In chronic lymphocytic leukemia (CLL) a diverse set of genetic mutations is embedded in a deregulated epigenetic landscape that drives cancerogenesis. To elucidate the role of aberrant chromatin features, we mapped DNA methylation, 7 histone modifications, nucleosome positions, chromatin accessibility, binding of EBF1 and CTCF as well as the transcriptome of B cells from CLL patients and healthy donors. A globally increased histone deacetylase activity was detected and half of the genome comprised transcriptionally downregulated partially DNA methylated domains demarcated by CTCF. CLL samples displayed a H3K4me3 redistribution and nucleosome gain at promoters as well as changes of enhancer activity and enhancer linkage to target genes. A DNA binding motif analysis identified transcription factors that gained or lost binding in CLL at sites with aberrant chromatin features. These findings were integrated into a gene regulatory enhancer containing network enriched for B cell receptor signaling pathway components. Our study predicts novel molecular links to targets of CLL therapies and provides a valuable resource for further studies on the epigenetic contribution to the disease.
The CancerEpisys epigenome dataset was made accessible via UCSC Genome browser track-hub for interactive visualization.
Example Track-hub file: http://www.cancerepisys.org/data/cancerepisys_data/track-hub/CLL_vs_healthy/hub.txt link for UCSC genome browser: http://genome.ucsc.edu/cgi-bin/hgTracks?db=hg19&hubUrl=http://www.cancerepisys.org/data/cancerepisys_data/track-hub/CLL_vs_healthy/hub.txt
BigBed and bigWig file table for visualization of individual samples
Supplementary data sets
- Dataset_EV01-overview_datasets.xlsx Inventory of EV data sets 2-14.
- Dataset_EV02-samples.xlsx Data CLL patient samples and reference samples from healthy donors
- Dataset_EV03-meC.xlsx The merged list of consensus PMDs and DMRs identified.
- Dataset_EV04-histone-ChIPseq-QC.xlsx Quality parameters describing histone ChIPseq quality for each sample, and inclusion of sample is ChromHMM model generation and differential histone modification analysis
- Dataset_EV05-promoters.xlsx List of promoters with H3K4me3 broadening and bivalent promoters gained/lost in CLL.
- Dataset_EV06-ChromHMM-model.xlsx ChromHMM 12 state model emission parameters, state descriptions, transition parameters, probabilities and segmentations of samples (A-V) including all CLL, non-malignant, and panobinostat/mock treated samples at 24 hours.
- Dataset_EV07-ChromHMM-merged-states.xlsx Merged chromatin states occuring in at least 3 samples (A-L) for each chromatin state.
- Dataset_EV08-ChIPseq-dif_histone-mod_CTCF_EBF1.xlsx Differential histone modifications regions for each of the 7 histone modifications comparing CLL to non-malignant using only samples passing QC.
- Dataset_EV09-enhancers.xlsx List of consensus enhancers for CLL, non-malignant, CLL + non-malignant and panobinostat treatment at 24hours. List of the differential enhancers between CLL and non-malignant.
- Dataset_EV10-ATAC.xlsx List of differential ATAC peaks between CLL an non-malignant.
- Dataset_EV11-RNAseq-dif-gene-expr.xlsx List of differentiall expressed genes in CLL vs non-malignant.
- Dataset_EV12-chromatin-expr-changes.xlsx Enrichment of differential gene expression with differential epigenetic changes in CLL.
- Dataset_EV13-B-cell_network.xlsx The ARACNE B-cell network.
- Dataset_EV14-CLLspecific_GREN.cys CLL specific gene regulatory enhancer containing network that contains the connected part centered around the core TF set linked to aberrant chromatin features. File format is for the cytoscape network viewer available at cytoscape.org.
Bed files of peaks called from ChIP-seq data (under construction)
ChromHMM annotation (under construction)
- ChromHMM 12 state chromatin model segmentation of individual samples
- ChromHMM annotation in IGV format
- Consensus chromatin states E1, E2, E3, E4, E5, E6, E7, E8, E9, E10, E11 and E12
Consensus data sets (under construction)
CLL |
non-malignant B cell |
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ChromHMM consensus annotation |
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Active enhancers from ChromHMM with ATAC peak (+/- 1kb) |
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CTCF consensus peaks |
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EBF1 consensus peaks |
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The analysis of CLL epigenome was developed by CancerEpiSys team (Zapatka, Lichter, Eils, Brors, Mertens, Rippe groups from DKFZ and Vingron group from molgen.mpg). The source code used in the analysis of CLL epigenome is released under the GNU General Public License v3.0. The CancerEpiSys source code is Copyright (C) 2018 Jan-Philipp Mallm, Murat Iskar, Naveed Ishaque, Jose M. Muino, Lara Klett, Alexandra M. Poos, Benedikt Brors, Martin Vingron, Marc Zapatka, Daniel Mertens, Karsten Rippe and DKFZ.
- Github repository of analysis scripts
- RWire R-script to compute correlations between open sites from scATAC-seq
- Other software used in the data analysis
Download summary (under construction)
- Download all supplementary files including EV datasets (.zip file)
- Supplementary Information (Appendix) with supplementary tables S1-S7 and supplementary figures S1-S7.