Insight into genetic predisposition to chronic lymphocytic leukemia from integrative epigenomics

Author/s: Helen E. Speedy, Renée Beekman, Vicente Chapaprieta, Giulia Orlando, Philip J. Law, David Martín-García, Jesús Gutiérrez-Abril, Daniel Catovsky, Sílvia Beà, Guillem Clot, Montserrat Puiggros, David Torrents, Xose S. Puente, James M. Allan, Carlos López-Otín, Elias Campo, Richard S. Houlston, José I. Martín-Subero

Nature Communications, volume 10, 3615 (2019)

doi:10.1038/s41467-019-11582-2

Abstract

Genome-wide association studies (GWAS) have provided evidence for inherited genetic predisposition to chronic lymphocytic leukemia (CLL). However, efforts to define the mechanisms mediating the, largely non-coding, signals revealed by GWAS have been constrained by a lack of integrated genome-wide data in large CLL series. We performed a detailed epigenomic characterization of the 42 known CLL risk loci by analysing chromatin accessibility, active regulatory elements marked by H3K27ac, and DNA methylation in up to 486 primary CLLs. Risk loci were significantly enriched for active chromatin in CLL with evidence of being CLL-specific or differentially regulated in normal B-cell development. We used in situ promoter capture Hi-C (CHi-C), in conjunction with gene expression data to identify likely target genes of the risk loci. Candidate target genes were enriched for pathways related to B-cell development such as MYC and BCL2 signalling. At 14 loci our analysis highlights 63 variants that potentially influence CLL risk. In summary, the integration of genetic and epigenetic information has provided insights into the relationship between inherited predisposition and the regulatory landscape of CLL.

UCSC tracks

Please, use this link to access the CLL Referece Epigenome tracks in the UCSC genome browser. The presented tracks are briefly described in this document.

Data

All raw data for this study was mined from previous studies and has been deposited at the European Genome-Phenome Archive (EGA, https://ega-archive.org), which is hosted at the European Bioinformatics Institute (EBI), under accession numbers EGAS00000000092, EGAD00001004046, EGAS00001000272 and EGAS00001001911.

The normalized data matrices for the QTL analyses can be found in the following table.


File	Details	File size	Download
H3K27ac peaks	This file contains the information which H3K27ac peaks were used for the QTL analysis. Per SNP (columns), only the peaks which have assigned a 2 were used. 0 = peak present in less than 10% (with a minimum of two) of the patients in all of the following subgroups: homozygous non-risk, heterozygous risk or homozygous risk based on the sentinel SNP genotype; 1 = peak present in at least 10% (with a minimum of two) of the patients in one or more of the following subgroups: homozygous non-risk, heterozygous risk or homozygous risk based on the sentinel SNP genotype located outside the linkage disequilibrium region (LD, r2≥0.2) of the corresponding SNPs; 2 = peak present in at least 10% (with a minimum of two) of the patients in one or more of the following subgroups: homozygous non-risk, heterozygous risk or homozygous risk based on the sentinel SNP genotype located within the linkage disequilibrium region (LD, r2≥0.2) of the corresponding SNPs.	1,3M	Link
H3K27ac normalized values	This file contains the normalized H3K27ac signals used for the QTL analysis.	91M	Link
ATAC-seq peaks	This file contains the information which ATAC-seq peaks were used for the QTL analysis. Per SNP (columns), only the peaks which have assigned a 2 were used. 0 = peak present in less than 10% (with a minimum of two) of the patients in all of the following subgroups: homozygous non-risk, heterozygous risk or homozygous risk based on the sentinel SNP genotype; 1 = peak present in at least 10% (with a minimum of two) of the patients in one or more of the following subgroups: homozygous non-risk, heterozygous risk or homozygous risk based on the sentinel SNP genotype located outside the linkage disequilibrium region (LD, r2≥0.2) of the corresponding SNPs; 2 = peak present in at least 10% (with a minimum of two) of the patients in one or more of the following subgroups: homozygous non-risk, heterozygous risk or homozygous risk based on the sentinel SNP genotype located within the linkage disequilibrium region (LD, r2≥0.2) of the corresponding SNPs.	2M	Link
ATAC-seq normalized values	This file contains the normalized ATAC-seq signals used for the QTL analysis.	132M	Link
DNA methylation CpGs	Per SNP the list of CpGs used for the QTL analysis are listed. These CpGs are located within the linkage disequilibrium region (LD, r2≥0.2) of the corresponding SNPs.	14K	Link
DNA methylation normalized beta values	This file contains the normalized beta values of the DNA methylation data which were transformed to M-values for the QTL analysis.	1,8G	Link
Gene expression probes	This file contains the information which probes were used for the RNA expression QTL analysis. Per SNP (columns), only the probes which have assigned a 2 were used. 0 = probes expressed (GC-RMA levels > 4.5) in less than 10% (with a minimum of two) of the patients in all of the following subgroups: homozygous non-risk, heterozygous risk or homozygous risk based on the sentinel SNP genotype; 1 = probes expressed (GC-RMA levels > 4.5) in at least 10% (with a minimum of two) of the patients in one or more of the following subgroups: homozygous non-risk, heterozygous risk or homozygous risk based on the sentinel SNP genotype located outside the linkage disequilibrium region (LD, r2≥0.2) of the corresponding SNPs; 2 = probes expressed (GC-RMA levels > 4.5) in at least 10% (with a minimum of two) of the patients in one or more of the following subgroups: homozygous non-risk, heterozygous risk or homozygous risk based on the sentinel SNP genotype located within the linkage disequilibrium region (LD, r2≥0.2) of the corresponding SNPs.	6,4K	Link
Gene expression normalized data	This file contains the GC-RMA normalized gene expression data used for the QTL analysis.	79M	Link

Code

We also provide the custom code in the next table.

File	Details	File Size	Download
Chromatin states enrichment	Evaluation of chromatin states enrichment in 7 chronic lymphocytic leukemia (CLL) patients at CLL, breast cancer (BC) and colorectal cancer (CRC) risk loci.	79K	Link
H3K27ac enrichment	Enrichment of H3K27ac on non-individual peaks within the linkage disequilibrium regions	10M	Link
Allelic imbalance	Statistical analysis evaluating allelic imbalance in 99 CLL patients.	3,6M	Link