(194e) Using Rnaseq to Investigate Population Heterogeneity Among Human Pluripotent Stem Cells Cultured on 2D or in 3D Biomaterial Scaffolds

Human pluripotent stem cells, with potential for indefinite self-renewal, may be an unlimited source of cells for a variety of biomedical applications including cell replacement therapy, disease modeling or drug screening. Often, success in these applications rely on our ability to control the stem-cell fate during expansion or differentiation. However, culture platform and stochasticity are two of the major factors that influence stem cell fate and affect the desired output. Single-cell RNAseq is a powerful, high-throughput, rapidly-evolving technique that may help us understand the effect of these factors on stem cell fate. Here, we use single-cell analysis to investigate the population heterogeneity within human induced pluripotent stem cells (hiPSCs) cultured either on 2D or in 3D scaffolds. We simultaneously analyzed ~10,000 different cells and identified ~26000 different genes. Subsequently, we developed a customized data analysis pipeline and observed distinct transcriptomic differences (specifically, ~8000 differentially expressed genes) between cells cultured on 2D and in 3D, and biological pathway analysis revealed phenotypes that correlated with our experimental observations. Importantly, single-cell analysis identified several subpopulations within the cells cultured using each platform, with unique biological properties. Further investigation of the population heterogeneity may elucidate the heterogeneous stem cell response to homogenous inputs.