Summary
For pluripotent stem cells, transcriptional profiling is central to discovering the key genes and gene networks governing the undifferentiated state. However, the heterogeneity of cell states represented in pluripotent cultures have not been described at the transcriptional level. Since gene expression is highly heterogeneous between cells, single-cell RNA sequencing (scRNA-seq) can be used to increase our understanding of how individual pluripotent cells function. Here, we present the scRNA-seq results of 18,787 individual WTC CRISPRi human induced pluripotent stem cells. Four subpopulations were distinguishable on the basis of their pluripotent state including: quiescent (48.3%), proliferative (47.8%), early-primed for differentiation (2.8%) and late-primed for differentiation (1.1%). We identified novel genes and pathways defining each of the subpopulations and developed a multigenic prediction model to accurately classify single cells into subpopulations. This study provides a benchmark single cell dataset that expands our understanding of the cellular complexity of pluripotency.
