Bai W L, Yin R H, Zhao S J, Jiang W Q, Yin R L, Ma Z J, Wang Z Y, Zhu Y B, Luo G B, Yang R J, Zhao Z H
College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang 110866, China.
College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang 110866, China.
J Dairy Sci. 2014 Feb;97(2):902-10. doi: 10.3168/jds.2012-6437. Epub 2013 Dec 15.
Quantitative real-time PCR is the most sensitive technique for gene expression analysis. Data normalization is essential to correct for potential errors incurred in all steps from RNA isolation to PCR amplification. The commonly accepted approach for normalization is the use of reference gene. Until now, no suitable reference genes have been available for data normalization of gene expression in milk somatic cells of lactating yaks across lactation. In the present study, we evaluated the transcriptional stability of 10 candidate reference genes in milk somatic cells of lactating yak, including ACTB, B2M, GAPDH, GTP, MRPL39, PPP1R11, RPS9, RPS15, UXT, and RN18S1. Four genes, RPS9, PPP1R11, UXT, and MRPL39, were identified as being the most stable genes in milk somatic cells of lactating yak. Using the combination of RPS9, PPP1R11, UXT, and MRPL39 as reference genes, we further assessed the relative expression of 4 genes of interest in milk somatic cells of yak across lactation, including ELF5, ABCG2, SREBF2, and DGAT1. Compared with expression in colostrum, the overall transcription levels of ELF5, ABCG2, and SREBF2 in milk were found to be significantly upregulated in early, peak, and late lactation, and significantly downregulated thereafter, before the dry period. A similar pattern was observed in the relative expression of DGAT1, but no significant difference was revealed in its expression in milk from late lactation compared with colostrum. Based on these results, we suggest that the geometric mean of RPS9, PPP1R11, UXT, and MRPL39 can be used for normalization of real-time PCR data in milk somatic cells of lactating yak, if similar experiments are performed.
定量实时PCR是基因表达分析中最敏感的技术。数据归一化对于校正从RNA分离到PCR扩增的所有步骤中可能出现的潜在误差至关重要。普遍接受的归一化方法是使用参考基因。到目前为止,还没有合适的参考基因可用于泌乳期牦牛乳汁体细胞基因表达的数据归一化。在本研究中,我们评估了10个候选参考基因在泌乳期牦牛乳汁体细胞中的转录稳定性,包括ACTB、B2M、GAPDH、GTP、MRPL39、PPP1R11、RPS9、RPS15、UXT和RN18S1。四个基因,RPS9、PPP1R11、UXT和MRPL39,被确定为泌乳期牦牛乳汁体细胞中最稳定的基因。使用RPS9、PPP1R11、UXT和MRPL39的组合作为参考基因,我们进一步评估了泌乳期牦牛乳汁体细胞中4个感兴趣基因的相对表达,包括ELF5、ABCG2、SREBF2和DGAT1。与初乳中的表达相比,发现ELF5、ABCG2和SREBF2在泌乳早期、高峰期和晚期的乳汁中的总体转录水平显著上调,此后在干奶期前显著下调。在DGAT1的相对表达中也观察到类似的模式,但与初乳相比,其在泌乳后期乳汁中的表达没有显著差异。基于这些结果,我们建议,如果进行类似实验,RPS9、PPP1R11、UXT和MRPL39的几何平均值可用于泌乳期牦牛乳汁体细胞实时PCR数据的归一化。