Lukaszewicz Germán, Amé María Valeria, Menone Mirta Luján
Instituto de Investigaciones Marinas y Costeras (IIMyC) UNMDP, CONICET, Mar del Plata, Argentina.
2Dto. Bioquímica Clínica-CIBICI, Facultad de Ciencias Químicas, Universidad Nacional de Córdoba - CONICET, Haya de la Torre esq. Medina Allende, 5000 Córdoba, Argentina.
Physiol Mol Biol Plants. 2018 Sep;24(5):781-792. doi: 10.1007/s12298-018-0534-3. Epub 2018 Jun 26.
The RT-qPCR has been the method used to analyze gene expression in plants but its benefits have not been completely exploited in the field of plants ecotoxicology when used as molecular biomarkers. The correct use of RT-qPCR demands to establish a certain number of reference genes (RG) which are expected to be invariable in their expression although it does not always happen. The main goals of this work were to: (1) analyze the stability of six potential RG, (2) establish the optimum number of RG, (3) select the most suitable RG to be applied in under different test conditions and tissues and (4) confirm its convenience by normalizing the expression of one gene of interest under three different challenges. When all data were pooled together, the geNorm algorithm pointed out beta-actin and beta-tubulin (TUB) as the optimal RG pair while NormFinder algorithm selected nicotinamide adenine dinucleotide dehydrogenase (NADHD) and histone 3 (H3) as possessing the most invariable levels of expression. On the other hand, when data were grouped by tissues, ANOVA test selected H3 and TUB, while data grouped by conditions indicated that H3 and NADHD were the most stable RG under this analysis. Therefore, for a general-purpose set of RG, the overall analysis showed that a set of three RG would be optimum, and H3, TUB and NADHD were the selected ones. On the other hand, as RG can vary depending on the tissues or conditions, results achieved with ANOVA would be more reliable. Thus, appropriate normalization process would clearly need more than one RG.
逆转录定量聚合酶链反应(RT-qPCR)一直是用于分析植物基因表达的方法,但当用作分子生物标志物时,其在植物生态毒理学领域的优势尚未得到充分利用。正确使用RT-qPCR需要建立一定数量的参考基因(RG),这些基因的表达预期是不变的,尽管并非总是如此。这项工作的主要目标是:(1)分析六个潜在RG的稳定性,(2)确定RG的最佳数量,(3)选择最适合在不同测试条件和组织中应用的RG,以及(4)通过在三种不同挑战下对一个目标基因的表达进行标准化来确认其适用性。当所有数据汇总在一起时,geNorm算法指出β-肌动蛋白和β-微管蛋白(TUB)是最佳的RG对,而NormFinder算法选择烟酰胺腺嘌呤二核苷酸脱氢酶(NADHD)和组蛋白3(H3)作为表达水平最稳定的基因。另一方面,当按组织对数据进行分组时,方差分析(ANOVA)测试选择了H3和TUB,而按条件分组的数据表明,在此分析下H3和NADHD是最稳定的RG。因此,对于一组通用的RG,总体分析表明一组三个RG是最佳的,所选的是H3、TUB和NADHD。另一方面,由于RG可能因组织或条件而异,ANOVA得出的结果会更可靠。因此,适当的标准化过程显然需要不止一个RG。