Similar Datasets
Project description:Transcriptional profiling of rice shoot or root treated with acetate. Goal was to determine the effects of acetate on changes in gene expression.
2021-03-23 | GSE115825 | GEO
Project description:Comparative transcriptional profiling of two contrasting rice genotypes,IRAT109 (drought-resistant japonica cultivar) and ZS97 (drought-sensitive indica cultivar), under drought stress during the reproductive stage
2011-11-05 | GSE25176 | GEO
Project description:Rice is highly sensitive to drought, and the effect of drought may vary with the different genotypes and development stages. Genome-wide gene expression profiling was used as the initial point to dissect molecular genetic mechanism of this complex trait and provide valuable information for the improvement of drought tolerance in rice. Affymetrix rice genome array containing 48,564 japonica and 1,260 indica sequences was used to analyze the gene expression pattern of rice exposed to drought stress. The transcriptome from leaf, root, and young panicle at three developmental stages was comparatively analyzed combined with bioinformatics exploring drought stress related cis-elements.
2010-12-23 | GSE26280 | GEO
Project description:To investigate the relative effects of drought and heat on the rice (Oryza sativa) transcriptome, we subjected rice seedlings to 3 levels of long-term drought or 2 levels of short-term heat stock
2022-12-27 | GSE221542 | GEO
Project description:Several homeobox genes belonging to HD-ZIP I subfamily are highly induced by drought stress at various developmental stages in rice. To analyze the role of a candidate HD-ZIP I subfamily member, OsHOX24, we constitutively overexpressed it in rice. The physiological analyses revealed that overexpression of OsHOX24 gene reduced drought stress tolerance in transgenic plants as compared to wild-type. We used microarrays to study the global effect of OsHOX24 overexpression in rice as compared to wild-type under control and drought stress condition.
2017-06-12 | GSE79212 | GEO
Project description:We generated the global transcriptome profile of the two rice genotypes under control and drought conditions. More than 80 million high-quality reads were obtained for each cultivar and different conditions using the Illumina platform. Reference-based assembly was generated for each cultivar and condition. Differentially expressed genes were identified between drought and control condittons for each cultivar.
2023-12-31 | GSE183894 | GEO
Project description:Comparative transcriptional profiling of two contrasting rice genotypes,IRAT109 (drought-resistant japonica cultivar) and ZS97 (drought-sensitive indica cultivar), under drought stress during the reproductive stage Four samples with RWC in the range of 94–95% (no stress, D0), 83–88% (slight drought in which leaves were slightly rolled, D1), 74–78% (moderate drought in which about half of each leaf was rolled, D2), and 65–69% (severe drought in which all leaves were completely rolled, D3) were collected for expression profiling analysis using an Affymetrix GeneChip.
2011-11-05 | E-GEOD-25176 | biostudies-arrayexpress
Project description:We investigated the physiological and gene expression response of drought-tolerant (IR57311 and LC-93-4; subgroup indica) and drought-sensitive (Nipponbare and Taipai 309; subgroup japonica) rice (Oryza sativa) cultivars to 18 days of drought stress in climate chamber experiments. Rice plants were grown under water sufficient and water limiting conditions in three independent experiments in a controlled climate chamber with 12 h day length at 600 µE m-2 s-1; temperature was 26°C in the light and 22°C at night, with a relative humidity of 75% in the light and 70% at night. Leaf material for expression profiling analysis was harvested five hours after the beginning of the light period after 18 days of stress or control treatment. Normalization and statistical testing was performed using the R package limma (R 2.3.1, limma version 2.7.3; (Smyth, 2005)). The methods Robustspline for within array normalization and Quantile for between array normalization were applied. A linear model with the effects genotype, drought treatment, genotype x drought, dye was fitted to normalized data in limma that models the systemic variation in the data. Afterwards, for the comparisons of interest, moderated t-statistics that use an empirical Bayes method were calculated. Differentially expressed genes were identified using the decideTests function (method global, Benjamini & Hochberg fdr corrected p-value <0.05 in limma) Keywords: stress reponse Growth design. Three independent experiments were performed. The design was a split-plot design with five blocks per drought or control treatment in each experiment. Each treatment and cultivar was represented by five replicate pots with one plant per pot. Pots were randomized within the blocks. Block position was rotated daily. Hybridisation design: A total of 28 samples, each representing mRNA from four parallel plants, were hybridized to 14 arrays. The hybridization design was optimized for the estimation of the effects of condition and the condition x cultivar interaction taking a variance minimization approach. In a two-step procedure, a smaller design for one sensitive and one tolerant cultivar was enlarged to encompass all four cultivars by integrating eight additional arrays. The optimization was programmed using R [R Development Core Team 2006] and carried out on the 16-node Beowulf Linux-Cluster at the University of Potsdam. R-scripts are available upon request and from the Bioinformatics Team at the MPI of Molecular Plant Physiology (see the website for more information). Allocation of the three biological replicates of each of the combinations of treatment and cultivar was completed such that a balanced distribution with respect to the labeling was achieved. Each combination of condition and cultivar from all experiments has been used at least once.
2008-10-29 | E-GEOD-7766 | biostudies-arrayexpress
Project description:The severity of impact of drought on crops is contingent on the developmental stage of the plant, with the most sensitive stage being the reproductive stage. Hence, gene expression profiling has been used to understanding drought response and resistance mechanism in rice. Here we present drought transcriptomes of rice in three developmental stages and gain insights into the processes and regulatory mechanisms involved in common and stage specific drought responses.
2016-07-20 | GSE81253 | GEO