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Evaluation of candidate reference genes for RT-qPCR studies in three metabolism related tissues of mice after caloric restriction

Reverse transcription quantitative-polymerase chain reaction (RT-qPCR) is a routine method for gene expression analysis, and reliable results depend on proper normalization by stable reference genes. Caloric restriction (CR) is a robust lifestyle intervention to slow aging and delay onset of age-ass...

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Detalles Bibliográficos
Autores principales: Gong, Huan, Sun, Liang, Chen, Beidong, Han, Yiwen, Pang, Jing, Wu, Wei, Qi, Ruomei, Zhang, Tie-mei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5138604/
https://www.ncbi.nlm.nih.gov/pubmed/27922100
http://dx.doi.org/10.1038/srep38513
Descripción
Sumario:Reverse transcription quantitative-polymerase chain reaction (RT-qPCR) is a routine method for gene expression analysis, and reliable results depend on proper normalization by stable reference genes. Caloric restriction (CR) is a robust lifestyle intervention to slow aging and delay onset of age-associated diseases via inducing global changes in gene expression. Reliable normalization of RT-qPCR data becomes crucial in CR studies. In this study, the expression stability of 12 candidate reference genes were evaluated in inguinal white adipose tissue (iWAT), skeletal muscle (Sk.M) and liver of CR mice by using three algorithms, geNorm, NormFinder, and Bestkeeper. Our results showed β2m, Ppia and Hmbs as the most stable genes in iWAT, Sk.M and liver, respectively. Moreover, two reference genes were sufficient to normalize RT-qPCR data in each tissue and the suitable pair of reference genes was β2m-Hprt in iWAT, Ppia-Gusb in Sk.M and Hmbs-β2m in liver. By contrast, the least stable gene in iWAT or Sk.M was Gapdh, and in liver was Pgk1. Furthermore, the expression of Leptin and Ppar-γ were profiled in these tissues to validate the selected reference genes. Our data provided a basis for gene expression analysis in future CR studies.