Ontology highlight
ABSTRACT:
PROVIDER: PRJNA831335 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR18906704_1.fastq.gz | Fastqsanger.gz | |||
| SRR18906704_2.fastq.gz | Fastqsanger.gz | |||
| SRR18906705_1.fastq.gz | Fastqsanger.gz | |||
| SRR18906705_2.fastq.gz | Fastqsanger.gz | |||
| SRR18906706_1.fastq.gz | Fastqsanger.gz |
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Project description:A large number of transcription factors are enriched at specific DNA sites in the nuclear, playing an important role in the regulation of gene expression. Chromatin immunoprecipitation sequencing (ChIP seq) is the classic method for the detection of chromatin transcription factor landscape. This method is limited by the complexity of steps, low signal to noise ratio, large number of cells required, high cost, and heavy reliance on high-purity high-performance antibodies. In recent years, based on MNase and Tn5 transposase, CUT&RUN, CUT&Tag, ChIL-seq, itChIP-seq have been developed and widely used, but they still rely on antibodies and take a long time. Here, we develop an antibody-free and fast method for profiling transcription factor binding sites, called Aptamer-Guided Chromatin Cleavage with Sequencing (AptaChC-seq). AptaChC-seq has the advantages of high signal to noise ratio, low cost, good reproducibility.
2023-01-07 | GSE221869 | GEO
Project description:Background: Genome-wide profiling of DNA-protein interactions in cells can provide important information about mechanisms of gene regulation. Most current methods for genome-wide profiling of DNA-bound proteins such as ChIP-seq and CUT&Tag use conventional IgG antibodies to bind the target protein(s). This limits their applicability to targets with available high affinity and specificity antibodies and prevents their use for other targets. Here we describe NanoTag, an IgG-free method derived from CUT&Tag to profile DNA-protein interactions. NanoTag is based on a fusion between an anti-GFP nanobody and Tn5 transposase that can map GFP-tagged proteins associated with chromatin in a fast, cost-effective and animal-free manner. Results: We used NanoTag to indirectly profile the histone mark H3K4me3 genome-wide via its binding partner TATA box-binding protein-associated factor 3 (TAF3) and the transcription factors Nanog and CTCF in mouse embryonic stem cells (mESCs). NanoTag results show high inter-replicate reproducibility, high signal-to-noise ratio and strong correlation with CUT&Tag datasets, validating its accuracy and reliability. Conclusions: NanoTag provides a novel, flexible and cost-effective IgG-free method to generate high resolution DNA-binding profiles in cells and tissues.
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Project description:5-methylcytosine (5-mC) can be oxidized to 5-hydroxymethylcytosine (5-hmC). Genome-wide profiling of 5-hmC thus far indicated 5-hmC may not only be an intermediate form of DNA demethylation but could also constitute an epigenetic mark per se. We describe a cost-effective and selective method to detect both the hydroxymethylation and methylation status of cytosines in more than 1.8 million MspI sites in the human genome. This method involves the selective glucosylation of 5-hmC residues, short-sequence tag generation and high-throughput sequencing. We tested this method by screening H9 human embryonic stem cells and their differentiated embroid body cells, and found that differential hydroxymethylation preferentially occur in bivalent genes during cellular differentiation. Especially, our results support hydroxymethylation can regulate key transcription regulators with bivalent marks through demethylation and affect cellular decision on choosing active or inactive state of these genes upon cellular differentiation. We developed a cost-effective and selective method to detect both the hydroxymethylation and methylation status of cytosines in more than 1.8 million MspI sites in the human genome. In order to validate the results generated by this method, we applied MeDIP-seq and hMeDIP-seq to screen H9 human embryonic stem cells in comparison with the newly developed method.
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Project description:Precise profiling of epigenomes, including histone modifications and transcription factor binding sites, is essential for better understanding gene regulatory mechanisms. Cleavage Under Targets & Tagmentation (CUT&Tag) is an easy and low-cost epigenomic profiling method that can be performed on a low number of cells and at the single-cell level. A large number of CUT&Tag datasets have been generated in various biological systems, providing a valuable resource. CUT&Tag experiments use the hyperactive transposase Tn5 for tagmentation. We found that the preference of Tn5 captured reads toward accessible chromatin regions can influence the distribution of CUT&Tag reads and cause open chromatin biases, further confounding the analysis of CUT&Tag data. The high sparsity of single-cell sequencing data makes the open chromatin biases more substantial than in bulk sequencing data. Here, we present a comprehensive computational method, PATTY (Propensity Analyzer for Tn5 Transposase Yielded bias), to mitigate the open chromatin bias inherent in CUT&Tag data at both bulk and single-cell levels. By integrating existing transcriptome and epigenome data using machine learning and comprehensive modeling, we demonstrate that PATTY yields more accurate and robust detection of occupancy sites for both active and repressive histone marks than existing methods, with experimental validation. We further designed a single-cell CUT&Tag analysis framework by utilizing this model and showing improved cell clustering from bias-corrected single-cell CUT&Tag data compared to using raw data. This model paved the way for further development of computational tools for improving bulk and single-cell CUT&Tag data analysis.
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Project description:5-methylcytosine (5-mC) can be oxidized to 5-hydroxymethylcytosine (5-hmC). Genome-wide profiling of 5-hmC thus far indicated 5-hmC may not only be an intermediate form of DNA demethylation but could also constitute an epigenetic mark per se. We describe a cost-effective and selective method to detect both the hydroxymethylation and methylation status of cytosines in more than 1.8 million MspI sites in the human genome. This method involves the selective glucosylation of 5-hmC residues, short-sequence tag generation and high-throughput sequencing. We tested this method by screening H9 human embryonic stem cells and their differentiated embroid body cells, and found that differential hydroxymethylation preferentially occur in bivalent genes during cellular differentiation. Especially, our results support hydroxymethylation can regulate key transcription regulators with bivalent marks through demethylation and affect cellular decision on choosing active or inactive state of these genes upon cellular differentiation. We developed a cost-effective and selective method to detect both the hydroxymethylation and methylation status of cytosines in more than 1.8 million MspI sites in the human genome. In this method, we took advantage of the differential enzymatic sensitivities of the isoschizomers MspI and HpaII. HpaII cleaves only a completely unmodified site, any modification at either cytosine blocks the cleavage, while MspI recognizes and cleaves both 5-mC and 5-hmC, but not the newly discovered 5-formylcytosine (5-fC) and 5-carboxylcytosine (5-caC). Furthermore, beta-glucosyltransferase (beta-GT) can transfer a glucose to the hydroxyl group of 5-hmC and generate beta-glucosyl-5-hydroxymethylcytosine (5-ghmC) that blocks MspI digestion. Thus, either by combining beta-GT treatment with MspI digestion or simply applying MspI/HpaII digestion, short sequence tags generated can be used for inferring hydroxymethylation or methylation status in around 1.8 million cytosine sites in the human genome. We tested this method by screening H9 human embryonic stem cells and their differentiated embroid body cells.
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