Tracking the best reference genes for RT-qPCR data normalization in filamentous fungi

Area of Science:

• Molecular Biology
• Mycology
• Genomics

Background:

• Accurate gene expression analysis via RT-qPCR relies on reliable data normalization.
• Reference genes are crucial for normalizing RT-qPCR data, but suitable genes vary across species and conditions.
• Identifying universally applicable reference genes in filamentous fungi is essential for robust research.

Purpose of the Study:

• To identify and validate stable reference genes for RT-qPCR data normalization in Talaromyces versatilis.
• To propose a set of reference genes applicable across diverse filamentous fungi.
• To ensure accurate gene expression quantification in fungal biology.

Main Methods:

• In silico screening of candidate reference genes from Talaromyces versatilis RNA-seq data.
• RT-qPCR analysis of candidate genes across over 30 culture conditions.
• Validation of gene stability using geNorm and analysis across 100 RNA-seq datasets from 18 fungal species.

Main Results:

• A selection of candidate genes exhibited stable transcript levels in T. versatilis under various conditions.
• Hierarchical clustering identified a group of 6 genes with minimal expression changes across diverse filamentous fungi.
• Genes including ubcB, sac7, fis1, sarA, TFC1, and UBC6 were found to be highly stable.

Conclusions:

• A set of 6 validated reference genes is proposed for RT-qPCR normalization in fungal biology.
• Systematic experimental validation and geometric averaging of at least 3 genes are recommended for optimal results.
• This approach minimizes normalization bias and supports trustworthy biological conclusions.