Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Automated in situ profiling of chromatin modifications resolves cell types and gene regulatory programs

ABSTRACT: Our understanding of eukaryotic gene regulation is limited by the complexity of protein-DNA interactions that comprise the chromatin landscape and inefficient methods for characterizing these interactions. We recently introduced CUT&RUN, an antibody-targeted method that profiles DNA-binding proteins, histones and chromatin modifying proteins with high sensitivity and resolution. Here we describe an automated CUT&RUN platform and apply it to profile the chromatin landscapes of human cell lines. We develop a metric to quantitatively compare chromatin features between cell types and identify their distinctive gene expression programs. Finally, we use this method to identify gene expression features of two different pediatric diffuse midline gliomas using frozen tissue from patient-derived xenografts. Our easy, cost-effective workflow makes automated CUT&RUN an attractive tool for high-throughput characterization of cell types and patient samples.

ORGANISM(S): Homo sapiens

PROVIDER: GSE120011 | GEO | 2018/12/22

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Automated CUT&Tag profiling of chromatin heterogeneity in mixed-lineage leukemia

Project description:Acute myeloid and lymphoid leukemias often harbor chromosomal translocations involving the Mixed Lineage Leukemia-1 gene, which encodes the KMT2A lysine methyltransferase. The most common translocations produce in-frame fusions of KMT2A to trans-activation domains of chromatin regulatory proteins. Here we develop a strategy to map the genome-wide occupancy of oncogenic KMT2A fusion proteins in primary patient samples regardless of fusion partner. By modifying the versatile CUT&Tag method for full automation we identify common and tumor-specific patterns of aberrant chromatin regulation induced by different KMT2A fusion proteins. Integration of automated and single-cell CUT&Tag uncovers lineage heterogeneity within patient samples and provides an attractive avenue for future diagnostics.

2021-06-10 | GSE159608 | GEO

AutoRELACS: Automated Generation And Analysis of Ultra-parallel ChIP-seq

Project description:We present AutoRELACS, an automated implementation of the RELACS protocol using the Biomek i7 automated workstation (Beckman&Coulter). We test the performance of AutoRELACS by assessing 1) the scalability of the chromatin barcode integration step, 2) the quality of the generated data in comparison to the benchmark set by the manual protocol, and 3) the sensitivity of the automated method when working with low (≤ 25.000 cells/sample) and very low (≤ 5.000 cells/sample) cell numbers.

2020-07-28 | GSE147042 | GEO

Identification of chromatin states during zebrafish gastrulation using CUT&RUN and CUT&Tag

Project description:Here we describe successful implementation of CUT&RUN for profiling protein-DNA interactions in zebrafish embryos. We apply modified a CUT&RUN method to generate high resolution maps of enrichment for H3K4me3, H3K27me3, H3K9me3, and RNA polymerase II during zebrafish gastrulation. Using this data, we identify a conserved subset of developmental genes that are enriched in both H3K4me3 and H3K27me3 during gastrulation, and we demonstrate the increased effectiveness of CUT&RUN for detecting protein enrichment at repetitive sequences with reduced mappability. Our work demonstrates the power of combining CUT&RUN with the strengths of the zebrafish system to better understand the changing embryonic chromatin landscape and its roles in shaping development.

2021-06-17 | GSE178343 | GEO

Genome-wide profiling of transcription factor-DNA binding interactions in Candida albicans: a comprehensive CUT&RUN method and data analysis workflow

Project description:Regulatory transcription factors control many important biological processes including cellular differentiation, responses to environmental perturbations and stresses, and host-pathogen interactions. Determining the genome-wide binding of regulatory transcription factors to DNA is essential to understanding the function of transcription factors in these often complex biological processes. Cleavage Under Targets and Release Using Nuclease (CUT&RUN) is a modern method for genome-wide mapping of in vivo protein-DNA binding interactions that is an attractive alternative to the traditional and widely used chromatin immunoprecipitation followed by sequencing (ChIP-seq) method. CUT&RUN is amenable to a higher throughput experimental setup and has a substantially higher dynamic range with lower per-sample sequencing costs compared to ChIP-seq. Here, we describe a comprehensive CUT&RUN protocol and accompanying data analysis workflow that is tailored for genome-wide analysis of transcription factor-DNA binding interactions in the human fungal pathogen Candida albicans. This detailed protocol describes all necessary experimental procedures, from epitope tagging of transcription factor coding genes, to library preparation for sequencing; additionally, it includes our customized computational workflow for CUT&RUN data analysis.

2022-07-15 | GSE193803 | GEO

Automated CUT&Tag profiling of chromatin heterogeneity in mixed-lineage leukemia

Project description:Automated CUT&Tag profiling of chromatin heterogeneity in mixed-lineage leukemia

| PRJNA669859 | ENA

Cut-and-Run in situ factor profiling maps DNA binding and 3D contact sites at high resolution

Project description:Unlike Chromatin Immunoprecipitation (ChIP), which fragments and solubilizes total chromatin, Cut-and-Run is performed in situ, allowing for both high-resolution chromatin mapping and probing of the local chromatin environment. When applied to yeast and human nuclei, Cut-and-Run yielded precise transcription factor profiles while avoiding cross-linking and solubilization issues. Cut-and-Run is simple to perform and at low temperatures is inherently robust, with extremely low backgrounds that make it especially cost-effective for transcription factor and chromatin profiling. When used in conjunction with native ChIP-seq and applied to human CTCF, Cut-and-Run mapped high-resolution 3D directional interactions. We conclude that Cut- and-Run is a suitable complement or replacement for ChIP-seq that can also provide 3D mapping information.

2016-12-30 | GSE84474 | GEO

Epigenomic profiling of H3K9me3 in the absence and presence of Periphilin variants

Project description:Targeted epigenomic profiling method CUT&RUN was used to examine PPHLN-regulated H3K9me3 deposition on chromatin.

2020-08-07 | GSE155824 | GEO

A streamlined protocol and analysis pipeline for CUT&RUN chromatin profiling

Project description:Over the past two decades, the dominant technology for chromatin profiling has been chromatin immunoprecipitation (ChIP), in which cellular components are solubilized to fragment chromatin, and an antibody is added to precipitate a DNA/protein complex of interest. We previously described a novel alternative to ChIP, Cleavage Under Targets & Release Using Nuclease (CUT&RUN), in which the antibody is added to permeabilized cells followed by binding of a Protein A-Micrococcal Nuclease (pA/MNase) fusion protein to the antibody (PMID 29651053). Upon activation of tethered MNase, the bound complex is excised and released into the supernatant for DNA extraction and sequencing. Here we introduce four extensions to CUT&RUN: 1) a hybrid Protein A-Protein G-MNase construct that allows simplified purification using a commercial kit; 2) a modified digestion protocol that prevents release of the enzyme and so minimizes artifactual cleavage of accessible DNA; 3) a calibration strategy based on carryover of E. coli DNA introduced with the fusion protein; and 4) a novel peak-calling strategy that is customized for the low-background profiles obtained using CUT&RUN. These new features, coupled with the previously described low-cost, high efficiency, high reproducibility and high-throughput capability of CUT&RUN make it the method of choice for routine epigenomic profiling.

2019-06-24 | GSE126612 | GEO

Deep sequencing and automated histochemistry of human tissue slice cultures improve their usability as preclinical model for cancer research

Project description:Cancer research requires models closely resembling the tumor in the patient. Human tissue cultures can overcome interspecies limitations of animal models or the loss of tissue architecture in in vitro models. However, analysis of tissue slices is often limited to histology. Here, we demonstrate that slices are also suitable for whole transcriptome sequencing and present a method for automated histochemistry of whole slices. Tumor and peritumoral tissue from a patient with glioblastoma was processed to slice cultures, which were treated with standard therapy including temozolomide and X-irradiation. Then, RNA sequencing and automated histochemistry was performed. RNA sequencing was successfully performed with a sequencing depth of 243 to 368 x 106 reads per sample. Comparing tumor and peritumoral tissue, we identified 1888 genes significantly downregulated and 2382 genes upregulated in tumor. Treatment significantly downregulated 2017 genes, whereas 1399 genes were upregulated. Pathway analysis revealed changes in the expression profile of treated glioblastoma tissue pointing towards downregulated proliferation. This was confirmed by automated analysis of whole tissue slices stained for Ki67. In conclusion, we demonstrate that RNA sequencing of tissue slices is possible and that histochemical analysis of whole tissue slices can be automated which increases the usability of this preclinical model.

2020-02-04 | GSE119102 | GEO

Automated high-throughput chromatin immunoprecipitation

Project description:The submitted files contain ChIP-seq data for the p300 transcriptional coactivator in GM12878 cells and for the NRSF transcription factor in GM12878 and Jurkat cells generated using a fully automated robotic chromatin immunoprecipitation protocol. Cells were fixed using 1% formaldehyde (NRSF samples) or 1% formaldehyde at 37C (p300 samples).

2014-06-01 | GSE53366 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data