Laboratory of Statistical Genetics and Epigenetics, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China.
Laboratory of Statistical Genetics and Epigenetics, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China.
Gene. 2024 Mar 1;897:148089. doi: 10.1016/j.gene.2023.148089. Epub 2023 Dec 18.
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.
选择最佳的参考基因（RGs）对于功能基因组学研究和基因表达分析至关重要，这是鉴定功能基因及其表达模式的两种主要方法。然而，目前还没有系统的研究确定猪卵巢颗粒细胞（GCs）中合适的 RGs，而这些 RGs对于卵泡命运和母猪生育能力至关重要。在这项研究中，系统地研究了 12 个广泛使用的 RG（GAPDH、RPLP0、ACTB、TUBA1B、EIF3K、PPIA、ATP5F1、B2M、HPRT1、UBC、RPS3 和 EEF1A1）在猪 GCs 中的表达谱在卵泡发育过程中和不同的非生物应激下。通过包括 ΔCt、NormFinder、BestKeeper、geNorm 和 RefFinder 在内的五种统计算法，全面评估候选 RGs 的表达稳定性，表明 RPS3 和 PPIA 是卵泡发育过程中的最佳 RGs，EEF1A1 和 RPLP0 在氧化应激和炎症下最稳定，而 ATP5F1、B2M 和 RPS3 在饥饿和热应激下具有更高的稳定性。值得注意的是，最常用的 RGs（ACTB、GAPDH 和 TUBA1B）在 GCs 中表现出较低的稳定性。通过 RT-qPCR 验证了稳定 RGs 的可靠性，结果表明选择稳定的 RGs 显著提高了 qPCR 的检测准确性，这再次证实 RGs 的稳定性不应被视为理所当然。我们的研究结果确定了不同条件下猪 GCs 中的最佳 RG 集，这有助于未来的研究准确识别母猪卵泡发育过程中的关键调节因子及其表达模式。
