Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA316190 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR3289640.fastq.gz | Fastqsanger.gz | |||
| SRR3289641.fastq.gz | Fastqsanger.gz | |||
| SRR3289642.fastq.gz | Fastqsanger.gz | |||
| SRR3289643.fastq.gz | Fastqsanger.gz | |||
| SRR3289644.fastq.gz | Fastqsanger.gz |
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Project description:Input Strategy for Improving Analysis of ChIP-exo Data and Beyond
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Project description:Input Strategy for Improving Analysis of ChIP-exo Data and Beyond [RNA-Seq]
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Project description:Recently, a number of advances have been implemented into the core ChIP-seq (chromatin immunoprecipitation coupled with next-generation sequencing) methodology to streamline the process, reduce costs or improve data resolution. Several of these emerging ChIP-based methods perform additional chemical steps on bead-bound immunoprecipitated chromatin, posing a challenge for generating similarly treated input controls required for artifact removal during bioinformatics analyses. Here we present a versatile method for producing technique-specific input controls for ChIP-based methods that utilize additional bead-bound processing steps. This reported method, termed protein attached chromatin capture (PAtCh-Cap), relies on the non-specific capture of chromatin-bound proteins via their carboxylate groups, leaving the DNA accessible for subsequent chemical treatments in parallel with chromatin separately immunoprecipitated for the target protein. Application of this input strategy not only significantly enhanced artifact removal from ChIP-exo data, increasing confidence in peak identification and allowing for de novo motif searching, but also afforded discovery of a novel CTCF binding motif.
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Project description:Several recently emerging ChIP-seq (chromatin immunoprecipitation followed by sequencing) based methods perform chemical steps on bead-bound immunoprecipitated chromatin, posing a challenge for generating similarly treated input controls required for bioinformatics and data quality analyses. Here we present a versatile method for producing technique-specific input controls for ChIP-based methods that utilize additional bead-bound processing steps. Application of this method allowed for discovery of a novel CTCF binding motif from ChIP-exo data.
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Project description:RNA aliquots were digested with 5’-phosphate-dependent exonuclease (5'-exo) following pre-treatment with tobacco acid pyrophosphatase (TAP) to release the 5’ cap and render the RNA susceptible to 5’ exonuclease digestion (TAP+/5'-exo+). Two color array hybridizations were performed and TAP+/5'-exo+ samples were compared with TAP-/5'-exo+ control samples. Two-condition experiment, TAP+/5'-exo+ vs. TAP-/5'-exo+ treated total RNA samples. Biological replicates: 4 with dye swap
2015-06-30 | E-GEOD-62984 | biostudies-arrayexpress
Project description:RNA aliquots were digested with 5’-phosphate-dependent exonuclease (5'-exo) following pre-treatment with tobacco acid pyrophosphatase (TAP) to release the 5’ cap and render the RNA susceptible to 5’ exonuclease digestion (TAP+/5'-exo+). Two color array hybridizations were performed and TAP+/5'-exo+ samples were compared with TAP-/5'-exo+ control samples.
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Project description:We performed an RNA pulldown against a methyl group on the mRNA cap using a fusion protein, GST-eIF4E, highly specific for a m7G-mRNA cap. We performed RNA-seq on both the pulldowns and inputs and normalized our pulldown to input in order to determine which genes MYC targets for mRNA cap methylation above and beyond any affect at the transcriptional level. We found that MYC targets approximately 30% of transcripts for enhanced mRNA cap methylation above 1.2 fold on a global scale following 24 h of MYC induction, specifically transcripts involved in the canonical Wnt/β-catenin signaling pathway. We used this dataset to validate transcripts targeted by MYC for mRNA cap methylation and to help us determine the mechanism responsible for this phenomenon.
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Project description:The human K562 chronic myeloid leukemia cell line has long served as an experimental paradigm for functional genomic studies. To systematically and functionally annotate the human genome, the ENCODE consortium generated hundreds of functional genomic data sets, such as ChIP-seq. While ChIP-seq analyses have provided tremendous insights into gene regulation, spatiotemporal insights were limited by a resolution of several hundred base pairs. ChIP-exonuclease (ChIP-exo) is a refined version of ChIP-seq that overcomes this limitation by providing higher precision mapping of protein-DNA interactions. To study the interplay of transcription initiation and chromatin, we profiled the genome-wide locations for RNA-polymerase II (Pol II), the histone variant H2A.Z, and the histone modification H3K4me3 using ChIP-seq and ChIP-exo.
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Project description:Regulatory proteins associate with the genome either by directly binding cognate DNA motifs or via protein-protein interactions with other regulators. Each genomic recruitment mechanism may be associated with distinct motifs, and may also result in distinct characteristic patterns in high-resolution protein-DNA binding assays. For example, the ChIP-exo protocol precisely characterizes protein-DNA crosslinking patterns by combining chromatin immunoprecipitation (ChIP) with 5’ to 3’ exonuclease digestion. Since different regulatory complexes will result in different protein-DNA crosslinking signatures, analysis of ChIP-exo sequencing tag patterns should enable detection of multiple protein-DNA binding modes for a given regulatory protein. However, current ChIP-exo analysis methods either treat all binding events as being of a uniform type, or rely on the presence of DNA motifs to cluster binding events into subtypes. To systematically detect multiple protein-DNA interaction modes in a single ChIP-exo experiment, we introduce the ChIP-exo mixture model (ChExMix). ChExMix probabilistically models the genomic locations and subtype membership of protein-DNA binding events using both ChIP-exo tag enrichment patterns and DNA sequence information, thus offering a principled and robust approach to characterizing binding subtypes in ChIP-exo data. We demonstrate that ChExMix achieves accurate detection and classification of binding event subtypes using in silico mixed ChIP-exo data. We further demonstrate the unique analysis abilities of ChExMix using a collection of ChIP-exo experiments that profile the binding of key transcription factors in MCF-7 cells. In these data, ChExMix detects cooperative binding interactions between FoxA1, ERalpha, and CTCF, thus demonstrating that ChExMix can effectively stratify ChIP-exo binding events into biologically meaningful subtypes.
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