ArticleEnvironmental toxicology and chemistry2017
Tools to minimize interlaboratory variability in vitellogenin gene expression monitoring programs.
Article in Environmental toxicology and chemistry, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Effects-based monitoring of bioactive compounds associated with municipal wastewater treatment plant effluent discharge to the South Platte River, Colorado, USA.Environmental pollution (Barking, Essex : 1987) · 2021Article
- Effects-Based Monitoring of Bioactive Chemicals Discharged to the Colorado River before and after a Municipal Wastewater Treatment Plant Replacement.Environmental science & technology · 2021Article
- Twenty years of transcriptomics, 17alpha-ethinylestradiol, and fish.General and comparative endocrinology · 2020Review
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10 authors.
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Abstract
The egg yolk precursor protein vitellogenin is widely used as a biomarker of estrogen exposure in male fish. However, standardized methodology is lacking and little is known regarding the reproducibility of results among laboratories using different equipment, reagents, protocols, and data analysis programs. To address this data gap we tested the reproducibility across laboratories to evaluate vitellogenin gene (vtg) expression and assessed the value of using a freely available software data analysis program. Samples collected from studies of male fathead minnows (Pimephales promelas) exposed to 17α-ethinylestradiol (EE2) and minnows exposed to processed wastewater effluent were evaluated for vtg expression in 4 laboratories. Our results indicate reasonable consistency among laboratories if the free software for expression analysis LinRegPCR is used, with 3 of 4 laboratories detecting vtg in fish exposed to 5 ng/L EE2 (n = 5). All 4 laboratories detected significantly increased vtg levels in 15 male fish exposed to wastewater effluent compared with 15 male fish held in a control stream. Finally, we were able to determine that the source of high interlaboratory variability from complementary deoxyribonucleic acid (cDNA) to quantitative polymerase chain reaction (qPCR) analyses was the expression analysis software unique to each real-time qPCR machine. We successfully eliminated the interlaboratory variability by reanalyzing raw fluorescence data with independent freeware, which yielded cycle thresholds and polymerase chain reaction (PCR) efficiencies that calculated results independently of proprietary software. Our results suggest that laboratories engaged in monitoring programs should validate their PCR protocols and analyze their gene expression data following the guidelines established in the present study for all gene expression biomarkers. Environ Toxicol Chem 2017;36:3102-3107. Published 2017 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.
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