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Identification of Potential Gene Signatures Related to Sleep Deprivation.
Journal of Computational Biology ( IF 1.4 ) Pub Date : 2020-06-05 , DOI: 10.1089/cmb.2019.0177
Sha-Sha Ruan 1 , Yi-Chen Xiao 2 , Pei-Cheng He 2 , Yi Wang 3 , Tao Ma 1
Affiliation  

This study aimed to identify possible therapeutic targets involved in sleep deprivation (SD) risks. GSE77393 data set was acquired from Gene Expression Omnibus database. Functional analysis and protein–protein interaction (PPI) analysis were used to extract the differentially expressed genes (DEGs) between two SD samples and control samples. Moreover, submodule network with the same function was further extracted and the functional enrichment analysis of corresponding genes was carried out. Afterward, the transcriptional regulation analysis and drug–gene interaction were also carried out to identify the essential genes associated with SD susceptibility. Totally, 121 DEGs, including 90 consistently upregulated DEGs and 31 downregulated DEGs, were screened and the results of functional analysis indicated that upregulated genes were related to learning or memory and response to drug, whereas downregulated DEGs were mainly responsible for response to UV and cell differentiation. Moreover, PPI network and submodule analysis revealed that many key genes (FOS and BDNF) were hub genes and the KEGG enrichment analysis found that these genes such as FOS and BDNF were considerably enriched in pathways such as MAPK signaling pathway, HTLV-I infection, and Hepatitis B. In addition, two genes (FOS and BDNF) with a higher degree were found to be key regulators and play important roles in the transcriptional regulator network and drug–gene interactions, suggesting that these two genes were associated with SD development. FOS and BDNF might be served as the potential targets for SD treatment.

中文翻译:

与睡眠剥夺相关的潜在基因特征的鉴定。

本研究旨在确定与睡眠剥夺 (SD) 风险相关的可能治疗目标。GSE77393 数据集是从 Gene Expression Omnibus 数据库中获取的。功能分析和蛋白质 - 蛋白质相互作用(PPI)分析用于提取两个SD样品和对照样品之间的差异表达基因(DEG)。此外,进一步提取具有相同功能的子模块网络,并进行相应基因的功能富集分析。随后,还进行了转录调控分析和药物-基因相互作用,以确定与 SD 易感性相关的必需基因。总共 121 个 DEG,包括 90 个持续上调的 DEG 和 31 个下调的 DEG,筛选和功能分析结果表明,上调基因与学习或记忆和对药物的反应有关,而下调的 DEGs 主要负责对紫外线和细胞分化的反应。此外,PPI 网络和子模块分析揭示了许多关键基因(FOSBDNF ) 是枢纽基因,KEGG 富集分析发现FOSBDNF等基因在 MAPK 信号通路、HTLV-I 感染和乙型肝炎等通路中显着富集。 此外,还有两个基因 ( FOSBDNF) ) 被发现是关键调节因子,并在转录调节网络和药物-基因相互作用中发挥重要作用,表明这两个基因与 SD 发展有关。FOSBDNF可能作为 SD 治疗的潜在目标。
更新日期:2020-06-05
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