ArticleEnvironmental science and pollution research international2018
Fishing for contaminants: identification of three mechanism specific transcriptome signatures using Danio rerio embryos.
Article in Environmental science and pollution research international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Editorial: Special Issue "Effect-related evaluation of anthropogenic trace substances-concepts for genotoxicity, neurotoxicity and endocrine effects".Environmental science and pollution research international · 2018Article
- Transcriptional changes measured in rice roots after exposure to arsenite-contaminated sediments.Environmental science and pollution research international · 2018Article
- Towards a holistic and solution-oriented monitoring of chemical status of European water bodies: how to support the EU strategy for a non-toxic environment?Environmental sciences Europe · 2018Article
- PI3K and Inhibitor of Apoptosis Proteins Modulate Gentamicin- Induced Hair Cell Death in the Zebrafish Lateral Line.Frontiers in cellular neuroscience · 2017Article
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Authors and funding
12 authors.
Funding
Abstract
In ecotoxicology, transcriptomics is an effective way to detect gene expression changes in response to environmental pollutants. Such changes can be used to identify contaminants or contaminant classes and can be applied as early warning signals for pollution. To do so, it is important to distinguish contaminant-specific transcriptomic changes from genetic alterations due to general stress. Here we present a first step in the identification of contaminant class-specific transcriptome signatures. Embryos of zebrafish (Danio rerio) were exposed to three substances (methylmercury, chlorpyrifos and Aroclor 1254, each from 24 to 48 hpf exposed) representing sediment typical contaminant classes. We analyzed the altered transcriptome to detect discriminative genes significantly regulated in reaction to the three applied contaminants. By comparison of the results of the three contaminants, we identified transcriptome signatures and biologically important pathways (using Cytoscape/ClueGO software) that react significantly to the contaminant classes. This approach increases the chance of finding genes that play an important role in contaminant class-specific pathways rather than more general processes.
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