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25967b7c-e693-49da-a54b-4e2cec4f4330 - samples

ABSTRACT: In this study, we aimed to identify somatic structural variation of acute myeloid leukemia (AML) at the single-cell level and investigate its direct consequence on the nucleosome occupancy using scNOVA approach. For this purpose, we performed strand-specific single-cell sequencing of primary leukemia samples from 32-year-old male donor.

PROVIDER: EGAD00001006782 | EGA |

REPOSITORIES: EGA

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Finding structural variation and functional consequences from the primary leukemia cells (AML) at the single-cell level

Project description:In this study, we aimed to identify somatic structural variation of acute myeloid leukemia (AML) at the single-cell level and investigate its direct consequence on the nucleosome occupancy using scNOVA approach. For this purpose, we performed strand-specific single-cell sequencing of primary leukemia samples from 32 year old male donor.

| EGAS00001004903 | EGA

f129cf9e-793d-428b-a718-8fc71d4f5ca9 - samples

Project description:In this study, we aimed to identify somatic structural variation of Skin fibroblast at the single-cell level and investigate its direct consequence on the nucleosome occupancy using scNOVA approach. For this purpose, we performed strand-specific single-cell sequencing of skin fibroblast sample from male donor.

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Finding structural variation and functional consequences from the primary leukemia cells (CLL) at the single-cell level

Project description:In this study, we aimed to identify somatic structural variation of chronic lymphocytic leukemia (CLL) at the single-cell level and investigate its direct consequence on the nucleosome occupancy using scNOVA approach. For this purpose, we performed strand-specific single-cell sequencing of primary leukemia samples from 63-year-old female patient.

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6c230511-9373-4a9b-bbba-dcbccba244dc - samples

Project description:In this study, we aimed to identify somatic structural variation of acute myeloid leukemia with complex karyotype (CK-AML) at the single-cell level and to investigate its direct consequence on the nucleosome occupancy using scNOVA approach. For this purpose, we performed strand-specific single-cell sequencing of primary leukemia samples from four CK-AML patients. We also performed strand-specific single-cell sequencing of two patient-derived xenografts (PDXs).

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Finding structural variation from the human skin fibroblast at the single-cell level

Project description:Somatic structural variants (SVs) are widespread in cancer, but their impact on disease evolution is understudied due to a lack of methods to directly characterize their molecular consequences. We present a computational method, scNOVA, that integrates haplotype-resolved SV discovery with nucleosome occupancy analysis using Strand-seq, to functionally characterize SVs in single cells.

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Comparison of gene expression profiles across the normal human body

Project description:Normal human tissue samples from ten post-mortem donors were processed to generate total RNA, which was subsequently analyzed for gene expression using Affymetrix U133 plus 2.0 arrays. Donor information: Donor 1 - 25 year old male; donor 2 - 38 year old male; donor 3 - 39 year old female; donor 4 - 30 year old male; donor 5 - 35 year old male; donor 6 - 52 year old male; donor 7 - 50 year old female; donor 8 - 48 year old female; donor 9 - 53 year old female; donor 10 - 23 year old female Keywords: normal human tissue comparison

2006-03-30 | GSE3526 | GEO

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Project description:Nucleosome occupancy

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Transcription profiling by array of human post mortem tissue samples

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Genome-wide mapping of nucleosome positioning and DNA methylation within Individual DNA molecules

Project description:DNA methylation and nucleosome positioning work together to generate chromatin structures that regulate gene expression. Nucleosomes are typically mapped using nuclease digestion requiring significant amounts of material and varying enzyme concentrations. We have developed a method (NOMe-seq) that uses a GpC methyltransferase (M.CviPI) and next generation sequencing to generate a high resolution footprint of nucleosome positioning genome-wide using less than 1 million cells while retaining endogenous DNA methylation information from the same DNA strand. Using a novel bioinformatics pipeline we show a striking anti-correlation between nucleosome occupancy and DNA methylation at CTCF regions, that is not present at promoters. We further show that the extent of nucleosome depletion at promoters is directly correlated to expression level and can accommodate multiple nucleosomes and provide genome-wide evidence that expressed non-CpG island promoters are nucleosome depleted. Importantly, NOMe-seq obtains DNA methylation and nucleosome positioning information from the same DNA molecule, giving the first genome-wide DNA methylation and nucleosome positioning correlation at the single molecule and thus, single cell level that can be used to monitor disease progression and response to therapy. Nucleosome Occupancy and Methylome-Sequencing (NOMe-Seq) on IMR90 cell line and 2 GBM cell lines

2012-09-12 | E-GEOD-40770 | biostudies-arrayexpress

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