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, which we complemented by ChIPmentation and RNA-seq data for a representative subset of samples. Furthermore, we devised a bioinformatic method for linking these 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 regulatory differences between these two disease subtypes. In summary, we found widespread heterogeneity in the CLL chromatin landscape, established a community resource for studying epigenome deregulation in leukemia, and demonstrated the feasibility of chromatin accessibility mapping in cancer cohorts and clinical research.
This track hub includes several types of tracks:
| Analysis | Description and download |
| Cohort-level map of chromatin-accessible regions in CLL |
▸ Accessibility values (quantile normalized, log2) and cohort level statistics (217 MB) |
| Hypervariable regions within sample groups with different IGHV mutation status |
▸ BED file with regions more variable in mCLL (19.3 Kb) ▸ BED file with regions more variable in uCLL (37.5 Kb) |
| Differentially expressed genes between CLL disease subtypes |
▸ uCLL vs mCLL (25.5 Kb) ▸ uCLL vs iCLL (43.5 Kb) ▸ iCLL vs mCLL (10.8 Kb) |
| Chromatin accessibility regions associated with IGHV mutation status |
▸ BED file with associated regions (37.9 Kb) ▸ Accessibility values (quantile normalized, log2) and cohort level statistics of IGHV regions (3.2 MB) |
| Gene regulatory networks |
Transcription factor footprint-based inference of TF-DNA interactions and network inference. Networks are directed, weighted graphs. ▸ CLL cohort-level network (infered from all samples) (6.9 MB) ▸ CD19+ DNase-seq network (from publicly available data) (10.3 MB) ▸ mCLL cohort-level network (infered from IGHV mutated samples) (7.9 MB) ▸ uCLL cohort-level network (infered from IGHV unmutated samples) (5.4 MB) |
| Chromatin accessibility (ATAC-seq) | Histone Marks (ChIPmentation) | Gene Expression (RNA-seq) | |
| Raw sequencing data | ATAC-seq raw sequence reads (Raw data available through European Genome-phenome Archive (EGA)) |
ChIPmentation raw sequence reads (Raw data available through European Genome-phenome Archive (EGA)) |
RNA-seq raw sequence reads (Raw data available through European Genome-phenome Archive (EGA)) |
| Processed data | ATAC-seq peaks (BigWig and BED files available at the Gene Expression Omnibus (GEO) repository) |
ChIPmentation histone peaks (BigWig and BED files available at the Gene Expression Omnibus (GEO) repository) |
RNA-seq gene expression values (CSV file available at the Gene Expression Omnibus (GEO) repository) |
Download the complete set of analysis outputs.
If you use this resource in your research, please cite:
André F. Rendeiro*, Christian Schmidl*, Jonathan C. Strefford*, Renata Walewska, Zadie Davis, Matthias Farlik, David Oscier, Christoph Bock
Chromatin accessibility maps of chronic lymphocytic leukemia identify subtype-specific epigenome signatures and transcription regulatory networks.
Nat. Commun. 7:11938 doi: 10.1038/ncomms11938 (2016).
*Shared first authors