Bioinformatics approach for choosing the correct reference genes when studying gene expression in human keratinocytes

Area of Science:

• Dermatology
• Molecular Biology
• Bioinformatics

Background:

• Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is crucial for skin research.
• Accurate normalization using reliable reference genes (RGs) is essential for quantitative analysis.
• Selecting appropriate RGs significantly impacts experimental outcomes in keratinocyte studies.

Purpose of the Study:

• To identify and validate the most suitable reference genes for qRT-PCR in human primary keratinocytes (KCs).
• To evaluate RG stability across diverse experimental conditions using bioinformatics tools and experimental validation.
• To establish GUSB as a superior RG for keratinocyte research.

Main Methods:

• Utilized the 'RefGenes' bioinformatics tool, based on curated microarray data, to identify candidate RGs.
• Validated the expression stability of 6 RefGenes-identified RGs and 12 commonly used RGs via qRT-PCR.
• Assessed RG validity using four bioinformatics tools and coefficient of variation (CV) analysis.

Main Results:

• GUSB was identified as the most stably expressed reference gene across various experimental conditions.
• Commonly used RGs, GAPDH and B2M, showed significant expression variability.
• RefGenes proved effective in identifying reliable RGs for qRT-PCR.

Conclusions:

• GUSB is the most reliable reference gene for normalization in human primary keratinocyte qRT-PCR experiments.
• The RefGenes tool is a powerful resource for selecting validated RGs.
• Standard reference genes like GAPDH and B2M may not be suitable for all experimental conditions in keratinocyte research.