Abstract
The aim of this study was to select the most suitable reference genes for quantitative real-time polymerase chain reaction (qRT-PCR) of spotted sea bass (Lateolabrax maculatus), an important commercial marine fish in Pacific Asia, under normal physiological and salinity stress conditions. A total of 9 candidate reference genes (HPRT, GAPDH, EF1A, TUBA, RPL7, RNAPol II, B2M, ACTB and 18S rRNA) were analyzed by qRT-PCR in 10 tissues (intestine, muscle, stomach, brain, heart, liver, gill, kidney, pectoral fins and spleen) of L. maculatus. Four algorithms, geNorm, NormFinder, BestKeeper, and comparative ΔCt method, were used to evaluate the expression stability of the candidate reference genes. The results showed the 18S rRNA was most stable in different tissues under normal conditions. During salinity stress, RPL7 was the most stable gene according to overall ranking and the best combination of reference genes was RPL7 and RNAPol II. In contrast, GAPDH was the least stable gene which was not suitable as reference genes. The study showed that different algorithms might generate inconsistent results. Therefore, the combination of several reference genes should be selected to accurately calibrate system errors. The present study was the first to select reference genes of L. maculatus by qRT-PCR and provides a useful basis for selecting the appropriate reference gene in L. maculatus. The present study also has important implications for gene expression and functional genomics research in this species or other teleost species.
Highlights
Quantifying gene expression levels is an essential research strategy to understand and reveal complex regulatory gene networks in organisms (Dekkers et al, 2012)
The transcription levels of all 9 candidate reference genes were assessed by Quantitative real-time PCR (qRT-PCR)
To avoid unnecessary errors in the profiling of gene expression, the expression stability of 9 candidate reference genes in different tissues and under salinity stress was analyzed by four programs
Summary
Quantifying gene expression levels is an essential research strategy to understand and reveal complex regulatory gene networks in organisms (Dekkers et al, 2012). Quantitative real-time PCR (qRT-PCR) is considered the most powerful and commonly used tool for analyzing the relative transcription levels in gene expression because of its advantages of easy accessibility, high-throughput and fast-processing. The optimal reference genes should be constant with the adjustment of the experimental procedure (tissues, treatments and developmental stages) (Radonić et al, 2004). The stability of the reference gene is relative, and the expression level of the reference gene used might commonly be unstable under different conditions (Gutierrez et al, 2008). No single gene maintained constant expression levels in all species and different tissues and under different experimental conditions. It is necessary to select specific reference genes of species and tissues that could be helpful for studies on regulatory gene networks under different conditions
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