Discovery of consensus gene signature and intermodular connectivity defining self-renewal of human embryonic stem cells

Abstract

Molecular markers defining self-renewing pluripotent embryonic stem cells (ESCs) have been identified by relative comparisons between undifferentiated and differentiated cells. Most of analysis has been done under a specific differentiation condition that may present significantly different molecular changes over others. Therefore, it is currently unclear if there are true consensus markers defining undifferentiated human ESCs (hESCs). To identify a set of key genes consistently altered during differentiation of hESCs regardless of differentiation conditions, we have performed microarray analysis on undifferentiated hESCs (H1 and H9) and differentiated EBs and validated our results using publicly available expression array datasets. We constructed consensus modules by Weighted Gene Coexpression Network Analysis and discovered novel markers that are consistently present in undifferentiated hESCs under various differentiation conditions. We have validated top markers (downregulated: LCK, KLKB1, and SLC7A3; upregulated: RhoJ, Zeb2, and Adam12) upon differentiation. Functional validation analysis of LCK in self-renewal of hESCs using LCK inhibitor or gene silencing with siLCK resulted in a loss of undifferentiation characteristics-morphological change, reduced alkaline phosphatase activity, and pluripotency gene expression, demonstrating a potential functional role of LCK in self-renewal of hESCs. We have designated hESC markers to interactive networks in the genome, identifying possible interacting partners and showing how new markers relate to each other. Furthermore, comparison of these datasets with available datasets from induced pluripotent stem cells (iPSCs) revealed that the level of these newly identified markers was correlated to the establishment of iPSCs, which may imply a potential role of these markers in gaining of cellular potency.

Keywords: Consensus gene signature; Human embryonic stem cells; Interactive molecular network; Self-renewal; Weighted Gene Coexpression Network Analysis.