Research Article

Identification of marker genes in diabetic wounds by DNA microarray study

Published: November 07, 2013
Genet. Mol. Res. 12 (4) : 5348-5355 DOI: 10.4238/2013.November.7.9

Abstract

This study aimed to identify marker genes in diabetic wounds using a dataset based on a DNA microarray of dermal lymphatic endothelial cells, and our results provide a basic understanding of diabetic wounds through further study of these differentially expressed genes (DEGs). From the Gene Expression Omnibus database, we downloaded a gene expression microarray (GSE38396) that includes 8 samples: 4 normal controls and 4 disease samples (type II diabetes). We then identified genes that were differentially expressed between normal and disease samples using packages in R language, constructed a protein-protein interaction (PPI) network and analyzed modules in the network. In addition, phylogenetic analysis was performed by MEGA to find the most conserved genes. Two hundred and thirteen genes were identified as being differentially expressed between normal and disease samples, and we constructed a PPI network that included 213 pairs of proteins. We then identified a module including 20 genes, the function of which was significantly enriched in wounding response. Lastly, the most conserved genes, CD44 and CCL5, were identified through phylogenetic analysis. In summary, we found differentially expressed marker genes, a wounding response-related module, and the most important genes CD44 and CCL5. Our findings suggest new approaches to therapies for diabetic wounds.

This study aimed to identify marker genes in diabetic wounds using a dataset based on a DNA microarray of dermal lymphatic endothelial cells, and our results provide a basic understanding of diabetic wounds through further study of these differentially expressed genes (DEGs). From the Gene Expression Omnibus database, we downloaded a gene expression microarray (GSE38396) that includes 8 samples: 4 normal controls and 4 disease samples (type II diabetes). We then identified genes that were differentially expressed between normal and disease samples using packages in R language, constructed a protein-protein interaction (PPI) network and analyzed modules in the network. In addition, phylogenetic analysis was performed by MEGA to find the most conserved genes. Two hundred and thirteen genes were identified as being differentially expressed between normal and disease samples, and we constructed a PPI network that included 213 pairs of proteins. We then identified a module including 20 genes, the function of which was significantly enriched in wounding response. Lastly, the most conserved genes, CD44 and CCL5, were identified through phylogenetic analysis. In summary, we found differentially expressed marker genes, a wounding response-related module, and the most important genes CD44 and CCL5. Our findings suggest new approaches to therapies for diabetic wounds.

About the Authors