MicroRNAs based regulation of cytokine regulating immune expressed genes and their transcription factors in COVID-19

IF 0.8 Q4 GENETICS & HEREDITY
Manoj Khokhar, Sojit Tomo, Purvi Purohit
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引用次数: 20

Abstract

Background

Coronavirus disease 2019 is characterized by the elevation of a broad spectrum of inflammatory mediators associated with poor disease outcomes. We aimed at an in-silico analysis of regulatory microRNA and their transcription factors (TF) for these inflammatory genes that may help to devise potential therapeutic strategies in the future.

Methods

The cytokine regulating immune-expressed genes (CRIEG) were sorted from literature and the GEO microarray dataset. Their co-differentially expressed miRNA and transcription factors were predicted from publicly available databases. Enrichment analysis was done through mienturnet, MiEAA, Gene Ontology, and pathways predicted by KEGG and Reactome pathways. Finally, the functional and regulatory features were analyzed and visualized through Cytoscape.

Results

Sixteen CRIEG were observed to have a significant protein-protein interaction network. The ontological analysis revealed significantly enriched pathways for biological processes, molecular functions, and cellular components. The search performed in the miRNA database yielded ten miRNAs that are significantly involved in regulating these genes and their transcription factors.

Conclusion

An in-silico representation of a network involving miRNAs, CRIEGs, and TF, which take part in the inflammatory response in COVID-19, has been elucidated. Thus, these regulatory factors may have potentially critical roles in the inflammatory response in COVID-19 and may be explored further to develop targeted therapeutic strategies and mechanistic validation.

Abstract Image

Abstract Image

Abstract Image

基于microrna的细胞因子调控新冠病毒免疫表达基因及其转录因子
2019冠状病毒病的特点是与疾病预后不良相关的广谱炎症介质升高。我们的目标是对这些炎症基因的调控microRNA及其转录因子(TF)进行计算机分析,这可能有助于在未来设计潜在的治疗策略。方法从文献资料和GEO微阵列数据中筛选细胞因子调节免疫表达基因(CRIEG)。他们的共差异表达的miRNA和转录因子从公开的数据库中预测。富集分析通过mienturnet、MiEAA、Gene Ontology以及KEGG和Reactome途径预测的途径进行。最后,通过Cytoscape分析并可视化了其功能和调控特性。结果16个CRIEG具有明显的蛋白-蛋白相互作用网络。本体论分析显示,生物过程、分子功能和细胞成分的通路显著丰富。在miRNA数据库中进行的搜索产生了10个显著参与调节这些基因及其转录因子的miRNA。已经阐明了参与COVID-19炎症反应的mirna、CRIEGs和TF网络的计算机表征。因此,这些调节因子可能在COVID-19的炎症反应中发挥潜在的关键作用,可以进一步探索以制定有针对性的治疗策略和机制验证。
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来源期刊
Meta Gene
Meta Gene Biochemistry, Genetics and Molecular Biology-Genetics
CiteScore
1.10
自引率
0.00%
发文量
20
期刊介绍: Meta Gene publishes meta-analysis, polymorphism and population study papers that are relevant to both human and non-human species. Examples include but are not limited to: (Relevant to human specimens): 1Meta-Analysis Papers - statistical reviews of the published literature of human genetic variation (typically linked to medical conditionals and/or congenital diseases) 2Genome Wide Association Studies (GWAS) - examination of large patient cohorts to identify common genetic factors that influence health and disease 3Human Genetics Papers - original studies describing new data on genetic variation in smaller patient populations 4Genetic Case Reports - short communications describing novel and in formative genetic mutations or chromosomal aberrations (e.g., probands) in very small demographic groups (e.g., family or unique ethnic group). (Relevant to non-human specimens): 1Small Genome Papers - Analysis of genetic variation in organelle genomes (e.g., mitochondrial DNA) 2Microbiota Papers - Analysis of microbiological variation through analysis of DNA sequencing in different biological environments 3Ecological Diversity Papers - Geographical distribution of genetic diversity of zoological or botanical species.
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