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American Physiological Society, Physiological Genomics, 9(47), p. 420-431, 2015

DOI: 10.1152/physiolgenomics.00123.2014

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Identification of conserved hepatic transcriptomic responses to 17β-estradiol using high-throughput sequencing in brown trout.

Journal article published in 2015 by Tm Uren Webster, Ja Shears, Karen Moore, Em Santos ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Estrogenic chemicals are major contaminants of surface waters and can threaten the sustainability of natural fish populations. Characterization of the global molecular mechanisms of toxicity of environmental contaminants has been conducted primarily in model species rather than species with limited existing transcriptomic or genomic sequence information. We aimed to investigate the global mechanisms of toxicity of an endocrine disrupting chemical of environmental concern [17β-estradiol (E2)] using high-throughput RNA sequencing (RNA-Seq) in an environmentally relevant species, brown trout ( Salmo trutta). We exposed mature males to measured concentrations of 1.94, 18.06, and 34.38 ng E2/l for 4 days and sequenced three individual liver samples per treatment using an Illumina HiSeq 2500 platform. Exposure to 34.4 ng E2/L resulted in 2,113 differentially regulated transcripts (FDR < 0.05). Functional analysis revealed upregulation of processes associated with vitellogenesis, including lipid metabolism, cellular proliferation, and ribosome biogenesis, together with a downregulation of carbohydrate metabolism. Using real-time quantitative PCR, we validated the expression of eight target genes and identified significant differences in the regulation of several known estrogen-responsive transcripts in fish exposed to the lower treatment concentrations (including esr1 and zp2.5). We successfully used RNA-Seq to identify highly conserved responses to estrogen and also identified some estrogen-responsive transcripts that have been less well characterized, including nots and tgm2l. These results demonstrate the potential application of RNA-Seq as a valuable tool for assessing mechanistic effects of pollutants in ecologically relevant species for which little genomic information is available.