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E459cce1-11c5-49bb-80e8-130ada807b62 - samples

ABSTRACT: This dataset contains 18 ATACseq reads, in fastq format. Samples were collected from fresh bone marrow and peripheral blood sample from AML patients.

PROVIDER: EGAD00001006670 | EGA |

REPOSITORIES: EGA

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5c8d899b-6f57-4347-88de-617a3af63822 - samples

Project description:This dataset contains 91 RNAseq paired reads, in fastq format. Samples were collected from fresh bone marrow and peripheral blood sample from AML patients.

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The SWI/SNF subunit Dpf2 licenses Nrf2-dependent gene expression to enforce multilineage control of inflammation [ATAC-seq]

Project description:Purpose: Multi-omics characterization of the consequences of deleting the SWI/SNF subunit Dpf2 in the transcriptome (RNAseq), accessibility of the genome (ATACseq) and binding of SWI/SNF subunits (CUT&RUN) in hematopoietic stem/progenitor cells, resting and polarized bone-marrow derived macrophages and resting and activated CD4+ T cells obtained from Dpf2f/f and Dpf2D/D mice. Methods: Lin- cKit+ cells were sorted from bone marrow of 28-days old Dpf2f/f and Dpf2D/D mice. Bone-marrow derived macrophages were obtained from 28-days old Dpf2f/f and Dpf2D/D mice and polarized with IFNg and LPS, or IL-4 for 24hours. CD4+ splenic T helper cells were obtained from 28-days old Dpf2f/f and Dpf2D/D mice and activated by treatment with PMA and Ionomycin. Methods: For ATACseq, Lin- cKit+ cells were processed following the OMIM-ATAC-seq protocol (Corces MR et al., Nature Methods 2017). Libraries were sequenced on a NextSeq (75bp, paired end reads) to obtain more than 40 million reads/sample. Results: For ATACseq, we obtained more than 40 million reads per sample. ATAC-Seq chromatin accessible regions were determined using ENCODE pipeline standards (https://github.com/ENCODE-DCC/atac-seq-pipeline; git commit 2b693ab). Conclusions: The absence of Dpf2 in LK cells results in downregulation of anti-oxidative and anti-inflammatory gene expression programs in bone marrow LK cells, bone-marrow derived macrophages and CD4+ T cells.

2023-06-06 | GSE192776 | GEO

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Finding new Chimeric RNAs in RNA-seq data, a test study in Acute Myeloid Leukemia patient cells

Project description:In this strudy, we seek out new chimeric RNA in RNA-seq data from acute myeloid leukemia (AML) patient cells as new biomarkers to improve diagnosis and prognosis in cancer. Total RNA were extracted from bone marrow or peripheral blood mononuclear cells in three AML patients. polyA+ cDNAs were sequenced to generate stranded paired-end reads. RNA-seq analyses were performed using Crac and CracTools software. In particular using these tools, we classified chimeric RNA in four classes, finding new chimeric RNAs. By analysis a larger cohort by qPCR, we were able to define new chimeric RNA as new biomarkers in AML patients.

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