Mus musculus
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA174285 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Robust 4C-seq data analysis to screen for regulatory DNA interactions
| PRJNA173815 | ENA
Project description:Regulatory DNA elements can control expression of distant genes via physical interactions. Here, we present a cost-effective methodology and computational analysis pipeline for robust characterization of the physical organization around selected promoters and other functional elements using Chromosome Conformation Capture combined with high-throughput sequencing (4C-seq) data. Our approach can be multiplexed and routinely integrated with other functional genomics assays to facilitate physical characterization of gene regulation. A high resolution 4C-seq protocol involving two restriction digests and a revised analysis pipeline was applied to several viewpoints in four genomic loci (the well-characterized alpha-globin and beta-globin loci, and the novel Oct4 and Satb1 loci), allowing robust detection of physical interactions between regulatory DNA elements.
2012-09-04 | E-GEOD-40420 | biostudies-arrayexpress
Project description:Regulatory DNA elements can control expression of distant genes via physical interactions. Here, we present a cost-effective methodology and computational analysis pipeline for robust characterization of the physical organization around selected promoters and other functional elements using Chromosome Conformation Capture combined with high-throughput sequencing (4C-seq) data. Our approach can be multiplexed and routinely integrated with other functional genomics assays to facilitate physical characterization of gene regulation.
2012-09-04 | GSE40420 | GEO
Project description:4C-Seq has proven to be a powerful technique to identify genome-wide interactions with a single locus of interest (or "bait") that can be important for gene regulation. However, analysis of 4C-Seq data is complicated by the many biases inherent to the technique. An important consideration when dealing with 4C-Seq data is the differences in resolution of signal across the genome that result from differences in 3D distance separation from the bait. This leads to the highest signal in the region immediately surrounding the bait and increasingly lower signals in far-cis and trans. Another important aspect of 4C-Seq experiments is the resolution, which is greatly influenced by the choice of restriction enzyme and the frequency at which it can cut the genome. Thus, it is important that a 4C-Seq analysis method is flexible enough to analyze data generated using different enzymes and to identify interactions across the entire genome. Current methods for 4C-Seq analysis only identify interactions in regions near the bait or in regions located in far-cis and trans, but no method comprehensively analyzes 4C signals of different length scales. In addition, some methods also fail in experiments where chromatin fragments are generated using frequent cutter restriction enzymes. Here, we describe 4C-ker, a Hidden-Markov Model based pipeline that identifies regions throughout the genome that interact with the 4C bait locus. In addition, we incorporate methods for the identification of differential interactions in multiple 4C-seq datasets collected from different genotypes or experimental conditions. Adaptive window sizes are used to correct for differences in signal coverage in near-bait regions, far-cis and trans chromosomes. Using several datasets, we demonstrate that 4C-ker outperforms all existing 4C-Seq pipelines in its ability to reproducibly identify interaction domains at all genomic ranges with different resolution enzymes. 4C-Seq experiments from Igh and Cd83 bait in activated B cells and Tcrb (Eb) bait in double negative T cells and immature B cells. RNA-Seq and ATAC-Seq experiments in DN and Immature B cells.
2016-02-27 | E-GEOD-77645 | biostudies-arrayexpress
Project description:fourSig: A Method for Determining Chromosomal Interactions in 4C-Seq Data
| PRJNA219332 | ENA
Project description:4C-Seq has proven to be a powerful technique to identify genome-wide interactions with a single locus of interest (or "bait") that can be important for gene regulation. However, analysis of 4C-Seq data is complicated by the many biases inherent to the technique. An important consideration when dealing with 4C-Seq data is the differences in resolution of signal across the genome that result from differences in 3D distance separation from the bait. This leads to the highest signal in the region immediately surrounding the bait and increasingly lower signals in far-cis and trans. Another important aspect of 4C-Seq experiments is the resolution, which is greatly influenced by the choice of restriction enzyme and the frequency at which it can cut the genome. Thus, it is important that a 4C-Seq analysis method is flexible enough to analyze data generated using different enzymes and to identify interactions across the entire genome. Current methods for 4C-Seq analysis only identify interactions in regions near the bait or in regions located in far-cis and trans, but no method comprehensively analyzes 4C signals of different length scales. In addition, some methods also fail in experiments where chromatin fragments are generated using frequent cutter restriction enzymes. Here, we describe 4C-ker, a Hidden-Markov Model based pipeline that identifies regions throughout the genome that interact with the 4C bait locus. In addition, we incorporate methods for the identification of differential interactions in multiple 4C-seq datasets collected from different genotypes or experimental conditions. Adaptive window sizes are used to correct for differences in signal coverage in near-bait regions, far-cis and trans chromosomes. Using several datasets, we demonstrate that 4C-ker outperforms all existing 4C-Seq pipelines in its ability to reproducibly identify interaction domains at all genomic ranges with different resolution enzymes.
2016-02-27 | GSE77645 | GEO
Project description:Artiodactyls display skeletal adaptations for cursorial (running) locomotion. In these animals, the distal limb skeleton is symmetric, which facilitates walking on the tips of the two central digits, while lateral digits are reduced or lost. We have identified that one primary molecular alteration during the formation of the bovine limb is that, in contrast to mouse, the posterior limb bud mesenchyme does not upregulate Ptch1 expression in response to SHH. We have tracked down this dissimilarity to a cis-regulatory SHH-responsive element that is functionally altered in bovine and established a causal link between lack of upregulation of Ptch1 and acquisition of a symmetric distal autopod. A high resolution 4C-seq protocol involving two restriction digests was applied to viewpoint in Ptch1 promoter (mm9 chr13:63,667,995-63,669,157) in three different tissues, allowing robust detection of physical interactions between regulatory DNA elements.
2014-06-19 | E-GEOD-52988 | biostudies-arrayexpress
Project description:4C-seq analysis of interactions with the Albumin promoter in mouse liver
| PRJNA399717 | ENA
Project description:Drosophila Insulator proteins mediate long-range chromosomal interactions. ChIP-seq revealed that binding of insulator proteins to some specific DNA sites was regulated by poly(ADP-ribosyl)ation in S2 cells. Three insulator sites regulated by poly(ADP-ribosyl)ation were used as baits to map their distant interacting sites using 4C assay in control S2 cells. Mapping the chromosomal interactions of three specific insulator binding sites with 4C assay in control S2 cells.
2013-09-15 | E-GEOD-50768 | biostudies-arrayexpress
Project description:4C-seq data was generated for regions of interest to confirm enhancer-gene promoter interactions
| EGAD00001001847 | EGA