Resolving Cell Fate Decisions during Somatic Cell Reprogramming by Single-Cell RNA-Seq

Abstract Single-cell RNA-Seq has the potential to become a dominant approach in probing diverse and complex developmental compartments. Its unbiased and comprehensive nature could enable developmental ordering of cellular and regulatory gene hierarchies without prior knowledge. To test general utility we performed single-cell RNA-seq of murine hematopoietic progenitors focusing on the myeloid developmental hierarchy. Using novel unsupervised clustering analysis, ICDS, we correctly ordered known hierarchical states as well as revealed rare intermediates. Regulatory state analysis suggested that the transcription factors Gfi1 and Irf8 function antagonistically to control homeostatic neutrophil and macrophage production, respectively. This prediction was validated by complementary genetic and genomic experiments in granulocyte-macrophage progenitors. Using knock-in reporters for Gfi1 and Irf8 and clonogenic analyses coupled with single-cell RNA-seq we distinguished regulatory states of bi-potential progenitors from their lineage specifying or committed progeny. Thus single-cell RNA-Seq is a powerful developmental tool to characterize hierarchical and rare cellular states along with the regulators that control their dynamics. Disclosures No relevant conflicts of interest to declare.

Download Full-text

Small molecules that modulate embryonic stem cell fate and somatic cell reprogramming

Trends in Pharmacological Sciences ◽

10.1016/j.tips.2009.10.002 ◽

2010 ◽

Vol 31 (1) ◽

pp. 36-45 ◽

Cited By ~ 138

Author(s):

Wenlin Li ◽

Sheng Ding

Keyword(s):

Stem Cell ◽

Embryonic Stem Cell ◽

Small Molecules ◽

Somatic Cell ◽

Cell Fate ◽

Embryonic Stem ◽

Cell Reprogramming ◽

Stem Cell Fate ◽

Somatic Cell Reprogramming

Download Full-text

SCPattern: A statistical approach to identify and classify expression changes in single cell RNA-seq experiments with ordered conditions

10.1101/046110 ◽

2016 ◽

Cited By ~ 1

Author(s):

Ning Leng ◽

Li-Fang Chu ◽

Jeea Choi ◽

Christina Kendziorski ◽

James A. Thomson ◽

...

Keyword(s):

Single Cell ◽

Cell Fate ◽

Empirical Bayes ◽

Time Course ◽

Expression Patterns ◽

R Package ◽

Embryonic Cell ◽

Rna Seq ◽

Cell Fate Decisions ◽

Probability Estimates

AbstractMotivationWith the development of single cell RNA-seq (scRNA-seq) technology, scRNA-seq experiments with ordered conditions (e.g. time-course) are becoming common. Methods developed for analyzing ordered bulk RNA-seq experiments are not applicable to scRNA-seq, since their distributional assumptions are often violated by additional heterogeneities prevalent in scRNA-seq. Here we present SC-Pattern - an empirical Bayes model to characterize genes with expression changes in ordered scRNA-seq experiments. SCPattern utilizes the non-parametrical Kolmogorov-Smirnov statistic, thus it has the flexibility to identify genes with a wide variety of types of changes. Additionally, the Bayes framework allows SCPattern to classify genes into expression patterns with probability estimates.ResultsSimulation results show that SCPattern is well powered for identifying genes with expression changes while the false discovery rate is well controlled. SCPattern is also able to accurately classify these dynamic genes into directional expression patterns. Applied to a scRNA-seq time course dataset studying human embryonic cell differentiation, SCPattern detected a group of important genes that are involved in mesendoderm and definitive endoderm cell fate decisions, positional patterning, and cell cycle.Availability and ImplementationThe SCPattern is implemented as an R package along with a user-friendly graphical interface, which are available at:https://github.com/lengning/SCPatternContact:[email protected]

Download Full-text

Chromatin accessibility dynamics and single cell RNA-Seq reveal new regulators of regeneration in neural progenitors

eLife ◽

10.7554/elife.52648 ◽

2020 ◽

Vol 9 ◽

Cited By ~ 2

Author(s):

Anneke Dixie Kakebeen ◽

Alexander Daniel Chitsazan ◽

Madison Corinne Williams ◽

Lauren M Saunders ◽

Andrea Elizabeth Wills

Keyword(s):

Single Cell ◽

Cell Fate ◽

Neural Progenitor Cells ◽

Cell Types ◽

Chromatin Accessibility ◽

Rna Seq ◽

Tail Regeneration ◽

Cell Fate Decisions ◽

Transcriptional Regulatory ◽

Regulatory Dynamics

Vertebrate appendage regeneration requires precisely coordinated remodeling of the transcriptional landscape to enable the growth and differentiation of new tissue, a process executed over multiple days and across dozens of cell types. The heterogeneity of tissues and temporally-sensitive fate decisions involved has made it difficult to articulate the gene regulatory programs enabling regeneration of individual cell types. To better understand how a regenerative program is fulfilled by neural progenitor cells (NPCs) of the spinal cord, we analyzed pax6-expressing NPCs isolated from regenerating Xenopus tropicalis tails. By intersecting chromatin accessibility data with single-cell transcriptomics, we find that NPCs place an early priority on neuronal differentiation. Late in regeneration, the priority returns to proliferation. Our analyses identify Pbx3 and Meis1 as critical regulators of tail regeneration and axon organization. Overall, we use transcriptional regulatory dynamics to present a new model for cell fate decisions and their regulators in NPCs during regeneration.

Download Full-text