Journal: Journal of immunology (Baltimore, Md. : 1950)

Article Title: RREB-1 is a transcriptional repressor of HLA-G.

doi: 10.4049/jimmunol.0902053

Figure Lengend Snippet: FIGURE 8. In situ binding of RREB-1 or HDAC1 to the HLA-G pro- moter in a repressive and active-type chromatin. A and B, ChIP performed with JEG-3 (HLA-G ) and M8 (HLA-G ) cells using anti-RREB-1 and anti-HDAC1 Abs on distal and proximal promoter regions (A) Abs target- ing RNA polymerase II (RNApolII), acetylated histone H3 (AcH3), and phosphorylated histone H3 (AcH3 P) on proximal promoter region (B). Immunoprecipitated HLA-G promoter regions are analyzed on agarose gels by semiquantitative HLA-G-specific PCRs targeting proximal and distal HLA-G promoter. Input chromatin (Input) used as PCR control and IgG () are shown. The absence of RREB-1 and HDAC1 binding observed in JEG-3 cells and the absence of RNA polymerase II, acetylated histone H3, and phosphorylated histone H3 binding in M8 cells validate the specificity of Abs used in ChIP assays.

Article Snippet: ChIP assays were performed as previously described (51) using antiRREB-1 from Rockland; anti-acetylated histone H3 (06-599) and antiphosphorylated Ser10 histone H3 (07-081) from Upstate Biotechnology Associates; and anti-RNApolII (C-21) and anti-HDAC1 (H-51) from Santa Cruz Biotechnology.

Techniques: In Situ, Binding Assay, Immunoprecipitation, Control

Journal: Bioinformatics

Article Title: Deep5hmC: predicting genome-wide 5-hydroxymethylcytosine landscape via a multimodal deep learning model

doi: 10.1093/bioinformatics/btae528

Figure Lengend Snippet: Overview of Deep5hmC. ( A ) The training set of Deep5hmC can be derived from matched 5hmC-seq and other epigenetic data such as histone ChIP-seq or DNase-seq/ATAC-seq from one condition. Specifically, the 5hmC-seq data can be collected from tissue-specific human tissues, which include bladder, brain, breast, heart, kidney, liver, lung, marrow, ovary (female), pancreas, placenta (female), prostate (male), colon (sigmoid), colon (transverse), skin, stomach, and testis (male). The matched tissue-specific epigenetic data, such as histone ChIP-seq data profiling histone modification and DNase-seq/ATAC-seq profiling chromatin accessibility, can be collected from public consortiums such as Roadmap Epigenomics and ENCODE. In this context, Deep5hmC aims to predict genome-wide 5hmC modification in a single condition. ( B ) The training set of Deep5hmC can also be derived from matched 5hmC-seq and ChIP-seq from a case–control study (e.g. Alzheimer’s disease (AD) versus healthy control) for predicting differentially hydroxymethylated regions (DhMRs). ( C ) Deep5hmC is a multimodal deep learning model to improve the prediction of tissue/cell type-specific genome-wide 5hmC modification by leveraging both DNA sequence and epigenetic features such as histone modification and chromatin accessibility. Deep5hmC consists of four modules, including Deep5hmC-binary, Deep5hmC-cont, Deep5hmC-gene, and Deep5hmC-diff. Specifically, Deep5hmC-binary takes the labeled 5hmC peaks and non-peaks as the training set to identify the 5hmC-enriched regions. Deep5hmC-cont takes the normalized read counts in 5hmC peaks and aims to predict the continuous 5hmC modification genome-wide. By leveraging Deep5hmC-cont, Deep5hmC-gene aggregates the predictions of Deep5hmC-cont in the gene bodies as the surrogate for the predicted gene expression. Different from Deep5hmC-binary, Deep5hmC-diff takes the labeled DhMRs/non-DhMRs in a case–control design of 5hmC-seq as the training set to predict genome-wide DhMRs and may discover de novo DhMRs. ( D ) Model architecture of Deep5hmC. Deep5hmC consists of both sequence modality and epigenetic modality consisting of their own convolutional neural networks (CNNs) to derive separate feature representations, which will be joined later via the multi-modal factorized bilinear (MFB) pooling fusion layer. The output of the MFB fusion layer will further connect to fully connected layers and the output layer afterward.

Article Snippet: For “Human Tissues,” we carefully select aligned bed files of ChIP-seq data from Roadmap Epigenomics by ensuring a match between ChIP-seq data and 5hmC-seq data based on tissue type.

Techniques: Derivative Assay, ChIP-sequencing, Modification, Genome Wide, Control, Sequencing, Labeling, Expressing

Journal: Bioinformatics

Article Title: Deep5hmC: predicting genome-wide 5-hydroxymethylcytosine landscape via a multimodal deep learning model

doi: 10.1093/bioinformatics/btae528

Figure Lengend Snippet: Distribution pattern of histone modification around 5hmC peaks. EB 5hmC peaks are collected from “Forebrain Organoid” 5hmC-seq data and ChIP-seq data in “Brain Angular Gyrus” from seven histone marks are collected from Roadmap Epigenomics. Histone features are obtained and averaged in the neighborhood of all 5hmC peaks for the positive and negative sets, respectively. Specifically, histone features are created by segmenting an extended genomic region of 10 kb both upstream and downstream of each 5hmC peak into 41 1 kb windows with a sliding size of 500 bp and counting reads for each 1 kb windows. For each histone mark, the Kolmogorov–Smirnov test is performed to test the distribution difference of histone features between positive and negative 5hmC peaks and the P -value is reported.

Article Snippet: For “Human Tissues,” we carefully select aligned bed files of ChIP-seq data from Roadmap Epigenomics by ensuring a match between ChIP-seq data and 5hmC-seq data based on tissue type.

Techniques: Modification, ChIP-sequencing

Journal: Bioinformatics

Article Title: Deep5hmC: predicting genome-wide 5-hydroxymethylcytosine landscape via a multimodal deep learning model

doi: 10.1093/bioinformatics/btae528

Figure Lengend Snippet: Comparison of unimodal and multimodal Deep5hmC for predicting binary 5hmC modification sites. When using histone modification in the epigenetic modality, two unimodal models of Deep5hmC: Deep5hmC-Seq using only DNA sequence as the model input and Deep5hmC-His using only histone modification as the model input are compared to the default multimodal Deep5hmC-Seq+His using both DNA sequence and histone modification as the model input. 5hmC peaks from the EB stage “Forebrain Organoid” and two histone marks: H3K4me1 and H3K4me3 ChIP-seq data in all brain regions from Roadmap Epigenomics are used as the training set. ( A ) AUROC reported for three compared methods. ( B ) AUPRC reported three compared methods.

Article Snippet: For “Human Tissues,” we carefully select aligned bed files of ChIP-seq data from Roadmap Epigenomics by ensuring a match between ChIP-seq data and 5hmC-seq data based on tissue type.

Techniques: Comparison, Modification, Sequencing, ChIP-sequencing

Journal: bioRxiv

Article Title: Chrom-Sig: de-noising 1-dimensional genomic profiles by signal processing methods

doi: 10.1101/2025.08.12.670000

Figure Lengend Snippet: Paired End Example for GM12878 Chrom-Sig results for all paired-end datasets from GM12878 cell-line, visualized in the genome browser. CTCF Motif: CTCF binding sites with orientation. Original: Bedgraph file generated directly from input BAM/bed file. SICER peaks: Bed file result of running SICER algorithm on the original bedgraph file. Chrom-Sig FDR 0.1 pass: pass bedgraph generated from original bedgraph by Chrom-Sig (percentage refers to how many reads were retained by Chrom-Sig result from original bedgraph). SICER peaks (below Chrom-Sig FDR 0.1 pass): Bed file from SICER algorithm run on pass-pileup bed generated by Chrom-Sig. ChromHMM: Chromatin states.

Article Snippet: The analysis looks at GM12878 CTCF ChIP-seq ENCFF355CYX (36,269 peaks original, 24,872 peaks after Chrom-Sig) as well as GM12878 CTCF CUT&RUN replicates 4DNFI2G71DR4 (55,251 peaks original, 22,554 peaks after Chrom-Sig) and 4DNFI9U71IB4 (62,176 peaks original, 19,233 peaks after Chrom-Sig).

Techniques: Binding Assay, Generated

Journal: bioRxiv

Article Title: Chrom-Sig: de-noising 1-dimensional genomic profiles by signal processing methods

doi: 10.1101/2025.08.12.670000

Figure Lengend Snippet: Single End Example Chrom-Sig results for all single-end datasets (all single-end data is from GM12878 cell-line), visualized in the genome browser. CTCF Motif: CTCF binding sites with orientation. Original: Bedgraph file generated directly from input BAM/bed file. SICER peaks: Bed file result of running SICER algorithm on the original bedgraph file. Chrom-Sig FDR 0.1 pass: pass bedgraph generated from original bedgraph by Chrom-Sig (percentage refers to how many reads were retained by Chrom-Sig result from original bedgraph). SICER peaks (below Chrom-Sig FDR 0.1 pass): Bed file from SICER algorithm run on pass-pileup bed generated by Chrom-Sig. ChromHMM: Chromatin states.

Article Snippet: The analysis looks at GM12878 CTCF ChIP-seq ENCFF355CYX (36,269 peaks original, 24,872 peaks after Chrom-Sig) as well as GM12878 CTCF CUT&RUN replicates 4DNFI2G71DR4 (55,251 peaks original, 22,554 peaks after Chrom-Sig) and 4DNFI9U71IB4 (62,176 peaks original, 19,233 peaks after Chrom-Sig).

Techniques: Binding Assay, Generated

Journal: bioRxiv

Article Title: Chrom-Sig: de-noising 1-dimensional genomic profiles by signal processing methods

doi: 10.1101/2025.08.12.670000

Figure Lengend Snippet: CTCF Motif Analyses a) Top enriched motifs, E-value, and matching motifs from MEME-Chip for GM12878 CUT&RUN CTCF 4DNFI2G71DR4 before and after Chrom-Sig. b) Comparison of CTCF motif precision between original data and Chrom-Sig with FDR 0.1 and 5000 pseudo-reads for GM12878 ChIP-seq CTCF ENCFF355CYX, GM12878 CUT&RUN CTCF 4DNFI2G71DR4 and 4DNFI9U71IB4.

Article Snippet: The analysis looks at GM12878 CTCF ChIP-seq ENCFF355CYX (36,269 peaks original, 24,872 peaks after Chrom-Sig) as well as GM12878 CTCF CUT&RUN replicates 4DNFI2G71DR4 (55,251 peaks original, 22,554 peaks after Chrom-Sig) and 4DNFI9U71IB4 (62,176 peaks original, 19,233 peaks after Chrom-Sig).

Techniques: Comparison, ChIP-sequencing

Journal: bioRxiv

Article Title: Chrom-Sig: de-noising 1-dimensional genomic profiles by signal processing methods

doi: 10.1101/2025.08.12.670000

Figure Lengend Snippet: ChromHMM State Annotation Distribution Comparison of the distribution of chromHMM states between original data and Chrom-Sig with FDR 0.1 and 5000 pseudo-reads for K562 RNAPII ChIP-seq ENCFF480AJZ and ENCFF785OCU and GM12878 ATAC-seq ENCFF646NWY. The proportion of enhancer and promotor states increases when Chrom-Sig is applied to the data. Between K562 RNAPII ChIP-seq replicates there is an average of 12.3% higher distribution of enhancers and promotors (ENCFF480AJZ: 77% original vs 87.3% Chrom-Sig and ENCFF785OCU: 76.9% original vs 85.5% Chrom-Sig). In ATAC-seq data, the percentage of transcription and heterochromatin states drops from 28.9% to 12.6% after Chrom-Sig.

Article Snippet: The analysis looks at GM12878 CTCF ChIP-seq ENCFF355CYX (36,269 peaks original, 24,872 peaks after Chrom-Sig) as well as GM12878 CTCF CUT&RUN replicates 4DNFI2G71DR4 (55,251 peaks original, 22,554 peaks after Chrom-Sig) and 4DNFI9U71IB4 (62,176 peaks original, 19,233 peaks after Chrom-Sig).

Techniques: Comparison, ChIP-sequencing

Journal: EMBO Molecular Medicine

Article Title: Reciprocal inhibition of NOTCH and SOX2 shapes tumor cell plasticity and therapeutic escape in triple-negative breast cancer

doi: 10.1038/s44321-024-00161-8

Figure Lengend Snippet: Reagents and tools table

Article Snippet: iDeal ChIP-seq kit for Transcription Factors Kit , Diagenode , Cat#C01010170.

Techniques: Recombinant, Plasmid Preparation, Binding Assay, Polymer, SYBR Green Assay, Transfection, Protease Inhibitor, Reporter Assay, Gel Purification, Purification, Ligation, Software

Journal: bioRxiv

Article Title: Angioplasty-induced epigenomic remodeling entails BRD4 and EZH2 hierarchical regulations

doi: 10.1101/2020.03.12.989640

Figure Lengend Snippet: Balloon-injured rat left common carotid arteries and contralateral arteries (uninjured control) were collected at day 7 post angioplasty and snap frozen until use for ChIPseq. A . Heatmaps of ChIPseq peak density for BRD4, H3K27ac, H3K27me3, and H3K4me1. ChIPseq signal anchors 10 kb center region with 5 kb flanking on either side of the transcription start site (TSS) of over 24000 genes. Three clusters show the main pattern of co-localization of the ChIP-seq signal and non-overlap between H3K27ac and H3K27me3. Note increased (injured- vs -uninjured) H3K27me3 ChIPseq signal mainly in Cluster-1. B . Distribution of transcript abundance of the genes associated with BRD4 and the three histone marks. C . ChIPseq intensity changes in injured ( vs uninjured) arteries. Red, increased intensity; blue, decreased intensity; a cutoff of 2-fold change of read intensity was used. Note the prevailing H3K27me3 ChIPseq signal increase after injury.

Article Snippet: Artery tissues from 40 rats were pooled for ChIPseq analysis at Active Motif per company standard procedures.

Techniques: Control, ChIP-sequencing

Journal: bioRxiv

Article Title: Angioplasty-induced epigenomic remodeling entails BRD4 and EZH2 hierarchical regulations

doi: 10.1101/2020.03.12.989640

Figure Lengend Snippet: A and B . Comparison of ChIPseq binding density (near Ezh2 ) between injured (+, light color) and uninjured (-, dark color) arteries. The profiles for Nrp2 , which is known as upregulated in balloon-injured rat carotid arteries , are presented for positive control to validate the ChIP methodology and data. Non-specific input indicates very low background noise. C and D . Effect of BRD4 silencing on EZH2 expression. BRD2, BRD3, or BRD4 was silenced with their specific siRNAs (validated in our recent reports) , . Rat aortic SMCs were cultured, starved for 6h, then transduced with BRD2,3,4 siRNA overnight, recovered for 24h and 48h before RNA and protein extraction.EZH2 protein and mRNA were measured with Western blot and qRT-PCR (normalized by ΔΔCT-log2) assays. Quantification: Mean ± SEM; n =3 independent experiments; one-way ANOVA with Bonferroni test, *P<0.05 compared to the scrambled-sequence siRNA control. E . BRD4 ChIPseq binding density focusing on Ezh2 . Red and blue bars mark enhancers. Box highlights an enhancer region where ChIPseq intensity increased in injured vs uninjured arteries. F . Effect of CRISPR-mediated enhancer region deletion on EZH2 expression. sg, short guide RNA. Quantification: Mean ± SEM; n =3 independent experiments; one-way ANOVA with Bonferroni test, *P<0.05.

Article Snippet: Artery tissues from 40 rats were pooled for ChIPseq analysis at Active Motif per company standard procedures.

Techniques: Comparison, Binding Assay, Positive Control, Expressing, Cell Culture, Transduction, Protein Extraction, Western Blot, Quantitative RT-PCR, Sequencing, Control, CRISPR

Journal: bioRxiv

Article Title: Angioplasty-induced epigenomic remodeling entails BRD4 and EZH2 hierarchical regulations

doi: 10.1101/2020.03.12.989640

Figure Lengend Snippet: MOVAS cells were cultured, starved, pre-treated with vehicle (DMSO) or the pan-EZH1/2 inhibitor UNC1999 (5 µM) for 2h, and then stimulated with PDGF-BB (final 20 ng/ml). For lentivirus-mediated overexpression or silencing, cells were transduced with lentivirus overnight, recovered for 24h, and then starved for 6h prior to adding PDGF-BB. Cells were harvested 24h or 48h after stimulation with PDGF-BB, for qRT-PCR and Western blot assay, respectively. Quantification: Mean ± SEM; n =3 independent experiments; one-way ANOVA with Bonferroni test, *P<0.05. A . H3K27me3 ChIPseq binding density at Cdkn1c (P57) and Ccnd1 (cyclin-D1) in balloon-injured (red) and uninjured (gray) artery tissues. B and C . Effect of pan-EZH1/2 inhibition on P57 and cyclin-D1 expression. D and E . Effect of EZH1 or EZH2 silencing on P57 and cyclin-D1 expression. F and G . Effect of EZH1 or EZH2 overexpression on P57 and cyclin-D1 expression.

Article Snippet: Artery tissues from 40 rats were pooled for ChIPseq analysis at Active Motif per company standard procedures.

Techniques: Cell Culture, Over Expression, Transduction, Quantitative RT-PCR, Western Blot, Binding Assay, Inhibition, Expressing

Journal: bioRxiv

Article Title: Angioplasty-induced epigenomic remodeling entails BRD4 and EZH2 hierarchical regulations

doi: 10.1101/2020.03.12.989640

Figure Lengend Snippet: MOVAS cells were cultured, starved, pre-treated with UNC1999 or transduced with lentivirus, stimulated with PDGF-BB, and assayed, as described for . Quantification: Mean ± SEM; n =3 independent experiments; one-way ANOVA with Bonferroni test, *P<0.05. A . H3K27me3 ChIPseq binding density at Uhrf1 in balloon-injured (red) and uninjured (gray) artery tissues. B . Effect of pan-EZH1/2 inhibition on UHRF1 expression. C . Effect of EZH1 or EZH2 silencing on UHRF1 expression. D . Effect of EZH1 or EZH2 overexpression on UHRF1 expression.

Article Snippet: Artery tissues from 40 rats were pooled for ChIPseq analysis at Active Motif per company standard procedures.

Techniques: Cell Culture, Transduction, Binding Assay, Inhibition, Expressing, Over Expression

Journal: bioRxiv

Article Title: H3K27me3 spreading organizes canonical PRC1 chromatin architecture to regulate developmental programs

doi: 10.1101/2023.11.28.567931

Figure Lengend Snippet: A. Hi-C data generated from brain tumors and normal brain tissues are analyzed at genome-wide scales. UMAP embedding based on genome-wide comparison across Hi-C contact matrices at three different scales: compartmentalization (first principal component / compartment score), topologically associating domain organization (RobusTAD boundary score), and matrix similarity (HiCRep coefficient). H3K27M pHGGs do not separate from H3 WT pHGGs by any of the three modalities examined. B. From Hi-C datasets in A, silhouette width based on inter-sample similarity in terms of three different modalities, with more positive values indicating that a sample is closer to other samples belonging to the same class whereas more negative samples indicating lack of cohesion (i.e., class label is not reflected by high inter-sample similarity for those belonging to the same class). H3K27M pHGGs emerge as the only tumor subtype demonstrating lack of distinct signatures across all three scales considered, generally showing negative silhouette scores (i.e., less similar to other H3K27M pHGGs than to tumors of another type). Therefore H3K27M does not impose a specific signature on large-scale genome organization. C. Euler diagram of CTCF peaks identified in isogenic H3K27M pHGG cell lines and their KO counterparts, demonstrating a substantial overlap. D. Pile-up of pairwise Hi-C interactions among the union CTCF peak set across all H3K27M and KO samples; only pairs of sites with convergent motif orientations were considered. This reveals a lack of global differences in CTCF interaction strength between isogenic H3K27M and H3K27M-KO pHGG cells. E. Correlation of compartment/insulation score differences (H3K27M versus KO/WT) between isogenic comparisons. The weak correlation coefficients demonstrate lack of consistent changes in compartment/domain structures upon the removal or overexpression of H3K27M. F. Representative tracks of experimental and simulated ChIP-seq datasets, demonstrating the distinction between confined versus diffuse profiles of H3K27me3 or CTCF. G. Genome-wide fragment cluster score computed at either 1kb shift distance and simulated H3K27me3 at varying shift distances. Our choice for measuring “confinement” can quantitatively distinguish confined versus diffuse experimental ChIP-seq profiles. H. Metaplots showing aggregate depth-normalized H3K27me3 signals from simulated datasets with varying degrees of confinement, with hypothetically no difference in true modification levels at the very center. This reinforces that depth-normalization (e.g., CPM) of a more diffuse profile will yield the impression of a lower peak as compared to confined profile, despite no difference in the absolute value at the center (i.e., a by-product of ChIP-seq depth-normalization). This phenomenon can be important to consider when assessing normalized metaplots I. Confinement scores of H3K27me3 (fragment cluster score at 10kb, see methods) for published ChIP-seq data from the developing mouse brain, ranging from embryonic day 10.5 (E10.5) to birth (P0), in Gorkin et al. (2020) . Diminishing scores indicate the spread of H3K27me3 accompanies early brain development.

Article Snippet: ChIP reaction for histone modifications was performed on a Diagenode SX-8G IP-Star Compact using Diagenode automated Ideal ChIP-seq Kit.

Techniques: Hi-C, Generated, Genome Wide, Comparison, Insulation, Over Expression, ChIP-sequencing, Modification

Journal: bioRxiv

Article Title: H3K27me3 spreading organizes canonical PRC1 chromatin architecture to regulate developmental programs

doi: 10.1101/2023.11.28.567931

Figure Lengend Snippet: A. Chromatin conformation capture (Hi-C) matrices showing a representative loop interaction (green circle) in a pHGG cell line BT245 (H3K27M versus H3K27M-KO) between the H3K27me3-enriched promoters of genes PRDM13 and SIM1 (top). ChIP-seq tracks of H3K27me3 showcase H3K27M-induced confinement of H3K27me3 at these genes’ promoters, whereas the spread of this mark covers a broad domain upon removal of the mutation in KO cells (bottom). B. Summary of quantitative approaches to measure aggregate enrichment of H3K27me3 at CGIs, and pile-up of pairwise contacts between H3K27me3-enriched CGIs in Hi-C data. C. ChIP-seq tracks of H3K27me3, normalized by Rx spike-in or abundance measured by mass spectrometry. A representative polycomb target locus ( HOXD cluster) in isogenic matched comparisons of confined H3K27me3 due to H3K27M, EZHIP, or primed pluripotency is showcased. Loss of glioma drivers or iPSC-to-NPC differentiation is accompanied by the expansion of H3K27me3 domains in cell-type specific patterns. D. Metaplots of H3K27me3 aggregate ChIP-seq signals around H3K27me3-enriched CpG islands, normalized by total H3K27me3 abundance measured by ChIP-Rx spike-in. E. Metaplots as in D, normalized by read depth (counts per million; CPM). F. Measure of H3K27me3 ChIP-seq signal confinement (fragment cluster score at 1kb separation, computed using the tool “ssp”, see methods), comparing confined (H3K27M, EZHIP, primed pluripotency) versus diffuse profiles. Individual data points correspond to a replicate, with connected points indicating replicates from the same batch; connections not linking points indicate that multiple replicates were sequenced in a batch, and so the links are drawn between the average value per condition. G. Pile-up of Hi-C interactions among H3K27me3-enriched CpG islands, as defined in D, portraying average pairwise contact strength between such regions (in units of enrichment, i.e., observed / expected). Punctate enrichment signal in the center indicates elevated long-range interaction anchored at H3K27me3-enriched CGIs in cells with confined H3K27me3. H3K27me3-enriched is defined as the union set of top 1000 CpG islands with the most H3K27me3 alignments in either condition.

Article Snippet: ChIP reaction for histone modifications was performed on a Diagenode SX-8G IP-Star Compact using Diagenode automated Ideal ChIP-seq Kit.

Techniques: Hi-C, ChIP-sequencing, Mutagenesis, Mass Spectrometry

Journal: bioRxiv

Article Title: H3K27me3 spreading organizes canonical PRC1 chromatin architecture to regulate developmental programs

doi: 10.1101/2023.11.28.567931

Figure Lengend Snippet: A. Schematic summary of PRC1 subunit composition defining core (yellow), canonical (green) and variant (pink) subcomplexes. Those known to engage self-associating properties are labeled with a star. B. Intensity-Based Absolute Quantification (iBAQ) values showing PRC1 subunit abundance in chromatin-fractionation lysates from DIPGXIII H3K27M and KO lines. H3K27me3 abundance (mass spectrometry) is included for comparison (left). C. Euler diagram of called peaks for H3K27me3, cPRC1 subunits (CBX2/4/8, PHC2) and core subunit RING1B in H3K27M pHGG cell line BT245. The strong overlap between CBX2/4/8 and PHC2 identify a common target group of cPRC1 sites, representing a minority of all PRC1 sites indicated by RING1B peaks. D. Density plots showing differential CGI enrichment of H3K27me3 (x-axis), RING1B (y-axis), and CBX2 or H2AK119ub (color code) between H3K27M and H3K27M-KO BT245 cells. Each dot represents a CGI and the differential enrichment is plotted as log2 ratio of K27M/KO. Retainment of H3K27me3 enrichment at CGIs associates with several fold greater enrichment for RING1B and CBX2 ChIP-seq signals, indicating the correlation between H3K27me3 confinement and enhanced cPRC1 recruitment (top). In contrast, there is a lack of correlation between H3K27me3 confinement and H2AK119ub enrichment (bottom). E. Correlation network of differential H3K27me3, RINGB1, CBX2 and H2AK119ub enrichment at CGIs of BT245 cells, demonstrating the weak correlation between H2AK119ub changes and changes of H3K27me3, RINGB1, CBX2. Edgewidths reflect the absolute value Pearson correlation coefficients. F. ChIP-seq tracks of a representative locus including cPRC1 sites (green) and adjacent vPRC1 site (pink). Track normalization by MS-iBAQ values provides quantitative measures of chromatin occupancy for each cPRC1 subunit, showing their concordance and heightened concentration due to the H3K27M mutation.

Article Snippet: ChIP reaction for histone modifications was performed on a Diagenode SX-8G IP-Star Compact using Diagenode automated Ideal ChIP-seq Kit.

Techniques: Variant Assay, Labeling, Fractionation, Mass Spectrometry, Comparison, ChIP-sequencing, Concentration Assay, Mutagenesis

Journal: bioRxiv

Article Title: H3K27me3 spreading organizes canonical PRC1 chromatin architecture to regulate developmental programs

doi: 10.1101/2023.11.28.567931

Figure Lengend Snippet: A. Expression of cPRC1 subunit genes ( CBX2 , CBX4 , CBX6 , CBX7 , CBX8 ) in pHGG H3K27M cell lines based on bulk RNA-seq. B. Metaplot of CBX2 and RING1B aggregate ChIP-seq signals around H3K27me3-enriched CpG islands (union set of top 1000 most enriched in both conditions per cell line, as defined previously), normalized by read depth. CBX2 and RING1B occupancy at H3K27me3 sites are consistently diluted by KO of H3K27M. C. Bar graphs showing RING1B/CBX2 ChIP-seq signal confinement scores (fragment cluster score at 10kb, see Methods) in 3 distinct cell lines (BT245, DIPGXIII, HSJ019). RING1B/CBX2 are less confined (ie. more diluted) upon KO of H3K27M mutations. D. Correlation network of differential H3K27me3, RING1B, CBX2 and H2AK119ub enrichment at CGIs of BT245 cells, demonstrating the weak correlation between H2AK119ub changes and the changes of H3K27me3, RING1B and CBX2. Edgewidths reflect the absolute value Pearson correlation coefficients. E. Density plots showing differential CGI enrichment of H3K27me3 (x-axis), RING1B (y-axis), and CBX2 (color code) between H3K27M and H3K27M-KO DIPGXIII (top) and HSJ019 (bottom) cells. Each dot represents a CGI and the differential enrichment is plotted as log2 ratio of K27M/KO. Retainment of H3K27me3 enrichment at CGIs associates with several fold greater enrichment for RING1B and CBX2 ChIP-seq signals, indicating the correlation between H3K27me3 confinement and enhanced cPRC1 recruitment. F. Western blot showing equivalent levels of H2AK119ub abundance in isogenic H3K27M and KO BT245 and DIPGXIII cell lines. G. ChIP-seq/CUT&RUN-seq tracks for H3K27me3 and all cPRC1 subunits profiled, showing that broad domain spreading of H3K27me3 correlates with enrichment of RING1B, CBX2, CBX8 and PHC2 subunits (less so for CBX4) at Mb scale. This indicates cPRC1 can be distributed as both focal peaks and broad domains as determined by the degree of H3K27me3 spreading. H. Mass spectrometry-based measurement of protein abundance (iBAQ) for all subunits of PRC1 and PRC2 complexes, showing most subunits are comparably present in both nucleoplasm (soluble) and chromatin-bound protein fractions of H3K27M and KO cells for the pHGG line DIPGXIII. H3K27M mutations do not therefore dramatically alter the composition or abundance of PRC1/2.

Article Snippet: ChIP reaction for histone modifications was performed on a Diagenode SX-8G IP-Star Compact using Diagenode automated Ideal ChIP-seq Kit.

Techniques: Expressing, RNA Sequencing Assay, ChIP-sequencing, Western Blot, Mass Spectrometry

Journal: bioRxiv

Article Title: H3K27me3 spreading organizes canonical PRC1 chromatin architecture to regulate developmental programs

doi: 10.1101/2023.11.28.567931

Figure Lengend Snippet: A. Expression of genes (transcripts per million, TPM) associated with the promoters from the four clusters derived in , demonstrating the lowest expression levels in the cPRC1 cluster in H3K27M-mutant cell lines. Boxplots’ hinges correspond to the 25 th and 75 th percentiles, with whiskers extending to the most extreme value within 1.5 × interquartile range from the hinges, whereas the central band mark the median value. B. Euler diagram of sites identified for the four clusters showing concordance of “Active” and “Other” cluster sites among the three H3K27M pHGG cell lines. A substantial fraction of cPRC1 cluster sites also overlap, termed the consensus cPRC1 sites, whereas the PRC2-only cluster sites show less concordance. C. Enrichment of CTCF ChIP-seq signal among the UMAP projection and cluster classification. CTCF is not strongly enriched in the cPRC1 cluster, compared to Active and PRC2-only clusters. D. Enrichr pathway enrichment analysis of consensus cPRC1 targets among three H3K27M pHGG cell lines, demonstrating the enrichment in genes annotated as relating to development and neuron differentiation.

Article Snippet: ChIP reaction for histone modifications was performed on a Diagenode SX-8G IP-Star Compact using Diagenode automated Ideal ChIP-seq Kit.

Techniques: Expressing, Derivative Assay, Mutagenesis, ChIP-sequencing

Journal: bioRxiv

Article Title: H3K27me3 spreading organizes canonical PRC1 chromatin architecture to regulate developmental programs

doi: 10.1101/2023.11.28.567931

Figure Lengend Snippet: A. Chromatin conformation capture (Hi-C) matrices showing a representative loop interaction (green circle) between cPRC1 sites bridging the promoters of Nkx2-1 and Foxa1 that is weakened upon KO of Nsd1 in mESCs (top). ChIP-seq profiles of H3K36me2, H3K27me3, RING1B, and CBX2 (bottom) reveal that H3K27me3 spread accompanies H3K36me2 depletion in Nsd1 -KO mESCs (blue), and cPRC1 binding becomes more diffuse compared to WT cells (red). B. Metaplot of H3K27me3 and PRC1 (RING1B, CBX2) aggregate ChIP-seq signal around H3K27me3-enriched CpG islands, in units of log2 enrichment over input, confirming Nsd1 -KO reduces occupancy of cPRC1 at H3K27me3-enriched CGIs (union set of top 1000 most enriched in both conditions, as defined previously). C. Density plot showing differential CGI enrichment of H3K27me3 (x-axis), RING1B (y-axis), and CBX2 (color code) between WT and Nsd1 -KO mESCs. Each dot represents a CGI and the differential enrichment is plotted as log2 ratio of Nsd1 KO/WT. Loss of CBX2 binding correlates with decreases in H3K27me3 and Ring1b at CGIs upon Nsd1 -KO. D. UMAP embedding and HDBSCAN clustering of chromatin state signals at CpG islands and promoters in mESC (a combination of public and data from this study). Individual data points correspond to a genomic interval (promoter or CpG island), and the embedding is based on dimension reduction of all features. We derive four different clusters matching that of pHGG lines in ; Active, cPRC1, PRC2 (with SUZ12 and H3K27me3, lacking CBX2 enrichment), and Other. E. Pile-up of Hi-C pairwise interactions were computed among genomic regions within the same cluster (i.e., intra-cluster looping). On average, cPRC1 sites demonstrate the greatest differences in intra-class looping between WT and Nsd1 -KO mESCs.

Article Snippet: ChIP reaction for histone modifications was performed on a Diagenode SX-8G IP-Star Compact using Diagenode automated Ideal ChIP-seq Kit.

Techniques: Hi-C, ChIP-sequencing, Binding Assay

Journal: bioRxiv

Article Title: H3K27me3 spreading organizes canonical PRC1 chromatin architecture to regulate developmental programs

doi: 10.1101/2023.11.28.567931

Figure Lengend Snippet: A. Average signals of transcription and chromatin features for CGIs & promoters in each of the four clusters in mESCs (see ), demonstrating the characteristic chromatin state of each cluster. Symbols indicate data sources: * = Chen 2022 , \ = Kundu 2017 , ^ = Healy 2019 , ‵ = Mas 2018 , ° = ENCODE, no symbol = this study. B. Genomic distribution of H3K27me3 (ChIP-seq coverage tracks in units of counts-per-million-alignments) at representative loci in germinal center B cells and acute lymphoblastic leukemia cells, demonstrating distinctive profiles of confined versus diffuse H3K27me3. C. Measure of H3K27me3 ChIP-seq signal confinement (fragment cluster score at 1kb separation, computed using the tool “ssp”, see methods), comparing confined (H1 KO, NSD2 mutant) versus diffuse profiles. Individual data points correspond to a replicate, with connected points indicating replicates from the same batch; connections not linking points indicate that multiple replicates were sequenced in a batch, and so the links are drawn between the average value per condition. D. Metaplots of H3K27me3 aggregate ChIP-seq signals around H3K27me3-enriched CpG islands, normalized by total read depth. H3K27me3-enriched is defined as the union set of top 1000 CpG islands with the most H3K27me3 alignments in either condition. E. Pile-up of Hi-C interactions among H3K27me3-enriched CpG islands, as defined above, portraying average pairwise contact strength between such regions (in units of enrichment, i.e., observed / expected). Punctate enrichment signal in the center indicates elevated long-range interaction anchored at H3K27me3-enriched CGIs in cells with confined H3K27me3.

Article Snippet: ChIP reaction for histone modifications was performed on a Diagenode SX-8G IP-Star Compact using Diagenode automated Ideal ChIP-seq Kit.

Techniques: ChIP-sequencing, Mutagenesis, Hi-C

Journal: bioRxiv

Article Title: H3K27me3 spreading organizes canonical PRC1 chromatin architecture to regulate developmental programs

doi: 10.1101/2023.11.28.567931

Figure Lengend Snippet: A. Metaplots of CBX2 or RING1B aggregate ChIP-seq signals around CpG islands within each annotated cluster (see ), for BT245 H3K27M lines treated with DMSO control or CBX-AM compound. CBX-AM treatment attenuates the enrichment of RING1B and CBX2 at cPRC1 target sites. B. Pile-up of Hi-C pairwise interactions were computed among genomic regions within cPRC1 subclusters A and B, in BT245 H3K27M lines treated with DMSO or CBX-AM. CBX-AM treatment weakens frequencies of Hi-C interactions specifically at cPRC1 subcluster A sites. C. Violin plots of genes’ differential expression values in RNA-seq data. CBX-AM treatment results in upregulation of cPRC1 subcluster A genes, and to a less extent subcluster B genes, in H3K27M BT245 cells treated with differentiation media. Violin plots’ hinges correspond to the 25 th and 75 th percentiles, with whiskers extending to the most extreme value within 1.5 × interquartile range from the hinges, whereas the central band mark the median value. D. Immunofluorescence microscopy imaging of the oligodendrocyte progenitor cell differentiation marker SRY-box Transcription Factor 10 (SOX10). CBX-AM treatment elevates SOX10 expression in H3K27M BT245 cells to levels comparable to KO cells. E. Summary of CBX-AM treatment and H3K27M-KO’s effect on H3K27me3, CBX chromodomain localization and chromatin architecture of H3K27M pHGG cells. Manipulation of cPRC1 concentration through either H3K27M KO or CBX-AM dilution of chromodomains results in loss of repressive loop architecture and potentiation of differentiation.

Article Snippet: ChIP reaction for histone modifications was performed on a Diagenode SX-8G IP-Star Compact using Diagenode automated Ideal ChIP-seq Kit.

Techniques: ChIP-sequencing, Hi-C, Expressing, RNA Sequencing Assay, Immunofluorescence, Microscopy, Imaging, Cell Differentiation, Marker, Concentration Assay