Tramontana S, Bionaz M, Sharma A, Graugnard D E, Cutler E A, Ajmone-Marsan P, Hurley W L, Loor J J
Istituto di Zootecnica, Università Cattolica del Sacro Cuore, 29100 Piacenza, Italy.
J Dairy Sci. 2008 Aug;91(8):3057-66. doi: 10.3168/jds.2008-1164.
High-throughput microarray analysis is an efficient means of obtaining a genome-wide view of transcript profiles across physiological states. However, quantitative PCR (qPCR) remains the chosen method for high-precision mRNA abundance analysis. Essential for reliability of qPCR data is normalization using appropriate internal control genes (ICG), which is now, more than ever before, a fundamental step for accurate gene expression profiling. We mined mammary tissue microarray data on >13,000 genes at -34, -14, 0, 7, 14, 21, and 28 d relative to parturition in 27 crossbred primiparous gilts to identify suitable ICG. Initial analysis revealed TBK1, PCSK2, PTBP1, API5, VAPB, QTRT1, TRIM41, TMEM24, PPP2R5B, and AP1S1 as the most stable genes (sample/reference = 1 +/- 0.2). We also included 9 genes previously identified as ICG in bovine mammary tissue. Gene network analysis of the 19 genes identified AP1S1, API5, MTG1, VAPB, TRIM41, MRPL39, and RPS15A as having no known co-regulation. In addition, UXT and ACTB were added to this list, and mRNA abundance of these 9 genes was measured by qPCR. Expression of all 9 of these genes was decreased markedly during lactation. In a previous study with bovine mammary tissue, mRNA of stably expressed genes decreased during lactation due to a dilution effect brought about by large increases in expression of highly abundant genes. To verify this effect, highly abundant mammary genes such as CSN1S2, SCD, FABP3, and LTF were evaluated by qPCR. The tested ICG had a negative correlation with these genes, demonstrating a dilution effect in the porcine mammary tissue. Gene stability analysis identified API5, VABP, and MRPL39 as the most stable ICG in porcine mammary tissue and indicated that the use of those 3 genes was most appropriate for calculating a normalization factor. Overall, results underscore the importance of proper validation of internal controls for qPCR and highlight the limitations of using absence of time effects as the criteria for selection of appropriate ICG. Further, we showed that use of the same ICG from one organism might not be suitable for qPCR normalization in other species.
高通量微阵列分析是一种在生理状态下获得全基因组转录谱视图的有效方法。然而，定量PCR（qPCR）仍然是高精度mRNA丰度分析的首选方法。使用合适的内参基因（ICG）进行标准化是qPCR数据可靠性的关键，现在它比以往任何时候都更是准确基因表达谱分析的基本步骤。我们挖掘了27头杂交初产母猪在分娩前34、14、0、7、14、21和28天的乳腺组织微阵列数据，涉及超过13000个基因，以确定合适的ICG。初步分析显示，TBK1、PCSK2、PTBP1、API5、VAPB、QTRT1、TRIM41、TMEM24、PPP2R5B和AP1S1是最稳定的基因（样本/对照 = 1±0.2）。我们还纳入了先前在牛乳腺组织中被确定为ICG的9个基因。对这19个基因的基因网络分析确定，AP1S1、API5、MTG1、VAPB、TRIM41、MRPL39和RPS15A没有已知的共调控关系。此外，UXT和ACTB也被列入此列表，并通过qPCR测量这9个基因的mRNA丰度。在泌乳期间，这9个基因的表达均显著下降。在先前一项关于牛乳腺组织的研究中，稳定表达基因的mRNA在泌乳期间下降是由于高丰度基因表达大幅增加带来的稀释效应。为验证这种效应，通过qPCR评估了CSN1S2、SCD、FABP3和LTF等高丰度乳腺基因。测试的ICG与这些基因呈负相关，表明在猪乳腺组织中存在稀释效应。基因稳定性分析确定API5、VABP和MRPL39是猪乳腺组织中最稳定的ICG，并表明使用这3个基因最适合计算标准化因子。总体而言，结果强调了对qPCR内参进行适当验证的重要性，并突出了将无时间效应作为选择合适ICG标准的局限性。此外，我们表明，在一个生物体中使用的相同ICG可能不适用于其他物种的qPCR标准化。
