Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1196497 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR31680293_1.fastq.gz | Fastqsanger.gz | |||
| SRR31680293_2.fastq.gz | Fastqsanger.gz | |||
| SRR31680294_1.fastq.gz | Fastqsanger.gz | |||
| SRR31680294_2.fastq.gz | Fastqsanger.gz | |||
| SRR31680295_1.fastq.gz | Fastqsanger.gz |
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Project description:Drought is a harmful abiotic stress that threatens the growth, development, and yield of rice plants. To cope with drought stress, plants have evolved diverse and sophisticated stress-tolerance pathways by regulating gene expression. Previous genome-wide studies have revealed many rice drought stress-responsive genes that are involved in various metabolism, hormone biosynthesis and signaling pathways, and transcriptional regulation. However, little is known about the regulation of drought-responsive genes during rehydration after dehydration. In this study, we examined the dynamic gene expression patterns in rice seedling shoots during dehydration and rehydration using RNA-seq analysis. To investigate the transcriptome-wide rice gene expression patterns during dehydration and rehydration, RNA-seq libraries were sequenced and analyzed to identify differentially expressed genes (DEGs). DEGs were classified into five clusters based on their gene expression patterns. The clusters included drought-responsive DEGs that were either rapidly or slowly recovered to control levels by rehydration treatment. Representative DEGs were selected and validated using qRT-PCR. In addition, we performed a detailed analysis of DEGs involved in nitrogen metabolism, phytohormone signaling, and transcriptional regulation. In this study, we revealed that drought-responsive genes were dynamically regulated during rehydration. Moreover, our data showed the potential role of nitrogen metabolism and jasmonic acid signaling during the drought stress response. The transcriptome data in this study could be a useful resource for understanding drought stress responses in rice, and may provide a valuable gene list for developing drought-resistant crop plants.
2023-05-17 | GSE222438 | GEO
Project description:Drought stress response involves vigorous reprogramming of transcriptome while the mechanism modulating this process remains elusive. The role of 3D-genome in the regulation of rice development has recently been unveiled in rice, which exhibited characteristics distinct from that in mammals and other plants. However, the relationship between spatial chromosome organization and drought responsive gene reprogramming is still poorly understood. In this study, we identified H3K9ac as an efficient histone mark that response dynamically to drought stress in rice and re-constructed high-resolution 3D genome contact maps based on these sites under the normal, drought, and recovery conditions. We discovered significant decondensation of chromatin contacts with over 10000 chromatin loops lost upon drought stress treatment while the recovery of 3D genome was limited after 4-day’s re-watering. We identified dominate promoter-promoter interacting (PPI) loops under each condition and identified their significant correlations to altered gene expressions in response to the corresponding condition. Based on the relative contact intensities of the PPI connections, we characterized super-promoter regions that integrate closer connections of genes with more vigorous inductions to condition shifts. Especially, about 75% of the drought stress-dominate PPI loops were associated to the binding by a well-defined drought stress-responsive transcription factor, OsbZIP23. The mutation of OsbZIP23 led to the diffuse of over 80% DS-dominate PPI loops and impaired the expression of the connected genes. As a case study, we showed how OsbZIP23 binding to a super-promoter region can integrate the PPI loop formation and transcriptional activation of four function-vital dehydrin genes upon drought stress. Our results shed light on the mechanisms of 3D genome dynamic in response to water supply variations in rice and highlight the role of OsbZIP23 in the regulation of chromatin loop formation under drought stress.
2024-09-19 | GSE242453 | GEO
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 We used Agilent rice gene chips (G4138A) to investigate the transcript level changes in rice leaf tissues during drought stress. We used two contrasting rice genotypes (IR64 drought susceptible and Apo drought tolerant) differing in their degree of drought tolerance. Plants were grown under green house conditions and drought stress was imposed on 33rd DAS. Leaf sampling was done in both control and drought stressed plants after 6 days of drought stress. Three replications of microarray experiments were carried out by hybridizing the control samples against the drought stressed samples.
2012-04-30 | E-GEOD-5978 | biostudies-arrayexpress
Project description:The OsCPK4 gene is a member of the complex gene family of the Calcium-dependent protein kinases (CPKs) in rice. Expression of OsCPK4 is induced by high salinity, drought and the phytohormone abscisic acid. The OsCPK4 protein localizes to the plasma membrane. Transgenic rice overexpressing OsCPK4 enhances tolerance to salt and drought stress, the transgenic plants having stronger water-holding capability than control plants. Microarray analysis of OsCPK4 rice plants revealed up-regulation of genes involved in metabolism, particularly lipid metabolism, as well as genes involved in oxidative stress and redox control. Meanwhile, OsCPK4 overexpression has no impact on the expression of the well-characterized abiotic stress-associated transcription factors (i.e. DREB and NAC), or the typical salt and drought-inducible genes (i.e. LEA genes, including Dehydrin genes). Under salt stress conditions, the OsCPK4 transgenic lines showed lesser membrane lipid peroxidation as compared to control plants, indicating that OsCPK4 rice plants have a better capacity to prevent oxidative damage in cellular membrane lipids. Collectively, our data suggest that OsCPK4-mediated processes protect the plant cell from uncontrolled redox reactions affecting membrane functions, which, in turn, results in salt and drought tolerance. OsCPK4 shows great promise for genetic improvement of tolerance to abiotic stress in rice.
2014-07-03 | GSE52353 | GEO
Project description:We have characterized the changes in miRNA expression profiles in rice leaves under drought stress and As stress and compared these to unstressed leaves. 10 pairs of drought responsive and 8 pairs of As responsive miRNA-gene were identified and validated by qRT-PCR. This study identifies putative specific miRNA-mRNA regulatory modules with roles during drought and As stress. Putative microRNAs identified in this study are involved in hormone signaling, lipid and carbohydrate metabolism, and antioxidant defence. The results of this study will assist in elucidating the role of miRNAs in post-transcriptional regulation of target genes during abiotic stress and may contribute to the development of strategies to engineer drought and heavy metal resistance.
2017-05-20 | GSE99083 | GEO
Project description:Background Drought is a global challenge that severely restricts crop yields and threatens food security. Plants respond to drought stress by modulating gene expression before visible phenotypic changes occur. However, most studies of drought resistance have examined phenotypes after drought treatment, with little emphasis on how severely the plants were perceiving drought-stress conditions before the appearance of stress symptoms. We therefore developed drought-stress biomarkers (DSBMs) to detect drought-stress perception levels based on gene expression profiles by performing time-series transcriptome analysis and phenotypic analysis of rice (Oryza sativa) under drought conditions in the growth chamber. Results Time-series RNA-seq of the drought-susceptible rice cultivar IR64 revealed drastic changes in the transcriptome after 4–6 days of drought treatment in plants grown in pot culture mimicking drought conditions in the field, particularly for genes related to photosynthesis. Among the differentially expressed genes, we selected 23 DSBM genes that consistently responded to drought stress. Rehydration immediately reset the changes in expression of these DSBM genes, indicating that their expression changes reflect current drought-stress perception levels, but not stress memories. Responses of DSBM genes tended to be conserved among rice accessions, irrespective of the rice subpopulation (such as indica, aus, and japonica). We developed a machine learning model using the expression levels of DSBM genes trained by the time-series RNA-seq data for IR64. This model successfully predicted the drought-stress perception levels of various rice accessions, representing the probability of exposure to drought treatment, with an accuracy of 75%. Extreme root architecture traits, such as the largest root surface area, narrowest crown root diameter, and largest ratio of deep rooting, influenced the predicted drought-stress perception levels. Conclusion We identified DSBM genes and developed a machine learning model as a robust tool for assessing drought-stress perception levels in rice. Monitoring and predicting drought-stress perception levels should contribute to more efficient crop management and breeding schemes. Furthermore, our dataset would serve as a resource for further understanding the mechanisms of drought resistance in rice.
2025-07-30 | GSE288412 | GEO
Project description:Background Drought is a global challenge that severely restricts crop yields and threatens food security. Plants respond to drought stress by modulating gene expression before visible phenotypic changes occur. However, most studies of drought resistance have examined phenotypes after drought treatment, with little emphasis on how severely the plants were perceiving drought-stress conditions before the appearance of stress symptoms. We therefore developed drought-stress biomarkers (DSBMs) to detect drought-stress perception levels based on gene expression profiles by performing time-series transcriptome analysis and phenotypic analysis of rice (Oryza sativa) under drought conditions in the growth chamber. Results Time-series RNA-seq of the drought-susceptible rice cultivar IR64 revealed drastic changes in the transcriptome after 4–6 days of drought treatment in plants grown in pot culture mimicking drought conditions in the field, particularly for genes related to photosynthesis. Among the differentially expressed genes, we selected 23 DSBM genes that consistently responded to drought stress. Rehydration immediately reset the changes in expression of these DSBM genes, indicating that their expression changes reflect current drought-stress perception levels, but not stress memories. Responses of DSBM genes tended to be conserved among rice accessions, irrespective of the rice subpopulation (such as indica, aus, and japonica). We developed a machine learning model using the expression levels of DSBM genes trained by the time-series RNA-seq data for IR64. This model successfully predicted the drought-stress perception levels of various rice accessions, representing the probability of exposure to drought treatment, with an accuracy of 75%. Extreme root architecture traits, such as the largest root surface area, narrowest crown root diameter, and largest ratio of deep rooting, influenced the predicted drought-stress perception levels. Conclusion We identified DSBM genes and developed a machine learning model as a robust tool for assessing drought-stress perception levels in rice. Monitoring and predicting drought-stress perception levels should contribute to more efficient crop management and breeding schemes. Furthermore, our dataset would serve as a resource for further understanding the mechanisms of drought resistance in rice.
2025-07-30 | GSE288615 | GEO
Project description:Background Drought is a global challenge that severely restricts crop yields and threatens food security. Plants respond to drought stress by modulating gene expression before visible phenotypic changes occur. However, most studies of drought resistance have examined phenotypes after drought treatment, with little emphasis on how severely the plants were perceiving drought-stress conditions before the appearance of stress symptoms. We therefore developed drought-stress biomarkers (DSBMs) to detect drought-stress perception levels based on gene expression profiles by performing time-series transcriptome analysis and phenotypic analysis of rice (Oryza sativa) under drought conditions in the growth chamber. Results Time-series RNA-seq of the drought-susceptible rice cultivar IR64 revealed drastic changes in the transcriptome after 4–6 days of drought treatment in plants grown in pot culture mimicking drought conditions in the field, particularly for genes related to photosynthesis. Among the differentially expressed genes, we selected 23 DSBM genes that consistently responded to drought stress. Rehydration immediately reset the changes in expression of these DSBM genes, indicating that their expression changes reflect current drought-stress perception levels, but not stress memories. Responses of DSBM genes tended to be conserved among rice accessions, irrespective of the rice subpopulation (such as indica, aus, and japonica). We developed a machine learning model using the expression levels of DSBM genes trained by the time-series RNA-seq data for IR64. This model successfully predicted the drought-stress perception levels of various rice accessions, representing the probability of exposure to drought treatment, with an accuracy of 75%. Extreme root architecture traits, such as the largest root surface area, narrowest crown root diameter, and largest ratio of deep rooting, influenced the predicted drought-stress perception levels. Conclusion We identified DSBM genes and developed a machine learning model as a robust tool for assessing drought-stress perception levels in rice. Monitoring and predicting drought-stress perception levels should contribute to more efficient crop management and breeding schemes. Furthermore, our dataset would serve as a resource for further understanding the mechanisms of drought resistance in rice.
2025-07-30 | GSE288713 | GEO
Project description:Drought stress response involves vigorous reprogramming of transcriptome while the mechanism modulating this process remains elusive. The role of 3D-genome in the regulation of rice development has recently been unveiled in rice, which exhibited characteristics distinct from that in mammals and other plants. However, the relationship between spatial chromosome organization and drought responsive gene reprogramming is still poorly understood. In this study, we identified H3K9ac as an efficient histone mark that response dynamically to drought stress in rice and re-constructed high-resolution 3D genome contact maps based on these sites under the normal, drought, and recovery conditions. We discovered significant decondensation of chromatin contacts with over 10000 chromatin loops lost upon drought stress treatment while the recovery of 3D genome was limited after 4-day’s re-watering. We identified dominate promoter-promoter interacting (PPI) loops under each condition and identified their significant correlations to altered gene expressions in response to the corresponding condition. Based on the relative contact intensities of the PPI connections, we characterized super-promoter regions that integrate closer connections of genes with more vigorous inductions to condition shifts. Especially, about 75% of the drought stress-dominate PPI loops were associated to the binding by a well-defined drought stress-responsive transcription factor, OsbZIP23. The mutation of OsbZIP23 led to the diffuse of over 80% DS-dominate PPI loops and impaired the expression of the connected genes. As a case study, we showed how OsbZIP23 binding to a super-promoter region can integrate the PPI loop formation and transcriptional activation of four function-vital dehydrin genes upon drought stress. Our results shed light on the mechanisms of 3D genome dynamic in response to water supply variations in rice and highlight the role of OsbZIP23 in the regulation of chromatin loop formation under drought stress.
2024-09-19 | GSE242459 | GEO
Project description:Drought stress response involves vigorous reprogramming of transcriptome while the mechanism modulating this process remains elusive. The role of 3D-genome in the regulation of rice development has recently been unveiled in rice, which exhibited characteristics distinct from that in mammals and other plants. However, the relationship between spatial chromosome organization and drought responsive gene reprogramming is still poorly understood. In this study, we identified H3K9ac as an efficient histone mark that response dynamically to drought stress in rice and re-constructed high-resolution 3D genome contact maps based on these sites under the normal, drought, and recovery conditions. We discovered significant decondensation of chromatin contacts with over 10000 chromatin loops lost upon drought stress treatment while the recovery of 3D genome was limited after 4-day’s re-watering. We identified dominate promoter-promoter interacting (PPI) loops under each condition and identified their significant correlations to altered gene expressions in response to the corresponding condition. Based on the relative contact intensities of the PPI connections, we characterized super-promoter regions that integrate closer connections of genes with more vigorous inductions to condition shifts. Especially, about 75% of the drought stress-dominate PPI loops were associated to the binding by a well-defined drought stress-responsive transcription factor, OsbZIP23. The mutation of OsbZIP23 led to the diffuse of over 80% DS-dominate PPI loops and impaired the expression of the connected genes. As a case study, we showed how OsbZIP23 binding to a super-promoter region can integrate the PPI loop formation and transcriptional activation of four function-vital dehydrin genes upon drought stress. Our results shed light on the mechanisms of 3D genome dynamic in response to water supply variations in rice and highlight the role of OsbZIP23 in the regulation of chromatin loop formation under drought stress.
2024-09-19 | GSE242455 | GEO