Abstract

RAW264.7 is a macrophage strain derived from mice tumour and shows a significant ability in antigen uptake. Real-time quantitative PCR (RT-qPCR) is one of the most commonly used methods in gene studies and requires suitable reference genes to normalize and quantitate the expression of gene of interest with sensitivity and specificity. However, suitable reference genes in RAW264.7 cells have not yet been identified for accurate gene expression quantification. In the current study, we evaluated expression levels of ten candidate reference genes in RAW264.7 cells under different conditions. RT-qPCR results indicated significant differences in the expression levels among the ten reference genes. Statistical analyses were carried out using geNorm, NormFinder, and BestKeeper software to further investigate the stability of the reference genes. Integrating the results from the three analytical methods, cytochrome c-1 and hydroxymethylbilane synthase were found to be the most stable and therefore more suitable reference genes, while ribosomal protein L4 and cyclophilin A were the least stable. This study emphasises the importance of identifying and selecting the most stable reference genes for normalization and provides a basis for future gene expression studies using RAW264.7 cells.

Highlights

  • Reverse transcription quantitative real-time PCR (RT-qPCR) is an important method for gene expression studies [1, 2]

  • The cycle threshold (Ct) value generated from the RT-qPCR is the fluorescence threshold for each primer pair and reflects the expression levels of the reference genes; a low Ct value indicates high expression [4,5,6]

  • lactate dehydrogenase A (LDHA) had a narrow range of Ct values, indicating that the variability of the expression level was constant under different conditions and it might be the best reference gene with a relatively high expression level

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Summary

Introduction

Reverse transcription quantitative real-time PCR (RT-qPCR) is an important method for gene expression studies [1, 2]. This technology has become a very popular method owing to its high speed, high sensitivity, and high-throughput capabilities [3,4,5]. Considering that gene expression levels may vary among cells or tissues and may change under certain circumstances, geNorm [11], NormFinder [12], and BestKeeper [13] analytical software have been specially designed for screening of reference gene stability

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