Profiling of chicken adipose tissue gene expression by genome array

通过基因组阵列分析鸡脂肪组织基因表达

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作者:Hong-Bao Wang, Hui Li, Qi-Gui Wang, Xin-Yu Zhang, Shou-Zhi Wang, Yu-Xiang Wang, Xiu-Ping Wang

Background

Excessive accumulation of lipids in the adipose tissue is a major problem in the present-day broiler industry. However, few studies have analyzed the expression of adipose tissue genes that are involved in pathways and mechanisms leading to adiposity in chickens. Gene expression profiling of chicken adipose tissue could provide key information about the ontogenesis of fatness and clarify the molecular mechanisms underlying obesity. In this study, Chicken Genome Arrays were used to construct an adipose tissue gene expression profile of 7-week-old broilers, and to screen adipose tissue genes that are differentially expressed in lean and fat lines divergently selected over eight generations for high and low abdominal fat weight.

Conclusion

Our results establish the groundwork for further studies of the basic genetic control of growth and development of chicken adipose tissue, and will be beneficial in clarifying the molecular mechanism of obesity in chickens.

Results

The gene expression profiles detected 13,234-16,858 probe sets in chicken adipose tissue at 7 weeks, and genes involved in lipid metabolism and immunity such as fatty acid binding protein (FABP), thyroid hormone-responsive protein (Spot14), lipoprotein lipase(LPL), insulin-like growth factor binding protein 7(IGFBP7) and major histocompatibility complex (MHC), were highly expressed. In contrast, some genes related to lipogenesis, such as leptin receptor, sterol regulatory element binding proteins1 (SREBP1), apolipoprotein B(ApoB) and insulin-like growth factor 2(IGF2), were not detected. Moreover, 230 genes that were differentially expressed between the two lines were screened out; these were mainly involved in lipid metabolism, signal transduction, energy metabolism, tumorigenesis and immunity. Subsequently, real-time RT-PCR was performed to validate fifteen differentially expressed genes screened out by the microarray approach and high consistency was observed between the two methods.

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