Global Chromatin Modifications at Enhancers Correlate with Cell Type-Specific Gene Expression in the Human Genome
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE14083 | GEO | 2009/03/01
SECONDARY ACCESSION(S): PRJNA112507
REPOSITORIES: GEO
Similar Datasets
Project description:Differential roles of promoters, enhancers, and insulators in cell-type specific gene expression
| PRJNA100953 | ENA
Project description:Chromatin profiling has emerged as a powerful means for annotating genomic elements and detecting regulatory activity. Here we generate and analyze a compendium of epigenomic maps for nine chromatin marks across nine cell types, in order to systematically characterize cis-regulatory elements, their cell type-specificities, and their functional interactions. We first identify recurrent combinations of histone modifications and use them to annotate diverse regulatory elements including promoters, enhancers, transcripts and insulators in each cell type. We next characterize the dynamics of these elements, revealing meaningful patterns of activity for promoter states and exquisite cell type-selectivity for enhancer states. We define multi-cell activity profiles that reflect the patterns of enhancer state activity across cell types, as well as analogous profiles for gene expression, regulatory motif enrichments, and expression of the corresponding regulators. We use correlations between these profiles to link enhancers to putative target genes, to infer cell type-specific activators and repressors, and to predict and validate functional regulator binding motifs in specific chromatin states. These functional annotations and regulatory predictions enable us to revisit intergenic single-nucleotide polymorphisms (SNPs) associated with human disease in genome-wide association studies (GWAS). We find that for several diseases, top-scoring SNPs are precisely positioned within enhancer elements specifically active in relevant cell types. In several cases a disease variant affects a motif instance for one of the predicted causal regulators, thus providing a potential mechanistic explanation for the disease association. Our study presents a general framework for applying multi-cell chromatin state analysis to decipher cis-regulatory connections and their role in health and disease. 9 human cell types were cultured in duplicate and subject to Affymetrix profiling
2011-03-22 | E-GEOD-26312 | biostudies-arrayexpress
Project description:These tracks display a synthesis of evidence from different assays as part of the four Open Chromatin track sets. This track displays open chromatin regions and/or transcription factor binding sites identified in multiple cell types by one or more complementary methodologies, DNaseI hypersensitivity (HS) (Duke DNaseI HS), Formaldehyde-Assisted Isolation of Regulatory Elements (FAIRE) (UNC FAIRE), and chromatin immunoprecipitation (ChIP) for select regulatory factors (UTA TFBS). Each methodology was performed on the same cell type using identical growth conditions. (Note: Data for some or all ChIP experiments may not be available for all cell types). Regions that overlap between methodologies identify regulatory elements that are cross-validated indicating high confidence regions. In addition, multiple lines of evidence suggest that regions detected by a single assay (e.g., DNase-only or FAIRE-only) are also biologically relevant (Song et al., submitted). DNaseI HS data: DNaseI is an enzyme that has long been used to map general chromatin accessibility, and DNaseI "hypersensitivity" is a feature of active cis-regulatory sequences.The use of this method has led to the discovery of functional regulatory elements that include promoters, enhancers, silencers, insulators, locus control regions, and novel elements. DNaseI hypersensitivity signifies chromatin accessibility following binding of trans-acting factors in place of a canonical nucleosome. FAIRE data: FAIRE (Formaldehyde Assisted Isolation of Regulatory Elements) is a method to isolate and identify nucleosome-depleted regions of the genome. FAIRE was initially discovered in yeast and subsequently shown to identify active regulatory elements in human cells (Giresi et al., 2007). Similar to DNaseI HS, FAIRE appears to identify functional regulatory elements that include promoters, enhancers, silencers, insulators, locus control regions and novel elements. ChIP data: ChIP (Chromatin Immunoprecipitation) is a method to identify the specific location of proteins that are directly or indirectly bound to genomic DNA. By identifying the binding location of sequence-specific transcription factors, general transcription machinery components, and chromatin factors, ChIP can help in the functional annotation of the open chromatin regions identified by DNaseI HS mapping and FAIRE. Input data: As a background control experiment, we sequenced the input genomic DNA sample that was used for ChIP. Crosslinked chromatin is sheared and the crosslinks are reversed without carrying out the immunoprecipitation step. This sample is otherwise processed in a manner identical to the ChIP sample as described below. The input track is useful in revealing potential artifacts arising from the sequence alignment process such as copy number differences between the reference genome and the sequenced samples, as well as regions of poor sequence alignability. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf For each site, the maximum F-Seq Density Signal value has been calculated for each assay that was performed in that cell type. F-Seq employs Parzen kernel density estimation to create base pair scores (Boyle et al., 2008b). Significant regions, or peaks, were determined by fitting the data to a gamma distribution to calculate p-values. Contiguous regions where p-values were below a 0.05 (DNaseI HS, ChIP) or 0.1 (FAIRE) threshold were considered significant. See assay specific description pages ( Duke DNaseI HS, UNC FAIRE and UTA TFBS) for more details. A Fisher's Combined P-value for DNaseI HS and FAIRE was calculated using Fisher's combined probability test. First, a test statistic is calculated using the formula x^2 = -2*sum(ln(pi)) where pi are the p-values calculated for DNaseI HS and FAIRE. X2 follows a chi-squared distribution, thus a combined p-value can be assigned to this test statistic.
2012-09-12 | E-GEOD-40833 | biostudies-arrayexpress
Project description:Characterisation of different histone modifications is crucial to understand gene regulation. In order to study the most predictive histone modification for active enhancers we created unbiased set of enhancers and used machine learning approach. Our approach revealed an unconventional histone modification H2BK20ac as most efficient marker of active enhancers. H2BK20ac also showed superior coverage of tissue specific active enhancers in complex invivo samples. Adding H2BK20ac to set of conventional histone modifications lead to identification of new chromatin state which could be active enhancers. H2BK20ac tends to occur only at cell-type specific active promoters and showed higher specificity for related disease mutations than H3K27ac and other histone modifications. Using transient state of BV2 microglia cells after lipopolysaccharide based activation, we found that H2BK20ac also marks cell-state specific cis-regulatory elements. Further analysis using inhibition of TGF-beta pathway in BV2 cells and LPS stimulation, revealed differential patterns of H2BK20ac and H3K27ac at genome locations associated with opposite roles response to stmulation. Our study about H2BK20ac hints about a new mechanism of regulation of cell-type specificity and a distinct mode of action of pathways to maintain balance between cell-responses. Chip-seq of H2BK20ac and other histone modifcation was performed in 3 cell types and embryonic mouse forebrain. The sensitivity for active enhancers was compared for different histone modification ChIP-seq.The level of H2BK20ac at promoters and enhancers was assesed for relationship to cell-type specific expression. H2BK20ac signals were also analysed during cell-state transition when microgila are stimulated by LPS
2016-02-25 | E-GEOD-72886 | biostudies-arrayexpress
Project description:The spatiotemporal specific gene expression is regulated by cell type-specific regulatory elements including enhancers, silencers and insulators etc. The massively parallel reporter assay (MPRA) methods like STARR-seq facilitate the systematic study of DNA sequence intrinsic enhancer activities in a large scale. However, when applied to human cells, it remains challenging to identify and quantify cell type-specific active enhancers in the genome-wide scale with high-resolution, due to the large size of human genome. In this study, we selected the H3K4me1 associated dinucleosome with the linker DNA sequences as candidate enhancer sequences in two different human cell lines and performed ChIP-STARR-seq to quantify the cell type-specific enhancer activities with high-resolution in a genome-wide scale. Furthermore, we investigated how the activity landscape of enhancer repository would change when transferred from native cells (cis activity) to another cell lines (trans activity). Using ChIP-STARR-seq of the candidate enhancers in native cells and another type of cells, we obtained enhancers cis activity maps and trans activity maps in two different cell lines. The cis and trans activity maps enabled us to identify cell type-specific active enhancers, with enrichment of motifs of differentially expressed TFs. Comparisons between the cis and trans activity maps revealed general consistent regulatory property with different levels of activity in the two cell types, suggesting the sequence intrinsic regulatory properties keep similar in different type of cells. This study provides a new perspective of sequence intrinsic enhancer activities in different types of cells.
2023-09-22 | GSE243793 | GEO
Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Terry Furey mailto:tsfurey@duke.edu). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). These tracks display a synthesis of evidence from different assays as part of the four Open Chromatin track sets. This track displays open chromatin regions and/or transcription factor binding sites identified in multiple cell types by one or more complementary methodologies, DNaseI hypersensitivity (HS) (Duke DNaseI HS), Formaldehyde-Assisted Isolation of Regulatory Elements (FAIRE) (UNC FAIRE), and chromatin immunoprecipitation (ChIP) for select regulatory factors (UTA TFBS). Each methodology was performed on the same cell type using identical growth conditions. (Note: Data for some or all ChIP experiments may not be available for all cell types). Regions that overlap between methodologies identify regulatory elements that are cross-validated indicating high confidence regions. In addition, multiple lines of evidence suggest that regions detected by a single assay (e.g., DNase-only or FAIRE-only) are also biologically relevant (Song et al., submitted). DNaseI HS data: DNaseI is an enzyme that has long been used to map general chromatin accessibility, and DNaseI "hypersensitivity" is a feature of active cis-regulatory sequences.The use of this method has led to the discovery of functional regulatory elements that include promoters, enhancers, silencers, insulators, locus control regions, and novel elements. DNaseI hypersensitivity signifies chromatin accessibility following binding of trans-acting factors in place of a canonical nucleosome. FAIRE data: FAIRE (Formaldehyde Assisted Isolation of Regulatory Elements) is a method to isolate and identify nucleosome-depleted regions of the genome. FAIRE was initially discovered in yeast and subsequently shown to identify active regulatory elements in human cells (Giresi et al., 2007). Similar to DNaseI HS, FAIRE appears to identify functional regulatory elements that include promoters, enhancers, silencers, insulators, locus control regions and novel elements. ChIP data: ChIP (Chromatin Immunoprecipitation) is a method to identify the specific location of proteins that are directly or indirectly bound to genomic DNA. By identifying the binding location of sequence-specific transcription factors, general transcription machinery components, and chromatin factors, ChIP can help in the functional annotation of the open chromatin regions identified by DNaseI HS mapping and FAIRE. Input data: As a background control experiment, we sequenced the input genomic DNA sample that was used for ChIP. Crosslinked chromatin is sheared and the crosslinks are reversed without carrying out the immunoprecipitation step. This sample is otherwise processed in a manner identical to the ChIP sample as described below. The input track is useful in revealing potential artifacts arising from the sequence alignment process such as copy number differences between the reference genome and the sequenced samples, as well as regions of poor sequence alignability. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf For each site, the maximum F-Seq Density Signal value has been calculated for each assay that was performed in that cell type. F-Seq employs Parzen kernel density estimation to create base pair scores (Boyle et al., 2008b). Significant regions, or peaks, were determined by fitting the data to a gamma distribution to calculate p-values. Contiguous regions where p-values were below a 0.05 (DNaseI HS, ChIP) or 0.1 (FAIRE) threshold were considered significant. See assay specific description pages ( Duke DNaseI HS, UNC FAIRE and UTA TFBS) for more details. A Fisher's Combined P-value for DNaseI HS and FAIRE was calculated using Fisher's combined probability test. First, a test statistic is calculated using the formula x^2 = -2*sum(ln(pi)) where pi are the p-values calculated for DNaseI HS and FAIRE. X2 follows a chi-squared distribution, thus a combined p-value can be assigned to this test statistic.
2011-10-25 | E-GEOD-33213 | biostudies-arrayexpress
Project description:Regulatory DNA elements in the human genome play important roles in determining the transcriptional abundance and spatiotemporal gene expression. It is a mystery how chromatin marks in regulatory elements are modulated to establish cell type-specific gene expression. Here we profiled a variety of epigenetic marks in the regulatory elements using massive ChIP-seq (n=84). We uncovered two classes of regulatory elements: Class I was identified with ubiquitous enhancer (H3K4me1) and promoter (H3K4me3) marks in all cell types, whereas Class II was enriched with H3K4me1 and H3K4me3 in a cell type-specific manner. For common genes regulated by both promoters and enhancers, Class I promoters displayed dominant regulatory effects on transcriptional abundance. Moreover, human iPSCs and somatic cells selected their preferential regulatory elements to maintain cell type-specific gene expression. Our study provides valuable resources for deciphering the epigenetic modulation of regulatory elements that fine-tune spatiotemporal gene expression in human development and diseases.
2017-12-04 | GSE97033 | GEO
Project description:The readout of genome information is controlled by transcriptional regulatory elements, but a comprehensive view of the combinatorial control by these DNA sequences, which bind regulatory protein and/or the modified histones in regulating gene transcription, is clearly preliminary. We have developed an experimental strategy for comprehensive determination of such functional elements in human DNA. This strategy involves the application of genome-wide location analysis, also known as ChIP-chip, to a panel of well-characterized regulatory proteins and histones with specific modifications, known to generally associate with transcriptional regulatory elements in vivo. Identification of their genomic binding sites will allow us to determine the sequence features in the human genome that carry out transcriptional regulatory function. We have designed and produced DNA microarrays to represent all the non-repetitive sequences in the 30 million basepair ENCODE regions of the human genome to map various types of transcriptional regulatory elements in three model cell types. We have identified promoters by mapping the genomic sequences associated with RNA polymerase II and the general transcription factor TFIID in cells, enhancer elements by mapping the genomic sequences associated with transcriptional co-activators and enhancer-specific chromatin modifications, and insulators by mapping the genomic sequences associated with the insulator binding protein CTCF. The raw microarray results are released periodically prior to publication. Keywords: ChIP-chip ENCODE ChIP-chip analyses were performed for various transcription factors and chromatin modifications in various cell types. Details to be described in publications.
2010-06-12 | E-GEOD-7118 | biostudies-arrayexpress
Project description:Chromatin profiling has emerged as a powerful means for annotating genomic elements and detecting regulatory activity. Here we generate and analyze a compendium of epigenomic maps for nine chromatin marks across nine cell types, in order to systematically characterize cis-regulatory elements, their cell type-specificities, and their functional interactions. We first identify recurrent combinations of histone modifications and use them to annotate diverse regulatory elements including promoters, enhancers, transcripts and insulators in each cell type. We next characterize the dynamics of these elements, revealing meaningful patterns of activity for promoter states and exquisite cell type-selectivity for enhancer states. We define multi-cell activity profiles that reflect the patterns of enhancer state activity across cell types, as well as analogous profiles for gene expression, regulatory motif enrichments, and expression of the corresponding regulators. We use correlations between these profiles to link enhancers to putative target genes, to infer cell type-specific activators and repressors, and to predict and validate functional regulator binding motifs in specific chromatin states. These functional annotations and regulatory predictions enable us to revisit intergenic single-nucleotide polymorphisms (SNPs) associated with human disease in genome-wide association studies (GWAS). We find that for several diseases, top-scoring SNPs are precisely positioned within enhancer elements specifically active in relevant cell types. In several cases a disease variant affects a motif instance for one of the predicted causal regulators, thus providing a potential mechanistic explanation for the disease association. Our study presents a general framework for applying multi-cell chromatin state analysis to decipher cis-regulatory connections and their role in health and disease.
2011-03-23 | GSE26320 | GEO
Project description:Chromatin profiling has emerged as a powerful means for annotating genomic elements and detecting regulatory activity. Here we generate and analyze a compendium of epigenomic maps for nine chromatin marks across nine cell types, in order to systematically characterize cis-regulatory elements, their cell type-specificities, and their functional interactions. We first identify recurrent combinations of histone modifications and use them to annotate diverse regulatory elements including promoters, enhancers, transcripts and insulators in each cell type. We next characterize the dynamics of these elements, revealing meaningful patterns of activity for promoter states and exquisite cell type-selectivity for enhancer states. We define multi-cell activity profiles that reflect the patterns of enhancer state activity across cell types, as well as analogous profiles for gene expression, regulatory motif enrichments, and expression of the corresponding regulators. We use correlations between these profiles to link enhancers to putative target genes, to infer cell type-specific activators and repressors, and to predict and validate functional regulator binding motifs in specific chromatin states. These functional annotations and regulatory predictions enable us to revisit intergenic single-nucleotide polymorphisms (SNPs) associated with human disease in genome-wide association studies (GWAS). We find that for several diseases, top-scoring SNPs are precisely positioned within enhancer elements specifically active in relevant cell types. In several cases a disease variant affects a motif instance for one of the predicted causal regulators, thus providing a potential mechanistic explanation for the disease association. Our study presents a general framework for applying multi-cell chromatin state analysis to decipher cis-regulatory connections and their role in health and disease.
2011-03-23 | GSE26312 | GEO