elucidation of plant growth patterns in response to environmental stimuli and hormonal signals. Ethylene, a gaseous phytohormone, modulates root developmental plasticity, including primary root elongation, lateral root formation, and root hair growth. We present a protocol for mapping ethylene-specific RSA traits in Arabidopsis thaliana using a hydroponic growth system. Arabidopsis seedlingsgrow on a polypropylene mesh supported by polycarbonate wedges in a magenta box-based setup. Wetreat seedlings with ethylene or its precursor, thenspread root system on agar plates with an art brush. High-resolution images are recorded and analyzed withfree ImageJ software. This protocol allows detailed RSA analysisunder controlled ethylene treatments and can be adapted for other plant species.

Influences of cerium oxide nanoparticles and salinity on common bean (Phaseolus vulgaris) growth, physiology, and root system architectural and anatomical traits

BackgroundPhosphorus (P) is an important in ensuring plant morphogenesis and grain quality, therefore an efficient root system is crucial for P-uptake. Identification of useful loci for root morphological and P uptake related traits at seedling stage is important for wheat breeding. The aims of this study were to evaluate phenotypic diversity of Yangmai 16/Zhongmai 895 derived doubled haploid (DH) population for root system architecture (RSA) and biomass related traits (BRT) in different P treatments at seedling stage using hydroponic culture, and to identify QTL using 660 K SNP array based high-density genetic map.ResultsAll traits showed significant variations among the DH lines with high heritabilities (0.76 to 0.91) and high correlations (r = 0.59 to 0.98) among all traits. Inclusive composite interval mapping (ICIM) identified 34 QTL with 4.64–20.41% of the phenotypic variances individually, and the log of odds (LOD) values ranging from 2.59 to 10.43. Seven QTL clusters (C1 to C7) were mapped on chromosomes 3DL, 4BS, 4DS, 6BL, 7AS, 7AL and 7BL, cluster C5 on chromosome 7AS (AX-109955164 - AX-109445593) with pleiotropic effect played key role in modulating root length (RL), root tips number (RTN) and root surface area (ROSA) under low P condition, with the favorable allele from Zhongmai 895.ConclusionsThis study carried out an imaging pipeline-based rapid phenotyping of RSA and BRT traits in hydroponic culture. It is an efficient approach for screening of large populations under different nutrient conditions. Four QTL on chromosomes 6BL (2) and 7AL (2) identified in low P treatment showed positive additive effects contributed by Zhongmai 895, indicating that Zhongmai 895 could be used as parent for P-deficient breeding. The most stable QTL QRRS.caas-4DS for ratio of root to shoot dry weight (RRS) harbored the stable genetic region with high phenotypic effect, and QTL clusters on 7A might be used for speedy selection of genotypes for P-uptake. SNPs closely linked to QTLs and clusters could be used to improve nutrient-use efficiency.

Lack of phosphorus (P) is a major environmental factor affecting rapeseed (Brassica napus. L) root growth and development. For breeding purposes, it is crucial to identify the molecular mechanisms of root system architecture (RSA) traits underlying low P tolerance in rapeseed. The natural variations in the glycine-rich protein gene, BnGRP1, were analyzed in the natural population of 400 rapeseed cultivars under low P stress through genome-wide association study (GWAS) and transcriptome analyses. Based on 11 SNP mutations in BnGRP1 sequence, ten types of haplotypes (Hap) were formed. Compared with the other types, the cultivar of BnGRP1Hap1 type in the panel demonstrated the longest root length and heaviest root weight. BnGRP1Hap1 overexpression in rapeseed depicted the ability to enhance its resistance in response to low P tolerance. CRISPR/Cas9-derived BnGRP1Hap4 knockout mutations in rapeseed can lead to sensitivity to low P stress. Furthermore, BnGRP1Hap1 influences the expression of phosphate transporter 1 (PHT1) genes associated with P absorption. Overall, the findings of this study highlight new mechanisms of GRP1 genes in enhancing low P tolerance in rapeseed.

Root system architecture (RSA) is important in optimizing the use of nitrogen. High-throughput phenotyping techniques may be used to study root system architecture traits under controlled environments. A root phenotyping platform, consisting of germination paper-based pouch and wick coupled with image analysis, was used to characterize root seedling traits in 30 landrace-derived bread wheat genotypes and the bread wheat parent Paragon under hydroponic high N (HN) and low N (LN) conditions. In addition, two glasshouse experiments under HN and LN conditions were carried out to measure whole plant performance including flag-leaf photosynthetic rate, N uptake and biomass per plant for 13 wheat genotypes of which eight were common with those in the root phenotyping hydroponic experiment. There were significant differences in RSA traits between genotypes for seminal root number per plant, lateral root number per plant, seminal root length per plant and seminal root angle, with transgressive segregation for landrace-derived lines above the elite parental cultivar Paragon under HN and LN conditions. In the glasshouse experiments, genetic variation in flag-leaf photosynthesis rate was found in landrace-derived genotypes in the range 25.9–33.3 µmol m−2 s−1 under HN and in N uptake in the ranges 0.37–0.48 g N plant−1and 0.21–0.30 g plant−1 under HN and LN conditions, respectively (P < 0.05), with transgressive segregation above Paragon. Plant Nitrogen Nutrition Index also showed transgressive segregation in the landrace-derived lines above Paragon under HN and LN conditions. Greater maximum root depth and more lateral roots per plant in the hydroponic screen were each correlated with increased biomass per plant under LN conditions. Results from this study demonstrated genetic variation for seedling RSA traits in landrace-derived lines above the elite parental cultivar Paragon, which potentially could be utilized to improve N-use efficiency in breeding programmes.

This work reports a rapid procedure of comparing root development among different genotypes of Brachypodium spp., using three plant growth supports: gel chamber, ‘Termita’ chamber and Whatman paper. Eight variables of the root system architecture (RSA) (number of seminal roots, number of lateral roots, total length of the roots, length of the primary root, mean diameter of the roots, mean diameter of the primary root, total surface area and total volume of the roots) were studied in seedling of four genotypes each of Brachypodium distachyon, B. stacei and B. hybridum. Correlations between pairs of growth supports in terms of the eight variables examined were highly significant. In all three supports, B. stacei showed the greatest root system development while B. distachyon showed the least; B. hybridum, an allotetraploid species derived from hybridization between B. distachyon and B. stacei, showed intermediate development. ANOVA and LSD tests showed that significant differences exist between the supports, species and genotypes with respect to all the variables analysed. A cluster analysis was conducted to determine if the RSA traits could be used to differentiate the species and genotypes of Brachypodium. This analysis allowed differentiated between the three species and twelve genotypes of Brachypodium spp., although a certain overlap between species was observed. The Whatman paper support was the easiest to use, and is recommended for the characterization of large collections of genotypes.

Chapter 3 - Molecular advances in plant root system architecture response and redesigning for improved performance under unfavorable environments

Roots anchor plants in soil, and the failure of anchorage (i.e. root lodging) is a major cause of crop yield loss. Anchorage is often assumed to be driven by root system architecture (RSA). We made use of a natural experiment to measure the overlap between the genetic regulation of RSA and anchorage. After one of the most devastating derechos ever recorded in August 2020, we phenotyped root lodging in a maize (Zea mays) diversity panel consisting of 369 genotypes grown in 6 environments affected by the derecho. Genome-wide and transcriptome-wide association studies identified 118 candidate genes associated with root lodging. Thirty-four percent (40/118) of these were homologs of genes from Arabidopsis (Arabidopsis thaliana) that affect traits such as root morphology and lignin content, expected to affect root lodging. Finally, gene ontology enrichment analysis of the candidate genes and their predicted interaction partners at the transcriptional and translational levels revealed the complex regulatory networks of physiological and biochemical pathways underlying root lodging in maize. Limited overlap between genes associated with lodging resistance and RSA in this diversity panel suggests that anchorage depends in part on factors other than the gross characteristics of RSA.

Cadmium (Cd) contamination in paddy fields affects human health because of the consumption of Cd-contaminated rice. In the current study, we demonstrated that variation in root system architecture (RSA) influenced Cd uptake by rice. Rice cultivars consisting of KDML105, Mali Dang, Pitsanulok2 and Niaw San-pah-tawng were assessed in hydroponics and mesocosms while KDML 105, Pitsanulok2, and RD53 were used in field experiments. In hydroponics, root number and root weight were positively correlated with Cd uptake. In mesocosms, we found that the effects of Cd on RSA depended on rice varieties. Among different rice varieties, Mali Dang consistently accumulated high concentration of Cd, while Niaw San-pah-tawng tended to accumulate much lower amount in its shoot in both hydroponics and mesocosms. Correlation analysis indicates that Cd concentrations in shoot was positively correlated with root weight (R2 = 0.95), crown root number (R2 = 0.74), and negatively correlated with root depth (R2 = 0.86). In the field, Cd is most abundant at a depth of 10–20 cm. and root distribution influenced Cd uptake as evidenced by high root Cd content in the RD53 variety. We propose that low crown root number and deep RSA could be promising traits for selection and breeding for low Cd uptake rice.

Genome-wide association studies of doubled haploid exotic introgression lines for root system architecture traits in maize (Zea mays L.)