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过载诱导的骨骼肌肥大中实时定量 RT-PCR 靶 mRNA 定量的陷阱。

Pitfalls in target mRNA quantification for real-time quantitative RT-PCR in overload-induced skeletal muscle hypertrophy.

机构信息

Operational environments, Genomic core facility, IRBA La Tronche, La Tronche, France.

出版信息

Physiol Genomics. 2011 Feb 24;43(4):228-35. doi: 10.1152/physiolgenomics.00109.2010. Epub 2010 Dec 14.

Abstract

Quantifying target mRNA using real-time quantitative reverse transcription-polymerase chain reaction requires an accurate normalization method. Determination of normalization factors (NFs) based on validated reference genes according to their relative stability is currently the best standard method in most usual situations. This method controls for technical errors, but its physiological relevance requires constant NF values for a fixed weight of tissue. In the functional overload model, the increase in the total RNA concentration must be considered in determining the NF values. Here, we pointed out a limitation of the classical geNorm-derived normalization. geNorm software selected reference genes despite that the NF values extensively varied under experiment. Only the NF values calculated from four intentionally selected genes were constant between groups. However, a normalization based on these genes is questionable. Indeed, three out of four genes belong to the same functional class (negative regulator of muscle mass), and their use is physiological nonsense in a hypertrophic model. Thus, we proposed guidelines for optimizing target mRNA normalization and quantification, useful in models of muscle mass modulation. In our study, the normalization method by multiple reference genes was not appropriate to compare target mRNA levels between overloaded and control muscles. A solution should be to use an absolute quantification of target mRNAs per unit weight of tissue, without any internal normalization. Even if the technical variations will stay present as a part of the intergroup variations, leading to less statistical power, we consider this method acceptable because it will not generate misleading results.

摘要

使用实时定量逆转录聚合酶链反应定量靶 mRNA 需要准确的归一化方法。根据相对稳定性确定基于经过验证的参考基因的归一化因子 (NF) 是目前大多数常见情况下的最佳标准方法。该方法控制技术误差,但需要固定组织重量的 NF 值具有生理相关性。在功能过载模型中,在确定 NF 值时必须考虑总 RNA 浓度的增加。在这里,我们指出了经典 geNorm 衍生归一化的一个局限性。geNorm 软件选择了参考基因,尽管在实验中 NF 值广泛变化。仅从四个有意选择的基因计算出的 NF 值在组间保持恒定。然而,基于这些基因的归一化是值得怀疑的。实际上,四个基因中有三个属于同一功能类别(肌肉质量负调节剂),在肥大模型中,它们的使用在生理上是没有意义的。因此,我们提出了优化靶 mRNA 归一化和定量的指南,这在肌肉质量调节模型中非常有用。在我们的研究中,使用多个参考基因的归一化方法不适合比较过载和对照肌肉中的靶 mRNA 水平。一种解决方案是使用组织单位重量的靶 mRNAs 的绝对定量,而无需任何内部归一化。即使技术变化将作为组间变化的一部分存在,导致统计能力降低,我们也认为这种方法是可以接受的,因为它不会产生误导性结果。

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