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• W2002077803 abstract "The transcriptional profiles of cardiac cells derived from murine embryos and from mouse embryonic stem cells (mESCs) have primarily been studied within a cell population. However, the characterization of gene expression in these cells at a single-cell level might demonstrate unique variations that cannot be appreciated within a cell pool. In this study, we aimed to establish a single-cell quantitative PCR platform and perform side-by-side comparison between cardiac progenitor cells (CPCs) and cardiomyocytes (CMs) derived from mESCs and mouse embryos. We first generated a reference map for cardiovascular single cells through quantifying lineage-defining genes for CPCs, CMs, smooth muscle cells (SMCs), endothelial cells (EDCs), fibroblasts and mESCs. This panel was then applied against single embryonic day 10.5 heart cells to demonstrate its ability to identify each endocardial cell and chamber-specific CM. In addition, we compared the gene expression profile of embryo- and mESC-derived CPCs and CMs at different developmental stages and showed that mESC-derived CMs are phenotypically similar to embryo-derived CMs up to the neonatal stage. Furthermore, we showed that single-cell expression assays coupled with time-lapse microscopy can resolve the identity and the lineage relationships between progenies of single cultured CPCs. With this approach, we found that mESC-derived Nkx2-5+ CPCs preferentially become SMCs or CMs, whereas single embryo-derived Nkx2-5+ CPCs represent two phenotypically distinct subpopulations that can become either EDCs or CMs. These results demonstrate that multiplex gene expression analysis in single cells is a powerful tool for examining the unique behaviors of individual embryo- or mESC- derived cardiac cells." @default.
• W2002077803 created "2016-06-24" @default.
• W2002077803 creator A5013355431 @default.
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• W2002077803 date "2015-01-01" @default.
• W2002077803 modified "2023-10-12" @default.
• W2002077803 title "Identification of cardiovascular lineage descendants at single-cell resolution" @default.
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• W2002077803 doi "https://doi.org/10.1242/dev.116897" @default.
• W2002077803 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4352984" @default.
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• W2002077803 hasPublicationYear "2015" @default.
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