# Extracellular matrix stiffness modulates nuclear lamina organisation and sets nuclear conditions for PRC2 repression

Alexia Pigeot, Martin Rey-Millet, Amal Zine El Aabidine, Antonio Trullo, Lea Costes, Manoel Manghi, Kerstin Bystricky, Jean-Christophe Andrau, Cyril Esnault

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## To cite this version:

Alexia Pigeot, Martin Rey-Millet, Amal Zine El Aabidine, Antonio Trullo, Lea Costes, et al. Extra-cellular matrix stiffness modulates nuclear lamina organisation and sets nuclear conditions for PRC2 repression. 2025. hal-05339295

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1 **Extracellular matrix stiffness modulates nuclear lamina organisation and sets nuclear conditions for PRC2 repression.**

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Alexia Pigeot¹, Martin Rey-Millet², Amal Zine El Aabidine¹, Antonio Trullo¹, Lea

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Costes², Manoel Manghi³, Kerstin Bystricky², Jean-Christophe Andrau¹# and Cyril

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Esnault¹#

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¹ Institut de Génétique Moléculaire de Montpellier, University of Montpellier, CNRS-UMR 5535, 1919 Route de Mende, 34293 cedex 5, Montpellier, France.

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²Université de Toulouse, CNRS, Centre de Biologie Integrative, CBI, MCD, Toulouse, France.

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³ Université de Toulouse, CNRS, Laboratoire de Physique Théorique, IRSAMC, Toulouse, France.

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# Corresponding authors:

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cyril.esnault@igmm.cnrs.fr and jean-christophe.andrau@igmm.cnrs.fr
19 Abstract

Capability of cells to respond to tissue-level elasticity has important physiological and pathological implications. Stiffening of the extracellular matrix (ECM) promotes invasive behaviour of cancer cells, supports the transformation of fibroblasts into cancer-associated fibroblasts and primes stem cell differentiation programs. Here, we investigated how ECM stiffness modulates the Nuclear Lamina (NL) and its impact on gene expression programs, epigenetic marking and 3D genome organisation. By combining hydrogel cell culturing of primary fibroblasts, genomics and super-resolution microscopy, we found that ECM stiffness modifies composition of the NL, modulates long range chromatin interactions, induces changes in chromatin motion and regulates thousands of genes. We identified a specific set of genes coding proteins involved in pathways related to mechanical adaptation such as adhesion and signalling. These genes harbour an apparent bivalent chromatin signature and are expressed under soft condition while repressed in stiff condition through Polycomb Repressive Complex 2 (PRC2). We found that this stiffness-specific repression is tempered by mechano-transduction and the NL. This work uncovers mechano-dependent NL composition, changes in 3D genome organisation and in chromatin motion which underlie adaptive gene expression programs controlled through PRC2.

37 Introduction

Mechano-sensation controls morphogenesis, tissue maintenance and regulates cellular homeostasis, behaviour and commitments. Mechanical cues arise from both active forces such as shear, compression or stretch and from forces generated by the cell itself resisting to viscoelastic properties of the extracellular matrix (ECM) or the surrounding cells ¹,². Modifications of the ECM stiffness is of physiological and pathological importance. It regulates mesenchymal and epidermal stem cell fates ³,⁴, invasiveness of cancer cells ⁵ and influences fibroblast transformation into cancer associated fibroblasts (CAFs) ⁶,⁷. Mechanical properties of the ECM can fluctuate from tissues mechanics ⁸, during tumour growth ⁵ or with aging ⁹. Generally, long-term cell function is sensitive to environmental cues which remodel the epigenetic status and expression programs ¹⁰. But, how are epigenetics and gene expression regulation established in response to mechanical cues remain largely elusive: in particular how mechanical transmission of forces to the Nuclear Lamina (NL) impacts chromatin properties and genome organisation, as well as the physiological relevance of such modifications and the definition of gene sets sensitive to nuclear mechanics.

Cell adhesion to ECM and mechano-transduction involve focal adhesion (FA) complexes and actin cytoskeleton reorganisation ¹¹. Actin polymerisation in response to increasing stiffness of the ECM alters the rates of globular actin (G-actin) and filamentous actin (F-actin) pools. A decrease in the limited G-actin pool leads to Myocardin-Related Transcription Factors (MRTFs) activation which in turn co-activate the Serum Response Factor (SRF) and its expression programs ¹²⁻¹⁵. Similarly,
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59 increased actomyosin cytoskeleton tension promotes YAP/TAZ transcription factor activity ¹⁶. In addition to these well-established transcriptional systems, a direct 60 implication of the NL in gene expression program regulation in response to mechanical 61 cues remains largely unknown. 62

63 The cytoskeleton is physically connected to the NL through the Linker of 64 Nucleoskeleton and Cytoskeleton (LINC) complex, composed of SUN and Nesprin 65 proteins ¹⁷, which transmit mechanical forces to the nucleus ¹⁸,¹⁹. The NL is a 66 meshwork of nuclear intermediate filaments lining the inner part of the nucleus 67 consisting of Lamin A and C isoforms, encoded by *LMNA* gene, and Lamin-B1 and B2 68 respectively encoded by *LMNB1* and *LMNB2*. The latter are ubiquitously expressed 69 while Lamin-A/C expression is acquired through cell differentiation and development 70 ²⁰,²¹. Lamin-A/C expression tunes with ECM stiffness ⁸ and acts as a nucleoskeleton 71 by regulating nuclear mechanics ²².

72 Mechanical cues may also directly act at the chromatin level. In the nucleus, the 73 genome is organized in functional domains exhibiting features that show preferential 74 chromatin interactions delimiting Topologically Associating Domains (TADs) ²³⁻²⁶. 75 Large chromatin regions are also found at the nuclear periphery in association with 76 the NL creating the Lamina Associating Domains (LADs). LADs mainly contain 77 transcriptionally inactive genes and are enriched in repressive histone marks such as 78 H3K27me3 and H3K9me2/3 ²⁷⁻³¹. Some LADs are constitutively found and shared 79 between various cell types (cLAD) while facultative LADs (fLADs) are cell-type specific 80 and acquired during cell differentiation ³²,³³. Genome organisation is not static: local 81 chromatin fibre folding varies from cell to cell and protein complexes stochastically 82 coalesce and diffuse. Chemical stimuli or external forces could modulate epigenetic 83 states. Mechanical transmission of forces to the NL and to chromatin could thus impact 84 chromatin dynamics. ECM elasticity tunes the expression of NL components such as 85 Lamin-A types or the Lamin-B Receptor (LBR) inclusion and affects NL properties ⁸,³⁴. 86 Hence, mechano-sensation and nuclear mechanics may have a direct impact on gene 87 expression through the NL.

88 Finally, mechanical cues also signal on epigenetic marking and histone 89 modifications. Histone modifications characterise promoters and regulatory elements 90 in active, inactive or poised states ³⁵. H3K27me3 is a mark deposited by the Polycomb 91 Repressive Complex 2 (PRC2) and associated with gene repression ³⁶. Acute 92 mechanical strain leads to global gene repression with increased H3K27me3 marking, 93 in an actin dependent manner ³⁷,³⁸. H3K4me3 is found at most promoters which 94 globally correlates with the level of transcription but which can also be found at inactive 95 loci ³⁹,⁴⁰. Both marks can be associated at the same genomic locations, defining 96 bivalent promoters that are generally poised for transcription ⁴¹,⁴². Bivalent promoters 97 were first described in mouse embryonic stem (ES) cells and found to mark 98 developmental genes ⁴³⁻⁴⁷. They are not restricted to pluripotent cells and were 99 observed in differentiated cells where their roles remain uncharacterised ⁴⁵⁻⁴⁸.
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Interestingly, recent works associate ECM niche stiffening with reduced ability to activate bivalent genes for efficient self-renewal and differentiation of hair follicle stem cells during aging ⁹.

To uncover the impact of ECM stiffness on chromatin organisation and gene expression, we cultured primary human fibroblasts (BJ) on polyacrylamide hydrogels mimicking physiological stiffness: 0.5kPa (soft), observed near the vascular parts of the bone marrow or of soft primary solid tumours and 50kPa (stiff), found at the proximity of bones or in fibrotic tumours ⁴⁹⁻⁵¹. We found that nuclear flattening and stiffening following exposure to stiff substrate reduces long-range 3D chromatin contacts and chromatin mobility especially in areas close to the nuclear periphery. In addition, we identified 310 genes with apparent bivalent chromatin more frequently associated to the NL and whose repression under stiff condition requires NL components. Our study suggests that nuclear reorganisations driven by mechanical cues regulate gene expression not only through chromatin landscape modifications but also through the regulation of chromatin motion.

## 115 Results

### 116 Extracellular matrix stiffness tunes nuclear lamina organisation.

Hydrogels have emerged in the last decades for cell culture, they mimic salient elements of native extracellular matrices (ECMs), have tuneable mechanics ranging from soft to stiff tissues, and can support cell adhesion and protein sequestration ⁵². We have used hydrogels of 0.5kPa (soft) and 50kPa (stiff) to study responses to extracellular matrix stiffness in primary fibroblast (BJ cells) and to mimic mechanical conditions to which fibroblast cells are exposed to (Fig. 1a). Using confocal microscopy, we confirm cytoskeleton modifications with increased cell surface, enhanced staining of actin stress fibres (phalloidin) and increased adhesion foci marked with Vinculin under stiff hydrogels (Fig. 1b).

Nuclear shape is also sensitive to ECM stiffness as previously shown ⁸ with small and wrinkled nuclei on soft matrix, and smoothed-out and flattened nuclei on stiff matrix (Fig. 1b). We confirm and extend this observation using western blotting of the main NL components. We found increased levels of Lamins A/C and B1 under stiff condition while Emerin and LBR signals are stronger under soft condition (Fig. 1c, Extended Data Fig. 1a). We also note a change in gel mobility of LBR indicating further post translational modifications. Using super resolution microscopy, we then show that ECM stiffness promotes the NL thickening. The NL width increases from ~140nm on soft hydrogels to ~300nm on stiff hydrogels (Fig. 1d-f). ECM stiffness however does not affect nuclear volume of fibroblasts which are flattened under stiff condition (Fig. 1f).
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To then investigate if the observed modifications of the NL organisation influence the lamina association with DNA, we scored genome wide LADs under soft and stiff conditions using Cut&Run, targeting Lamin B1 (Fig. 1g). Our results show that LADs size ranges between 40kb and 8Mb with a median size of about 250kb and are linked to genes with lower expression levels measured by total RNA-seq. These analyses are consistent with previous studies²⁷ (Extended Data Fig. 1b-c). We found that most LADs remain unchanged (~97%) in response to matrix stiffness and only 236 domains display mechano-specific tethering (81 domains associate with the lamina under soft and 155 under stiff condition - Fig. 1g, Extended Data Fig. 1d-e, Extended Data Table 1). Our results demonstrate that the nuclear shape, the NL organisation, its properties and its composition are modulated in response to matrix stiffness with only minor changes in LAD identity (Fig. 1h).

**Extracellular matrix stiffness promotes changes of chromatin motion at the nuclear periphery and shapes 3D compartment contacts.**

Chromosomes are long fibers with structural dynamics that can be investigated from the angle of their polymer nature⁵³. Within the nucleus, the genome is 3D organised in space and in time, defining chromosome territories, compartments, TADs and loops, all being closely related to transcription program regulations. The NL also contributes to this organisation and influences gene expression through LADs⁵⁴⁻⁵⁶. Thus, to investigate and quantify the impacts of ECM stiffness variations and of the modifications observed in the NL, in turn, influence chromatin motion, we used high-resolution diffusion mapping (HiD). HiD was developed to study motion of densely distributed fluorescent molecules such as chromatin labelled by incorporation of H2B-GFP⁵⁷. Time-lapse fluorescent microscopy is performed at 200 ms intervals over 1 - 3 minutes. HiD integrates dense optical flow methods to reconstruct trajectories of imaged fluorescent molecules at sub-pixel precision. In the subsequent steps, it fits the experimental Mean Square Displacement (MSD) of each trajectory with an anomalous diffusion model (MSD(t)=At^α with A=DT0^1-α), used to describe chromatin motion, allowing the extraction of biophysical parameters describing the dynamic behaviour of chromatin. In this way, diffusion constants (A) and anomalous exponents (α) are estimated for each pixel, allowing the generation of two-dimensional maps that depict chromatin dynamics at single-pixel resolution in living cells. (Fig. 2a). Anomalous exponents α inform on diffusion modes with values <1 indicating subdiffusion due to crowding or retention, equal to 1 suggesting Brownian motion, and >1 reflecting superdiffusion or directed motion which can result from active cellular processes (Fig. 2b). Here, we analysed local chromatin motion by HiD distinguishing two zones within nuclei of cells grown on soft vs stiff hydrogels. MSDs and anomalous exponents were determined within the most peripheral rim of 840 nm and compared to the ones assessed in the internal nuclear space (Fig. 2c). Importantly, HiD is not sensitive to the substrate as MSDs extracted from fixed cells on soft and stiff hydrogels are confounded. We found that chromatin motion differs between stiff and soft conditions and between the nuclear interior and the periphery. First, in the nuclear
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179 interior, chromatin motion is subdiffusive ($\alpha < 1$) and greater in cells grown under soft
180 compared to those under stiff condition. However, at the nuclear periphery, the MSD
181 curve under soft condition displays a distinct shape and rises above that of the curve
182 determined under stiff condition, indicating enhanced chromatin motion likely driven
183 by different underlying processes (Fig. 2c). Indeed, at the periphery, $\alpha > 1$ (1.1,
184 SEM=0.03; active motion) in soft condition while $\alpha$ remains below 1 (subdiffusion)
185 under stiff condition (Fig. 2d). This active motion at the nuclear periphery of soft matrix
186 growth cells likely stems in part from movements of the nuclear envelope permitted by
187 a less rigid NL. This motion is constrained following NL thickening in response to
188 mechanical cues in stiff condition.

189 To then further infer how the NL modifications and changes in chromatin motion
190 impact 3D genome architecture, we performed HiC experiments on cells grown on soft
191 or stiff hydrogels (Fig.3a). Analysis of interaction frequencies indicates that long
192 distance interactions are favoured under soft matrix growth condition in which the NL
193 is thinner and chromatin motion is less constrained (Fig.3b, Wilcoxon test: 1.5e-148).
194 We thus derived 3D interacting maps for each condition and differential contact
195 frequencies all to all loci. The differential map confirmed the increase in long range
196 contact frequencies on soft hydrogels (Fig.3c-d). Hence, we compared the 3D
197 interaction maps with our LAD mapping and observed that structures that show
198 differential interaction frequencies are largely defined by LAD positions (Fig.3c-d). To
199 further validate and visualise these modifications in the 3D genome architecture, we
200 used a 3D genome reconstruction contacts tool that recreates spatial distances and
201 three-dimensional genome structures from observed contacts between genomic loci
202 ⁵⁸. In this reconstruction, the distance between the dots represents the probability of
203 interaction between the genomic locations: the closer they are the most frequently they
204 are interacting. We show our results at chromosomes 11 to 20 to avoid overcrowded
205 display and confirmed that cells growing under soft matrix have enhanced 3D
206 interactions (Fig.3e). Our datasets support the notion that ECM stiffness impacts 3D
207 genome organisation. Notably, on stiff matrix, the NL is thickening and chromatin
208 motion in its vicinity is constrained. The changes in chromatin motion mode between
209 the two conditions correlates with modifications in 3D genomic contacts largely defined
210 by LADs. Overall, chromatin interactions seem favoured under soft growth
211 "permissive" condition.

212 **Extracellular matrix stiffness sets adaptive gene expression programs.**

213 To investigate the influence of the ECM stiffness on gene expression programs,
214 we then performed total RNA sequencing on primary fibroblasts subjected to soft and
215 stiff hydrogels. We found that gene expression is changing to large levels in response
216 to these mechanical stimuli. Genes such as *MMP11* and *CYR61* display very specific
217 expression patterns depending on which stiffness the cells are exposed to (Fig. 4a).
218 In total over 30% of the human annotated genes we analysed show significant ECM
219 stiffness-dependent expression levels (5973/19238 with 2804 and 3069 more
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220 expressed on soft or on stiff condition respectively, adjusted p-value < 0.01; Fig. 4b,
221 Extended Data Table 2). We further confirmed this observation by specifically
222 quantifying precursor RNA using intronic reads on 1698 genes with sufficient read
223 coverage to be called using the DESEQ algorithm (adjusted p-value < 0.01 ; Extended
224 Data Fig. 2a-c, Extended Data Table 2).

225 Then, we used gene ontology to identify the biological functions of genes with
226 differential expression. Despite that gene sets displaying mechano-dependent
227 expression patterns are very large, our gene ontology analyses were still able to
228 highlight adaptative gene groups in our lists. Enriched groups in soft growth condition
229 embrace regulatory transcription factors, signalling pathways, ECM regulators and
230 components and negative regulator of cell proliferation, while on stiff, house-keeping
231 genes are over-represented such as cell division, translation and DNA repair (Fig. 4c,
232 Extended Data Fig. 2d). We then used the GSEA TFT module to explore transcription
233 factors that are at play in mechano-transduction. This module catalogues motifs highly
234 conserved in promoters of four mammalian species (human, mouse, rat and dog ; Fig.
235 4d) 59. We found SRF and E2F motifs as highly significant in our stiff gene signature
236 which is consistent with SRF role as cytoskeleton and mechano-regulator 2,13 and with
237 expression programs of cell division regulating genes. We also identified NFKB and
238 Foxo family member enriched at promoters of the soft gene signature, pointing to
239 potential input of unknown signalling programs in mechano-sensation. Finally, we
240 used GSEA to interrogate enriched signatures across available expression datasets
241 (Fig. 4e). Our main results comprise the YAP and, again, the serum response
242 signatures which are known to involve cytoskeleton remodelling and to overlap with
243 transduction of mechanical forces 13,16. Additionally, we found very high correlation
244 scores between our signatures and PRC2-dependent genes in fibroblasts 60. In fact,
245 sets of genes that are down regulated upon EZH2 knock-down, indicative of an
246 activating role of EZH2 through possible indirect or non-canonical role of PRC2, are
247 also enriched in our stiff signature. Furthermore, genes that are derepressed by
248 inactivation of PRC2 components in fibroblasts 60 strongly overlap with the soft
249 signature. These results strongly suggest that PRC2-dependent repression is
250 impaired under soft growth condition and that EZH2, through an indirect or non-
251 canonical role, supports the expression of some genes under stiff condition. Taken
252 together, our transcriptome results indicate major reprogramming of gene expression
253 during the transition from stiff to soft growth conditions associated with signalling and
254 more wide-spread functions in soft and stiff media, respectively. Our data also suggest
255 an involvement of PRC2 in the regulation of this transition.

256 **Soft matrix impedes PRC2-dependent repression of genes associated with**
257 **H4K4me3 and H3K27me3 marking.**

258 Histone modifications regulate physical properties of chromatin and are important
259 players in the regulation of gene expression 61. Chromatin accessibility remains an
260 essential step for gene expression and promoter activity 62. Furthermore, our
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ontological analysis suggests a role of PRC2 in gene regulation in response to ECM
261
stiffness. We thus used ATAC-seq to investigate how ECM stiffness and mechano-
262
transduction shape the chromatin landscape and promoter opening of differently
263
expressed genes between soft and stiff hydrogels (Fig. 5a). Our results show no major
264
differences between the two conditions despite different gene activities. They are
265
however consistent with known properties of mammalian promoters which display
266
open chromatin structures independently of transcription 63. Histone modifications
267
characteristic of active promoters or poised promoters such as H3K4me3 in
268
association or not with H3K27me3 are proposed to maintain promoter in an open state
269
42,64. Bivalent promoters harbouring both marks are mainly poised and were observed
270
in ES cells being associated to the pluripotent potential of these cells 41 and in
271
differentiated cells where their roles remain to be addressed 45,48. We used H3K4me3
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ChIP-seq and H3K27me3 Cut&Run to map these histone marks and again observed
273
no differences between cells grown on stiff or soft hydrogels (Fig. 5a). However, we
274
made two significant observations. First, the most differently expressed genes either
275
on soft or on stiff condition display less H3K4me3 signals (Hi-soft and Hi-stiff found at
276
top and bottom parts of the heatmaps, respectively, Extended Data Table 3),
277
suggesting that responsiveness to mechano-transduction is compatible with lower
278
levels of H3K4me3. This is consistent with the associated role of this mark to
279
transcriptional consistency in particular at broad domains 40. Second, we found that
280
genes that are more differentially expressed in soft (Hi-soft, top of the heatmaps) are
281
enriched for both H3K4me3 and H3K27me3 histone marks, suggesting bivalent
282
marking of the chromatin of these promoters. These genes are repressed under stiff
283
ECM as expected but show significant expression levels when cells are grown under
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soft gels (Fig. 5a-b). We confirmed this tendency at the genome-wide level, where
285
genes harbouring apparent chromatin bivalency are more expressed in soft as
286
compared to stiff (Extended Figure 3a, Extended Data Table 4). While H3K27me3
287
marking deposited by PRC2 is generally associated with transcription inhibition, cells
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subjected to soft ECM seem to escape such repression in the context of bivalent
289
chromatin. This could figure a novel mechanism for gene expression regulation
290
through PRC2-dependent repression. Furthermore, genes from this group are
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enriched in biological processes linked to cellular adaptation to ECM modifications
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such as signalling proteins and components or regulators of extracellular matrix
293
organisation and focal adhesion (Extended Data Fig. 3b).
294

To test the role of PRC2 in the inhibition of these set of genes, we used
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Tazemetostat, an FDA-approved EZH2 inhibitor used in the clinic for cancer treatment
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65,66. Primary fibroblasts were treated for 7 days with 5µM of Tazemetostat resulting in
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80 to 90 % decrease in H3K27me3 signal (Fig. 5c, Extended Data Fig. 4a). We then
298
used total RNA-seq and focused on genes behaving similarly in untreated and control
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condition since adding DMSO has only slight effects on gene expression (Extended
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Data 4b, Extended Data Table 5). We found that under stiff condition the genes that
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display both H3K4me3 and H3K27me3 are indeed derepressed by Tazemetostat
302
treatment (Fig. 5d). We also note that Hi-stiff genes are also down regulated in soft
303
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condition suggesting an indirect or non-canonical role of EZH2, independent of H3K27me3 marking, in the regulation of stiff-induced genes (Extended Data Fig. 4c-d). These results are consistent with our signature analysis that highlights the overlap of mechano-responsive genes with genes that were de-repressed in our soft signature or down-regulated in our stiff signature in fibroblast with EZH2 knock-down <sup>60</sup>. Our genomic and functional analyses show that a set of Hi-soft genes with higher expression under soft ECM are marked in a bulk population by both H3K4me3 and H3K27me3 and require functional PRC2 for an efficient repression under stiff ECM.

**The nuclear lamina integrity is required for proper PRC2-dependent repression of genes associated to bivalency.**

As cells adhere and pull on their surrounding environment, the nuclear lamina is changing <sup>67</sup>. In our primary fibroblast model, ECM stiffness promotes lamina component rearrangements, impact chromatin polymer properties and 3D genome modifications. To further address the NL role in softness-dependent and PRC2-dependent transcription programs, we compared our Hi-soft signature to LADs mapped by LaminB1 Cut&Run. Lamin B1 is part of the lamina meshwork facing the inner part of the nucleus (Fig. 6a). We first confirmed that globally, genomic regions covered by broad H3K27me3 domains are more associated to Lamin B1 than inter-LAD regions (Extended Data Fig. 5a). As exempled by the *BACH2* gene, embedded in a H3K27me3 domain and associated to a large Lamin B1 domain (Fig. 6b), genes of the Hi-soft signature tend to be more associated to the NL than the rest of the genome or other soft-responding genes (Fig. 6c). This is observed in cells plated on both soft and stiff hydrogels since LAD domains remain largely unaffected by matrix stiffness. To further investigate if NL and the LINC complex are required for mechano-dependent transcription programs, we used siRNA targeting main NL components (LBR (LBR), Lamin A (LMNA), Lamin B1 (LMNB1) and Emerin (EMD)) and SUN proteins (SUN1, SUN2 and SUN1/2 in combination). We set scrambled siRNA as control (siNeg) in these series of experiments since transfection had some effects on the cellular response to ECM. We then performed total RNA-seq and only considered genes responding similarly to ECM stiffness with and without transfection (Extended Data Fig. 5b, Extended Data Table 6). We first confirmed the reduced RNA levels of our targeted genes (Extended Data Fig. 5c) and measure the effects of these treatments on the expression of the mechano-sensitive genes. Strikingly, we found that our Hi-soft signature is escaping repression on stiff condition when the NL is impaired, in particular when using siRNA targeting the LBR, LMNA or LMNB1 (Fig. 6d-e). We also noticed that siRNA treatments only have slight effects in soft condition suggesting that NL regulates gene expression mainly in response to stiff condition (Extended Data Fig. 5d-e). Hence, the NL integrity is required for proper PRC2 inhibition of the Hi-soft gene signature in stiff condition. To conclude, we have defined a Hi-soft gene signature enriched for mechanical-adaptive genes in our gene ontology analysis, controlling processes of ECM regulation, cell adhesion and signalling pathways. This set of genes is found associated to Lamin B1 in both condition but only
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346 expressed in cells platted on soft hydrogels. Under this condition, the NL is weakened,
347 the chromatin is highly mobile and long-range 3D interactions are favoured. Under stiff
348 condition, repression of these genes is altered when the NL is targeted by siRNAs or
349 when EZH2 is inhibited by Tazemetostat. This supports the idea that thick and
350 unaltered NL is required for PRC2-dependent Hi-soft gene repression. On soft
351 hydrogels, wrinkled nuclei with loose lamina and mobile chromatin permit expression
352 of this specific set of genes. We thus propose a novel regulatory mechanism where
353 modifications in nuclear mechanics modulate chromatin mobility and 3D genome
354 organisation. Under stiff ECM, nuclear flattening and stiffening associated with NL
355 thickening create a constrain and rigid environment where chromatin motion and long-
356 range 3D genome interactions are limited. This represents conditions for efficient
357 PRC2 repression of genes with bivalently marked chromatin with both H3K4me3 and
358 H3K27me3 histone modifications. Repression that could be tempered using the EZH2
359 inhibitor Tazemetostat or by targeting the NL components (Fig. 7).

360 Discussion

361 Our data show that the NL and effective gene repression by PRC2 are mechano-
362 sensitive and regulate the expression of specific sets of genes harbouring both
363 H3K4me3 and H3K27me3 histone modifications. These genes are enriched in
364 effectors of ECM adhesion and signalling. Antagonistic histone modification signatures
365 that combine the activating histone H3K4me3 and the repressive H3K27me3 marks
366 have been defined as bivalent. Bivalent marking was first identified in mES cells at
367 genes characteristic of differentiation and developmental processes 43-47. While
368 bivalency is proposed to contribute to the flexibility of the activation and repression of
369 differentiation genes, its occurrence is not restricted to pluripotent cells and has also
370 been observed in non-pluripotent cells 45. Furthermore, bivalent domains of terminal
371 stages of differentiation can be distinct to those of ES cells 48 and their function
372 remains quite unclear. We propose that they are at play in an adaptative mechanism
373 where the NL acts as a sensor of extracellular matrix stiffness. As the environmental
374 elasticity conditions are changing, the focal adhesion foci and the cytoskeleton adapt,
375 resulting in profound cellular modifications. The NL organisation is in turn changing
376 and regulates nuclear physical properties. This finally tunes the repression of genes
377 harbouring bivalent marking of H3K4me3 and H3K27me3. In this model, bivalency
378 would allow plasticity in the repression of mechano-adaptative genes which would thus
379 respond to the modifications of the physical properties of the nucleus. Due to the
380 limitation in primary fibroblast cell culturing, re-ChIP or similar approaches could not
381 be performed and thus an alternative model would be that at the bulk population level,
382 this specific set of gene would be differently marked at the subpopulation scale with a
383 group of cells harbouring the H3K4me3 marking and another H3K27me3. This model
384 remains however unlikely since only gene expression is changing without affecting the
385 balance of H3K4me3 and H3K27me3.
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This mechanism may also act during differentiation since the NL evolves during this process. The balance between Lamins A/C and the LBR changes with high levels of LBR and low levels of Lamins A/C in ES cells and with the opposite at the latest stages ⁶⁸. This evolution is very similar to the differences we observed in response to ECM stiffness and may thus contribute to changes in expression and further modifications in the epigenetic marking of the bivalent genes. Similarly, our model could also contribute to aging since recent works have identified alterations in extracellular matrix composition and mechanics during aging of murine hair follicle stem cells ⁹. In this model, ECM is stiffening with aging concomitantly with the loss of bivalency with decreasing H3K4me3 signal and chromatin opening at bivalent genes.

Associations of H3K27me3 domains and LADs are still in debates. LADs are enriched in repressive marks including H3K27me3 ²⁷,³⁰,³² which may contribute to the attachment of the chromatin to the lamina through its interplay with YY1 ³¹. Moreover, Lamin-A/C was shown to interact with PRC2 proteins regulating their foci architecture and PRC2-dependent repression of myogenic genes ⁶⁹. In contrast, recent works propose that H3K27me3 and PRC2 could antagonise LADs ⁷⁰,⁷¹. However, one of these studies was conducted in the non-adherent cancer cell line K562 ⁷¹, while the other focused on early mouse embryonic development, a context in which non-canonical H3K27me3 domains have been described ⁷⁰,⁷². These differences in cellular context, developmental stage, mechanical states and probably in NL composition may underlie the discrepancies between our findings and those previously reported.

Our gene expression assays show that a very large set of genes is mechano-responsive. Our ontology analysis indicates more house-keeping gene functions being enhanced under stiff condition. Due to the limited duration of our experimental setup, BJ primary fibroblasts which have a doubling time of over a week under hydrogel were not afforded sufficient time to initiate or complete cell proliferation. However, our assays predict that long term exposure on differential hydrogel stiffness would impact cell fitness and proliferation. In addition, our assays also highlight the transcriptional regulation of TNF, AKT or MAPK signalling components in the soft responding gene signature. These signalling pathways are proposed to be at play in response to mechanical inputs or focal adhesion dependent signalling ⁷³⁻⁷⁵. Hence, further investigation of these signalling cascade dependencies and activations in response to ECM stiffness and to its gene expression program regulation would be of great interest. In particular for AKT dependent signalling since it controls both NFKB and Foxo transcription programs ⁷⁶,⁷⁷ for which binding motif enrichments were also identified in our study.

3D genome organisation and gene regulation are paired. Here, we found that long range interactions at the compartment scale are influenced by the ECM stiffness. Under soft growth condition, the frequency of interactions at this scale is increased. This also correlates with LADs and with changes in chromatin motion. Chromatin in the nucleus can be model and its viscoelastic displacement are consistent with Rouse
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427 polymer models 78. Our HiD measurement indicates directed motion in cells grown on 428 soft hydrogels close to the nuclear periphery that would be consistent with broad 429 movement of the NL and of its associated chromatin domains. These movements 430 could also represent a novel layer of gene regulation by the NL and its flexibility. 431 Increase in motion of large chromatin domains linked to the NL could thus enhance 432 the likelihood of long-range interactions measured by HiC and loose repression that 433 occurs at sub diffusing domains in stiff condition. We propose that flattening of the 434 nucleus associated to NL thickening change nuclear mechanical properties, 3D 435 genome organisation as well as chromatin motion and promote H3K27me3-dependent 436 repression of genes with bivalent chromatin found close to NL by creating a more 437 restrictive environment. 438

438 All in all, our data suggest that NL acts as a mechano-sensor and effector to 439 control specific sets of adaptative genes that are bivalently marked. We propose a 440 gene expression control mechanism where modifications in the NL organisation in 441 response to extracellular matrix stiffness leads to nuclear and chromatin mechanics 442 modifications. These changes would set conditions for efficient or loose PRC2- 443 dependent repression of bivalently marked genes. Hence, sensed mechanical inputs 444 through the NL would control a specific set of genes regulating biological pathways 445 involved in the cellular adaptation to mechanical cues. These findings could be further 446 used to understand how 3D genome rewiring could promote mechano-dependent 447 physiological effects such as tumour progression and stem cell differentiation and to 448 define PRC2 as a potential target for treatments.. 449

## 449 Experimental procedures

450 Antibodies and applications

451 All antibodies and their applications are listed in Extended Data Table 7.

452 Cell amplification

453 Primary BJ fibroblasts were expanded on plastic plates in DMEM High Glucose 454 (ThermoFisher, 31966021) supplemented with 10% foetal bovine serum (FBS, Gibco) 455 at 37°C and 5% CO2.

456 Hydrogel-based cell culture

457 Polyacrylamide hydrogels (Matrigen, Cell Guidance System) with a stiffness of 458 0.5kPa (SOFT) and 50kPa (STIFF) were coated with fibronectin from human plasma 459 (Sigma, F0895) at a final concentration of 10µg/mL for 2h at room temperature (RT). 460 Then, cells were trypsinised and plated on fibronectin-coated hydrogels in DMEM High 461 Glucose (ThermoFisher, 31966021) supplemented with 10% foetal bovine serum 462 (FBS, Gibco) at 37°C and 5% CO2 for 48h before performing the subsequent
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463 experiments. Different types of hydrogels were used depending of the experiment. For 464 RNA and proteins isolations: Softwell 6-well plate Easy Coat (SW6-EC-0.5 and SW6- 465 EC-50), for microscopy experiments: SoftSlip 12-well plate Easy Coat (SS12-EC-0.5 466 and SS12-EC-50), for genomic analysis requiring large amount of cells: PetriSoft 467 150mm Dish Easy Coat (PS150-EC-0.5 and PS150-EC-50) and for live microscopy 468 HiD experiments: Softview 35mm dishes (SV3520-EC-0.5 and SV3520-EC-50).

469 **siRNA and Tazemetostat treatments**

470 **siRNA**

471 Cells were transfected using Lipofectamin RNAiMAX (Invitrogen, 13778150) and 472 20nM of siRNA (Dharmacon, Horizon Discovery) according to the protocol of reverse 473 transfection to maximise the efficiency. All siRNA references are listed in Extended 474 Data Table 8. Briefly, for one 10cm dish, 15µL of Lipofectamin RNAiMax was diluted 475 in 1mL of Opti-MEM medium (Gibco, 31985062) and incubated for 5min at RT. 476 Simultaneously, siRNA were diluted in 1mL of Opti-MEM medium and incubated 5min 477 at RT. Both solutions were then mixed at a 1:1 ratio into a 10cm dish and incubated 478 20min at RT. Resuspended trypsinized cells were added for a final concentration of 479 siRNA at 20nM and incubated 3 days in DMEM High Glucose 10% FBS at 37°C and 480 5% CO2. Afterwards, cells were trypsinised and plated on fibronectin-coated 481 hydrogels for 48h with 20nM siRNA.

482 **Tazemetostat**

483 Cells were plated on plastic plate and treated for 5 days with 5µM of Tazemetostat 484 (Selleckchem, EPZ-6438) in DMEM High Glucose 10% FBS at 37°C and 5% CO2. 485 Media was changed each 2days. Afterwards, cells were trypsinized and plated on 486 fibronectin-coated Softwell 6-well plate Easy Coat hydrogels (SW6-EC-0.5 and SW6- 487 EC-50) for 48h with 5µM Tazemetostat.

488 **Confocal and super-resolution microscopy**

489 Cells were fixed directly in the wells with freshly prepared 4% paraformaldehyde 490 in PBS 1X for 10min at RT, permeabilised with 0.2% Triton X-100 for 10min at RT and 491 incubated in blocking solution (10% FBS, 1% Cold Fish Skin Gelatin in PBS 1X) for 492 10min at RT. Primary antibodies were diluted in blocking solution and incubated for 2h 493 at RT. Secondary antibodies as well as phalloidin labelling actin filaments were diluted 494 in blocking solution and incubated for 1h at RT. Nuclei were stained with DAPI for 495 10min at RT. After extensive washes with PBS-Tween 0.5%, a final wash with H2O 496 was performed to remove salts. A drop of Prolong Gold (Invitrogen, P36930) was 497 deposited on the microscopy slide to mount the coverslip containing-hydrogel, 10µL 498 of Vectashield was used to mount the coverslip on the hydrogel and transparent nail
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499 polish was immediately used to seal the mounting. Confocal images were acquired
500 with a Zeiss LSM780 and super-resolution images with a DeltaVision OMX 3D-SIM.

501 **Live microscopy for HiD**

502 Three days prior imaging, cells were transfected with H2B-GFP with FuGene HD
503 transfection reagent (promega, E2311) at a ratio of 4:1. Two days before, cells were
504 transferred in Softview dishes of 0.5 and 50kPa respectively. On the day of imaging,
505 culture medium was changed to L-15 medium (gibco, 21083-027) supplemented with
506 10% FBS. Cells were placed in a 37°C, 5% CO2 humid chamber (OkoLab system).
507 Imaging was performed using a DMi8 inverted automated microscope (Leica
508 Microsystems) featuring a confocal spinning disk unit (CSU-X1-M1N, Yokogawa). A
509 63x oil immersion objective (Leica HC-PL APO, 11506349) with a 1.4 NA was used
510 for high resolution imaging. Image (16bit) was acquired using Metamorph 7.10.5
511 software (Molecular Devices) and detected using a CMOS Hamamatsu Flash4 V2+
512 camera (1003x1433) and 1 x 1 binning, with sample pixel size of 120 nm. Image series
513 of H2B-GFP (488 nm laser with a band pass emission filter of 510-540) of 500 frames,
514 with exposure time of 200 ms per frame (5fps) were acquired.

515 **Western-blot**

516 Cells were lysed directly in the well with RIPA buffer (10mM Tris-HCl pH 8.0, 1mM
517 EDTA, 0.5mM EGTA, 1% Triton X-100, 0.1% Sodium deoxycholate, 0.1% SDS,
518 140mM NaCl). Protein extracts were then complemented with Laemmli 4X (250mM
519 Tris ph6.8, 8% SDS, 40% glycero, 5% β-mercaptoethanol, bromophenol blue) to a
520 final concentration of 2X, incubated 5min at 95°C on a thermomixer before loading on
521 a 4-12% Bis-Tris gel. After the transfer on a nitrocellulose membrane, blocking solution
522 (5% milk in PBS-Tween 0.2%) was added for 1h at RT. Primary antibodies were diluted
523 in 2% milk PBS-Tween 0.2% and incubated O/N at 4°C. Secondary antibodies were
524 diluted in 2% milk PBS-Tween 0.2%, incubated 1h at RT and revelation was performed
525 with ECL (BioRad) or SuperSignal West Femto (Thermofisher) on an Amersham
526 Imager 680 (GE LifeSciences). Bands quantifications were performed using the
527 ImageJ software.

528 **Total RNA-seq**

529 Cells were plated on Softwell 6-well plate Easy Coat hydrogels with each well
530 representing one biological replicate. Total RNAs were purified using RNeasy Plus
531 Mini Kit (Qiagen) and eluted in 30µL of nuclease-free water. Quantifications were
532 performed using Nanodrop and qualities were assessed with a BioAnalyzer Pico RNA
533 chip (Agilent). A fraction of purified RNA was used for subsequent reverse-
534 transcription with the Superscript Vilo kit (Thermofisher, 11754250) and expression of
535 known mechano-responsive genes such as ANKRD1 and CTGF was assessed by
536 qPCR. For RNA isolated from cells treated with siRNA, qPCR were performed on the
targeted associated gene (all primers listed in Extended Data Table 9). Then, 10µL of total RNA was mixed with ERCC92 spike-in (Invitrogen, 4456740) depending on RNA quantity according to manufacturer instructions and treated with DNase before proceeding to libraries preparation using the TruSeq Stranded Total RNA Ribo-Zero H/M/R Gold (Illumina). Libraries were quantified using the Qubit dsDNA kit (Thermofisher) and size distribution was assessed with a BioAnalyzer High Sensitivity DNA chip (Agilent). All the fragments with a size superior to 700bp were cleaned with CleanNGS beads (CleanNA) and libraries were sequenced in 2x50bp paired-end on an HiSeq4000 or a NovaSeq.

## 546 ATAC-seq

ATAC-seq experiments were performed as described previously in ⁷⁹ in triplicates. Briefly, cells were trypsinised, washed in PBS 1X and counted in order to have ~65000 cells per replicate. Cells were centrifugated 10min at 500g at 4°C and supernatant was discarded. Cell pellets were lysed with 50µL of cold lysis buffer (10mM Tris-HCl pH 7.5, NaCl 10mM, MgCl2 3mM, 0.1% Igepal CA-630). After centrifugation 15min at 500g 4°C, nuclei were resuspended into 50µL of tagmentation buffer (25µL of TD buffer, 2.5µL of Tn5 transposase, qsp 50µL with nuclease-free water) and incubated 30min at 37°C. DNA was then purified with MinElute columns (Qiagen) according to the protocol. Samples were indexed and amplified by PCR for 10 cycles to generate sequencing libraries. Libraries were purified using the PCR purification kit (Qiagen), quantified with Qubit dsDNA kit (Thermofisher) and deposited on a BioAnalyzer High Sensitivity DNA chip (Agilent). All fragments with a size superior to 300bp were eliminated with CleanNGS beads (CleanNA) to keep only the subnucleosomal fraction. Libraries were then sequenced on an HiSeq4000 in 2x75bp paired-end.

## 561 ChIP-seq

ChIP-seq experiments were performed in triplicates. Approximately 8x10⁵ cells per replicate were collected by trypsinisation and washed with PBS 1X before fixation with 1% formaldehyde for 10min at 37°C. Reaction was stopped by the addition of glycine to reach a final concentration of 125mM and incubated 5min at RT. All centrifugation steps were done at 4°C 1200g. Cells were abundantly washed with cold PBS 1X, resuspended in 10mL of buffer A (5mM Hepes pH 7.5, 85mM KCl, 0.5% Triton X-100), incubated for 10min on ice. After centrifugation, 5mL of buffer A' (5mM Hepes pH 7.5, 85mM KCl) were added. Cellular pellet was resuspended in 500µL of lysis buffer (50mM Tris-HCl pH 8.0, 1% SDS, 10mM EDTA, 1mM PMSF, 1X cOmplete Protease Inhibitor), incubated on ice for 10min before snap-freezing in liquid nitrogen. After defrosting, chromatin was sonicated with a Bioruptor Pico (Diagenode) for 4 cycles 30sec ON/30sec OFF. A 10µL aliquot was added to 90µL of FA/SDS/like buffer, 25µL of elution buffer 5X (125mM Tris-HCl pH 7.5, 25mM EDTA, 2.5% SDS) and 5µL of proteinase K before incubation O/N at 65°C. Next day, DNA was cleaned using PCR Purification kit (Qiagen) and eluted in 30µL of nuclease-free water. Then, DNA was
quantified using Qubit dsDNA kit and ran on a 1.5% agarose gel to verify that mean DNA shearing was below 500bp. After validation of sonication profiles, samples were centrifugated to pellet cell debris, supernatant was recovered and diluted 10 times in FA/SDS/Like buffer (50mM Hepes pH 7.5, 150mM NaCl, 1% Triton X-100, 0.1% Na-Deoxycholate). Diluted chromatin was aliquoted in 1mL, snapped-freeze in liquid nitrogen and conserved at -80°C until use. Protein-G coated dynabeads (Thermofisher) were blocked with PBS-BSA 0.1% and 25µL of beads per immunoprecipitation (IP) was coupled with the antibodies of interest on a wheel for 2h at 4°C. An aliquot of 1mL of sonicated chromatin was precleared by addition of 25µL of dynabeads resuspended in PBS-BAS 1% per sample to reach a final concentration of 01% BSA and incubated on a wheel for 2h at 4°C. An aliquot of 20µL was taken as input and treated as described above for sonication check. Beads incubated with the antibodies were collected and washed 4 times with PBS-BSA 0.1% before addition of pre-cleared chromatin and incubation O/N at 4°C on a rotating wheel. The following day, beads were washed one time with 500µL of FA/SDS/PMSF buffer (50mM Hepes pH 7.5, 150mM NaCl, 1mM EDTA, 1% Triton X-100, 0.1% Na-Deoxycholate, 0.1% SDS) and 3 times with 500µL of FA/SDS/PMSF buffer 300mM NaCl. During the last wash, samples were placed on a rotating wheel 10min at 4°C. Then, beads were washed with 500µL of washing buffer (10mM Tris-HCl pH 8.0, 250mM LiCl, 1mM EDTA, 0.5% NP-40, 0.5% Na-Deoxycholate) and 500µL of TE buffer (10mM Tris-HCl pH 8.0, 1mM EDTA) before incubation 25min at 65°C in a thermomixer with 125µL of pronase buffer 1X (25mM Tris pH 7.5, 5mM EDTA, 0.5% SDS). Supernatant containing immunoprecipitated fragments was recovered, purified with PCR purification kit (Qiagen), eluted in 30µL of nuclease-free water and quantified using Qubit dsDNA kit (Thermofisher). Enrichment on target control regions was assessed by qPCR (primers listed in Extended Data Table 9) and sequencing libraries were prepared with MicroPlex Library Preparation V2 or V3 kits (Diagenode). Libraries were quantified using the Qubit dsDNA kit (Thermofisher) and size distribution was assessed with a BioAnalyzer High Sensitivity DNA chip (Agilent). All the fragments with a size superior to 700bp were cleaned with CleanNGS beads (CleanNA) and libraries were sequenced in 2x50bp paired-end on a NovaSeq.

## 608 Cut&Run

Cut&Run experiments were performed in triplicates as previously described in ⁸⁰ with minor modifications. Each Cut&Run was performed with 8x10⁵ cells. After cells permeabilisation with 0.05% digitonin and incubation with washed and activated beads, the mix was resuspended in 300µL of antibody buffer containing antibodies targeting either LaminB1, H3K27me3 or IgG (negative control) at a 1/100 dilution and incubated 2h at 4°C under agitation. After washing, samples were resuspended in 100µL of cold digitonin buffer and 5µL of diluted 1/10 pAG-MNase was added to reach a final concentration of 700ng/mL and incubated 10min at RT. After washing to remove unbound pAG-MNase, 100µL of cold digitonin buffer was added as well as 2µL of CaCl₂ 100mM. Samples were incubated 2h at 4°C under agitation to proceed to the
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619 digestion process. Reaction was stopped by the addition of 66µL of Stop Buffer 2X
620 and digested chromatin was released in the supernatant by incubation 10min at 37°C.

621 Supernatant was recovered and purified with Monarch kit (NEB). Sequencing libraries
622 were prepared using the MicroPlex Library Preparation V3 kit (Diagenode), quantified
623 with Qubit dsDNA, and size distribution was assessed with a BioAnalyzer High
624 Sensitivity DNA chip (Agilent). All the fragments with a size superior to 700bp were
625 cleaned with CleanNGS beads (CleanNA) and libraries were sequenced in 2x50bp
626 paired-end on an HiSeq 4000 or a NovaSeq.

627 Hi-C experiments

628 Hi-C experiments were performed in duplicates with the Arima Hi-C kit (Arima
629 Genomics, Inc.; Cat # A510008) according to the manufacturer instructions. One
630 million cells were crosslinked with formaldehyde and subjected to Arima HiC Standard
631 Input protocol. Briefly, cells were lysed and chromatin was digested using a
632 combination of restriction enzymes. The 5'-digested ends were filled in with a
633 biotinylated nucleotide and spatially proximal digested ends were ligated. Proximally
634 ligated DNA was purified using CleanNGS beads (CleanNA) and fragmented using
635 the Covaris sonicator to reach an average size of 400bp (temperature: 20°C ; peak
636 incident power: 50W ; duty factor: 10% ; cycles per burst: 200cpb ; time: 70s).

637 Fragments between 200bp and 600bp were size-selected and biotinylated ones were
638 enriched using furnished streptavidin enrichment beads. On-beads sequencing
639 libraries were prepared using the MicroPlex Library Preparation V2 kit (Diagenode),
640 quantified with Qubit dsDNA and size distribution was assessed with a BioAnalyzer
641 High Sensitivity DNA chip (Agilent). All the fragments with a size superior to 700bp
642 were cleaned with CleanNGS beads (CleanNA) and libraries were sequenced in
643 2x50bp paired-end on an HiSeq 4000.

644 Bioinformatic procedures

645 Quantifications of nuclear volume and nuclear lamina thickness

646 Nuclear volumes and NL thicknesses were quantified using ThicknessGui
647 (https://github.com/ant-trullo/ThicknessGui). Briefly, after opening the Z-stack files
648 obtained from super-resolution acquisitions, we manually selected the frames of
649 interest and divided our nuclei in 180 slices. After calculation, we exported the .csv file
650 and the visual representation of nuclei segmentation. We then selected the slices that
651 fit the best with our Lamin A/C signal. Since the values in the .csv files are pixels, we
652 multiplied by pixel size (pixel width: 0.4µm, height: 0.4µm, depth: 0.125µm) to obtain
653 NL thickness and nuclear volume values in µm and µm3, respectively.

654 HiD data processing
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Before HiD analysis, nuclei with a low GFP intensity (less than two time the intensity of the background) and which undergo Z-plan drift were eliminated. Bleaching and XY-plan drift were corrected using Bleach Correction (10.12688/f1000research.27171.1) and StackReg translation correction (10.1109/83.650848) imageJ plugins respectively. Finally, to remove high gain noise from time laps image streams, the Kalman Stack Filter plugin from image J is applied.

HiD analysis is based on the method of (10.1186/s13059-020-02002-6 , 10.1038/s41596-024-01038-3). Briefly, detection of movement between two consecutive frames were computed by the Farneback Optical Flow based on polynomial expansion (10.1007/3-540-45103-X_50). For a sequence with N frames, N-1 flow fields were produced and linked to compute a trajectory per pixel. The MSD curves are computed for every trajectory as function of the time interval (τ)and the first 20% (100 frames = 20s) of the experimental MSDs were fitted with the following anomalous diffusion model:

$$MSD(\tau) = A\tau^{\alpha} \text{ with } A = DT_{0}^{(1-\alpha)}$$

Where A (in µm²/s⁴) is the product of the diffusion constant D (in µm²/s) and T0 (in s), a characteristic time at which a diffusive particle sense its neighbours. α is its anomalous exponent allowing to characterise three model of diffusion, i. free diffusion, α=1, ii. subdiffusion or anomalous diffusion with 0<α<1, iii. superdiffusion or directed motion with 1<α.

RNA-seq data processing

Raw sequencing reads were aligned to the human genome (hg19) using TopHat2 ⁸¹. Sequences aligning on positive and negative strands were separated and processed separately using PASHA pipeline ⁸² to generate strand-specific WIG files representing the average enrichment score every 50bp. All WIG files were then rescaled to normalize the enrichment scores to the depth of sequencing. Rescaled WIG files of biological replicates from the same condition were then merged to produce merged WIG files. Reads Per Kilobase per Million (RPKM) were generated based on DESeq values normalised by annotation size.

ATAC-seq, ChIP-seq and Cut&Run data processing

Raw sequencing reads were aligned to the human genome (hg19) using Bowtie2 ⁸³. WIG files were generated using the PASHA R pipeline ⁸². For ATAC-seq, WIG files represent average enrichment score over 10bp while for ChIP-seq data and Cut&Run targeting H3K27me3, those represent the average signal over 50bp and for Lamin B1 Cut&Run over 10kb. All WIG files were then rescaled to normalize the enrichment scores to the depth of sequencing. Rescaled WIG files of biological replicates from the same condition were then merged to produce merged WIG files. For Lamin B1 and
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negative control IgG files, signal over 10bins, representing signal on 100kb, was averaged to produce a rescaled and normalized WIG with a resolution of 100kb. Then, Lamin B1 signal over 100kb was normalized with negative IgG control and logged in log2 to highlight Lamin B1 associated domains.

### H3K4me3 peak-calling

Peak-calling was performed using MACS2<sup>84</sup>. Only peaks found in at least 2 over 3 replicates are conserved. For ChIP-seq targeting H3K4me3, peak-calling was performed with the merged bam file of control IgG in 0.5kPa and 50kPa as background using the parameter -c. All peaks with a threshold of p-value < 10<sup>-15</sup> were selected and conserved based on the “narrow peak” table provided by MACS2. DESeq package was used to quantify reads mapping on the called peaks and Reads Per Kilobase per Million (RPKM) were generated using DESeq output values normalised by domain size.

### H3K27me3 domains calling

H3K27me3 bam files from the same stiffness condition were merged and used for peak-calling. Peak-calling as performed using MACS2<sup>82</sup> with parameters --keep-dup all, -f BAMPE, -maxgap 3000. The merged bam file of control IgG in 0.5kPa and 50kPa was used as background with the parameter -c. All peaks with a threshold of p-value < 10<sup>-3</sup> were selected and conserved based on the “narrow peak” table provided by MACS2. DESeq package was used to quantify reads mapping on the called domains and Reads Per Kilobase per Million (RPKM) were generated using DESeq output values normalised by domain size.

### Lamin B1 domains calling

Lamin B1 WIG files normalized on the depth of sequencing were then normalized over IgG control signal and logged in log2 to allow domain visualization on the IGB tool. Then, wigs from the same stiffness condition were merged and peak-calling was performed using WigPeakCalling script<sup>63</sup> which extracts values from the thresholding function of IGB. The parameters used were: --minRun 30000 and --maxGap 50000. DESeq package was used to quantify reads mapping on the called domains and Reads Per Kilobase per Million (RPKM) were generated using DESeq output values normalised by domain size.

## Differential Expression Analysis

Differential Gene Expression (DGE) analysis was performed using the DESeq package<sup>85</sup>. First, HTseq-count<sup>86</sup> was used to count the sequenced reads mapping to hg19 Refseq protein coding gene annotations or protein coding genes introns annotations. These counts were merged in order to have tables containing all biological replicates from different conditions. Then, these tables were processed
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729 using the DESeq package to identify genes that are significantly differentially expressed relative to the reference sample. A threshold of padj < 0.01 and Fold change < 1 (more expressed on SOFT) or > 1 (more expressed on STIFF) was used to identify differentially expressed genes in untreated samples and a pval < 0.05 was used for Tazemetostat and siRNA treated samples.

734 Coverage calculations

735 Coverage represents the number of base pairs covered by an epigenetic mark on an annotation of the genomic reference. H3K27me3 domains were characterised by peak calling and a bed file containing the corresponding coordinates was generated. This bed file was then intersected with interLAD or LAD annotations. All base pairs of an annotation covered by the epigenetic mark were accumulated and divided by the annotation size.

741 Gene ontology and gene signature enrichment

742 Gene ontology analysis was performed using DAVID software 87,88. Signature enrichment studies were completed using DESeq output data used as input in GSEA software 89.

745 Average binding profiles and heatmaps

746 To generate average binding profiles of Lamin B1, annotation files containing the 747 311 apparent bivalent genes in one hand and all genes more expressed on SOFT 748 (identified with DESeq: padj < 0.01 and FC < 1) in another hand were generated. Log2- 749 normalised Lamin B1 WIG files were converted into bigWIG files and used in the 750 Deeptool software 90 to extract signal in a window of 1Mb around the selected 751 annotations. Heatmaps were generated, viewed and colour-scaled using Java 752 TreeView 91. Regions were centred on the annotated transcription start sites (TSS) of 753 the differential protein coding genes identified and signal in defined windows was 754 retrieved from WIG scaled files.

755 Identification of bivalent genes at genome-wide level

756 Promoter regions for all protein coding genes from RefSeq hg19 annotations were 757 defined as a window of 300bp before and 100bp after the annotated transcription start 758 site (TSS). Using the bedtools intersect tool, promoter regions overlapping in their 759 whole with H3K27me3 (in H3K27me3 domains), H3K4me3 (Others) or both (Bivalency 760 - In H3K27me3 domains) were identified.

761 Hi-C analysis

762 Sequences were analysed and aligned using the HiCUP/bowtie2 pipeline 92 with 763 the by default parameters. Briefly, the human genome (hg19) was digested in silico
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764 with the restriction enzymes of the Arima option to create a reference genome.
765 Sequences were then cut at the putative ligation site and all artefacts such as re-
766 ligation of adjacent genomic fragments or PCR duplicates were removed. The
767 remaining were aligned using bowtie2 on the digested reference genome. Homer was
768 then used to generate the interaction matrix.

769 3D contacts modelling

770 3D genomic contacts were modelled with the ShRec3D algorithm using the default
771 parameters 58,93 on chromosomes from 11 to 20. Each colour represents one
772 chromosome.

773 Acknowledgements

774 This work was supported by a grant from "Agence Nationale de la Recherche"
775 (MecEpi, ANR-18-CE12-0019), la Fondation ARC (PJA-2018), La ligue contre le
776 cancer, le cancéropôle GSO Emergence (N°2022-E07 / CANCÉROPÔLE GSO). We
777 are grateful to Robert Feil for critical reading of the manuscript.

778 Author contributions

779 AP and CE designed experiments; AP and MRM performed the experiments; CE,
780 AP and AZEA analyzed genomic data. AT designed the software for lamina thickness
781 determination from high resolution microcopy images. MRM, LC, MM and KB
782 performed the HiD experiments and developed the associated analytical tools. CE
783 conceived and supervised the project, suggested and interpreted experiment. JCA
784 advised on the conception and the supervision of the project. AP and CE wrote the
785 article. All authors reviewed the manuscript.

786 Competing interests

787 Authors declare no competing interests.

788 Data availability

789 The GEO accessions for specific experiments related to this study are recorded
790 under GSE303010, GSE303013, GSE303014, GSE303016 and GSE303035.
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792 **Figure 1: ECM stiffness regulates cell morphology and nuclear lamina**
793 **organisation without major alteration of lamina associating domains**
794 **distribution.**

795 a. Experimental setup.

796 b. Representative confocal images of primary BJ fibroblasts plated on SOFT (top)
797 or STIFF (bottom) hydrogels. Actin stress fibers are labelled with phalloidin
798 (red), focal adhesions are visualised by vinculin staining (green) and nuclei are
799 labelled with DAPI staining (white). Scaling bar: 20µm.

800 c. Western blot of Nuclear Lamina (NL, Lamin A/C and Lamin B1) and NL
801 associated components (LBR and Emerin) at different hydrogel stiffness in
802 primary BJ fibroblasts. Lamin A and C isoforms are highlighted with black
803 arrows. An asterix illustrates an observed shift in LBR size depending on the
804 stiffness conditions. Loading control: VCP (Valosin-Containing Protein). See
805 Figure S1a for quantifications.

806 d. Representative super-resolution microscopy images of nuclei of primary BJ
807 fibroblasts plated either on SOFT (top) or STIFF (bottom) hydrogels. NL
808 component Lamin A/C are in green and nuclei are labelled with DAPI (white).
809 Right: merge of Lamin A/C and DAPI channels. Scaling bar: 5µm.

810 e. Zoom of Lamin A/C signal from dashed white scared region in e. Scaling bar:
811 1µm.

812 f. Quantifications of nuclear volumes and NL thickness from super-resolution
813 images. Blue: values for cells plated on SOFT, red: values for cells plated on
814 STIFF. Statistical tests: Mann-Whitney. Median and quartiles are shown as
815 dashed lines.

816 g. Representative IGB screenshots of Lamin B1 Cut&Run signal normalised over
817 IgG negative control for the whole chromosome 17 in SOFT (top) or STIFF
818 (bottom) condition. Called lamina associating domains (LADs) are illustrated on
819 the top of each track and highlighted with light green rectangles. Dashed black
820 squares illustrate genomic region differentially associated to Lamin B1 in
821 different stiffness conditions.

822 h. Model illustrating observed cell and nuclear changes.

823 **Figure 2: SOFT matrix promotes directed chromatin motion at the nuclear**
824 **periphery.**

825 a. Hi-D analysis workflow.

826 b. Scheme representing anomalous exponent values (α) inferred from HiD.

827 c. Chromatin Mean Square Displacement (MSD) for chromatin located at nuclear
828 periphery or in the center of the nucleus. Blue: MSD from cells plated on SOFT;
829 red: MSD from cells plated on STIFF; black: MSD from fixed cells plated either
830 on SOFT or STIFF. Dashed lines represent the standard deviations.

831 d. Anomalous exponent values (α) depending on nuclear region (center or nuclear
832 periphery or on stiffness. Statistical tests are one-way anova.
833 **Figure 3: Long range 3D chromatin contacts are favoured under SOFT condition**

834 a. Hi-C workflow.

835 b. Decay plot representing interactions frequencies depending on contact distances. Dashed rectangle: highlight the increase of interaction frequencies in SOFT of long distance chromatin regions.

836 837 c. Hi-C maps illustrating contact frequencies over the all chr12 and LADs signals from LaminB1 Cut&Run in cells plated on SOFT (left) and STIFF (middle) hydrogels. Right: differential Hi-C map.

841 d. Zoom on the region defined by the dashed yellow rectangle in (c).

842 e. 3D genome contact models based on Hi-C maps from each stiffness condition for chromosomes from 11 to 20.

844 **Figure 4: Substrate stiffness drives cell adaptation through modifications of**
845 **gene expression programs.**

846 a. IGB screenshots of total RNA signal on stiffness specific mechano-responsive genes. Total RNA signal from cells plated on SOFT (top) and STIFF (bottom) hydrogels are in blue and red respectively.

847 848 b. Volcano plot of differentially expressed genes at total RNA levels between stiffness conditions (DESeq package; threshold: padj < 0.01, Fold-Change: 1). Genes more expressed on SOFT are in blue and those more expressed on STIFF hydrogels are in red.

851 c. Gene ontology (GO) analysis of differentially expressed genes using DAVID.

852 853 d. Enriched transcription factor binding sites in promoters of differentially expressed genes identified (GSEA, TFT module). Blue: enriched in SOFT. Red: enriched in STIFF hydrogels.

854 855 e. Identification of enriched gene signatures in cells plated on SOFT (blue) or STIFF (red) hydrogels using GSEA.

859 **Figure 5: The SOFT gene signature involves H3K27me3-dependent repression**
860 **of apparent bivalent genes.**

861 a. Heatmaps showing changes in gene expression of differentially expressed genes and their associated chromatin landscape (ATAC-seq, H3K4me3 ChIP-seq and H3K27me3 CUT&RUN). Genes are ranked based on the total RNAfold change between SOFT and STIFF conditions. Absolute levels: absolute number of reads from DESeq for each gene. A dashed rectangle highlights a group of genes harbouring both H3K4me3 and H3K27me3.

862 863 b. Metaprofiles confirming the apparent chromatin bivalency and the changes in RNA levels of genes identified in a.

864 865 c. Top: schematic representation of the core PRC2 complex and mode of action of the Tazemetostat drug. Bottom: western-blot comparing H3K27me3 signals
Pigeot et al.

871 without (-) and with (+) Tazemetostat treatment in each stiffness condition. VCP
872 is used as loading control.

873 d. Effects of Tazemetostat treatments on gene expression of mechano-
874 responsive genes. Genes are ranked based on the fold change in expression
875 between SOFT and STIFF hydrogels in DMSO condition. Fold changes in total
876 RNA and H3K27me3 signals in untreated condition are also displayed. Pink:
877 distribution of apparent bivalent genes identified in **a** and **b**. Right:
878 Tazemetostat effect on gene expression in STIFF condition after Tazemetostat
879 treatment (+) compared to DMSO (-).

880 e. Tukey plots comparing fold changes of each of the 10 groups of genes
881 determined in **d**. Statistical tests are Mann-Whitney.

882 **Figure 6: The nuclear lamina integrity is required for a proper repression of**
883 **apparent bivalent genes in STIFF condition.**

884 a. NL scheme illustrating NL (Lamin-A/C and Lamin B1) and NL associated
885 proteins (LBR and Emerin) as well as SUN proteins.

886 b. IGB screenshots of Lamin B1 (light blue), H3K27me3 (black), H3K4me3 (cyan)
887 and total RNA (blue for sense and red for anti-sense) signals on a genomic
888 region containing the *BACH2* gene.

889 c. Metaprofiles of Lamin B1 signals on apparent bivalent genes (Hi-soft, purple)
890 and the other genes more expressed on SOFT hydrogels (blue). The dashed
891 black line representes the average LaminB1 signal on the genome.

892 d. Effects of siRNA treatments on gene expression of mechano-responsive
893 genes. Genes are ranked based on the total-RNA fold change between SOFT
894 and STIFF hydrogels in siNeg condition. Fold changes in total-RNA and
895 H3K27me3 signals in untreated condition are also displayed. Pink: distribution
896 of apparent bivalent genes. Right: siRNA targeting NL or NL-associated
897 proteins effects on gene expression in STIFF condition (+) compared to siNeg
898 (-).

899 e. Tukey plots comparing fold changes of each of the 10 groups of genes
900 determined in d for siLBR, siLMNA and siLMNB1. Statistical tests are Mann
901 Whitney.

902 **Figure 7: Model of bivalently marked genes regulation by mechanical cues.**

903 In both stiffness conditions, we identified genes marked by both H3K4me3 and
904 H3K27me3 and associated to NL. In SOFT condition, Lamin A/C and Lamin B1 are
905 lowly expressed, leading to a loose and wrinkled NL. This low physically constrained
906 context allows chromatin motion, favour 3D genomic interactions and bivalent genes
907 expression. In STIFF condition, NL is reinforced with high expression of Lamin A/C
908 and Lamin B1 proteins. The nuclear flattening and NL stiffening creates a highly rigid
909 and restrictive environment inducing the reduction of chromatin diffusion and the
910 repression of bivalent genes. Tazemetostat targeting EZH2 or siRNA targeting NL
Pigeot et al.

911 main components lead to the re-expression of bivalent genes in STIFF condition,
912 confirming that both PRC2 and the NL are required for the proper repression of these
913 bivalently marked genes in this condition. Finally, this set of gene code for mechano-
914 adaptive genes regulating extracellular matrix interactions, focal adhesion and
915 signalling pathways.

916 **Extended Data Figure 1: LADs organisation is largely unaffected by stiffness.**

917 a. Quantifications of NL and NL-associated proteins abundance by western-
918 blot in Figure 1c. Mean with SEM of 3 independent replicates are
919 represented. Statistical tests are unpaired two-tailed t-tests.

920 b. Tukey plots analysing LADs size (in kb). Middle bar represents the median
921 size.

922 c. Tukey plots of Reads Per Kilobase per Million of reads (RPKM) of total
923 RNAseq in interLAD (iLAD) and LAD regions for each stiffness condition.
924 Middle bar represents the median. Statistical tests are Mann-Whitney.

925 d. Volcano plot of genomic regions differentially associated to Lamin B1
926 between stiffness conditions (DESeq package; threshold: pval < 0.05, Fold-
927 Change: 1.2). Genomic regions more associated on SOFT are in blue and
928 those more associated on STIFF hydrogels are in red.

929 e. IGB screenshots of genomic regions illustrating a genomic locus more
930 associated to Lamin B1 in SOFT (left) or in STIFF (right) hydrogels. Arrows
931 on top represent LADs called in SOFT (blue), in STIFF (red) or the merge of
932 both conditions (black). Region more associated in SOFT: Fold-change =
933 0.69 and p-value = 1.3e-9. Region more associated in STIFF: Fold-change =
934 1.54 and p-value = 4.42e-20.

935 **Extended Data 2: Matrix stiffness regulates gene expression programs at**
936 **transcriptional levels.**

937 a. Comparison of gene expression changes driven by matrix stiffness at whole
938 protein coding gene and intronic reads levels. Genes are ranked based on
939 their RNA-seq fold change between SOFT vs STIFF hydrogels at the whole
940 gene level. Associated ratio at intronic levels are shown on the right.
941 Absolute levels of expression corresponding to the number of reads from
942 DESeq are shown for both whole and intronic signals.

943 b. Volcano plot of differentially expressed genes between soft and stiff
944 hydrogels at intronic levels. (DESeq package; threshold: padj < 0.01, Fold-
945 Change = 1). Genes more expressed on SOFT are in blue and those more
946 expressed on STIFF hydrogels are in red.

947 c. Venn-diagrams illustrating the genes that are differential at whole, intronic or
948 both levels depending on stiffness conditions.

949 d. Gene ontology (GO) analysis of differentially expressed genes at intronic
950 levels.
951 **Extended Data 3: Bivalent genes tend to be more expressed under SOFT**
952 **condition at genome-wide levels.**

953 a. Tukey plots of RPKM from total RNA-seq experiments for genes marked in
954 their promoter (region -300bp before and +100bp after TSS) with H3K4me3
955 only (Others: SOFT n=8824 and STIFF n=8578) or with in H3K27me3 only
956 (SOFT n=3252, STIFF n=3903). Bivalency: genes harbouring H3K4me3 and
957 H3K27me3 at their promoters (SOFT n=606 and STIFF n=1055). Middle bar
958 represents the median. Statistical tests are Mann-Whitney.

959 b. Gene ontology (GO) analysis of apparent bivalent genes.

960 **Extended Data 4: EZH2 also impact gene activation in STIFF condition**

961 a. Quantifications H3K27me3 abundance analysed by western-blot in Figure
962 4c. Mean with SEM of 2 independent replicates are represented.

963 b. Venn-diagrams comparing mechano-dependent genes identified in
964 Untreated and DMSO condition.

965 c. Effects of Tazemetostat treatments on gene expression of mechano-
966 responsive genes. Only genes with common effects between untreated and
967 DMSO control conditions were considered, to avoid indirect DMSO effects.
968 Genes are ranked based on their total RNA fold changes between SOFT and
969 STIFF hydrogels in the DMSO condition. Fold changes in total RNA and
970 H3K27me3 signals in untreated condition are also displayed. Pink:
971 distribution of apparent bivalent genes identified in **a** and **b**. Right:
972 Tazemetostat effect on gene expression in SOFT condition in Tazemetostat
973 treated cells (+) compared to DMSO (-).

974 d. Tukey plots comparing fold-changes of each of the 10 groups of genes
975 determined in **c**. Statistical tests are Mann-Whitney.

976 **Extended Data 5: Impairing the nuclear lamina components has little effects on**
977 **gene expression in cells grown on SOFT condition.**

978 a. Base pair coverage of H3K27me3 on interLAD (iLAD) or (LAD) depending
979 on stiffness conditions.

980 b. Venn-diagrams comparing differential genes identified in Untreated and
981 siNeg conditions.

982 c. Effects of the siRNA on their target genes. Barplots representing mean with
983 SD of RPKM from total RNA-seq experiments of the siRNA target genes.
984 siNeg (control) and specific siRNA effects are shown on their target genes in
985 each stiffness condition. Each bar represents 3 independent replicates.

986 d. Effects of siRNA treatments on gene expression of mechano-responsive
987 genes on SOFT hydrogels. Only genes with common effects between
988 untreated and siNEG control conditions were considered, to avoid indirect
989 effects of transfection reagents. Genes are ranked based on their total-RNA
Pigeot et al.

990 fold change between SOFT and STIFF in the siNEG condition. Fold changes
991 in total RNA and H3K27me3 signals in untreated condition are also
992 displayed. Pink: distribution of apparent bivalent genes identified in a and b.
993 Right: siRNA targeting NL or NL-associated proteins effects on gene
994 expression in SOFT condition (+) compared to siNeg (-).

995 e. Tukey plots comparing fold changes of each of the 10 groups of genes
996 determined in d for siLBR, siLMNA and siLMNB1. Statistical tests are Mann-
997 Whitney.

998
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1209
<figure><img src="image_3.png" /><figcaption>Pigeot *et al.* Figure 1</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>Pigeot et al. Figure 2</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>Pigeot *et al.* Figure 3</figcaption></figure>

Chr11

Chr12

Chr13

Chr14

Chr15

Chr16

Chr17

Chr18

Chr19

Chr20

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>
<figure><img src="image_8.png" /><figcaption>Pigeot *et al.* Figure 4</figcaption></figure>
<figure><img src="image_9.png" /><figcaption>Pigeot *et al.* Figure 5</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>Pigeot *et al.* Figure 6</figcaption></figure>

<figure><img src="image_11.png" /></figure>
<figure><img src="image_12.png" /></figure>

Gene expression program of mechano-adaptative genes: Extracellular matrix interactions, focal adhesion and signaling pathways
Pigeot *et al.* Extended Data Figure 1

<figure><img src="image_13.png" /><figcaption>b
LADs size</figcaption></figure>

<figure><img src="image_14.png" /><figcaption>c
TotRNA</figcaption></figure>

<figure><img src="image_15.png" /><figcaption>d
Lamin B1 domains</figcaption></figure>

<figure><img src="image_16.png" /><figcaption>e
More associated in **SOFT**
More associated in **STIFF**</figcaption></figure>

<figure><img src="image_17.png" /></figure>
<caption>Pigeot *et al.* Extended Data Figure 2</caption>

a

<figure><img src="image_18.png" /></figure>

<figure><img src="image_19.png" /></figure>

c

<figure><img src="image_20.png" /></figure>

<figure><img src="image_21.png" /></figure>
Pigeot *et al.* Extended Data Figure 3

a

Gene expression levels

<figure><img src="image_22.png" /></figure>

b

Gene ontology
Enriched pathways: Bivalent genes

<figure><img src="image_23.png" /></figure>
Pigeot et al. Extended Data Figure 4

a

H3K27me3 signal

<figure><img src="image_24.png" /></figure>

b

Genes more expressed in **SOFT**

<figure><img src="image_25.png" /></figure>

Genes more expressed in **STIFF**

<figure><img src="image_26.png" /></figure>

c

<figure><img src="image_27.png" /></figure>

<figure><img src="image_28.png" /></figure>

d

<figure><img src="image_29.png" /></figure>
<figure><img src="image_30.png" /><figcaption>Pigeot *et al.* Extended Data Figure 5</figcaption></figure>