Ng Hien Fuh, Ngeow Yun Fong
Centre for Research on Communicable Diseases, Faculty of Medicine and Health Sciences, Universiti Tunku Abdul Rahman, Kajang, Selangor, Malaysia.
Biochem Mol Biol Educ. 2022 Jan;50(1):99-103. doi: 10.1002/bmb.21596. Epub 2021 Dec 2.
Relative quantification is a popular analysis in gene expression studies using quantitative real-time PCR (qPCR). However, the calculation steps using the major algorithms for this analysis are rather complicated. In this study, we developed an easy-to-use spreadsheet-based method for relative quantification. The inputs from end-users are the efficiencies of both target and reference genes and the C values of those genes from cases and controls. This method performed normalization (with one or more reference genes), calculation of fold change of gene expression, and statistical analysis to analyze the difference between the groups in a step-by-step manner, which would allow the end-users to understand how the analysis arrived at the conclusion. Four previously published data sets with different experimental designs were used as examples. The calculated results were concordant with the results computed by the Relative Expression Software Tool (REST) 2009, a popular tool for relative quantification. Altogether, our method, which offers easy-to-understand calculation steps and does not require specialized instruments, software, or expertise to operate, would be a useful tool for students, educators, and scientists in the field of molecular biology.
相对定量是使用定量实时聚合酶链反应（qPCR）进行基因表达研究时一种常用的分析方法。然而，使用该分析的主要算法进行计算的步骤相当复杂。在本研究中，我们开发了一种基于电子表格的易于使用的相对定量方法。终端用户的输入是靶基因和参照基因的效率以及这些基因在病例组和对照组中的C值。该方法进行了标准化（使用一个或多个参照基因）、基因表达倍数变化的计算以及统计分析，以逐步分析组间差异，这将使终端用户能够理解分析是如何得出结论的。四个先前发表的具有不同实验设计的数据集被用作示例。计算结果与相对表达软件工具（REST）2009（一种常用的相对定量工具）计算的结果一致。总之，我们的方法提供了易于理解的计算步骤，并且不需要专门的仪器、软件或专业知识来操作，对于分子生物学领域的学生、教育工作者和科学家来说将是一个有用的工具。
