Weighted gene co expression network analysis (WGCNA) with key pathways and hub-genes related to micro RNAs in ischemic stroke

IF 1.9 4区 生物学 Q4 CELL BIOLOGY IET Systems Biology Pub Date : 2021-04-20 DOI:10.1049/syb2.12016
Xiang Qu, Shuang Wu, Jinggui Gao, Zhenxiu Qin, Zhenhua Zhou, Jingli Liu
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引用次数: 3

Abstract

Ischemic stroke (IS) is one of the major causes of death and disability worldwide. However, the specific mechanism of gene interplay and the biological function in IS are not clear. Therefore, more research into IS is necessary. Dataset GSE110993 including 20 ischemic stroke (IS) and 20 control specimens are used to establish both groups and the raw RNA-seq data were analysed. Weighted gene co-expression network analysis (WGCNA) was used to screen the key micro-RNA modules. The centrality of key genes were determined by module membership (mm) and gene significance (GS). The key pathways were identified by enrichment analysis with Kyoto Protocol Gene and Genome Encyclopedia (KEGG), and the key genes were validated by protein-protein interactions network. Result: Upon investigation, 1185 up- and down-regulated genes were gathered and distributed into three modules in response to their degree of correlation to clinical traits of IS, among which the turquoise module show a trait-correlation of 0.77. The top 140 genes were further identified by GS and MM. KEGG analysis showed two pathways may evolve in the progress of IS. Discussion: CXCL12 and EIF2a may be important biomarkers for the accurate diagnosis and treatment in IS.

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加权基因共表达网络分析(WGCNA)在缺血性卒中中与微rna相关的关键途径和中心基因
缺血性中风(IS)是世界范围内导致死亡和残疾的主要原因之一。然而,IS中基因相互作用的具体机制和生物学功能尚不清楚。因此,有必要对IS进行更多的研究。数据集GSE110993包括20例缺血性卒中患者和20例对照标本建立两组,并分析原始RNA-seq数据。采用加权基因共表达网络分析(WGCNA)筛选关键微rna模块。关键基因的中心性通过模块隶属度(mm)和基因显著性(GS)来确定。通过京都议定书基因和基因组百科(KEGG)富集分析确定了关键通路,并通过蛋白-蛋白相互作用网络对关键基因进行了验证。结果:经调查,共收集到1185个上调和下调基因,并根据其与IS临床特征的相关程度分为三个模块,其中绿松石模块的性状相关性为0.77。通过GS和MM进一步鉴定了前140个基因。KEGG分析显示,在IS的发展过程中可能有两条途径。讨论:CXCL12和EIF2a可能是IS准确诊断和治疗的重要生物标志物。
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来源期刊
IET Systems Biology
IET Systems Biology 生物-数学与计算生物学
CiteScore
4.20
自引率
4.30%
发文量
17
审稿时长
>12 weeks
期刊介绍: IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells. The scope includes the following topics: Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.
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