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.
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.
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.
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).
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.
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.
Project description:We investigated the regions that are occupied by deltaNp63 in BxPC-3 and L3.6pl and identification of super enhancers in different pancreatic cancer cell lines. Thereby, we identified a group of 45 super enhancers that are associated with poorer prognosis and are highly dependent on deltaNp63.
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.
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.