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.
journal_name
Sci Repjournal_title
Scientific reportsauthors
Perez LJ,Rios L,Trivedi P,D'Souza K,Cowie A,Nzirorera C,Webster D,Brunt K,Legare JF,Hassan A,Kienesberger PC,Pulinilkunnil Tdoi
10.1038/s41598-017-03730-9subject
Has Abstractpub_date
2017-06-15 00:00:00pages
3612issue
1issn
2045-2322pii
10.1038/s41598-017-03730-9journal_volume
7pub_type
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