ArticlePloS one2020
Statistical differences resulting from selection of stable reference genes after hypoxia and hypothermia in the neonatal rat brain.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- A systematic review on the selection of reference genes for gene expression studies in rodents: are the classics the best choice?Molecular biology reports · 2024Pooled it
- The Expression Patterns of Reference Genes in the Brains of Male Rats Subjected to CUMS-induced Depressive-like Behavior Strongly Depends on both the Age and the Specific Brain Region.Journal of molecular neuroscience : MN · 2026Article
- Nicorandil treatment improves survival and spatial learning in aged granulin knockout mice.Brain pathology (Zurich, Switzerland) · 2025Article
- Evaluation of suitable reference genes for gene expression studies in the developing mouse cortex using RT-qPCR.BMC neuroscience · 2025Article
- Reference Gene Validation in the Embryonic and Postnatal Brain in the Rat Hyperhomocysteinemia Model.Neurotoxicity research · 2024Article
- Optimal Reference Genes for RT-qPCR Experiments in Hippocampus and Cortex of Rats Chronically Exposed to Excessive Fluoride.Biological trace element research · 2024Article
- Impact of thyroid hormone perturbations in adult mice: brain weight and blood vessel changes, gene expression variation, and neurobehavioral outcomes.Neurobiology of aging · 2023Article
- Modulating Thyroid Hormone Levels in Adult Mice: Impact on Behavior and Compensatory Brain Changes.Journal of thyroid research · 2021Article
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Authors and funding
7 authors at 5 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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