How consistent are we? Interlaboratory comparison study in fathead minnows using the model estrogen 17α-ethinylestradiol to develop recommendations for environmental transcriptomics.
Fundamental questions remain about the application of omics in environmental risk assessments, such as the consistency of data across laboratories. The objective of the present study was to determine the congruence of transcript data across 6 independent laboratories. Male fathead minnows were exposed to a measured concentration of 15.8 ng/L 17α-ethinylestradiol (EE2) for 96 h. Livers were divided equally and sent to the participating laboratories for transcriptomic analysis using the same fathead minnow microarray. Each laboratory was free to apply bioinformatics pipelines of its choice. There were 12 491 transcripts that were identified by one or more of the laboratories as responsive to EE2. Of these, 587 transcripts (4.7%) were detected by all laboratories. Mean overlap for differentially expressed genes among laboratories was approximately 50%, which improved to approximately 59.0% using a standardized analysis pipeline. The dynamic range of fold change estimates was variable between laboratories, but ranking transcripts by their relative fold difference resulted in a positive relationship for comparisons between any 2 laboratories (mean R2> 0.9, p < 0.001). Ten estrogen-responsive genes encompassing a fold change range from dramatic (>20-fold; e.g., vitellogenin) to subtle (∼2-fold; i.e., block of proliferation 1) were identified as differentially expressed, suggesting that laboratories can consistently identify transcripts that are known a priori to be perturbed by a chemical stressor. Thus, attention should turn toward identifying core transcriptional networks using focused arrays for specific chemicals. In addition, agreed-on bioinformatics pipelines and the ranking of genes based on fold change (as opposed to p value) should be considered in environmental risk assessment. These recommendations are expected to improve comparisons across laboratories and advance the use of omics in regulations. Environ Toxicol Chem 2017;36:2593-2601. © 2017 SETAC.
Department of Biology, University of New Brunswick, Saint John, New Brunswick, Canada.
April
A
Feswick
Department of Biology, University of New Brunswick, Saint John, New Brunswick, Canada.
Meghan
M
Isaacs
Molecular Indicators Research Branch, National Exposure Research Laboratory, Cincinnati, Ohio, USA.
Adam
A
Biales
Molecular Indicators Research Branch, National Exposure Research Laboratory, Cincinnati, Ohio, USA.
Robert W
RW
Flick
Molecular Indicators Research Branch, National Exposure Research Laboratory, Cincinnati, Ohio, USA.
David C
DC
Bencic
Molecular Indicators Research Branch, National Exposure Research Laboratory, Cincinnati, Ohio, USA.
Rong-Lin
RL
Wang
Department of Nutritional Science and Toxicology, University of California-Berkeley, Berkeley, California, USA.
Chris
C
Vulpe
Department of Nutritional Science and Toxicology, University of California-Berkeley, Berkeley, California, USA.
Marianna
M
Brown-Augustine
Department of Nutritional Science and Toxicology, University of California-Berkeley, Berkeley, California, USA.
Alex
A
Loguinov
Institute of Integrative Biology, University of Liverpool, Liverpool, United Kingdom.
Francesco
F
Falciani
Institute of Integrative Biology, University of Liverpool, Liverpool, United Kingdom.
Philipp
P
Antczak
Institute of Integrative Biology, University of Liverpool, Liverpool, United Kingdom.
John
J
Herbert
Pacific Environmental Science Centre, North Vancouver, British Columbia, Canada.
Lorraine
L
Brown
Center for Environmental and Human Toxicology, Department of Physiological Sciences, UF Genetics Institute, College of Veterinary Medicine, University of Florida, Gainesville, Florida, USA.
Nancy D
ND
Denslow
Center for Environmental and Human Toxicology, Department of Physiological Sciences, UF Genetics Institute, College of Veterinary Medicine, University of Florida, Gainesville, Florida, USA.
Kevin J
KJ
Kroll
Center for Environmental and Human Toxicology, Department of Physiological Sciences, UF Genetics Institute, College of Veterinary Medicine, University of Florida, Gainesville, Florida, USA.
Candice
C
Lavelle
Center for Environmental and Human Toxicology, Department of Physiological Sciences, UF Genetics Institute, College of Veterinary Medicine, University of Florida, Gainesville, Florida, USA.
Viet
V
Dang
US Army Engineer Research & Development Center, Vicksburg, Mississippi.
Lynn
L
Escalon
US Army Engineer Research & Development Center, Vicksburg, Mississippi.|Institute for Genomics, Biocomputing and Biotechnology, Mississippi State University, Starkville, Mississippi, USA.
Natàlia
N
Garcia-Reyero
Department of Biology, University of New Brunswick, Saint John, New Brunswick, Canada.|Center for Environmental and Human Toxicology, Department of Physiological Sciences, UF Genetics Institute, College of Veterinary Medicine, University of Florida, Gainesville, Florida, USA.
Christopher J
CJ
Martyniuk
Department of Biology, University of New Brunswick, Saint John, New Brunswick, Canada.
Kelly R
KR
Munkittrick
D000818:Animals; D003530:Cyprinidae / Q000235:genetics* / Q000378:metabolism; D052244:Endocrine Disruptors / Q000633:toxicity*; D004797:Enzyme-Linked Immunosorbent Assay; D004997:Ethinyl Estradiol / Q000633:toxicity*; D007753:Laboratories / Q000592:standards*; D008099:Liver / Q000187:drug effects / Q000378:metabolism*; D008297:Male; D008956:Models, Chemical; D020411:Oligonucleotide Array Sequence Analysis; D012313:RNA / Q000302:isolation & purification / Q000378:metabolism; D059467:Transcriptome / Q000187:drug effects*; D014819:Vitellogenins / Q000097:blood
D052244:Endocrine Disruptors; D014819:Vitellogenins; D004997:Ethinyl Estradiol; D012313:RNA
Endocrine disruptor; Estrogenic compound; Interlaboratory comparison; Risk assessment; Transcriptomics