Eutrophic water under eCO2 condition
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ABSTRACT:
PROVIDER: PRJNA546038 | ENA |
REPOSITORIES: ENA
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Project description:A cultivation facility that can assist users in controlling the soil water condition is needed for accurately phenotyping plants under drought stress in an artificial environment. Here we report the Internet of Things (IoT)-based pot system controlling optional treatment of soil water condition (iPOTs), an automatic irrigation system that mimics the drought condition in a growth chamber. The Wi-Fi-enabled iPOTs system allows water supply from the bottom of the pot, based on the soil water level set by the user, and automatically controls the soil water level at a desired depth. The iPOTs also allows users to monitor environmental parameters, such as soil temperature, air temperature, humidity, and light intensity, in each pot. To verify whether the iPOTs mimics the drought condition, we conducted a drought stress test on rice varieties and near-isogenic lines, with diverse root system architecture, using the iPOTs system installed in a growth chamber. Similar to the results of a previous drought stress field trial, the growth of shallow-rooted rice accessions was severely affected by drought stress compared with that of deep-rooted accessions. The microclimate data obtained using the iPOTs system increased the accuracy of plant growth evaluation. Transcriptome analysis revealed that pot positions in the growth chamber had little impact on plant growth. Together, these results suggest that the iPOTs system represents a reliable platform for phenotyping plants under drought stress.
2021-08-24 | GSE171578 | GEO
Project description:One of the serious constraints to realize high level of rice crop productivity in agriculture has been due to Soil Water Stress (SWS) situation that growing plants often face. In order to increase or maintain the crop productivity in SWS situation, our initial aim is to understand the drought response mechanism in different genotypes of rice. For thorough analysis of SWS situation in rice we have taken here two wild genotypes of rice namely Oryza nivara, Oryza rufipogon and three Oryza sativa indica cultivars namely Nagina-22, IR20 and Vandana, where IR20 is known to be susceptible and Vandana is known to be tolerant under SWS condition [GSE49364 and the current study]. Global analysis of transcript profiling under SWS condition reveal the actual picture of genes responsive to stress situation in different genetic background of rice. Furthermore it would help us in the selection of most desirable resource for crop breeding without compromising the yield of crop. We used the 44k rice Oligoarray from Agilent technologies to study the expression profiles from five rice genotypes during vegetative (Veg) and grain-filling (GF) stages under varying water conditions, viz. Before Stress (BS), After Stress (AS) and After Recovery (AR).
2016-04-01 | GSE63718 | GEO
Project description:Mesotrophic and eutrophic lakes metagenome Raw sequence reads
| PRJNA449138 | ENA
Project description:Mesotrophic and eutrophic lakes metagenome Raw sequence reads
| PRJNA448990 | ENA
Project description:Interventions: ESD for colorectal tumors using conventional methods.
ESD for colorectal tumors using the under water method.
Primary outcome(s): Completion rate of under water ESD by non-expert
Study Design: Parallel Non-randomized
| 2656206 | ecrin-mdr-crc
Project description:Genome-wide transcriptome analysis was performed to understand the expression pattern of transcriptomes in tolerant and susceptible subtropical maize genotypes under water deficit stress condition.<br><br>
2014-10-11 | E-MEXP-3992 | biostudies-arrayexpress
Project description:Drought is one of the most serious abiotic stresses, under which the crop yield is significantly reduced. Elite winter wheat cultivar Henong 341 (Triticum aestivum L.) was grown in experimental fields of China Hebei province (116°37′23″E, 37°41′02″N) Two different treatment conditions were designed: rain-fed (no water irrigation) and well-watered (water irrigation) conditions at jointing and flowering stages. Each treatment included three biological replicates and each plot was 25m2. In this study, a comprehensive phosphoproteomic analysis of developing grains of 26th day after flowering (DAF) in Chinese bread wheat cultivar Henong 341 under well-watered and water-deficit conditions was performed by means of TiO2 enrichment, LC/MS/MS analysis, and Label-free peptide-intensity quantification. Under well-watered conditions, a total of 590 unique phosphopeptides corresponding to 603 nonredundant phosphorylation sites, representing 471 phosphoproteins, were identified. While under water deficit, 63 unique phosphopeptides, corresponding to 61 phosphoproteins, were found to be differently regulated in phosphorylation status compared to well-watered conditions (≥2 fold intensities).
2016-07-09 | PXD000806 | Pride
Project description:Purpose: The purpose of this study are to identify the miRNA involved in regulating the production of metabolites in Chlorella sorokiniana and Chlorella zofingiensis under normal and stress-induced condition through RNA-sequencing technique. Methods: miRNA transcriptome profile from normal and stress sample of C. sorokiniana and C. zofingiensis were generated, in triplicate, using Illumina Miseq. The sequence reads that passed quality filters were analysed using CLC genomic workbench and OmiRas. Results: The known and predicted novel miRNAs were identified. Although most of the identified miRNAs were not functionally determined, this study suggests that they were species-specific, which may have roles in regulating genes during stress related condition.
2022-10-01 | GSE107372 | GEO
Project description:This project contains two experimental proteome, one of which is that Methanosarcina barkeri MS was grown in 10 and 50 mM acetate, respectively. And in the second experiment, M.barkeri MS was grown in 1 and 7 g-N/L, respectively, where the acetate concentration was 10 mM. In order to study how this species cope with stress in molecular level, samples were collected for proteomics under each condition. This is raw data of the proteome.
2019-03-25 | PXD013207 | iProX