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Dynamic analysis of gene expression and genome wide transcription factor binding during lineage-specification of multipotent progenitors [PC]

ABSTRACT: Primary hematopoietic cells from mouse bone marrow were sorted and hybridised expression microarrays as part of a study investigating the differentiation of a multipotential cell-line to erthroid and myeloid fates. We used the paradigmatic 'GATA-PU.1 axis’ to explore, at systems-level, dynamic relationships between transcription factor (TF) binding and global gene expression programs as multipotent cells differentiate. We combined global ChIPSeq of GATA1, GATA2 and PU.1 with expression profiling during differentiation to erythroid and neutrophil lineages. Our analysis reveals (i) differential complexity of sequence motifs bound by GATA1, GATA2 and PU.1; (ii) the scope and interplay of the GATA1 and GATA2 programs within, and during transitions between, different cell compartments, and the extent of their hard-wiring by DNA motifs; (iii) the potential to predict gene expression trajectories based on global associations between TF-binding data and target gene expression and (iv) how dynamic modeling of DNA-binding and gene expression data can be used to infer regulatory logic of TF circuitry. This 'rubric' exemplifies the utility of this cross-platform resource for deconvoluting the complexity of transcriptional programs controlling stem/progenitor cell fate in hematopoiesis.

ORGANISM(S): Mus musculus

PROVIDER: GSE49988 | GEO | 2013/10/17

SECONDARY ACCESSION(S): PRJNA215761

REPOSITORIES: GEO

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Dynamic analysis of gene expression and genome wide transcription factor binding during lineage-specification of multipotent progenitors [ChIP-seq].

Project description:We used the paradigmatic 'GATA-PU.1 axis’ to explore, at systems-level, dynamic relationships between transcription factor (TF) binding and global gene expression programs as multipotent cells differentiate. We combined global ChIPSeq of GATA1, GATA2 and PU.1 with expression profiling during differentiation to erythroid and neutrophil lineages. Our analysis reveals (i) differential complexity of sequence motifs bound by GATA1, GATA2 and PU.1; (ii) the scope and interplay of the GATA1 and GATA2 programs within, and during transitions between, different cell compartments, and the extent of their hard-wiring by DNA motifs; (iii) the potential to predict gene expression trajectories based on global associations between TF-binding data and target gene expression and (iv) how dynamic modeling of DNA-binding and gene expression data can be used to infer regulatory logic of TF circuitry. This 'rubric' exemplifies the utility of this cross-platform resource for deconvoluting the complexity of transcriptional programs controlling stem/progenitor cell fate in hematopoiesis. We examine binding of three factors Gata1, Gata2 and Pu1 at 3 stages of differentiation (multipotential, 5 days of erytroid and neutrophil) , while looking at 2 intermeditate stages of erythroid differentiation for factors Gata2 and Gata1. We also look at Gata2 and Gata1 binding after Gata1 induction using an ER fusion protein.

2013-10-17 | E-GEOD-50406 | biostudies-arrayexpress

Dynamic analysis of gene expression and genome wide transcription factor binding during lineage-specification of multipotent progenitors [ChIP-seq].

2013-10-17 | GSE50406 | GEO

Dynamic analysis of gene expression and genome wide transcription factor binding during lineage-specification of multipotent progenitors [HP]

Project description:FDCPmix cells were infected with Gata, Pu1 shRNAs and microarrayed 5 days after infecton as part of a study investigating the differentiation of a multipotential cell-line to erthroid and myeloid fates. We used the paradigmatic 'GATA-PU.1 axis’ to explore, at systems-level, dynamic relationships between transcription factor (TF) binding and global gene expression programs as multipotent cells differentiate. We combined global ChIPSeq of GATA1, GATA2 and PU.1 with expression profiling during differentiation to erythroid and neutrophil lineages. Our analysis reveals (i) differential complexity of sequence motifs bound by GATA1, GATA2 and PU.1; (ii) the scope and interplay of the GATA1 and GATA2 programs within, and during transitions between, different cell compartments, and the extent of their hard-wiring by DNA motifs; (iii) the potential to predict gene expression trajectories based on global associations between TF-binding data and target gene expression and (iv) how dynamic modeling of DNA-binding and gene expression data can be used to infer regulatory logic of TF circuitry. This 'rubric' exemplifies the utility of this cross-platform resource for deconvoluting the complexity of transcriptional programs controlling stem/progenitor cell fate in hematopoiesis. FDCPmix cells were infected with lentivirus containing either Pu1 or Gata2 shRNAs. After 5 days cells were washed, GFP sorted and microarrayed. Controlled against empty vector.

2013-10-17 | E-GEOD-49989 | biostudies-arrayexpress

Dynamic analysis of gene expression and genome wide transcription factor binding during lineage-specification of multipotent progenitors [TC]

Project description:An expression time course experiment to investigate gene expression changes during differentiation of multipotential cells over two lineages using the model cell line FDCPmix differentiating towards erytroid and myeloid fates. We used the paradigmatic 'GATA-PU.1 axis’ to explore, at systems-level, dynamic relationships between transcription factor (TF) binding and global gene expression programs as multipotent cells differentiate. We combined global ChIPSeq of GATA1, GATA2 and PU.1 with expression profiling during differentiation to erythroid and neutrophil lineages. Our analysis reveals (i) differential complexity of sequence motifs bound by GATA1, GATA2 and PU.1; (ii) the scope and interplay of the GATA1 and GATA2 programs within, and during transitions between, different cell compartments, and the extent of their hard-wiring by DNA motifs; (iii) the potential to predict gene expression trajectories based on global associations between TF-binding data and target gene expression and (iv) how dynamic modeling of DNA-binding and gene expression data can be used to infer regulatory logic of TF circuitry. This 'rubric' exemplifies the utility of this cross-platform resource for deconvoluting the complexity of transcriptional programs controlling stem/progenitor cell fate in hematopoiesis. Multipotential FDCPmix cells were placed in two separate cytokine conditions and differentiated to erythroid and myeloid cells. Samples were taken at the time intervals indicated and hybridised to Agilent expression arrays. Each time point was done in triplicate.

2013-10-17 | E-GEOD-49987 | biostudies-arrayexpress

Dynamic analysis of gene expression and genome wide transcription factor binding during lineage-specification of multipotent progenitors [PC]

Project description:Primary hematopoietic cells from mouse bone marrow were sorted and hybridised expression microarrays as part of a study investigating the differentiation of a multipotential cell-line to erthroid and myeloid fates. We used the paradigmatic 'GATA-PU.1 axis’ to explore, at systems-level, dynamic relationships between transcription factor (TF) binding and global gene expression programs as multipotent cells differentiate. We combined global ChIPSeq of GATA1, GATA2 and PU.1 with expression profiling during differentiation to erythroid and neutrophil lineages. Our analysis reveals (i) differential complexity of sequence motifs bound by GATA1, GATA2 and PU.1; (ii) the scope and interplay of the GATA1 and GATA2 programs within, and during transitions between, different cell compartments, and the extent of their hard-wiring by DNA motifs; (iii) the potential to predict gene expression trajectories based on global associations between TF-binding data and target gene expression and (iv) how dynamic modeling of DNA-binding and gene expression data can be used to infer regulatory logic of TF circuitry. This 'rubric' exemplifies the utility of this cross-platform resource for deconvoluting the complexity of transcriptional programs controlling stem/progenitor cell fate in hematopoiesis. Primary hematopoietic cells from mouse bone marrow sorted using the dissection as described by Pronk et al (2007,Cell Stem Cell) where lin was defined as B220, CD3, CD4, CD8, CD41, Mac1, Gr1, Ter119.

2013-10-17 | E-GEOD-49988 | biostudies-arrayexpress

Dynamic analysis of gene expression and genome wide transcription factor binding during lineage-specification of multipotent progenitors [ER]

Project description:FDCPmix cells were infected with Gata1 and Pu1 ER fusion proteins and microarrayed after induction to reveal genes regulated by each factor as part of a study investigating the differentiation of a multipotential cell-line to erthroid and myeloid fates. We used the paradigmatic 'GATA-PU.1 axis’ to explore, at systems-level, dynamic relationships between transcription factor (TF) binding and global gene expression programs as multipotent cells differentiate. We combined global ChIPSeq of GATA1, GATA2 and PU.1 with expression profiling during differentiation to erythroid and neutrophil lineages. Our analysis reveals (i) differential complexity of sequence motifs bound by GATA1, GATA2 and PU.1; (ii) the scope and interplay of the GATA1 and GATA2 programs within, and during transitions between, different cell compartments, and the extent of their hard-wiring by DNA motifs; (iii) the potential to predict gene expression trajectories based on global associations between TF-binding data and target gene expression and (iv) how dynamic modeling of DNA-binding and gene expression data can be used to infer regulatory logic of TF circuitry. This 'rubric' exemplifies the utility of this cross-platform resource for deconvoluting the complexity of transcriptional programs controlling stem/progenitor cell fate in hematopoiesis. FDCPmix cells were inected with lentivirus containing either Gata1 or Pu1 ER fusion protein, or a empty vector. Cells were sort on GFP and tamoxifen added after a period of growth. Expression arrays were performed at the beginning, and 24hr after induction of the ER fusion construct.

2013-10-17 | E-GEOD-49990 | biostudies-arrayexpress

Dynamic analysis of gene expression and genome wide transcription factor binding during lineage-specification of multipotent progenitors [TC]

2013-10-17 | GSE49987 | GEO

Dynamic analysis of gene expression and genome wide transcription factor binding during lineage-specification of multipotent progenitors [HP]

2013-10-17 | GSE49989 | GEO

Dynamic analysis of gene expression and genome wide transcription factor binding during lineage-specification of multipotent progenitors [ER]

2013-10-17 | GSE49990 | GEO

Genome-wide transcription factor binding and chromatin methylation marks in the G1ME megakaryocytic progenitor model cell line

Project description:There are many examples of transcription factor families whose members control gene expression profiles of diverse cell types. However, the mechanism by which closely related factors occupy distinct regulatory elements and impart lineage specificity is largely undefined. Here we demonstrate on a genome wide scale that the hematopoietic GATA factors GATA-1 and GATA-2 bind overlapping sets of genes, often at distinct sites, as a means to differentially regulate target gene expression and to regulate the balance between proliferation and differentiation. We also reveal that the GATA switch, which entails a chromatin occupancy exchange between GATA2 and GATA1 in the course of differentiation, operates on more than a third of GATA1 bound genes. The switch is equally likely to lead to transcriptional activation or repression and, in general, GATA1 and GATA2 act oppositely on switch target genes. In addition, we reveal that genomic regions co-occupied by GATA2 and the ETS factor ETS1 are strongly enriched for regions marked by H3K4me3 and occupied by Pol II. Finally, by comparing GATA1 occupancy in erythroid cells and megakaryocytes, we find that the presence of ETS factor motifs is a major discriminator of megakaryocyte versus red cell specification.

2012-03-05 | GSE31331 | GEO

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