Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Integration of Hi-C and ChIP-seq data reveals distinct types of chromatin hubs

ABSTRACT: We have analyzed publicly available K562 Hi-C data, which enables genome-wide unbiased capturing of chromatin interactions, using a Mixture Poisson Regression Model to define a highly specific set of interacting genomic regions. We integrated multiple ENCODE Consortium resources with the Hi-C data, using DNase-seq data and ChIP-seq data for 46 transcription factors and 8 histone modifications. We classified 12 different sets (clusters) of interacting loci that can be distinguished by their chromatin modifications and which can be categorized into three types of chromatin hubs. The different clusters of loci display very different relationships with transcription factor binding sites. As expected, many of the transcription factors show binding patterns specific to clusters composed of interacting loci that encompass promoters or enhancers. However, cluster 6, which is distinguished by marks of open chromatin but not by marks of active enhancers or promoters, was not bound by most transcription factors but was highly enriched for 3 transcription factors (GATA1, GATA2, and c-Jun) and 3 chromatin modifiers (BRG1, INI1, and SIRT6). To validate the identification of the clusters and to dissect the impact of chromatin organization on gene regulation, we performed RNA-seq analyses before and after knockdown of GATA1 or GATA2. We found that knockdown of the GATA factors greatly alters the expression of genes within cluster 6. Our work, in combination with previous studies linking regulation by GATA factors with c-Jun and BRG1, provide genome-wide evidence that Hi-C data identifies sets of biologically relevant interacting loci.

ORGANISM(S): Homo sapiens

PROVIDER: GSE32213 | GEO | 2012/07/01

SECONDARY ACCESSION(S): PRJNA147485

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Integration of Hi-C and ChIP-seq data reveals distinct types of chromatin hubs

Project description:We have analyzed publicly available K562 Hi-C data, which enables genome-wide unbiased capturing of chromatin interactions, using a Mixture Poisson Regression Model to define a highly specific set of interacting genomic regions. We integrated multiple ENCODE Consortium resources with the Hi-C data, using DNase-seq data and ChIP-seq data for 46 transcription factors and 8 histone modifications. We classified 12 different sets (clusters) of interacting loci that can be distinguished by their chromatin modifications and which can be categorized into three types of chromatin hubs. The different clusters of loci display very different relationships with transcription factor binding sites. As expected, many of the transcription factors show binding patterns specific to clusters composed of interacting loci that encompass promoters or enhancers. However, cluster 6, which is distinguished by marks of open chromatin but not by marks of active enhancers or promoters, was not bound by most transcription factors but was highly enriched for 3 transcription factors (GATA1, GATA2, and c-Jun) and 3 chromatin modifiers (BRG1, INI1, and SIRT6). To validate the identification of the clusters and to dissect the impact of chromatin organization on gene regulation, we performed RNA-seq analyses before and after knockdown of GATA1 or GATA2. We found that knockdown of the GATA factors greatly alters the expression of genes within cluster 6. Our work, in combination with previous studies linking regulation by GATA factors with c-Jun and BRG1, provide genome-wide evidence that Hi-C data identifies sets of biologically relevant interacting loci. RNA-seq of control, siGATA1 and siGATA2 K562 cells

2012-06-30 | E-GEOD-32213 | biostudies-arrayexpress

GATA Switch Enhancers Mark Dynamically Regulated Chromatin Interaction Nodes during Erythroid Maturation

Project description:Erythropoiesis is among the best understood examples of cell differentiation. In a required step, GATA1 replaces GATA2 at genomic loci, termed GATA switch enhancers. Little is known about how this switch affects chromatin architecture. Here, we show that cohesin binds GATA1 and occupies most GATA switch enhancers. Cohesin-based chromatin interaction analysis demonstrated that the most dynamic and interactive enhancers are enriched for GATA switch sites/TAL1 occupancy and frequently lack super-enhancer features. A c-kit locus CRISPR/Cas9 screen identified GATA motifs within one such element as strongly impacting expression. These data highlight the role of developmentally exchanged transcription factors in modulating genomic folding.

2024-01-05 | GSE155103 | GEO

Divergent functions of hematopoietic transcription factors in lineage priming and differentiation during erythro-megakaryopoiesis

Project description:Combinatorial actions of relatively few transcription factors control hematopoietic differentiation. To investigate this process in erythro-megakaryopoiesis, we correlated the genome-wide chromatin occupancy signatures of four master hematopoietic transcription factors (GATA1, GATA2, TAL1, and FLI1) and three diagnostic histone modification marks with the gene expression changes that occur during development of primary cultured megakaryocytes (MEG) and primary erythroblasts (ERY) from murine fetal liver hematopoietic stem/progenitor cells. We identified a robust, genome-wide mechanism of MEG-specific lineage priming by a previously described stem/progenitor cell-expressed transcription factor heptad (GATA2, LYL1, TAL1, FLI1, ERG, RUNX1, LMO2) binding to MEG-associated cis-regulatory modules (CRMs) in multipotential progenitors. This is followed by genome-wide GATA factor switching that mediates further induction of MEG-specific genes following lineage commitment. Interaction between GATA and ETS factors appears to be a key determinant of these processes. In contrast, ERY-specific lineage priming is biased toward GATA2-independent mechanisms. In addition to its role in MEG lineage priming, GATA2 plays an extensive role in late megakaryopoiesis as a transcriptional repressor at loci defined by a specific DNA signature. Our findings reveal important new insights into how ERY and MEG lineages arise from a common bipotential progenitor via overlapping and divergent functions of shared hematopoietic transcription factors. Genome-wide chromatin occupancy using ChIP-seq on 4 transcription factors (GATA1, GATA2, TAL1, and FLII) and three histone marks (H3K4me1, H3K4me3, and H3K27me3) in lineage-commited primary erythoblasts (ERY) and primary cultured megakaryocytes (MEG).

2014-11-14 | E-GEOD-51337 | biostudies-arrayexpress

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. We used Illumina ChIP-Seq to examine binding of GATA1, GATA2, and ETS1 transcription factors as well as the genomic locations of two histone methylation marks, H3K4me3 and H3K27me3. Except H3K4me3 (1 sample), all data were generated from at least 2 biological replicates of immunoprecipitations from megakaryocyte progenitor cells, G1ME. Input DNA was prepared and sequenced along with each immunoprecipitation and used as a control dataset for binding site identification.

2012-03-05 | E-GEOD-31331 | biostudies-arrayexpress

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

2012-03-05 | GSE31331 | GEO

Divergent functions of hematopoietic transcription factors in lineage priming and differentiation during erythro-megakaryopoiesis

Project description:Combinatorial actions of relatively few transcription factors control hematopoietic differentiation. To investigate this process in erythro-megakaryopoiesis, we correlated the genome-wide chromatin occupancy signatures of four master hematopoietic transcription factors (GATA1, GATA2, SCL/TAL1 and FLI1) and three diagnostic histone modification marks with the gene expression changes that occur during development of primary megakaryocytes (MEG) and erythroblasts (ERY) from murine fetal liver hematopoietic stem/progenitor cells. We identified a robust, genome-wide mechanism of MEG-specific lineage priming by a previously described stem/progenitor cell-expressed transcription factor heptad (GATA2, LYL1, SCL/TAL1, FLI1, ERG, RUNX1, LMO2) binding to MEG-specific cis-regulatory modules in multipotential hematopoietic progenitors. This is followed by genome-wide GATA factor switching that mediates further induction of MEG-specific genes following lineage commitment. Interaction between GATA and ETS factors appears to be a key determinant of these processes. In contrast, ERY-specific lineage priming occurs is biased toward GATA2-independent mechanisms. In addition to its role in MEG lineage priming, GATA2 plays an extensive role in late megakaryopoiesis as a transcriptional repressor at loci defined by a specific DNA signature. Our findings reveal important new insights into how ERY and MEG lineages arise from a common bipotential precursor via overlapping and divergent functions of shared hematopoietic transcription factors. Gene expression changes during the development of primary megakaryocytes (MEG) and erythroblasts (ERY) from murine fetal liver hematopoietic stem/progenitor cells

2013-08-09 | E-GEOD-49664 | biostudies-arrayexpress

Divergent functions of hematopoietic transcription factors in lineage priming and differentiation during erythro-megakaryopoiesis

Project description:Combinatorial actions of relatively few transcription factors control hematopoietic differentiation. To investigate this process in erythro-megakaryopoiesis, we correlated the genome-wide chromatin occupancy signatures of four master hematopoietic transcription factors (GATA1, GATA2, SCL/TAL1 and FLI1) and three diagnostic histone modification marks with the gene expression changes that occur during development of primary megakaryocytes (MEG) and erythroblasts (ERY) from murine fetal liver hematopoietic stem/progenitor cells. We identified a robust, genome-wide mechanism of MEG-specific lineage priming by a previously described stem/progenitor cell-expressed transcription factor heptad (GATA2, LYL1, SCL/TAL1, FLI1, ERG, RUNX1, LMO2) binding to MEG-specific cis-regulatory modules in multipotential hematopoietic progenitors. This is followed by genome-wide GATA factor switching that mediates further induction of MEG-specific genes following lineage commitment. Interaction between GATA and ETS factors appears to be a key determinant of these processes. In contrast, ERY-specific lineage priming occurs is biased toward GATA2-independent mechanisms. In addition to its role in MEG lineage priming, GATA2 plays an extensive role in late megakaryopoiesis as a transcriptional repressor at loci defined by a specific DNA signature. Our findings reveal important new insights into how ERY and MEG lineages arise from a common bipotential precursor via overlapping and divergent functions of shared hematopoietic transcription factors.

2013-08-09 | GSE49664 | GEO

Divergent functions of hematopoietic transcription factors in lineage priming and differentiation during erythro-megakaryopoiesis

2014-11-14 | GSE51337 | GEO

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

Genome-wide maps of GATA factor occupancy in K562 cells

Project description:GATA factors interact with simple DNA motifs (WGATAR) to regulate critical processes, including hematopoiesis, but very few WGATAR motifs are occupied in genomes. Given the rudimentary knowledge of mechanisms underlying this restriction, and how GATA factors establish genetic networks, we used ChIP-seq to define GATA-1 and GATA-2 occupancy genome-wide in erythroid cells. Coupled with genetic complementation analysis and transcriptional profiling, these studies revealed a rich collection of targets containing a characteristic binding motif of greater complexity than WGATAR. GATA factors occupied loci encoding multiple components of the Scl/TAL1 complex, a master regulator of hematopoiesis and leukemogenic target. Mechanistic analyses provided evidence for cross-regulatory and autoregulatory interactions among components of this complex, including GATA-2 induction of the hematopoietic corepressor ETO-2 and an ETO-2 negative autoregulatory loop. These results establish fundamental principles underlying GATA factor mechanisms in chromatin and illustrate a complex network of considerable importance for the control of hematopoiesis. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Examination of GATA1 and GATA2 occpancy in K562 cells

2009-11-25 | E-GEOD-18868 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data