Selection of reference genes suitable for normalization of qRT‐PCR data in spotted sea bass ( Lateolabrax maculatus ) under conditions of pathogen infections

2021 ◽  
Author(s):  
Jieyun Guo ◽  
Lulu Yan ◽  
Pengfei Wang ◽  
Chao Zhao ◽  
Sigang Fan ◽  
...  
PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5631 ◽  
Author(s):  
Haolong Wang ◽  
Haishen Wen ◽  
Yun Li ◽  
Kaiqiang Zhang ◽  
Yang Liu

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.


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PLoS ONE ◽  
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Vol 12 (1) ◽  
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Author(s):  
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Vol 9 (1) ◽  
pp. 78 ◽  
Author(s):  
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Jae-Won Huh ◽  
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Dae-Soo Kim ◽  
Hong-Seok Ha ◽  
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2018 ◽  
Vol 35 (10) ◽  
pp. 1851-1860 ◽  
Author(s):  
D. A. Nikishin ◽  
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T. S. Bagaeva ◽  
V. V. Konduktorova ◽  
...  

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