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通过转录组网络分析鉴定的肺泡缺氧潜在候选基因。

Potential candidate genes for alveolar hypoxia identified by transcriptome network analysis.

机构信息

Department of Cardiovascular Diseases, Changhai Hospital, Second Military Medical University, 168 Changhai Road, Shanghai 200433, China.

出版信息

Medicina (Kaunas). 2012;48(11):572-80.

PMID:23455892
Abstract

BACKGROUND. Alveolar hypoxia is an important condition related to many disorders such as chronic pulmonary hypertension, pulmonary vasoconstriction, and pulmonary vascular remodeling. The aim of present study was to disclose the biological response and the potential transcriptome networks regulating the hypoxia response in the lungs. MATERIALS AND METHODS. In this study, the microarray dataset GSE11341 was used to construct a regulatory network and identify the potential genes related to alveolar hypoxia. In addition, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) term enrichment analyses were also performed. RESULTS. Hypoxia inducible factor 1 alpha (HIF-1α), peroxisome proliferator-activated receptor gamma (PPARγ), and nuclear factor of kappa light polypeptide gene enhancer in B cells (NF-кB) were to be the hub nodes in the transcriptome network. HIF-1α may regulate potassium voltage-gated channel, shaker-related subfamily, member (5KCNA5), solute carrier family 2 (facilitated glucose transporter), member (1SLC2A1), and heme oxygenase (decycling) 1 (HMOX1) expression through the regulation of membrane potential, glucose metabolism, and anti-inflammation pathways. HMOX-1 mediates signaling pathways that relate to NF-кB. CCND1 (cyclin D1) expression could be regulated by PPARγ and HIF-1α via the cell cycle pathway. In addition, new transcriptional factors and target genes, such as phosphofructokinase (PFKL, liver), aldolase A (ALDOA, fructose-bisphosphate), and trefoil factor 3 (intestinal) (TFF3), were also identified. CONCLUSIONS. Transcriptome network analysis is a helpful method for the identification of the candidate genes in alveolar hypoxia. The KEGG pathway and GO term analysis are beneficial in the prediction of the underlying molecular mechanism of these identified genes in alveolar hypoxia.

摘要

背景

肺泡缺氧是与许多疾病相关的重要条件,如慢性肺动脉高压、肺血管收缩和肺血管重塑。本研究旨在揭示调节肺部缺氧反应的生物学反应和潜在转录组网络。

材料和方法

本研究使用微阵列数据集 GSE11341 构建调控网络,鉴定与肺泡缺氧相关的潜在基因。此外,还进行了京都基因与基因组百科全书(KEGG)途径和基因本体论(GO)术语富集分析。

结果

缺氧诱导因子 1 阿尔法(HIF-1α)、过氧化物酶体增殖物激活受体γ(PPARγ)和核因子 kappa 轻链增强子 B 细胞(NF-кB)是转录组网络中的枢纽节点。HIF-1α可能通过调节膜电位、葡萄糖代谢和抗炎途径,调节钾电压门控通道、Shaker 相关亚家族成员 5(5KCNA5)、溶质载体家族 2(促进葡萄糖转运体)成员 1(SLC2A1)和血红素加氧酶(脱环)1(HMOX1)的表达。HMOX-1 介导与 NF-кB 相关的信号通路。CCND1(周期蛋白 D1)的表达可通过细胞周期途径被 PPARγ 和 HIF-1α 调节。此外,还鉴定了新的转录因子和靶基因,如磷酸果糖激酶(PFKL,肝脏)、醛缩酶 A(ALDOA,果糖-二磷酸)和三叶因子 3(肠道)(TFF3)。

结论

转录组网络分析是鉴定肺泡缺氧候选基因的有用方法。KEGG 途径和 GO 术语分析有助于预测这些鉴定基因在肺泡缺氧中的潜在分子机制。

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