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Locus-specific induction of gene expression from heterochromatin loci during cellular senescence

Nature Aging volume 2, pages 31–45 (2022)Cite this article

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Abstract

Senescence is a fate-determined state, accompanied by reorganization of heterochromatin. Although lineage-appropriate genes can be temporarily repressed through facultative heterochromatin, stable silencing of lineage-inappropriate genes often involves the constitutive heterochromatic mark, histone H3 lysine 9 trimethylation (H3K9me3). The fate of these heterochromatic genes during senescence is unclear. In the present study, we show that a small number of lineage-inappropriate genes, exemplified by the LCE2 skin genes, are derepressed during senescence from H3K9me3 regions in fibroblasts. DNA FISH experiments reveal that these gene loci, which are condensed at the nuclear periphery in proliferative cells, are decompacted during senescence. Decompaction of the locus is not sufficient for LCE2 expression, which requires p53 and C/EBPβ signaling. NLRP3, which is predominantly expressed in macrophages from an open topologically associated domain (TAD), is also derepressed in senescent fibroblasts due to the local disruption of the H3K9me3-rich TAD that contains it. NLRP3 has been implicated in the amplification of inflammatory cytokine signaling in senescence and aging, highlighting the functional relevance of gene induction from ‘permissive’ H3K9me3 regions in senescent cells.

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Fig. 1: Aberrant expression of lineage-inappropriate LCE2 genes during senescence.
Fig. 2: Decompaction of EDC locus in senescent IMR90 cells.
Fig. 3: Decompaction of EDC locus and senescence effectors.
Fig. 4: H3K9me3 peak characterization.
Fig. 5: Aberrant expression of lineage-specific genes and chromatin decompaction during senescence.
Fig. 6: Distinct mode of expression of lineage-appropriate and lineage-inappropriate genes during RIS.
Fig. 7: Differential 3D behavior of permissive H3K9me3 peaks.

Data availability

Human KC RNA-seq, ChIP-seq data, IMR90 ATAC-seq data (RIS) and RNA-seq data generated for the present study have been deposited at the GEO (accession nos. GSE130457 and GSE180469). Control ATAC-seq data were previously published (accession no. GSE103590)9. Microarray datasets (Extended Data Fig. 1) have been previously published (accession nos. GSE53379 and GSE59522)15,26. RNA-seq data for RIS/DDIS IMR90 cells are available at accession no. GSE72407 (ref. 21). Other senescence RNA-seq data17,18 were downloaded from GSE61130 (ref. 17), GSE74238 (ref. 6), GSE45833 (ref. 18), GSE85082, GSE63577, GSE56293 and GSE130306 (ref. 19). SF RNA-seq was downloaded from accession no. GSE163749 (ref. 46). HPA RNA-seq data were downloaded from the HPA (https://www.proteinatlas.org), accession no. E-MTAB-2836 (ref. 34). THP-1 RNA-seq data were downloaded from accession no. GSE96800 (ref. 45). ChIP-seq for H3K9m3, H3K27me3 (ref. 10), H3K27ac9 and Lamin B1 (ref. 11) are available at accession nos. GSE38448, GSE103590 and GSE49341, respectively. ChIP-seq data for hES cells were downloaded from ENCODE, accession no. GSE29611 (ref. 63). H3K27ac ChIP-seq and ATAC-seq data for THP-1 cells were downloaded from the GEO, accession no. GSE96800 (ref. 45). Hi-C data (IMR90 cells) can be found at accession no. GSE135090. Hi-C data (human KCs) were downloaded from accession no. GSE84660. Hi-C data (THP-1 cells) were downloaded from the Sequence Read Archive accession no. PRJNA385337 (ref. 45). Hi-C data (WI38 cells) were downloaded from accession no. GSE130306 (ref. 19). Source data are provided with this paper.

Code availability

No customized code was used. FISH signal length measurement was performed using LAS-AF software (v.4.0.0). X–Z re-sliced images were generated from Z-stack images using ImageJ (v.2.1.0). GraphPad Prism 6.0, 7.0, 8.0 and 9.0 were used for general statistical analyses. For sequence data analysis, BWA (v.0.7.12), Cutadapt (v.1.10.0), ChIPQC Bioconductor package (v.1.14.0), MACS2 (v.2.1.0), bedtools (v.2.26.0), EDD (v.1.1.19), THOR (v.0.11.4), STAR aligner (v.2.5.3a), Rsubread (v.1.5.2), edgeR (v.3.20.9), GEOquery package (v.2.60.0), limma package (v.3.48.3), HiC-Pro (v.2.10.0), FastQC (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/), diffHiC (v.1.10.0) and HiCvizR (v.3.4.4) were used.

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Acknowledgements

We thank all members of the Narita laboratory for helpful discussions, A. Young for editing and the staff of the CRUK-CI core facilities (Microscopy, Genomics, Biorepository, Bioinformatics and Research Instrumentation) for technical support, and T. Tsuda and E. Nishihama at the Ehime University for isolation and expansion of human primary KCs. This work is supported by a Cancer Research UK Cambridge Institute core grant (no. C9545/A29580) to Masashi N.’s laboratory, and in part by the Human Frontier Science Program (no. RGY0078/2010) (to Masashi N.). Masashi N. is also supported by the Medical Research Council (MRC) (MR/M013049/1 and MR/R010013/1), BBSRC (BB/S013466/1) and Diabetes UK via BIRAX and the British Council (65BX18MNIB). I.O. is supported by the Cancer Research UK Pioneer grant (no. C63389/A30462). S.A.S and D.B. are supported by the MRC (MC_UU_12022/10). S.S. is supported by the UKRI Biotechnology and Biological Science Research Council (BB/J004480/1), the UKRI MRC (MR/T016787/1) and a Career Progression Fellowship from the Babraham Institute. P.J.R.-G. is supported by the BBSRC (BBS/E/B/000C0422), the MRC (MR/T011769/1 and MR/N018419/1) and the Wellcome Trust (215116/Z/18/Z). H.K. is supported by JSPS KAKENHI (nos. JP17H01417 and JP18H05527). The funders had no role in study design, data collection and analysis, the decision to publish or the preparation of the manuscript.

Author information

Author notes

  1. Kosuke Tomimatsu

    Present address: Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan

  2. Dóra Bihary

    Present address: VIB-KU Leuven Center for Cancer Biology, Leuven, Belgium

  3. Yoko Ito

    Present address: International University of Health and Welfare, Tochigi, Japan

  4. Kristina Kirschner

    Present address: Institute for Cancer Sciences, University of Glasgow, Glasgow, UK

  5. Camino Bermejo-Rodriguez

    Present address: Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, UK

  6. These authors contributed equally: Dóra Bihary, Ioana Olan.

Authors and Affiliations

  1. Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK

    Kosuke Tomimatsu, Ioana Olan, Aled J. Parry, Adelyne S. L. Chan, Guy St. C. Slater, Yoko Ito, Kristina Kirschner, Camino Bermejo-Rodriguez, Masako Narita & Masashi Narita

  2. Shiga University of Medical Science, Shiga, Japan

    Kosuke Tomimatsu

  3. MRC Cancer Unit, Hutchison/MRC Research Centre, University of Cambridge, Cambridge, UK

    Dóra Bihary & Shamith A. Samarajiwa

  4. Epigenetics Programme, The Babraham Institute, Cambridge, UK

    Aled J. Parry, Stefan Schoenfelder & Peter J. Rugg-Gunn

  5. Nuclear Dynamics Programme, The Babraham Institute, Cambridge, UK

    Stefan Schoenfelder & Peter Fraser

  6. Department of Biomedical Science, Institute of Regenerative Medicine and Biofunction, Graduate School of Medical Science, Tottori University, Yonago, Japan

    Tomomi Seko & Hiroyuki Kugoh

  7. Chromosome Engineering Research Center, Tottori University, Yonago, Japan

    Tomomi Seko & Hiroyuki Kugoh

  8. Department of Dermatology, Graduate School of Medicine, Ehime University, Toon, Japan

    Ken Shiraishi & Koji Sayama

  9. Tokyo Tech World Research Hub Initiative and Cell Biology Center, Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan

    Hiroshi Kimura & Masashi Narita

  10. Department of Biological Science, Florida State University, Tallahassee, FL, USA

    Peter Fraser

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  1. Kosuke Tomimatsu
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Contributions

Masashi N., S.A.S. and K.T. conceived the project. K.T., A.J.P., S.S., Y.I., K.K., C.B.R., Masako N., T.S., H. Kugoh, P.J.R.-G., P.F. and Masashi N. designed and performed experiments, and analyzed the data. D.B., I.O., G.St.C.S., A.S.L.C. and S.A.S analyzed the sequencing data. I.O. analyzed the Hi-C data. H. Kimura provided histone antibodies. K. Shiraishi and K. Sayama provided the human KCs. Masashi N. and K.T. wrote the manuscript with input from all authors.

Corresponding authors

Correspondence to Masako Narita, Shamith A. Samarajiwa or Masashi Narita.

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Competing interests

P.F. and S.S. are co-founders of Enhanc3D Genomics Ltd. All other authors declare no competing interests.

Peer review information Nature Aging thanks Peter Adams, Rugang Zhang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Peer review information Nature Aging thanks Peter Adams, Rugang Zhang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Transcriptional profile of genes in the EDC locus.

(a) Image corrected, quantile normalized and log2 transformed microarray intensity values were downloaded from the indicated NCBI GEO entries. Control, proliferative; RIS, HRAS-G12V-induced senescent; Qui, quiescent; DDIS, DNA damage-induced senescent; acDDR, acute DNA damage response to etoposide (24 or 48 hours); E1A + RAS, transformed/senescence-bypassed. Genes for which there is no available transcript probe on the microarray platform used are greyed out. (b) Meta-analysis of senescence-associated transcriptomic changes of genes in the EDC locus using RNA-seq datasets, downloaded from indicated NCBI GEO, comparing between different cellular phenotypes. The datasets were processed using the same analysis pipeline. Values for the indicated genes are shown for each of the senescent samples and their corresponding growing controls. Values are Transcripts-Per-Million (TPM). Genes are ordered according to their position along Chr. 1. Genes for which there were no aligned reads in the specified RNA-seq runs are greyed out. (c) Immunoblot analysis of IMR90 cells stably expressing vector (-) or HRAS-G12V and control miR30 vector (-) or sh-p53 (+) for the proteins indicated. Arrow indicates specific bands. p21 is a p53-dependent cell cycle inhibitor that is upregulated during senescence. Experiments were performed at least 3 times. (d-e) IMR90 cells expressing ectopic mVenus-LCE2A and control vector were assessed for cumulative population doublings (d) and colony formation capacity P-value: 0.0193 (Two-tailed Paired t-test) (e) (n = 3). Error bars indicate mean + /− SD. The inset shows representative immunoblots of indicated protein (d).

Extended Data Fig. 2 Correlation between EDC decompaction and SAHF formation.

(a) 3D confocal images of DNA-FISH for the EDC locus in the cells indicated (see Fig. 2a for two alternate color probe designs). The perinuclear localization of the EDC locus was quantified on visual inspections by counting FISH signal, which attached at least 1 of the 7 tiled signals to the nuclear periphery (white arrowhead). Bars are % of signals on the nuclear periphery (n > 100 alleles from 3 biological replicates). (b) Representative images of DNA-FISH for the EDC and OR loci using the probes indicated and quantification of signal length. Note, for the EDC, 5 out of 7 probes (Fig. 2a) were used. Bars are median with inter-quartile range. Two-tailed Mann-Whitney-Wilcoxon test (n ≥ 107 alleles from 3 biological replicates) (c) FISH signal length of EDC on SAHF-negative or positive RIS cells. Bars are median with inter-quartile range. Two-tailed Mann-Whitney-Wilcoxon test (n = 100 alleles from 3 biological replicates). (d) LCE2 immunofluorescence signal on SAHF-negative or positive RIS cells (n = 3). (e-h) Quantification of SAHF-positive cells in the indicated conditions (e, g) and comparative analysis of LCE2 expression by immunoblotting in the conditions indicated (f, h). Arrows indicate specific bands on the immunoblotting. Bars indicate mean + /- s.e.m. One-way ANOVA with Tukey’s multiple comparisons test (n = 3 biological replicates) (e left, g). Two-tailed unpaired t-test (n = 3 biological replicates) (e right). (i) Quantification of FISH signal length in the conditions indicated for BJ and WI38 cells. Bars are median with interquartile range. Two-tailed Mann-Whitney-Wilcoxon test (n = 150 alleles from 3 biological replicates).

Extended Data Fig. 3 H3K9me3 exhibits increases in accessibility and H3K27ac ChIP-seq signal in RIS.

(a) ATAC-seq and H3K27ac THOR-normalized signal in proliferative and RIS cells centred on three classes of ATAC-seq peaks: proliferative-specific, RIS-specific, and common between the two conditions. (b) Number of ATAC-seq (top) and H3K27ac (bottom) peaks (in the consensus peak sets in the n = 3 proliferative and n = 3 RIS ATAC-seq samples and n = 4 proliferative and n = 4 RIS H3K27ac ChIP-seq samples) across the three groups of H3K9me3 peaks defined as permissive (group 2 n = 110 peaks and group 3 n = 26 peaks) and non-permissive (group 1 n = 627 peaks). The boxplots correspond to the median, 25th to 75th percentiles, and the whiskers correspond to the 10th to 90th percentiles. (c) IGV tracks of genes of interest and position of SINE and Alu repeats (UCSC annotation) over their gene bodies. (d) Region surrounding the SERPINA1 gene characterised by H3K9me3 ChIP-seq signal, as well as protruding H3K27ac and ATAC-seq peaks.

Extended Data Fig. 4 Tissue specificity of genes in H3K9me3 peaks.

(a) Tissue specificity score of the genes within the three groups of H3K9me3 peaks (group 1 n = 627 peaks, group 2 n = 110 peaks and group 3 n = 26 peaks) against all other genes. The Tau score ranges from 0 - ubiquitous expression across tissues to 1 - tissue specific; the 8 genes of interest in group 3 are highlighted. Significance testing was performed with two-sided Student’s t-tests, ***P < 0.001, n.s., not significant. The exact P-values are: 1 vs 2 0.7492, 2 vs 3 1.281e-06, 1 vs 3 1.594e-13, 1 vs Other 2.2e-16, 2 vs Other 2.2e-16, 3 vs Other 1.944e-07. The boxplots correspond to the median, 25th to 75th percentiles, and the whiskers correspond to the 10th to 90th percentiles. (b) DCC (left) and TMEM132B (right) genes represented by multiprobe DNA-FISH signals in the proliferative and RIS conditions. Probe sets are shown in Fig. 5b. Note, single colour probe images are shown for TMEM132B.

Extended Data Fig. 5 Three-dimensional interaction changes occurring during RIS.

(a) 200 kb resolution Hi-C maps in proliferative and RIS cells as well as significant interaction changes between the two conditions, where green arcs represent increases and blue arcs represent decreases. (b) Significant H3K9me3-H3K9me3 interaction changes (200 kb bins): log-fold changes (logFC) against distance between the interacting regions, dotted line corresponds to 10 Mb distance. (c) Hi-C interaction profiles at 40 kb resolution in proliferating (Prolif) and RIS IMR90 cells as well as differentiating keratinocytes at the EDC/OR loci. (d) Epigenetic profile of the NLRP3 locus in terms of H3K9me3, LaminB1 and H3K27me3 THOR-normalized ChIP-seq signal in proliferating and RIS cells. (e) Normalized gene expression (log-counts per million) of pro-inflammatory genes, EDC genes and senescence-representative genes in -/MSU and MSU/MSU synovial fibroblasts. *Adjusted P < 0.05, **P < 0.01, ***P < 0.001.

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43587_2021_147_MOESM2_ESM.xlsx

Supplementary Table: Genes included in each H3K9me3-peak group. List of genes within the three types of H3K9me3 peaks determined; 38 genes significantly upregulated in group 3 are shown in bold text.

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Tomimatsu, K., Bihary, D., Olan, I. et al. Locus-specific induction of gene expression from heterochromatin loci during cellular senescence. Nat Aging 2, 31–45 (2022). https://doi.org/10.1038/s43587-021-00147-y

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