Rice Root System Architecture Research Articles

Genetic mapping of regions associated with root system architecture in rice using MutMap QTL-seq

The root system architecture is an important complex trait in rice. With changing climatic conditions and soil nutrient deficiencies, there is an immediate need to breed nutrient-use-efficient rice varieties with robust root system architectural (RSA) traits. To map the genomic regions associated with crucial component traits of RSA viz. root length and root volume, a biparental F2 mapping population was developed using TI-128, an Ethyl Methane Sulphonate (EMS) mutant of a mega variety BPT-5204 having high root length (RL) and root volume (RV) with wild type BPT-5204. Extreme bulks having high RL and RV and low RL and RV were the whole genome re-sequenced along with parents. Genetic mapping using the MutMap QTL-Seq approach elucidated two genomic intervals on Chr.12 (3.14–3.74 Mb, 18.11–20.85 Mb), and on Chr.2 (23.18–23.68 Mb) as potential regions associated with both RL and RV. The Kompetitive Allele Specific PCR (KASP) assays for SNPs with delta SNP index near 1 were associated with higher RL and RV in the panel of sixty-two genotypes varying in root length and volume. The KASP_SNPs viz. Chr12_S4 (C→T; Chr12:3243938), located in the 3’ UTR region of LOC_Os12g06670 encoding a protein kinase domain-containing protein and Chr2_S6 (C→T; Chr2:23181622) present upstream in the regulator of chromosomal condensation protein LOC_Os2g38350. Validation of these genes using qRT-PCR and in-silico studies using various online tools and databases revealed higher expression in TI-128 as compared to BPT- 5204 at the seedling and panicle initiation stages implying the functional role in enhancing RL and RV.

Regulation and Expression of Phytohormones for Root Architectural Trait Development in Rice: A Review

The root system architecture (RSA) in monocotyledonous plants like rice is consists of primary roots, lateral roots, seminal/crown roots, and root hairs. The soil nutrients also influence many physiological processes via various root parameters like root length, root diameter and root angle for growth and development. The variation in root system architecture in rice is influenced by the intrinsic factors (phytohormones, transcription factors) and extrinsic factors (light, temperature and moisture) and their collective effect. The phytohormones such as; auxin, cytokinin, abscisic acid and ethylene, and their mutual effects play vital role for root architectural trait development. Many genes/QTLs were identified in rice which are strong role player for root development. But the biochemical signaling pathways are not completely understood. The modern molecular tools like genome editing, sequencing and multi-omics (transcriptomics and proteomics) approaches and multi-disciplinary system biology studies can provide a better solution for this issue. To improve the sustainable food grain production under extreme environment, it is important to understand the physiological and biochemical mechanism of root development. Moreover, it is imperative to establish a resilient root system in rice cultivation in order to mitigate the overuse of chemical fertilizers, enhance nutrient efficiency, and improve climate resilience of the plant.

Deep placement of fertilizer enhances mineral uptake through changes in the root system architecture in rice

Deep placement of fertilizer enhances mineral uptake through changes in the root system architecture in rice

Root system architecture in rice: impacts of genes, phytohormones and root microbiota.

To feed the continuously expanding world's population, new crop varieties have been generated, which significantly contribute to the world's food security. However, the growth of these improved plant varieties relies primarily on synthetic fertilizers, which negatively affect the environment and human health; therefore, continuous improvement is needed for sustainable agriculture. Several plants, including cereal crops, have the adaptive capability to combat adverse environmental changes by altering physiological and molecular mechanisms and modifying their root system to improve nutrient uptake efficiency. These plants operate distinct pathways at various developmental stages to optimally establish their root system. These processes include changes in the expression profile of genes, changes in phytohormone level, and microbiome-induced root system architecture (RSA) modification. Several studies have been performed to understand microbial colonization and their involvement in RSA improvement through changes in phytohormone and transcriptomic levels. This review highlights the impact of genes, phytohormones, and particularly root microbiota in influencing RSA and provides new insights resulting from recent studies on rice root as a model system and summarizes the current knowledge about biochemical and central molecular mechanisms.

Pinpointing genomic regions associated with root system architecture in rice through an integrative meta-analysis approach.

Applying an integrated meta-analysis approach led to identification of meta-QTLs/ candidate genes associated with rice root system architecture, which can be used in MQTL-assisted breeding/ genetic engineering of root traits. Root system architecture (RSA) is an important factor for facilitating water and nutrient uptake from deep soils and adaptation to drought stress conditions. In the present research, an integrated meta-analysis approach was employed to find candidate genes and genomic regions involved in rice RSA traits. A whole-genome meta-analysis was performed for 425 initial QTLs reported in 34 independent experiments controlling RSA traits under control and drought stress conditions in the previous twenty years. Sixty-four consensus meta-QTLs (MQTLs) were detected, unevenly distributed on twelve rice chromosomes. The confidence interval (CI) of the identified MQTLs was obtained as 0.11-14.23cM with an average of 3.79cM, which was 3.88 times narrower than the mean CI of the original QTLs. Interestingly, 52 MQTLs were co-located with SNP peak positions reported in rice genome-wide association studies (GWAS) for root morphological traits. The genes located in these RSA-related MQTLs were detected and explored to find the drought-responsive genes in the rice root based on the RNA-seq and microarray data. Multiple RSA and drought tolerance-associated genes were found in the MQTLs including the genes involved in auxin biosynthesis or signaling (e.g. YUCCA, WOX, AUX/IAA, ARF), root angle (DRO1-related genes), lateral root development (e.g. DSR, WRKY), root diameter (e.g. OsNAC5), plant cell wall (e.g. EXPA), and lignification (e.g. C4H, PAL, PRX and CAD). The genes located within both the SNP peak positions and the QTL-overview peaks for RSA are suggested as novel candidate genes for further functional analysis. The promising candidate genes and MQTLs can be used as basis for genetic engineering and MQTL-assisted breeding of root phenotypes to improve yield potential, stability and performance in a water-stressed environment.

The WUSCHEL-related homeobox transcription factor OsWOX4 controls the primary root elongation by activating OsAUX1 in rice

Primary root is the basic component of root system and plays a key role in early seedling growth and survival in rice. However, the molecular mechanism of primary root elongation still needs to be well understood. Here, we showed that OsWOX4, a WUSCHEL-related homeobox (WOX) transcription factor, was involved in the primary root elongation in rice. Silencing of OsWOX4 by RNA interference (RNAi) greatly increased the primary root length, whereas its overexpression reduced primary root elongation significantly. Moreover, the size of meristem zone and epidermal cell length of mature zone in RNAi root tips were drastically enhanced, while they were reduced markedly in overexpression lines, in comparison with that of wild type. Further analysis showed that the accumulation of free IAA was slightly increased in RNAi roots, but drastically reduced in plants overexpressing OsWOX4. The expression of genes responsible for auxin biosynthesis and transport was also changed in OsWOX4 transgenic lines. Transient transcriptional activation and electrophoretic mobility shift assays showed that OsWOX4 directly regulated the transcription of OsAUX1 through binding to its promoter region. Collectively, our results indicated that OsWOX4 played a crucial role in the primary root elongation by regulating auxin transport, suggesting its importance in rice root system architecture.

High-throughput three-dimensional visualization of root system architecture of rice using X-ray computed tomography

BackgroundX-ray computed tomography (CT) allows us to visualize root system architecture (RSA) beneath the soil, non-destructively and in a three-dimensional (3-D) form. However, CT scanning, reconstruction processes, and root isolation from X-ray CT volumes, take considerable time. For genetic analyses, such as quantitative trait locus mapping, which require a large population size, a high-throughput RSA visualization method is required.ResultsWe have developed a high-throughput process flow for the 3-D visualization of rice (Oryza sativa) RSA (consisting of radicle and crown roots), using X-ray CT. The process flow includes use of a uniform particle size, calcined clay to reduce the possibility of visualizing non-root segments, use of a higher tube voltage and current in the X-ray CT scanning to increase root-to-soil contrast, and use of a 3-D median filter and edge detection algorithm to isolate root segments. Using high-performance computing technology, this analysis flow requires only 10 min (33 s, if a rough image is acceptable) for CT scanning and reconstruction, and 2 min for image processing, to visualize rice RSA. This reduced time allowed us to conduct the genetic analysis associated with 3-D RSA phenotyping. In 2-week-old seedlings, 85% and 100% of radicle and crown roots were detected, when 16 cm and 20 cm diameter pots were used, respectively. The X-ray dose per scan was estimated at < 0.09 Gy, which did not impede rice growth. Using the developed process flow, we were able to follow daily RSA development, i.e., 4-D RSA development, of an upland rice variety, over 3 weeks.ConclusionsWe developed a high-throughput process flow for 3-D rice RSA visualization by X-ray CT. The X-ray dose assay on plant growth has shown that this methodology could be applicable for 4-D RSA phenotyping. We named the RSA visualization method ‘RSAvis3D’ and are confident that it represents a potentially efficient application for 3-D RSA phenotyping of various plant species.

Control of root system architecture by phytohormones and environmental signals in rice

Drought and flooding are environmental extremes and major threats to crop production. Water uptake is achieved by plant roots which have to explore new soil spaces to alleviate water deficit during drought or to cope with water excess during flooding. Adaptation of the root system architecture helps plants cope with such extreme conditions and is crucial for plant health and survival. While for dicot plants the well studied model plant Arabidopsis thaliana has provided insight into the genetic and molecular regulation of the root system, less information is available for monocot species, which include the agronomically important cereal crops. Rice (Oryza sativa L.) is a semi-aquatic monocot plant that develops strong tolerance to flooding. Flooding tolerance of rice is closely linked to its adaptive root system. The functional root system of rice is mainly composed of crown roots and is shifted to nodal adventitious roots during flooding which allows rice to maintain oxygen supply to the roots and to survive longer periods of partial submergence as compared with other crops. Likewise, a number of drought-tolerance traits of rice are the result of an altered root system architecture. Hence, the structure of the root system adapts to, both, flooding and drought. Understanding the regulatory mechanisms that control root system adaptation to extreme environments is a key task for scientists to accelerate the breeding efforts for stress-tolerant crops. This review summarizes recently identified genes and molecular mechanisms that regulate root system architecture in rice in response to drought and flooding.

Selenium downregulates auxin and ethylene biosynthesis in rice seedlings to modify primary metabolism and root architecture.

Selenium modulates the formation of primary and lateral roots through alterations in auxin and ethylene, leading to new patterns of root architecture in rice seedlings. Selenium (Se) at low concentrations can control root growth through interaction with hormone biosynthesis. Auxin and ethylene have been shown to control the root architecture, with most of the information obtained from the eudicots such Arabidopsis and Nicotiana tabacum. Here, we presented the effects of Se on auxin and ethylene pathways and examined their impact on primary metabolism and root system architecture in rice (Oryza sativa L.) seedlings. Se treatment increased elongation of primary root, but decreased the number and length of lateral roots. Se led to decreased expression of genes associated with the biosynthesis of auxin and ethylene, concomitantly with reduced production of these hormones by the roots. Moreover, Se decreased the abundance of transcripts encoding auxin transport proteins. Indole-3-acetic acid (IAA) treatment overrode the repressive effect of Se on lateral root growth. The ethylene synthesis inhibitor L-α-(2-aminoethoxyvinyl)-glycine (AVG) increased elongation of primary root, whereas the ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC) resulted in the opposite effect. Soluble sugars accumulate in roots of rice seedlings under Se treatment. Thus, Se modulates the formation of primary and lateral roots through alterations in auxin and ethylene, leading to new patterns of root architecture in rice seedlings.

A Digitization and Visualization Procedure for 3D Wheat Root System Architecture in Rice–Wheat Rotation

A method consisting of soil core with undisturbed sample of root architecture, digitizer and commercial software was developed to visualize wheat root system architecture (RSA) in a field experiment. At first, root-zone soil was excavated and wheat RSA was digitized in every 5-mm-thick soil layers. By then, the 3D root morphological data were re-integrated by Pro-E software, where 3D models of wheat RSAs could be reconstructed, scaled and calculated. Results revealed markedly distorted morphological structures of wheat axial roots in both curvature and helical morphology. Scaled RSA models also revealed severe restrictions on overall RSAs, illustrating the intense constraint of root topology by the heterogeneous environment. Time-series presentation of RSAs clearly displayed the fine structural details of root morphological dynamics, indicating that a high accuracy of data had been achieved for field crop physiology. Laminated digitization combined with Pro-E modelling was featured as a deterministic, data-driven and model-assisted procedure, which was particularly suitable for crop RSAs in field. Wheat RSA dynamics and temporal variations of 3D root topology illustration could be realized by undisturbed sampling, digitizing and modelling method for field-state crops with fine and fibrous root systems. It had potential to provide a means of illustrating the influence of anisotropy of the soil environment.

Fine Mapping of QUICK ROOTING 1 and 2, Quantitative Trait Loci Increasing Root Length in Rice.

The volume that the root system can occupy is associated with the efficiency of water and nutrient uptake from soil. Genetic improvement of root length, which is a limiting factor for root distribution, is necessary for increasing crop production. In this report, we describe identification of two quantitative trait loci (QTLs) for maximal root length, QUICK ROOTING 1 (QRO1) on chromosome 2 and QRO2 on chromosome 6, in cultivated rice (Oryza sativa L.). We measured the maximal root length in 26 lines carrying chromosome segments from the long-rooted upland rice cultivar Kinandang Patong in the genetic background of the short-rooted lowland cultivar IR64. Five lines had longer roots than IR64. By rough mapping of the target regions in BC4F2 populations, we detected putative QTLs for maximal root length on chromosomes 2, 6, and 8. To fine-map these QTLs, we used BC4F3 recombinant homozygous lines. QRO1 was mapped between markers RM5651 and RM6107, which delimit a 1.7-Mb interval on chromosome 2, and QRO2 was mapped between markers RM20495 and RM3430-1, which delimit an 884-kb interval on chromosome 6. Both QTLs may be promising gene resources for improving root system architecture in rice.

LARGE ROOT ANGLE1, encoding OsPIN2, is involved in root system architecture in rice.

Root system architecture is very important for plant growth and crop yield. It is essential for nutrient and water uptake, anchoring, and mechanical support. Root growth angle (RGA) is a vital constituent of root system architecture and is used as a parameter for variety evaluation in plant breeding. However, little is known about the underlying molecular mechanisms that determine root growth angle in rice (Oryza sativa). In this study, a rice mutant large root angle1 (lra1) was isolated and shown to exhibit a large RGA and reduced sensitivity to gravity. Genome resequencing and complementation assays identified OsPIN2 as the gene responsible for the mutant phenotypes. OsPIN2 was mainly expressed in roots and the base of shoots, and showed polar localization in the plasma membrane of root epidermal and cortex cells. OsPIN2 was shown to play an important role in mediating root gravitropic responses in rice and was essential for plants to produce normal RGAs. Taken together, our findings suggest that OsPIN2 plays an important role in root gravitropic responses and determining the root system architecture in rice by affecting polar auxin transport in the root tip.

OsEXPB2, a β-expansin gene, is involved in rice root system architecture

Expansins are cell wall loosening proteins which generally play important roles as endogenous regulators in plants. Here we report a rice (Oryza sativa L.) β-expansin gene, OsEXPB2, which encodes a 28.6-kDa protein of 261 amino acids. Sequence alignment revealed that the N-terminal and C-terminal of OsEXPB2 share six discontinuous cysteine residues and four intermittent tryptophan residues, respectively. The OsEXPB2 promoter contains conserved root hair-specific elements. Subcellular localization assay revealed that OsEXPB2 was localized in the cell wall. Analysis of spatial and temporal expression patterns demonstrated that OsEXPB2 was predominantly expressed in root of rice. OsEXPB2 expression levels were up-regulated by abiotic stresses, such as phosphate or iron deficiency, and also suppressed by abscisic acid. A clear difference was observed between RNA interference (RNAi) lines and wild-type in root system architecture and plant height, and the suppression of OsEXPB2 resulted in a visible alteration of the width of the leaf blade. Anatomical analysis found that the cell size of root cortical cells in OsEXPB2-suppressed lines was significantly smaller than that of their counterparts in wild-type plants. Furthermore, cryo-scanning electron microscopy analysis showed that the development of root hair was suppressed in RNAi lines. All these results suggest that OsEXPB2 is a root-predominant gene with a key role in root-hair formation and has the potential to be utilized in transgenic root breeding to improve abiotic stress tolerance.

Imaging and Analysis Platform for Automatic Phenotyping and Trait Ranking of Plant Root Systems

The ability to nondestructively image and automatically phenotype complex root systems, like those of rice (Oryza sativa), is fundamental to identifying genes underlying root system architecture (RSA). Although root systems are central to plant fitness, identifying genes responsible for RSA remains an underexplored opportunity for crop improvement. Here we describe a nondestructive imaging and analysis system for automated phenotyping and trait ranking of RSA. Using this system, we image rice roots from 12 genotypes. We automatically estimate RSA traits previously identified as important to plant function. In addition, we expand the suite of features examined for RSA to include traits that more comprehensively describe monocot RSA but that are difficult to measure with traditional methods. Using 16 automatically acquired phenotypic traits for 2,297 images from 118 individuals, we observe (1) wide variation in phenotypes among the genotypes surveyed; and (2) greater intergenotype variance of RSA features than variance within a genotype. RSA trait values are integrated into a computational pipeline that utilizes supervised learning methods to determine which traits best separate two genotypes, and then ranks the traits according to their contribution to each pairwise comparison. This trait-ranking step identifies candidate traits for subsequent quantitative trait loci analysis and demonstrates that depth and average radius are key contributors to differences in rice RSA within our set of genotypes. Our results suggest a strong genetic component underlying rice RSA. This work enables the automatic phenotyping of RSA of individuals within mapping populations, providing an integrative framework for quantitative trait loci analysis of RSA.