Dos Santos Bronel Bruno Aristides, Anauate Ana Carolina, da Silva Novaes Antônio, Boim Mirian Aparecida, Maquigussa Edgar
Renal Division, Department of Medicine, Universidade Federal de São Paulo, Rua Pedro de Toledo, 781, 04039-032, São Paulo, SP, Brazil.
Biochem Genet. 2025 Apr 17. doi: 10.1007/s10528-025-11105-3.
Recently, several studies have aimed to establish the role of microRNAs (miRNAs) in the unilateral ureteral obstruction (UUO) model. Therefore, it is essential to identify the best housekeeping genes (HKG) to correctly estimate the expression levels of miRNAs. The present study aimed to identify suitable HKG to normalize the expression of miRNAs by RT-qPCR in kidney samples from the UUO mice model. We analyzed the stability of twelve endogenous reference genes of small non-coding RNAs (Snord61, Snord68, Snord72, Snord95, Snord96a, U6, let-7e-5p, let-7i-3p, miR-15b-5p, miR-16a-5p, miR-26a-5p, and miR-30c-5p) by using four software packages: NormFinder, GeNorm, ΔCt method, and BestKeeper. The optimal number of genes was calculated using GenEx software analysis. To validate the best HKG, we normalized the expression of miR-18a-5p, miR-21a-3p, and miR-29b-3p. In silico analysis revealed that Snord61, Snord68, and Snord72 were the most stable HKG between the groups. Using GenEX software and Pearson's correlation, we determined that the combination of Snord61 and Snord68 or the combination of Snord68 and Snord72, provided the best HKG association. These results along with the correlation analyses establish that the association of Snord68 and Snord72 is the best choice for miRNA expression analysis by RT-qPCR in the UUO model.
最近,多项研究旨在确定微小RNA(miRNA)在单侧输尿管梗阻(UUO)模型中的作用。因此,识别最佳管家基因(HKG)以正确估计miRNA的表达水平至关重要。本研究旨在识别合适的HKG,以通过RT-qPCR对UUO小鼠模型肾脏样本中miRNA的表达进行标准化。我们使用四种软件包(NormFinder、GeNorm、ΔCt法和BestKeeper)分析了12个小非编码RNA内源性参考基因(Snord61、Snord68、Snord72、Snord95、Snord96a、U6、let-7e-5p、let-7i-3p、miR-15b-5p、miR-16a-5p、miR-26a-5p和miR-30c-5p)的稳定性。使用GenEx软件分析计算最佳基因数量。为验证最佳HKG,我们对miR-18a-5p、miR-21a-3p和miR-29b-3p的表达进行了标准化。计算机分析显示,Snord61、Snord68和Snord72是组间最稳定的HKG。使用GenEX软件和Pearson相关性分析,我们确定Snord61和Snord68的组合或Snord68和Snord72的组合提供了最佳的HKG关联性。这些结果以及相关性分析表明,在UUO模型中,Snord68和Snord72的组合是通过RT-qPCR进行miRNA表达分析的最佳选择。