OBJECTIVE: To verify the most stable RG during osteogenic differentiation of human dental pulp stem cells (DPSCs) by RT-qPCR.
METHODS: We cultivated DPSCs under two conditions: Undifferentiated and osteogenic differentiation, both for 35 d. We evaluated the gene expression of 10 candidates for RGs [ribosomal protein, large, P0 (RPLP0), TATA-binding protein (TBP), GAPDH, actin beta (ACTB), tubulin (TUB), aminolevulinic acid synthase 1 (ALAS1), tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta (YWHAZ), eukaryotic translational elongation factor 1 alpha (EF1a), succinate dehydrogenase complex, subunit A, flavoprotein (SDHA), and beta-2-microglobulin (B2M)] every 7 d (1, 7, 14, 21, 28, and 35 d) by RT-qPCR. The data were analysed by the four main algorithms, ΔCt method, geNorm, NormFinder, and BestKeeper and ranked by the RefFinder method. We subdivided the samples into eight subgroups.
RESULTS: All of the data sets from clonogenic and osteogenic samples were analysed using the RefFinder algorithm. The final ranking showed RPLP0/TBP as the two most stable RGs and TUB/B2M as the two least stable RGs. Either the ΔCt method or NormFinder analysis showed TBP/RPLP0 as the two most stable genes. However, geNorm analysis showed RPLP0/EF1α in the first place. These algorithms\' two least stable RGs were B2M/GAPDH. For BestKeeper, ALAS1 was ranked as the most stable RG, and SDHA as the least stable RG. The pair RPLP0/TBP was detected in most subgroups as the most stable RGs, following the RefFinfer ranking.
CONCLUSIONS: For the first time, we show that RPLP0/TBP are the most stable RGs, whereas TUB/B2M are unstable RGs for long-term osteogenic differentiation of human DPSCs in traditional monolayers.
目的:通过RT-qPCR验证人牙髓干细胞(DPSC)成骨分化过程中最稳定的RG。
方法:我们在两种条件下培养DPSC:未分化和成骨分化,均为35d。我们评估了10个RGs候选物的基因表达[核糖体蛋白,大,P0(RPLP0),TATA结合蛋白(TBP),GAPDH,肌动蛋白β(ACTB),微管蛋白(TUB),氨基乙酰丙酸合成酶1(ALAS1),酪氨酸3-单加氧酶/色氨酸5-单加氧酶激活蛋白,zeta(YWHAZ),真核翻译延伸因子1α(EF1a),琥珀酸脱氢酶复合物,亚基A,黄素蛋白(SDHA),和β-2-微球蛋白(B2M)]每7d(1、7、14、21、28和35d)通过RT-qPCR。通过四种主要算法对数据进行了分析,ΔCt法,geNorm,NormFinder,和BestKeeper,并按RefFinder方法排名。我们将样本细分为八个亚组。
结果:使用RefFinder算法分析来自克隆和成骨样本的所有数据集。最终排名显示RPLP0/TBP为两个最稳定的RG,TUB/B2M为两个最不稳定的RG。ΔCt方法或NormFinder分析显示TBP/RPLP0是两个最稳定的基因。然而,geNorm分析显示RPLP0/EF1α居首位。这些算法\'两个最不稳定的RG是B2M/GAPDH。对BestKeeper来说,ALAS1被评为最稳定的RG,和SDHA作为最不稳定的RG。在大多数亚组中检测到RPLP0/TBP对是最稳定的RGs,遵循RefFinfer排名。
结论:第一次,我们发现RPLP0/TBP是最稳定的RGs,而TUB/B2M是不稳定的RGs,用于传统单层中人DPSC的长期成骨分化。