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Environ Sci Technol. 2014 Mar 18;48(6):3513-22. doi: 10.1021/es4053363. Epub 2014 Feb 26.

Genome-wide transcription profiles reveal genotype-dependent responses of biological pathways and gene-families in Daphnia exposed to single and mixed stressors.

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Laboratory of Environmental Toxicology and Aquatic Ecology, Ghent University , Gent, Belgium.


The present study investigated the possibilities and limitations of implementing a genome-wide transcription-based approach that takes into account genetic and environmental variation to better understand the response of natural populations to stressors. When exposing two different Daphnia pulex genotypes (a cadmium-sensitive and a cadmium-tolerant one) to cadmium, the toxic cyanobacteria Microcystis aeruginosa, and their mixture, we found that observations at the transcriptomic level do not always explain observations at a higher level (growth, reproduction). For example, although cadmium elicited an adverse effect at the organismal level, almost no genes were differentially expressed after cadmium exposure. In addition, we identified oxidative stress and polyunsaturated fatty acid metabolism-related pathways, as well as trypsin and neurexin IV gene-families as candidates for the underlying causes of genotypic differences in tolerance to Microcystis. Furthermore, the whole-genome transcriptomic data of a stressor mixture allowed a better understanding of mixture responses by evaluating interactions between two stressors at the gene-expression level against the independent action baseline model. This approach has indicated that ubiquinone pathway and the MAPK serine-threonine protein kinase and collagens gene-families were enriched with genes showing an interactive effect in expression response to exposure to the mixture of the stressors, while transcription and translation-related pathways and gene-families were mostly related with genotypic differences in interactive responses to this mixture. Collectively, our results indicate that the methods we employed may improve further characterization of the possibilities and limitations of transcriptomics approaches in the adverse outcome pathway framework and in predictions of multistressor effects on natural populations.

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