TaqMan® Assays for rapid assessment of genome, epigenome, and quality of integration- free induced Pluripotent Stem Cells

Pluripotent stem cells such as embryonic stem cells (ESC) and induced pluripotent stem cells (iPSC) are commonly identified and characterized based on biomarker expression. Current methods rely on a combination of in vitro and in vivo cellular methods to confirm pluripotency and tri-lineage differentiation potential. As the bottleneck in efficiency of reprogramming is alleviated with faster and better reprogramming systems, there is a need for high throughput characterization methods that allow for rapid confirmation of the quality of the resulting iPSC. Molecular analysis platforms offer a quantitative, accurate and fast alternative to current methods and have recently been utilized to qualify pluripotent stem cells. Several platforms are available for gene expression analysis varying in content and complexity. To determine the optimal method and minimal set of genes required for definitive characterization of pluripotency, we have utilized high density array, medium and low density TaqMan ® qPCR arrays to compare expression pattern of partially reprogrammed clones and fully reprogrammed iPSC in comparison to parental fibroblast and control embryonic stem cells. Results indicate that a focused set of genes in low and medium density arrays can recapitulate the information obtained with large scale arrays with distinct clustering of samples based on their pluripotency that correlated with cellular data. Further, this method was used to identify unique genes that were expressed differentially between partially reprogrammed cells and true iPSC clones as well as pluripotent cells and cells randomly differentiated via embryoid body formation. Additional assays were carried in parallel to assess epigenome signature using TaqMan® Array Human MicroRNA Card and TaqMan® assays for copy number variation. Comprehensive analysis of the resulting data indicates similarities between the pluripotent clones but also detects subtle differences that can be further evaluated for their impact on functionality and long-term stability.