A genome-wide comparison of mesenchymal stem cells derived from human placenta and umbilical cord

Abstract

Objective: The human umbilical cord and placenta have been considered as attractive alternative sources for noninvasive isolation of human mesenchymal stem cells (hMSCs). Different sources of MSC may have individual differentiation potential and phenotype. In this study, we compared the genome-wide expression data of umbilical cord and placenta derived hMSCs to identify specific differential expression genes (DEGs) and corresponding functions.

Materials and methods: We collected human placental tissues and umbilical cord from healthy full-term placenta (n = 17). The genome-wide gene expression data of hMSCs were used to analyze and compare with that of fibroblasts. We identified the differential expression genes (DEGs) based on the Student's t-test and one-way ANOVA.

Results: According to the DEGs of umbilical cord and placenta, we used the Venn diagram to evaluate the consistence and specific genes. There are 390 umbilical cord specific DEGs which functions are related to movement of sub-cellular component. Then, the DEGs derived from placenta have two major clusters (i.e., placenta-specific (AM-CM-specific) and UC-like (UC-CD-specific)). 247 placenta-specific DEGs are down-regulated and involved in cell communication. 278 UC-like genes are up-regulated and are involved in the cell cycle, cell division, and DNA repair process. Finally, we also identified 239 umbilical cord-placenta consistence DEGs. According to the umbilical cord-placenta consistence DEGs, 175 genes are down-regulated and involved in cell death, cell growth, cell developmental processes.

Conclusion: We identified the consistence and specific DEGs of human placenta and umbilical cord based on the genome-wide comparison. Our results indicated that hMSCs derived from umbilical cord and placenta have different gene expression patterns, and most of specific genes are involved in the cell cycle, cell division, cell death, and cell developmental processes.

Keywords: Gene expression pattern analysis; Gene expression profiling; Mesenchymal stem cells; Protein interaction networks.