通过生物信息学方法鉴定人类骨骼肌的运动和时间效应。

Identification of the Exercise and Time Effects on Human Skeletal Muscle through Bioinformatics Methods.

机构信息

School of Sports Science and Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China.

Department of Rehabilitation, Minhang Hospital Fudan University, 170 Xin-Song Road, Shanghai 201199, China.

出版信息

Genet Res (Camb). 2022 Aug 21;2022:9582363. doi: 10.1155/2022/9582363. eCollection 2022.

DOI:10.1155/2022/9582363

PMID:36072011

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9420641/

Abstract

BACKGROUND

The human body has more than 600 kinds of skeletal muscles, which accounts for about 40% of the whole weight. Most skeletal muscles can make bones move, and their strength and endurance directly affect their performance during exercise.

METHODS

To determine the effects of exercise and time on human skeletal muscle, we downloaded the microarray expression profile of GSE1832 and analyzed it to select differentially expressed genes (DEGs). Then, a protein-protein interaction (PPI) network was established, and the hub genes were identified. Afterwards, DEGs were applied to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Finally, with the help of Gene Set Enrichment Analysis (GSEA), the gene sets in the 7 samples were enriched in the KEGG pathway.

RESULTS

Through a series of bioinformatics analyses, we obtained a total of 271 DEGs. After that, four hub genes were determined through the PPI network, namely, EP300, STAT1, CDKN1A, and RAC2. In addition, we got that these DEGs were enriched in GO, such as regulation of cell population proliferation, cellular water homeostasis, and so on, and in KEGG, namely, hepatitis B, Epstein-Barr virus infection, small cell lung cancer, pathways in cancer, and others. Finally, the gene set in the samples obtained by GSEA was enriched in the cell cycle, chemokine signaling pathway, DNA replication, cytokine receptor interaction, ECM receptor interaction, and focal adhesion in KEGG.

CONCLUSION

The findings obtained in this study will provide new clues for elucidating the mechanism of exercise and time on human skeletal muscles.

摘要

背景

人体拥有超过 600 种骨骼肌，占体重的 40%左右。大多数骨骼肌可以使骨骼运动，其力量和耐力直接影响运动时的表现。

方法

为了确定运动和时间对人体骨骼肌的影响，我们下载了 GSE1832 的基因芯片表达谱，并对其进行分析，以选择差异表达基因（DEGs）。然后，构建蛋白质-蛋白质相互作用（PPI）网络，并识别出核心基因。之后，应用 DEGs 进行基因本体论（GO）和京都基因与基因组百科全书（KEGG）富集分析。最后，借助基因集富集分析（GSEA），在 7 个样本中的基因集在 KEGG 通路中富集。

结果

通过一系列生物信息学分析，我们总共获得了 271 个 DEGs。之后，通过 PPI 网络确定了四个核心基因，即 EP300、STAT1、CDKN1A 和 RAC2。此外，我们发现这些 DEGs 富集在 GO 中，如细胞群体增殖的调节、细胞水稳态等，以及在 KEGG 中，如乙型肝炎、爱泼斯坦-巴尔病毒感染、小细胞肺癌、癌症途径等。最后，GSEA 获得的样本中的基因集在 KEGG 中的细胞周期、趋化因子信号通路、DNA 复制、细胞因子受体相互作用、细胞外基质受体相互作用和焦点黏附中富集。