Transcriptomics

Dataset Information

0

Identification of Cardiovascular Lineage Descendants at Single Cell Resolution


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 may demonstrate unique variations that are not able to be appreciated as a pool. In this study, we aimed to establish a single cell quantitative PCR platform and perform side-by-side comparison between cardiac progenitors cells (CPCs) and cardiomyocytes (CMs) derived from mESC 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 day 10.5 embryonic heart single 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 CM is phenotypically similar to embryo-derived CM up to the neonatal stage. Furthermore, we show that single cell expression assay coupled with time-lapse microscopy can resolve the identity and the lineage relationships between progenies of single cultured CPC. With this approach, we found differential propensity for mESC-derived CPCs to become SMCs or CMs, whereas single embryo-derived CPC to become either EDCs or CMs. These results demonstrate that multiplex gene expression analysis in single cells is a powerful tool in examining the unique behavior in individual embryo- or mESC-derived cardiac cells.

ORGANISM(S): Mus musculus

PROVIDER: GSE64938 | GEO | 2015/01/16

SECONDARY ACCESSION(S): PRJNA272535

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2024-09-05 | GSE254295 | GEO
2024-09-05 | GSE254294 | GEO
2023-06-20 | GSE159315 | GEO
2022-11-21 | GSE196556 | GEO
2022-12-31 | GSE202347 | GEO
2022-12-31 | GSE202345 | GEO
2007-08-30 | GSE5671 | GEO
2023-04-07 | GSE208153 | GEO
2023-04-07 | GSE210638 | GEO
2012-12-01 | E-GEOD-41175 | biostudies-arrayexpress