Detection of quantitative trait loci for rice root systems grown in paddies based on nondestructive phenotyping using X-ray computed tomography.

Plant roots are essential for water and nutrient uptake, as well as resistance to abiotic stresses. While measuring root systems under field conditions is labor-intensive, most quantitative trait loci (QTLs) related to root traits have been detected under artificial conditions. However, QTLs identified under artificial conditions may not always manifest the expected effects that are observed under field conditions.

Hydroponic Culture of Rice Seedlings for Stress Response Assay.

The major environmental factors limiting rice growth and production are osmotic stresses such as drought and high salinity. High osmotic stresses directly disrupt cellular activities, leading to plant growth retardation or death. Plants have various response mechanisms to survive under such stresses.

Transcriptome-based prediction for polygenic traits in rice using different gene subsets.

Background: Transcriptome-based prediction of complex phenotypes is a relatively new statistical method that links genetic variation to phenotypic variation. The selection of large-effect genes based on a priori biological knowledge is beneficial for predicting oligogenic traits; however, such a simple gene selection method is not applicable to polygenic traits because causal genes or large-effect loci are often unknown. Here, we used several gene-level features and tested whether it was possible to select a gene subset that resulted in better predictive ability than using all genes for predicting a polygenic trait.

Convolutional neural networks combined with conventional filtering to semantically segment plant roots in rapidly scanned X-ray computed tomography volumes with high noise levels.

Background: X-ray computed tomography (CT) is a powerful tool for measuring plant root growth in soil. However, a rapid scan with larger pots, which is required for throughput-prioritized crop breeding, results in high noise levels, low resolution, and blurred root segments in the CT volumes. Moreover, while plant root segmentation is essential for root quantification, detailed conditional studies on segmenting noisy root segments are scarce.

Non-destructive real-time monitoring of underground root development with distributed fiber optic sensing.

Crop genetic engineering for better root systems can offer practical solutions for food security and carbon sequestration; however, soil layers prevent the direct visualization of plant roots, thus posing a challenge to effective phenotyping. Here, we demonstrate an original device with a distributed fiber-optic sensor for fully automated, real-time monitoring of underground root development. We show that spatially encoding an optical fiber with a flexible and durable polymer film in a spiral pattern can significantly enhance sensor detection.

Genome- and Transcriptome-wide Association Studies to Discover Candidate Genes for Diverse Root Phenotypes in Cultivated Rice.

Root system architecture plays a crucial role in nutrient and water absorption during rice production. Genetic improvement of the rice root system requires elucidating its genetic control. Genome-wide association studies (GWASs) have identified genomic regions responsible for rice root phenotypes.

Life-Cycle Multiomics of Rice Shoots Reveals Growth Stage-Specific Effects of Drought Stress and Time-Lag Drought Responses.

Field-grown rice plants are exposed to various stresses at different stages of their life cycle, but little is known about the effects of stage-specific stresses on phenomes and transcriptomes. In this study, we performed integrated time-course multiomics on rice at 3-d intervals from seedling to heading stage under six drought conditions in a well-controlled growth chamber. Drought stress at seedling and reproductive stages reduced yield performance by reducing seed number and setting rate, respectively.

Development of 12 sets of chromosome segment substitution lines that enhance allele mining in Asian cultivated rice.

Many agronomic traits that are important in rice breeding are controlled by multiple genes. The extensive time and effort devoted so far to identifying and selecting such genes are still not enough to target multiple agronomic traits in practical breeding in Japan because of a lack of suitable plant materials in which to efficiently detect and validate beneficial alleles from diverse genetic resources. To facilitate the comprehensive analysis of genetic variation in agronomic traits among Asian cultivated rice, we developed 12 sets of chromosome segment substitution lines (CSSLs) with the background, 11 of them in the same genetic background, using donors representing the genetic diversity of Asian cultivated rice.

Transcriptome profiles of rice roots under simulated microgravity conditions and following gravistimulation.

Root system architecture affects the efficient uptake of water and nutrients in plants. The root growth angle, which is a critical component in determining root system architecture, is affected by root gravitropism; however, the mechanism of root gravitropism in rice remains largely unknown. In this study, we conducted a time-course transcriptome analysis of rice roots under conditions of simulated microgravity using a three-dimensional clinostat and following gravistimulation to detect candidate genes associated with the gravitropic response.

Constitutively active B2 Raf-like kinases are required for drought-responsive gene expression upstream of ABA-activated SnRK2 kinases.

Osmotic stresses, such as drought and high salinity, adversely affect plant growth and productivity. The phytohormone abscisic acid (ABA) accumulates in response to osmotic stress and enhances stress tolerance in plants by triggering multiple physiological responses through ABA signaling. Subclass III SNF1-related protein kinases 2 (SnRK2s) are key regulators of ABA signaling.

MORE PANICLES 3, a natural allele of OsTB1/FC1, impacts rice yield in paddy fields at elevated CO levels.

Improving crop yield potential through an enhanced response to rising atmospheric CO levels is an effective strategy for sustainable crop production in the face of climate change. Large-sized panicles (containing many spikelets per panicle) have been a recent ideal plant architecture (IPA) for high-yield rice breeding. However, few breeding programs have proposed an IPA under the projected climate change.

Four-dimensional measurement of root system development using time-series three-dimensional volumetric data analysis by backward prediction.

Background: Root system architecture (RSA) is an essential characteristic for efficient water and nutrient absorption in terrestrial plants; its plasticity enables plants to respond to different soil environments. Better understanding of root plasticity is important in developing stress-tolerant crops. Non-invasive techniques that can measure roots in soils nondestructively, such as X-ray computed tomography (CT), are useful to evaluate RSA plasticity.

Identification of a unique allele in the quantitative trait locus for crown root number in rice from Japan using genome-wide association studies.

To explore the genetic resources that could be utilized to help improve root system architecture phenotypes in rice (), we have conducted genome-wide association studies to investigate maximum root length and crown root number in 135 10-day-old Japanese rice accessions grown hydroponically. We identified a quantitative trait locus for crown root number at approximately 32.7 Mbp on chromosome 4 and designated it ().

Improving the efficiency of plant root system phenotyping through digitization and automation.

Root system architecture (RSA) determines unevenly distributed water and nutrient availability in soil. Genetic improvement of RSA, therefore, is related to crop production. However, RSA phenotyping has been carried out less frequently than above-ground phenotyping because measuring roots in the soil is difficult and labor intensive.

Quantification of Soil-surface Roots in Seedlings and Mature Rice Plants.

Soil-surface roots (SORs) in rice are primary roots that elongate over or near the soil surface. SORs help avoid excessive reduction of stress that occurs in paddy, such as in saline conditions. SORs may also be beneficial for rice growth in phosphorus-deficient paddy fields.

RSAtrace3D: robust vectorization software for measuring monocot root system architecture.

Background: The 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.

iPOTs: Internet of Things-based pot system controlling optional treatment of soil water condition for plant phenotyping under drought stress.

A cultivation facility that can assist users in controlling the soil water condition is needed for accurately phenotyping plants under drought stress in an artificial environment. Here we report the Internet of Things-based pot system controlling optional treatment of soil water condition (iPOTs), an automatic irrigation system that mimics the drought condition in a growth chamber. The Wi-Fi-enabled iPOTs system allows water supply from the bottom of the pot, based on the soil water level set by the user, and automatically controls the soil water level at a desired depth.

Synergy between a shallow root system with a DRO1 homologue and localized P application improves P uptake of lowland rice.

Improved phosphorus (P) use efficiency for crop production is needed, given the depletion of phosphorus ore deposits, and increasing ecological concerns about its excessive use. Root system architecture (RSA) is important in efficiently capturing immobile P in soils, while agronomically, localized P application near the roots is a potential approach to address this issue. However, the interaction between genetic traits of RSA and localized P application has been little understood.

Challenges to design-oriented breeding of root system architecture adapted to climate change.

Roots are essential organs for capturing water and nutrients from the soil. In particular, root system architecture (RSA) determines the extent of the region of the soil where water and nutrients can be gathered. As global climate change accelerates, it will be important to improve belowground plant parts, as well as aboveground ones, because roots are front-line organs in the response to abiotic stresses such as drought, flooding, and salinity stress.

The transcriptomic landscapes of rice cultivars with diverse root system architectures grown in upland field conditions.

Root system architecture affects plant drought resistance and other key agronomic traits such as lodging. However, although phenotypic and genomic variation has been extensively analyzed, few field studies have integrated phenotypic and transcriptomic information, particularly for below-ground traits such as root system architecture. Here, we report the phenotypic and transcriptomic landscape of 61 rice (Oryza sativa) accessions with highly diverse below-ground traits grown in an upland field.

Root angle modifications by the homolog improve rice yields in saline paddy fields.

The root system architecture (RSA) of crops can affect their production, particularly in abiotic stress conditions, such as with drought, waterlogging, and salinity. Salinity is a growing problem worldwide that negatively impacts on crop productivity, and it is believed that yields could be improved if RSAs that enabled plants to avoid saline conditions were identified. Here, we have demonstrated, through the cloning and characterization of (), that a shallower root growth angle (RGA) could enhance rice yields in saline paddies.