Daphnia magna
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ABSTRACT:
PROVIDER: PRJNA327219 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:This experiment was conducted to study the short-term (12h) transcriptional responses in Daphnia magna after exposure to the anti-sea lice chemical emamectin benzoate (EMB). The microarray results were further vefiried using qPCR. The gene exression responses were linked to adverse effects after 48h exposure, in order to supply knowledge for environmental hazard assessment of this chemical in non-target crustaceans. Neonatal (<24h) Daphnia magna were exposed to 7.8-2000 pM waterborne emamectin benzoate for 12h. Microarray analysis was performed using pooled whole-organism D. magna (8 individuals) and 4 biological replicates were analyzed for each treatment group.
2016-06-30 | E-GEOD-83859 | biostudies-arrayexpress
Project description:This experiment was conducted to study the short-term (12h) transcriptional responses in Daphnia magna after exposure to the anti-sea lice chemical emamectin benzoate (EMB). The microarray results were further vefiried using qPCR. The gene exression responses were linked to adverse effects after 48h exposure, in order to supply knowledge for environmental hazard assessment of this chemical in non-target crustaceans.
2016-06-30 | GSE83859 | GEO
Project description:We determined lithium cobalt oxide LCO’s effects on pathways in the model organism Daphnia magna through RNA-Seq global gene expression analysis.
2022-05-03 | GSE174016 | GEO
Project description:Daphnia magna is a widely used model organism in ecological and evolutionary studies. DNA methylation in D. magna can influence development and adaptation to changing environments. Previous studies have demonstrated that D. magna is generally hypomethylated. In this study we confirmed these observations using whole genome bisulfite sequencing (WGBS). In line with previous studies we observe that DNA methylation is elevated in the first exons downstream of the transcription start sites (TSS). Moreover, these exons are hypermethylated compared to adjacent introns. In contrast to prior studies in Daphnia, we found no significant changes in DNA methylation with age. These observations extend our understanding of the epigenetic landscape in D. magna, and motivate further exploration of epigenetic regulation in this organism and its response to environmental factors.
2024-07-05 | GSE267859 | GEO
Project description:In the past years, the research focus on the effects of microplastics (MP) on aquatic organisms extended from marine systems towards freshwater systems. An important freshwater model organism in the MP field is the cladoceran Daphnia, which plays a central role in lacustrine ecosystems and has been established as a test organism in ecotoxicology. To investigate the effects of MP on Daphnia magna, we performed a chronic exposure experiment with polystyrene MP under strictly standardized conditions. Chronic exposure of D. magna to PS microparticles led to a significant reduction in body length and number of offspring. To shed light on underlying molecular mechanisms induced by microplastic ingestion in D. magna, we assessed the effects of PS-MP at the proteomic level.
2021-07-07 | PXD025108 | Pride
Project description:Daphnia magna is a bio-indicator organism accepted by several international water quality regulatory agencies. Current approaches for assessment of water quality rely on acute and chronic toxicity that provide no insight into the cause of toxicity. Recently, molecular approaches, such as genome wide gene expression responses, are enabling an alternative mechanism based approach to toxicity assessment. While these genomic methods are providing important mechanistic insight into toxicity, statistically robust prediction systems that allow the identification of chemical contaminants from the molecular response to exposure are needed. Here we apply advanced machine learning approaches to develop predictive models of contaminant exposure using a D. magna gene expression dataset for 36 chemical exposures. We demonstrate here that we can discriminate between chemicals belonging to different chemical classes including endocrine disruptors, metals and industrial chemicals based on gene expression. We also show that predictive models based on indices of whole pathway transcriptional activity can achieve comparable results while facilitating biological interpretability. D. magna were exposed to 36 Chemicals and 5 control series in quadruplicate.
2013-01-17 | E-GEOD-43564 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the following subset Series: GSE29854: Daphnia magna exposed to narcotics and polar narcotics - aniline GSE29856: Daphnia magna exposed to narcotics and polar narcotics - 4-chloroaniline GSE29857: Daphnia magna exposed to narcotics and polar narcotics - 3,5-dichloroaniline GSE29858: Daphnia magna exposed to narcotics and polar narcotics - 2,3,4-trichloroaniline GSE29862: Daphnia magna exposed to narcotics and polar narcotics - ethanol GSE29864: Daphnia magna exposed to narcotics and polar narcotics - isopropanol GSE29867: Daphnia magna exposed to narcotics and polar narcotics - methanol Refer to individual Series
2012-02-01 | E-GEOD-29993 | biostudies-arrayexpress
Project description:Daphnia magna is a bio-indicator organism accepted by several international water quality regulatory agencies. Current approaches for assessment of water quality rely on acute and chronic toxicity that provide no insight into the cause of toxicity. Recently, molecular approaches, such as genome wide gene expression responses, are enabling an alternative mechanism based approach to toxicity assessment. While these genomic methods are providing important mechanistic insight into toxicity, statistically robust prediction systems that allow the identification of chemical contaminants from the molecular response to exposure are needed. Here we apply advanced machine learning approaches to develop predictive models of contaminant exposure using a D. magna gene expression dataset for 36 chemical exposures. We demonstrate here that we can discriminate between chemicals belonging to different chemical classes including endocrine disruptors, metals and industrial chemicals based on gene expression. We also show that predictive models based on indices of whole pathway transcriptional activity can achieve comparable results while facilitating biological interpretability.
2013-01-17 | GSE43564 | GEO
Project description:Deep metabolome annotation of model organism Daphnia magna
2024-06-07 | MSV000094957 | GNPS
Project description:Background: Toxicogenomics provides new opportunities for innovative and proactive approaches to chemical screening, risk assessment, and predictive toxicology. If applied to ecotoxicology, genomics tools could greatly enhance the ability to detect toxicants and understand the modes of toxicity in an environmental setting. However, few studies have yet to illustrate the potential of genomic techniques in ecotoxicology. Objective: Therefore, our objective was to demonstrate the potential utility of gene expression profiling in ecotoxicology using Daphnia magna, a standard aquatic ecotoxicity test organism. Methods: D. magna were exposed to copper, cadmium, and zinc at the 1/10 LC50 for 24 hours. Following each exposure, RNA was isolated, reverse transcribed, and the cDNA was hybridized to a 5000 clone cDNA microarray for D. magna. Differentially expressed cDNAs were sequenced and homology searches revealed each gene product's potential function. Real time PCR was used to verify the differential expression of several genes, and enzyme assays were used to assess the significance of these changes. Results: We identified distinct expression profiles in response to acute copper, cadmium, and zinc exposures and discovered specific biomarkers of exposure including two probable metallothioneins, and a ferritin mRNA with a functional IRE. The gene expression patterns support known mechanisms of metal toxicity and reveal novel modes of action including zinc inhibition of chitinase activity. Conclusions: Using a cDNA microarray for traditional ecotoxicology organism, D. magna, we have identified novel biomarkers of exposure and revealed possible modes of toxicity, providing experimental support for the utility of ecotoxicogenomics. Keywords: comparative toxicant exposure
2006-12-22 | GSE4759 | GEO