The mechanisms underlying gene repression and silencers are poorly understood. Here we investigate the hypothesis that H3K27me3-rich regions of the genome, defined from clusters of H3K27me3 peaks, may be used to identify silencers that can regulate gene expression via proximity or looping. We find that H3K27me3-rich regions are associated with chromatin interactions and interact preferentially with each other. H3K27me3-rich regions component removal at interaction anchors by CRISPR leads to upregulation of interacting target genes, altered H3K27me3 and H3K27ac levels at interacting regions, and altered chromatin interactions. Chromatin interactions did not change at regions with high H3K27me3, but regions with low H3K27me3 and high H3K27ac levels showed changes in chromatin interactions. Cells with H3K27me3-rich regions knockout also show changes in phenotype associated with cell identity, and altered xenograft tumor growth. Finally, we observe that H3K27me3-rich regions-associated genes and long-range chromatin interactions are susceptible to H3K27me3 depletion. Our results characterize H3K27me3-rich regions and their mechanisms of functioning via looping. Mechanisms underlying gene repression and silencers remain poorly understood. Here the authors investigate the role of H3K27me3-rich regions in the genome, as defined from clusters of H3K27me3 peaks, in regulating gene expression via looping. The genome is organized into large Topologically-Associated Domains (TADs) and chromatin interactions. Gene transcription is controlled by transcription factors (TFs) that bind to enhancers and promoters to regulate genes4. TFs can bind to proximal enhancers in the genome, and enhancers distal to genes can loop to gene promoters via chromatin interactions to activate gene expression3. Cancer cells show altered chromatin interactions3 including altered chromatin loops to key oncogenes such as TERT5.The 3-dimensional organization of our genomes is important for gene regulation6, the human BDNF gene7 and the human CD4 gene9  proteins including Polycomb Repressive Complexes, PRC1 and PRC2 are widely recognized to mediate gene silencing of developmental genes20. H3K27me3 marks are associated with gene repression for cell type-specific genes. Unlike H3K9me3 which remains silenced all the time and prevents multiple TFs from binding21, H3K27me3 still allows these genes to be activated through TF binding in a different cell state22. H3K27me3 is known to be a characteristic of silencers23. Although large blocks of H3K27me3-marked loci have been observed in previous studies26, their roles in chromatin loops and consequent regulatory actions were not explored in these manuscripts.PcG domains are marked by H3K27me3, which is deposited by the catalytic component of PRC2 complex, mainly Enhancer of Zeste Homolog 2 (EZH2) and sometimes EZH127. At the same time, Jayavelu et al. used a subtractive analysis approach to predict silencers in over 100 human and mouse cell types28. Moreover, Pang and Snyder identified silencers through an innovative “ReSE screen” which screened for genomic regions that can repress caspase 9 expression upon apoptosis induction29. Ngan et al. characterized silencers in mouse development through PRC2 Chromatin Interaction Analysis with Paired-End Tag sequencing (ChIA-PET) in mouse embryonic stem cells. They concluded that PRC2-bound looping anchors function as transcriptional silencers suggesting that we can identify silencers through investigating chromatin interactions13.Recently, several studies have proposed methods to identity silencer elements in a genome-wide manner. Huang et al. defined silencers using the correlation between H3K27me3-DNase I hypersensitive site (DHS) and gene expressionHowever, there is no consensus yet in terms of how to identify silencers. Notably, each of these methods identify different genomic regions as silencers, raising the question of whether there may be different classes of silencers. Moreover, current methods for identifying silencers are laborious and require complicated bioinformatics analyses and/or genome-wide screening ” from clusters of H3K27me3 peaks in the genome can be identified through H3K27me3 ChIP-seq, as how super-enhancers are defined. We hypothesize that H3K27me3-rich regions may be a useful concept in identifying genomic regions that contain silencers which can repress target genes either in proximity or via long-range chromatin interactions. The target genes may be tumor suppressors in cancer cells, and also cell fate-associated genes that need to be turned off for differentiation to occur.bona fide silencers. CRISPR excision leads to changes in chromatin loops, histone modifications, and cell phenotype including cell adhesion, growth and differentiation. Initial histone modification states predict changes in chromatin loops. Finally, EZH2 inhibition leads to changes in chromatin interactions and histone modifications at MRRs, and MRR-associated gene up-regulation. Taken together, silencers identified from clustering H3K27me3 peaks regulate key epigenomic, transcriptomic and phenotypic events in cells.Here, we show that MRRs can be identified using H3K27me3 ChIP-seq data. MRRs show dense chromatin interactions connecting to target genes and to other MRRs. CRISPR excision of two examples of looping silencers leads to gene up-regulation, indicating they are indeed 34 in the following manner: we first identified H3K27me3 peaks, then clustered nearby peaks, and ranked the clustered peaks by average H3K27me3 signals levels. The top clusters with the highest H3K27me3 signal were called as “H3K27me3-rich regions” (MRRs) and the rest were called as “typical H3K27me3” regions  from cell lines using H3K27me3 ChIP-seq dataons Fig. . The peaRRs Fig. . This ovRRs Fig. . AlthougRRs Fig. . This inThe number of constituent peaks and overlapping genes at MRRs is larger than typical H3K27me3 peaks  and can act as a tumor suppressor through inhibiting Wnt signaling42, also overlaps with an MRR in K562. Gene ontology analysis showed that MRR-related genes are enriched in developmental and differentiation processes, while genes associated with typical H3K27me3 peaks are enriched in cell metabolism and transportation processes . These results suggested that MRR may regulate important genes related to development and tumorigenesis.Many MRR-overlapping genes in different cell lines are known or predicted tumor suppressor genesChIP-seq signals of EZH2 showed high correlation with H3K27me3 signal at typical H3K27me3, MRRs, constituent peaks of typical H3K27me3 and constituent peaks of MRRs, which is consistent with EZH2’s role in H3K27me3 mark deposition Fig. . NotablyCPED1 is covered by a broad MRR in GM12878, but overlaps with a super-enhancer in K562  on the x-axis). If the observed proportion of a certain category of interactions were more frequently seen, the log2(Obs/Exp) value would be positive; conversely, if a certain category was depleted, the log2(Obs/Exp) value would be negative.We assigned chromatin states at Hi-C interaction anchors using H3K27me3 and H3K27ac peaks: active (A) anchors overlap with H2K27ac peaks, repressive (R) anchors overlap with H3K27me3 peaks, bivalent (B) anchors overlap with both H3K27me3 and H3K27ac peaks, and quiescent (Q) anchors overlap with neither peak Fig. . We furtInteractions between anchors of the same state  were more likely to interact with each other, while interactions with vastly different chromatin state pairs  were less likely to interact Fig. , left, rTo further explore the potential regulatory role of MRRs in chromatin interactions, we identified the subset of MRR-anchored interactions where at least one anchor peak overlapped a gene transcription start site, and grouped them according to whether the MRR anchor was proximal or distal to the TSS anchor Fig. . The difTMCO4 4C data showed that most 4C interactions fell within the same MRR as the bait and only a handful of them were outside of the MRR. This suggested that MRR can have extensive internal looping.In order to validate the “like-like” preference of chromatin interactions, we performed Circular Chromosome Conformation Capture (4C) experiments on selected loci at MRR to investigate the associated chromatin interactions in a comprehensive and high-resolution manner. We annotated the interactions based on the chromatin state of the anchor distal from the bait in K562 Fig. , and acrPSMD5 and TOR1A in K562 were validated using reciprocal 4C bait design. When the PSMD5 bait region was A (active) in either GM12878 or HAP1 cells, the BB interactions were largely reduced and other types of interactions started to appear , cohesin subunits , and transcription repression-associated proteins  were downloaded from ENCODE and overlapped with the interacting regions of MRRs, which were then normalized to FGF18, a fibroblast growth factor involved in cell differentiation and cell-to-cell adhesion47  located in the F18 Fig. . This reF18 Fig. . MRR1-A1F18 Fig.  from FigTD2 Fig. .FGF18 and UBTD2  clones . Upon GSK343 treatment, lls Fig. . This inTo explore if the MRR1 is cell type-specific, we identified MRRs in seven cell lines and found that MRR1 is specific to two of the seven cell lines, K562 and GM12878  analysis which showed that KO clones may undergo cell adhesion and cell differentiation  by RT-qPCR  that can induce differentiation have been useful in the treatment of Acute Promyelocytic Leukemia, suggesting that methods to induce differentiation could lead to potential leukemia treatments52. Therefore, we asked if silencer removal is associated with growth inhibition in vivo, given that silencer removal leads to cell differentiation. To test this, we performed xenograft experiments with two different KO clones. Both KO clones showed inhibition of tumor growth in the mice  were upregulated in the KO clones  analysis of the RNA-seq on the MRR2-A1 KO clone, we found the term “cell differentiation” Fig. . Thus, wnes Fig.  and IGF2Finally, we tested to see whether the CRISPR KO clones showed tumor growth inhibition in vivo, similar to MRR1. Xenograft experiments showed severe tumor growth inhibition of two different clones Fig.  which fuIGF2 looping silencer (MRR2-A1) example. First, we asked whether the chromatin interaction landscape will be changed upon looping silencer removal. We performed 4C-seq in the KO and control clones. Using IGF2 as the bait, we detected there are 33 chromatin interactions lost and 12 chromatin interactions gained after MRR2-A1 knocking out while a control bait remains highly unchanged  in K562 cells to reduce H3K27me3 levels. Western blot confirmed that even just 1 μM of GSK343 treatment in K562 cells was sufficient to lead to a global loss of H3K27me3  overlapped with peaks at their transcription start sites (TSS); (2) associated with peaks via Hi–C interaction. The RNA-seq results indicated strong upregulation of H3K27me3-associated genes, while genes associated with H3K27ac peaks  underwent minimal net change Fig. . SimilarFGF18 gene showed that H3K27me3 level was decreased and there were accompanied lost peaks, while the H3K27ac and H3K4me3 signal were mostly unaltered  in 1 μM treated GSK343 K562 cells. The 4C interaction profiles in 5 μM and 1 μM treated GSK343 K562 cells were very similar  based on their distance to the bait. We found that the short distance category has the highest proportion of unchanged loops in all the 4C libraries  that we explored before, they both demonstrated loss of H3K27me3 and gain of H3K27ac at the 4C interacting anchors . The second model is that depletion of H3K27me3 abrogates long-range chromatin interactions and upregulates target genes . H3K27me3 might facilitate the MRR2-TRPM5 chromatin interaction, which in turn silences TRPM5; alternatively, H3K27me3 might facilitate the MRR2-TRPM5 chromatin interaction and TRPM5 silencing in parallel.Taken together, the integrative analysis combined with the 3C-PCR showed two models regarding how EZH2 inhibition functions Fig. . Model 1nt Figs.  and 5e. ene Fig. . TherefoDrosophila12 and in mice13, no silencers that work via a looping mechanism have been characterized in humans yet. Here, we propose a method to identify H3K27me3-rich regions (MRRs) or putative “super-silencers” through clustering and ranking H3K27me3 signals.Silencers are important regulatory elements for gene regulation, and several studies have suggested that they loop to target genes, in a manner analogous to enhancers. Although there are several examples of proposed silencers that have been experimentally validated . We showed that silencer removal causes cell identity changes and further related to tumor growth inhibition. Moreover, MRR2-A1 example demonstrated that silencer removal will cause changes of long-range chromatin interactions and high H3K27ac loops were gained to activate IGF2 silencer example, we showed that that looping silencer removal causes distant loops to change and histone states in the initial conditions can predict loop changes. Importantly, we found that loops with high H3K27ac and low H3K27me3 tend to change, which provides evidence that histone modifications can affect overall genome architecture. Secondly, we found that short-range loops tend to remain unchanged while long range loops are disturbed either upon silencer KO or GSK343 treatment which is in line with the finding that showed PRC1 and PRC2 are necessary to maintain the chromatin interactions landscape57. Thirdly, there are multiple regions inside an MRR that are involved in chromatin interactions and may also function as silencers. It would be informative to see whether the putative silencers in an MRR function similarly or differently and to dissect different functional mechanisms of silencers. Fourthly, transcription factors can contribute to the chromatin interaction landscape and cell type-specific transcription factors may result in different chromatin interaction landscape58. Therefore, elucidating the transcription factors involved in silencer functioning would be an important future direction for research.The mechanism of how silencers function to repress genes will be an important topic to explore. Through the IGF2 can lead to IGF2 upregulation, which indicated the repressive ability of H3K27me3 at distal MRRs. This question could be further addressed by more targeted perturbation of H3K27me3 at both or either end of the chromatin interactions and investigating how gene expression levels change.Another question concerns the relative importance of H3K27me3 at distal silencers as compared with target gene promoters in terms of controlling gene expression levels. In our CRISPR knockout results, we observed that excision of a distally interacting MRR region (MRR2-A1) to 60, whether chromatin interactions can be affected by the perturbation of histone modifications is still an open question.Our EZH2 inhibition treatment showed that MRR-associated genes as well as long-range chromatin interactions were susceptible to the depletion of H3K27me3 histone marks. MRR-associated genes were more susceptible to the depletion of H3K27me3 marks than genes associated with typical H3K27me3 peaks. This result suggested that the response of different genes to H3K27me3 loss may correlate with their chromatin state. Although differences in chromatin interactions have been observed in cells at different developmental stages29 . Super-enhancers were called in a similar manner except that a stitching window of 12.5 kb was used and H3K27ac ChIP-seq signal was used in the ranking process.H3K27me3 ChIP-seq signal and peaks were obtained from ENCODE and used as inputs of an in-house customized script that mimicked the signal calculation of the ROSE (0.1) package. Missing H3K27me3 peaks from ENCODE were called using MACS2 (2.1.0.20150731)66. HAP1 wild-type cells (purchased from Horizon) were cultured in IMDM supplemented with 10% FBS and 1% penicillin-streptomycin. All cultures were maintained at 37 °C, 5% CO2 in a humidified incubator.GM12878 normal lymphoblastoid cell line and Chronic Myelogenous Leukemia cell line K562 were cultured in RPMI-1640 supplemented with 10% Fetal Bovine Serum (FBS) and 1% penicillin-streptomycin. HAP1 cell line is a haploid human cell line that was derived from KBM7 cells67 with slight modifications. Briefly, 4 × 107 cells were cross-linked with 1% formaldehyde. The nuclei pellets were isolated by cell lysis with cold lysis buffer  supplemented with protease inhibitors (Roche). First step digestion was performed overnight at 37 °C with HindIII enzyme (NEB). Digestion efficiency was measured by RT-qPCR with HindIII site-specific primers. After confirmation of good digestion efficiency, DNA was ligated overnight at 16 °C by T4 DNA ligase (Thermo Scientific) and de-crosslinked. Following de-crosslinking, DNA was extracted by phenol-chloroform and this is the 3C library. The DNA was then processed for second digestion with DpnII enzyme (NEB) overnight at 37 °C. After final ligation, 4C template DNA was obtained, and the concentration was determined using Qubit assays (Thermo Scientific). The 4C template DNA was then amplified using specific primers with Illumina Nextera adapters and sent for sequencing on the MiSeq system. All the 4C genome coordinates are listed in Supplementary Table 4C-seq assays were performed according to Splinter et al.68. Primers used are listed in Supplementary Table The 3C libraries were generated as described in the 4C section. Digestion efficiency was checked by gel electrophoresis and concentration was determined by Qubit assay. The Taq PCR core kit (Qiagen) was used for PCR reactions with 600 ng 3C library template using the following protocol: 98 °C 3 min, 33 cycles , 72 °C 10 min. PCR products were run on 1.5% agarose gels. After gel electrophoresis, bands corresponding to the expected products were gel excised (Qiagen) and purified for Sanger sequencing. The intensities of the bands were measured by Image Lab. Primers were designed for 3C-PCR following the unidirectional strategy69 with slight modifications. Briefly, cells were crosslinked with 1% methanol-free formaldehyde (Thermo Scientific) at room temperature for 10 min, followed by quenching with glycine for 5 min at room temperature. The fixed cell pellet was lysed in 1% SDS lysis buffer supplemented with protease inhibitor cocktail tablet (Roche), and sonicated using Bioruptor (Diagenode).ChIP-seq was performed according to Robertson et al.The cell lysate was precleared through centrifugation in dilution buffer and incubation with Protein G Dynabeads (Invitrogen) overnight at 4 °C. The precleared lysate was added into the prepared antibody-conjugated beads, and incubated overnight at 4 °C, with rotation. The beads were then washed thrice in 0.1% SDS lysis buffer, once in high salt wash buffer, once in lithium chloride wash and once in TE buffer. The beads were eluted in elution buffer treated with RNase A (Qiagen) followed by decrosslinking with Proteinase K (Ambion) at 37 °C overnight. ChIP DNA was cleaned up with QIAquick PCR purification kit (Qiagen), and quantitated using Qubit High Sensitivity dsDNA Assay (Invitrogen).ChIP DNA was used for the construction of DNA library for Illumina HiSeq 4000 NGS sequencing using ThruPLEX DNA-seq 48D Kit (Rubicon) according to the instruction. Antibodies used include H3K4me3 , H3K27me3 , H3K27ac  and mouse IgG . 3.5 μg of antibodies were used for each ChIP.ChIP-qPCR reactions were performed in triplicates on a Quantstudio 5 quantitative PCR machine (Life Technologies) using GoTaq qPCR Master Mix (Promega). Primers used are listed in Supplementary Table 2 humidified incubator for 48 h before harvesting for various experiments.Small molecular inhibitor GSK343 (Sigma-Aldrich) targeting EZH2 were solubilized in DMSO (Sigma-Aldrich) according to the manufacturer’s instructions and used at a final concentration of 5 μM. K562 cells with GSK343 or DMSO vehicle control were incubated at 37 °C, 5% CO−ΔΔCt method70.Total RNA were isolated from the cells using RNeasy Mini Kit (Qiagen) with on-column DNase digestion (Qiagen). 1 ug of total RNA was then reverse transcribed to cDNA using the SuperScript III first-strand synthesis system using oligodT (Invitrogen). The expression levels of various genes were analysed by real-time PCR. Quantitative real-time PCR (qPCR) was performed using the Applied Biosystems QuantStudio 3 Real-Time PCR system using SYBR Green PCR Master Mix and appropriate primers. Primers used are listed in Supplementary Table Total RNA was extracted from cells using RNeasy Mini Kit (Qiagen), with on-column DNase I treatment (Qiagen). The quality of the RNA extracted was checked using Agilent RNA 6000 Nano Kit (Agilent), and quantitated using Nanodrop ND1000 (Thermo Scientific). 850 ng of RNA was used for the construction of cDNA library for Illumina HiSeq 2500 High Output v4 NGS sequencing using TruSeq Stranded Total RNA LT (w/ Ribo- Zero Gold) Set A (Illumina) as per protocol.® TGX™ Precast Gels (Bio-Rad) and transferred to PVDF membrane. After blocking with TBST containing 5% nonfat dried milk for 1 h at room temperature, the membrane was washed twice with TBST and incubated with primary antibodies: EZH2 , beta-Actin (abcam ab6276), total H3 (abcam ab1791) and H3K27me3  overnight at 4 °C. Primary antibodies are diluted at 1:1000 with 5% non-fat dried milk (dissolved in TBST). The membrane was washed three times with TBST for 10 min and then incubated for 1 h at room temperature with either mouse (CST 7076) or rabbit (CST 7074) HRP-conjugated secondary antibodies  diluted at 1:5000 or 1:2000 with 5% non-fat dried milk (dissolved in TBST), respectively. After extensive washing, bands were detected by enhanced chemiluminescence reagent (Bio-Rad) and imaged using the ChemiDoc™ imaging system (Bio-Rad) or ImageQuant™ LAS 500 .Proteins were extracted from the cells using RIPA buffer (Sigma-Aldrich) with protease inhibitor cocktail (Life Technologies). Protein concentrations were determined using BCA assay (Thermo Scientific). 20 μg of proteins were separated in 4–20% Mini-PROTEAN71. Briefly, gRNAs were designed using Zhang Feng’s website (http:// CRISPR.mit.edu)72 and two gRNAs were designed for each region. Single gRNA was cloned into either pX330A/pX330S vector  followed by Sanger sequencing to confirm insertion of single gRNA. Golden gate assembly of two gRNAs was performed according to Sakuma et al.71. Positive two gRNAs insertion plasmids were confirmed by Sanger sequencing using CRISPR-step2-F and CRISPR-step2-R primers .5 cells/200 ml FBS-free medium) was added to fibronectin-coated wells and BSA-coated wells (negative control) respectively. After 3 h of incubation, cells were washed with PBS, stained with crystal violet and then eluted with extraction solution. The levels of adhesion were quantified by optical absorbance at 560 nm using the Tecan plate reader.Cell adhesion assay was performed using CytoSelect 48-Well Adhesion Assay  according to the manufacturer’s protocol. Briefly, a cell suspension . Luminescence was measured on a Tecan plate reader.FGF18-siRNA-1, 5′-GAGACGGAAUUCUACCUGUtt-3′, FGF18-siRNA-2, 5′-AGACACCUUCGGUAGUCAAtt-3′, IGF2-siRNA-1, 5′-CCAUGCAAAUGAAAUGUAAtt-3′ IGF2-siRNA-2, 5′-GGAAGCACAGCAGCAUCUUtt-3′ were used for RNA interference. After 48 h incubation, cells were harvested for RT-qPCR. Primers used were listed in Supplementary Table siRNAs (Thermo Fisher) were introduced into cells using Neo transfection system (Thermo Fisher) according to the manufacturer’s instructions. All animal experiments were carried out in accordance with ethical guidelines and approved by the Institutional Animal Care and Use Committee (IACUC), Biological Resource Center (BRC) A*STAR under protocol ID #161111.Mice were purchased from InVivos, Singapore and fed with standard laboratory diet and distilled water ad libitum. The animals were kept on a 12 h light/dark cycle at 22 ± 2 °C in individually ventilated caging system with 50–65% humidity in the Biological Resource Centre, A-Star, Singapore.n = 5) were injected subcutaneously. All the mice were monitored for tumor growth at the site of inoculation and the tumor volume was measured twice a week using Vernier caliper for 40 days or till the tumor volume reaches 1000 mm3 whichever is earlier. The tumor volume was calculated using the following formula V = a × b2 × 0.52, where a is the largest and b the smallest diameter of the tumor. At the end of the experimental period, the tumors were resected out and each tumor piece was then divided into 2 pieces. One piece of the tumor was fixed in 10% NBF for 24 h at room temperature and then paraffin embedded for H&E & IHC analysis. The other piece was snap frozen for RNA and protein analysis.Female CB17 SCID mice (6–8 weeks old) were used for the present study. The mice .29 list and calculate the overlap percentage. (1) First randomly shuffled 1000 times on MRR/typical H3K27me3 peaks on the same chromosome; (2) calculated overlap percentage using the 1000 time randomly shuffled regions.MRR and typical H3K27me3 peaks were first randomly shuffled to another position on the same chromosome for 1000 times. After that, the resulting genomic regions of the 1000 times shuffling were overlapped with ReSEGenes were classified based on the states of their overlapping peaks in different cell lines: [state in the first cell line] vs. [state in the second cell line], where the state can be super-enhancer (SE), H3K27me3-rich region (MRR), typical enhancer (H3K27ac), typical H3K27me3 peak (H3K27me3), or no overlapping peaks (Others). The expression data is from Epigenetic RoadMap68 and in-house HAP1 WT RNA-seq.Hi-C anchors are classified by whether they overlap with H3K27me3 or H3K27ac peaks. A (active) overlap with only H3K27ac peaks; R (repressive), overlap with only H3K27me3 peaks; Q (quiescent), overlap with neither H3K27ac nor H3K27me3 peaks; B (both), overlap with both H3K27ac and H3K27me3 peaks. The height of Hi–C interactions (arcs) represents the highest read counts in the interacting regions.73 with option “TruSeq3-PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36” and retained only those properly-paired reads after trimming. RNA-seq reads were analyzed with kallisto (0.44.0)74 with option “-b 100”. Differentially expressed genes were called using sleuth (0.29.0)75 with gene-level aggregation and wald test. ChIP-seq reads of H3K2me3 and H3K27ac were mapped by BOWTIE2 (v2.2.5)76 using default parameters in pair-end mode and filter out alignment with a mapq score smaller than 30. The two replicates were combined and peaks and bigWig files were generated by MACS2 (2.1.0.20150731)65 using option “-q 0.01” for H3K27ac and H3K4me3 and “–broad –broad-cutoff 0.1 -q 0.05” "for H3K27me3. 4C reads were trimmed off HindIII digestion site using tagdust (2.33)77 and only those remained paired were mapped by BOWTIE2 (v2.2.5)76 with option “–end-to-end” in single-end mode. R3Cseq (1.24.0)78 was used to call significant interactions against Hind III digested genome background with a cut-off p value of 0.05. Two replicates were performed for each 4C analysis, and significant interactions from the two replicates were pooled.For reads of RNA-seq and ChIP-seq, adaptors are trimmed off by trimmomatic (0.38)Genes were first associated with Hi–C interactions. Proximal/distal/internal labels were assigned according to the positional relationship between the gene and MRRs as described in Fig. 79 from Bioconductor. The heights of Hi-C and 4C were the largest read counts at Hi-C interacting regions and RPM at 4C interacting regions, respectively. The colors of Hi-C and 4C interactions were decided by the state on the distal interacting regions relative to gene TSS or 4C baits, respectively. Blue: repressive; orange: active; green: both; gray: quiescent. Tracks of ChIP-seq signal and peaks were generated by Gviz (1.22.3)80 from Bioconductor.Hi-C and 4C interactions were drawn in arc style using Sushi (1.16.0)81. Gene ontology, pathway enrichment analysis (REACTOME & KEGG) and map-view representation of enriched pathways were performed using R package clusterProfiler (3.10.1)82 and ReactomeRA (1.26.0)83.Genomic feature enrichment analysis was performed using R package annotatr (1.8.0)84, CCLE 85. Gene expressions in each cell line were compared with 69 facets of annotated CAGE clusters with normalized expression data from FANTOM586. The grouping facets were obtained from Andersson et al.87. The average expression of all samples in a facet was assigned to that facet. For each cell line, gene expression was considered as 1 facet and combined with the other 69 facets from FANTOM5 to form 70 facets in total. Gene expression specificity was calculated on these 70 facets for each cell line independently. The specificity of each gene X is calculated by: Specificity(X) = 1 − (entropy(X)/log2(N)) where X is the vector of expression values of the cluster in across all facets, and N = | × | . The definition of specificity is identical to that used by Andersson et al.87. Quartile Q1 and Q3 are used as cut-off of “Low specificity” and “High specificity”, respectively.Cell line expression data were obtained from Epigenetic RoadMap ENCFF738TKN”), RAD21 (“ENCFF002CXU”), SMC3 (“ENCFF041YQC”), REST (“ENCFF895QLA”), ZNF143 (“ENCFF114IWY”), EZH2 (“ENCFF083IDB”), GATAD2B (“ENCFF549KOD”), and YY1 (“ENCFF557DSM”) from K562 were downloaded from ENCODE. Interacting regions of MRRs were generated by overlapping MRRs with Hi-C loops. The number of overlapping ChIP-seq peaks was calculated by overlapping interacting regions with different TF. These numbers were then standardized into Z score across all interacting regions and subjected to heatmap clustering using pheatmap (1.0.12) (https://CRAN.R-project.org/package=pheatmap)88.ChIP-seq peaks of CTCF . After that, 4C interactions were classified into gained, lost, or unchanged. Gained, 4C interactions present in the experimental condition but not in the control condition; lost, 4C interaction present in the control condition but not in the experimental condition; unchanged, 4C interactions present in both control and experimental conditions. The proportions of unchanged 4C interactions in different distance categories were calculated as unchanged 4C interactions divided by the total number of 4C interactions in that distance category. Categories with fewer than 3 4C interactions were excluded in this analysis.All the 4C interactions that passed the threshold of FGF18-MRR1-A1 KO or IGF2-MRR2-A1 KO clones, while the control condition is the EV clones. Gained, 4C interactions only present in the experiment condition but not in the control condition; Lost, 4C interactions only present in the control condition but not in experiment condition; unchanged, 4C interactions present in both control and experiment conditions. In this comparison, only those 4C interactions with p value < 0.05 are considered.4C regions are classified as gained, lost, and unchanged according to their presence in experiment versus control condition. For GSK343-treated K562 4C data, the experiment condition is GSK343-treated K562, while the control condition is DMSO-treated K562. Similarly, for CRISPR KO K562 4C data, the experiment condition is either For RPM signal heatmap, different types of 4C regions (gained/lost/unchanged) are first classified according to their H3K27ac/H3K27me3 ChIP-seq signal levels in the control condition. Tertiles are used to classify these 4C regions into high, medium, or low category. The 4C intensity in RPM of each 4C regions are shown in a color-scaled manner.89 is used to calculated ChIP-seq signal at these 4C regions, and then the total signal areas are calculated as: Total Signal Area = sum (Sig *BS), where BS is the size of bins used when summarizing RPKM, and Sig is the ChIP-seq signal in RPKM at individual bin. For ChIP-seq signal boxplot, the same 4C region (gained/lost/unchanged) in different conditions are connected using gray line. Wilcoxon paired test are used, and p value are indicated accordingly: ns, p > 0.05, *p < = 0.05, **p < = 0.01, ***p < = 0.001, ****p < = 0.0001.For the ChIP-seq signal heatmap, ChIP-seq signal different types of 4C regions (gained/lost/unchanged) are calculated as the area of signal at these regions. Deeptools computeMatrixGSE133183” accession code.ChIP-seq, 4C-seq, and RNA-seq sequencing data generated in this study have been deposited in GEO with the “Further information on research design is available in the Supplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Reporting Summary


Drosophila ND models such as Parkinson’s Disease (PD), Huntington’s Disease (HD) and Amyotrophic Lateral Sclerosis (ALS). Repressed neuroplasticity genes show reduced enrichment of Tip60 and epigentic acetylation signatures at all gene loci examined with certain genes showing inappropriate HDAC2 repressor enrichment. Functional neuronal consequences for these disease conditions are reminiscent of human pathology and include locomotion, synapse morphology, and short-term memory deficits. Increasing Tip60 HAT levels specifically in the mushroom body learning and memory center in the Drosophila brain protects against locomotion and short-term memory function deficits in multiple NDs. Together, our results support a model by which Tip60 protects against neurological impairments in different NDs via similar modes of action.Epigenetic dysregulation is a common mechanism shared by molecularly and clinically heterogenous neurodegenerative diseases (NDs). Histone acetylation homeostasis, maintained by the antagonistic activity of histone acetyltransferases (HATs) and histone deacetylases (HDACs), is necessary for appropriate gene expression and neuronal function. Disruption of neural acetylation homeostasis has been implicated in multiple types of NDs including Alzheimer’s disease (AD), yet mechanisms underlying alterations remain unclear. We show that like AD, disruption of Tip60 HAT/HDAC2 balance with concomitant epigenetic repression of common Tip60 target neuroplasticity genes occurs early in multiple types of  Despite exhibiting a wide range of molecular and phenotypic heterogeneity, NDs share some general characteristics, such as protein misfolding and aggregation, mitochondrial dysfunction, dysregulation of similar molecular/cellular pathways and loss of chromatin dynamics4. Together, these similarities support convergence of heterogeneous NDs, and better insight into these common links will help target multiple NDs with potential unifying therapeutics4.Neurodegenerative diseases (NDs) are a heterogeneous group of disorders marked by progressive loss of neuronal cells in the brain and/or the spinal cord. Some common NDs include Alzheimer’s Disease (AD), Huntington’s. Depending on the specific subset of neurons and/or the area of nervous system severely affected, NDs vary with respect to the molecular pathways underlying the disease and the subsequent clinical manifestations6. Acetylation homeostasis in the brain is maintained by the antagonistic activity of histone acetyltransferases (HATs) and histone deacetylases (HDACs), and is essential for proper neuronal gene expression and concomitant neural health7. Compelling evidence demonstrates that histone acetylation dysregulation contributes to age related cognitive impairment and age associated neurodegenerative diseases, such as HD, PD, ALS and AD10. For instance, the polyglutamate repeat region in HD was shown to sequester HATs CREB-binding protein (CBP) and p300/CBP associated factor (PCAF), resulting in global reduction of H3 and H4 acetylation levels and altered gene expression11. In PD, associated α-synuclein can inhibit H3 histone acetylation by CBP, p300 and PCAF, causing apoptosis in human neuroblastoma cells12 and mitochondrial dysfunction13. In a mouse model of ALS, loss of CBP HAT activity was observed14. Additionally, impaired expression levels of class I, II and IV HDACs and Sirtuins have been observed in human postmortem ALS brain and spinal cord16. In line with these studies, we previously reported decreased levels of the HAT, Tat interactive protein 60 kDa (Tip60), and concomitant loss of Tip60 associated specific histone acetylation marks in an AD Drosophila model and in human postmortem AD brain. We further demonstrated that increasing Tip60 levels in the AD Drosophila brain protects against alteration of Tip60 HAT/HDAC2 balance, epigenetic-mediated neuroplasticity gene repression and functional cognitive deficits that occur during early stages of neurodegenerative progression17. These findings raise the possibility that Tip60 HAT/HDAC2 imbalance may be an early common event that contributes to epigenetic mediated gene misregulation and cognition deficits in other NDs as well.Over the past decade, histone acetylation mediated epigenetic mechanisms have been implicated in a variety of neural processes required for brain function that include neuronal differentiation and maintenance of activity-dependent synaptic plasticity in mature neuronsDrosophila ND models that include Parkinson’s Disease (PD), Huntington’s Disease (HD) and Amyotrophic Lateral Sclerosis (ALS). Functional neuronal consequences of each of these disease conditions are consistent with human pathology and include defects in locomotion, synapse morphology, and short-term memory deficits. Increasing Tip60 HAT levels in the mushroom body learning and memory center in the Drosophila brain protects against these neural deficits. Our findings are the first to demonstrate that disruption of Tip60 HAT/HDAC2 homeostasis and concomitant Tip60 gene control is a critical initial mechanism common to multiple neurodegenerative disorders.Here, we test the hypothesis that Tip60 mediated histone acetylation homeostasis is disrupted during early stages of neurodegeneration in multiple types of NDs. We show that disruption of Tip60 HAT/HDAC2 balance with concomitant epigenetic repression of common neuroplasticity Tip60 target genes is an early event in multiple types of 18, PD19, HD20 and ALS21. However, whether these gene expression alterations occur during early stages of disease progression remains to be elucidated. Our previous transcriptional analysis17 suggested that Tip60-mediated neuronal transcriptional dysregulation is an early event in AD progression. To test whether this is a common early event in additional types of NDs, we assessed expression of four Tip60 neuroplasticity genes using RNA isolated from the brains of three distinct and well-characterized early-stage Drosophila ND third instar larval models: the HD associated model expressing 128 poly-Q repeats in the human Huntingtin (Htt) gene (Htt(128Q))22, PD associated model expressing mutated form of human α-synuclein (SNCAA30P)23 and ALS associated model overexpressing Vap-33-1, a Drosophila homolog of VAMP-associated protein (Vap-33-1)24. These disease genes were inducibly and specifically expressed in all neurons using the pan-neuronal elav-Gal4 driver. The four synaptic plasticity genes, shaker (sh), futsch, discs large (dlg) and dishevelled (dsh), were selected because they are conserved within mammals, are bona fide direct targets of Tip60 HAT and their expression was repressed during early stages of APP mediated neurodegeneration and restored by increasing Tip60 in the brain17. We observed that futsch, a microtubule-associated protein essential in promoting synaptic bouton formation 25, and dsh, a key component of the Wnt- signaling pathway26 were repressed in the brain during early stages of all three neurodegenerative conditions  mRNA levels in HD, PD and ALS Drosophila larval brain  during early stages of APP mediated neurodegeneration. To test whether similar mechanisms underly the Tip60 neuroplasticity gene repression we observed in the brains of PD, HD and ALS Drosophila models, we carried out ChIP-qPCR using Abs to Tip60 and HDAC2 to assess their recruitment at these same genes the PD, HD, and ALS larval heads. Strikingly, and similar to AD, enrichment of Tip60 binding was significantly reduced at sh, futsch, dlg and dsh gene loci in the larval brains of all three PD, HD, and ALS fly models  gene loci or repressed heterochromatin region (hc) specificity controls. We next used ChIP to assess acetylation enrichment at four repressed synaptic plasticity gene loci  in PD, HD and ALS larval brains using Abs to well characterized Tip60-mediated cognition linked histone acetylated (Ac) marks AcH4K12 and AcH4K16. Similar to our previous findings in the fly AD model, we found reduced levels of AcH4K16 at all genes in all disease models, and reduced levels of AcH4K12 at all gene loci in all disease models except at sh. Together, these results suggest that disruption of Tip60 HAT homeostasis and concomitant epigenetic mediated neuroplasticity gene repression we previously observed in the AD brain is also an early common feature in PD, HD and ALS.We previously uncovered a mechanism underlying AD associated neuroplasticity gene repression in the brain involving inappropriate HDAC2 enrichment at specific Tip60 neuroplasticity target genes , SNCAA30P or Vap-33-1 expressed pan-neuronally with elav-Gal4 driver , we observed a significant increase in the total number of boutons per NMJ in our ALS model . Together, these results reveal that synaptic morphological defects are a central common feature during early neurodegenerative progression in the Drosophila models of PD and ALS and are consistent with the early alterations in epigenetic mediated synaptic plasticity gene expression we observe.Since the area of contact between neurons and muscles is generally proportional to the level of neurotransmissionons Fig. A and pre40. Our observation that NMJ associated synaptic morphological alterations were identified in all three NDs tested prompted us to ask whether concomitant locomotor deficits would be apparent as well. While early stage locomotor deficits in the HD fly model have been previously reported41, whether such deficits occur in PD and ALS fly models in this study were unknown. To assess whether locomotor function during early neurodegeneration is compromised, we performed a well characterized Drosophila larval line crossing assay, where the number of lines crossed in 30 s by the head of a larva placed on a grid were recorded. This assay was performed using third instar larvae expressing either Htt(128Q), SNCAA30P or Vap-33-1 under the control of mushroom body (MB)-specific 201Y-Gal4 driver. This region in the Drosophila brain is associated with a diverse set of behavioral functions, including olfactory learning, short-term memory and locomotion43. Our results showed that Htt(128Q), SNCAA30P and Vap-33-1 larvae were significantly less mobile and crossed significantly lesser grid lines when compared to control wild-type larvae  model system that enables us to modulate Tip60 HAT levels specifically in the MB, in vivo. We then performed the Drosophila line crossing locomotor assay using third instar larvae co-expressing both Htt(128Q), SNCAA30P or Vap-33-1 along with increased levels of Tip60 in the MB. We observed a significant restoration of locomotor ability in HD, PD and ALS Drosophila larvae with increased Tip60 MB levels  using published methodology 46. Larvae expressing either Htt(128Q), SNCAA30P or Vap-33-1 under the control of MB-specific 201Y-Gal4 driver were first conditioned to associate the given odor, linalool (LIN), to an appetitive gustatory reinforcer, sucrose (SUC). These larvae were exposed to LIN for 30 min on agar plate containing SUC. After conditioning, the larvae were tested for olfactory response on the test plate , SNCAA30P or Vap-33-1 with 201Y;Tip60 for co-expression of disease-associated proteins and Tip60 in the mushroom body of the progeny. Of note, olfactory and gustatory responses of all genotypes were normal when compared to control 201Y-GAL4 driver alone  are also inappropriately repressed during early stages of neurodegenerative progression in the HD, ALS and PD models examined with futsch and dsh gene repression common in all three diseases. Interestingly, we also observed that sh is reduced in Htt128 OE, but not in SNCA or Vap-33 OE models while dlg is altered in SNCA, but not in Htt128 OE or Vap-33 OE, suggesting that sh reduction may be linked to HD, whereas dlg reduction may be linked to PD. Similar to AD, each of the repressed Tip60 target neuroplasticity genes  showed reduced Tip60 binding as well as loss of acetylation at cognition linked Tip60 mediated H4K12 and H4K16 acetylation marks in comparison to healthy wild-type flies of identical developmental staging. These findings suggest that disruption of Tip60 HAT function in epigenetic gene control is a common early event in multiple NDs. Our previous studies and others52 demonstrate significant inappropriate upregulation of HDAC2 neural transcripts and recruitment to synaptic plasticity gene loci in both AD fly and mouse models, supporting an HDAC2 specific mechanism underling disease associated gene repression. Similar to AD, here we show inappropriate upregulation of neural HDAC2 transcripts in HD, PD and ALS and a significant increase in inappropriate HDAC2 enrichment at sh in both ALS and HD brains and dlg and dsh in HD larval brains. However, unlike AD, we fail to observe HDAC2 enrichment at the remainder of plasticity gene loci tested. These results suggest HDAC2 independent modes of repression for certain synaptic plasticity genes in NDs and support the need for high resolution genome-wide ChIP-Seq mapping to identify the full repertoire of potential inappropriately regulated HDAC2 gene loci common in different NDs.Epigenetic mediated transcriptional dysregulation of neuroplasticity genes in the brain is a well-characterized key step in many NDs However, many studies characterize such alterations in either aged ND animal models or post-mortem human brainsfutsch and dsh) common to HD, PD, ALS and AD play critical roles in regulating synaptic plasticity and long-term potentiation (LTP). For example, microtubule associated protein, futsch, binds to atypical protein kinase (aPKC) for regulation of long-term potentiation (LTP) and memory maintenance53. Moreover, dsh is a downstream effector of the Wnt signaling, which has been shown to facilitate LTP expression54. Consistent with these functions, and in general agreement with prior reports39, here we observed functional deficits in locomotor ability in all three ALS, PD and HD ND models examined and concomitant alterations in NMJ synaptic morphology in ALS and PD. Although no morphological defects in the NMJ were observed in our HD model, previous literature shows Htt(128Q) expression has functional consequences on synaptic transmission, such as reduction in evoked transmission and quantal size55. Further, we observed short term memory deficits in both the HD and PD models with the HD fly model also exhibiting defects in olfactory learning and the ALS fly model exhibiting a non-significant yet downward trend in STM. Thus, early alterations in Tip60 epigenetic mediated control of target neuroplasticity genes may cause the subtle synaptic defects and mild cognitive impairment (MCI) believed to represent a transitional period before full pathophysiology of these NDs appears57. Our results are in general agreement with recent findings that report early alterations in epigenetic gene control in an HD and AD61, and modest but still early transcriptome changes in ALS and PD64. We propose that epigenetic Tip60/HDAC2 imbalance occurs early in multiple NDs and triggers certain critical synaptic gene expression alterations that persist and/or initiate additional gene disruptions during later stages of the disease that negatively impact synaptic plasticity and LTP.Strikingly, the two Tip60 mediated epigenetically misregulated genes  have risen as a promising new strategy for treatment of neurodegenerative conditions that include cognitive deficits, motor impairments and other neuropathological phenotypesDrosophila media . The pan-neuronal driver elavC155, MB-specific driver 201Y, UAS-Htt(128Q), UAS-Hsap/SNCAA30P and UAS-Vap-33-1, Cyo/Sco, and TM3/TM6 were all obtained from Bloomington Drosophila Stock Center . For controls for all experiments, the respective UAS or GAL4 driver lines were used alone and yielded identical phenotypes. All experimental crosses were carried out at normal physiological temperature of 25 °C with 12 h light/dark cycle. Controls for all experiments.All fly lines were raised under standard conditions at 22 °C on standard yeasted 201Y-Gal4; UAS-Tip60 line expressing Tip60WT in the mushroom body of the brain followed standard genetic techniques. Balancers with visible phenotypes on the 2nd chromosome (Cyo/Sco) and 3rd chromosome (TM3/TM6), as well as eye phenotype associated with mini white gene in 201Y-Gal4 and UAS-Tip60 insertions were used to select for desired genotypes. Briefly, flies containing homozygous 201Y-Gal4 (201Y) on 2nd chromosome were crossed with TM3/TM6 whereas flies containing homozygous UAS-Tip60 (Tip60) on 3rd chromosome were crossed with Cyo/Sco. These crosses resulted in the F1 progeny being heterozygous for the balancer as well as 201Y or Tip60. These flies were then crossed with their balancer counterpart (i.e. TM3 with TM6 and Cyo with Sco), and F2 progeny were selected for 201Y/201Y; TM3/TM6 or CyO/Sco; Tip60/Tip60. Next, F2 progeny flies were crossed together, and flies were selected for 201Y/CyO; Tip60/TM3 in the next generation. A final self-cross was executed and flies homozygous for 201Y and Tip60  were selected for experiments. Tip60 overexpression in the larval brains was confirmed by RT-qPCR using a mixture of exogenous and endogenous Tip60 primers. Flies containing an extra ectopic copy of UAS-GFP  which is the same genetic background as the 201Y-Gal4; UAS-Tip60 used to test Tip60 rescue, showed no significant difference in line-crossing then third instar larvae expressing either Htt(128Q), SNCAA30P or Vap-33-1 under the control of mushroom body (MB)-specific 201Y-Gal4 driver alone. These results confirmed that the Tip60 mediated rescue we observed is not due to GAL4 dilution caused by the extra Tip60 construct.Generation of the double transgenic 78. UAS-Htt (128Q), UAS-Hsap/SNCAA30P and UAS-Vap-33-1 were crossed with elavC155-Gal4 for expression of the respective transgene in all neurons. elavC155-Gal4 crossed to w1118 served as wild type control. Briefly, wandering third instar larvae were dissected in calcium-free Haemolymph-like saline (HL3) saline on a sylgard dish. Fillet preparations were fixed in 4% paraformaldehyde for 30 min, followed by 2 washes in 1X PBS and one with 1 × PBS with 0.2% Triton (PBS-T). Samples were blocked with 5% goat serum for 30 min and then incubated overnight in conjugated primary antibodies at 4 °C. After 2 washes in 1X PBS-T and one wash in 1X PBS, samples were mounted on Vectashield mounting media . Slides were imaged within 24 h of mounting. Goat anti-HRP primary antibody conjugated with Alexa488 was obtained from Jackson Immunoresearch Laboratories Inc. and used at a dilution of 1:25. Rhodamine phalloidin was obtained from Molecular Probes, Invitrogen and used at a dilution of 1:40.Antibody staining and imaging was performed as previously describedwww.ncbi.nlm.nih.gov/tools/primer-blast/). Fold enrichment for all the respective genes was calculated relative to the non-specific Mouse IgG Polyclonal Antibody control.Chromatin was extracted and sheared from ~ 200third instar larval heads per experiment. To obtain larval heads, the first 1/3 of the larvae (anterior head region) was isolated. Remaining fat bodies were carefully dissected and discarded. All larval heads were inspected visually to ensure that the entire CNS was intact. Because we use a GAL4-inducible system to target gene expression exclusively in the nervous system of the larvae, this method ensures virtually no variability in gene expression in the samples used. For ChIPs, we used truChIP Chromatin Shearing Kit from Covaris following the manufacturer’s instructions. Briefly, protein–DNA cross-links were made at RT for 5 min with 1% formaldehyde and tissue was pulverized using the CryoPrep from Covaris. Cells were lysed and nuclei were prepared using Covaris lysis buffer. Sonication of DNA was performed using a Covaris E220 Ultrasonicator for 13 min. The sheared chromatin was immunoprecipitated using the EZ-Magna ChIP A Chromatin Immunoprecipitation Kit (Millipore) following the manufacturer's instructions. Briefly, ChIP was performed with 30 μg of sheared chromatin using anti-Rpd3 , anti-Tip60 , anti-H4K5ac , anti-H4K12ac , anti-H4K16ac , and Normal Mouse IgG Polyclonal Antibody control (Millipore) antibodies. The eluted material from the immunoprecipitation was then purified using a QIAquick PCR purification kit (QIAGEN) and used directly for qPCR. Primer sets were designed by NCBI/Primer-BLAST . Quantitative analysis of boutons per NMJ, area of NMJ and area of muscle was performed using ImageJ. In order to minimize variation across larval dissection preparations between samples, NMJ area was normalized to the area covered by muscles 6/7 in segment A3 for each sample.79. The line crossing apparatus consisted of a petri plate containing 1% agar positioned on a 0.2 cm2 grid paper. A single third instar larva was placed on the petri plate and allowed to acclimate to the plate for 5 min. After initial acclimation, the number of grid lines passed by the head of the larva in 30 s were recorded. This was performed a total of three times for each larva and averaged. Data from thirty larvae were collected.Larval locomotion was analyzed as previously described46. Freshly prepared 2.5% agar plates with 2 ml 1 M SUC or DW (for control) spread over the agar were used to train the third instar larvae. 10 µl of undiluted odor Linalool (LIN)  was spotted on a filter disk and placed on the lid of the petri dish  was added to 20ul reaction volume. PCR was performed using an ABI 7500 Real-Time PCR system (Applied Biosystems) following the manufacturer’s instructions. Fold change in mRNA expression was determined by the ∆∆Ct method.Total RNA was isolated from 40 staged third instar larval brains using the RNeasy Plus Mini Kit (QIAGEN). Complementary DNA (cDNA) was prepared using SuperScript II reverse transcriptase kit (Invitrogen) according to the manufacturer’s instructions with 1 µg total RNA and 0.2 µg/ml random hexamer primers (Roche Applied Science). PCRs were performed in a 20 µl reaction volume containing cDNA, 1 µM Power SYBR Green PCR Master Mix (Applied Biosystems), and 10 µM of both forward and reverse primers. Primer sequences are available in the Supplementary Table Supplementary Information.


Trachinotus ovatus (designated ToIRF1), and its immune function was identified to elucidate the transcriptional regulatory mechanism of ToIFNa3. The full-length complementary DNA (cDNA) of IRF1 is 1763 bp, including a 900-bp open reading frame (ORF) encoding a 299-amino-acid polypeptide. The putative protein sequence has 42.7–71.7% identity to fish IRF1 and possesses a representative conserved domain (a DNA-binding domain (DBD) at the N-terminus). The genomic DNA sequence of ToIRF1 consists of eight exons and seven introns. Moreover, ToIRF1 is constitutively expressed in all examined tissues, with higher levels being observed in immune-relevant tissues . Additionally, Cryptocaryon irritans challenge in vivo increases ToIRF1 expression in the skin as determined by Western blotting (WB); however, protein levels of ToIRF1 in the gill did not change significantly. The subcellular localization indicates that ToIRF1 is localized in the nucleus and cytoplasm with or without polyinosinic/polycytidylic acid (poly (I:C)) induction. Furthermore, overexpression of ToIRF1 or ToIFNa3 shows that ToIRF1 can notably activate ToIFNa3 and interferon signaling molecule expression. Promoter sequence analysis finds that several interferon stimulating response element (ISRE) binding sites are present in the promoter of ToIFNa3. Additionally, truncation, point mutation, and electrophoretic mobile shift (EMSA) assays confirmed that ToIRF1 M5 ISRE binding sites are functionally important for ToIFNa3 transcription. These results may help to illuminate the roles of teleost IRF1 in the transcriptional mechanisms of type I IFN in the immune process.Interferon (IFN) regulatory factor 1 (IRF1), a transcription factor with a novel helix–turn–helix DNA-binding domain, plays a crucial role in innate immunity by regulating the type I IFN signaling pathway. However, the regulatory mechanism through which IRF1 regulates type I IFN in fish is not yet elucidated. In the present study, IRF1 was characterized from golden pompano,  Mus musculus and Homo sapiens, while IRF10 is observed only in avian and fish species. Moreover, IRF11 can be found in lower vertebrates, such as Danio rerio [Miichthys miiuy [Epinephelus coioides [Interferon (IFN) regulatory factors (IRFs) are important transcriptional modulators of bacteria-, parasite-, virus-, and IFN-induced signaling pathways in the process of response to virus infection, immune response, cell growth, and apoptosis ,2,3,4,5.io rerio , Miichthcoioides . Furthercoioides . In the coioides ,15. Depecoioides ,17,18,19IFNɑ expression is mediated by IRF1 and IRF2 in leukemia patients [Trachinotus ovatus [Branchiostoma belcheri tsingtauense IRF1 was found to bind ISRE and recognize the promoter of human IFNα1, IFNα2, IFNα6, and IFNβ [Crassostrea gigas IRF1 could bind ISRE, regulate the expression of IFNLP as a transcriptional regulatory factor, and participate in the antiviral immune response of oysters [IRF1 are not yet characterized in detail in teleosts.According to the number of cysteine residues, IFNs are divided into two major categories. Type I IFNs contain two cysteine residues in all teleost fish lineages; nevertheless, type II IFNs include four cysteine residues in only a few species ,20,21,22patients . In lowes ovatus ,29. In iand IFNβ . Pacific oysters . ConsequT. ovatus , which is distributed in the Asia Pacific region, is considered an important aquaculture fish in South China [Cryptocaryon irritans [T. ovatus [C. irritans spans four important periods, i.e., trophont, protomont, tomont, and theront [T. ovatus. Bioinformatic analysis revealed several ISRE sites in the promoter of IFNα3 in T. ovatus, but it is unclear whether T. ovatus IFNα3 (ToIFNα3) is involved in antiparasitic diseases and how IRF1 plays its regulatory role. Therefore, to investigate the potential function of ToIFNα3 and transcriptional regulation of ToIRF1, the present study focused on describing the importance of ToIRF1 in the regulation of ToIFNα3 expression. Firstly, overexpressed ToIRF1 was used to detect the transcription of type I IFN signaling molecules. Secondly, to demonstrate whether IRF1 was the key element in the ToIFNα3 promoter, promoter activity assays employing mutations to potential IRF1 binding sites were implemented. Finally, the role of the IRF1 M5 binding site in the ToIFNα3 promoter was explored using an electrophoretic mobility shift assay (EMSA). These results may help to characterize the regulation associated with type I IFN-associated signaling in marine fish.th China ,32. Mariirritans , is a do. ovatus . The lif theront . The inf theront . To date theront . Moreove theront ,39,40,41ToIRF1  that is located in the N-terminal region and includes six typical tryptophan residues   of d Trp76) . AdditioD domain .ToIRF1 is 3220 bp, including nine exons and eight introns  to higher vertebrates  with nine exons and eight introns, except for eight exons and seven introns in both D. rerio and Astyanax mexicanus. Additionally, the phylogenetic relationship of IRF1 was determined in vertebrates .To investigate the role of  qRT-PCR B. The hiC. irritans challenge by Western blot analysis. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as an internal control for normalization. The expression pattern of ToIRF1 protein was stable throughout the infection  after nfection . Moreove at 12 h . OverallToIRF1, plasmids expressing pEGFP-ToIRF1 and pEGFP-N3 (control group) were transfected into GPS cells. Subsequently, those cells were infected with poly (I:C) before use for the immunofluorescence staining assay. The fluorescent signals of pEGFP-N3 were distributed throughout the cytosol and nucleus with or without poly (I:C) stimulation  challenge (ToIRF1 are not influenced by poly(I:C) infection, suggesting that ToIRF1 is a broadly expressed protein.To observe the subcellular localization of mulation A. Furthehallenge B. On theToIRF1 overexpression on ToIFNa3 and the interferon signaling pathway, GPS cells were transfected with pcDNA3.1-IRF1 or pcDNA3.1. Using qRT-PCR, ToIRF1 dramatically activated ToIFNa3 expression  were compounded and incubated with HEK293T cell lysates containing recombinant ToIRF1 in vitro according to the predicted ToIRF1 binding sites .To further confirm the ToIRF1 binding motif in the ng sites . Recombing sites , suggestIFNa3 by IRF1 in T. ovatus. To this end, the functional characterization, tissue expression patterns, and regulatory relationship between ToIRF1 and ToIFNa3 were determined. The ToIRF1 ORFs encoded a protein that was 42.7%–71.7% identical to IRF1 proteins from other teleosts. The highly conserved DBD was in the N-terminal region, which was structurally analogous to that of Pacific oyster, Crassostrea gigas [Salmo salar [Pseudosciaena crocea [Polyodon spathula [Cynoglossus semilaevis [Epinephelus coioides [Siniperca chuatsi [11, Trp26, Trp38, Trp46, Trp58, and Trp76) were located in the DBD, which was reported to polymerize a helix–turn–helix structure to bind DNA sequences containing 5′–GAAA–3′ tetranucleotides in specific promoters [IRF1 genes in the majority of vertebrates, the genomic sequence of ToIRF1 is also composed of nine exons and eight introns  after challenge with C. irritans [C. irritans infection, the role of ToIRF1 after stimulation with C. irritans was determined. WB results showed that similar expression levels between ToIRF1 and ToIRF2 after C. irritans stimulation in skin, but not in gill, implying that ToIRF1 might be involved in the host defense against C. irritans by mucosal immunity [. ovatus ,51. In Tand skin , while Timmunity , which simmunity ,40,46,47ToIRF1 was primarily situated in both the nucleus and cytoplasm with or without poly (I:C), showing that ToIRF1 activated the downstream signaling pathway from the cytoplasm or nucleus, where ToIRF1 was also regulated by upstream molecules. These data sustained the nuclear and cytoplasmic localization of IRF1 as responsible for its activation and function in T. ovatus, revealing that the location of IRF1 is conserved among different species [IRF1 was primarily localized to the nucleus and cytoplasm, where it retained basal transcription of a suite of antiviral genes in mammalian cells ,52. Cons species ,52.IFNa3 transcription in T. ovatus was proven by overexpression and promoter activity analysis. Moreover, the expression levels of several IFN/IRF-based signaling pathway genes were significantly increased in ToIRF1-overexpressing cells. These results were consistent with those in ToIRF2- [ToIRF5- [ToIRF8-overexpressing [In teleosts, according to differential structural and functional features, IFNs are divided into two subfamilies of IFNs, type I and type II IFNs . The typ ToIRF2- , ToIRF5-[ToIRF5- , and ToIpressing  cells. Ipressing ,45. In tpressing .ToIFNa3 promoter sequence, the analysis of truncation mutations, point mutations, and EMSAs were implemented. The region between −896 bp and +1 bp was identified as the core regulatory region in the ToIFNa3-p2 promoter, in which the underlying binding site of ToIRF1 was located. IRF1 bound ISRE/IRF-E motifs within IFN promoters with its DBD helix α3 to induce the transcription of IFN in D. rerio [C. gigas, IRF1 could act as a DNA-binding protein to recognize the core sequence GAAA in ISRE, rather than CAAA [ToIFNa3 (ToIFNa3 promoter at the binding M5 site (GAAATCCACTGAGCGGGAAAAATAT) but not mutant ISRE (CAGCAAGAATCTGCTGAATGGGAGGAATAT) in vitro, implying that ToIRF1 could only recognize DNA sequences, including 5′–GAAA–3′ [ToIFNa3 expression by binding the M5 binding sites in fish.To further elucidate the binding of ToIRF1 to the D. rerio . In C. ghan CAAA . In the [ToIFNa3 . The EMS M5 site . ToIRF1 –GAAA–3′ ,48. BrieToIRF1 were described. ToIRF1 possessed representative features of the IRF family. Furthermore, the expression of ToIRF1 was higher in immune-relevant tissues than in other tissues. The protein level of ToIRF1 was upregulated only in skin after C. irritans challenge in vivo, but not in the gill. Moreover, overexpression of ToIRF1 showed that ToIRF1 positively regulated the interferon immune response in vitro. ToIFNa3 could also positively monitor IRF1 expression in vitro. Thus, a positive feedback mechanism mediated by type I IFN-induced IRF1 activation was proposed in T. ovatus. Additionally, ToIRF1 activated ToIFNa3 expression by binding with the ISRE site on its promoter. EMSA assays further verified that ToIRF1 bound effectively to the M5 binding sites in the ToIFNa3 promoter. These findings might help to clarify the feedback regulation mechanisms of fish IRF1 and type I IFNs.In summary, the sequence, expression characteristics, and regulatory role of In the present study, all experiments were permitted by the Animal Care and Use Committee of South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences , and the trials were implemented based on the related regulations and guidelines established by this committee.C. irritans infection experiment was performed according to Zhu et al. (2020) [C. irritans at a dose of 600 theronts/fish in triplicate, and 50 fish were identified as the control group. Two parasitic tissues (skin and gill) were collected after challenge for 0 h, 6 h, 12 h, 1 d, 2 d, and 3 d from six challenged fish. Moreover, the same tissues from the control group were considered to be a negative control at each time point. To investigate the tissue expression pattern of ToIRF1, adult fish tissues (n = 3) containing heart, eye, skin, brain, fin, spleen, small intestine, gill, white muscle, kidney, liver, stomach, and male and female gonads were sampled. Before dissection, all fish were anesthetized using MS222 . All samples were instantly frozen in liquid nitrogen and then stored at −80 °C until use.Healthy juvenile fish 98.0 ± 15.0 g) and senior fish (356.0 ± 25.0 g) were acquired from Linshui Marine Fish Farm in Hainan Province, China. The fish were accommodated for two weeks and fed commercial feed  before the test and were preserved in fresh seawater at 26–30 °C with 25‰ salinity. The .0 g and 16 (0.5 μg) and RNA (1 µg) were mixed and reacted for 5 min at 70 °C. Then, the mixture was refrigerated for 2 min on ice, and M-MLV (200 units), RNasin (25 units), 5× buffer, and dNTPs (0.8 mM) were added in a total volume of 25 μL and extended for 1 h at 42 °C for reverse transcription. Moreover, the total protein was extracted using the ProteoPrep® Total Extraction Sample Kit (Sigma-Aldrich).Total RNA was extracted from different tissues and cells with TRIzol reagent  following the manufacturer’s protocol. Total RNA quality and quantity were authenticated by 1% agarose gels and a NANODROP 2000 spectrophotometer , respectively. Moreover, Oligo(dT)IRF1-derived sequences were acquired from T. ovatus genomic data [ToIRF1 sequence from gill cDNA of healthy fish, gene-specific primers were designed by Primer Premier 5 (ToIFNa3 were referenced in our previous study [IRF1 gene was obtained. This fragment was used as a core sequence to amplify the full-length cDNA of IRF1 with the Rapid Amplification of cDNA Ends (RACE) method (The mic data . Furtherremier 5 . The relus study . A 900-b) method . Accordihttp://blast.ncbi.nlm.nih.gov/Blast.cgi) was used to identify the amino acid (aa) sequences of ToIRF1. The exon and intron sequences of the IRF1 gene were determined by Ensembl (http://asia.ensembl.org/). Different aa sequences of IRF1 were aligned by ClustalW2 . Moreover, MEGA 6.0 software was used to structure a maximum likelihood (ML) phylogenetic tree  of IRF1 aa [http://tree.bio.ed.ac.uk/software/figtree/), respectively. To calculate the molecular weights (Mw) and theoretical isoelectric points (pI), Compute pI/Mw software (http://web.expasy.org/protparam/) was used.The basic local alignment search tool (BLAST) program from the national center for biotechnology information national center for biotechnology information (NCBI) database  with the BamHI and XhoI sites  snout tissue (GPS) cells were transfected with expressing plasmid ToIRF1 (pEGFP-IRF1) or empty vector (pEGFP-N3), separately [To structure the plasmid for subcellular localization, the cloning open reading frame (ORF) of oI sites  was usedparately . Twenty-ToIRF1 was inserted into the pCDNA3.1 vector  with the BamHI and XhoI sites , and the cells were harvested after 24 h. Total RNA was extracted as described above. Moreover, to further confirm the regulatory relationship between ToIRF1 and ToIFNa3, pGL3-basic-IFNa3-P1 was transfected into GPS cells together with pcDNA3.1-IRF1 or empty vector [Renilla luciferase plasmid pRL-TK  was defined as an internal control. To construct the expression plasmid, the ORF of oI sites . To survy vector ,29. At 0ToIFNa3, the transcription factor binding site prediction (TFBS)-JASPAR database (http://jaspar.genereg.net/) and TRANSFAC® and MatInspector® software were used to predict the binding sites of ToIRF1 in the promoter sequences of ToIFNa3. According to the location of the predicted binding sites of ToIRF2, five truncated mutants from the ToIFNa3 promoter were designed and preserved in our lab. The corresponding promoter cloning and plasmid construction were described in a previous study  were mutated. Based on the prediction, six assumed recombinant plasmids of mutations were constructed as in previous research [To validate the potential role of the ToIRF1 binding sites on the core research . The pGLresearch .The EMSA procedure was implemented according to a previously described procedure . BrieflyToIRF1 mRNA levels in the tissues and GPS cells were determined by quantitative real-time PCR (qRT-PCR). Total RNA was extracted from different tissues and cells as described above. The specific primers for the IFN signaling pathway genes IRF1, IFNa3, tumor necrosis factor (TNF) receptor associated factor 6 (TRAF6), interferon stimulated gene (ISG15), viperin1, viperin2, mitochondrial antiviral signaling protein (Mavs), MAX interactor 1 (MXI), and the reference gene elongation factor-1 alpha (EF-1α) are displayed in −ΔΔCT method [The relative gene ISG1, viperinT method .279–291) of ToIRF1 was compounded from Genecreate . The PCR product was inserted into the pET-B2M vector using NdeI and XhoI restriction enzyme cutting sites. To express recombinant ToIRF1 protein (rToIRF1), Escherichia coli BL21 (DE3)  was transformed with the recombinant plasmid. rToIRF1 was purified as previously described [E. coli lysate supernatants to detach inhomogeneous antibodies and was purified on a HiTrapTM Protein A HP column on an AKTAprime™ Plus system .To manufacture the polyclonal anti-IRF1 antibody, a peculiar domain  membranes  using the PierceG2 Fast Blotter . Western blotting (WB) analyses were carried out according to a previously described protocol [To verify the specificity of the rabbit anti-IRF1 antibody, HEK293T cells were transfected with pcDNA3.1-IRF1 or pcDNA3.1 for 48 h. Then, the cells were harvested by centrifugation at 160× C. irritans challenge in gill and skin was determined by WB analyses. Moreover, to detect endogenous IRF1, GPS cells were cultured in a 6-cm plate (2.5 × 106) and treated with rIFNa3 at final concentrations of 50, 100, and 200 ng/mL or PBS (as a control) for 24 h. Total protein was isolated by 12% SDS-PAGE, and the membrane was transferred as described before. Primary antibodies  and the loading control, the anti-glyceraldehyde 3-phosphate dehydrogenase antibody , 1:1000) were incubated with the PVDF membrane in 1% (w/v) non-fat milk in Tris-buffered saline and Tween-20 (TBST) buffer (0.1% Tween-20) for 3 h. Horseradish peroxidase (HRP)-conjugated goat anti-rabbit antibody (1:3000) was used as a secondary antibody  [The endogenous IRF1 protein expression response to ch, USA) . Finallyp < 0.05 and p < 0.01 were considered to be significant.All trials were performed in triplicate. SPSS 19.0 software  was used to analyze the data. All values are displayed as the mean ± SD. Significant differences were calculated by one-way ANOVA tests, and


Mat1-mediated transcriptional repressor (MMTR)/DNA methyltransferase 1 (DNMT1)-associated protein (Dmap1) is a transcription corepressor involved in chromatin remodeling, cell cycle regulation, DNA double-strand break repair, and tumor suppression. The Tip60-p400 complex proteins, including MMTR/Dmap1, interact with the oncogene Myc in embryonic stem cells (ESCs). These proteins interplay with the stem cell-related proteome networks and regulate gene expressions. However, the detailed mechanisms of their functions are unknown. Here, we show that MMTR/Dmap1, along with other Tip60-p400 complex proteins, bind the promoters of differentiation commitment genes in mouse ESCs. Hence, MMTR/Dmap1 controls gene expression alterations during differentiation. Furthermore, we propose a novel mechanism of MMTR/Dmap1 function in early stage lineage commitment of mouse ESCs by crosstalk with the polycomb group (PcG) proteins. The complex controls histone mark bivalency and transcriptional poising of commitment genes. Taken together, our comprehensive findings will help better understand the MMTR/Dmap1-mediated transcriptional regulation in ESCs and other cell types.Chromatin remodeling, including histone modification, chromatin (un)folding, and nucleosome remodeling, is a significant transcriptional regulation mechanism. By these epigenetic modifications, transcription factors and their regulators are recruited to the promoters of target genes, and thus gene expression is controlled through either transcriptional activation or repression. The  Sox2, Oct4, Klf4, and Nanog have been identified as crucial factors for gene expression control, forming a core pluripotency network in collaboration with transcriptional co-regulators [Preimplantation embryo-derived embryonic stem cells (ESCs) are able to self-renew and differentiate into multi-lineage cell types in vitro and in vivo with a normal karyotype ,2,3. Duegulators ,7,8,9. Rgulators ,11,12. Igulators . The Corgulators , the Corgulators . In factgulators ,16. HoweThe DNA methyltransferase 1-associated protein (Dmap1) was originally identified as a protein associated with DNA methyltransferase 1 (Dnmt1) and is implicated in gene regulation through chromatin modification . In addiEarlier, we characterized the MAT1-mediated transcriptional repressor (MMTR) from mouse ESCs as a novel clone and found it to be identical to Dmap1 . MMTR isIn terms of the ESC physiology, MMTR/Dmap1 is critical for pluripotency as a subunit of the Tip60-p400 complex . The hom2. We cultured the mESC lines CCE (129/sv) and J1 (129S4/SvJae) under feeder-free conditions and maintained in DMEM with 15% heat-inactivated FBS, 1X MEM Non-Essential Amino Acids Solution (Sigma Aldrich), 300 μM monothioglycerol (Sigma Aldrich), 1X penicillin/streptomycin, and 1000 U/mL LIF  in 0.1% gelatin-coated cell culture dishes at 37 °C with 5% CO2. For differentiation, a hanging drop method [The HEK (Human Embryonic Kidney) 293T-17 cells were cultured in Dulbecco’s modified Eagle’s medium  with 10% fetal bovine serum , 50 units/mL penicillin , and 50 μg/mL streptomycin (Sigma Aldrich) at 37 °C with 5% COp method  was emplWe constructed the pcDNA3 Flag-MMTR plasmid and the pEF1-3xFB-MMTR plasmid swapping the FlagBio sequences in the pEF1α-FlagBio-Dmap1 with 3xFLAG-Bio Sequences . To gene−ΔCt, based on ΔCt = ΔCt (treated) − ΔCt (untreated), with GAPDH levels as internal controls. Errors were calculated from at least two independent experiments.Total cellular RNA was extracted using Qiazol reagent  according to the manufacturer’s procedures for RT-PCR. Purified RNA was resuspended in DEPC water. Four hundred nanograms of total RNA were used for cDNA synthesis using 10 pmol random hexamer and the High Capacity cDNA Reverse Transcription Kit . We conducted RT-qPCR using SYBR green  with the specific primers . AmplifiWestern blots were performed as previously described . Protein3 at 1 × 106 cells/100 μL. Cells were washed, fixed with 10% formalin in PBS, stained with 5 mg/mL propidium iodide (Sigma Aldrich) with 10 mg/mL RNase A for 10 min, and analyzed using FACSCalibur .Cells were trypsinized, washed in 0.1% BSA in PBS, counted, and resuspended in 2% FBS/0.01% NaN6 cells) were injected with sterile 26 G needle subcutaneously into the dorsoposterior region of 7~8 week old mice. Teratomas were obtained at 4 weeks post-injection. All animal procedures were approved by the Animal Care and Use Committee and the Institutional Review Board of Hanyang UniversityImmunodeficient SCID mice (ICN nude) were used for the teratoma assay. Cells from each mESCs line were mechanically detached from the surface. Obtained cell aggregates  in over 50% samples were filtered out. Selected gene signal value was transformed by logarithm and normalized by quantile method. Raw Microarray data were analyzed at October, 2013 and uplosded at February, 2020 through the Gene Expression Omnibus under accession no. GSE145561 [Total RNA was extracted using Trizol (Invitrogen) and purified using RNeasy columns (Qiagen) according to the manufacturer’s protocol. After DNase digestion and clean-up procedures, RNA samples were quantified, aliquoted, and stored at −80 °C. For quality control, RNA purity and integrity were analyzed on Agilent 2100 Bioanalyzer (Agilent Technologies). Total RNA was amplified and purified using the Ambion Illumina RNA amplification kit  to yield biotinylated cRNA according to the manufacturer’s instructions. Seven hundred and fifty nanograms of labeled cRNA samples were hybridized to each Mouse WG-6 expression v.2 bead array for 16–18 h at 58 °C, according to the manufacturer’s instructions . Array signal was detected using Amersham fluorolink streptavidin-Cy3 (Invitrogen) following the bead array manual. The quality of hybridization and overall ChIP were monitored by visual inspection of both internal quality control checks and the raw data. Raw data were obtained using the software, Illumina GenomeStudio v2011.1 (Gene Expression Module v1.9.0). Array probes with detection SE145561 . Data pohttps://usegalaxy.org/), and the resulting files were mapped with mouse reference genome mm9 using the Bowtie2  utility. Peak calling was performed by MACS , and each binding peak’s gene was annotated by the BETA-minus tool in Galaxy cistrome (http://cistrome.org/ap/root#) using the <20 kb of each peak and <100 kb of TSS option. Binding regions were called by CEAS  in Galaxy cistrome. Common factor binding regions were analyzed by intersect tools . Heatmap analyses were performed using the R-bioconductors package in Galaxy cistrome version 1.0.0. De novo DNA binding motif search was performed using MDscan algorithm, and similar DNA binding motif identification was performed using cistrome motif database in Galaxy cistrome SeqPos motif tool [We used the following Public ChIP-data sources (GEO Datasets): DNA methylation , Dmap1 (GSM1183112), Tip60 (GSM1183114), p400 (GSM1269901), Max (GSM1183115), Myc (GSM1183111), Suz12 (GSM1041374), Cbx7 (GSM1041373), Ring1B (GSM1041372), Ezh2 (GSM590132), H3K4me3 (GSM769008), H3K27ac (GSM1000099), H3K27me3 (GSM1000089), and H2A.Z (GSM849928). Each fastq file was converted into fastqsanger format using the Fastqgroomer utility , the wig format was converted to the bigwig format. The stemness and differentiation-related enrichment was analyzed using the GSEA2 utility (http://software.broadinstitute.org/gsea/index.jsp) (v.2.2.0) with the 2015 July database. Data are presented as the mean +/− standard error. The sample size for each experiment, n, is included in the results section  less than 0.05. Statistical analyses were performed using IBM SPSS statistics 23.Enrichment term analyses for the microarray and ChIP-seq data were performed using the Clue GO program (v. 2.1.7) and Cytoscape 3.0 (v.3.2.1). To identify the binding position of the target peak in the UCSC genome browser ( section  and the We established MMTR knockdown (MMTR KD) or MMTR/Dmap1 full-length overexpressed (MMTR-F) mESCs to test whether MMTR/Dmap1 is crucial for the maintenance and/or differentiation of mESCs. Morphologies of the established cell lines were not significantly different from each other A. MeanwhTo test the functional roles of MMTR/Dmap1 domains, N- and C-terminal mutants  were constructed and overexpressed in mESCs A,B. MMTR2 Fc| ≥ 0.5). The significantly changed genes comprised 1084 upregulated genes (4.02%) and 1020 downregulated genes (3.78%)  . Prefere (3.78%) , and we  (3.78%) . When we (3.78%) . It was Pou5f1, Nanog, Sox2, and Klf4) and trophectoderm  markers to verify whether these genes influence the lineage commitment during mESCs differentiation. Although MMTR/Dmap1 binds to the regulatory region(s) of both pluripotency and trophectoderm markers, significant expression changes appeared only in the pluripotency markers during commitment of differentiation  genes in the microarray were binding targets of MMTR/Dmap1 by public ChIP-Seq data  analyses A. Interentiation . These fMMTR/Dmap1 was initially identified to bind to Dnmt1 for DNA methylation ,43. The Importantly, 15,157 raw peaks in the MMTR/Dmap1 ChIP-seq data met the peak-calling algorithm. These peaks were strikingly enriched around the transcriptional start site (TSS), such that approximately 40% of the promoter regions (between ± 3 kb) of target genes were occupied by MMTR/Dmap1, although 5’ UTR, intron, exon, and distal intergenic regions of targets showed MMTR/Dmap1 preference . Based oThe Tip60-p400 complex activates gene expression through its histone acetyltransferase and ATP-dependent H2AZ-H2B dimer exchange activities ,44. We aInterestingly, the H3K27me3 modification strength was different between up- and downregulated genes during the mESC differentiation, such that 33.9% and 26.0% of the upregulated genes showed high or moderate H3K27me3 modification, respectively, whereas only 9.8% and 18.2% of the downregulated genes showed high or moderate H3K27me3 modification, respectively C. In botTo further explore the relationship between the MMTR/Dmap1 and PRC complexes for gene regulation, we conducted Gene Set Enrichment Analysis 2 (GSEA2)  on gene Some of the MMTR1/Dmap1 target genes are also regulated by Suz12 KO mESCs E, and thTo verify our hypothesis that interplay between the Tip60-p400 and PRC complexes regulates the MMTR/Dmap1 targets, we tested the correlation of the expression level with the MMTR/Dmap1 and Suz12 binding status in the promoters of selected commitment genes during differentiation of MMTR OE/KD mESCs . In geneKlf4 and developmental Tead2 promoters  and the modified histones (H2AZ and H3.3) B. Histonromoters B. Therefromoters  and the romoters  but not The Myc targets are involved predominantly in cellular metabolism, cell cycle, and protein synthesis pathways, whereas the targets of core factors are more related to the development and transcription . The corThe active stemness genes in ESCs must shut off during early differentiation commitment, while the lineage commitment genes must concurrently turn on. A previous study indicated that PcG proteins induce the ESCs to acquire and maintain specific development gene expression programs by forming a poised bivalent chromatin structure of the target gene promoters . In thisIn contrast to moderate or weak association between the PcG proteins and the Tip60-p400 complex in MMTR/Dmap1 downregulated genes, rapid transcription repression can be achieved by the strong association between PRCs and the Tip60-p400 complex. This leads to a transiently poised bivalent chromatin state. Likewise, dissociation of PRCs from the chromatin through an unknown mechanism releases genes from the transcriptional pausing. In ESCs, most bivalent promoters are thought to harbor a paused RNA pol II enzyme, although there is no evidence of this . In mostMMTR/Dmap1 functions as a somatic Dnmt1- or HDAC2-mediated transcription repressor . HomozygAlthough the precise molecular mechanisms of PcG-mediated repression are still unknown, they might comprise two scenarios: (i) direct inhibition of the transcriptional machinery, PRC1-mediated ubiquitylation of lysine 119 of histone H2A, or (ii) chromatin compaction . RecentlGFAP  and is required for its transcriptional suppression [GFAP promoter before the onset of astroglial differentiation [The context-dependent and transient repression exerted by PcG proteins implies a dynamic control of PRC function during differentiation, possibly through the cooperation with auxiliary proteins such as sequence-specific transcription factors or enzymes modifying PRC core components. Chromodomain helicase DNA binding protein 4 (Chd4) in the Nucleosome Remodeling Deacetylase (NuRD) complex is essential for the localization of Ezh2 at the promoter of the key astrogenic marker gene pression . PcG propression . DNA metntiation . It implntiation . NuRD hantiation . Importantiation . Furtherntiation  recentlyPromoters and enhancers control the temporal and spatial gene expressions, and approximately 70% of the most common promoters in the vertebrate genome are associated with the CpG islands (CGIs) ,80. AbouMeanwhile, it is well known that the self-renewal mechanism of hESCs differs from that of the mESCs, although both of them are established from the inner cell mass of mouse or human preimplantation embryos. For example, hESCs respond to signaling between the NODAL/ACTIVIN-A-activated fibroblast growth factor (FGF) and transforming growth factor-beta (TGF-β) signaling pathway to sustain prolonged self-renewal, but different growth factors, leukemia inhibitory factor (LIF), and bone morphogenic protein 4 (BMP4) are required for mESCs . To checHere, we identified a novel mechanism of MMTR/Dmap1 in terms of bivalent regulations in maintenance and differentiation of mESCs. The Tip60-p400 complex, including MMTR/Dmap1, binds to almost all preferential genes for the maintenance of pluripotency. MMTR/Dmap1 regulates bivalent genes through intimate interaction with PRC complexes in mESCs . In norm