Genomics,Multiomics

Dataset Information

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Ena-DATASET-CeMM-13-05-2016-20:41:19:139-66 - samples


ABSTRACT: Chronic lymphocytic leukemia (CLL) is characterized by substantial clinical heterogeneity, despite relatively few genetic alterations. To provide a basis for studying epigenome deregulation in CLL, we established genome-wide chromatin accessibility maps for 88 CLL samples from 55 patients using the ATAC-seq assay, and we also performed ChIPmentation and RNA-seq profiling for ten representative samples. Based on the resulting dataset, we devised and applied a bioinformatic method that links chromatin profiles to clinical annotations. Our analysis identified sample-specific variation on top of a shared core of CLL regulatory regions. IGHV mutation status – which distinguishes the two major subtypes of CLL – was accurately predicted by the chromatin profiles, and gene regulatory networks inferred for IGHV-mutated vs. IGHV-unmutated samples identified characteristic differences between these two disease subtypes. In summary, we discovered widespread heterogeneity in the chromatin landscape of CLL, established a community resource for studying epigenome deregulation in leukemia, and demonstrated the feasibility of chromatin accessibility mapping in cancer cohorts and clinical research.

OTHER RELATED OMICS DATASETS IN: PRJNA321180

PROVIDER: EGAD00001002110 | EGA |

REPOSITORIES: EGA

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Publications

Chromatin accessibility maps of chronic lymphocytic leukaemia identify subtype-specific epigenome signatures and transcription regulatory networks.

Rendeiro André F AF   Schmidl Christian C   Strefford Jonathan C JC   Walewska Renata R   Davis Zadie Z   Farlik Matthias M   Oscier David D   Bock Christoph C  

Nature communications 20160627


Chronic lymphocytic leukaemia (CLL) is characterized by substantial clinical heterogeneity, despite relatively few genetic alterations. To provide a basis for studying epigenome deregulation in CLL, here we present genome-wide chromatin accessibility maps for 88 CLL samples from 55 patients measured by the ATAC-seq assay. We also performed ChIPmentation and RNA-seq profiling for ten representative samples. Based on the resulting data set, we devised and applied a bioinformatic method that links  ...[more]

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