Alignment and quantification of ChIP-exo crosslinking patterns reveal the spatial organization of protein-DNA complexes
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA591557 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR10528328_1.fastq.gz | Fastqsanger.gz | |||
| SRR10528328_2.fastq.gz | Fastqsanger.gz | |||
| SRR10528329_1.fastq.gz | Fastqsanger.gz | |||
| SRR10528329_2.fastq.gz | Fastqsanger.gz | |||
| SRR10528330_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 30 |
Similar Datasets
Project description:Each protein within a regulatory complex associates with the genome by either binding DNA directly or by forming protein-protein interactions with DNA-bound proteins. In the chromatin immunoprecipitation (ChIP) assay, each protein’s unique mode of genomic association may be reflected by their patterns of formaldehyde-induced crosslinks to the DNA sequences that are in very close proximity. The ChIP-exo protocol precisely delineates protein-DNA crosslinking patterns by combining ChIP with 5' to 3' exonuclease digestion. Within a regulatory complex, the physical distance of a regulatory protein to the DNA affects crosslinking efficiencies. Therefore, the spatial organization of a protein-DNA complex could potentially be inferred by analyzing how crosslinking signatures vary between the subunits of a regulatory complex, and how they remain consistent over a set of coordinately regulated regions. Here, we present a computational framework that aligns ChIP-exo crosslinking patterns from multiple proteins across a set of regulatory regions, and which detects and quantifies protein-DNA crosslinking events within the aligned profiles. Our gapped multiple profile alignment approach does not rely on sequence motif features, but rather operates directly on the multi-protein, strand separated ChIP-exo tag patterns. The output of the alignment approach is a set of composite profiles that represent the crosslinking signatures of the complex across analyzed regulatory regions. We then use a probabilistic mixture model to deconvolve individual crosslinking events within the aligned ChIP-exo profiles, enabling consistent measurements of protein-DNA crosslinking strengths across multiple proteins. Lastly, we apply dimensionality reduction to visualize the relative organization of proteins within the regulatory complex. We demonstrate our approach by applying it to characterize regulatory complex organization in three biological settings. Firstly, we demonstrate that our alignment approach can recover the known organization of regulatory proteins at yeast ribosomal protein genes, without relying on any DNA sequence features. Secondly, we apply our gapped alignment and crosslinking quantification approaches to a novel set of ChIP-exo data to characterize the spatial organization of Pol III transcriptional machinery assembly at yeast tRNA genes. Finally, we demonstrate that our approach can be used to quantify changes in protein-DNA complex organization when applied to ChIP-nexus data from Drosophila Pol II transcriptional components in two experimental conditions. Our results suggest that principled analyses of ChIP-exo crosslinking patterns enable inference of spatial organization within protein-DNA complexes.
2019-12-08 | GSE140923 | GEO
Project description:The ChIP-exo assay precisely delineates protein-DNA crosslinking patterns by combining chromatin immunoprecipitation with 5' to 3' exonuclease digestion. Within a regulatory complex, the physical distance of a regulatory protein to DNA affects crosslinking efficiencies. Therefore, the spatial organization of a protein-DNA complex could potentially be inferred by analyzing how crosslinking signatures vary between its subunits. Here, we present a computational framework that aligns ChIP-exo crosslinking patterns from multiple proteins across a set of coordinately bound regulatory regions, and which detects and quantifies protein-DNA crosslinking events within the aligned profiles. By producing consistent measurements of protein-DNA crosslinking strengths across multiple proteins, our approach enables characterization of relative spatial organization within a regulatory complex. Applying our approach to collections of ChIP-exo data, we demonstrate that it can recover aspects of regulatory complex spatial organization at yeast ribosomal protein genes and yeast tRNA genes. We also demonstrate the ability to quantify changes in protein-DNA complex organization across conditions by applying our approach to analyze Drosophila Pol II transcriptional components. Our results suggest that principled analyses of ChIP-exo crosslinking patterns enable inference of spatial organization within protein-DNA complexes.
| S-EPMC7672471 | biostudies-literature
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.
2018-02-13 | GSE110502 | GEO
Project description:Dynamic conformational and structural changes in proteins and protein complexes play a central and ubiquitous role in the regulation of protein function, yet it is very challenging to study these changes, especially for large protein complexes, under physiological conditions. Here we introduce a novel isobaric crosslinker, Qlinker, for studying conformational and structural changes in proteins and protein complexes using quantitative crosslinking mass spectrometry (qCLMS). Qlinkers are small and simple, amine-reactive molecules with an optimal extended distance of ~10 Å which use MS2 reporter ions for relative quantification of Qlinker-modified peptides derived from different samples. We synthesized the 2-plex Q2linker and showed that the Q2linker can provide quantitative crosslinking data that pinpoints key conformational and structural changes in biosensors, binary and ternary complexes composed of the general transcription factors TBP, TFIIA, and TFIIB, and RNA polymerase II (pol II) complexes.
2024-11-13 | PXD056825 | Pride
Project description:XL-MS of RAGE oligomeric complexes. The Crosslinking agent is BS3. Samples were subjected to sequential digestion. 91212_AM_1_3_1_HCDFT, 91212_AM_1_3_2_HCDFT, 91212_AM_4_3_1_HCDFT, 91212_AM_4_3_2_HCDFT - Tryp-Gluc;
91212_AM_1_2_1_HCDFT, 91212_AM_1_2_2_HCDFT, 91212_AM_4_2_1_HCDFT, 91212_AM_4_2_2_HCDFT - Tryp-Chym;
91212_AM_1_1_1_HCDFT, 91212_AM_1_1_2_HCDFT, 91212_AM_4_1_1_HCDFT, 91212_AM_4_1_2_HCDFT - Tryp-Tryp.
2020-11-11 | MSV000086438 | MassIVE
Project description:A novel assay based on proximity ligation assay for high-throughput quantification of proteins, protein complexes and mRNA in single cells Here we present proximity-sequencing (Prox-seq), a method for simultaneous measurement of an individual cell’s proteins, protein complexes and mRNA. Prox-seq utilizes deep sequencing and barcoded proximity assays to measure proteins and their complexes from all pairwise combinations of targeted proteins, without any prior knowledge of which proteins can form complexes. The number of measured protein complexes scales quadratically with the number of targeted proteins, allowing for unparalleled multiplexing capacity. We developed a high-throughput experimental and computational pipeline and demonstrated the potential of Prox-Seq for multi-omic analysis with a panel of 13 proximity probes, enabling the measurement of 91 protein complexes, along with thousands of mRNA molecules in single T cells and B cells. Prox-seq is compatible with current single-cell RNA sequencing assays, such as Drop-seq and Smart-seq2. Prox-seq provides access to an untapped yet powerful measurement modality for single-cell phenotyping and has the potential to discover new protein interactions in single-cells.
2020-05-16 | GSE149574 | GEO
Project description:The emerging evidences support that exosome cargo miRNAs function as important regulators in cell differentiation. Therefore, in order to figure out the mechanism that Exo-AT mediated adipogenesis, we profiled miRNAs in Exo-AT using high-throughput sequencing (miRNA-seq). After trimming low-quality reads, contaminants, adaptors, and reads smaller than 15 nt, the remaining reads were mapped to merged pre-miRNA data bases. To identify the conserved miRNAs in Exo exosomes, miRNAs were aligned to miRBase v21. 148 and 154 types of known miRNAs in Exo-ADSCs and Exo-AT, respectively, were identified in the two replicates. Among these miRNAs, 103 miRNAs were simultaneously detected in both Exo-ADSCs and Exo-AT. Compared to Exo-ADSCs, 45 conserved miRNAs were enriched (expressed ≥ 2 folds, FDR<0.05) in Exo-AT. KEGG Pathway analysis was performed for the targets of the most 20 enriched miRNAs in Exo-AT (compared with Exo-ADSCs) to determine their potential function. Data showed that pathways that regulate adipogenesis such as Wnt signaling pathway, Insulin signaling pathway, MAPK signaling pathway, TGF-ß signaling pathway were enriched significantly for targets of Exo-AT miRNAs. Furthermore, 14 of 45 enriched miRNAs in Exo-AT (31.11%, such as miR-30a-5p, miR-148a-3p) were reported to participate in regulation of adipogenesis while 8 miRNAs (17.78%, such as miR-93-5p, miR-150-3p) that negatively control osteoblastic differentiation of MSC have been described.
2018-12-01 | GSE92313 | GEO
Project description:miRNA array experiment of NC-Exo and GATA4-Exo
| PRJNA592052 | ENA
Project description:To explore the possibility of miRNA(s) contributing to the cardioprotection induced by plasma exosomes at the late phase of RIPC, we performed a miRNA profiling assay (763 rat miRNAs) comparing the differences between RIPC-exo and Control-exo using Illumina HiSeq 2500 high-throughput sequencing.
2021-12-23 | GSE182675 | GEO
Project description:RNA-seq read alignment evaluation
| PRJEB4265 | ENA