EMBO/soda-nel huggingface dataset:
HMGB1 coordinates SASP-related chromatin folding and RNA homeostasis on the path to senescence (2021)
Figure 2

Figure 2 HMGB1 binds active genomic loci and demarcates a subset of TAD and loop domains.

Genome browser view of HMGB1 ChIP-seq (normalized to input; mean from two replicates) from proliferating HUVEC (red) or proliferating/senescent IMR90 (grey/green) in the TMEM92 locus.

Bar graphs showing the genomic distribution of HMGB1 ChIP-seq peaks in HUVEC and IMR90. The number of peaks (N) analyzed per each cell type is indicated.

Venn diagram showing HMGB1 ChIP-seq peaks shared between proliferating HUVEC (red) or proliferating/senescent IMR90 (grey/green) data. *: P<0.001; more than expected by chance, hypergeometric test.

Exemplary Hi-C heatmap for a subregion of IMR90 chr6 aligned to HMGB1 ChIP-seq; peaks at TAD boundaries (orange lines) are indicated (red arrowheads).

Line plots showing normalised HMGB1 (red) and CTCF ChIP-seq signal (dark grey) along TADs ±20 kbp from proliferating IMR90.

Line plots showing normalised HMGB1 (red) and CTCF ChIP-seq signal (dark grey) in the 160 kbp around HMGB1- (left) or CTCF-marked TAD boundaries (right).

Line plots showing mean normalized insulation scores calculated from proliferating (black) and senescent IMR90 Hi-C data (blue) in the 240 kbp around HMGB1 peaks residing at TAD boundaries (top) or not (bottom).

Aggregate plots showing 20 kbp-resolution Hi-C signal for proliferating (top), senescent-specific (bottom) or shared loops (middle). The number of loops in each category (N) is indicated.

Line plots showing normalised HMGB1 (red) and CTCF ChIP-seq signal (grey) along proliferating (top) or shared loop domains (bottom) ±50 kbp from proliferating IMR90. The percentage of HMGB1 peaks residing at loop anchors is indicated.

Box plot (left) showing significantly up/downregulated IMR90 genes harboured inside the 607 loops from panel H. The number of genes in each group (N) is indicated; center lines represent medians, box limits indicate the 25th and 75th percentile, whiskers extend 1.5 times the 25th-75th interquartile range, and outliers are represented by dots. Bar plots (right) show Go terms associated with these up/downregulated genes.
HMGB1 coordinates SASP-related chromatin folding and RNA homeostasis on the path to senescence (2021)
Figure 4

Figure 4 Modulating HMGB1 expression induces senescence-specific gene expression changes.

Immunofluorescence (top), western blot (middle) and RT-qPCR analyses (bottom; mean fold-change ±S.D. from two biological replicates) confirm HMGB1 knockdown in IMR90.

PCA analysis plot (top) of control (black) and HMGB1-knockdown replicates (blue). Scatter plot (bottom) showing significantly up- (>0.6 log2-fold change; orange) or downregulated genes (<-0.6 log2-fold change; green) upon HMGB1 knockdown.

Bar plots showing GO terms associated with the up/downregulated genes from panel B and their enrichment P-values (-log; right).

Gene set enrichment analysis of HMGB1-KD data. Normalized enrichment scores (NES) and associated P-values for each gene set are shown.

Representative images of IMR90 overexpressing HMGB1-GFP, immunostained for p21 and CTCF, and counterstained with DAPI. IMR90 transfected with empty vectors provide a control. Bar: 5 μm.

Bar plots showing RT-qPCR data (mean mRNA fold-change ±S.D., from two biological replicates) for selected genes in HMGB1-overexpressing compared to control IMR90. The mean fold-change for each mRNA from HMGB1-knockdown RNA-seq data is also shown for comparison (magenta bars). *: P<0.01; unpaired two-tailed Student's t-test.
HMGB1 coordinates SASP-related chromatin folding and RNA homeostasis on the path to senescence (2021)
Figure 5

Figure 5 HMGB1 binds specific mRNAs and its loss affects splicing.

Volcano plot (left) showing mass-spec data for proteins co-immunoprecipitating with HMGB1. Statistically-enriched HMGB1 interactors (orange dots) associate with the GO terms/pathways illustrated in the network analysis (right; node size reflects the number of proteins it includes; proteins are listed in Dataset EV4).

Venn diagram showing 1/3 of HMGB1 interactors classifying as RNA-binding proteins (according to Castello et al, 2016).

Genome browser views showing HMGB1 sCLIP data (black) along the ASH1L, CCNL2 and TET2 loci; input tracks (grey) provide background levels. *: significantly-enriched peaks. The consensus motif for HMGB1 binding on RNA is also shown (bottom right).

Bar graphs showing genomic distribution of HMGB1 RNA-bound peaks (log2 enrichment).

Bar plots showing relative occurrence of differential-splicing events in IMR90 undergoing senescence (left), in HMGB1-knockdown IMR90 (middle) or in HMGB1-bound mRNAs (right). The number of bound mRNAs (N) analyzed is indicated below each bar.

Venn diagram showing differential-splicing events shared between conditions from panel F.

Heatmaps showing GO terms/pathways associated with differentially-spliced mRNAs shared between senescence entry and HMGB1-knockdown from panel F.

As in panel G, but for the 75 mRNAs also bound by HMGB1 in sCLIP data.

Venn diagram (left) showing 15 HMGB1 interacting proteins from panel A are also downregulated upon both senescence entry and HMGB1-knockdown in IMR90. Of these, 12 are RBPs, 6 have been implicated in senescence (asterisks), and 4 are bound by HMGB1 in sCLIP data (arrows).

Bar graphs showing mean fold-change of selected mRNAs (over ±S.D. from two biological replicates) from ILF3- (purple), RBMX- (white) or PNN-knockdown experiments (blue) in proliferating IMR90. *: significantly different to siRNA controls; P<0.01, unpaired two-tailed Student's t-test. Dashed line indicates no change in expression.
Precise transcriptional control of cellular quiescence by BRAVO/WOX5 complex in Arabidopsis roots (2021)
Figure 1

Figure 1: BRAVO and WOX5 are required for the QC identity and stem cells maintenance.

A-D) Confocal images of mPS-PI stained 6-day-old seedlings of Col-0 (A), bravo-2 (B), wox5-1 (C) and bravo-2 wox5-1 (D) mutants. Left black arrows indicate QC cells and right white arrows indicate CSC. Scale bar: 50 µm.

E) Quantification of the QC divisions in 6-day-old roots expressed in percentage (n>50, 3 replicates). D: QC divided; ND: QC non divided.

F) Quantification of CSC layers in 6-day-old roots expressed in percentage (n>50, 3 replicates).

G) Lateral root density (number of lateral roots per mm of root length) of 7-day-olf WT, bravo-2, wox5-1 and bravo-2 wox5-1 mutants (n>40, 2 replicates). Different letters indicate statistically significant differences (p- value < 0.05 Student´s t-test). In the boxplot, box width represents the interquartile range (IQR=Q3-Q1), with the horizontal line denoting the median, while whiskers extend from Q1-1.5IQR to Q3+1.5IQR. White dots are the outliers.
Precise transcriptional control of cellular quiescence by BRAVO/WOX5 complex in Arabidopsis roots (2021)
Figure 2

Figure 2: BRAVO and WOX5 reinforce each other at the root stem cell niche.

A-G) Confocal images of PI-stained 6-day-old roots. GFP-tagged expression is shown in yellow. A-C) pBRAVO:GFP in WT (A), bravo-2 (B) and wox5-1 (C) knockout backgrounds. D-G) pWOX5:GFP in the WT (D), bravo-2 (E), wox5-1 (F) and bravo-2 wox5-1 (G) knockout backgrounds. Scale bar: 50 µm.

H, I) Quantification of the GFP fluorescent signal of the roots in A-C (H) and D-G (I). Boxplot indicating the average pixel intensity of the GFP in the stem cell niche (n>25, 3 biological replicates, *p-value < 0.05 Student´s t- test for each genotype versus the WT in the same condition). Quantification was done by integrating the GFP signal in each root across defined areas that included the whole SCN (Appendix Figure S7). In the boxplot, box width represents the interquartile range (IQR=Q3-Q1), with the horizontal line denoting the median, while whiskers extend from Q1-1.5IQR to Q3+1.5IQR. White dots are the outliers and black dots are the experimental observations.
Precise transcriptional control of cellular quiescence by BRAVO/WOX5 complex in Arabidopsis roots (2021)
Figure 3

Figure 3: Two different models for the cross-regulations between BRAVO and WOX5 in the SCN

A, B) Schematic representation of the effective regulations in the SCN between BRAVO and WOX5 in the Alleviation (A) and Activation (B) models. (A) In the alleviation model BRAVO feeds back on its own expression by reducing it and is activated by WOX5. WOX5 also feeds back on its own expression by reducing it, a regulation that becomes partially impaired by BRAVO. (B) In the activation model, BRAVO is also able to activate WOX5 which negatively feedbacks on its own expression. BRAVO is regulated by WOX5 as in the alleviation model.

C, D) Parameter space exploration of (C) the alleviation and the (D) activation models. Boxplots showing the distribution of stationary promoter pBRAVO (pB) and pWOX5 (pW) fold-changes in each mutant and overexpression lines over the WT obtained for different parameter values. Superindexes denote the genotype, standing bravo for bravo mutant, wox5 for wox5 mutant, dm for the bravo wox5 double mutant, Woe for WOX5 overexpression and Boe for BRAVO overexpression. Box width represents the interquartile range (IQR=Q3-Q1), with the horizontal line denoting the median, while whiskers extend from Q1-1.5IQR to Q3+1.5IQR. The results are obtained by solving N=1000 different runs of each model at the stationary state (red and blue stripplots) for the WT, mutants and overexpressor scenarios. These N runs differ in the parameter values, which are chosen at random from a uniform distribution between
Precise transcriptional control of cellular quiescence by BRAVO/WOX5 complex in Arabidopsis roots (2021)
Figure 4

Figure 4: BRAVO interacts with WOX5.

A-J) Interaction of BRAVO with WOX5 (B), BES1 (C), BES1D (D) and TPL (E); and interaction of WOX5 with BRAVO (G), BES1 (H), BES1D (I) and TPL (J) measured by FRET-FLIM. GFP fluorescence lifetime τ [ns] was measured in transiently expressing Nicotiana benthamiana leaf epidermal cells. GFP fluorescence lifetime fitted pixel-wise with a mono-exponential model of BRAVO and WOX5 interactions. mV, mVenus; mCh, mCherry. Scale bar: 5 µm.

K) Fluorescence-weighted average lifetimes of BRAVO and WOX5 interactions fitted with a double-exponential model of the indicated samples are summarized in box plots. Statistical significance was tested by one-way ANOVA with a Sidakholm post-hoc test. Different letters indicate statistically significant differences (p-value < 0.01). For each combination two to three independent experiments were carried out and in total more than 20 biological replicates were measured. In the boxplot, box width represents the interquartile range (IQR=Q3-Q1), with the horizontal line denoting the median, while whiskers extend from Q1-1.5IQR to Q3+1.5IQR. White dots are the outliers.

L) Yeast two-hybrid assay showing BRAVO interacting with WOX5, BES1-D and TPL; and BES1-D interacting with TPL. In the left column yeast cells were grown on control media, and in the right column yeast cells were grown on control media lacking Leu, Trp and His, indicating an interaction between the proteins.
Precise transcriptional control of cellular quiescence by BRAVO/WOX5 complex in Arabidopsis roots (2021)
Figure 6

Figure 6: Transcriptional profile of bravo and wox5 QC cells.

Scheme of the methodology used for the QC-specific RNAseq. Plants expressing pWOX5:GFP in WT, bravo-2 and wox5-1 background were used for protoplasting followed by Fluorescent Activated Cell Sorting (FACS) to isolate QC for RNA sequencing.

Area-proportional Venn diagram showing the overlap between BRAVO and WOX5 regulated genes in the QC (q-value< 0.05 and FC > 1).

Expression of the 380 common BRAVO and WOX5 regulated genes from (B).

Expression of the 53 genes from (C) showing similar expression in bravo and wox5 mutants.

Expression of the 41 genes from (C) showing opposite expression levels in bravo and wox5 mutants.

Data information: Left column in (C, D and E) heatmaps shows expression WT vs bravo comparisons. Right column shows expression in WT vs wox5 comparisons. Color bar: log2 of the fold change.
PP4-dependent HDAC3 dephosphorylation discriminates between axonal regeneration and regenerative failure (2019)
Figure 1

Figure 1. Pharmacological HDAC3 inhibition and HDAC3 dead mutant enhance DRG neurite outgrowth

A. RGFP966 (966)-dependent HDAC3 inhibition resulted in significant and robust neurite outgrowth (24h in culture) compared to HDAC class II, HDAC1/2 and HDAC1 or 3 inhibitions via 69A, 963 and 233 respectively.

B, C. Specific pharmacological inhibition of HDAC3 facilitates DRG neurite outgrowth (average neurite outgrowth after 24h in culture, Tuj1 positive neurons) on PDL-laminin or Myelin substrates. Scale bars, 100 μm.

D, E. Immunoblotting shows significantly increased H3K9 acetylation after 966 vs vehicle.

F, G. AAV-mediated mutant HDAC3 (Y298H, V5) infection of DRG neurons induces neurite outgrowth (Tuj-1/V5 double positive neurons) after 36h in culture, which is repressed by wildtype HDAC3 overexpression. Scale bars, 100 μm.

Data information: Data expressed as mean fold change or average neurite length ± s.e.m. N= 3-9 biological replicates. (*p<0.05, **p<0.01, ***p<0.005) indicate significant difference of 966 versus vehicle or V5 vs AAV-GFP (C and E, Student's t-test) (A and G, ANOVA followed by Bonferroni test).
PP4-dependent HDAC3 dephosphorylation discriminates between axonal regeneration and regenerative failure (2019)
Figure 2

Figure 2. Regenerative sciatic nerve injury selectively decreases HDAC3 phosphorylation and activity in DRG neurons.

A. IHC in DRG sections for pHDAC3 revealed that HDAC3 phosphorylation is decreased, primarily in the nucleus 24h after sciatic nerve axotomy (SNA) but not spinal dorsal column axotomy (DCA). Scale bars, 100 μm.

B-C. Bar graphs show mean fold change levels (B) or % of pHDAC3+ cells (C) (pHDAC3+ threshold was set at the minimum intensity level of sham cells) ± s.e.m. DAPI counter staining was used to label nuclei N= 9-10 biological replicates. (***p<0.005) indicate significant difference versus sham or laminectomy (lam) (ANOVA followed by Bonferroni test).

D. Western blot revealed that HDAC3 phosphorylation is decreased in DRG nuclear extracts but not in the cytoplasm 24h after SNA.

E. Bar graphs show intensity measurement of nuclear vs cytoplasm immunoblot. Data is expressed as mean ± s.e.m. N= 3 biological replicates. (***p<0.005) indicate significant difference versus sham (Student´s t-test).

F. HDAC3 activity (HDAC3 IP and activity assay) is strongly reduced after SNA but not DCA. Data is expressed as mean ± s.e.m. N= 3 biological replicates. (*p<0.05) indicate significant difference versus sham (ANOVA followed by Bonferroni test).
PP4-dependent HDAC3 dephosphorylation discriminates between axonal regeneration and regenerative failure (2019)
Figure 3

Figure 3. SNA induced calcium regulates PP4/2 activity that in turn control HDAC3 phosphorylation and DRG regenerative growth.

A-B. PP4 and PP2 activities are induced after SNA but not DCA, and are blocked by the calcium chelator EGTA. Data is expressed as mean ± s.e.m. N= 3-4 biological replicates. (***p<0.001) indicate significant difference versus sham or lam (Two-way ANOVA followed by Bonferroni test).

C. SNA but not DCA significantly enhances calcium levels in DRG. Data is expressed as mean ± s.e.m. N= 4 biological replicates. (*p<0.05) indicate significant difference versus sham or lam (ANOVA followed by Bonferroni test).

D-F. Immunoblotting of DRG homogenates shows that nerve injury-dependent nuclear HDAC3 dephosphorylation is reduced by the calcium scavenger EGTA upon in vivo delivery on the injured sciatic nerve (Axo=Axotomy). Cytoplasmic pERK levels are used as control of axotomy-dependent signalling. (E-F). Data is expressed as mean fold change of band intensity levels ± s.e.m. N= 3 biological replicates. (**p<0.01, ***p<0.001) indicate a significant difference (ANOVA followed by Bonferroni test).

G-H. Significant Pearson correlations between calcium levels (Fluo4AM) and H3K9ac, r2: 0.7802 (G); or pHDAC3, r2: 0.6366 (H) in cultured DRG neurons after KCl. The Pearson correlations were disrupted by administration of Fostriecin (calcium and H3K9ac, r2: 0.0007; calcium and pHDAC3, r2: 0.3025). Data is expressed as single cell fluorescence levels. N=50 cells per condition from 4 biological replicates.

I. Schematic pathway summarizing Ca2+ and PP4c and PP2a-dependent HDAC3 dephosphorylation.

J-L. Immunofluorescence (J) in DRG tissue sections 24h after injury in vivo shows that the PP2a/PP4 inhibitor Fostriecin (F) inhibits the injury-induced decrease in pHDAC3 (K) and the increase in H3K9ac (L). Scale bar, 10 μm. (K-L). Data is expressed as mean fluorescence intensity in arbitrary units ± s.e.m. N= 3 (L) or 4 (K) biological replicates (*p<0.05; **p<0.01) indicate significant difference versus sham (ANOVA followed by Bonferroni test).

M-N. Pharmacological inhibition of PP2a/PP4 impairs conditioning-induced DRG neurite outgrowth ex vivo (12h in culture). M. DRG neurite outgrowth (TUJ1 positive cells) 24h after sham or sciatic nerve axotomy (SNA) prior to i.t. administration of vehicle (V) or Fostriecin (F) (240µM). Scale bar, 100µm. (N) Data is expressed as average neurite length per neuron ± s.e.m. N= 3 biological replicates per condition, technical triplicate. *** p<0.005 indicate significant difference versus sham/vehicle (One way ANOVA followed by Bonferroni).
PP4-dependent HDAC3 dephosphorylation discriminates between axonal regeneration and regenerative failure (2019)
Figure 4

Figure 4. PP4c and PP2A dephosphorylate HDAC3 at Ser424, which is required for DRG outgrowth

A-E. PP4c gene silencing promotes HDAC3 phosphorylation in the presence of KCl (A-C, arrows), both in the nucleus and the cytoplasm (D). Scale bar, 20 μm. (C,D) Data is expressed as mean fold change vs scrambled (scr) siRNA of fluorescent intensity of pHDAC3 or PP4c in GFP positive cells ± s.e.m. N=3 biological replicates. (**p<0.01; ***p<0.005) indicate significant difference versus scrambled siRNA (Student's t-test). (E) PCR against PP4c demonstrates silencing of PP4c mRNA.

F-G. PP2a gene silencing inhibits the KCl induced dephosphorylation of HDAC3 as shown by immunoblotting of pHDAC3 (F). (G) Data is expressed as mean fold change of immunoblot band intensity ± s.e.m. N= 3 biological replicates (*p<0.05; ****p<0.001) indicate significant difference versus control siRNA (Student's t-test).

H-I. Genetic modification of activity-dependent phosphorylation of serine 424 of HDAC3 affects DRG neurite outgrowth. (H) DRG neurite outgrowth after transfection of control (V5 control), WT HDAC3-V5, phospho-dead HDAC3 (S424A)-V5 or phospho-mimetic HDAC3 (S424D)-V5 and after 24h in culture. Scale bar, 50µm. (I) Data is expressed as mean ± s.e.m. N= 8-9 biological replicates, approximately 35 V5 positive cells each. * p<0.05, ** p<0.01, *** p<0.005 indicate significant difference (One way ANOVA followed by Bonferroni).
PP4-dependent HDAC3 dephosphorylation discriminates between axonal regeneration and regenerative failure (2019)
Figure 5

Figure 5. H3K9ac ChIPseq and HDAC3 interactome signalling network.

A. The graph shows the number of differentially expressed (DE) genes 24h following SNA or DCA compared to their respective controls.

B. RNAseq read counts show differential occupancy of H3K9ac on specific gene regions, including an increased occupancy close to the transcriptional start site (TSS) after SNA only, when compared to corresponding controls.

C. Bar graph shows the number of genes that are upregulated or downregulated following SNA or DCA (RNAseq) with an increased or decreased H3K9ac occupancy (ChIPseq), respectively.

D. Odds ratio analysis of the enrichment/depletion of genes with differential H3K9ac occupancy across each upregulated and downregulated gene cluster in (C); the numbers in red represent the p value given by Fisher's exact test (ns= not significant).

E. Out of the 321 upregulated genes associated with increased H3K9ac upon SNA, the majority does not show a change in expression following DCA (grey), while some of them are downregulated (white).

F. Cytoscape visualization of the protein network resulting from HDAC3 interactome and H3K9ac ChIPseq and RNAseq upon SNA. The signalling network was created by combining the protein interactome of HDAC3 and H3K9ac dependent genes with increased gene expression upon SNA. HDAC3 is in red at the center of the network. The line thickness is proportional to the interaction score. Highlighted in orange circles are the validated pathways and targets via IHC (Figure 6) or ChIP-qPCR (EV Figure 4), regeneration associated genes (RAG) are highlighted in orange triangles.
PP4-dependent HDAC3 dephosphorylation discriminates between axonal regeneration and regenerative failure (2019)
Figure 6

Figure 6. Intrathecal pharmacological inhibition of HDAC3 activity promotes H3K9ac and RAG expression in DRG neurons after spinal cord injury.

A, B. Co-immunofluorescence of anti-neuronal and anti-regeneration associated proteins in DRG following SCI and treatment with 966 or vehicle. Shown is increased protein expression for regeneration-associated targets in NF200 positive DRG neurons (arrows) after 966 treatment (5 weeks following SCI). Scale bar, 50 μm. (B) Data is expressed as fold change of fluorescence intensity in NF200+ cells, 966 versus vehicle ± s.e.m. N=4-7 biological replicates * p<0.05, ** p<0.01, *** p<0.005 indicate significant difference versus vehicle (Student's t-test).
PP4-dependent HDAC3 dephosphorylation discriminates between axonal regeneration and regenerative failure (2019)
Figure 7

Figure 7. Genetic inactivation of HDAC3 deacetylase activity with HDAC3 dead mutant promotes DRG regenerative growth in vivo after SCI.

A-B. AAV-HDAC3 mutant (Y298H; dominant negative deacetylase inactive) promoted DRG regenerative growth after spinal cord injury vs AAV-V5 control (injected 5 weeks prior to SCI in the sciatic nerve bilaterally) as shown by dextran-red traced axons across and beyond the lesion site (GFAP, green) (dotted lines denote the rostral and caudal margins of the scar around the lesion). Scale bar, (A-B) 200 μm.

C-F. Immunofluorescence for H3K9ac. AAV-HDAC3 mutant induced upregulation of H3K9ac in vivo in DRG neurons, but not in surrounding nuclei of satellite cells. Scale bar, (C-F) 50 μm.

G-J. New synaptic formations (VGlut1+) from regrowing axons are shown beyond the lesion site after injection of AAV-HDAC3mut. (G) Scale bar 200 μm, (H-J) High magnification insets depict co-localization of Dextran and vGlut1 staining. Scale bar 50 μm.

K-L. Quantification of dextran positive axons shows that AAV-HDAC3mut promotes DRG regenerative growth across and beyond the spinal lesion site. Data is expressed as percentage of dextran+ axons at each distance vs dextran+ axons at -700μm from the lesion margin (K) or distance from the caudal margin of the lesion to the most rostral dextran+ axon tip for each animal (L). N= 10 animals per condition, ± s.e.m. *p<0.05, **p<0.01, ***p<0.005, ****p<0.001 indicate a significant difference (ANOVA followed by Bonferroni test).
ALX1-related Frontonasal Dysplasia Results From Defective Neural Crest Development and Migration (2020)
Figure 3

Figure 3: Timeline of key NCC-associated genes during differentiation.

Gene expression analysis across NCC differentiation of unaffected control ALX1165L/165L (green), heterozygous ALX1165L/165F (magenta) and homozygous ALX1165F/165F iPSC: ALX1, neural plate border specifier genes ZIC1, PAX7, PAX3, MSX1, MSX2, DLX5; neural crest specifier genes FOXD3, P75, TFAP2A, SNAI2, TWIST1; and lineage specifier gene HAND2. The RT-qPCR relative expression values were normalized to RPLP0 and GAPDH expression. Data is represented as pooled mean ± SEM of three experiments on three clones from each genotype. Exact p-values are provided in Table EV1. Data from each clone were pooled and the mathematical mean was calculated. SEM was used to determine the standard error. To test statistical significance, an ANOVA test was performed. A p-value <0.05 was considered to be statistically significant.