Statistical differences resulting from selection of stable reference genes after hypoxia and hypothermia in the neonatal rat brain.

Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Original Publication: San Francisco, CA : Public Library of Science

Genes, Essential*; Brain/*metabolism ; Gene Expression Profiling/*methods ; Hypothermia/*genetics ; Hypoxia, Brain/*genetics; Animals ; Animals, Newborn ; Gene Expression ; Hypothermia/metabolism ; Hypoxia, Brain/metabolism ; Rats ; Real-Time Polymerase Chain Reaction/methods ; Reproducibility of Results

Competing Interests: The authors have declared that no competing interests exist.
Real-time reverse transcription PCR (qPCR) normalized to an internal reference gene (RG), is a frequently used method for quantifying gene expression changes in neuroscience. Although RG expression is assumed to be constant independent of physiological or experimental conditions, several studies have shown that commonly used RGs are not expressed stably. The use of unstable RGs has a profound effect on the conclusions drawn from studies on gene expression, and almost universally results in spurious estimation of target gene expression. Approaches aimed at selecting and validating RGs often make use of different statistical methods, which may lead to conflicting results. Based on published RG validation studies involving hypoxia the present study evaluates the expression of 5 candidate RGs (Actb, Pgk1, Sdha, Gapdh, Rnu6b) as a function of hypoxia exposure and hypothermic treatment in the neonatal rat cerebral cortex-in order to identify RGs that are stably expressed under these experimental conditions-using several statistical approaches that have been proposed to validate RGs. In doing so, we first analyzed RG ranking stability proposed by several widely used statistical methods and related tools, i.e. the Coefficient of Variation (CV) analysis, GeNorm, NormFinder, BestKeeper, and the ΔCt method. Using the Geometric mean rank, Pgk1 was identified as the most stable gene. Subsequently, we compared RG expression patterns between the various experimental groups. We found that these statistical methods, next to producing different rankings per se, all ranked RGs displaying significant differences in expression levels between groups as the most stable RG. As a consequence, when assessing the impact of RG selection on target gene expression quantification, substantial differences in target gene expression profiles were observed. Altogether, by assessing mRNA expression profiles within the neonatal rat brain cortex in hypoxia and hypothermia as a showcase, this study underlines the importance of further validating RGs for each individual experimental paradigm, considering the limitations of the statistical methods used for this aim.

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Date Created: 20200522 Date Completed: 20200812 Latest Revision: 20200812

20250114

PMC7241816

10.1371/journal.pone.0233387

32437382