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Dev Cell. 2016 Nov 21;39(4):491-507. doi: 10.1016/j.devcel.2016.10.014. Epub 2016 Nov 10.

Transcriptomic Profiling Maps Anatomically Patterned Subpopulations among Single Embryonic Cardiac Cells.

Author information

1
Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA 94305, USA.
2
Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
3
Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA 94305, USA; Division of Pediatric Cardiology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA.
4
State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
5
Palo Alto Veteran Administration, Palo Alto, CA 94304, USA.
6
Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA 94305, USA; Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
7
Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA 94305, USA; Palo Alto Veteran Administration, Palo Alto, CA 94304, USA; Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
8
Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
9
Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA 94305, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA; Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA. Electronic address: smwu@stanford.edu.

Abstract

Embryonic gene expression intricately reflects anatomical context, developmental stage, and cell type. To address whether the precise spatial origins of cardiac cells can be deduced solely from their transcriptional profiles, we established a genome-wide expression database from 118, 949, and 1,166 single murine heart cells at embryonic day 8.5 (e8.5), e9.5, and e10.5, respectively. We segregated these cells by type using unsupervised bioinformatics analysis and identified chamber-specific genes. Using a random forest algorithm, we reconstructed the spatial origin of single e9.5 and e10.5 cardiomyocytes with 92.0% ± 3.2% and 91.2% ± 2.8% accuracy, respectively (99.4% ± 1.0% and 99.1% ± 1.1% if a ±1 zone margin is permitted) and predicted the second heart field distribution of Isl-1-lineage descendants. When applied to Nkx2-5-/- cardiomyocytes from murine e9.5 hearts, we showed their transcriptional alteration and lack of ventricular phenotype. Our database and zone classification algorithm will enable the discovery of novel mechanisms in early cardiac development and disease.

KEYWORDS:

Nkx2-5; cardiac development; cardiomyocyte; congenital heart disease; single-cell RNA sequencing

PMID:
27840109
PMCID:
PMC5130110
DOI:
10.1016/j.devcel.2016.10.014
[Indexed for MEDLINE]
Free PMC Article

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