Super-silencers are crucial for development and carcinogenesis in B cells

Abstract

The strength of the repressive histone H3 lysine 27 trimethylation modification signal varies drastically at individual silencers. Focusing on cases of an unusually strong repressive signal in regions that we refer to as super-silencers, we demonstrate that the regions that become B-cell super-silencers are originally associated with gene upregulation during development, and their target genes are highly expressed in stem cells, especially during early developmental stages. About 13% of B-cell super-silencers transmute to super-enhancers in B-cell lymphoma and 22% of these conversions recur across more than half of patients. Notably, genes associated with these conversions, like BCL6 and BACH2, are downregulated more swiftly than others when subjected to JQ1, a super-enhancer-disrupting bromodomain and extra-terminal domain inhibitor utilized in cancer chemotherapy. Furthermore, super-silencers are characterized by an over-representation of B-cell-cancer-associated mutations, both somatic and germline, and B-cell-cancer translocation breakpoints. This surpasses the prevalence found in other regulatory elements, such as CTCF binding sites, underlining the crucial role of super-silencers in forming and stabilizing regulatory topologies in standard B cells. For example, over 80% of cases involving the B-cell-lymphoma translocation t(3;14)(q27;q32) fuse super-silencers in the BCL6 locus with enhancer-rich domains. Finally, we demonstrate that the repressive mechanisms of super-silencers are partially governed by the CpG content in their sequences. While CpG-rich super-silencers often prevent promoters from interacting with enhancers, CpG-depleted super-silencers typically suppress the chromatin looping of nearby enhancers. In summary, our findings accentuate the critical role super-silencers play in the normal function of B-cells, suggesting that sequence mutations and activity modifications in these elements could be primary factors in B-cell carcinogenesis.

Figure 1.

Identification of SSs in GM12878 cells. (A) Distribution of H3K27me3 ChIP-seq intensity in the silencers (blue) and of H3K27ac in the enhancers (pink). Intensity levels were linearly normalized to have a maximum of 1 for display purposes. (B) Results of ROSE with the intensities of H3K27me3 in GM12878 silencers. (C) Genomic distribution and overlap with CGIs of different enhancer and silencer types. (D) Average methylation levels of CpG sites in different enhancer and silencer types. Expression of genes (E) most proximal to and (F) having contacts with different enhancer/silencer types. Tissue-specificity of genes (as measured by tau) (G) most proximal to and (H) having contacts with different enhancer/silencer types. Here, SS and SE represent SS and SE components, respectively. In (E-H), “All” represented all genes profiled in RNA-seq data. The SS components (represented by dark blue) are frequently located close to or target the genes lowly expressed in GM12878 and with a high tissue specificity. (I) Average ATAC-STARR-seq scores of different enhancer and silencer types, with asterisks indicating significant values as compared to TEs. (J) Activity similarity among SS components within the same SS regions across cell types. (K) TFBS similarity between SS components located within the same SS regions across cell types, with “SS comp” and “SE comp” representing SS and SE components, respectively. In the left panel of (J, K), “BK” is the TSs randomly selected to match the distribution of distances between SS components, and “random” represents the randomly selected silencers. Similarly, “BK” and “random” in the (J, K) right panel are SE-distribution-matching and randomly selected TEs, respectively. **: P < 10⁻¹⁰ and *: P < 10⁻⁵.

Figure 2.

Experimental validation of SSs. (A) Elements tested in the experiments, accompanied by the genomic and epigenetic profiles of the regions hosting these elements in normal and cancer genomes. The numbers in the track of “DLBCL SE” and “CLL SE” are the numbers of patients having the corresponding SEs out of all patients. (B) Luciferase activities of the tested SSs in GM12878 and K562. Asterisks over pink bars indicate a significant decrease in luciferase activity as compared to the control elements.

Figure 3.

Functional analysis on GM12878 SSs. (A) Biological processes associated with SS components and TSs. These are the evaluation results of GREAT . (B) Expression of genes associated with different REs across the cell types relevant to B-cell differentiation and Psoas muscle (used as reference). (C) Top-ranked biological processes enriched by the genes in which the promoters interact with SS components. These are the evaluation results of DAVID . Analysis results for TSs are presented in Fig. S11. Here, “SS comp” and “SE comp” represent SS and SE components, respectively. Asterisks above the boxplot represent the significance levels compared to “all” genes. and

Figure 4.

Disease association of SSs. Enrichment of GWAS SNPs associated with (A) all traits and (B) traits relevant to immunity, B-cell lymphoma, and CLL. WG is the whole human genome, and BK is the background sequences, i.e., randomly selected DNase-seq peaks in other cell types. (C) Enrichment fold of GWAS SNPs associated with individual traits. “SS comp” and “SE comp” represent SS and SE components, respectively. The asterisks above boxes indicate significant enrichment of the traits having an enrichment fold of in a subgroup of traits. (D) Fraction of replicated GWAS SNPs in different enhancer/silencer types. The asterisks above bars indicate depletion significance levels as compared to SS components. and

Figure 5.

Enrichment of B-cell-cancer variants in GM12878 SSs. (A) Fractions of B-cell-cancer SNVs in different RE types. Fractions of recurrent (B) B-cell-cancer SNVs and (C) non-B-cell cancer SNVs in different enhancer and silencer types. (D) Fractions of B-cell-cancer TLBPs in and by different enhancer and silence types. “IN” and “BY” represent the RE sequences and the genomic regions proximal to enhancers or silencers within. (E) Distribution of target enhancers or silencers of B-cell-cancer translocations (TLs). (F) Genomic and epigenetic profiles in the BCL6 SS (left panel) and IGHM SE (right panel) regions in normal and cancer genomes. “SS comp” and “SE comp” represent SS and SE components, respectively. These two regions are merged by the DLBCL translocation t(3;14)(q27;q32). The distribution of non-B-cell-cancer mutations (i.e., SNVs and TLBPs) is not presented here since close-to-zero non-B-cell-cancer mutations are reported in these regions. Another DLBCL translocation t(3;14)(q27;p14) joints this BCL6 SS region with the RHOH SE region (Fig. S10). The numbers in the track of “DLBCL SE” are the numbers of patients having a SE and all patients. In (A-E), “SS comp” and “SE comp” represent SS and SE components, respectively. “BK” represents the randomly selected DNase-seq peaks in other cell types. Asterisks in bars or above markers indicate significant enrichment in comparison to BK. and.

Figure 6.

Conversion of GM12878 SSs to SEs during carcinogenesis. (A) Enrichment of SS components in the loci of DLBCL-essential and DLBCL suppressor genes. (B) Enrichment of enhancers and silencers in each DLBCL-essential and DLBCL suppressor gene locus. (C) Fractions of GM12878 enhancers and silencers coinciding with DLBCL SE regions. (D) Numbers of DLBCL patients in which SEs were detected. SS-to-SE and TS-to-SE represent the DLBCL SEs converted from GM12878 SSs and TSs, respectively. (E) Average binding intensities of BRD4 (as measured by TF ChIP-seq signals) in DLBCL SEs and BK sequences in DLBCL Ly4 cells. These intensity levels were detected at 24 hours after JQ1 and DMSO treatments. (F) Fractions of genes significantly upregulated and downregulated at different time points following JQ1 treatment. The genes are categorized based on their association with different DLBCL SE groups. (G) Expression levels of BCL2 and BACH2 at different time points following JQ1 treatment in DLBCL cells. “SS comp” and “SE comp” represent SS and SE components, respectively. “BK” is DNase-seq peaks randomly selected from other cell types. Asterisks above bars and violin plots indicate the significance levels in comparison to BK in (A, C) or to all SEs in (D, F, H). and

Figure 7.

Enrichment of SSs in TAD-shores. (A) Distribution of REs in different TAD sections (boundaries, shores, and centers). The pie chart presents the distribution of SSs in TADs. (B) Enrichment of silencers and enhancers in SS-counterpart-TAD-shores. The schematic shows two neighboring TADs. The Shore2 is the counterpart-TAD-shore of the Shore1, and vice versa. Each row in this heatmap represent a TAD boundary. Enrichment fold is calculated through comparing with the whole genome. (C) Enrichment of enhancers in the SS-counterpart-TAD-shores. The values above bars are the significance level as compared to all TAD-shores. CTCF-TAD-shores have no significant preference for enhancers. (D) Enrichment of disease-associated mutations in different RE types across TAD sections. Pie charts are the distribution of mutations in SS components. “BK” is DNase-seq peaks randomly selected in other cell types. “SS comp” and “SE comp” represent SS and SE components, respectively. Asterisks above bars indicate significant enrichment in comparison to BK.

Figure 8.

Repression models of SSs. (A) Enrichment of chromatin contacts to different enhancer and silencer types (as illustrated in bar plots) and contact enrichment between two enhancer and silencer types (in the bubble plots). (B) Two major repression models utilized by silencers. (C) Contact enrichment in proximities of different enhancer and silencer types, with the asterisks indicating significant enrichment in comparison to BK. and. (D) Contact enrichment of promoters which are categorized based on their enhancer or silencer contacts. (E) Numbers of ChIP-seq TFBSs located within silencers and enhancers. (F) Signatures of ChIP-seq TFBSs and epigenetic marks in CGI and non-CGI silencers. All enhancers were used as the background in the top four rows. CGI enhancers were used as background for the bottom two rows. High similarity between the top two and bottom two rows suggests that CGI is one of the factors determining TFBS features of CGI silencers. “BK” is DNase-seq peaks randomly selected from other cell types. “SS comp” and “SE comp” represent SS and SE components, respectively.