Water deficiencies are one of the most serious challenges to crop productivity. To improve our understanding of soil moisture stress, we performed RNA-Seq analysis using roots from 4-week-old rice seedlings grown in soil that had been subjected to drought conditions for 2–3 d. In all, 1,098 genes were up-regulated in response to soil moisture stress for 3 d, which causes severe damage in root development after recovery, unlikely that of 2 d. Comparison with previous transcriptome data produced in drought condition indicated that more than 68% of our candidate genes were not previously identified, emphasizing the novelty of our transcriptome analysis for drought response in soil condition. We then validated the expression patterns of two candidate genes using a promoter-GUS reporter system in planta and monitored the stress response with novel molecular markers. An integrating omics tool, MapMan analysis, indicated that RING box E3 ligases in the ubiquitin-proteasome pathways are significantly stimulated by induced drought. We also analyzed the functions of 66 candidate genes that have been functionally investigated previously, suggesting the primary roles of our candidate genes in resistance or tolerance relating traits including drought tolerance (29 genes) through literature searches besides diverse regulatory roles of our candidate genes for morphological traits (15 genes) or physiological traits (22 genes). Of these, we used a T-DNA insertional mutant of rice phytochrome B (OsPhyB) that negatively regulates a plant's degree of tolerance to water deficiencies through the control of total leaf area and stomatal density based on previous finding. Unlike previous result, we found that OsPhyB represses the activity of ascorbate peroxidase and catalase mediating reactive oxygen species (ROS) processing machinery required for drought tolerance of roots in soil condition, suggesting the potential significance of remaining uncharacterized candidate genes for manipulating drought tolerance in rice.

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BackgroundRice is one of the most important food crops for humans. To improve the agronomical traits of rice, the functions of more than 1,000 rice genes have been recently characterized and summarized. The completed, map-based sequence of the rice genome has significantly accelerated the functional characterization of rice genes, but progress remains limited in assigning functions to all predicted non-transposable element (non-TE) genes, estimated to number 37,000–41,000.ResultsThe International Rice Functional Genomics Consortium (IRFGC) has generated a huge number of gene-indexed mutants by using mutagens such as T-DNA, Tos17 and Ds/dSpm. These mutants have been identified by 246,566 flanking sequence tags (FSTs) and cover 65 % (25,275 of 38,869) of the non-TE genes in rice, while the mutation ratio of TE genes is 25.7 %. In addition, almost 80 % of highly expressed non-TE genes have insertion mutations, indicating that highly expressed genes in rice chromosomes are more likely to have mutations by mutagens such as T-DNA, Ds, dSpm and Tos17. The functions of around 2.5 % of rice genes have been characterized, and studies have mainly focused on transcriptional and post-transcriptional regulation. Slow progress in characterizing the function of rice genes is mainly due to a lack of clues to guide functional studies or functional redundancy. These limitations can be partially solved by a well-categorized functional classification of FST genes. To create this classification, we used the diverse overviews installed in the MapMan toolkit. Gene Ontology (GO) assignment to FST genes supplemented the limitation of MapMan overviews.ConclusionThe functions of 863 of 1,022 known genes can be evaluated by current FST lines, indicating that FST genes are useful resources for functional genomic studies. We assigned 16,169 out of 29,624 FST genes to 34 MapMan classes, including major three categories such as DNA, RNA and protein. To demonstrate the MapMan application on FST genes, transcriptome analysis was done from a rice mutant of 1-deoxy-D-xylulose 5-phosphate reductoisomerase (DXR) gene with FST. Mapping of 756 down-regulated genes in dxr mutants and their annotation in terms of various MapMan overviews revealed candidate genes downstream of DXR-mediating light signaling pathway in diverse functional classes such as the methyl-D-erythritol 4-phosphatepathway (MEP) pathway overview, photosynthesis, secondary metabolism and regulatory overview. This report provides a useful guide for systematic phenomics and further applications to enhance the key agronomic traits of rice.Electronic supplementary materialThe online version of this article (doi:10.1186/s12284-016-0089-2) contains supplementary material, which is available to authorized users.

BackgroundProtein kinases catalyze the transfer of a phosphate moiety from a phosphate donor to the substrate molecule, thus playing critical roles in cell signaling and metabolism. Although plant genomes contain more than 1000 genes that encode kinases, knowledge is limited about the function of each of these kinases. A major obstacle that hinders progress towards kinase characterization is functional redundancy. To address this challenge, we previously developed the rice kinase database (RKD) that integrated omics-scale data within a phylogenetics context.ResultsAn updated version of rice kinase database (RKD) that contains metadata derived from NCBI GEO expression datasets has been developed. RKD 2.0 facilitates in-depth transcriptomic analyses of kinase-encoding genes in diverse rice tissues and in response to biotic and abiotic stresses and hormone treatments. We identified 261 kinases specifically expressed in particular tissues, 130 that are significantly up- regulated in response to biotic stress, 296 in response to abiotic stress, and 260 in response to hormones. Based on this update and Pearson correlation coefficient (PCC) analysis, we estimated that 19 out of 26 genes characterized through loss-of-function studies confer dominant functions. These were selected because they either had paralogous members with PCC values of <0.5 or had no paralog.ConclusionCompared with the previous version of RKD, RKD 2.0 enables more effective estimations of functional redundancy or dominance because it uses comprehensive expression profiles rather than individual profiles. The integrated analysis of RKD with PCC establishes a single platform for researchers to select rice kinases for functional analyses.Electronic supplementary materialThe online version of this article (doi:10.1186/s12284-016-0106-5) contains supplementary material, which is available to authorized users.