Single-Cell Transcript Profiling of Differentiating Embryonic Stem Cells

Heterogeneity of stem cell populations is a well-known but poorly characterized phenomenon. Here, we demonstrate the qualitative and quantitative power of single-cell transcript analysis to characterize transcriptome dynamics in embryonic stem cells (ESC). In this chapter, we describe a method for isolation, characterization, and analysis of single-cell transcript profiles of individual human ESC that clearly identifies cellular heterogeneity within undifferentiated populations and identifies novel cell types in differentiating cultures. This analysis is presented at a level of depth and resolution not attainable by other methods. None of the insights in this study would have been possible with standard population-level transcript analysis or single-cell FACS analysis of known cell-surface markers. Only by developing robust single-cell transcript profiling techniques and applying these to established stem cell differentiation paradigms were we able to deconstruct complex populations of cells into their component parts. Single-cell analysis can systematically determine unique cellular profiles for use in cell sorting and identification, show the potential to augment standing models of cellular differentiation, and elucidate the behavior of stem cells exiting pluripotency.