Stable reference genes selected from RNAseq data do not offer any significant advantage over conventional reference genes for normalizing qPCR assays

Using robust reference genes which are stably expressed across the samples to normalized qPCR data in a study is crucial. The choice of such reference genes are made based on different approaches. Additionally, a growing body of literature suggests the use of RNA-seq as a prerequisite for choosing optimal reference genes. In this study, we raised two major questions. Firstly, is RNA-seq necessary to find stably expressing genes that could be used as reference genes to normalize qPCR data? In order to address this question we have devised a previously described statistical pipeline of ours to best select the reference genes. Interestingly, we found that RNA-seq is not necessarily needed to find optimal reference genes. Addressing this question raised the second question, is this pipeline is effective for cross-sectional studies and longitudinal studies and in different models of various species. We report that our statistical pipeline that combines two different approaches works robustly in both of the setups we have tried. Overall design: Comparison of two approaches (stably expressed genes from RNA-seq or conventional genes) to find the optimal reference genes for qPCR analyses.

在相关研究中，选取在各类受试样本中稳定表达的稳健内参基因（reference gene）对qPCR（定量聚合酶链反应）数据进行标准化，是至关重要的核心环节。此类内参基因的筛选需基于多种不同策略。此外，越来越多的研究成果表明，筛选最优内参基因需以RNA测序（RNA sequencing, RNA-seq）数据作为前置条件。
本研究提出了两个核心科学问题：其一，是否必须借助RNA-seq数据，才能筛选出可用于qPCR数据标准化的稳定表达基因作为内参基因？为解答该问题，我们采用了此前已报道的自研统计分析流程（pipeline），以实现内参基因的最优筛选。有趣的是，我们发现筛选最优内参基因并非必须依赖RNA-seq数据。
在解答第一个问题的过程中，我们同时提出了第二个问题：该统计分析流程是否适用于横断面研究、纵向研究，以及不同物种的各类实验模型体系？本研究结果表明，结合两种不同筛选策略的统计分析流程，在我们测试的两类实验设置中均表现出优异的稳健性。
整体实验设计：对比两种筛选策略——基于RNA-seq的稳定表达基因法与传统基因法，以筛选适用于qPCR分析的最优内参基因。