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Meta-Analysis of Microarray Data of Rainbow Trout Fry Gonad Differentiation Modulated by Ethynylestradiol

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Listed:
  • Sophie Depiereux
  • Florence Le Gac
  • Bertrand De Meulder
  • Michael Pierre
  • Raphaël Helaers
  • Yann Guiguen
  • Patrick Kestemont
  • Eric Depiereux

Abstract

Sex differentiation in fish is a highly labile process easily reversed by the use of exogenous hormonal treatment and has led to environmental concerns since low doses of estrogenic molecules can adversely impact fish reproduction. The goal of this study was to identify pathways altered by treatment with ethynylestradiol (EE2) in developing fish and to find new target genes to be tested further for their possible role in male-to-female sex transdifferentiation. To this end, we have successfully adapted a previously developed bioinformatics workflow to a meta-analysis of two datasets studying sex reversal following exposure to EE2 in juvenile rainbow trout. The meta-analysis consisted of retrieving the intersection of the top gene lists generated for both datasets, performed at different levels of stringency. The intersecting gene lists, enriched in true positive differentially expressed genes (DEGs), were subjected to over-representation analysis (ORA) which allowed identifying several statistically significant enriched pathways altered by EE2 treatment and several new candidate pathways, such as progesterone-mediated oocyte maturation and PPAR signalling. Moreover, several relevant key genes potentially implicated in the early transdifferentiation process were selected. Altogether, the results show that EE2 has a great effect on gene expression in juvenile rainbow trout. The feminization process seems to result from the altered transcription of genes implicated in normal female gonad differentiation, resulting in expression similar to that observed in normal females (i.e. the repression of key testicular markers cyp17a1, cyp11b, tbx1), as well as from other genes (including transcription factors) that respond specifically to the EE2 treatment. The results also showed that the bioinformatics workflow can be applied to different types of microarray platforms and could be generalized to (eco)toxicogenomics studies for environmental risk assessment purposes.

Suggested Citation

  • Sophie Depiereux & Florence Le Gac & Bertrand De Meulder & Michael Pierre & Raphaël Helaers & Yann Guiguen & Patrick Kestemont & Eric Depiereux, 2015. "Meta-Analysis of Microarray Data of Rainbow Trout Fry Gonad Differentiation Modulated by Ethynylestradiol," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-27, September.
    • Handle: RePEc:plo:pone00:0135799
    DOI: 10.1371/journal.pone.0135799
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    References listed on IDEAS

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    1. Smyth Gordon K, 2004. "Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 3(1), pages 1-28, February.
    2. Bertrand De Meulder & Fabrice Berger & Eric Bareke & Sophie Depiereux & Carine Michiels & Eric Depiereux, 2014. "Meta-Analysis and Gene Set Analysis of Archived Microarrays Suggest Implication of the Spliceosome in Metastatic and Hypoxic Phenotypes," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-13, January.
    3. Opgen-Rhein Rainer & Strimmer Korbinian, 2007. "Accurate Ranking of Differentially Expressed Genes by a Distribution-Free Shrinkage Approach," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 6(1), pages 1-20, February.
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