Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA236115 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Purpose: 253 GSM Samples from GSE32970 and GSE29692 was reanalyzed to find the highly occupied target (HOT) regions of 154 cell lines. Methods: 1. We assigned the binding sites of 542 TFs in 154 cell lines as GSE53962 (Our last submission). 2.We performed a Gaussian kernel density estimation across the genome with a bandwidth of 300 bp, using the centers of each of the TF binding peaks as points. Then, we scanned this density for peaks, and denoted each peak a TF region(Candidate region to find HOT regions).To determine the complexity of the TF region, we summed the Gaussian kernalized distance from the peak to each TF that contributed at least 0.1 to its strength. The TF region around eat peak was derived by finding the maximum distance (in bp) from the peak to a contributing TF, and then adding 150 bp (one half of the bandwidth). Each TF region is centered on the peak, and have a TF complexity value. 3.To define HOT region according to the TF complexity, we required a complexity cutoff for each cell line.To geometrically define the cutoff we first scaled the TF complexity such that the x and y axis were from 0-1. We then found the x axis point for which a line with a slope of 1 was tangent to the curve. We define this point as the cutoff value,TF region whose complexity above this point to be HOT region, and TF region complexity below that point to be lowly occupied target (LOT) regions. Result: Using the binding sites of 542 TFs in 145 cell lines, we assigned a TF complexity score to each TF region corresponding to the number of distinct TFs bound, resulting in HOT regions of 145 cell lines.
2015-01-14 | GSE54296 | GEO
Project description:Transcription Factor Binding Sites clustered Regions of 133 Cell Lines
| PRJNA254146 | ENA
Project description:Transcriptional regulation is central to organisms’ response and adaptation to environmental changes. However, the coordination of transcriptional machinery with chromatin when rapid transcriptional changes are needed is largely unknown. Here, we studied the rapid response of histone modifications upon heat treatment of fission yeast Schizosaccharomyces pombe. We observed a significant eviction of H3 in the transcribed regions of upregulated genes, named Hasty Overheat-Triggered Differentially Occupied Genes (HOT-DOGs), including Heat Shock Protein-encoding genes. The loss of H3 in a third of the HOT-DOGs were dependent on the Atf1-Pcr1 transcription factor complex. Furthermore, the H3K9 methyltransferase Clr4 likely modulates the rate of transcription elongation and helps prevent transcriptional read-through beyond polyadenylation sites in these genes. Our results unveiled a novel function of Clr4 in regulating the dynamics of transcription within gene bodies and provided insights into how cells cope with rapid environmental changes while preserving chromatin integrity.
2026-02-25 | GSE265755 | GEO
Project description:Transcription factor overexpression in HeLa cell lines
| PRJNA92001 | ENA
Project description:Somatic hypermutation (SHM) introduces point mutations into immunoglobulin (Ig) genes of activated B cells to support the process of antibody affinity maturation but also causes "off-target" mutations in other parts of the genome. We have used sensitive lentiviral SHM reporter vectors and a mutationally active human B cell line to identify dozens of regions of the genome that are intrinsically susceptible to SHM ("hot" regions) and many hundreds of regions that are resistant to SHM ("cold" regions). Hot and cold regions are frequently contained within topologically associated domains (TADs). Comparison of hot and cold TADs reveals that while overall levels of transcription are equal, hot TADs are enriched for NIPBL (a component of the cohesin loader), super enhancers, markers of paused/stalled RNA polymerase 2, and multiple transcription factors implicated in B cell development and targeting of SHM. We demonstrate that at least some hot TADs contain enhancer elements that possess SHM targeting activity and that insertion of a strong Ig SHM-targeting element into a cold TAD renders it hot. Our findings lead to a model for SHM susceptibility involving the cooperative action of cis-acting SHM targeting elements and the dynamic and architectural properties of TADs.
2019-12-04 | GSE139810 | GEO
Project description:To gain insights into the interplay between DNA methylation and gene regulation we generated a basepair resolution reference map of the mouse methylome in stem cells and neurons. High genome coverage allowed for a novel quantitative analysis of local methylation states, which identified Low Methylated Regions (LMR) with an average methylation of 30%. These regions are evolutionary conserved, reside outside of CpG islands and distal to promoters. They represent regulatory regions evidenced by their DNaseI hypersensitivity and chromatin marks of enhancer elements. LMRs are occupied by transcription factors (TF) and their reduced methylation requires TF binding while introduction of TF binding sites creates LMRs de novo. This dependency on TF activity is further evident when comparing the methylomes of embryonic stem cells and derived neuronal cells. LMRs present in both cell types are occupied by broadly expressed factors, while LMRs present at only one state are occupied by cell-type specific TFs. Methylome data can thus enhance the prediction of occupied TF binding sites and identification of active regulatory regions genome-wide. Our study provides reference methylomes for the mouse at two cell states, identifies a novel and highly dynamic feature of the epigenome that defines distal regulatory elements and shows that transcription factor binding dynamically shapes mammalian methylomes. Strand specific expression profiling by high throughput sequencing.
2011-12-15 | E-GEOD-31385 | biostudies-arrayexpress
Project description:To gain insights into the interplay between DNA methylation and gene regulation we generated a basepair resolution reference map of the mouse methylome in stem cells and neurons. High genome coverage allowed for a novel quantitative analysis of local methylation states, which identified Low Methylated Regions (LMR) with an average methylation of 30%. These regions are evolutionary conserved, reside outside of CpG islands and distal to promoters. They represent regulatory regions evidenced by their DNaseI hypersensitivity and chromatin marks of enhancer elements. LMRs are occupied by transcription factors (TF) and their reduced methylation requires TF binding while introduction of TF binding sites creates LMRs de novo. This dependency on TF activity is further evident when comparing the methylomes of embryonic stem cells and derived neuronal cells. LMRs present in both cell types are occupied by broadly expressed factors, while LMRs present at only one state are occupied by cell-type specific TFs. Methylome data can thus enhance the prediction of occupied TF binding sites and identification of active regulatory regions genome-wide. Our study provides reference methylomes for the mouse at two cell states, identifies a novel and highly dynamic feature of the epigenome that defines distal regulatory elements and shows that transcription factor binding dynamically shapes mammalian methylomes. RNA_sequencing of mouse embryonic stem (ES) cells and derived neuronal progenitors (NP).
2011-12-22 | E-GEOD-30280 | biostudies-arrayexpress
Project description:Amplification of the locus encoding the oncogenic transcription factor MYCN is a defining feature of high-risk neuroblastoma. Here we present the first dynamic chromatin and transcriptional landscape of MYCN perturbation in neuroblastoma. At oncogenic levels, MYCN associates with E-box binding motifs in an affinity-dependent manner, binding to strong canonical E-boxes at promoters and invading abundant weaker non-canonical E-boxes clustered at enhancers. Loss of MYCN leads to a global reduction in transcription, which is most pronounced at MYCN target genes with the greatest enhancer occupancy. These highly occupied MYCN target genes show tissue-specific expression and are linked to poor patient survival. The activity of genes with MYCN-occupied enhancers is dependent on the tissue-specific transcription factor TWIST1, which co-occupies enhancers with MYCN and is required for MYCN-dependent proliferation. These data implicate tissue-specific enhancers in defining often highly tumor-specific ‘MYC target gene signatures’ and identify disruption of the MYCN enhancer regulatory axis as a promising therapeutic strategy in neuroblastoma.
2018-01-29 | GSE80154 | GEO
Project description:To gain insights into the interplay between DNA methylation and gene regulation we generated a basepair resolution reference map of the mouse methylome in stem cells and neurons. High genome coverage allowed for a novel quantitative analysis of local methylation states, which identified Low Methylated Regions (LMR) with an average methylation of 30%. These regions are evolutionary conserved, reside outside of CpG islands and distal to promoters. They represent regulatory regions evidenced by their DNaseI hypersensitivity and chromatin marks of enhancer elements. LMRs are occupied by transcription factors (TF) and their reduced methylation requires TF binding while introduction of TF binding sites creates LMRs de novo. This dependency on TF activity is further evident when comparing the methylomes of embryonic stem cells and derived neuronal cells. LMRs present in both cell types are occupied by broadly expressed factors, while LMRs present at only one state are occupied by cell-type specific TFs. Methylome data can thus enhance the prediction of occupied TF binding sites and identification of active regulatory regions genome-wide. Our study provides reference methylomes for the mouse at two cell states, identifies a novel and highly dynamic feature of the epigenome that defines distal regulatory elements and shows that transcription factor binding dynamically shapes mammalian methylomes. Whole genome shotgun bisulfite sequencing of mouse embryonic stem (ES) cells and derived neuronal progenitors (NP). CTCF ChIP sequencing in mouse ES and Dnmt1/3a/3b triple knock-out ES (TKO) cells. H3K4me1, H3K4me2 and H3K27me3 ChIP sequencing in mouse SE cells. Pax6 ChIP-chip in mouse NP cells.
2011-12-09 | E-GEOD-30204 | biostudies-arrayexpress
Project description:To gain insights into the interplay between DNA methylation and gene regulation we generated a basepair resolution reference map of the mouse methylome in stem cells and neurons. High genome coverage allowed for a novel quantitative analysis of local methylation states, which identified Low Methylated Regions (LMR) with an average methylation of 30%. These regions are evolutionary conserved, reside outside of CpG islands and distal to promoters. They represent regulatory regions evidenced by their DNaseI hypersensitivity and chromatin marks of enhancer elements. LMRs are occupied by transcription factors (TF) and their reduced methylation requires TF binding while introduction of TF binding sites creates LMRs de novo. This dependency on TF activity is further evident when comparing the methylomes of embryonic stem cells and derived neuronal cells. LMRs present in both cell types are occupied by broadly expressed factors, while LMRs present at only one state are occupied by cell-type specific TFs. Methylome data can thus enhance the prediction of occupied TF binding sites and identification of active regulatory regions genome-wide. Our study provides reference methylomes for the mouse at two cell states, identifies a novel and highly dynamic feature of the epigenome that defines distal regulatory elements and shows that transcription factor binding dynamically shapes mammalian methylomes. Whole genome shotgun bisulfite sequencing of mouse embryonic stem (ES) cells and derived neuronal progenitors (NP). CTCF ChIP sequencing in mouse ES and Dnmt1/3a/3b triple knock-out ES (TKO) cells. H3K4me1, H3K4me2 and H3K27me3 ChIP sequencing in mouse ES cells. Pax6 ChIP-chip in mouse ES cells.
2011-12-09 | E-GEOD-30203 | biostudies-arrayexpress