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Histone acetylation dynamics modulates chromatin conformation and allele-specific interactions at oncogenic loci

Nature Genetics volume 53, pages 650–662 (2021)Cite this article

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Abstract

In cancer cells, enhancer hijacking mediated by chromosomal alterations and/or increased deposition of acetylated histone H3 lysine 27 (H3K27ac) can support oncogene expression. However, how the chromatin conformation of enhancer–promoter interactions is affected by these events is unclear. In the present study, by comparing chromatin structure and H3K27ac levels in normal and lymphoma B cells, we show that enhancer–promoter-interacting regions assume different conformations according to the local abundance of H3K27ac. Genetic or pharmacological depletion of H3K27ac decreases the frequency and the spreading of these interactions, altering oncogene expression. Moreover, enhancer hijacking mediated by chromosomal translocations influences the epigenetic status of the regions flanking the breakpoint, prompting the formation of distinct intrachromosomal interactions in the two homologous chromosomes. These interactions are accompanied by allele-specific gene expression changes. Overall, our work indicates that H3K27ac dynamics modulates interaction frequency between regulatory regions and can lead to allele-specific chromatin configurations to sustain oncogene expression.

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Fig. 1: Repositioning of enhancer regions in chromatin subcompartment domains.
Fig. 2: Changes in H3K27ac modulate the frequency and size of EPIs.
Fig. 3: Reduction of H3K27ac modulates the frequency and the size of EPIs.
Fig. 4: Depletion of H3K27ac modulates the conformation of the BCL11A enhancer–promoter loop.
Fig. 5: Enhancer region on chr.3 regulates the expression of BCL6 and MYC.
Fig. 6: Allele-specific epigenetic marks and chromatin interactions at the MYC locus.
Fig. 7: Allele-specific epigenetic marks and chromatin interactions at the BCL2 locus.

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Data availability

RNA-seq and H3K27ac ChIP–seq data were obtained as follows: for lymphoblastoid cells from ref. 68 and the ArrayExpress Archive (http://www.ebi.ac.uk/arrayexpress), accession nos. E-MTAB-3656 and E-MTAB-3657, for GM12878 from ENCODE accession nos. GSE78551 and GSM733771, for SU-DHL-4, accession nos. GSM1227199 and GSM1703927, for OCI-LY7, accession nos. GSM1227199 and GSE86708, for DoHH2 ENCODE accession nos. GSM2366283 and GSE86743, for Karpas-422 accession no. GSE86733 (H3K27ac), for primary centrocytes and centroblasts, accession nos. GSE62246 and GSE89688, for five primary follicular lymphoma and two GC diffuse large B-cell lymphoma BLUEPRINT, accession no. EGAD00001001502. WGS data and RNA-seq data were obtained for lymphoma cell lines and for 30 primary DLBCLs and their matched controls from dbGaP (phs000235.v13.p2). WGS data and RNA-seq data for Burkitt’s lymphoma or DLBCL with t(8;14) were downloaded from the Malignant Lymphoma MMML ICGC portal. RNA-seq data were generated for Karpas-422 and WSU-DLCL2 that were nontreated and treated by A-485 and for three independent clones WSU-DLCL2 with BCL11A knockout (data are deposited in the Gene Expression Omnibus database at accession no. GSE168471). CTCF ChIP–seq data were obtained from ENCODE for GM12878 and we generated the data for Karpas-422 and WSU-DLCL2 that were nontreated and treated by A-485 (accession no. GSE168470). H3K36me3 ChIP–seq data were generated for WSU-DLCL2 (accession no. GSE168472). Hi-C data for nontreated WSU-DLCL2 and Karpas-422 were obtained from Donaldson-Collier et al.4 and generated for the treated replicates for the present study (accession no. GSE168470). Source data are provided with this paper.

Code availability

Code availability for Calder method: https://github.com/CSOgroup/CALDER.

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Acknowledgements

We thank EPFL facilities and, in particular, B. Mangeat for the sequencing facility and M. Pujol for cell sorting at CIML. This work was supported by the ISREC Foundation (E.O.), the Swiss National Science Foundation (grant number 31003A_182526) (E.O.) and Swiss Cancer Research foundation (grant number KFS-3982-08-2016-R) (E.O.), and the Gelu Foundation. G.C. is supported by the Giorgi–Cavaglieri Foundation. S.R. is supported by the French National Cancer Institute (INCa) Epigenetic and Cancer program. S.S. has been supported with a Marie Curie EPFL fellow.

Author information

Author notes

  1. Maria Donaldson Collier

    Present address: Division of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands

  2. These authors equally contributed to this work: Stephanie Sungalee, Yuanlong Liu.

Authors and Affiliations

  1. Swiss Institute for Experimental Cancer Research, School of Life Sciences, EPFL, Lausanne, Switzerland

    Stephanie Sungalee, Ruxandra A. Lambuta, Natalya Katanayeva, Maria Donaldson Collier & Elisa Oricchio

  2. Swiss Cancer Center Leman, Lausanne, Switzerland

    Stephanie Sungalee, Yuanlong Liu, Ruxandra A. Lambuta, Natalya Katanayeva, Daniele Tavernari, Giovanni Ciriello & Elisa Oricchio

  3. Department of Computational Biology, University of Lausanne, Lausanne, Switzerland

    Yuanlong Liu, Daniele Tavernari & Giovanni Ciriello

  4. Swiss Institute of Bioinformatics, Lausanne, Switzerland

    Yuanlong Liu, Daniele Tavernari & Giovanni Ciriello

  5. Aix-Marseille University, CNRS, INSERM, Centre d’Immunologie de Marseille-Luminy, Marseille, France

    Sandrine Roulland

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Contributions

S.S. was involved in the experimental design. Y.L. developed a new method and analyzed Hi-C data. S.S. and Y.L. analyzed Hi-C, UMI-4C and ChIP–seq data, and performed the phasing analyses. M.D.C., R.L. and N.K. prepared Hi-C, UMI-4C, ChIP- and RNA-seq libraries, and performed all experimental validations. D.T. analyzed and normalized ChIP–seq data. S.R. obtained and sorted the germinal center cells and prepared cells for ChIP and Hi-C library preparation G.C. supervised the computational analyses. E.O. designed the study and wrote the manuscript, with comments from all authors.

Corresponding author

Correspondence to Elisa Oricchio.

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The authors declare no competing interests.

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Peer review information Nature Genetics thanks Berkley Gryder, Rolf Ohlsson and the other, anonymous, reviewer for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Genome-wide analyses of H3K27ac changes and chromatin sub-compartments.

a. t-SNE plot based on the levels of H3K27ac in 9250 MERs in lymphoblastoid samples (n = 76, blue, GM12878 in dark blue), GC, (n = 5 green), and GC-DLBCL (n = 5, red). b. Heatmap and clustering of 5 cell lines based on the Pearson’s correlation coefficients (values are indicated and color coded) between H3K27ac levels of MERs (n = 1644). c. Heatmap and clustering of 4 cell lines analyzed by Hi-C based on the Pearson’s correlation coefficients (values are indicated and color coded) between compartment domain ranks of MERs (n = 1644). d. For each pair of cell lines a scatterplot comparison shows the difference of compartment domain ranks computed by CALDER (x-axis) and of H3K27ac levels (y-axis) computed for each enhancer region (dots). Enhancer regions exhibiting concordant changes are color-coded (red positive differences, >5%, blue negative differences <−5%). For each comparison, the radius of the circle comprising 90% of the points (R90) is shown. e. For each comparison, Pearson’s correlation coefficient (x-axis) between differences of compartment domain ranks and of H3K27ac. Distribution of correlation values (colored) are compared to expected distributions (gray). f-g. Comparison of compartment domain rank differences computed with CALDER between (f) Karpas-422 and GC cells (x-axis) and Karpas-422 and GM12878 (y-axis) and between (g) WSU-DLCL2 and GC cells (x-axis) and WSU-DLCL2 and GM12878 (y-axis). Each dot is a merged enhancer region color coded by the difference of H3K27ac between Karpas-422 (left) or WSU-DLCL2 (right) and GC h. Overlap of repositioned enhancer regions towards a more active (red) or inactive (blue) sub-compartments in Karpas-422 and WSU-DLCL2 cells with respect to GM12878. P-values and odds-ratio (OR) were computed by two-sided Fisher’s exact test. i. Comparison of compartment domain rank differences computed with CALDER between (left) Patient 1 and GC cells (x-axis) and Patient 1 and GM12878 (y-axis) and between (right) Patient 7 and GC cells (x-axis) and Patient 7 and GM12878 (y-axis). j. Overlap of repositioned enhancer regions towards a more active (red) or inactive (blue) sub-compartments in Patient 1 and Patient 7 with respect to GM12878. P-values and odds-ratio (OR) were computed by two-sided Fisher’s exact test.

Extended Data Fig. 2 Genome wide analyses of enhancer promoter interactions (EPIs) and changes in H3K27ac.

a. Graphical representation of enhancer-promoter interactions (EPIs, top) analysis. The total number of tested and significant EPIs is reported for each cell line. b. Fraction of significant EPI that are expected (top) and that were observed (bottom) to occur between enhancers and promoters within the same compartment domain. c. Percentage of significantly different EPIs (y-axis) which are more frequent either in GC than in the indicated lymphoma samples (blue bars) or in lymphoma samples than in GC (red bars). Results are shown for enhancer regions that were repositioned from inactive to active compartment (left) or from active to inactive compartment (right) in lymphoma samples with respect to GC. d. Fold-change between the observed and expected number of significantly more frequent EPIs (y-axis) in Karpas-422 than in GM12878 (left) and in GC (right) with respect to the difference in H3K27ac in these regions. e. Number of significant interactions per EPI (that is, number of bins of the Hi-C map with significantly frequent interactions between the enhancer and promoter regions) (x-axis) with respect to the difference in H3K27ac in these regions. Results are shown for EPIs that were more frequent in Karpas-422 than in GM12878 (top) or in GC (bottom). f. Representative western blot image (n=2 independent experiments) detecting the H3K27ac and histone-3 treated with DMSO (vehicle) or 0.2 μM and 0.5 μM A-485 for 48h in the indicated lymphoma cell lines. g. Quantification of cell survival of Karpas-422 and Su-DHL-4 cells treated with 0.5 μM and 1μM A-485 or DMSO. h. Density plot of the p-values inferred by HiC-DC for each interaction in WSU-DLCL2 and Karpas-422 Hi-C maps connecting bins at most 2 Mb apart. P-values below 0.05 (left of black dashed line) indicate significant contacts.

Source data

Extended Data Fig. 3 Chromatin conformation analyses of BCL11A region upon pharmacological depletion of H3K27ac.

a. Representation of 20kb interacting regions on chr.2: 60.46–60–86 Mb color coded based on their q-value in Karpas-422 cells untreated and treated with A-485 inhibitor (top) and corresponding ChIP-sequencing track of H3K27ac (NRPM) (botton). b. Representative H3K27ac ChIP sequencing tracks for the indicated genomic locus of lymphoblastoid samples, GC, lymphoma cells and lymphoma patients (NRPM). Patient 1 and Patient 7 are reported as RRPM x 10−2. c. Spearman correlation plot of H3K27ac levels and BCL11A expression in 70 lymphoblastoid samples. two-tailed p value is calculated from the t-statistics of the corresponding correlation value. d. BCL11A expression levels in GC-DLBCL patients (n=30) and lymphoblastoid cells (n=70). The thick central line of each box plot represents the median expression value, the bounding box corresponds to the 25th–75th percentiles, and the whiskers extend up to 1.5 times the interquartile range. p-value was calculated with two tailed t-test. e. Quantification of expression changes of BCL11A upon treatment with A-485 0.5 μM for 48h in Karpas-422 (n= 6) and WSU-DLCL2 (n= 3) compared to the same cells treated with DMSO (vehicle Karpas-422 n= 5 and WSU-DLCL2 n=3). The black dots represent the number of independent experiments. Data are presented as mean value + SD. p-value were calculated using unpaired two-tailed t-test f. Hi-C contact maps of chr.2: 60.16–61.46 Mb region in Karpas-422 and WSU-DLCL2 cells untreated and treated with A-485. The lines in black delineate the compartment domains. The position of relevant genes is indicated. g. CTCF ChiP-seq tracks of chr.2: 60.16–61.46 Mb region in Karpas-422 and WSU-DLCL2 treated and untreated with A-485 (RPM). The detection of CTCF and their orientation is reported.

Extended Data Fig. 4 Chromatin conformation analyses of BCL11A region upon genetic modification of H3K27ac.

a. Quantification of BCL11A expression changes in Su-DHL-4 cells expressing dCas9-KRAB-sgRNA1, dCas9-KRAB-sgRNA2, dCas9-KRAB-sgRNA3 compared to cells expressing dCas9-KRAB. n=3 independent biological replicates. Data are presented as mean value + SD p-value were calculated by unpaired two-tailed t-test. b. H3K27ac ChIP sequencing tracks in Su-DHL-4 labelled with the position of the primers used for ChIP-qPCR and quantification of H3K27ac by ChIP-qPCR with the indicated primers. n=3 independent biological replicates. Data are presented as mean value ± SD. p-value were calculated by unpaired two-tailed t-test c. H3K27ac ChIP sequencing tracks in Su-DHL-4 on the regions on chr.2 (60.85–61.45 Mb) flanking the BCL11A region (RRPM x10−3). d. Hi-C contact map and ChIP sequencing track of H3K27ac (RPM) in K562 cells in the indicated genomic region. e. Representation of 20kb interacting regions on chr.2: 60.46–60–86 Mb color coded based on their q value in K562 cells. f. Representation of the number of reads spanning BCL11A exon2 detected by RNA-sequencing in K562 cells expressing dCas9-EP300 and dCas9-EP300-sgRNA2. g. Representative western-blot image (n=2) of BCL11A and tubulin in WSU-DLCL2 cells (control) and three independent BCL11A knock-out clones (KO#2, KO#12, KO#25). h. Bar plot of the representative gene set enriched categories that significantly scored.

Source data

Extended Data Fig. 5 Analyses of the chromatin structure in BCL6 and MYC loci.

a. Representative ChIP sequencing tracks of H3K27ac in lymphoblastoid cells, GC, DLBCL tumor cells, and in primarylymphoma samples (NRPM), Patient 1 and Patient 7 are reported as RRPM x10−2. b-c. Representation of 20kb interacting regions in chr.3 187.4–188.7 Mb color coded based on their q value (top) in Karpas-422 untreated (b) or treated with A-485 inhibitor (c) and corresponding H3K27ac ChIP-sequencing (NRPM). d. Quantification of expression changes of BCL6 upon treatment with A-485 0.5 μM for 48h in Karpas-422 (n=6) and WSU-DLCL2 (n=6) compared to the same cells treated with DMSO (vehicle, n=5). The black dots represent the number of independent experiments. Data are presented as mean value + SD. p-value were calculated using unpaired two-tailed t-test. e. Representation of copy number changes detected on chr. 8 and chr. 3 and graphical representation of the derivative chromosome t(3;8). f. Hi-C inter-chromosomal contact maps of chr.8 and chr.3 in the region spanning the breakpoint in WSU-DLCL2 cells. g. ChIP-sequencing track of H3K27ac (blue, NRPM) and UMI-4C domainogram with two different bait-primers representing the mean number of contacts (% of the maximum) on chr.8 spanning the breakpoint in WSU-DLCL2 cells treated with A-485 (0.5 μM for 48h) or DMSO as control.

Extended Data Fig. 6 Epigenetic marks distributed to each copy of chromosome 8 based on their haplotype.

a. Schematic representation of the phasing protocol used to define the haplotypes of the two copies of chr. 8. b.H3K27ac and H3K36me3 signal distribution in wild-type (WT) and translocated chromosome (TRA) in WSU-DLCL2 cells between chr.8:128,745–128,755 Mb region c. H3K27ac ChIP tracks of chr.8 indicated region in Karpas-422. In grey the total number of reads, in blue the number of reads with SNPs mapping on the haplotype 1 and red the number of reads with SNPs mapping on the haplotype 2 (NRPM). d. Representation of the reads distribution in whole genome sequencing (WGS), H3K27ac and H3K36me3 ChIP sequencing in the indicated genomic regions. In grey, genomic positions without detected SNPs and in two color bars genomic position with detected SNPs. e. H3K27ac and H3K36me3 ChIP tracks in the chr.8 indicated region (NRPM). In grey the total number of reads, in blue the reads with SNPs mapping on the haplotype 1 and red the number of reads with SNPs mapping on the haplotype 2. f. Quantification of the number of reads spanning the chr8:129,047,325 SNP harboring an adenine (A) or a guanine (G) detected by whole genome sequencing (WGS) and RNA- sequencing (RNA-seq) in Karpas-422 cells.

Extended Data Fig. 7 Chr.14–18 inter-chromosomal interactions in samples with and without translocation.

a-d. Hi-C inter-chromosomal contact maps of chr.14 and chr.18 in the region spanning the breakpoint in WSU-DLCL2 cells (a), Patient 1(b), GC (c) and Patient 7 (d).

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Unprocessed western blots.

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Unprocessed western blots.

Source Data Extended Data Figure 4

Unprocessed western blots.

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Sungalee, S., Liu, Y., Lambuta, R.A. et al. Histone acetylation dynamics modulates chromatin conformation and allele-specific interactions at oncogenic loci. Nat Genet 53, 650–662 (2021). https://doi.org/10.1038/s41588-021-00842-x

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