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DARESOME enables concurrent profiling of multiple DNA modifications in single cells and multi-omics detection of cancer signatures in cell-free DNA

ABSTRACT: DARESOME enables concurrent profiling of multiple DNA modifications in single cells and multi-omics detection of cancer signatures in cell-free DNA

PROVIDER: PRJNA857676 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR20078537_1.fastq.gz	Fastqsanger.gz
	SRR20078537_2.fastq.gz	Fastqsanger.gz
	SRR20078538_1.fastq.gz	Fastqsanger.gz
	SRR20078538_2.fastq.gz	Fastqsanger.gz
	SRR20078539_1.fastq.gz	Fastqsanger.gz

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DARESOME enables concurrent profiling of multiple DNA modifications in single cells and multi-omics detection of cancer signatures in cell-free DNA

Project description:DARESOME enables concurrent profiling of multiple DNA modifications in single cells and multi-omics detection of cancer signatures in cell-free DNA

2023-08-04 | GSE207918 | GEO

DNA Analysis by Restriction Enzyme (DARE) enables concurrent genomic and epigenomic characterization of single cells

Project description:DNA Analysis by Restriction Enzyme (DARE) enables concurrent genomic and epigenomic characterization of single cells

| PRJNA528100 | ENA

DARESOME enables concurrent profiling of multiple DNA modifications with restriction enzymes in single cells and cell-free DNA.

Project description:5-Methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) are the most abundant DNA modifications that have important roles in gene regulation. Detailed studies of these different epigenetic marks aimed at understanding their combined effects and dynamic interconversion are, however, hampered by the inability of current methods to simultaneously measure both modifications, particularly in samples with limited quantities. We present DNA analysis by restriction enzyme for simultaneous detection of multiple epigenomic states (DARESOME), an assay based on modification-sensitive restriction digest and sequential tag ligation that can concurrently perform quantitative profiling of unmodified cytosine, 5mC, and 5hmC in CCGG sites genome-wide. DARESOME reveals the opposing roles of 5mC and 5hmC in gene expression regulation as well as their interconversion during aging in mouse brain. Implementation of DARESOME in single cells demonstrates pronounced 5hmC strand bias that reflects the semiconservative replication of DNA. Last, we showed that DARESOME enables integrative genomic, 5mC, and 5hmC profiling of cell-free DNA that uncovered multiomics cancer signatures in liquid biopsy.

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A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways

Project description:A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways

| PRJNA283126 | ENA

DNA Analysis by Restriction Enzyme (DARE) enables concurrent genomic and epigenomic characterization of single cells

Project description:Genome-wide profiling of copy number alterations and DNA methylation in single cells could enable detailed investigation into the genomic and epigenomic heterogeneity of tumor populations. However, current methods to do this require complex sample processing and cleanup steps, lack consistency, or are biased in their genomic representation. Here, we describe a novel single-tube enzymatic method, DNA Analysis by Restriction Enzyme (DARE), to perform deterministic whole genome amplification while preserving DNA methylation information. This method was evaluated on low amounts of DNA and single cells, and provides accurate copy number aberration calling and representative DNA methylation measurement across the whole genome. Single cell DARE is an attractive and scalable approach for concurrent genomic and epigenomic characterization of cells in a heterogeneous population.

2019-08-14 | GSE128560 | GEO

Chromatin integration labeling for mapping multiple DNA binding proteins and modifications with low input.

Project description:We established a novel epigenomic profiling method multi–target ChIL–seq, mtChIL-seq, which enables the detection of the DNA binding proteins and histone modifications simultaneously using a same sample.

2021-08-17 | GSE140659 | GEO

A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways [mESCs]

Project description:To characterize the largely unknown functions of oxidised methylcytosines (oxi-mC; 5hmC/5fC/5caC) in DNA, several sequencing protocols have been recently developed. Quantitative analysis is complicated because DNA methylation modifications need to be deconvoluted from the data which is affected by several experimental parameters, including e.g. imperfect bisulphite conversion, oxidation efficiencies, various chemical labeling and protection steps, and sequencing errors. Here, we present a hierarchical generative model, Lux, for integrative analysis of any combination of BS-seq and âoxi-mCâ-seq (BS-seq/oxBS-seq/TAB-seq/fCAB-seq/CAB-seq/redBS-seq/MAB-seq) data. We show that Lux improves quantification and comparison of methylation levels over existing methods and that Lux can easily process any oxi-mC-seq data sets to quantify all cytosine modifications simultaneously together with their experimental parameters. Application of Lux to targeted data from Tet2 knockdown ESCs and T cells during development demonstrates DNA modification quantification at unprecedented detail, quantifies active demethylation pathway and reveals 5hmC localization in putative regulatory regions. Examine the distribution of C, 5mC, and 5hmC in ES and Tet2 knock-down cells within selected loci. Half of the samples are measured using the traditional bisulphite-seq protocol but the other half is measured using the oxidative bisulphite-seq protocol (oxBS-seq).

2016-07-03 | E-GEOD-68574 | biostudies-arrayexpress

A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways [T-cells]

Project description:To characterize the largely unknown functions of oxidised methylcytosines (oxi-mC; 5hmC/5fC/5caC) in DNA, several sequencing protocols have been recently developed. Quantitative analysis is complicated because DNA methylation modifications need to be deconvoluted from the data which is affected by several experimental parameters, including e.g. imperfect bisulphite conversion, oxidation efficiencies, various chemical labeling and protection steps, and sequencing errors. Here, we present a hierarchical generative model, Lux, for integrative analysis of any combination of BS-seq and âoxi-mCâ-seq (BS-seq/oxBS-seq/TAB-seq/fCAB-seq/CAB-seq/redBS-seq/MAB-seq) data. We show that Lux improves quantification and comparison of methylation levels over existing methods and that Lux can easily process any oxi-mC-seq data sets to quantify all cytosine modifications simultaneously together with their experimental parameters. Application of Lux to targeted data from Tet2 knockdown ESCs and T cells during development demonstrates DNA modification quantification at unprecedented detail, quantifies active demethylation pathway and reveals 5hmC localization in putative regulatory regions. Examine the distribution of C, 5mC, and 5hmC in DP, CD4 SP, and naÃ¯ve CD4 T cells within selected loci. Half of the samples are measured using the traditional bisulphite-seq protocol but the other half is measured using the oxidative bisulphite-seq protocol (oxBS-seq).

2016-07-03 | E-GEOD-68575 | biostudies-arrayexpress

A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways [mESCs]

Project description:To characterize the largely unknown functions of oxidised methylcytosines (oxi-mC; 5hmC/5fC/5caC) in DNA, several sequencing protocols have been recently developed. Quantitative analysis is complicated because DNA methylation modifications need to be deconvoluted from the data which is affected by several experimental parameters, including e.g. imperfect bisulphite conversion, oxidation efficiencies, various chemical labeling and protection steps, and sequencing errors. Here, we present a hierarchical generative model, Lux, for integrative analysis of any combination of BS-seq and “oxi-mC”-seq (BS-seq/oxBS-seq/TAB-seq/fCAB-seq/CAB-seq/redBS-seq/MAB-seq) data. We show that Lux improves quantification and comparison of methylation levels over existing methods and that Lux can easily process any oxi-mC-seq data sets to quantify all cytosine modifications simultaneously together with their experimental parameters. Application of Lux to targeted data from Tet2 knockdown ESCs and T cells during development demonstrates DNA modification quantification at unprecedented detail, quantifies active demethylation pathway and reveals 5hmC localization in putative regulatory regions.

2016-01-01 | GSE68574 | GEO

A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways [T-cells]

Project description:To characterize the largely unknown functions of oxidised methylcytosines (oxi-mC; 5hmC/5fC/5caC) in DNA, several sequencing protocols have been recently developed. Quantitative analysis is complicated because DNA methylation modifications need to be deconvoluted from the data which is affected by several experimental parameters, including e.g. imperfect bisulphite conversion, oxidation efficiencies, various chemical labeling and protection steps, and sequencing errors. Here, we present a hierarchical generative model, Lux, for integrative analysis of any combination of BS-seq and “oxi-mC”-seq (BS-seq/oxBS-seq/TAB-seq/fCAB-seq/CAB-seq/redBS-seq/MAB-seq) data. We show that Lux improves quantification and comparison of methylation levels over existing methods and that Lux can easily process any oxi-mC-seq data sets to quantify all cytosine modifications simultaneously together with their experimental parameters. Application of Lux to targeted data from Tet2 knockdown ESCs and T cells during development demonstrates DNA modification quantification at unprecedented detail, quantifies active demethylation pathway and reveals 5hmC localization in putative regulatory regions.

2016-01-01 | GSE68575 | GEO

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