A Whole-Transcriptome Approach to Evaluating Reference Genes for Quantitative Gene Expression Studies: A Case Study...

Area of Science:

• Plant genomics
• Molecular biology
• Gene expression analysis

Background:

• Quantitative PCR (qPCR) relies on stable reference genes for accurate gene expression quantification.
• Traditional reference genes may not be universally applicable across different species or conditions.
• High-throughput transcriptomic data offers a powerful resource for identifying novel reference genes.

Purpose of the Study:

• To identify and validate novel qPCR reference genes using RNA-sequencing (RNA-seq) in the plant genus *Mimulus*.
• To evaluate the suitability of traditional housekeeping genes as reference genes.
• To propose a generalizable method for reference gene discovery using transcriptomic data.

Main Methods:

• RNA-sequencing (RNA-seq) was performed on *Mimulus* species.
• Gene expression means and variability were analyzed and compared between RNA-seq and qPCR data.
• The impact of environmental and genetic variation on gene expression was assessed.

Main Results:

• RNA-seq accurately estimated gene expression means compared to qPCR.
• Expression means were robust to moderate environmental and genetic variation.
• Expression variability agreement between RNA-seq and qPCR was limited to samples from a shared environment, indicating environmental impact.

Conclusions:

• Whole-transcriptome approaches, like RNA-seq, are valuable for identifying robust qPCR reference genes.
• Environmental factors significantly influence gene expression variability, necessitating careful experimental design for reference gene validation.
• Existing transcriptomic datasets provide a cost-effective resource for reference gene discovery in diverse organisms.