Selection of suitable endogenous reference genes for qPCR in kidney and hypothalamus of rats under testosterone influence.
Khadijeh GholamiSu Yi LohNaguib SallehSau Kuen LamSee Ziau HoePublished in: PloS one (2017)
Real-time quantitative PCR (qPCR) is the most reliable and accurate technique for analyses of gene expression. Endogenous reference genes are being used to normalize qPCR data even though their expression may vary under different conditions and in different tissues. Nonetheless, verification of expression of reference genes in selected studied tissue is essential in order to accurately assess the level of expression of target genes of interest. Therefore, in this study, we attempted to examine six commonly used reference genes in order to identify the gene being expressed most constantly under the influence of testosterone in the kidneys and hypothalamus. The reference genes include glyceraldehyde-3-phosphate dehydrogenase (GAPDH), actin beta (ACTB), beta-2 microglobulin (B2m), hypoxanthine phosphoribosyltransferase 1 (HPRT), peptidylprolylisomerase A (Ppia) and hydroxymethylbilane synthase (Hmbs). The cycle threshold (Ct) value for each gene was determined and data obtained were analyzed using the software programs NormFinder, geNorm, BestKeeper, and rank aggregation. Results showed that Hmbs and Ppia genes were the most stably expressed in the hypothalamus. Meanwhile, in kidneys, Hmbs and GAPDH appeared to be the most constant genes. In conclusion, variations in expression levels of reference genes occur in kidneys and hypothalamus under similar conditions; thus, it is important to verify reference gene levels in these tissues prior to commencing any studies.
Keyphrases
- genome wide
- genome wide identification
- gene expression
- bioinformatics analysis
- poor prognosis
- genome wide analysis
- dna methylation
- transcription factor
- computed tomography
- electronic health record
- long non coding rna
- machine learning
- magnetic resonance
- magnetic resonance imaging
- binding protein
- deep learning
- pet ct
- big data
- smoking cessation