ArticleScientific reports2017
Validation of optimal reference genes for quantitative real time PCR in muscle and adipose tissue for obesity and diabetes research.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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36 citing papers in PubMed, 67 citations in OpenAlex.
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- LRP10, PGK1 and RPLP0: Best Reference Genes in Periprostatic Adipose Tissue under Obesity and Prostate Cancer Conditions.International journal of molecular sciences · 2023Article
- Multitissue responses to exercise: a MoTrPAC feasibility study.Journal of applied physiology (Bethesda, Md. : 1985) · 2023Article
- Altered sialin mRNA gene expression in type 2 diabetic male Wistar rats: implications for nitric oxide deficiency.Scientific reports · 2023Article
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- Critical Sites on Ostreolysin Are Responsible for Interaction with Cytoskeletal Proteins.Biomedicines · 2022Article
- Review
- Transcriptome-based selection and validation of optimal reference genes in perirenal adipose developing of goat (Frontiers in veterinary science · 2022Article
- Potential of Hibiscus sabdariffa Linn. in managing FGF21 resistance in diet-induced-obesity rats via miR-34a regulation.Veterinary medicine and science · 2022Article
- RPS13, a potential universal reference gene for normalisation of gene expression in multiple human normal and cancer tissue samples.Molecular biology reports · 2021Article
- Identification of Novel Endogenous Controls for qPCR Normalization in SK-BR-3 Breast Cancer Cell Line.Genes · 2021Article
- Identification of suitable reference genes for mesenchymal stem cells from menstrual blood of women with endometriosis.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
12 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The global incidence of obesity has led to an increasing need for understanding the molecular mechanisms that drive this epidemic and its comorbidities. Quantitative real-time RT-PCR (RT-qPCR) is the most reliable and widely used method for gene expression analysis. The selection of suitable reference genes (RGs) is critical for obtaining accurate gene expression information. The current study aimed to identify optimal RGs to perform quantitative transcriptomic analysis based on RT-qPCR for obesity and diabetes research, employing in vitro and mouse models, and human tissue samples. Using the ReFinder program we evaluated the stability of a total of 15 RGs. The impact of choosing the most suitable RGs versus less suitable RGs on RT-qPCR results was assessed. Optimal RGs differed between tissue and cell type, species, and experimental conditions. By employing different sets of RGs to normalize the mRNA expression of peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α), we show that sub-optimal RGs can markedly alter the PGC1α gene expression profile. Our study demonstrates the importance of validating RGs prior to normalizing transcriptional expression levels of target genes and identifies optimal RG pairs for reliable RT-qPCR normalization in cells and in human and murine muscle and adipose tissue for obesity/diabetes research.
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