Transcriptome-based identification of the optimal reference CHO genes for normalisation of qPCR data

Real-time quantitative PCR (qPCR) is the standard method for determination of relative changes in mRNA transcript abundance. Analytical accuracy, precision, and reliability are critically dependent on the selection of internal control reference genes. In this study we have identified optimal reference genes that can be utilized universally for qPCR analysis of CHO cell mRNAs. Initially, transcriptomic datasets were analysed to identify eight endogenous genes that exhibited high expression stability across four distinct CHO cell lines sampled in different culture phases. The relative transcript abundance of each gene in twenty diverse, commonly-applied experimental conditions was then determined by qPCR analysis. Utilizing GeNorm, BestKeeper, and NormFinder algorithms, we identified four mRNAs (Gnb1, Fkbp1a, Tmed2 and Mmadhc) that exhibited a highly stable level of expression across all conditions, validating their utility as universally-applicable reference genes. Whilst any combination of only two genes can be generally used for normalization of qPCR data, we show that specific combinations of reference genes are particularly suited to discrete experimental conditions. In summary we report the identification of fully-validated universal reference genes, optimized primer sequences robust to genomic mutations, and simple reference gene pair selection guidelines that enable streamlined qPCR analyses of mRNA abundance in CHO cells with maximum accuracy and precision.