4.2 Article

Reference Gene Optimization for Circadian Gene Expression Analysis in Human Adipose Tissue

Journal

JOURNAL OF BIOLOGICAL RHYTHMS
Volume 35, Issue 1, Pages 84-97

Publisher

SAGE PUBLICATIONS INC
DOI: 10.1177/0748730419883043

Keywords

human adipose tissue; circadian; qRT-PCR; reference gene; sleeve gastrectomy; weight loss surgery

Funding

  1. University of Chicago [DRTC P30DK020595]
  2. [R01 DK103014]
  3. [T32HL007909]

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A hallmark of biology is the cyclical nature of organismal physiology driven by networks of biological, including circadian, rhythms. Unsurprisingly, disruptions of the circadian rhythms through sleep curtailment or shift work have been connected through numerous studies to positive associations with obesity, insulin resistance, and diabetes. Quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) measures oscillation in messenger RNA expression, an essential foundation for the study of the physiological circadian regulatory network. Primarily, measured oscillations have involved the use of reference gene normalization. However, the validation and identification of suitable reference genes is a significant challenge across different biological systems. This study focuses on adipose tissue of premenopausal, otherwise healthy, morbidly obese women voluntarily enrolled after being scheduled for laparoscopic sleeve gastrectomy surgery. Acquisition of tissue was accomplished by aspiratory needle biopsies of subcutaneous adipose tissue 1 to 2 weeks prior to surgery and 12 to 13 weeks following surgery and an in-surgery scalpel-assisted excision of mesenteric adipose tissue. Each biopsy was sterile cultured ex vivo and serially collected every 4 h over approximately 36 h. The candidate reference genes that were tested were 18S rRNA, GAPDH, HPRT1, RPII, RPL13 alpha, and YWHAZ. Three analytic tools were used to test suitability, and the candidate reference genes were used to measure oscillation in expression of a known circadian clock element (Dbp). No gene was deemed suitable as an individual reference gene control, which indicated that the optimal reference gene set was the geometrically averaged 3-gene panel composed of YWHAZ, RPL13 alpha, and GAPDH. These methods can be employed to identify optimal reference genes in other systems.

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