ArticleScientific reports2022
Determination of reference genes as a quantitative standard for gene expression analysis in mouse mesangial cells stimulated with TGF-β.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed, 6 citations in OpenAlex.
- Identification of Stable Housekeeping Genes for miRNA Expression Studies in a Mouse Unilateral Ureteral Obstruction Model.Biochemical genetics · 2026Article
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5 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Reverse transcription-quantitative polymerase chain reaction (RT-PCR) is the gold standard technique for gene expression analysis, but the choice of quantitative reference genes (housekeeping genes, HKG) remains challenging. Identify the best HKG is essential for estimating the expression level of target genes. Therefore, the aim of this study was to determine the best HKG for an in vitro model with mouse mesangial cells (MMCs) stimulated with 5 ng/mL of TGF-β. Five candidates HKG were selected: Actb, Hprt, Gapdh, 18S and Ppia. After quantitative expression, the best combination of these genes was analyzed in silico using six software programs. To validate the results, the best genes were used to normalize the expression levels of fibronectin, vimentin and α-SMA. In silico analysis revealed that Ppia, Gapdh and 18S were the most stable genes between the groups. GenEX software and Spearman's correlation determined Ppia and Gapdh as the best HKG pair, and validation of the HKG by normalizing fibronectin, vimentin and α-SMA were consistent with results from the literature. Our results established the combination of Ppia and Gapdh as the best HKG pair for gene expression analysis by RT-PCR in this in vitro model using MMCs treated with TGF-β.
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