scholarly journals Cell Fate Determining Molecular Switches and Signaling Pathway in Pax7-expressing Somitic Mesoderm

2019 ◽  
Author(s):  
Cheuk Wang Fung ◽  
Han Zhu ◽  
Shao Pu Zhou ◽  
Zhenguo Wu ◽  
Angela R. Wu
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Signaling Pathway ◽  
Cell Fate ◽  
Molecular Switches ◽  
Functional Evaluation ◽  
Surface Markers ◽  
Time Points ◽  
Brown Adipose ◽  
Somitic Mesoderm

AbstractPax7-expressing progenitor cells in the somitic mesoderm differentiate into multiple lineages, such as brown adipose tissue, dorsal dermis, as well as muscle in the dorsal trunk and the diaphragm; however, the key molecular switches that determine and control the process of lineage commitment and cell fate are unknown. To probe the mechanisms behind mesoderm development, Pax7creER/R26-stop-EYFP embryos were tamoxifen-induced at E9.5 to label Pax7+ cells for lineage tracing and collected at later time points for analysis. The YFP-labelled cells which belonged to the Pax7 lineage were enriched by fluorescence-activated cell sorting (FACS) and subject to single-cell RNA profiling. We observed that a subpopulation of cells differentiated into the myogenic lineage, showing Myf5 expression as early as E12.5, whereas the rest of the population was fibroblast-like and appeared to be the early stage of the adipogenic and dermal lineages. Cells at E14.5 had distinct myogenic populations that expressed Myod1 and Myog; we also identified other populations with Ebf2 or Twist2 expression, which could belong to adipogenic or dermal lineages, respectively. Cell surface markers were also found for each specific lineage, providing insights in sorting strategy for lineage-of-interest for further functional evaluation. Adipogenic lineage was successfully sorted with a combination of Pdgfra and Thy1 antibodies. In addition, we found that upregulation of Wnt signaling pathway activity is dynamically regulated in dermal lineage. Finally, transcription factors that could potentially drive, or reprogram cell fate, were identified at different developmental time points.Summary statementInvestigation of Pax7 lineage transcriptomic profile at single-cell level identified multiple cell types, fate commitment time point, surface markers, transcription factors and signaling pathways that determine cell fate.

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.

Single Cell Proteomics Reveal that Temporal Changes in Transcription Factors Determine Cell-Fate

2018 ◽  
Author(s):  
Carmen G. Palii ◽  
Qian Cheng ◽  
Mark A. Gillespie ◽  
Michalina Mazurczyk ◽  
Giorgio Napolitani ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Cell Fate ◽  
Temporal Changes

scholarly journals Palantir characterizes cell fate continuities in human hematopoiesis

2018 ◽  
Author(s):  
Manu Setty ◽  
Vaidotas Kiseliovas ◽  
Jacob Levine ◽  
Adam Gayoso ◽  
Linas Mazutis ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Transcription Factors ◽  
High Resolution ◽  
Single Cell ◽  
Cell Fate ◽  
Terminal State ◽  
Rna Seq ◽  
Hematopoietic Differentiation ◽  
Cell Plasticity ◽  
Probabilistic Process

AbstractRecent studies using single cell RNA-seq (scRNA-seq) data derived from differentiating systems have raised fundamental questions regarding the discrete vs continuous nature of both differentiation and cell fate. Here we present Palantir, an algorithm that models trajectories of differentiating cells, which treats cell-fate as a probabilistic process, and leverages entropy to measure the changing nature of cell plasticity along the differentiation trajectory. Palantir generates a high resolution pseudotime ordering of cells, and assigns each cell state with its probability to differentiate into each terminal state. We apply Palantir to human bone marrow scRNA-seq data and detect key landmarks of hematopoietic differentiation. Palantir’s resolution enables identification of key transcription factors driving lineage fate choices, as these TFs closely track when cells lose plasticity. We demonstrate that Palantir is generalizable to diverse tissue types and well-suited to resolve less studied differentiating systems.

scholarly journals Single-Cell Proteomics Reveal that Quantitative Changes in Co-expressed Lineage-Specific Transcription Factors Determine Cell Fate

2019 ◽  
Vol 24 (5) ◽  
pp. 812-820.e5 ◽  
Author(s):  
Carmen G. Palii ◽  
Qian Cheng ◽  
Mark A. Gillespie ◽  
Paul Shannon ◽  
Michalina Mazurczyk ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Cell Fate ◽  
Quantitative Changes

scholarly journals Single-cell transcriptomics reveals a new dynamical function of transcription factors during embryonic hematopoiesis

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Isabelle Bergiers ◽  
Tallulah Andrews ◽  
Özge Vargel Bölükbaşı ◽  
Andreas Buness ◽  
Ewa Janosz ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Endothelial Cell ◽  
Single Cell ◽  
Cell Fate ◽  
Regulatory Networks ◽  
Hematopoietic Stem ◽  
Stem And Progenitor Cells ◽  
Cell Transcriptome ◽  
Dynamical Function ◽  
Single Cell Transcriptome

Recent advances in single-cell transcriptomics techniques have opened the door to the study of gene regulatory networks (GRNs) at the single-cell level. Here, we studied the GRNs controlling the emergence of hematopoietic stem and progenitor cells from mouse embryonic endothelium using a combination of single-cell transcriptome assays. We found that a heptad of transcription factors (Runx1, Gata2, Tal1, Fli1, Lyl1, Erg and Lmo2) is specifically co-expressed in an intermediate population expressing both endothelial and hematopoietic markers. Within the heptad, we identified two sets of factors of opposing functions: one (Erg/Fli1) promoting the endothelial cell fate, the other (Runx1/Gata2) promoting the hematopoietic fate. Surprisingly, our data suggest that even though Fli1 initially supports the endothelial cell fate, it acquires a pro-hematopoietic role when co-expressed with Runx1. This work demonstrates the power of single-cell RNA-sequencing for characterizing complex transcription factor dynamics.

scholarly journals Algorithmic Reconstruction of GBM Network Complexity

2021 ◽  
Author(s):  
Abicumaran Uthamacumaran ◽  
Morgan Craig
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Single Cell ◽  
Cell Fate ◽  
Data Science ◽  
Expression Patterns ◽  
State Transitions ◽  
Gene Expression Patterns ◽  
Cell Fate Decisions ◽  
Study Gene Expression

Glioblastoma (GBM) is a complex disease that is difficult to treat. Establishing the complex genetic interactions regulating cell fate decisions in GBM can help to shed light on disease aggressivity and improved treatments. Networks and data science offer novel approaches to study gene expression patterns from single-cell datasets, helping to distinguish genes associated with control of differentiation and thus aggressivity. Here, we applied a host of data theoretic techniques, including clustering algorithms, Waddington landscape reconstruction, trajectory inference algorithms, and network approaches, to compare gene expression patterns between pediatric and adult GBM, and those of adult GSCs (glioma-derived stem cells) to identify the key molecular regulators of the complex networks driving GBM/GSC and predict their cell fate dynamics. Using these tools, we identified critical genes and transcription factors coordinating cell state transitions from stem-like to mature GBM phenotypes, including eight transcription factors (OLIG1/2, TAZ, GATA2, FOXG1, SOX6, SATB2, YY1) and four signaling genes (ATL3, MTSS1, EMP1, and TPT1) as clinically targetable novel putative function interactions differentiating pediatric and adult GBMs from adult GSCs. Our study is among the first to provide strong evidence of the applicability of complex systems approaches for reverse-engineering gene networks from patient-derived single-cell datasets and inferring their complex dynamics, bolstering the search for new clinically- relevant targets in GBM.

scholarly journals Single-cell epigenomic tracing of lifelong endothelial cell plasticity across mouse organs

2021 ◽  
Author(s):  
Xianhong Yu ◽  
Yaxi Liu ◽  
Xiaoge Liu ◽  
Haiqing Xiong ◽  
Aibin He
Keyword(s):  
Endothelial Cells ◽  
Transcription Factors ◽  
Endothelial Cell ◽  
Single Cell ◽  
Cell Fate ◽  
Developmental Origins ◽  
Cellular Plasticity ◽  
Cell Plasticity ◽  
Mesenchymal Transition ◽  
Endothelial To Mesenchymal Transition

Endothelial cells (ECs) across ages and tissues are highly heterogeneous in developmental origins, structures, functions, and cellular plasticity. Here, we applied CoBATCH for single-cell epigenomic tracing of dynamic EC lineage histories in five mouse organs from development to ageing. Our analyses showed that epigenomic memory reflects both developmental origins and tissue-restricted specialization of EC sublineages but with varying time lengths across organs. To gain insights into cellular plasticity of ECs, we identified bivalent chromatin occupancy of otherwise mutually exclusive EC- (ERG) and mesenchymal-specific (TWIST1/SNAI1) transcription factors promoting endothelial-to-mesenchymal transition. We further revealed that pseudotime trajectories by histone modifications H3K36me3 and H3K27ac faithfully recapitulate short- and long-range EC fate change over senescence, respectively. Together, our data provide a unique exploration of chromatin-level cell fate regulation of organotypic EC lineages across the lifespan.

scholarly journals Single-cell chromatin and gene-regulatory dynamics of mouse nephron progenitors

2021 ◽  
Author(s):  
Sylvia Hilliard ◽  
Giovane Tortelote ◽  
Hongbing Liu ◽  
Chao-Hui Chen ◽  
Samir S El-Dahr
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Cell Fate ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Bulk Analysis ◽  
Disease States ◽  
Differentiated Cells ◽  
Nephron Progenitors

Background: Cis-regulatory elements (CREs), such as enhancers and promoters, and their cognate transcription factors play a central role in cell fate specification. Bulk analysis of CREs has provided insights into gene regulation in nephron progenitor cells (NPCs). However, the cellular resolution required to unravel the dynamic changes in regulatory elements associated with cell fate choices remains to be defined. Methods: We integrated single-cell chromatin accessibility (scATAC-seq) and gene expression (scRNA-seq) in embryonic E16.5 (self-renewing) and postnatal P2 (primed) mouse Six2GFP NPCs. This analysis revealed NPC diversity and identified candidate CREs. To validate these findings and gain additional insights into more differentiated cell types, we performed a multiome analysis of E16.5 and P2 kidneys. Results: CRE accessibility recovered the diverse states of NPCs and precursors of differentiated cells. Single-cell types such as podocytes, proximal and distal precursors are marked by differentially accessible CREs. Domains of regulatory chromatin as defined by rich CRE-gene associations identified NPC fate-determining transcription factors (TF). Likewise, key TF expression correlates well with its regulon activity. Young NPCs exhibited enrichment in accessible motifs for bHLH, homeobox, and Forkhead TFs, while older NPCs were enriched in AP-1, HNF1, and HNF4 motif activity. A subset of Forkhead factors exhibiting high chromatin activity in podocyte precursors. Conclusion: Defining the regulatory landscape of nephrogenesis at single-cell resolution informs the basic mechanisms of nephrogenesis and provides a foundation for future studies in disease states characterized by abnormal nephrogenesis.

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