Evaluation of Suitable Internal Control Genes for RT-qPCR in Yak Mammary Tissue during the Lactation Cycle.
Evaluation of Suitable Internal Control Genes for RT-qPCR in Yak Mammary Tissue during the Lactation Cycle.
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DOI：
10.1371/journal.pone.0147705
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发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Wang Y
中科院分区：
文献类型：
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作者：
Jiang M;Lee JN;Bionaz M;Deng XY;Wang Y
牦牛研究领域的一个关键问题是更好地了解哪些基因控制着牛奶的产量和成分。最准确、最灵敏的基因表达分析方法是定量逆转录聚合酶链反应（RT-qPCR）。利用内控基因（ICGs）对数据进行归一化处理是可靠的RT-qPCR的关键。然而，通过测试多个icg来评估标准化的可靠性是至关重要的。我们的目的是揭示在泌乳期牦牛乳腺组织中获得的RT-qPCR数据的可靠归一化。我们使用geNorm评估了10个ICGs （ACTB、EIF6、GAPDH、LRP10、MRPL39、MRPS15、MTG1、RPS8、RPS23和UXT）的可靠性。分析显示，所有测试的icg都可以被认为是可靠的，但应使用6个最稳定的icg来产生可靠的归一化因子（NF）。我们比较了3个目标基因（CSN1S1、ESR1和MYC）使用6、3或1个最佳ICGs归一化的结果。除了MYC的1个时间点外，我们没有观察到3种正常化策略之间的总体差异。不建议只使用单个ICG；因此，我们得出结论，使用3个最佳ICGs （MRPS15、RPS23和UXT）计算NF是一种可靠的归一化策略，用于牦牛妊娠和哺乳期乳腺组织RT-qPCR数据。先前观察到，在哺乳周期期间，牛和猪乳腺组织中丰表达基因的mRNA大量增加，从而导致ICGs的稀释效应。为了检验本研究是否存在稀释效应，我们评估了妊娠至哺乳期ICGs非归一化RT-qPCR数据的模式，并将其与3个靶基因的总RNA浓度、产奶量和非归一化RT-qPCR数据进行了比较。除少数例外，被测ICGs的非归一化RT-qPCR数据因哺乳而显著增加，且与总RNA和CSN1S1的非归一化RT-qPCR数据呈正相关。这些数据清楚地表明存在单个mRNA的“浓度效应”，这种效应仍然无法解释，但需要在RT-qPCR数据归一化过程中加以解释。基于我们的研究结果，我们建议将MRPS15、RPS23和UXT基因的NF用于哺乳期牦牛乳腺组织RT-qPCR数据的归一化。
The yak is primarily found throughout the Tibetan high plateau and the surrounding mountainous area of south central Asia; among its others attributes, its milk is very important for the local population. A key concern in the field of yak research is the better understanding of which genes control the production and composition of milk. The most accurate and sensitive method for gene expression analysis is quantitative reverse transcription polymerase chain reaction (RT-qPCR). It is essential for reliable RT-qPCR to be able to the normalize the data using internal control genes (ICGs). However, it is critical to assess the reliability of the normalization by testing multiple ICGs. Our objective was to uncover a reliable normalization for RT-qPCR data obtained from yak mammary tissue during the lactation cycle. We assessed the reliability of 10 ICGs (ACTB, EIF6, GAPDH, LRP10, MRPL39, MRPS15, MTG1, RPS8, RPS23, and UXT) using geNorm. The analysis revealed that all of the tested ICGs can be considered to be reliable, but the use of the 6 most stable ICGs should be applied to yield a reliable normalization factor (NF). We compared the results of 3 target genes (CSN1S1, ESR1, and MYC) normalized using 6, 3, or 1 of the best ICGs. We did not observe overall differences between the 3 normalization strategies with the exception of 1 time point in MYC. The use of only a single ICG is not recommended; thus, we concluded that the calculation of the NF using the 3 best ICGs, MRPS15, RPS23, and UXT, is a reliable normalization strategy for RT-qPCR data obtained from yak mammary tissue during pregnancy and lactation. A dilution effect of the ICGs due to a large increase in the mRNA of abundantly expressed genes in bovine and porcine mammary tissue during the lactation cycle was previously observed. To test for the presence of a dilution effect in our study, we evaluated the pattern of non-normalized RT-qPCR data of ICGs from pregnancy to lactation and compared them with the total RNA concentration, milk yield, and non-normalized RT-qPCR data of 3 target genes. With a few exceptions, the non- normalized RT-qPCR data for the tested ICGs was significantly increased by lactation and had a positive correlation with total RNA and the non-normalized RT-qPCR data of CSN1S1. These data clearly indicated the presence of a “concentration effect” of single mRNA that remains unexplained but needs to be accounted for during the normalization of RT-qPCR data. Based on our findings, we recommend that the NF of the MRPS15, RPS23, and UXT genes should be used in the normalization of RT-qPCR data obtained from mammary tissue of lactating yaks during pregnancy and lactation.