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Insight into molecular profile changes after skeletal muscle contusion using microarray and bioinformatics analyses
Authors:Na Li  Ru-feng Bai  Chun Li  Li-hong Dang  Qiu-xiang Du  Qian-qian Jin  Jie Cao  Ying-yuan Wang  Jun-hong Sun
Institution:1.School of Forensic Medicine, Shanxi Medical University, Jinzhong 030604, Shanxi, China;2.Key Laboratory of Evidence Science, China University of Political Science and law, Beijing, China;3.Collaborative Innovation Center of Judicial Civilization, Beijing, China
Abstract:Muscle trauma frequently occurs in daily life. However, the molecular mechanisms of muscle healing, which partly depend on the extent of the damage, are not well understood. The present study aimed to investigate gene expression profiles following mild and severe muscle contusion, and to provide more information about the molecular mechanisms underlying the repair process. A total of 33 rats were divided randomly into control (n=3), mild contusion (n=15), and severe contusion (n=15) groups; the contusion groups were further divided into five subgroups (1, 3, 24, 48, and 168 h post-injury; n=3 per subgroup). A total of 2844 and 2298 differentially expressed genes (DEGs) were identified using microarray analyses in the mild and severe contusions, respectively. From the analysis of the 1620 coexpressed genes in mildly and severely contused muscle, we discovered that the gene profiles in functional modules and temporal clusters were similar between the mild and severe contusion groups; moreover, the genes showed time-dependent patterns of expression, which allowed us to identify useful markers of wound age. The functional analyses of genes in the functional modules and temporal clusters were performed, and the hub genes in each module–cluster pair were identified. Interestingly, we found that genes down-regulated at 24-48 h were largely associated with metabolic processes, especially of the oxidative phosphorylation (OXPHOS), which has been rarely reported. These results improve our understanding of the molecular mechanisms underlying muscle repair, and provide a basis for further studies of wound age estimation.
Keywords:bioinformatics analysis  gene expression profile  microarray  Skeletal muscle healing  wound age
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