Single Cell RNA seq for Analysis of Cell Fate Decisions

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. SCI-20-SCI-20
Author(s):  
H. Leighton Grimes ◽  
Singh Harinder ◽  
Andre Olsson ◽  
Nathan Salomonis ◽  
Bruce J. Aronow ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Clustering Analysis ◽  
Conflicts Of Interest ◽  
Regulatory Gene ◽  
Rna Seq ◽  
Regulatory State ◽  
Cell Fate Decisions ◽  
General Utility ◽  
Developmental Hierarchy

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.

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

2019 ◽  
Vol 73 (4) ◽  
pp. 815-829.e7 ◽  
Author(s):  
Lin Guo ◽  
Lihui Lin ◽  
Xiaoshan Wang ◽  
Mingwei Gao ◽  
Shangtao Cao ◽  
...  
Keyword(s):  
Somatic Cell ◽  
Single Cell ◽  
Cell Fate ◽  
Cell Reprogramming ◽  
Rna Seq ◽  
Cell Fate Decisions ◽  
Somatic Cell Reprogramming

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

2016 ◽  
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]

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

eLife ◽  
2020 ◽  
Vol 9 ◽  
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.

scholarly journals Single Cell Transcriptome-Based Dissection of Lineage Fate Decisions in Myelopoiesis

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 1395-1395
Author(s):  
Andre Olsson ◽  
H. Leighton Grimes ◽  
Virendra K Chaudhri ◽  
Philip Dexheimer ◽  
Bruce J Aronow ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Molecular Mechanisms ◽  
Conflicts Of Interest ◽  
Expression Patterns ◽  
Rna Seq ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome ◽  
Cell Data ◽  
Insight Into

Abstract In spite of tremendous advances in the analysis of hematopoietic progenitors and transcription factors that give rise to different lineages, molecular insight into the mechanisms that underlie cell fate choice at the level of individual cells is lacking. We utilized single-cell RNA sequencing of murine granulocyte-monocyte progenitors (GMPs) to analyze the molecular basis of cell fate choice. Over 200 libraries were generated with average read depths of 4 million per library and an expressed gene call of over 3,800 genes with FPKM >3. Our data reveal a varied but coherent spectrum of gene expression patterns in individual murine GMPs. The majority of cells could be clustered into ones expressing either granulocytic or monocytic genes, suggesting that they were primed for lineage determination. A minority of GMPs expressed a mixed-lineage pattern of genes. The single-cell data suggested an antagonistic transcription factor circuit involving Gfi1 and IRF8 that was validated with both loss- and gain-of-function experiments in GMPs. Our data highlight the utility of single cell RNA-Seq analysis to reveal molecular mechanisms controlling lineage fate decisions in hematopoiesis. Disclosures No relevant conflicts of interest to declare.

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

2018 ◽  
Author(s):  
Lin Guo ◽  
Xiaoshan Wang ◽  
Lihui Lin ◽  
Mingwei Gao ◽  
Junqi Kuang ◽  
...  
Keyword(s):  
Somatic Cell ◽  
Single Cell ◽  
Cell Fate ◽  
Cell Reprogramming ◽  
Rna Seq ◽  
Cell Fate Decisions ◽  
Somatic Cell Reprogramming

scholarly journals Resolution of Cell Fate Decisions Revealed by Single-Cell Gene Expression Analysis from Zygote to Blastocyst

2010 ◽  
Vol 18 (4) ◽  
pp. 675-685 ◽  
Author(s):  
Guoji Guo ◽  
Mikael Huss ◽  
Guo Qing Tong ◽  
Chaoyang Wang ◽  
Li Li Sun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Cell Fate ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Cell Fate Decisions ◽  
Cell Gene Expression ◽  
Cell Gene

scholarly journals Single-cell transcriptional analysis to uncover regulatory circuits driving cell fate decisions in early mouse development

2014 ◽  
Vol 31 (7) ◽  
pp. 1060-1066 ◽  
Author(s):  
Haifen Chen ◽  
Jing Guo ◽  
Shital K. Mishra ◽  
Paul Robson ◽  
Mahesan Niranjan ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Transcriptional Analysis ◽  
Mouse Development ◽  
Cell Fate Decisions ◽  
Regulatory Circuits ◽  
Early Mouse

scholarly journals Leveraging high-powered RNA-Seq datasets to improve inference of regulatory activity in single-cell RNA-Seq data

2019 ◽  
Author(s):  
Ning Wang ◽  
Andrew E. Teschendorff
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Cell Fate ◽  
Regulatory Networks ◽  
Large Scale ◽  
Single Cells ◽  
Differential Expression Analysis ◽  
Dropout Rate ◽  
Rna Seq ◽  
Regulatory Activity

AbstractInferring the activity of transcription factors in single cells is a key task to improve our understanding of development and complex genetic diseases. This task is, however, challenging due to the relatively large dropout rate and noisy nature of single-cell RNA-Seq data. Here we present a novel statistical inference framework called SCIRA (Single Cell Inference of Regulatory Activity), which leverages the power of large-scale bulk RNA-Seq datasets to infer high-quality tissue-specific regulatory networks, from which regulatory activity estimates in single cells can be subsequently obtained. We show that SCIRA can correctly infer regulatory activity of transcription factors affected by high technical dropouts. In particular, SCIRA can improve sensitivity by as much as 70% compared to differential expression analysis and current state-of-the-art methods. Importantly, SCIRA can reveal novel regulators of cell-fate in tissue-development, even for cell-types that only make up 5% of the tissue, and can identify key novel tumor suppressor genes in cancer at single cell resolution. In summary, SCIRA will be an invaluable tool for single-cell studies aiming to accurately map activity patterns of key transcription factors during development, and how these are altered in disease.

scholarly journals Basal stem cell fate specification is mediated by SMAD signaling in the developing human lung

2018 ◽  
Author(s):  
Alyssa J. Miller ◽  
Qianhui Yu ◽  
Michael Czerwinski ◽  
Yu-Hwai Tsai ◽  
Renee F. Conway ◽  
...  
Keyword(s):  
Single Cell ◽  
Progenitor Cells ◽  
Cell Fate ◽  
Basal Cell ◽  
Human Lung ◽  
Branching Morphogenesis ◽  
Basal Cells ◽  
Smad Signaling ◽  
Cell Fate Decisions ◽  
Cell Transition

AbstractBasal stem cells (basal cells), located in the bronchi and trachea of the human lung epithelium, play a critical role in normal airway homeostasis and repair, and have been implicated in the development of diseases such as cancer1-4. Additionally, basal-like cells contribute to alveolar regeneration and fibrosis following severe injury5-8. However, the developmental origin of basal cells in humans is unclear. Previous work has shown that specialized progenitor cells exist at the tips of epithelial tubes during lung branching morphogenesis, and in mice, give rise to all alveolar and airway lineages9,10. These ‘bud tip progenitor cells’ have also been described in the developing human lung11-13, but the mechanisms controlling bud tip differentiation into specific cell lineages, including basal cells, are unknown. Here, we interrogated the bud tip-to-basal cell transition using human tissue specimens, bud tip progenitor organoid cultures11, and single-cell transcriptomics. We used single-cell mRNA sequencing (scRNAseq) of developing human lung specimens from 15-21 weeks gestation to identify molecular signatures and cell states in the developing human airway epithelium. We then inferred differentiation trajectories during bud tip-to-airway differentiation, which revealed a previously undescribed transitional cell state (‘hub progenitors’) and implicated SMAD signaling as a regulator of the bud tip-to-basal cell transition. We used bud tip progenitor organoids to show that TGFT1 and BMP4 mediated SMAD signaling robustly induced the transition into functional basal-like cells, and these in vitro-derived basal cells exhibited clonal expansion, self-renewal and multilineage differentiation. This work provides a framework for deducing and validating key regulators of cell fate decisions using single cell transcriptomics and human organoid models. Further, the identification of SMAD signaling as a critical regulator of newly born basal cells in the lung may have implications for regenerative medicine, basal cell development in other organs, and understanding basal cell misregulation in disease.

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