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From stability to reliability: Unveiling the un-biased reference genes in porcine ovarian granulosa cells under different conditions.
Huo, Yangan; Li, Xiaoxue; Sun, Chen; Pan, Zengxiang; Li, Qifa; Du, Xing.
Afiliación
  • Huo Y; Laboratory of Statistical Genetics and Epigenetics, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China.
  • Li X; Laboratory of Statistical Genetics and Epigenetics, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China.
  • Sun C; Laboratory of Statistical Genetics and Epigenetics, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China.
  • Pan Z; Laboratory of Statistical Genetics and Epigenetics, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China.
  • Li Q; Laboratory of Statistical Genetics and Epigenetics, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China.
  • Du X; Laboratory of Statistical Genetics and Epigenetics, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China. Electronic address: duxing@njau.edu.cn.
Gene ; 897: 148089, 2024 Mar 01.
Article en En | MEDLINE | ID: mdl-38123003
ABSTRACT
Selection of optimal reference genes (RGs) is fundamental for functional genomics studies and gene expression analysis, which are two main approaches to identify functional genes and their expression patterns. However, no systematic study has identified the suitable RGs in porcine ovarian granulosa cells (GCs) which are essential for follicle fate and sow fertility. In this study, the expression profiles of 12 widely-used RGs (GAPDH, RPLP0, ACTB, TUBA1B, EIF3K, PPIA, ATP5F1, B2M, HPRT1, UBC, RPS3, and EEF1A1) in porcine GCs during follicular development and under different abiotic stresses were systematically investigated. Expression stability of the candidate RGs were comprehensively accessed by five statistical algorithms including ΔCt, NormFinder, BestKeeper, geNorm, and RefFinder, indicating that RPS3 and PPIA are the optimal RGs during follicular development, EEF1A1 and RPLP0 are most stable under oxidative stress and inflammation, while ATP5F1, B2M, and RPS3 have higher stability under starvation and heat stress. Notably, the most commonly used RGs (ACTB, GAPDH, and TUBA1B) exhibited low stability in GCs. Reliability of stable RGs was verified by RT-qPCR and showed that selection of the stable RGs significantly improved the detection accuracy of qPCR, which confirms once again that the stability of RGs should not be taken for granted. Our findings identified optimal RG sets in porcine GCs under different conditions, which is helpful in future studies to accurately identify the key regulators and their expression patterns during follicular development in sows.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Perfilación de la Expresión Génica / Inflamación Límite: Animals Idioma: En Revista: Gene Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Perfilación de la Expresión Génica / Inflamación Límite: Animals Idioma: En Revista: Gene Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos