Genome-wide High Resolution Mapping of Active Regulatory DNA Elements in the Rice Genome
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PROVIDER: PRJNA136151 | ENA |
REPOSITORIES: ENA
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Project description:This SuperSeries is composed of the following subset Series: GSE26610: DNase I hypersensitive sites in two tissues of rice GSE26733: ChIP-seq to identify the positions of three histone modifications in the rice genome Refer to individual Series
2011-11-09 | E-GEOD-26734 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the SubSeries listed below.
2011-11-09 | GSE26734 | GEO
Project description:Interactions between cis-regulatory elements such as promoters and enhancers are important for transcription but global identification of these interactions remains a major challenge. Leveraging the chromatin accessiblity of regulatory elements, we developed ARC-C (accessible region chromosome conformation capture), which profiles chromatin regulatory interactions genome-wide at high resolution. Applying ARC-C to C. elegans, we identify ~15,000 significant interactions at 500bp resolution. Regions bound by transcription factors and chromatin regulators such as cohesin and condensin II are enriched for interactions, and we use ARC-C to show that the BLMP-1 transcription factor mediates interactions between its targets. Investigating domain level architecture, we find that C. elegans chromatin domains defined by either active or repressive modifications form topologically associating domains (TADs) and that these domains interact to form A/B (active/inactive) compartment structure. ARC-C is a powerful new tool to interrogate genome architecture and regulatory interactions at high resolution.
2021-06-01 | GSE144672 | GEO
Project description:Interactions between cis-regulatory elements such as promoters and enhancers are important for transcription but global identification of these interactions remains a major challenge. Leveraging the chromatin accessiblity of regulatory elements, we developed ARC-C (accessible region chromosome conformation capture), which profiles chromatin regulatory interactions genome-wide at high resolution. Applying ARC-C to C. elegans, we identify ~15,000 significant interactions at 500bp resolution. Regions bound by transcription factors and chromatin regulators such as cohesin and condensin II are enriched for interactions, and we use ARC-C to show that the BLMP-1 transcription factor mediates interactions between its targets. Investigating domain level architecture, we find that C. elegans chromatin domains defined by either active or repressive modifications form topologically associating domains (TADs) and that these domains interact to form A/B (active/inactive) compartment structure. ARC-C is a powerful new tool to interrogate genome architecture and regulatory interactions at high resolution.
2021-06-01 | GSE144671 | GEO
Project description:Interactions between cis-regulatory elements such as promoters and enhancers are important for transcription but global identification of these interactions remains a major challenge. Leveraging the chromatin accessiblity of regulatory elements, we developed ARC-C (accessible region chromosome conformation capture), which profiles chromatin regulatory interactions genome-wide at high resolution. Applying ARC-C to C. elegans, we identify ~15,000 significant interactions at 500bp resolution. Regions bound by transcription factors and chromatin regulators such as cohesin and condensin II are enriched for interactions, and we use ARC-C to show that the BLMP-1 transcription factor mediates interactions between its targets. Investigating domain level architecture, we find that C. elegans chromatin domains defined by either active or repressive modifications form topologically associating domains (TADs) and that these domains interact to form A/B (active/inactive) compartment structure. ARC-C is a powerful new tool to interrogate genome architecture and regulatory interactions at high resolution.
2021-06-01 | GSE144670 | GEO
Project description:Hundreds of thousands of candidate cis-regulatory elements (cCREs) have been identified across a myriad of cell types, but relatively few have been empirically characterized. Here, we present a scalable, phenotype-driven CRISPR screening method to test thousands of regulatory elements in parallel, by perturbing thousands of DNase hypersensitive sites (DHS) around hundreds of essential genes in K562. Integrating data from Cas9 exon-targeting with our CRISPRi screens, we nominate and validate promoters that regulate other nearby genes. Using higher-resolution CRISPR systems (dCas9 alone or Cas9) to tile across several essential enhancers, we resolve distinct peaks of activity and dissect core transcription factor binding sites (TFBSs) within enhancers, highlighting the advantages of complementary CRISPR systems to investigate CREs. Lastly, we use our tiling results to interrogate how TFBSs interact to drive enhancer function at the CBFA2T3 locus. This study demonstrates a scalable CRISPR screening framework for identifying and dissecting CREs that regulate cellular phenotypes.
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Project description:We report the genome-wide active regulatory elements in mouse dentate gyrus with or without presence of MBD1.
2018-05-15 | GSE99000 | GEO
Project description:The resolution limit of chromatin conformation capture methodologies (3Cs) has restrained their application in detection of fine-level chromatin structure mediated by cis-regulatory elements (CREs). Here we report two 3C-derived methods, Tri-4C and Tri-HiC, utilizing mult-restriction enzyme digestions capable of achieveing ultrafine genome digestion for targeted and global chromatin interaction mapping, respectively, at a one hundred basepair resolution. Tri-4C identified loops associated with CREs including those involving regulatory elements devoid of typical epigenomic marks, quantifatively revealing alterations in interaction networks underlying dynamic gene control. Tri-HiC successfully uncovers fine-gage enhancer:promoter (E:P) loops at genome-wide level, identifying > 20-fold more CRE loops than in situ HiC. In addition to refined loop detection, Tri-HiC also reveals interaction stripes and contact domain insulation from promoters and enhancers, revealing their loop extrusion behaviors resembling the topologically-associated domain (TAD) boundaries. Tri-4C and Tri-HiC provide robust approaches to achieve the high resolution interactome maps required for characterizing fine-gage regulatory chromatin interactions in analysis of development, homeostasis and disease.
2021-11-02 | GSE161014 | GEO
Project description:Histone acetylation H2BK20ac marks cell-state specific active regulatory elements
| PRJNA295265 | ENA
Project description:Transcriptional regulatory elements (TREs), including enhancers and promoters, determine the transcription levels of associated genes. We have recently shown that global run-on and sequencing (GRO-seq) with enrichment for 5'-capped RNAs reveals active TREs with high accuracy. Here, we demonstrate that active TREs can be identified by applying sensitive machine-learning methods to standard GRO-seq data. This approach allows TREs to be assayed together with gene expression levels and other transcriptional features in a single experiment. Our prediction method, called discriminative Regulatory Element detection from GRO-seq (dREG), summarizes GRO-seq read counts at multiple scales and uses support vector regression to identify active TREs. The predicted TREs are more strongly enriched for several marks of transcriptional activation, including eQTL, GWAS-associated SNPs, H3K27ac, and transcription factor binding than those identified by alternative functional assays. Using dREG, we survey TREs in eight human cell types and provide new insights into global patterns of TRE function. We analyzed GRO-seq or PRO-seq data from eight human cell lines. Please note that this study comprises new sample data plus reanalysis of old Sample data submitted by another user. Existing PRO-seq or GRO-seq data was combined as detailed in the GSE66031_readme.txt. See GSM1613181 and GSM1613182 Sample records for data processing information.
2015-02-19 | E-GEOD-66031 | biostudies-arrayexpress