A protocol for identifying universal reference genes within a genus based on RNA-Seq data: a case study of poplar...

Area of Science:

• Plant Molecular Biology
• Gene Expression Analysis
• Bioinformatics

Background:

• Accurate relative gene expression analysis using real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) is essential.
• Normalization relies on stably expressed reference genes (RGs), but suitable RGs for poplar stems under various conditions are not well-established.
• Publicly available RNA-Seq data offers a valuable resource for identifying RGs.

Purpose of the Study:

• To develop and present a systematic pipeline for identifying constitutively and stably expressed reference genes in poplar (Populus) stems.
• To validate candidate reference genes using RT-qPCR and multiple statistical algorithms.
• To identify the most reliable reference gene for gene expression studies in poplar stems.

Main Methods:

• Utilized DESeq2's median of ratios for normalization of 292 RNA-Seq samples.
• Identified 541 stably expressed genes based on coefficient of variance (CV) values (cutoff ≤ 0.3).
• Designed universal primers, assessed expression stability of 12 candidate and 6 reported RGs using RT-qPCR and validated with ΔCt, geNorm, NormFinder, and BestKeeper algorithms.

Main Results:

• A total of 541 candidate reference genes were identified from RNA-Seq data.
• All tested candidate RGs demonstrated stable expression across different experiments and conditions in Populus.
• Potri.001G349400 (CNOT2) was identified as the best reference gene, with six candidate and three reported RGs meeting the CV ≤ 0.3 criterion in a test dataset.

Conclusions:

• The study provides an optimized protocol for identifying stable reference genes from RNA-Seq data in poplar.
• Potri.001G349400 (CNOT2) is recommended as a reliable reference gene for gene expression studies in poplar stems.
• The developed pipeline can be applied to identify reference genes in other plant species or under different experimental conditions.