Abstract
Quantitative PCR (qPCR) is a widely-used technique for quantifying the expression of target genes across various tissues, as well as under different pathological and physiological conditions. One of the challenges associated with this method is the need to identify optimal reference genes (RGs) that maintain consistent expression levels under diverse experimental settings, thereby ensuring accurate biological interpretation. In this study, we conducted a thorough analysis of 18 candidate RGs (ACTB, BACH1, B2M, GAPDH, HMBS, HPRT1, PGK1, PPIA, PPIB, RPLP0, RPL19, RPS9, RPS15, RPS28, SDHA, TBP, UXT, and YWHAZ) across 10 ovine tissues (muscle, skin, kidney, liver, intestine, rumen, lung, testis, heart, and spleen) obtained from five individual sheep. We aimed to identify genes with stable expression across these tissues. A literature-based survey helped us shortlist candidate genes representing various functional classes from multiple livestock species. We employed four algorithms: geNorm, NormFinder, BestKeeper, and Delta Ct (ΔCt), to rank these genes based on their stability. A consistent trend in the rankings was observed across these different algorithms. RefFinder was then used for a comprehensive ranking, integrating the outputs from the various methods. ACTB, PPIB, BACH1, and B2M emerged as the most stable RGs, while RPS9, RPS15, and PGK1 displayed variable expression. We validated our findings through qPCR analysis of four target genes (ACTN2, CRYAB, DLK1, and TRIM54) in the skin samples from two different sheep breeds. Based on these results, we recommend ACTB, PPIB, BACH1, and B2M as reliable internal control genes for qPCR experiments involving diverse ovine tissues.
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