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.

尽管定量聚合酶链式反应（quantitative PCR, qPCR）被学界广泛认定为定量基因表达的最精准方法之一，但其应用高度依赖于可靠且表达稳定的内参基因的选用。随着基因表达高通量检测方法的普及度不断提升，全转录组分析方法正越来越多地被用于内参基因的筛选与验证。本研究中，我们利用RNA测序（RNA-seq）技术，在进化模式植物沟酸浆属（Mimulus）的两个物种中，鉴定出一批新型qPCR内参基因，并对一系列传统"持家"（housekeeping）内参基因进行了评估。从更广泛的层面来看，本研究提出的分析方法可借助转录组数据的分析潜力，在任意研究物种（包括新兴模式物种与非模式物种）中筛选适用于qPCR的内参基因。本研究发现，相较于qPCR，RNA-seq可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。但仅在来自同一培养环境的样本中，RNA-seq的表达变异度检测结果才与qPCR结果一致。结合全转录组水平的比对分析结果，这一发现表明环境变化对基因表达变异度的影响程度远大于其对表达均值的影响。我们讨论了可通过实验设计规避该问题的可行方案，并提出：日益增长的公开转录组数据资源，是开发更优质qPCR内参基因的丰富且低成本的宝贵宝库。