Reference gene validation for quantification of gene expression during ovarian development of turbot (Scophthalmus maximus)

Author:

Gao Yunhong,Gao Yuntao,Huang Bin,Meng Zhen,Jia Yudong

Abstract

AbstractQuantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) is a powerful and sensitive method used in gene expression analysis. Suitable reference genes, which are stable under all experimental circumstances and tissues significantly improve the accuracy of qRT-PCR data. In this study, the stability of six genes, namely, 18S ribosomal RNA (18s), beta-actin (actb), elongation factor 1-alpha (ef1α), glyceraldehyde-3-phosphate-dehydrogenase (gapdh), cathepsin D (ctsd), and beta-2-microglobulin (b2m) were evaluated as potential references for qRT-PCR analysis. The genes were examined in the hypothalamus-pituitary-ovary-liver (HPOL) axis throughout turbot ovarian development via using the geNorm, NormFinder and BestKeeper algorithms. Results showed that the most stable reference genes were ef1α, actb, and ctsd in the hypothalamus, pituitary, ovary and liver, respectively. The best-suited gene combinations for normalization were 18s, ef1α, and ctsd in the hypothalamus; actb, ctsd, and 18s in the pituitary; actb, and ctsd in the ovary; gapdh and ctsd in the liver. Moreover, the expression profile of estrogen receptor α (erα) manifested no significant difference normalization to the aforementioned best-suited gene during turbot ovarian development. However, no single gene or pair of genes is suitable as an internal control and account for the amplification differences among the four tissues during ovarian development. In summary, these results provide a basic data for the optimal reference gene selection and obtain highly accurate normalization of qRT-PCR data in HPOL axis-related gene expression analysis during turbot ovarian development.

Funder

National Natural Science Foundation of China

Earmarked Fund for China Agriculture Research System

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

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