Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14400530_1.fastq.gz | Fastqsanger.gz | |||
| SRR14400530_2.fastq.gz | Fastqsanger.gz | |||
| SRR14400531_1.fastq.gz | Fastqsanger.gz | |||
| SRR14400531_2.fastq.gz | Fastqsanger.gz | |||
| SRR14400532_1.fastq.gz | Fastqsanger.gz |
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Similar Datasets
Project description:In order to determine that CUT&Tag is similar to known DUX ChIP-seq, we performed CUT&Tag with a mCherry-tagged DUX (with the mCherry antibody). Once confirmed, we pewrformed CUT&Tag for other DUX derivatives with their mCherry tag Then, we performed CUT&Tag for H3K9ac, which is known to globally increase in 2-cell-like cells, which occurs after DUX expression, and CUT&Tag for SMARCC1, a subunit of the SWI/SNF complex
2023-08-07 | GSE224297 | GEO
Project description:Chromatin-protein interactions are fundamental for the regulation of gene transcription. While ChIP-seq has long been the standard method for mapping these interactions, emerging techniques such as CUT&RUN and CUT&Tag, which offer advantages including low input requirements and high signal-to-noise ratios, have garnered attention. However, these enzyme-based tagmentation approaches may introduce potential biases, and comparative assessment with ChIP-seq remain absent. This study aims to systematically evaluate and compare the performance of ChIP-seq, CUT&Tag, and CUT&RUN for profiling genome-wide transcription factors and histone modifications binding. This study provides a comprehensive evaluation of ChIP-seq, CUT&Tag, and CUT&RUN for detecting active and repressive histone modifications as well as transcription factor binding. Our results show that all three methods reliably detect histone modifications and transcription factor enrichment, with CUT&Tag demonstrating a relatively higher signal-to-noise ratio. Rigorous peak comparison analysis identified differential enrichment sites detected by the three methods. Additionally, we observed a notable correlation between CUT&Tag signal intensity and chromatin accessibility, suggesting the potential for CUT&Tag to detect regions of active chromatin.
2025-05-13 | GSE286751 | GEO
Project description:We developed scNanoSeq-CUT&Tag, a streamlined method by adapting a modified CUT&Tag protocol to Oxford Nanopore sequencing platform for efficient chromatin modification profiling at single-cell resolution. We firstly tested the performance of scNanoSeq-CUT&Tag on six human cell lines: K562, 293T, GM12878, HG002, H9, HFF1 and adult mouse blood cells, it showed that scNanoSeq-CUT&Tag can accurately distinguish different cell types in vitro and in vivo. Moreover, scNanoSeq-CUT&Tag enables to effectively map the allele-specific epigenomic modifications in the human genome andallows to analyze co-occupancy of histone modifications. Taking advantage of long-read sequencing,scNanoSeq-CUT&Tag can sensitively detect epigenomic state of repetitive elements. In addition, by applying scNanoSeq-CUT&Tag to testicular cells of adult mouse B6D2F1, we demonstrated that scNanoSeq-CUT&Tag maps dynamic epigenetic state changes during mouse spermatogenesis. Finally, we exploited the epigenetic changes of human leukemia cell line K562 during DNA demethylation, it showed that NanoSeq-CUT&Tag can capture H3K27ac signals changes along DNA demethylation. Overall, we prove that scNanoSeq-CUT&Tag is a valuable tool for efficiently probing chromatin state changes within individual cells.
2024-09-06 | GSE249799 | GEO
Project description:We comprehensively benchmarked CUT&Tag for H3K27ac and H3K27me3 against published ChIP-seq profiles from ENCODE in K562 cells. Combining multiple new and published CUT&Tag datasets, there was an average recall of 54% known ENCODE peaks for both histone modifications. To optimize data analysis steps, we tested peak callers MACS2 and SEACR and identified optimal peak calling parameters. Considering both precision and recall of known ENCODE peaks, the peak callers were comparable in their performance, although peaks produced by MACS2 match ENCODE peak width distributions more closely. We found that reducing PCR cycles during library preparation lowered duplication rates at the expense of ENCODE peak recovery. Despite the moderate ENCODE peak recovery, peaks identified by CUT&Tag represent the strongest ENCODE peaks and show the same functional and biological enrichments as ChIP-seq peaks identified by ENCODE. Our workflow systematically evaluates the merits of methodological adjustments, providing a benchmarking framework for the experimental design and analysis of CUT&Tag studies, and will facilitate future efforts to apply CUT&Tag in human tissues and single cells.
2025-01-14 | GSE286492 | GEO
Project description:This study aimed to adapt CUT&Tag to Plasmodium falciparum samples as an efficient and sensitive alternative to classical ChIP-sequencing. We compare H3K9me3 and HP1 CUT&Tag with ChIP-seq datasets, showing successful establishment of CUT&Tag in P. falciparum. Next we aimed to scale down required input material for our CUT&Tag reactions and generated high-quality HP1 tracks with as little as 10.000 nuclei. To minimise potential sample loss we tested feasibility of utilising (frozen) saponin parasite isolates as input material instead of nuclei, which proved to be viable. Lastly, we deployed our new technique Dimerisation-induced Biotinylation-CUT&Tag (DiBioCUT&Tag) to catch transient interactions by biotinylation of strongly associated proteins such as histones. We tested this technique on HP1 and compared standart CUT&Tag with DiBioCUT&Tag. Furthermore, we explored interactions of the transcription factor BDP5, which we were previously unable to succesfully ChIP.
2024-06-27 | GSE270104 | GEO
Project description:To understand the mechanistic insights on how KDM1A inhibition sensitizes glioblastoma (GBM) to temozolomide, we performed genome wide localization studies of KDM1A in patient derived glioma stem cells (GSCs) using CUT&Tag-seq. GSC082209 (GSC08) cells were treated with vehicle or NCD38 (5 μM) for 24 h and 250,000 cells per condition were used. Data analysis on CUT&Tag sequencing reads was performed by the nf-core/cutandrun bioinformatic analysis pipeline. We detected 75,491 KDM1A peaks in the genome of GSCs (p<0.0001). Pathway analysis of KDM1A binding genes using Gene Ontology showed KDM1A binding genes were enriched in DNA repair, cell cycle, and UPR signaling pathways . CUT&Tag sequencing for KDM1A in patient derived glioma stem cells.
2023-02-01 | GSE223280 | GEO
Project description:Cut & Run analysis was performed in an neuroblastoma cell line to analyze DNA bindings of ASCL1-tag-HA in GI-MEN ASCL1-tag-HA cells and GI-MEN ASCL1-tag-HA+4TFs cells; analyze DNA bindings of MYCN, PHOX2B and H3K27ac in, GI-MEN 4TFs cells, and GI-MEN ASCL1-tag-HA+4TFs cells.
2023-11-21 | GSE214793 | GEO
Project description:This study is aimed to Investigate whether C1qbp deficiency affects the histone modification during the differentiation stage of CD8+ T cells. Transferred WT and C1qbp KO P14 cells sorted from the spleen of donor mice on day 5 post-infection with LCMV Armstrong were collected and treated for CUT-tag. CUT-tag-Seq analysis provided evidence of histone modification changes between WT and C1qbp KO CD8+ T cells. Our study shows that on day 5 post-infection with LCMV Armstrong, along with mRNA expressing profiling, the CUT-tag-seq exhibits obvious changes in H3K27me3 and H3K27Ac modification of indicated genes of WT and C1qbp KO CD8+ T cells.
2021-06-09 | GSE176368 | GEO
Project description:Temporal epigenomic analysis of HD KI Q140 mouse striatal neurons using CUT&TAG on purified sorted neuronal nuclei.
2025-01-08 | GSE262077 | GEO
Project description:Cleavage Under Targets & Tagmentation (CUT&Tag) is an antibody-directed in situ chromatin profiling strategy that is rapidly replacing precipitation-based methods. The efficiency of the method enabled chromatin profiling in single cells but is limited by the numbers of cells that can be profiled. Here, we describe a combinatorial barcoding strategy for CUT&Tag that harnesses a nanowell dispenser for simple, high-resolution high-throughput single-cell chromatin profiling. We describe a pipeline for single-cell indexed CUT&Tag (sciCUT&Tag) that uses SNPs to facilitate doublet-cell removal and minimize batch effects. We illustrate the optimized protocol by analysis of mouse and human cell lines, as well as human peripheral blood mononuclear cells. We have also used sciCUT&Tag for simultaneous profiling of multiple chromatin epitopes in single cells. The reduced cost, improved resolution and scalability of sciCUT&Tag make it an attractive platform to profile chromatin features in single cells.
2023-07-13 | GSE224579 | GEO