A Whole-Transcriptome Approach to Evaluating Reference Genes for Quantitative Gene Expression Studies: A Case Study in Mimulus. Issue 4 (1st April 2017)

• Record Type: Journal Article
• Authors: Stanton, Kimmy A; Edger, Patrick P; Puzey, Joshua R; Kinser, Taliesin; Cheng, Philip; Vernon, Daniel M; Forsthoefel, Nancy R; Cooley, Arielle M
• Is Part Of: G3. Volume 7:Issue 4(2017)
• Page Start: 1085
• Page End: 1095
• Publication Date: 2017-04-01
• Subjects: expression stability -- Mimulus guttatus -- Mimulus luteus -- quantitative RT-PCR -- RNA-seq; Genetics -- Research -- Periodicals; Genomics -- Periodicals; Genetics; Genomics; Genes; Genetics -- Research; Genomics; Electronic journals; Periodical; Periodicals; Fulltext; Internet Resources; Periodicals; 572.8
• DOI: 10.1534/g3.116.038075
• Languages: English
• ISSNs: 2160-1836

Abstract

Abstract: 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.