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Identification of housekeeping genes for microRNA expression analysis in kidney tissues of Pkd1 deficient mouse models.

ABSTRACT: Polycystic kidney disease is a complex clinical entity which comprises a group of genetic diseases that leads to renal cyst development. We evaluated the most suitable housekeeping genes for microRNA expression by RT-qPCR analyses of kidney tissues in Pkd1-deficient mouse models from a panel of five candidates genes (miR-20a, miR-25, miR-26a, miR-191 and U6) and 3 target genes (miR-17, miR-21 and let-7a) using samples from kidneys of cystic mice (Pkd1flox/flox:Nestincre, CY), non-cystic controls (Pkd1flox/flox, NC), Pkd1-haploinsufficient (Pkd1+/-, HT), wild-type controls (Pkd1+/+, WT), severely cystic mice (Pkd1V/V, SC), wild-type controls (CO). The stability of the candidate genes was investigated using NormFinder, GeNorm, BestKeeper, DataAssist, and RefFinder software packages and the comparative ?Ct method. The analyses identified miR-26a as the most stable housekeeping gene for all kidney samples, miR-20a for CY and NC, miR-20a and miR-26a for HT and WT, and miR-25 and miR-26a for SC and CO. Expression of miR-21 was upregulated in SC compared to CO and trends of miR-21 upregulation and let-7a downregulation in CY and HT compared to its control kidneys, when normalized by different combinations of miR-20a, miR-25 and miR-26a. Our findings established miR-20a, miR-25, and miR-26a as the best housekeeping genes for miRNA expression analyses by RT-qPCR in kidney tissues of Pkd1-deficient mouse models.

SUBMITTER: Munoz JJ

PROVIDER: S-EPMC6959247 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Identification of housekeeping genes for microRNA expression analysis in kidney tissues of Pkd1 deficient mouse models.

Muñoz J J JJ Anauate A C AC Amaral A G AG Ferreira F M FM Meca R R Ormanji M S MS Boim M A MA Onuchic L F LF Heilberg I P IP

Scientific reports 20200114 1

Polycystic kidney disease is a complex clinical entity which comprises a group of genetic diseases that leads to renal cyst development. We evaluated the most suitable housekeeping genes for microRNA expression by RT-qPCR analyses of kidney tissues in Pkd1-deficient mouse models from a panel of five candidates genes (miR-20a, miR-25, miR-26a, miR-191 and U6) and 3 target genes (miR-17, miR-21 and let-7a) using samples from kidneys of cystic mice (Pkd1<sup>flox/flox</sup>:Nestin<sup>cre</sup>, CY ...[more]

PMID: 31937827

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Project description:BackgroundIschemia-reperfusion injury and drug-induced nephrotoxicity are the two most common reasons for acute kidney injury (AKI). However, little attention has been paid to early activation of fibroblasts in the progression of AKI to chronic kidney disease (CKD). The present study aimed to identify related genes and pathways on fibroblast activation in two mouse models of AKI: ischemia-reperfusion injury (IRI) model and folic acid (FA)-induced injury model.MethodsThe microarray expression profiles of GSE62732 and GSE121190 were downloaded from the GEO database, and the differentially expressed genes (DEGs) was analyzed using the Limma package of R software. Principal component analysis (PCA) was also performed using R. The functional information of gene products was annotated by Gene Ontology (GO) and DAVID online database, and the pathway analysis was carried out by using the Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) database. Protein-protein interactions (PPI) network was constructed by STRING and Cytoscape. Furthermore, in the Hypoxia/Reoxygenation (H/R) model, the morphological changes of cells were observed under microscope and the expression of the hub genes in NRK-49F cells were validated by qRT-PCR assays.ResultsA total of 457 DEGs were identified. Among these, 215 DEGs were upregulated and 242 DEGs were downregulated in the acute injured samples compared with uninjured samples. The GO enrichment analysis indicated that these DEGs were mainly involved in transport, the oxidation-reduction process, the metabolic process, metal ion binding, hydrolase activity, and oxidoreductase activity. The KEGG analysis revealed that these DEGs were significantly enriched in the PI3K-Akt signaling pathway, protein digestion and absorption pathway, and focal adhesion pathway. The hub genes including Hnf4α, Pck1 and Timp1 were validated by the qRT-PCR assay in NRK-49F cells in the H/R model.ConclusionsHnf4α, Pck1 and Timp-1 may play a pivotal role in the early activation of fibroblasts, providing novel therapeutic strategies for early prediction and treatment of renal fibrosis.

Project description:BACKGROUND: Gene expression analysis using real-time RT-PCR (qRT-PCR) is increasingly important in biological research due to the high-throughput and accuracy of qRT-PCR. For accurate and reliable gene expression analysis, normalization of gene expression data against housekeeping genes or internal control genes is required. The stability of reference genes has a tremendous effect on the results of relative quantification of gene expression by qRT-PCR. The expression stability of reference genes could vary according to tissues, age of individuals and experimental conditions. In the pig however, very little information is available on the expression stability of reference genes. The aim of this research was therefore to develop a new set of reference genes which can be used for normalization of mRNA expression data of genes expressed in varieties of porcine tissues at different ages. RESULTS: The mRNA expression stability of nine commonly used reference genes (B2M, BLM, GAPDH, HPRT1, PPIA, RPL4, SDHA, TBP and YWHAZ) was determined in varieties of tissues collected from newborn, young and adult pigs. geNorm, NormFinder and BestKeeper software were used to rank the genes according to their stability. geNorm software revealed that RPL4, PPIA and YWHAZ showed high stability in newborn and adult pigs, while B2M, YWHAZ and SDHA showed high stability in young pigs. In all cases, GAPDH showed the least stability in geNorm. NormFinder revealed that TBP was the most stable gene in newborn and young pigs, while PPIA was most stable in adult pigs. Moreover, geNorm software suggested that the geometric mean of three most stable gene would be the suitable combination for accurate normalization of gene expression study. CONCLUSIONS: Although, there was discrepancy in the ranking order of reference genes obtained by different analysing software methods, the geometric mean of the RPL4, PPIA and YWHAZ seems to be the most appropriate combination of housekeeping genes for accurate normalization of gene expression data in different porcine tissues at different ages.

Dataset Information

Identification of housekeeping genes for microRNA expression analysis in kidney tissues of Pkd1 deficient mouse models.

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Identification of housekeeping genes for microRNA expression analysis in kidney tissues of Pkd1 deficient mouse models.

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