Project description:Genomic diversity is a source of transcriptomic and phenotypic diversities. Although genomic variations in rice (Oryza sativa) accessions have been extensively analyzed, information of transcriptomic and phenotypic variations, especially for below-ground variations, are limited. Here, we report the diversities of above- and below-ground traits and transcriptomes in highly diversified 61 rice accessions grown in the upland-field. We found that phenotypic variations were explained by four principal components and that tiller numbers and crown root diameters could summarize admixture groups. Transcriptome analysis revealed that admixture-group-associated differentially expressed genes were enriched with stress response related genes, suggesting that admixture groups have distinct stress response mechanisms. Root growth was negatively correlated with auxin inducible genes, suggesting the association between auxin signaling and mild drought stress. Negative correlation between crown root diameters and stress response related genes suggested that thicker crown root diameter is associated with mild drought stress tolerance. Finally co-expression network analysis implemented with DAP-seq analysis identified phytohormone signaling network and key transcription factors negatively regulating crown root diameters. Our datasets would serve as an important resource for understanding genomic and transcriptomic basis of phenotypic variations under the upland-field condition.
Project description:In the current study we did microarray of upland rice cultivar Nagina22 for drought stress at reproductive stage (panicle initiation) and analyzed drought stress responsive genes. We have taken flag leaf for our study as it is most essential organ for photosynthesis in rice. Normal watering Vs Drought Stress Flag leaf of Control (Three biological replicates) plant of Nagina22: C1, C2, C3 Flag leaf of drought stressed (Three biological replicates) plant of Nagina 22: S1, S2, S3
Project description:Rice is a critically important food source but yields worldwide are vulnerable to periods of drought. We exposed eight genotypes of upland and lowland rice (Oryza sativa L. ssp. japonica and indica) to drought stress at the late vegetative stage and harvested leaves for protein extraction and subsequent label-free shotgun proteomics. Gene ontology analysis revealed some differentially expressed proteins were induced by drought in all eight genotypes; we speculate that these play a universal role in drought tolerance. However, some highly genotype-specific patterns of response to drought suggest that some mechanisms of metabolic reprogramming are not universal. Such proteins had largely uncharacterized functions, making them biomarker candidates for drought tolerance screens.
Project description:Rice (Oryza sativa), the major staple food crop is being cultivated under varying ecosystems ranging from irrigated lowland to rainfed upland environments. Improvement in the rice production under drought prone unfavourable environment depends on the development of drought tolerant genotypes which needs thorough understanding of physiological and molecular events behind the tolerance mechanism. There is considerable genetic variation for drought tolerance mechanism within the cultivated gene pool. To understand the diversity of drought response, two indica rice genotypes namely, i) Apo, an up-land drought tolerant indica veriety from Philippines and ii) IR64, a popular high yielding drought susceptible genotype were selected for this study. We used the 22K rice Oligoarray from Agilent technologies to study the transcript profile in the leaves of the two contrasting rice genotypes under control and drought stressed conditions during vegetative phase. Keywords: Drought response
Project description:In this study, we analysed the proteomic response of 5mm sections of root tips to water-deficit stress in two contrasting genotypes of rice: IR64, a lowland, drought-susceptible, and shallow-rooting genotype; and Azucena, an upland, drought-tolerant, and deep-rooting genotype. Using a Partial Least Square Discriminant Analysis, we identified statistically significant differentially abundant proteins across genotypes and conditions. Analysis of biological processes led to the identification of novel proteins involved in root elongation with specific expression patterns in Azucena.