生物
转录因子
增强子
脂肪肝
基因
CD36
基因调控网络
计算生物学
遗传学
疾病
基因表达
内科学
医学
作者
Yingying Hu,Run Xu,Jing Feng,Qingwei Zhang,Lifu Zhang,Yiyang Li,Xiuxiu Sun,Jin Nan Gao,Ximing Chen,Menghan Du,Zhouxiu Chen,Xin Liu,Yuhua Fan,Yong Zhang
标识
DOI:10.1016/j.jnutbio.2024.109584
摘要
Hyperlipidemia (HLP) is a prevalent metabolic disorder and a significant risk factor for cardiovascular disease. According to recent discoveries, super-enhancers (SEs) play a role in the increased expression of genes that encode important regulators of both cellular identity and the progression of diseases. However, the underlying function of SEs in the development of HLP is still unknown. We performed an integrative analysis of data on H3K27ac ChIP-seq and RNA sequencing obtained from liver tissues of mice under a low-fat diet (LFD) and high-fat diet (HFD) from GEO database. The rank ordering of super enhancers algorithm was employed for the computation and identification of SEs. A total of 1877 and 1847 SEs were identified in the LFD and HFD groups, respectively. The SE inhibitor JQ1 was able to potently reverse lipid deposition and the increased intracellular triglyceride and total cholesterol induced by oleic acid, indicating that SEs are involved in regulating lipid accumulation. 278 were considered as HFD-specific SEs (HSEs). GO and KEGG pathway enrichment analysis of the upregulated HSEs-associated genes revealed that they were mainly involved in lipid metabolic pathway. Four hub genes, namely Cd36, Pex11a, Ech1, and Cidec, were identified in the HSEs-associated protein‐protein interaction network, and validated with two other datasets. Finally, we constructed a HSEs-specific regulatory network with Cidec and Cd36 as the core through the prediction and verification of transcription factors. Our study constructed a HSEs-associated regulatory network in the pathogenesis of HLP, providing new ideas for the underlying mechanisms and therapeutic targets of HLP.
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