Time course profile of umbilical cord blood cells in culture
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE16589 | GEO | 2009/07/01
SECONDARY ACCESSION(S): PRJNA116153
REPOSITORIES: GEO
Similar Datasets
Project description:Despite the importance of inter-cellular communication networks in regulating stem cell fate decisions, very little is known about the topology, dynamics, or functional significance. Using human blood stem cell cultures as an experimental paradigm, we present a novel bioinformatic approach to integrate genome-scale molecular profiles (transcriptome and secretome) and publicly available databases to reconstruct soluble factor-mediated inter-cellular signalling networks regulating blood stem cell fate decisions. Umbilical cord blood UCB cells were lineage depleted via immuno-magnetic column and placed in serum free media, supplemented with SCF, FL, and TPO. At culture day 4, cells were either subject to Lin- cell re-selection + media exchange (S/E) or not (NS/NE) and cultured for an additional 4 days. At day-8, S/E cell sample was subject to another S/E procedure and cultured for an additional 4 days. At day-0, 4, 8, and 12, cells were separated into Lin- and Lin+ for independent profiling using Affymetrix HU133 v2.0 arrays.
2009-07-01 | E-GEOD-16589 | biostudies-arrayexpress
Project description:Hamey2017 - Blood stem cell regulatory
network
This model is described in the article:
Reconstructing blood stem
cell regulatory network models from single-cell molecular
profiles
Fiona K. Hamey, Sonia Nestorowa,
Sarah J. Kinston, David G. Kent, Nicola K. Wilson, and Berthold
Göttgens
Proceedings of the National Academy of
Sciences of the United States of America
Abstract:
Adult blood contains a mixture of mature cell types, each
with specialized functions. Single hematopoietic stem cells
(HSCs) have been functionally shown to generate all mature cell
types for the lifetime of the organism. Differentiation of HSCs
toward alternative lineages must be balanced at the population
level by the fate decisions made by individual cells.
Transcription factors play a key role in regulating these
decisions and operate within organized regulatory programs that
can be modeled as transcriptional regulatory networks. As
dysregulation of single HSC fate decisions is linked to fatal
malignancies such as leukemia, it is important to understand
how these decisions are controlled on a cell-by-cell basis.
Here we developed and applied a network inference method,
exploiting the ability to infer dynamic information from
single-cell snapshot expression data based on expression
profiles of 48 genes in 2,167 blood stem and progenitor cells.
This approach allowed us to infer transcriptional regulatory
network models that recapitulated differentiation of HSCs into
progenitor cell types, focusing on trajectories toward
megakaryocyte–erythrocyte progenitors and lymphoid-primed
multipotent progenitors. By comparing these two models, we
identified and subsequently experimentally validated a
difference in the regulation of nuclear factor, erythroid 2
(Nfe2) and core-binding factor, runt domain, alpha subunit 2,
translocated to, 3 homolog (Cbfa2t3h) by the transcription
factor Gata2. Our approach confirms known aspects of
hematopoiesis, provides hypotheses about regulation of HSC
differentiation, and is widely applicable to other hierarchical
biological systems to uncover regulatory relationships.
This model is hosted on
BioModels Database
and identified by:
MODEL1610060000.
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.
2017-06-09 | MODEL1610060000 | BioModels
Project description:Hamey2017 - Blood stem cell regulatory
network (LMPP network)
This model is described in the article:
Reconstructing blood stem
cell regulatory network models from single-cell molecular
profiles
Fiona K. Hamey, Sonia Nestorowa,
Sarah J. Kinston, David G. Kent, Nicola K. Wilson, and Berthold
Göttgens
Proceedings of the National Academy of
Sciences of the United States of America
Abstract:
Adult blood contains a mixture of mature cell types, each
with specialized functions. Single hematopoietic stem cells
(HSCs) have been functionally shown to generate all mature cell
types for the lifetime of the organism. Differentiation of HSCs
toward alternative lineages must be balanced at the population
level by the fate decisions made by individual cells.
Transcription factors play a key role in regulating these
decisions and operate within organized regulatory programs that
can be modeled as transcriptional regulatory networks. As
dysregulation of single HSC fate decisions is linked to fatal
malignancies such as leukemia, it is important to understand
how these decisions are controlled on a cell-by-cell basis.
Here we developed and applied a network inference method,
exploiting the ability to infer dynamic information from
single-cell snapshot expression data based on expression
profiles of 48 genes in 2,167 blood stem and progenitor cells.
This approach allowed us to infer transcriptional regulatory
network models that recapitulated differentiation of HSCs into
progenitor cell types, focusing on trajectories toward
megakaryocyte–erythrocyte progenitors and lymphoid-primed
multipotent progenitors. By comparing these two models, we
identified and subsequently experimentally validated a
difference in the regulation of nuclear factor, erythroid 2
(Nfe2) and core-binding factor, runt domain, alpha subunit 2,
translocated to, 3 homolog (Cbfa2t3h) by the transcription
factor Gata2. Our approach confirms known aspects of
hematopoiesis, provides hypotheses about regulation of HSC
differentiation, and is widely applicable to other hierarchical
biological systems to uncover regulatory relationships.
This model is hosted on
BioModels Database
and identified by:
MODEL1610060001.
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.
2017-06-09 | MODEL1610060001 | BioModels
Project description:The global gene expression profiles of human umbilical cord blood and adult bone marrow CD34+CD33-CD38-Rho(lo)c-kit+ cells, enriched for hematopoietic stem/progenitor cells (HSC) with CD34+CD33-CD38-Rho(hi) cells, enriched in committed hematopoietic progenitor cells (HPC), were compared to identify candidate regulators of HSC self-renewal versus differentiation fate decisions.
2007-10-30 | E-GEOD-2666 | biostudies-arrayexpress
Project description:The transcription factor Sox17 is expressed in early primitive endoderm-fated cells of the mouse embryo and in embryo-derived extraembryonic endoderm (ExEn) stem (XEN) cells. We have shown that overexpression of Sox17 in mouse embryonic stem cells (ESCs) drives cell fate to a committed XEN-like cell state (Sox17-XEN cells). When placed back into the embryo, Sox17-XEN cells contribute exclusively to the ExEn. Transient Sox17 expression is sufficient to drive this fate change during which time cells transit through distinct intermediate states prior to the generation of functional XEN-like cells. We identified dynamic regulatory networks driving Sox17-mediated XEN conversion by analyzing a dynamic regulatory map of gene expression bifurcation points throughout conversion, created using RNA-seq time series data. We found that Sox17 orchestrates this conversion process by acting in autoregulatory and feed-forward network motifs, regulating dynamic gene regulatory networks (GRNs) directing cell fate. We have shown that Sox17-mediated XEN conversion provides a powerful tool for understanding the regulation of cell fate changes and for the elucidation of GRNs regulating lineage decisions in the mouse embryo. Total RNA was extracted during a time course of Sox17 overexpression in mouse ESCs at 7 time points as well as from wild-type ESCs and wild-type XEN cells.
2014-09-05 | E-GEOD-61102 | biostudies-arrayexpress
Project description:Hematopoietic stem cells give rise to diverse cell types in the blood system, yet our molecular understanding of the earliest fate decisions that generate this enormous diversity in humans remains incomplete. Here we leverage Drop-seq to individually profile more than 20,000 progenitors cells from human cord blood, without prior enrichment or depletion for individual lineages based on surface markers. Our data reveal a transcriptional 'atlas' of progenitor states in human cord blood, which we leverage to reconstruct differentiation trajectories from HSC to four downstream lineages. And we also demonstrate that Drop-seq data can be utilized to identify new heterogeneous markers of cell state.
2018-03-15 | GSE97104 | GEO
Project description:Our data demonstrated an unprecedented role of RUNX1 in regulating hematopoietic and mesenchymal fate decisions in human pluripotent stem cells (hPSC)-derived hematopoiesis
2024-05-17 | GSE232147 | GEO
Project description:The transcription factor Sox17 is expressed in early primitive endoderm-fated cells of the mouse embryo and in embryo-derived extraembryonic endoderm (ExEn) stem (XEN) cells. We have shown that overexpression of Sox17 in mouse embryonic stem cells (ESCs) drives cell fate to a committed XEN-like cell state (Sox17-XEN cells). When placed back into the embryo, Sox17-XEN cells contribute exclusively to the ExEn. Transient Sox17 expression is sufficient to drive this fate change during which time cells transit through distinct intermediate states prior to the generation of functional XEN-like cells. We identified dynamic regulatory networks driving Sox17-mediated XEN conversion by analyzing a dynamic regulatory map of gene expression bifurcation points throughout conversion, created using RNA-seq time series data. We found that Sox17 orchestrates this conversion process by acting in autoregulatory and feed-forward network motifs, regulating dynamic gene regulatory networks (GRNs) directing cell fate. We have shown that Sox17-mediated XEN conversion provides a powerful tool for understanding the regulation of cell fate changes and for the elucidation of GRNs regulating lineage decisions in the mouse embryo.
2014-09-05 | GSE61102 | GEO
Project description:Developmental and metabolic signaling networks underpinning type-17 cell fate decisions in dictating tissue homeostasis versus fatal autoimmunity
2022-10-04 | GSE179511 | GEO
Project description:Developmental and metabolic signaling networks underpinning type-17 cell fate decisions in dictating tissue homeostasis versus tissue homeostasis
2022-10-04 | GSE206458 | GEO