Rising temperatures due to global warming can negatively impact rice grain quality and yield. This study investigates the effects of increased warmer night temperatures (WNT), a consequence of global warming, on the quality of rice kernel, particularly grain chalkiness. By integrating computational and experimental approaches, we used a rice grain metabolic network to discover the metabolic factors of chalkiness. For this, we reconstructed the rice grain genome-scale metabolic model (GSM), iOSA3474-G and incorporated transcriptomics data from three different times of the day (dawn, dawn 7 h, and dusk) for both control and WNT conditions with iOSA3474-G. Three distinct growth phases: anoxia, normoxia, and hyperoxia, were identified in rice kernels from the GSMs, highlighting the grain-filling pattern under varying oxygen levels. We predicted excess flux through histidine contributing to the biomass as a marker of normoxia, during which kernel chalkiness occurs. Moreover, similarly, we proposed tyrosine as a marker for the hyperoxic growth phase. We also proposed a potential link between monodehydroascorbate reductase, an enzyme with evolutionary significance dating back to the carboniferous era, in regulating the hyperoxic growth phase. Metabolic bottleneck analysis identified nucleoside diphosphate kinase as a central regulator of metabolic flux under different conditions. These findings provide targeted insights into the complex metabolic network governing rice grain chalkiness under WNT conditions. Integration of GSM and transcriptomics data, enhanced our understanding of the intricate relationship between environmental factors, metabolic processes, and grain quality and also offer markers that can be useful to develop rice with improved resilience.

Suboptimal grain filling in rice (Oryza sativa) inferior spikelets poses a constraint to maximizing the yield potential. The differential grain filling between superior and inferior spikelets has been primarily attributed to differences in endogenous phytohormone levels that determine grain sink capacity. In this study, we aimed to gain molecular insights into the role of two phytohormones, abscisic acid (S-ABA or ABA) and cytokinin (6-benzyladenine or BA) through exogenous applications on superior and inferior grains in rice. We found that ABA and a combination of ABA and BA (ABA+BA) applications increased the grain yield in field studies, primarily by improving the grain weight of both superior and inferior grains. Transcriptomic analysis of developing grains shows differences in the expression of core cell cycle genes between the superior and inferior grains at four days after fertilization between the control and phytohormone applications. ABA and ABA+BA applications induce DNA replication genes and cell cycle inhibitory genes in superior grains only, likely promoting endoreduplication for increased cell storage capacity. ABA and BA applications suppressed the expression of cytokinin signaling genes in superior grains but induced them in inferior grains emphasizing the key roles for cytokinins and ABA in superior and inferior grains, respectively. An early induction of several grain storage-related genes in inferior grains is associated with accelerated entry into the grain storage stage, thus limiting sink capacity and poor grain fill. Our results indicate that ABA alone promotes photosynthate remobilization into both superior and inferior grains while ABA + BA regulates grain filling via cell cycle-related transcriptomic changes. Overall, our study reveals an intrinsic difference in ABA+BA sensitivity between inferior and superior grains that is linked to regulation of cell cycle checkpoints and entry into endoreduplication in the endosperm.

Heat stress (HS) occurring during the grain-filling period has a detrimental effect on grain yield and quality in rice (Oryza sativa). The development of heat-resilient cultivars could partly solve this issue if tolerant alleles can be identified and incorporated into the germplasm. In this study, we posit that some of the phenotypic variations for heat resilience during grain development could be due to variations in gene expression among accessions. To test this, we characterized the HS response of 10 diverse rice accessions from three major sub-populations using physiological and transcriptome analyses. At a single-grain level, grain width and grain thickness emerged as the most heat-sensitive traits. During a transient HS, IND-3 was categorized as highly sensitive, while five accessions exhibited moderate heat sensitivity, and four accessions were tolerant. Only a core set of 29.4% of the differentially expressed genes was common to the three rice sub-populations. Heat-tolerant accession TEJ-5 uniquely triggered an unfolded protein response (UPR) under HS, as evident from the induction of OsbZIP50 and downstream UPR genes. OsbZIP58, a gene that positively regulates grain filling, was more highly induced by HS in IND-2 despite its moderate heat sensitivity. Collectively, our analysis suggests that both unique gene expression responses and variation in the level of responses for a given pathway distinguish diverse accessions. Only some of these responses are associated with single-grain phenotypes in a manner consistent with the known roles of these genes and pathways.

Heat stress occurring during rice ( Oryza sativa ) grain development reduces grain quality, which often manifests as increased grain chalkiness. Although the impact of heat stress on grain yield is well-studied, the genetic basis of rice grain quality under heat stress is less explored as quantifying grain quality is less tractable than grain yield. To address this, we used an image-based colorimetric assay (Red, R; and Green, G) for genome-wide association analysis to identify genetic loci underlying the phenotypic variation in rice grains exposed to heat stress. We found the R to G pixel ratio (RG) derived from mature grain images to be effective in distinguishing chalky grains from translucent grains derived from control (28/24°C) and heat stressed (36/32°C) plants. Our analysis yielded a novel gene, rice Chalky Grain 5 ( OsCG5 ) that regulates natural variation for grain chalkiness under heat stress. OsCG5 encodes a grain-specific, expressed protein of unknown function. Accessions with lower transcript abundance of OsCG5 exhibit higher chalkiness, which correlates with higher RG values under stress. These findings are supported by increased chalkiness of OsCG5 knock-out (KO) mutants relative to wildtype (WT) under heat stress. Grains from plants overexpressing OsCG5 are less chalky than KOs but comparable to WT under heat stress. Compared to WT and OE, KO mutants exhibit greater heat sensitivity for grain size and weight relative to controls. Collectively, these results show that the natural variation at OsCG5 may contribute towards rice grain quality under heat stress.

High-throughput, nondestructive, and precise measurement of seeds is critical for the evaluation of seed quality and the improvement of agricultural productions. To this end, we have developed a novel end-to-end platform named HyperSeed to provide hyperspectral information for seeds. As a test case, the hyperspectral images of rice seeds are obtained from a high-performance line-scan image spectrograph covering the spectral range from 600 to 1700 nm. The acquired images are processed via a graphical user interface (GUI)-based open-source software for background removal and seed segmentation. The output is generated in the form of a hyperspectral cube and curve for each seed. In our experiment, we presented the visual results of seed segmentation on different seed species. Moreover, we conducted a classification of seeds raised in heat stress and control environments using both traditional machine learning models and neural network models. The results show that the proposed 3D convolutional neural network (3D CNN) model has the highest accuracy, which is 97.5% in seed-based classification and 94.21% in pixel-based classification, compared to 80.0% in seed-based classification and 85.67% in seed-based classification from the support vector machine (SVM) model. Moreover, our pipeline enables systematic analysis of spectral curves and identification of wavelengths of biological interest.

The tapetum plays a crucial role in pollen development by nursing and releasing the microspore. The tapetum undergoes programmed cell death (PCD), and appropriate timing of PCD is essential for microsporogenesis. Undeveloped Tapetum1 (UDT1) is known to function in anther development, but the regulation mechanism of tapetum differentiation and degeneration by UDT1 is largely unknown. Through comparative transcriptome analysis, we selected 100 genes as udt1 downregulated genes. The biological process related to the negative regulation of translation is the most enriched in udt1 downregulated genes. It is attributed by ribosome inactivating proteins (RIPs), but the role of RIPs is not well defined, and they are assumed to participate in tapetal PCD. Lipid transport is another overrepresented Gene Ontology (GO) term in udt1 downregulated genes, indicating the functional loss of the tapetum as the nursing cell. Using comparative analysis and real-time PCR, we infer that UDT1 can trigger tapetal PCD by controlling the expression of RIPs and three aspartyl proteases (AP) grouped with OsAP37, which is well known as being involved in tapetum degeneration.

Potassium (K+) is an essential cation in all organisms that influences crop production and ecosystem stability. Although most soils are rich in K minerals, relatively little K+ is present in forms that are available to plants. Moreover, leaching and run-off from the upper soil layers contribute to K+ deficiencies in agricultural soils. Hence, the demand for K fertilizer is increasing worldwide. K+ regulates multiple processes in cells and organs, with K+ deficiency resulting in decreased plant growth and productivity. Here, we discuss the complexity of the reactive oxygen species-calcium-hormone signalling network that is responsible for the sensing of K+ deficiency in plants, together with genetic approaches using K+ transporters that have been used to increase K+ use efficiency (KUE) in plants, particularly under environmental stress conditions such as salinity and heavy metal contamination. Publicly available rice transcriptome data are used to demonstrate the two-way relationship between K+ and nitrogen nutrition, highlighting how each nutrient can regulate the uptake and root to shoot translocation of the other. Future research directions are discussed in terms of this relationship, as well as prospects for molecular approaches for the generation of improved varieties and the implementation of new agronomic practices. An increased knowledge of the systems that sense and take up K+, and their regulation, will not only improve current understanding of plant K+ homeostasis but also facilitate new research and the implementation of measures to improve plant KUE for sustainable food production.

Rice (Oryza sativaL.) is a staple crop with agricultural traits that have been intensively investigated. However, despite the variety of mutant population and multi-omics data that have been generated, rice functional genomic research has been bottlenecked due to the functional redundancy in the genome. This phenomenon has masked the phenotypes of knockout mutants by functional compensation and redundancy. Here, we present an intuitive tool,CRISPRapplicablefunctionalredundancyinspector to accelerate functional genomics in rice (CAFRI-Rice; cafri-rice.khu.ac.kr). To create this tool, we generated a phylogenetic heatmap that can estimate the similarity between protein sequences and expression patterns, based on 2,617 phylogenetic trees and eight tissue RNA-sequencing datasets. In this study, 33,483 genes were sorted into 2,617 families, and about 24,980 genes were tested for functional redundancy using a phylogenetic heatmap approach. It was predicted that 7,075 genes would have functional redundancy, according to the threshold value validated by an analysis of 111 known genes functionally characterized using knockout mutants and 5,170 duplicated genes. In addition, our analysis demonstrated that an anther/pollen-preferred gene cluster has more functional redundancy than other clusters. Finally, we showed the usefulness of the CAFRI-Rice-based approach by overcoming the functional redundancy between two root-preferred genes via loss-of-function analyses as well as confirming the functional dominancy of three genes through a literature search. This CAFRI-Rice-based target selection for CRISPR/Cas9-mediated mutagenesis will not only accelerate functional genomic studies in rice but can also be straightforwardly expanded to other plant species.

MicroProteins are a class of small single-domain proteins that post-translationally regulate larger multidomain proteins from which they evolved or which they relate to. They disrupt the normal function of their targets by forming microProtein-target heterodimers through compatible protein-protein interaction (PPI) domains. Recent studies confirm the significance of microProteins in the fine-tuning of plant developmental processes such as shoot apical meristem maintenance and flowering time regulation. While there are a number of well-characterized microProteins in Arabidopsis thaliana, studies from more complex plant genomes are still missing. We have previously developed miPFinder, a software for identifying microProteins from annotated genomes. Here we present an improved version where we have updated the algorithm to increase its accuracy and speed, and used it to analyze five cereal crop genomes - wheat, rice, barley, maize and sorghum. We found 20,064 potential microProteins from a total of 258,029 proteins in these five organisms, of which approximately 2000 are high-confidence, i.e., likely to function as actual microProteins. Gene ontology analysis of these 2000 microProtein candidates revealed their roles in stress, light and growth responses, hormone signaling and transcriptional regulation. Using a recently developed rice gene co-expression database, we analyzed 347 potential rice microProteins that are also conserved in other cereal crops and found over 50 of these rice microProteins to be co-regulated with their identified interaction partners. Overall, our study reveals a rich source of biotechnologically interesting small proteins that regulate fundamental plant processes such a growth and stress response that could be utilized in crop bioengineering.

Oryza sativa (rice) is an economically important crop, which is valued as a staple food source and as genetic model for cereals. Rice production needs to increase substantially to meet the growing global demand. Genetic studies have indicated that anther and pollen development genes can be used as targets to improve yield. Although several genes related to male organ developmental pathways have been characterized, the complete signaling network remains unclear. We used publicly available anther and pollen development transcriptome datasets to identify candidates for functional genomics studies. In addition, we newly generated RNA-Seq data for anther, anther wall and pollen samples with leaf sheath as control to provide the expression data for genes that are not covered by microarray technologies in rice. We constructed a platform, the rice male gamete expression database (RMEDB), comprising microarray and RNA-Seq based 188 transcriptome samples across diverse rice tissues and developmental stages of O. sativa japonica and O. sativa indica . Meta-expression analysis identified genes expressed at specific stages of anther or pollen developments. The functionalities in RMEDB database ( http://ricephylogenomics-khu.org/RMEDB/home.php ) can serve to identify candidates in male organ development for functional genomic studies of rice.

The mutant allele of rice calmodulin-binding transcription activator OsCBT, oscbt-1, exhibits broad-spectrum resistance against rice pathogens. Previously, we reported that the strong resistance of the oscbt-1 mutant to pathogens was conferred by a constitutive upregulation of defense-related genes even under pathogen-free conditions. We also found strong induction of the hypersensitive response as a reaction to pathogen invasion. The results suggest that OsCBT acts as a negative regulator of basal resistance to pathogen attack. To identify the transcriptional network regulated by OsCBT, we compared global gene expression profiles between wild-type (WT) and oscbt-1 rice plants grown under pathogen-free conditions. The results of a 3′ tiling microarray revealed that in oscbt-1 plants, 81 genes are upregulated and 200 genes are downregulated when compared with the WT. A gene ontology analysis showed that differentially regulated genes in oscbt-1 were very closely associated with “death” GO term in a biological process category, and “catalytic activity” and “binding” GO terms in a molecular function category. A MapMan analysis indicated that the functions of these genes were associated with plant responses to biotic stress. Moreover, the results from quantitative real-time PCR in the oscbt-1 mutant showed a significant effect on the gene expression patterns of the fungal pathogen response. Our results suggested that the OsCBT regulates a rice defense response by modulating the expressions of various defense-related genes.

Plant-growth-promoting bacteria (PGPB) are beneficial microorganisms that can also protect against disease and environmental stress. Silicon (Si) is the second most abundant element in soil, and is known to increase plant growth, grain yield, resistance to biotic stress, and tolerance to abiotic stress. Combined treatment of PGPB and Si has been shown to further enhance plant growth and crop yield. To determine the global effects of the PGPB and Si on rice growth, we compared rice plants treated with Paenibacillus yonginensis DCY84T (DCY84T) and Si with untreated rice. To identify the genes that respond to DCY84T+Si treatment in rice, we performed an RNA-Seq transcriptome analysis by sampling treated and untreated roots on a weekly basis for three weeks. Overall, 576 genes were upregulated, and 394 genes were downregulated in treated roots, using threshold fold-changes of at least 2 (log2) and p-values < 0.05. Gene ontology analysis showed that phenylpropanoids and the L-phenylalanine metabolic process were prominent in the upregulated genes. In a metabolic overview analysis using the MapMan toolkit, pathways involving phenylpropanoids and ethylene were strongly associated with upregulated genes. The functions of seven upregulated genes were identified as being associated with drought stress through a literature search, and a stress experiment confirmed that plants treated with DCY84T+Si exhibited greater drought tolerance than the untreated control plants. Furthermore, the predicted protein-protein interaction network analysis associated with DCY84T+ Si suggests mechanisms underlying growth promotion and stress tolerance.

Rice (Oryza sativa L.) is both a major staple food for the worldwide population and a model crop plant for studying the mode of action of agronomically valuable traits, providing information that can be applied to other crop plants. Due to the development of high-throughput technologies such as next generation sequencing and mass spectrometry, a huge mass of multi-omics data in rice has been accumulated. Through the integration of those data, systems biology in rice is becoming more advanced. To facilitate such systemic approaches, we have summarized current resources, such as databases and tools, for systems biology in rice. In this review, we categorize the resources using six omics levels: genomics, transcriptomics, proteomics, metabolomics, integrated omics, and functional genomics. We provide the names, websites, references, working states, and number of citations for each individual database or tool and discuss future prospects for the integrated understanding of rice gene functions.

Soil salinity is a major production constrain for agricultural crops, especially in Oryza sativa (rice). Analyzing physiological effect and molecular mechanism under salt stress is key for developing stress-tolerant plants. Roots system has a major role in coping with the osmotic change impacted by salinity and few salt-stress-related transcriptome studies in rice have been previously reported. However, transcriptome data sets using rice roots grown in soil condition are more relevant for further applications, but have not yet been available. The present work analyzed rice root and shoot physiological characteristics in response to salt stress using 250 mM NaCl for different timepoints. Subsequently, we identified that 5 day treatment is critical timepoint for stress response in the specific experimental design. We then generated RNA-Seq-based transcriptome data set with rice roots treated with 250 mM NaCl for 5 days along with untreated controls in soil condition using rice japonica cultivar Chilbo. We identified 447 upregulated genes under salt stress with more than fourfold changes (p value < 0.05, FDR < 0.05) and used qRT-PCR for six genes to confirm their salt-dependent induction patterns. GO-enrichment analysis indicated that carbohydrate and amino-acid metabolic process are significantly affected by the salt stress. MapMan overview analysis indicated that secondary metabolite-related genes are induced under salt stress. Metabolites profiling analysis confirmed that phenolics and flavonoids accumulate in root under salt stress. We further constructed a functional network consisting of regulatory genes based on predicted protein–protein interactions, suggesting useful regulatory molecular network for future applications.

Root hairs are tubular shaped protuberances of root epidermal cells and are found in nearly all vascular plants. Co-ordinate expression of a number of root hair morphogenesis genes involved in cytoskeleton reorganization, changes in homeostasis and distribution of ion gradients, and cell wall reassembly are required during root hair cell elongation. In this report, we have characterized a root hairspecific putative cellulase gene in rice, OsRHC . OsRHC is specifically expressed in elongating root hairs and OsRHC is targeted to the plasma membrane. The mutation of the OsRHC gene by a T-DNA knock-out and CRISPR-Cas9 system causes a severe reduction in root hair length. Bimolecular fluorescence complementation analysis demonstrated that the OsRHC protein interacts with a root hair-specific cellulose synthase protein (OsCSLD1) in the plasma membrane. Furthermore, we observed a moderate reduction of cellulose content in the osrhc mutant. Our results suggest that the plasma membrane-localized OsRHC plays a critical role in cell wall remodeling during root hair extension.

Transcription factors (TFs) are an important class of regulatory molecules. Despite their importance, only a small number of genes encoding TFs have been characterized in Oryza sativa (rice), often because gene duplication and functional redundancy complicate their analysis. To address this challenge, we developed a web-based tool called the Rice Transcription Factor Phylogenomics Database (RTFDB) and demonstrate its application for predicting TF function. The RTFDB hosts transcriptome and co-expression analyses. Sources include high-throughput data from oligonucleotide microarray (Affymetrix and Agilent) as well as RNA-Seq-based expression profiles. We used the RTFDB to identify tissue-specific and stress-related gene expression. Subsequently, 273 genes preferentially expressed in specific tissues or organs, 455 genes showing a differential expression pattern in response to 4 abiotic stresses, 179 genes responsive to infection of various pathogens and 512 genes showing differential accumulation in response to various hormone treatments were identified through the meta-expression analysis. Pairwise Pearson correlation coefficient analysis between paralogous genes in a phylogenetic tree was used to assess their expression collinearity and thereby provides a hint on their genetic redundancy. Integrating transcriptome with the gene evolutionary information reveals the possible functional redundancy or dominance played by paralog genes in a highly duplicated genome such as rice. With this method, we estimated a predominant role for 83.3% (65/78) of the TF or transcriptional regulator genes that had been characterized via loss-of-function studies. In this regard, the proposed method is applicable for functional studies of other plant species with annotated genome.

This work suggests 2020 potential candidates in rice for the functional annotation of unannotated genes using meta-analysis of anatomical samples derived from microarray and RNA-seq technologies and this information will be useful to identify novel morphological agronomic traits.

Plant root systems play essential roles in developmental processes, such as the absorption of water and inorganic nutrients, and structural support. Gene expression is affected by growth conditions and the genetic background of plants. To identify highly conserved root-preferred genes in rice across diverse growth conditions and varieties, we used two independent meta-anatomical expression profiles based on a large collection of Affymetrix and Agilent 44 K microarray data sets available for public use. We then identified 684 loci with root-preferred expression, which were validated with in silico analysis using both meta-expression profiles. The expression patterns of four candidate genes were confirmed in vivo by monitoring expression of β-glucuronidase under control of the candidate-gene promoters, providing new tools to manipulate agronomic traits associated with roots. We also utilized real-time PCR to examine the root-preferential expression of 14 genes across four rice varieties, including japonica and indica cultivars. Using a database of rice genes with known functions, we identified the reported functions of 39 out of the 684 candidate genes. Sixteen genes are directly involved in root development, while the remaining are involved in processes indirectly related to root development (i.e., soil-stress tolerance or growth retardation). This indicates the importance of our candidate genes for studies on root development and function. Gene ontology enrichment analysis in the ‘biological processes’ category revealed that root-preferred genes in rice are closely associated with nutrient transport-related genes, indicating that the primary role of roots is the uptake of nutrients from soil. In addition, predicted protein–protein interaction analysis suggested a molecular network for root development composed of 215 interactions associated with 44 root-preferred or root development-related genes. Taken together, our data provide an important foundation for future research on root development in rice.

Background: Root hairs are valuable in taking up nutrients and water from the rhizosphere and serving as sites of interactions with soil microorganisms. By increasing the external surface area of the roots or interacting with rhizobacteria, root hairs directly and indirectly promote plant growth and yield. Transcriptome data can be used to understand root-hair development in rice. Result: We performed Agilent 44 K microarray experiments with enriched root-hair samples and identified 409 root hair-preferential genes in rice. The expression patterns of six genes were confirmed using a GUS reporter system and quantitative RT-PCR analysis. Gene Ontology (GO) analysis demonstrated that 13 GO terms, including oxygen transport and cell wall generation, were highly over-represented in those genes. Although comparative analysis between rice and Arabidopsis revealed a large proportion of orthologous pairs, their spatial expression patterns were not conserved. To investigate the molecular network associated with root hair-preferential genes in rice, we analyzed the PPI network as well as coexpression data. Subsequently, we developed a refined network consisting of 24 interactions between 10 genes and 18 of their interactors. Conclusion: Identification of root hair-preferential genes and in depth analysis of those genes will be a useful reference to accelerate the understanding of root-hair development in rice.