Ontology highlight
ABSTRACT:
PROVIDER: PRJNA680158 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13167485_1.fastq.gz | Fastqsanger.gz | |||
| SRR13167485_2.fastq.gz | Fastqsanger.gz | |||
| SRR13167486_1.fastq.gz | Fastqsanger.gz | |||
| SRR13167486_2.fastq.gz | Fastqsanger.gz | |||
| SRR13167487_1.fastq.gz | Fastqsanger.gz |
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Project description:Traditional biomarkers for hydrocarbon exposure are not induced by all petroleum substances. The objective of this study was to determine if exposure to a crude oil and different refined oils would generate a common hydrocarbon-specific response in gene expression profiles that could be used as generic biomarkers of hydrocarbon exposure. Juvenile rainbow trout (Oncorhynchus mykiss) were exposed to the water accommodated fraction (WAF) of either kerosene, gas oil, heavy fuel oil, or crude oil for 96 hours. Tissue was collected for RNA extraction and microarray analysis. Exposure to each WAF resulted in a different list of differentially regulated genes, with few genes in common across treatments. Exposure to crude oil WAF changed the expression of genes including CYP1A and GST with known roles in detoxification pathways. These gene expression profiles were compared to others from previous experiments which used a diverse suite of toxicants. Clustering algorithms successfully i dentified gene expression profiles resulting from hydrocarbon exposure. These preliminary analyses highlight the difficulties of using single genes as diagnostic of petroleum hydrocarbon exposures. Further work is needed to determine if multivariate transcriptomic-based biomarkers may be a more effective tool than single gene studies for exposure monitoring of different oils. Two channel experiment; control versus exposed (samples were time matched). 3 biological replicates, three technical replicates for both exposed and control fish. Samples were paired at random. One replicate per array
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