Corrupted coordination of epigenetic modifications leads to diverging chromatin states and transcriptional heterogeneity in CLL

Abstract

Cancer evolution is fueled by epigenetic as well as genetic diversity. In chronic lymphocytic leukemia (CLL), intra-tumoral DNA methylation (DNAme) heterogeneity empowers evolution. Here, to comprehensively study the epigenetic dimension of cancer evolution, we integrate DNAme analysis with histone modification mapping and single cell analyses of RNA expression and DNAme in 22 primary CLL and 13 healthy donor B lymphocyte samples. Our data reveal corrupted coherence across different layers of the CLL epigenome. This manifests in decreased mutual information across epigenetic modifications and gene expression attributed to cell-to-cell heterogeneity. Disrupted epigenetic-transcriptional coordination in CLL is also reflected in the dysregulation of the transcriptional output as a function of the combinatorial chromatin states, including incomplete Polycomb-mediated gene silencing. Notably, we observe unexpected co-mapping of typically mutually exclusive activating and repressing histone modifications, suggestive of intra-tumoral epigenetic diversity. Thus, CLL epigenetic diversification leads to decreased coordination across layers of epigenetic information, likely reflecting an admixture of cells with diverging cellular identities.

Fig. 1

Super-enhancer rewiring in CLL. a H3K27ac profiles of 297 differentially regulated super-enhancers (absolute log₂[H3K27ac fold-change] > 2 and Wald test BH-FDR < 0.01) between CLL and normal B cells. Red indicates high H3K27ac level, blue low H3K27ac level. Gene assignment to super-enhancers based on proximity (average distance of 2775 bp). Genes critical for lymphocyte proliferation and differentiation are highlighted. b Differential H3K27ac at super-enhancers (n = 2869) between CLL and naïve B cells (same samples as in a were used in the analysis). Differentially regulated super-enhancers defined as having absolute log₂(H3K27ac fold-change) > 2 and Wald test BH-FDR < 0.01. c Same as b for differential H3K27ac at super-enhancers (n = 2869) between CLL and germinal center B cells. d KEGG pathways enriched at differentially regulated super-enhancers (n = 297; hypergeometric test BH-FDR < 0.01). e Comparison of rank in transcription factor de novo motif enrichment (n = 310, ranked by hypergeometric test P-value) between CLL (x-axis) and naïve B cells (y-axis) at super-enhancers. Critical TF motifs for lymphocyte proliferation and B cell differentiation are highlighted. LOESS regression line of observed ranked P-values is shown in dotted gray. Color: red—CLL biased; blue—naïve B cell biased, size adjusted based on residual. f Position weight matrices of selected de novo TF motifs significantly over-represented in CLL (standardized residuals > 1.65). For each motif, the differential ranked P-value between CLL and naïve B cells, motif enrichment hypergeometric test P-value, and the best match to JASPAR core database are shown

Fig. 2

DNA methylation alteration at super-enhancers in CLL. a Percentage of differentially methylated regions (DMRs) measured with targeted bisulfite sequencing capture assay in (i) Global: all covered 500bp-tiles in the genome; (ii) H3K27ac: union of all H3K27ac peaks; (iii) CGI: CpG islands; (iv) SE: union of all super-enhancers; (v) H3K27ac distal peaks: union of all H3K27ac peaks that did not overlap TSSs (±2.5 kb). P-values are shown for two-sided Fisher’s exact test. Bottom: percentage of distinct genomic features covered by the targeted bisulfite sequencing capture assay. b CpG methylation for CLL and normal B cells across all super-enhancers (left), super-enhancers upregulated in normal B cells (center), and super-enhancers upregulated in CLL (right), measured with targeted bisulfite sequencing capture assay. c Difference in mean CpG methylation between CLL and normal B cells for the three categories shown in b. Error bars represent 95% confidence interval. P-values are indicated for two-sided Mann–Whitney U-test. NS, not significant. d Epigenomic profiling of the BLC2 locus in CLL compared with normal B cells. e The percentage of CpG methylation values at super-enhancers in CLL (no. of CpGs used = 468,303) and normal B cells (no. of CpGs used = 502,607), measured with targeted bisulfite sequencing capture assay. P-value is shown for two-sided Fisher’s exact test for the intermediate category [0.2–0.8]

Fig. 3

Decreased epigenetic-transcriptional coordination in CLL. a Mutual information (MI) across super-enhancers (n = 2869) between bulk DNAme (measured with targeted bisulfite sequencing capture assay) and H3K27ac for CLL and normal B samples. P-values are indicated for two-sided Welch’s t-test. b Schematic of the experimental procedures of the joint multiplexed single-cell RRBS and transcriptomics analysis. c MI between expression and promoter single-cell DNAme rate (n = 759 genes with sufficient RNA [expression seen in >5 cells] and DNAme [>10 CpGs per promoter] information) in individual CLL cells (n = 84) and normal B cells (n = 65). The observed MI values were compared to values obtained by randomly permuting cell labels for the methylation values. Inset: percentage increase in MI when comparing matched vs. scrambled single-cell DNAme and RNA data in CLL and normal B cells. P-value is indicated for two-sided Mann–Whitney U-test. d Number of states gained when adding RNA data to the epigenomic mapping (H3K4m3, H3K27ac, H3K27me3, DNAme based on bulk bisulfite sequencing) in the DPM analysis for CLL and normal B samples. P-value is indicated for two-sided Mann–Whitney U-test. See also Supplementary Fig. 3d. e Expression levels (log₂[RPKM]) of 904 genes marked by H3K27me3^hi/H3K4me3^low/H3K27ac^low between normal B samples (blue) and CLL (red) samples (n = 2 and n = 7, respectively). P-value is shown for two-sided Mann–Whitney U-test. f Single-cell gene expression Shannon’s information entropy in relation to the population average gene expression (based on single-cell whole transcriptome data) in CLL (n = 94) and normal B cells (n = 84). Local regression lines for the H3K27me3^hi/H3K4me3^low/H3K27ac^low-marked genes in CLL (red) and normal B cells (blue) are shown. g Single-cell gene expression Shannon’s information entropy (left) for genes within a population average expression range of −1.25 to −0.75 log₁₀(TPM) (to control for differences in this variable). P-values are shown for two-sided Mann–Whitney U-test. Cumulative distribution (right) showing the proportion of intermediate single-cell gene expression Shannon’s information entropy values at H3K27me3^hi/H3K4me3^low/H3K27ac^low-marked genes. Throughout the figure: boxplot represents median and bottom and upper quartile; whiskers correspond to 1.5*IQR; error bars represent 95% confidence interval

Fig. 4

Corrupted coherence across layers of CLL epigenome leads to cell-to-cell transcriptional heterogeneity. a Chromatin state definitions and enrichments for a 12-state Hidden Markov Model based on three histone marks (H3K4me3, H3K27ac, H3K27me3), DNAme, and RNA information. P-values of a given HMM state between CLL and normal B cells are shown for two-sided hypergeometric test. b Epigenomic profiling of the FYN gene locus, demonstrating “H3K27a-H3K27me3” state increase in CLL compared with normal B cells across our cohort and Blueprint initiative samples. c Sankey diagram showing that ~47% of the regions in a “H3K27ac-H3K27me3” state in CLL carried repressive chromatin modifications in B cells. d Fold-change gene expression between CLL and normal B cells in relation to genomic distance from regions that gain H3K27ac (orange; n = 11,740 genes) or H3K27me3 (blue; n = 8867 genes) in CLL. Mann–Whitney U-test. e Position weight matrices of the top three motifs over-represented in CLL “H3K27ac-H3K27me3” regions. Motif enrichment hypergeometric test P-value and the best reference motif match (JASPAR core database) are shown. f Expression levels (log₂[TPM]) of MYC target genes (containing promoter MYC binding motif, as in analysis in e) compared with non-MYC target genes in “H3K27ac-H3K27me3” regions in CLL. Mann–Whitney U-test. g Single-cell (n = 94) gene expression Shannon’s information entropy in relation to the population average gene expression in CLL (scCLL_21). Colored lines—local regression curves for genes in a ‘H3K27ac-H3K27me3’ (brown) or “Repressed Polycomb (PRC)” (gray) state. Inset: single-cell gene expression Shannon’s information entropy for each of the two chromatin states comparing genes within a defined range of population average gene expression. Mann–Whitney U-test. h Gene expression magnitudes of genes in “Repressed Polycomb (PRC)” state and genes in “H3K27ac-H3K27me3” state. Cumulative distribution (right) showing the proportion of intermediate single-cell gene expression Shannon’s information entropy values at these genes is also shown. Kolmogorov–Smirnov test. i Well-coordinated chromatin programs stabilize gene expression and cellular identities in normal B cells (left). On the contrary, intra-leukemic epigenetic diversity results in a permissive chromatin state in CLL cells (right), enhancing cell-to-cell transcriptional variation. Boxplots represent median and bottom and upper quartile; whiskers correspond to 1.5*IQR; error bars represent 95% confidence interval