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NextPBM - A platform to study cell-specific transcription factor binding and cooperativity [array]

ABSTRACT: NextPBM - A platform to study cell-specific transcription factor binding and cooperativity [array]

PROVIDER: PRJNA510376 | ENA |

REPOSITORIES: ENA

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NextPBM - A platform to study cell-specific transcription factor binding and cooperativity [array]

Project description:High-throughput (HT) in vitro methods for measuring protein-DNA binding have become invaluable for characterizing transcription factor (TF) complexes and modeling gene regulation. However, current methods do not utilize endogenous proteins and, therefore, do not quantify the impact of cell-specific post-translational modifications (PTMs) and cooperative cofactors. We introduce the HT nextPBM (nuclear extract protein-binding microarray) approach to study DNA binding of native cellular TFs that accounts for PTMs and cell-specific cofactors. We integrate immune-depletion and phosphatase-treatment steps into our nextPBM pipeline to characterize the impact of cofactors and phosphorylation on TF binding. We analyze binding of PU.1/SPI1 and IRF8 from human monocytes, delineate DNA-sequence determinants for their cooperativity, and show how PU.1 affinity correlates with enhancer status and the presence of cooperative and collaborative cofactors. We describe how nextPBMs, and our accompanying computational framework, can be used to discover cell-specific cofactors, screen for synthetic cooperative DNA elements, and characterize TF cooperativity at single-nucleotide resolution.

2018-12-18 | GSE123946 | GEO

NextPBM - A platform to study cell-specific transcription factor binding and cooperativity

Project description:NextPBM - A platform to study cell-specific transcription factor binding and cooperativity

| PRJNA510373 | ENA

NextPBM - A platform to study cell-specific transcription factor binding and cooperativity [ChIP-Seq]

Project description:NextPBM - A platform to study cell-specific transcription factor binding and cooperativity [ChIP-Seq]

| PRJNA510375 | ENA

NextPBM - A platform to study cell-specific transcription factor binding and cooperativity [ChIP-Seq]

Project description:We analyzed binding of PU.1/SPI1 and IRF8 from human monocytes, delineate DNA-sequence determinants for their cooperativity using nextPBM, and show how PU.1 affinity correlates with enhancer status and the presence of cooperative and collaborative factors (C/EBPa)

2018-12-18 | GSE123872 | GEO

NextPBM: a platform to study cell-specific transcription factor binding and cooperativity.

Project description:High-throughput (HT) in vitro methods for measuring protein-DNA binding have become invaluable for characterizing transcription factor (TF) complexes and modeling gene regulation. However, current methods do not utilize endogenous proteins and, therefore, do not quantify the impact of cell-specific post-translational modifications (PTMs) and cooperative cofactors. We introduce the HT nextPBM (nuclear extract protein-binding microarray) approach to study DNA binding of native cellular TFs that accounts for PTMs and cell-specific cofactors. We integrate immune-depletion and phosphatase treatment steps into our nextPBM pipeline to characterize the impact of cofactors and phosphorylation on TF binding. We analyze binding of PU.1/SPI1 and IRF8 from human monocytes, delineate DNA-sequence determinants for their cooperativity, and show how PU.1 affinity correlates with enhancer status and the presence of cooperative and collaborative cofactors. We describe how nextPBMs, and our accompanying computational framework, can be used to discover cell-specific cofactors, screen for synthetic cooperative DNA elements, and characterize TF cooperativity.

| S-EPMC6451091 | biostudies-literature

NextPBM - A platform to study cell-specific transcription factor binding and cooperativity

Project description:This SuperSeries is composed of the SubSeries listed below.

2018-12-18 | GSE123947 | GEO

Transcription factor cooperativity in early adipogenic hotspots and super-enhancers

Project description:Here we have used a combination of advanced proteomics and genomics approaches to investigate the extent and mechanisms of transcription factor cross-talk at genomic hotspots. We identify ~12,000 transcription factor hotspots in the early phase of adipogenesis, and we find evidence of both simultaneous and sequential binding of transcription factors at these regions. We demonstrate for the first time that hotspots are highly enriched in large super-enhancer regions and that these drive the early adipogenic reprogramming of gene expression. Our results indicate that cooperativity between transcription factors at the level of hotspots as well as super-enhancers is very important for enhancer activity and transcriptional reprogramming. Thus, hotspots and super-enhancers constitute important regulatory hubs integrating external stimuli on chromatin. Genome-wide profiling of transcription factor and co-factor binding, epigenomic marks, and gene expression in 3T3-L1 pre-adipocytes.

2014-04-17 | E-GEOD-56872 | biostudies-arrayexpress

DNA-guided transcription factor cooperativity shapes face and limb mesenchyme

Project description:DNA-guided transcription factor cooperativity shapes face and limb mesenchyme

| PRJNA958229 | ENA

Cross-platform study

Project description:Cross-platform study

| PRJNA95853 | ENA

Cross-Platform Array Comparative Genomic Hybridization (array CGH) Meta-Analysis

Project description:A series of studies have been published that evaluate the chromosomal copy number changes of different tumor classes using array Comparative Genomic Hybridization (array CGH), however the chromosomal aberrations that distinguish the different tumor classes have not been fully characterized. Therefore, we performed a meta-analysis of different array CGH data sets in an attempt to classify samples tested across different platforms. As opposed to RNA expression a common reference is used in dual channel CGH arrays: normal human DNA, theoretically facilitating cross-platform analysis. To this aim, cell line and primary cancer data sets from three different dual channel array CGH platforms obtained by four different institutes were integrated. The cell line data were used to develop preprocessing methods which performed noise reduction and transformed samples into a common format. The transformed array CGH profiles allowed perfect clustering by cell line, but importantly not by platform or institute. The same preprocessing procedures used for the cell line data were applied to data from 373 primary tumors profiled by array CGH, including controls. Results indicated that there is no apparent feature related to the institute or platform and that array CGH allows for unambiguous cross-platform meta-analysis. Major clusters with common tissue origin were identified. Interestingly, tumors of hematopoietic and mesenchymal origins cluster separately from tumors of epithelial origin. Therefore it can be concluded that chromosomal aberrations of tumors from hematopoietic and mesenchymal origin versus tumors of epithelial origin are distinct, and these differences can be picked up by metaanalysis of array CGH data. This suggests the possibility of prospectively using combined analysis of diverse copy number datasets for cancer subtype classification. Keywords: comparative genomic hybridization, meta-analysis, cancer

2006-08-29 | GSE5051 | GEO

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