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Time course analysis of large-scale gene expression in incised muscle using correspondence analysis

ABSTRACT: Time course analysis of large-scale gene expression in incised muscle using correspondence analysis

PROVIDER: PRJNA590120 | ENA |

REPOSITORIES: ENA

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Time course analysis of large-scale gene expression in incised muscle using correspondence analysis

Project description:The time course of wound healing or the estimation of wound age is one of the most important research subjects in forensic pathology. In this study, we obtained microarray data of incision injury samples of mouse skeletal muscle at 3 different time points post-injury (6, 12, and 24 h). To visualize the time course fluctuation in gene expression on a plot, and to examine large-scale data using various analytical methods, correspondence analysis (CA) was carried out on microarray data that was converted to a matrix (data type is fold change (FC) values) consisting of data of each time point (columns) by each gene (rows) as variables. Genes were successfully clustered based on the magnitude relationship of FC values of 3 time series with a CA plot, which effectively visualizes the data of time course experiments.

2019-11-19 | GSE140517 | GEO

Time course analysis of large-scale gene expression in incised muscle using correspondence analysis.

Project 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.

| S-EPMC7094855 | biostudies-literature

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Time course analysis of colon cancer samples

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Large-scale analysis of novel cellular microbes

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Circadian time course

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Time-course gene expression analysis of melanocyte development

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Time-course bud expression data from Populus deltoides

Project description:We conducted micro-array analysis to quantify the global transcriptome variations in floral buds through the course of the year allowing for identification of changing developmental signals. We used RNA samples from floral buds, with bud scale removed, in the upper crown of a sexually mature Populus deltoides tree 2 hours after sunrise.

2011-12-29 | GSE29335 | GEO

Kidney development time course

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Lager beer fermentation time course

Project description:The dynamics of the Saccharomyces carlsbergensis brewing yeast transcriptome during a production scale lager beer fermentation. The transcriptome of a lager brewing yeast (Saccharomyces carlsbergensis, syn. of S. pastorianus), was analysed at 12 different time points spanning a production-scale lager beer fermentation. Generally, the average expression rapidly increased and had a maximum value on day 2, then decreased as the sugar got consumed. Especially genes involved in protein and lipid biosynthesis or glycolysis were highly expressed during the beginning of the fermentation. Similarities as well as significant differences in expression profiles could be observed when comparing to a previous transcriptome analysis of a laboratory yeast grown in YPD. The regional distribution of various expression levels on the chromosomes appeared to be random or near-random and no reduction in expression near telomeres was observed. Keywords: time-course

2002-09-09 | GSE79 | GEO

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