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

PROVIDER: PRJNA491336 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR7849900_1.fastq.gz	Fastqsanger.gz
	SRR7849900_2.fastq.gz	Fastqsanger.gz
	SRR7849910_1.fastq.gz	Fastqsanger.gz
	SRR7849910_2.fastq.gz	Fastqsanger.gz
	SRR7849920_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 130

Similar Datasets

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

Project description: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.

2018-12-22 | GSE120011 | GEO

Automated in situ chromatin profiling efficiently resolves cell types and gene regulatory programs.

Project description:BackgroundOur understanding of eukaryotic gene regulation is limited by the complexity of protein-DNA interactions that comprise the chromatin landscape and by inefficient methods for characterizing these interactions. We recently introduced CUT&RUN, an antibody-targeted nuclease cleavage method that profiles DNA-binding proteins, histones and chromatin-modifying proteins in situ with exceptional sensitivity and resolution.ResultsHere, we describe an automated CUT&RUN platform and apply it to characterize the chromatin landscapes of human cells. We find that automated CUT&RUN profiles of histone modifications crisply demarcate active and repressed chromatin regions, and we develop a continuous metric to identify cell-type-specific promoter and enhancer activities. We test the ability of automated CUT&RUN to profile frozen tumor samples and find that our method readily distinguishes two pediatric glioma xenografts by their subtype-specific gene expression programs.ConclusionsThe easy, cost-effective workflow makes automated CUT&RUN an attractive tool for high-throughput characterization of cell types and patient samples.

| S-EPMC6302505 | biostudies-literature

Microfluidic low-input fluidized-bed enabled ChIP-seq device for automated and parallel analysis of histone modifications

Project description:Genome-wide epigenetic changes such as histone modifications form a critical layer of gene regulations and have been implicated in a number of different disorders such as cancer and inflammation. Progress has made to decrease the input required for gold-standard genome-wide profiling tools like chromatin immunoprecipitation followed by next generation sequencing (i.e. ChIP-seq) to allow scarce primary tissues of specific type from patients and lab animals to be tested. However, there has been very little effort to rapidly increase the throughput of these low-input tools. In this report, we demonstrate LIFE-ChIP-seq (Low-Input Fluidized-bed Enabled Chromatin Immunoprecipitation combined with sequencing), an automated and high-throughput microfluidic platform capable of running multiple sets of ChIP assays in as little as 1 h with as few as 50 cells per assay. Our technology will enable testing of a large number of samples and replicates with low-abundance primary samples in the context of precision medicine.

2018-06-01 | GSE102932 | 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

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

Automated DNA metabarcoding

Project description:Standardized high-throughput biomonitoring using DNA metabarcoding: Strategies for the adoption of automated liquid handlers

| PRJEB45792 | ENA

An Automated Online Platform for Phosphoproteome Profiling

Project description:An Automated Online Platform for Phosphoproteome Profiling

2021-12-27 | PXD030655 |

Automated array-CGH optimized for archival formalin-fixed, paraffin-embedded tumor material

Project description:BACKGROUND: Array Comparative Genomic Hybridization (aCGH) is a rapidly evolving technology that still lacks complete standardization. Yet, it is of great importance to obtain robust and reproducible data to enable meaningful multiple hybridization comparisons. Special difficulties arise when aCGH is performed on archival formalin-fixed, paraffin-embedded (FFPE) tissue due to its variable DNA quality. Recently, we have developed an effective DNA quality test that predicts suitability of archival samples for BAC aCGH. METHODS: In this report, we first used DNA from a cancer cell-line (SKBR3) to optimize the aCGH protocol for automated hybridization, and subsequently optimized and validated the procedure for FFPE breast cancer samples. We aimed for highest throughput, accuracy, and reproducibility applicable to FFPE samples, which can also be important in future diagnostic use. RESULTS: Our protocol of automated array-CGH on archival FFPE ULS-labeled DNA showed very similar results compared with published data and our previous manual hybridization method. CONCLUSION: This report combines automated aCGH on unamplified archival FFPE DNA using non-enzymatic ULS labeling, and describes an optimized protocol for this combination resulting in improved quality and reproducibility. In this study, we optimized the BAC araay-CGH protocol for automated hybridization for FFPE breast cancer samples. We have tested hybridization temperature and duration, different hybridization buffer conditions, and post-hybridization washing.

2010-06-12 | E-GEOD-7122 | biostudies-arrayexpress

Automated array-CGH optimized for archival formalin-fixed, paraffin-embedded tumor material

2007-02-23 | GSE7122 | GEO

Automated proteomics workflows for consistent library generation and label-free protein quantitation in 96-well format and across different samples types

Project description:Automated workflows for high-throughput library generation and biomarker detection using data-independent acquisition

2023-04-22 | PXD038413 | Pride