Identification of the Exercise and Time Effects on Human Skeletal Muscle through Bioinformatics Methods
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 t...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Genetics Research |
| Online Access: | http://dx.doi.org/10.1155/2022/9582363 |
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| _version_ | 1850172659588923392 |
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| author | Mufang Feng Jie Ji Xiaoliu Li Xinming Ye |
| author_facet | Mufang Feng Jie Ji Xiaoliu Li Xinming Ye |
| author_sort | Mufang Feng |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-cda1aa49cd1d49b891d3d89ef6038d16 |
| institution | OA Journals |
| issn | 1469-5073 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Genetics Research |
| spelling | doaj-art-cda1aa49cd1d49b891d3d89ef6038d162025-08-20T02:20:02ZengWileyGenetics Research1469-50732022-01-01202210.1155/2022/9582363Identification of the Exercise and Time Effects on Human Skeletal Muscle through Bioinformatics MethodsMufang Feng0Jie Ji1Xiaoliu Li2Xinming Ye3School of Sports Science and EngineeringDepartment of RehabilitationDepartment of RehabilitationSchool of Sports Science and EngineeringBackground. 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.http://dx.doi.org/10.1155/2022/9582363 |
| spellingShingle | Mufang Feng Jie Ji Xiaoliu Li Xinming Ye Identification of the Exercise and Time Effects on Human Skeletal Muscle through Bioinformatics Methods Genetics Research |
| title | Identification of the Exercise and Time Effects on Human Skeletal Muscle through Bioinformatics Methods |
| title_full | Identification of the Exercise and Time Effects on Human Skeletal Muscle through Bioinformatics Methods |
| title_fullStr | Identification of the Exercise and Time Effects on Human Skeletal Muscle through Bioinformatics Methods |
| title_full_unstemmed | Identification of the Exercise and Time Effects on Human Skeletal Muscle through Bioinformatics Methods |
| title_short | Identification of the Exercise and Time Effects on Human Skeletal Muscle through Bioinformatics Methods |
| title_sort | identification of the exercise and time effects on human skeletal muscle through bioinformatics methods |
| url | http://dx.doi.org/10.1155/2022/9582363 |
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