Phenotypically supervised single cell sequencing parses within-cell-type heterogeneity

We used a phenotypic cell sorting technique to ask whether phenotypically supervised scRNAseq analysis (pheno-scRNAseq) can provide more insight into heterogeneous cell behaviors than unsupervised scRNAseq. Using a simple 3D in vitro breast cancer (BRCA) model, we conducted pheno-scRNAseq on invasive and non-invasive cells and compared the results to phenotype-agnostic scRNAseq analysis. Pheno-scRNAseq identified unique and more selective differentially expressed genes (DEGs) than unsupervised scRNAseq analysis. Functional studies validated the utility of pheno-scRNAseq in understanding within-cell-type functional heterogeneity and revealed that migration phenotypes were coordinated with specific metabolic, proliferation, stress, and immune phenotypes. Overall design: Transcriptomic examination of human and mouse breast cancer cells for phenotypic heterogeneity. Phenotypic supervision: Cells were phototagged using photoconversion of Dendra2 that was transduced into MDA-MB-231 cells. Cells were then sorted using fluorescence activated cell sorting. 2 samples were phenotypically supervised, 2 samples were phenotype-agnostic.