Time course analysis of large-scale gene expression in incised muscle using correspondence analysis.
Studying the time course of gene expression in injured skeletal muscle would help to estimate the timing of injuries. In this study, we investigated large-scale gene expression in incision-injured mouse skeletal muscle by DNA microarray using correspondence analysis (CA). Biceps femoris muscle sampl...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2020-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0230737 |
| _version_ | 1828958639622193152 |
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| author | Tetsuya Horita Mohammed Hassan Gaballah Mamiko Fukuta Sanae Kanno Hideaki Kato Masataka Takamiya Yasuhiro Aoki |
| author_facet | Tetsuya Horita Mohammed Hassan Gaballah Mamiko Fukuta Sanae Kanno Hideaki Kato Masataka Takamiya Yasuhiro Aoki |
| author_sort | Tetsuya Horita |
| collection | DOAJ |
| description | Studying the time course of gene expression in injured skeletal muscle would help to estimate the timing of injuries. In this study, we investigated large-scale gene expression in incision-injured mouse skeletal muscle by DNA microarray using correspondence analysis (CA). Biceps femoris muscle samples were collected 6, 12, and 24 hours after injury, and RNA was extracted and prepared for microarray analysis. On a 2-dimensional plot by CA, the genes (row score coordinate) located farther from each time series (column score coordinate) had more upregulation at particular times. Each gene was situated in 6 subdivided triangular areas according to the magnitude of the relationship of the fold change (FC) value at each time point compared to the control. In each area, genes for which the ratios of two particular FC values were close to 1 were distributed along the two border lines. There was a tendency for genes whose FC values were almost equal to be distributed near the intersection of these 6 areas. Therefore, the gene marker candidates for estimation of the timing of injuries were detectable according to the location on the CA plot. Moreover, gene sets created by a specific gene and its surrounding genes were composed of genes that showed similar or identical fluctuation patterns to the specific gene. In various analyses on these sets, significant gene ontology term and pathway activity may reflect changes in specific genes. In conclusion, analyses of gene sets based on CA plots is effective for investigation of the time-dependent fluctuation in gene expression after injury. |
| first_indexed | 2024-12-14T08:52:05Z |
| format | Article |
| id | doaj.art-9c23de9d45ff49feaa2c1ec941a825ad |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-14T08:52:05Z |
| publishDate | 2020-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-9c23de9d45ff49feaa2c1ec941a825ad2022-12-21T23:09:01ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-01153e023073710.1371/journal.pone.0230737Time course analysis of large-scale gene expression in incised muscle using correspondence analysis.Tetsuya HoritaMohammed Hassan GaballahMamiko FukutaSanae KannoHideaki KatoMasataka TakamiyaYasuhiro AokiStudying the time course of gene expression in injured skeletal muscle would help to estimate the timing of injuries. In this study, we investigated large-scale gene expression in incision-injured mouse skeletal muscle by DNA microarray using correspondence analysis (CA). Biceps femoris muscle samples were collected 6, 12, and 24 hours after injury, and RNA was extracted and prepared for microarray analysis. On a 2-dimensional plot by CA, the genes (row score coordinate) located farther from each time series (column score coordinate) had more upregulation at particular times. Each gene was situated in 6 subdivided triangular areas according to the magnitude of the relationship of the fold change (FC) value at each time point compared to the control. In each area, genes for which the ratios of two particular FC values were close to 1 were distributed along the two border lines. There was a tendency for genes whose FC values were almost equal to be distributed near the intersection of these 6 areas. Therefore, the gene marker candidates for estimation of the timing of injuries were detectable according to the location on the CA plot. Moreover, gene sets created by a specific gene and its surrounding genes were composed of genes that showed similar or identical fluctuation patterns to the specific gene. In various analyses on these sets, significant gene ontology term and pathway activity may reflect changes in specific genes. In conclusion, analyses of gene sets based on CA plots is effective for investigation of the time-dependent fluctuation in gene expression after injury.https://doi.org/10.1371/journal.pone.0230737 |
| spellingShingle | Tetsuya Horita Mohammed Hassan Gaballah Mamiko Fukuta Sanae Kanno Hideaki Kato Masataka Takamiya Yasuhiro Aoki Time course analysis of large-scale gene expression in incised muscle using correspondence analysis. PLoS ONE |
| title | Time course analysis of large-scale gene expression in incised muscle using correspondence analysis. |
| title_full | Time course analysis of large-scale gene expression in incised muscle using correspondence analysis. |
| title_fullStr | Time course analysis of large-scale gene expression in incised muscle using correspondence analysis. |
| title_full_unstemmed | Time course analysis of large-scale gene expression in incised muscle using correspondence analysis. |
| title_short | Time course analysis of large-scale gene expression in incised muscle using correspondence analysis. |
| title_sort | time course analysis of large scale gene expression in incised muscle using correspondence analysis |
| url | https://doi.org/10.1371/journal.pone.0230737 |
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