Data from: A whole-transcriptome approach to evaluating reference genes for quantitative gene expression studies: a case study in Mimulus

While quantitative PCR (qPCR) is widely recognized as being among the most accurate methods for quantifying gene expression, it is highly dependent on the use of reliable, stably expressed reference genes. With the increased availability of high-throughput methods for measuring gene expression, whole-transcriptome approaches may be increasingly utilized for reference gene selection and validation. In this study, RNA-seq was used to identify a set of novel qPCR reference genes and evaluate a panel of traditional “housekeeping” reference genes in two species of the evolutionary model plant genus Mimulus. More broadly, the methods proposed in this study can be used to harness the power of transcriptomes to identify appropriate reference genes for qPCR in any study organism, including emerging and nonmodel systems. We find that RNA-seq accurately estimates gene expression means in comparison to qPCR, and that expression means are robust to moderate environmental and genetic variation. However, measures of expression variability were only in agreement with qPCR for samples obtained from a shared environment. This result, along with transcriptome-wide comparisons, suggests that environmental changes have greater impacts on expression variability than on expression means. We discuss how this issue can be addressed through experimental design, and suggest that the ever-expanding pool of published transcriptomes represents a rich and low-cost resource for developing better reference genes for qPCR.尽管实时定量聚合酶链反应（quantitative PCR, qPCR）被广泛认为是定量基因表达最为精准的方法之一，但其高度依赖于可靠且表达稳定的内参基因的使用。随着基因表达检测高通量方法的日益普及，全转录组学方法正越来越多地被用于内参基因的筛选与验证。本研究利用RNA测序（RNA-seq）技术，在两种进化模式植物属沟酸浆属（Mimulus）物种中，鉴定出一组新型qPCR内参基因，并对一系列传统“管家”内参基因进行了评估。从更广泛的视角来看，本研究提出的方法可借助转录组的优势，为任何研究生物（包括新兴模式生物与非模式生物）的qPCR实验筛选合适的内参基因。研究结果表明，相较于qPCR，RNA-seq能够精准估算基因表达均值，且该表达均值对适度的环境与遗传变异具有鲁棒性。然而，仅当样本取自共享环境时，转录组的表达变异度测量结果才与qPCR结果一致。这一结果结合全转录组比较分析显示，环境变化对表达变异度的影响远大于其对表达均值的影响。本文讨论了可通过实验设计解决该问题的思路，并指出持续扩充的已发表转录组库，是开发更优质qPCR内参基因的丰富且低成本的资源。