Single-cell mapping of lineage and identity in direct reprogramming
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE99915 | GEO | 2018/09/25
REPOSITORIES: GEO
Similar Datasets
Project description:Chickarmane2008 - Stem cell lineage determination
In this work, a dynamical model of lineage
determination based upon a minimal circuit, as discussed in PMID: 17215298
, which contains the Oct4/Sox2/Nanog core as well its interaction
with a few other key genes is discussed.
This model is described in the article:
A computational model for understanding stem cell, trophectoderm and endoderm lineage determination.
Chickarmane V, Peterson C
PloS one. 2008, 3(10):e3478
Abstract:
BACKGROUND: Recent studies have associated the transcription factors, Oct4, Sox2 and Nanog as parts of a self-regulating network which is responsible for maintaining embryonic stem cell properties: self renewal and pluripotency. In addition, mutual antagonism between two of these and other master regulators have been shown to regulate lineage determination. In particular, an excess of Cdx2 over Oct4 determines the trophectoderm lineage whereas an excess of Gata-6 over Nanog determines differentiation into the endoderm lineage. Also, under/over-expression studies of the master regulator Oct4 have revealed that some self-renewal/pluripotency as well as differentiation genes are expressed in a biphasic manner with respect to the concentration of Oct4. METHODOLOGY/
PRINCIPAL FINDINGS: We construct a dynamical model of a minimalistic network, extracted from ChIP-on-chip and microarray data as well as literature studies. The model is based upon differential equations and makes two plausible assumptions; activation of Gata-6 by Oct4 and repression of Nanog by an Oct4-Gata-6 heterodimer. With these assumptions, the results of simulations successfully describe the biphasic behavior as well as lineage commitment. The model also predicts that reprogramming the network from a differentiated state, in particular the endoderm state, into a stem cell state, is best achieved by over-expressing Nanog, rather than by suppression of differentiation genes such as Gata-6.
CONCLUSIONS: The computational model provides a mechanistic understanding of how different lineages arise from the dynamics of the underlying regulatory network. It provides a framework to explore strategies of reprogramming a cell from a differentiated state to a stem cell state through directed perturbations. Such an approach is highly relevant to regenerative medicine since it allows for a rapid search over the host of possibilities for reprogramming to a stem cell state.
This model is hosted on BioModels Database
and identified
by: MODEL8390025091
.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource
for published quantitative kinetic models
.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to the public
domain worldwide. Please refer to CC0 Public Domain
Dedication
for more information.
2024-09-02 | BIOMD0000000209 | BioModels
Project description:Chickarmane2008 - Stem cell lineage - NANOG GATA-6 switch
In this work, a dynamical model of lineage
determination based upon a minimal circuit, as discussed in PMID: 17215298
, which contains the Oct4/Sox2/Nanog core as well its interaction
with a few other key genes is discussed.
This model is described in the article:
A computational model for understanding stem cell, trophectoderm and endoderm lineage determination.
Chickarmane V, Peterson C
PloS one. 2008, 3(10):e3478
Abstract:
BACKGROUND: Recent studies have associated the transcription factors, Oct4, Sox2 and Nanog as parts of a self-regulating network which is responsible for maintaining embryonic stem cell properties: self renewal and pluripotency. In addition, mutual antagonism between two of these and other master regulators have been shown to regulate lineage determination. In particular, an excess of Cdx2 over Oct4 determines the trophectoderm lineage whereas an excess of Gata-6 over Nanog determines differentiation into the endoderm lineage. Also, under/over-expression studies of the master regulator Oct4 have revealed that some self-renewal/pluripotency as well as differentiation genes are expressed in a biphasic manner with respect to the concentration of Oct4. METHODOLOGY/
PRINCIPAL FINDINGS: We construct a dynamical model of a minimalistic network, extracted from ChIP-on-chip and microarray data as well as literature studies. The model is based upon differential equations and makes two plausible assumptions; activation of Gata-6 by Oct4 and repression of Nanog by an Oct4-Gata-6 heterodimer. With these assumptions, the results of simulations successfully describe the biphasic behavior as well as lineage commitment. The model also predicts that reprogramming the network from a differentiated state, in particular the endoderm state, into a stem cell state, is best achieved by over-expressing Nanog, rather than by suppression of differentiation genes such as Gata-6.
CONCLUSIONS: The computational model provides a mechanistic understanding of how different lineages arise from the dynamics of the underlying regulatory network. It provides a framework to explore strategies of reprogramming a cell from a differentiated state to a stem cell state through directed perturbations. Such an approach is highly relevant to regenerative medicine since it allows for a rapid search over the host of possibilities for reprogramming to a stem cell state.
This model is hosted on BioModels Database
and identified
by: MODEL8389825246
.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource
for published quantitative kinetic models
.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to the public
domain worldwide. Please refer to CC0 Public Domain
Dedication
for more information.
2024-09-02 | BIOMD0000000210 | BioModels
Project description:In direct lineage reprogramming, transcription factor (TF) overexpression reconfigures Gene Regulatory Networks (GRNs) to convert cell identities between fully differentiated cell types. We previously developed CellOracle, a computational pipeline that integrates single-cell transcriptome and epigenome profiles to infer GRNs. CellOracle leverages these inferred GRNs to simulate gene expression changes in response to TF perturbation, enabling network re-configuration during reprogramming to be interrogated in silico. Here, we integrate CellOracle analysis with lineage tracing of fibroblast to induced endoderm progenitor (iEP) conversion, a prototypical direct lineage reprogramming paradigm. By linking early network state to reprogramming success or failure, we reveal distinct network configurations underlying different reprogramming outcomes. Using these network analyses and in silico simulation of TF perturbation, we identify new factors to coax cells into successfully converting cell identity, uncovering a central role for the AP-1 subunit Fos with the Hippo signaling effector, Yap1. Together, these results demonstrate the efficacy of CellOracle to infer and interpret cell-type-specific GRN configurations at high resolution, providing new mechanistic insights into the regulation and reprogramming of cell identity.
2022-12-20 | GSE217675 | GEO
Project description:Fusion of reprogramming factors alters trajectory of somatic lineage conversion
| PRJNA517430 | ENA
Project description:Differentiation into diverse cell lineages requires orchestration of gene regulatory networks guiding cell fate choices. Genetic factors acting through changes in transcriptional levels can contribute to cardiovascular disease risk by impacting early stages of development and have cell type-specific effects. We set out to characterize lineage trajectory progression of subpopulations and identify potential disease-related genes by examining their expression changes in single cells during early stages of cardiac lineage specification. Using 43,168 single-cell transcriptomes, we developed novel classification and trajectory analysis methods to dissect cellular composition and gene networks across five discrete time points underlying lineage derivation of mesoderm, definitive endoderm, vascular endothelium, cardiac precursors, and definitive cell types that comprise cardiomyocytes and a previously unrecognized cardiac outflow tract population.
2018-10-06 | E-MTAB-6268 | biostudies-arrayexpress
Project description:Direct lineage reprogramming represents a remarkable conversion of cellular and transcriptome states. However, the intermediates through which individual cells progress are largely undefined. Here we used single cell RNA-seq at multiple time points to dissect direct reprogramming from mouse embryonic fibroblasts (MEFs) to induced neuronal (iN) cells. By deconstructing heterogeneity at each time point and ordering cells by transcriptome similarity rather than time we reconstructed a continuous reprogramming path. We find that overexpression of a single factor (Ascl1) results in a well-defined initialization causing cells to exit the cell cycle and re-focus gene expression through distinct neural transcription factors. However, overexpression of Ascl1 alone leads to abundant alternative fates that are suppressed by the combination of additional factors (Myt1l, Pou3f2). We find transgene silencing and emergence of alternative fates are the major efficiency limits of direct reprogramming. These data provide a high-resolution approach for understanding transcriptome states during lineage differentiation.
2016-06-08 | GSE67310 | GEO
Project description:Direct lineage reprogramming provides a unique system to study cell fate transitions and unearth molecular mechanisms that safeguard cellular identity. We previously reported on direct conversion of mouse fibroblasts into induced myogenic progenitor cells (iMPCs) by transient MyoD overexpression in concert with small molecules treatment. Here we employed integrative multi-omic approaches to delineate the molecular landscape of fibroblast reprogramming into iMPCs in comparison to transdifferentiation into myogenic cells solely by MyoD overexpression. Utilizing bulk RNA-sequencing and mass spectrometry, we uncovered molecular regulators and pathways that endow a myogenic stem cell identity on fibroblasts only in the presence of small molecule treatment. In addition, we demonstrate that Pax7+ cells in iMPCs share molecular attributes with myoblasts, however in addition express unique genes, proteins and pathways that are indicative of a more activated satellite cell-like state in vitro. Collectively, this study charts a molecular blueprint for reprogramming fibroblasts into muscle stem and progenitor cells and further establishes the fidelity of stable iMPC cultures in capturing skeletal muscle regeneration in vitro for disease modeling and basic research applications.
2022-05-19 | PXD029379 | Pride
Project description:Direct lineage conversion offers a new strategy for tissue regeneration and disease modeling. Despite recent success in directly reprogramming fibroblasts into a wide spectrum of cell types, the precise changes that fibroblasts undergo as they progress to target cell fates remain unclear. The inherent heterogeneity and asynchronous nature of the reprogramming process make it difficult to study using bulk genomic techniques. Therefore, a fundamental and detailed understanding of global transcriptome changes at the single cell level is necessary to better optimize reprogramming for therapeutic purposes and to advance the understanding of cell plasticity and cell identity acquisition. Here, we applied single-cell RNA-seq to analyze global transcriptome changes at early stages of induced cardiomyocyte (iCM) reprogramming. Using unsupervised dimensionality reduction and clustering algorithms, we identified molecularly distinct subpopulations of cells along the reprogramming process from fibroblasts to iCMs, including a novel intermediate state that exhibited molecular signatures of both fibroblast and cardiomyocyte. In summary, our single cell transcriptomics approaches enabled us to construct a reprogramming trajectory and uncover the intermediate cell populations, regulatory pathways and genes putatively involved in iCM induction.
2017-10-25 | GSE98567 | GEO
Project description:Direct lineage conversion offers a new strategy for tissue regeneration and disease modeling. Despite recent success in directly reprogramming fibroblasts into a wide spectrum of cell types, the precise changes that fibroblasts undergo as they progress to target cell fates remain unclear. The inherent heterogeneity and asynchronous nature of the reprogramming process make it difficult to study using bulk genomic techniques. Therefore, a fundamental and detailed understanding of global transcriptome changes at the single cell level is necessary to better optimize reprogramming for therapeutic purposes and to advance the understanding of cell plasticity and cell identity acquisition. Here, we applied single-cell RNA-seq to analyze global transcriptome changes at early stages of induced cardiomyocyte (iCM) reprogramming. Using unsupervised dimensionality reduction and clustering algorithms, we identified molecularly distinct subpopulations of cells along the reprogramming process from fibroblasts to iCMs, including a novel intermediate state that exhibited molecular signatures of both fibroblast and cardiomyocyte. In summary, our single cell transcriptomics approaches enabled us to construct a reprogramming trajectory and uncover the intermediate cell populations, regulatory pathways and genes putatively involved in iCM induction.
2017-10-25 | GSE98569 | GEO
Project description:Direct lineage conversion offers a new strategy for tissue regeneration and disease modeling. Despite recent success in directly reprogramming fibroblasts into a wide spectrum of cell types, the precise changes that fibroblasts undergo as they progress to target cell fates remain unclear. The inherent heterogeneity and asynchronous nature of the reprogramming process make it difficult to study using bulk genomic techniques. Therefore, a fundamental and detailed understanding of global transcriptome changes at the single cell level is necessary to better optimize reprogramming for therapeutic purposes and to advance the understanding of cell plasticity and cell identity acquisition. Here, we applied single-cell RNA-seq to analyze global transcriptome changes at early stages of induced cardiomyocyte (iCM) reprogramming. Using unsupervised dimensionality reduction and clustering algorithms, we identified molecularly distinct subpopulations of cells along the reprogramming process from fibroblasts to iCMs, including a novel intermediate state that exhibited molecular signatures of both fibroblast and cardiomyocyte. In summary, our single cell transcriptomics approaches enabled us to construct a reprogramming trajectory and uncover the intermediate cell populations, regulatory pathways and genes putatively involved in iCM induction.
2017-10-25 | GSE98570 | GEO