IPO8 and FBXL10: New Reference Genes for Gene Expression Studies in Human Adipose Tissue

Abstract

Housekeeping genes frequently used in gene expression studies are highly regulated in human adipose tissue. To ensure a correct interpretation of results, it is critical to select appropriate reference genes. Subcutaneous (SC) and omental (OM) adipose tissue expression was analyzed from lean and obese subjects using whole genome complementary DNA (cDNA) microarrays to identify stably expressed genes and commercial TaqMan low density arrays (LDAs), with 16 common control genes. The best candidate gene from microarrays analysis was F‐box and leucine‐rich repeat protein‐10 (FBXL10) (fold‐change 10−3 P < 0.01), an ubiquitous nucleolar protein evolutionarily conserved. Hypoxanthine phosphoribosyltransferase 1 (HPRT1) and importin 8 (IPO8), were the best reference genes among the 16 genes in the LDAs with coefficient of variation (CV) of 4.51 and 4.55%, respectively. However, when the LDAs data were further analyzed by the geNorm and NormFinder softwares, IPO8, a nuclear protein mediating import of proteins, was the first and the third better reference gene, respectively. IPO8 and FBXL10 were further validated by real‐time PCR in additional OM and SC fat samples and primary cultured preadipocytes. According to their CV, IPO8 resulted more suitable than FBXL10 in both adipose tissue depots and SC preadipocytes, whereas FBXL10 performed better than IPO8 in OM cultured preadipocytes. Both genes expression levels did not change throughout adipogenesis. Thus, we provide clear evidence that IPO8 and FBXL10 are good candidates to use as reference genes in gene expression studies in human OM and SC adipose tissues as well as differentiated primary preadipocytes.

F-box protein 10, an NF-κB-dependent anti-apoptotic protein, regulates TRAIL-induced apoptosis through modulating c-Fos/c-FLIP pathway

“…23,24 Previously, we have demonstrated that c-Fos-mediated inhibition of c-FLIP(L) is an important pathway in regulating resistance to TRAIL. 2 FBXL10 has been implicated in the demethylation of trimethylated histone H3 lysine 4, 9 a negative regulator of c-Jun 10 and a new reference gene for gene expression studies in adipose tissue, 25 while others have found that FBXL10 regulates cell proliferation and senescence through p15. 26 However, FBXL10 0 s role in apoptosis has not been investigated.…”

Expression Profile in Omental and Subcutaneous Adipose Tissue from Lean and Obese Subjects. Repression of Lipolytic and Lipogenic Genes

“…Based on quantitative real-time PCR, LDAs maintain the technical sensitivity and allow to quantify simultaneously a maximal number of 384 genes per card. In our study, 18S and IPO8 served as endogenous control genes, but data were referred to IPO8 as we have recently reported IPO8 as an outstanding gene for normalization of gene expression studies in human adipose tissue in contrast to 18S [6]. For validation experiments, we included genes previously described to vary in obesity that served us as positive controls; however, most of the genes to validate the arrays were chosen on the basis of their differential expression obtained in the arrays and their relationship with processes related to obesity, but not previously described in obesity itself.…”

“…For the validation experiments, further 32 obese patients (17 females and 15 males) providing 30 samples from each depot because some of them were not paired were included in the analysis maintaining the samples of the lean subjects used in the arrays. Most of the lean and obese patients were included in a previous study to address a completely different question [6].…”

Contributions of adipose tissue architectural and tensile properties toward defining healthy and unhealthy obesity

“…Cycle conditions were 50°C for 2 min, 95°C for 10 min, and then 40 cycles of 95°C for 15 s/60°C for 1 min. Amplification cycle threshold (C T) number of housekeeping mRNA [hypoxanthine phosphoribosyltransferase 1; shown to be a reliable housekeeping gene in adipose tissue (19)] for each sample was determined to correct for template loading differences across all target genes (⌬C T ϭ target gene CT Ϫ reference gene CT), and expression values were determined relative to treatment control transcript levels using a previously described mathematical formula (36).…”