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缺氧和低温处理新生大鼠脑后,稳定参考基因的选择所导致的统计学差异。

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

机构信息

Department of Pediatrics, Maastricht University Medical Center (MUMC), Maastricht, The Netherlands.

Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands.

出版信息

PLoS One. 2020 May 21;15(5):e0233387. doi: 10.1371/journal.pone.0233387. eCollection 2020.

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.

摘要

实时逆转录聚合酶链反应(qPCR)标准化到内部参考基因(RG),是一种常用于定量神经科学中基因表达变化的方法。尽管 RG 表达被假定为在生理或实验条件下是恒定的,但几项研究表明,常用的 RG 并不稳定表达。使用不稳定的 RG 会对基于基因表达的研究得出的结论产生深远的影响,并且几乎普遍导致对靶基因表达的虚假估计。旨在选择和验证 RG 的方法通常利用不同的统计方法,这可能导致相互矛盾的结果。基于涉及缺氧的 RG 验证研究,本研究评估了 5 种候选 RG(Actb、Pgk1、Sdha、Gapdh、Rnu6b)的表达,作为其在新生大鼠大脑皮质中暴露于缺氧和低温处理的函数,以鉴定在这些实验条件下稳定表达的 RG-使用几种已被提出用于验证 RG 的统计方法。在这样做的过程中,我们首先分析了几种广泛使用的统计方法和相关工具提出的 RG 排名稳定性,即变异系数(CV)分析、GeNorm、NormFinder、BestKeeper 和 ΔCt 方法。使用几何平均秩,鉴定 Pgk1 为最稳定的基因。随后,我们比较了不同实验组之间 RG 的表达模式。我们发现,这些统计方法除了本身产生不同的排名外,还将显示组间表达水平显著差异的 RG 全部排名为最稳定的 RG。因此,当评估 RG 选择对靶基因表达定量的影响时,观察到靶基因表达谱有很大差异。总之,通过评估新生大鼠大脑皮质在缺氧和低温下的 mRNA 表达谱作为展示,本研究强调了为每个特定的实验范例进一步验证 RG 的重要性,同时考虑到为此目的使用的统计方法的局限性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/158b/7241816/af58d8c4f6aa/pone.0233387.g001.jpg

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