Gene expression variability in mammalian embryonic stem cells using single cell RNA-seq data

ABSTRACTGene expression heterogeneity in the pluripotent state of mouse embryonic stem cells (mESCs) has been increasingly well-characterized. In contrast, exit from pluripotency and lineage commitment have not been studied systematically at the single-cell level. Here we measured the gene expression dynamics of retinoic acid driven mESC differentiation using an unbiased single-cell transcriptomics approach. We found that the exit from pluripotency marks the start of a lineage bifurcation as well as a transient phase of susceptibility to lineage specifying signals. Our study revealed several transcriptional signatures of this phase, including a sharp increase of gene expression variability. Importantly, we observed a handover between two classes of transcription factors. The early-expressed class has potential roles in lineage biasing, the late-expressed class in lineage commitment. In summary, we provide a comprehensive analysis of lineage commitment at the single cell level, a potential stepping stone to improved lineage control through timing of differentiation cues.

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Pooled CRISPR-activation screening coupled with single-cell RNA-seq in mouse embryonic stem cells

STAR Protocols ◽

10.1016/j.xpro.2021.100426 ◽

2021 ◽

Vol 2 (2) ◽

pp. 100426

Author(s):

Celia Alda-Catalinas ◽

Melanie A. Eckersley-Maslin ◽

Wolf Reik

Keyword(s):

Stem Cells ◽

Embryonic Stem Cells ◽

Single Cell ◽

Embryonic Stem ◽

Mouse Embryonic Stem Cells ◽

Rna Seq ◽

Crispr Activation

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Abstract 14565: Comparative Transcriptomic Analysis of Multiple Cardiovascular Fates From Embryonic Stem Cells Predicts Regulatory Genes, Alternative Splicing and Long Non-coding RNAs in Human Cardiogenesis

Circulation ◽

10.1161/circ.132.suppl_3.14565 ◽

2015 ◽

Vol 132 (suppl_3) ◽

Author(s):

Yang Li ◽

Bo Lin ◽

Lei Yang

Keyword(s):

Gene Expression ◽

Stem Cells ◽

Embryonic Stem Cells ◽

Cell Fate ◽

Embryonic Stem ◽

Cardiovascular Development ◽

Rna Seq ◽

Comparison Analysis ◽

Lineage Specificity ◽

Early Human

Introduction: Dissecting the gene expression programs which control the early stage cardiovascular development is essential for understanding the molecular mechanisms of human heart development and heart disease. Many lineage-specific genes are involved in the differentiation into specific cell fate. Hypothesis: The lineage-specificity of the genes may predict regulatory potential during human cardiovascular differentiation. Methods: Here, we performed transcriptome sequencing (RNA-seq) of highly purified human Embryonic Stem Cells (hESCs), hESC-derived Multipotential Cardiovascular Progenitors (MCPs) and MCP-specified three cardiovascular lineages. A novel algorithm, named as Gene Expression Pattern Analyzer (GEPA), was developed to obtain a refined lineage-specificity map of all sequenced genes, which reveals dynamic changes of transcriptional factor networks underlying early human cardiovascular development. Results: The GEPA predictions captured ∼90% of top-ranked regulatory cardiac genes that were previously predicted based on chromatin signature changes in hESCs, and further defined their cardiovascular lineage-specificities, indicating that our multi-fate comparison analysis could predict novel regulatory genes. Furthermore, GEPA analysis revealed the MCP-specific expressions of genes in ephrin signaling pathway, positive role of which in cardiomyocyte differentiation was further validated experimentally. By using RNA-seq plus GEPA workflow, we also identified stage-specific RNA splicing switch and lineage-enriched long noncoding RNAs during human cardiovascular differentiation. Conclusions: Overall, our study utilized multi-cell-fate transcriptomic comparison analysis to establish a lineage-specific gene expression map for predicting and validating novel regulatory mechanisms underlying early human cardiovascular development.

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