Literature DB >> 26363320

Ecotoxicogenomics: Microarray interlaboratory comparability.

Doris E Vidal-Dorsch1, Steven M Bay2, Shelly Moore2, Blythe Layton2, Alvine C Mehinto2, Chris D Vulpe3, Marianna Brown-Augustine3, Alex Loguinov3, Helen Poynton4, Natàlia Garcia-Reyero5, Edward J Perkins6, Lynn Escalon6, Nancy D Denslow7, Colli-Dula R Cristina8, Tri Doan9, Shweta Shukradas10, Joy Bruno11, Lorraine Brown11, Graham Van Agglen11, Paula Jackman12, Megan Bauer12.   

Abstract

Transcriptomic analysis can complement traditional ecotoxicology data by providing mechanistic insight, and by identifying sub-lethal organismal responses and contaminant classes underlying observed toxicity. Before transcriptomic information can be used in monitoring and risk assessment, it is necessary to determine its reproducibility and detect key steps impacting the reliable identification of differentially expressed genes. A custom 15K-probe microarray was used to conduct transcriptomics analyses across six laboratories with estuarine amphipods exposed to cyfluthrin-spiked or control sediments (10 days). Two sample types were generated, one consisted of total RNA extracts (Ex) from exposed and control samples (extracted by one laboratory) and the other consisted of exposed and control whole body amphipods (WB) from which each laboratory extracted RNA. Our findings indicate that gene expression microarray results are repeatable. Differentially expressed data had a higher degree of repeatability across all laboratories in samples with similar RNA quality (Ex) when compared to WB samples with more variable RNA quality. Despite such variability a subset of genes were consistently identified as differentially expressed across all laboratories and sample types. We found that the differences among the individual laboratory results can be attributed to several factors including RNA quality and technical expertise, but the overall results can be improved by following consistent protocols and with appropriate training. Published by Elsevier Ltd.

Entities:  

Keywords:  Amphipod; Ecotoxicogenomics; Gene expression; Inter- and intra-laboratory reproducibility; Intercalibration; Microarray

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Substances:

Year:  2015        PMID: 26363320     DOI: 10.1016/j.chemosphere.2015.08.019

Source DB:  PubMed          Journal:  Chemosphere        ISSN: 0045-6535            Impact factor:   7.086


  4 in total

Review 1.  From the exposome to mechanistic understanding of chemical-induced adverse effects.

Authors:  Beate I Escher; Jörg Hackermüller; Tobias Polte; Stefan Scholz; Achim Aigner; Rolf Altenburger; Alexander Böhme; Stephanie K Bopp; Werner Brack; Wibke Busch; Marc Chadeau-Hyam; Adrian Covaci; Adolf Eisenträger; James J Galligan; Natalia Garcia-Reyero; Thomas Hartung; Michaela Hein; Gunda Herberth; Annika Jahnke; Jos Kleinjans; Nils Klüver; Martin Krauss; Marja Lamoree; Irina Lehmann; Till Luckenbach; Gary W Miller; Andrea Müller; David H Phillips; Thorsten Reemtsma; Ulrike Rolle-Kampczyk; Gerrit Schüürmann; Benno Schwikowski; Yu-Mei Tan; Saskia Trump; Susanne Walter-Rohde; John F Wambaugh
Journal:  Environ Int       Date:  2016-12-08       Impact factor: 9.621

2.  How consistent are we? Interlaboratory comparison study in fathead minnows using the model estrogen 17α-ethinylestradiol to develop recommendations for environmental transcriptomics.

Authors:  April Feswick; Meghan Isaacs; Adam Biales; Robert W Flick; David C Bencic; Rong-Lin Wang; Chris Vulpe; Marianna Brown-Augustine; Alex Loguinov; Francesco Falciani; Philipp Antczak; John Herbert; Lorraine Brown; Nancy D Denslow; Kevin J Kroll; Candice Lavelle; Viet Dang; Lynn Escalon; Natàlia Garcia-Reyero; Christopher J Martyniuk; Kelly R Munkittrick
Journal:  Environ Toxicol Chem       Date:  2017-04-19       Impact factor: 3.742

3.  The Transcriptome of the Zebrafish Embryo After Chemical Exposure: A Meta-Analysis.

Authors:  Andreas Schüttler; Kristin Reiche; Rolf Altenburger; Wibke Busch
Journal:  Toxicol Sci       Date:  2017-06-01       Impact factor: 4.849

4.  Evolutionary toxicology in an omics world.

Authors:  Elias M Oziolor; John W Bickham; Cole W Matson
Journal:  Evol Appl       Date:  2017-02-20       Impact factor: 5.183

  4 in total

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