通过加权基因共表达网络分析,将toll样受体5和酰基-CoA合成酶长链家族成员1鉴定为中枢基因与严重形式的新冠肺炎相关。

IF 1.9 4区 生物学 Q4 CELL BIOLOGY
Luoyi Wang, Zhaomin Mao, Fengmin Shao
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引用次数: 0

摘要

由于2019年重症冠状病毒病(新冠肺炎)患者的死亡率为25%,因此调查潜在的驱动因素仍然很重要。在这里,作者应用加权基因共表达网络分析来识别多个新冠肺炎表达谱的血液样本中的潜在驱动因素。作者发现,暗条带模块与关键的新冠肺炎显著相关,基因本体论分析表明,术语与炎症途径和凋亡过程相关。作者在Genecards数据集中交叉了差异表达基因、Maximal Clique Centrality计算的枢纽基因和新冠肺炎相关基因,并筛选出两个基因,即toll样受体5(TLR5)和酰基-CoA合成酶长链家族成员1(ACSL1)。基因集富集分析进一步支持它们在炎症途径中的核心作用。此外,通过估计RNA转录物的相对亚群进行的细胞类型鉴定表明,在新冠肺炎危重患者中,TLR5和ACSL1与中性粒细胞富集有关。总之,金确定了两个与关键的新冠肺炎密切相关的中枢基因。这些可能有助于阐明发病机制并有助于免疫疗法的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Identification of toll-like receptor 5 and acyl-CoA synthetase long chain family member 1 as hub genes are correlated with the severe forms of COVID-19 by Weighted gene co-expression network analysis

Identification of toll-like receptor 5 and acyl-CoA synthetase long chain family member 1 as hub genes are correlated with the severe forms of COVID-19 by Weighted gene co-expression network analysis

Since a 25% mortality rate occurred in critical Coronavirus disease 2019 (COVID-19) patients, investigating the potential drivers remains to be important. Here, the authors applied Weighted Gene Co-expression Network Analysis to identify the potential drivers in the blood samples of multiple COVID-19 expression profiles. The authors found that the darkslateblue module was significantly correlated with critical COVID-19, and Gene Ontology analysis indicated terms associated with the inflammation pathway and apoptotic process. The authors intersected differentially expressed genes, Maximal Clique Centrality calculated hub genes, and COVID-19 related genes in the Genecards dataset, and two genes, toll-like receptor 5 (TLR5) and acyl-CoA synthetase long chain family member 1 (ACSL1), were screened out. The Gene Set Enrichment Analysis further supports their core role in the inflammatory pathway. Furthermore, the cell-type identification by estimating relative subsets of RNA transcript demonstrated that TLR5 and ACSL1 were associated with neutrophil enrichment in critical COVID-19 patients. Collectively, the aurthors identified two hub genes that were strongly correlated with critical COVID-19. These may help clarify the pathogenesis and assist the immunotherapy development.

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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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