BACKGROUND RNA sequencing allows the measuring of gene expression at a resolution unmet by expression arrays or RT-qPCR. It is however necessary to normalize sequencing data by library size, transcript size and composition, among other factors, before comparing expression levels. The use of internal control genes or spike-ins is advocated in the literature for scaling read counts, but the methods for choosing reference genes are mostly targeted at RT-qPCR studies and require a set of pre-selected candidate controls or pre-selected target genes. RESULTS Here, we report an R-based pipeline to select internal control genes based solely on read counts and gene sizes. This novel method first normalizes the read counts to Transcripts per Million (TPM) and then excludes weakly expressed genes using the DAFS script to calculate the cut-off. It then selects as references the genes with lowest TPM covariance. We used this method to pick custom reference genes for the differential expression analysis of three transcriptome sets from transgenic Arabidopsis plants expressing heterologous fungal effector proteins tagged with GFP (using GFP alone as the control). The custom reference genes showed lower covariance and fold change as well as a broader range of expression levels than commonly used reference genes. When analyzed with NormFinder, both typical and custom reference genes were considered suitable internal controls, but the custom selected genes were more stably expressed. geNorm produced a similar result in which most custom selected genes ranked higher (i.e. were more stably expressed) than commonly used reference genes. CONCLUSIONS The proposed method is innovative, rapid and simple. Since it does not depend on genome annotation, it can be used with any organism, and does not require pre-selected reference candidates or target genes that are not always available.

中文翻译：

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在转录组分析中，定制选择的参考基因优于预定义的参考基因。


背景RNA测序允许以表达阵列或RT-qPCR无法满足的分辨率测量基因表达。然而，在比较表达水平之前，有必要根据文库大小、转录本大小和组成等因素对测序数据进行标准化。文献中提倡使用内参基因或spike-ins来扩大reads计数，但选择内参基因的方法大多针对RT-qPCR研究，需要一组预先选择的候选对照或预先选择的目标基因。结果在这里，我们报告了一个基于 R 的管道，仅根据读取计数和基因大小来选择内部对照基因。这种新颖的方法首先将读取计数标准化为每百万转录本 (TPM)，然后使用 DAFS 脚本计算截止值来排除弱表达基因。然后，它选择 TPM 协方差最低的基因作为参考。我们使用这种方法挑选定制参考基因，用于对表达带有 GFP 标记的异源真菌效应蛋白的转基因拟南芥植物的三个转录组组进行差异表达分析（单独使用 GFP 作为对照）。与常用的参考基因相比，定制的参考基因表现出较低的协方差和倍数变化以及更广泛的表达水平。当使用NormFinder进行分析时，典型和定制的参考基因都被认为是合适的内部对照，但定制选择的基因表达更稳定。 geNorm 产生了类似的结果，其中大多数定制选择的基因比常用的参考基因排名更高（即表达更稳定）。结论所提出的方法创新、快速且简单。 由于它不依赖于基因组注释，因此可以与任何生物体一起使用，并且不需要预先选择的参考候选或并不总是可用的目标基因。