Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Targeted in situ genome-wide profiling with high efficiency for low cell numbers

ABSTRACT: Cleavage Under Targets and Release Using Nuclease (CUT&RUN) is an epigenomic profiling strategy in which antibody-targeted controlled cleavage by micrococcal nuclease releases specific protein-DNA complexes into the supernatant for paired-end DNA sequencing. As only the targeted fragments enter into solution, and the vast majority of DNA is left behind, CUT&RUN has exceptionally low background levels. CUT&RUN outperforms the most widely- used Chromatin Immunoprecipitation (ChIP) protocols in resolution, signal-to-noise, and depth of sequencing required. In contrast to ChIP, CUT&RUN is free of solubility and DNA accessibility artifacts and has been used to profile insoluble chromatin and to detect long-range 3D contacts without cross-linking. Here we present an improved CUT&RUN protocol that does not require isolation of nuclei and provides high-quality data starting with only 100 cells for a histone modification and 1000 cells for a transcription factor. From cells to purified DNA CUT&RUN requires less than a day at the lab bench and requires no special skills.

ORGANISM(S): Homo sapiens

PROVIDER: GSE104550 | GEO | 2018/03/21

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Low-cost high-resolution chromatin profiling with CUT&Tag

Project description:We recently introduced CUT&Tag, an epigenomic profiling strategy in which antibodies are bound to chromatin proteins in situ in permeabilized nuclei, and then used to tether the cut-and-paste transposase Tn5. Activation of the transposase simultaneously cleaves DNA and adds DNA sequencing adapters (“tagmentation”) for paired-end DNA sequencing. Here, we introduce a streamlined CUT&Tag protocol that suppresses exposure artifacts to ensure high-fidelity mapping of the antibody-targeted protein and improves signal-to-noise over current chromatin profiling methods. Streamlined CUT&Tag can be performed in a single PCR tube from cells to amplified libraries, providing low-cost high-resolution genome-wide chromatin maps. By simplifying library preparation, CUT&Tag requires less than a day at the bench from live cells to sequencing-ready barcoded libraries. Because of low background levels, barcoded and pooled CUT&Tag libraries can be sequenced for ~$25 per sample, enabling routine genome-wide profiling of chromatin proteins and modifications that requires no special skills or equipment.

2020-07-15 | GSE145187 | GEO

The gene regulatory landscape of kidney organoid differentiation revealed by single nucleus multiomic analyses [CUT&RUN]

Project description:We performed cleavage under targets and release using nuclease (CUT&RUN) sequencing to characterize ATAC peaks identified by snATAC-seq.

2023-04-28 | GSE213150 | GEO

Identification of TFAP2A and MITF binding sites in the melanoma cell line SK-MEL-28

Project description:TFAP2A and MITF binding sites were identified in SK-MEL-28 cell lines using Cleavage Under Targets and Release Using Nuclease (CUT&RUN).

2021-02-08 | GSE153020 | 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

Chromatin conformation and histone modification profiling across human kidney anatomic regions [CUT&RUN]

Project description:Here, we leveraged our recently described high-yield nuclei extraction method and performed Hi-C and Cleavage Under Targets and Release Using Nuclease (CUT&RUN) sequencing of histone modifications (H3K4me3 and H3K27me3) in parallel on the kidney cortex, medulla and papilla samples dissected from the same donor. This site describes the CUT&RUN data.

2024-06-20 | GSE253630 | GEO

Low-input chromatin profiling in Arabidopsis endosperm using CUT&RUN

Project description:Endosperm is an essential seed tissue with a unique epigenetic landscape. During endosperm development, differential epigenetic regulation of the maternal and paternal genomes plays important roles in regulating gene expression, especially at imprinted genes. Profiling the endosperm epigenetic landscape on a genome-wide scale is challenging due to its small size, mode of development, and close association with maternal tissue. Here, we applied a low input chromatin profiling method, CUT&RUN (cleavage under targets and release using nuclease), to profile parental-specific chromatin modifications using low numbers of Arabidopsis endosperm nuclei. We demonstrate that CUT&RUN generates genome-wide H3K27me3 landscapes with high sensitivity, specificity and reproducibility using around 20,000 endosperm nuclei purified by flow cytometry and fluorescence-activated cell sorting. H3K27me3 peaks identified by CUT&RUN and previous ChIP (chromatin immunoprecipitation) approaches were largely overlapping, with some distinctions in heterochromatin. The versatility and simplicity of CUT&RUN makes it a viable alternative to ChIP, which requires greater amounts of starting material, and will enable the study of tissue or even cell-type specific epigenomes in Arabidopsis and other plant species.

2019-02-22 | GSE123602 | 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

Areas of H3K27 tri-methylation in CD8+ T cells from the spleens of LCMV-Armstrong or LCMV-Clone 13 infected mice

Project description:The profiles of H3K27 tri-methylation in CD8+ T cells from LCMV-Armstrong and LCMV-Clone 13 infected mice are known to be distinct from one another. We used CUT&RUN (Cleavage Under Targets and Release Using Nuclease) to analyze these differences in splenic CD8+ T cells of these two infection conditions.

2023-01-04 | GSE213467 | GEO

Chromatin conformation and histone modification profiling across human kidney anatomic regions [Hi-C]

2024-06-20 | GSE253632 | GEO

Integrative Low-input Transcriptomic and Cistromic Analyses Identify CREB Target Genes in Cystic Epithelial Cells [RNA-Seq]

Project description:Transcription factors (TFs) play crucial roles in kidney development and disease by recognizing specific DNA sequences to control gene expression programs. The kidney’s cellular heterogeneity poses substantial challenges to identifying the genomic binding sites and direct target genes of TFs in vivo. We apply the CUT&RUN (cleavage under targets and release using nuclease) technique, together with transcriptomic analysis, to identify cAMP-response element-binding protein (CREB) target genes in cystic epithelial cells of autosomal dominant polycystic kidney disease (ADPKD). Our results reveal that CREB binds to and activates ribosomal biogenesis genes, and that inhibition of CREB retards cyst growth in ADPKD mouse models. Our findings demonstrate that CUT&RUN is a powerful method for genome-scale profiling and identifying direct targets of TFs from small numbers of specific kidney cells.

2022-01-01 | GSE165417 | 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